Handbook of protocols for standardized measurement ...

Supporting Information

Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits Marco Moretti, André T.C. Dias, Francesco de Bello, Florian Altermatt, Steven L. Chown, Francisco M. Azcárate, James R. Bell, Bertrand Fournier, Michael Hedde, Joaquín Hortal, Sébastien Ibanez, Erik Öckinger, José Paulo Sousa, Jacintha Ellers and Matty P. Berg

Trait protocols 1. STANDARDISATION PROTOCOL ..................................................................................................

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2. MORPHOLOGY ................................................................................................................................... 4 2.1. Body size ...................................................................................................................................... 4 2.2. Eye morphology ........................................................................................................................... 7 2.3. Respiration system ....................................................................................................................... 9 2.4. Hairiness ....................................................................................................................................... 10 2.5. Colour ......................................................................................................................................... 12 3. FEEDING ............................................................................................................................................... 3.1. Feeding guild ................................................................................................................................ 3.2. Ingestion rate ................................................................................................................................ 3.3. Biting force ..................................................................................................................................

15 15 16 21

4. LIFE HISTORY .................................................................................................................................... 4.1. Ontogeny ...................................................................................................................................... 4.2. Clutch size .................................................................................................................................... 4.3. Egg size ........................................................................................................................................ 4.4. Life span ....................................................................................................................................... 4.5. Age at maturity ............................................................................................................................. 4.6. Parity ............................................................................................................................................ 4.7. Reproduction mode ...................................................................................................................... 4.8. Voltinism ......................................................................................................................................

24 24 26 27 29 31 32 33 35

5. PHYSIOLOGY ...................................................................................................................................... 5.1. Standard metabolic rate ................................................................................................................ 5.2. Relative growth rate ..................................................................................................................... 5.3. Desiccation resistance .................................................................................................................. 5.4. Inundation resistance .................................................................................................................... 5.5. Salinity resistance ......................................................................................................................... 5.6. Temperature tolerance .................................................................................................................. 5.7. pH resistance ................................................................................................................................

37 37 39 40 42 44 46 48

6. BEHAVIOUR ........................................................................................................................................ 6.1. Activity time ................................................................................................................................ 6.2. Aggregation .................................................................................................................................. 6.3. Dispersal mode ............................................................................................................................. 6.4. Locomotion speed ........................................................................................................................ 6.5. Sociality ....................................................................................................................................... 6.6. Annual activity rhythm ................................................................................................................

51 51 53 56 57 59 61

_________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776

2 Supporting Information for Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits, Moretti et al. (2016), Functional Ecology.

1. STANDARDISATION PROTOCOL This standardisation protocol lists the additional information that should be published together with values of trait measurements and describes recommendations for pre-treating and acclimating animals to obtain comparable values within and among species for all taxonomic groups. Animal and site description For the traits selected for this handbook it is essential that some site details where the animals were sampled are given together with values on trait measurements. When collecting animals from the field we recommend that latitude, longitude and elevation are published, as well as average minimum, mean and maximum temperature and annual precipitation of the site where the animals have been sampled. The latter data are often difficult to come by, but information on macroclimates and microclimates can be obtained from Hijmans et al. (2005) and from Kearney et al. (2014), respectively. Trait values often change during ontogeny and may differ between sexes. Prior to trait measurement, the developmental stage and, if possible, sex of the individual should therefore be described. Similarly, in insects with polymorphic castes also the caste should be determined. It is essential that this information is reported along with values of trait measurements indicated in the individual trait protocols. Acclimation Some trait values may depend on the immediate conditions an organism is subjected to at the place or time of collection. In these cases, to achieve standardized trait measurements it is necessary to provide the same conditions for all individuals measured. Before measurements, individuals should be acclimatized for a period of time to minimize effects of prior environmental conditions. For comparability of trait measurements across species, we recommend standard conditions of 20 °C for at least one week for most physiological and behavioural trait measurements in most species. Although this temperature may seem a curious choice given substantial global variation in mean temperatures, we suggest that it may be useful for many areas especially for organisms that are typically active in or have juvenile stages in the spring or summer months. We do so because globally, maximum temperatures and temperatures of the warmer months vary less than do mean temperatures and minima (see Addo-Bediako, Chown & Gaston 2000; Clarke & Gaston 2006; Buckley & Huey 2016). Nonetheless, for some environments acclimation to 20 °C may be unsuitable. In this case, reporting of the acclimation treatment (temperature and duration) are adequate, along with the light:dark (L:D) cycle employed. In some cases, such as investigations of cold tolerance, substantially different conditions will be appropriate. Again, clear reporting of treatments is the best approach (Loeschcke & Sǿrensen 2005). We recommend a static temperature rather than fluctuating temperatures to be used for the acclimation treatment. Although much recent emphasis has been placed on the extent to which fluctuating temperatures may alter traits (e.g. Paaijmans et al. 2013; Colinet et al. 2015; Dowd, King & Denny 2015; Chown & Gaston 2016; Woods, Dillon & Pincebourde 2016) and the form of responses (Angilletta et al. 2006; Colinet et al. 2015; Wu, Shiao & Okuyama 2015; Chown, Haupt & Sinclair 2016), they add substantial complexity to standardisation of trait protocols. A key reason for this complexity is the many additional variables that need to be considered: mean temperature, amplitude of fluctuations, frequency of fluctuations, the predictability of the fluctuations and the duration of the subsequent experiment (see discussion in Chown & Terblanche 2007; Colinet et al. 2015; Dowd, King & Denny 2015; Kingsolver, Higgins & Augustine 2015). These are clearly not matters for which a ready solution, in a standard trait protocol approach, is yet available – they require further deliberation. Our recommendation here is that for broad-scale comparisons, the mean temperature of the environment in which each sampled population occurs should be used, either following measurement (see Dowd, King & Denny 2015) or by estimation from global databases (macroclimate data and microclimate information can be obtained for _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


long periods, frequently at hourly intervals). Reporting exactly what was done is of most significance, and here, detailed descriptions either in the main work or as supplementary material would be especially important. The length of the acclimatization period will depend on the species and trait in focus, and therefore may need to be adapted on the species-specific life cycle, physiology and learning behaviour. Animals should be provided with ad libitum food and water. Usually this means that food and water are replaced frequently enough to ensure that the animal never experiences food shortage or a reduction in food quality and has the maximum possible body water content. If the biology of the species requires, one can deviate from these standard conditions. In any case, it is essential to report the exact acclimation conditions, such as temperature, length of acclimation, relative humidity (RH), light:dark (L:D), etc., together with measurements of trait values. References Addo-Bediako, A., Chown, S.L. & Gaston, K.J. (2000) Thermal tolerance, climatic variability and latitude. Proceedings of the Royal Society B, 267, 739-745. Angilletta, M.J., Bennett, A.F., Guderley, H., Navas, C.A., Seebacher, F. & Wilson, R.S. (2006) Coadaptation: a unifying principle in evolutionary thermal biology. Physiological and Biochemical Zoology, 79, 282-294. Buckley, L.B. & Huey, R.B. (2016) How extreme temperatures impact organisms and the evolution of their thermal tolerance. Integrative and Comparative Biology, 56, 98-109. Chown, S.L. & Gaston, K.J. (2016) Macrophysiology – progress and prospects. Functional Ecology, 30, 330344. Chown, S.L., Haupt, T.M. & Sinclair, B.J. (2016) Similar metabolic rate-temperature relationships after acclimation at constant and fluctuating temperatures in caterpillars of a sub-Antarctic moth. Journal of Insect Physiology, 85, 10-16. Chown, S.L. & Terblanche, J.S. (2007) Physiological diversity in insects: ecological and evolutionary contexts. Advances in Insect Physiology, 33, 50-152. Clarke, A. & Gaston, K.J. (2006) Climate, energy and diversity. Proceedings of the Royal Society B, 273, 22572266. Colinet, H., Sinclair, B.J., Vernon, P. & Renault, D. (2015) Insects in fluctuating thermal environments. Annual Review of Entomology, 60, 123-140. Dowd, W.W., King, F.A. & Denny, M.W. (2015) Thermal variation, thermal extremes and the physiological performance of individuals. Journal of Experimental Biology, 218, 1956-1967. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978. Kearney, M.R., Isaac, A.P. & Porter, W.P. (2014) microclim: Global estimates of hourly microclimate based on long-term monthly climate averages. Scientific Data, 1, 140006. Kingsolver, J.G., Higgins, J.K., & Augustine, K.E. (2015) Fluctuating temperatures and ectotherm growth: distinguishing non-linear and time dependent effects. Journal of Experimental Biology, 218, 2218-2225. Loeschcke, V. & Sǿrensen, J.G. (2005) Acclimation, heat shock and hardening - a response from evolutionary biology. Journal of Thermal Biology, 30, 255-257. Paaijmans, K.P., Heinig, R.L., Seliga, R.A., Blanford, J.I., Blanford, S., Murdock, C.C. et al. (2013) Temperature variation makes ectotherms more sensitive to climate change. Global Change Biology, 19, 2373-2380. Woods, H.A., Dillon, M.E. & Pincebourde, S. (2015) The roles of microclimatic diversity and of behavior in mediating the responses of ectotherms to climate change. Journal of Thermal Biology, 54, 86-97. Wu, T.H., Shiao, S.-F. & Okuyama, T. (2015) Development of insects under fluctuating temperature: a review and case study. Journal of Applied Entomology, 139, 592-599.



2. MORPHOLOGY 2.1. BODY SIZE Definition and relevance Body size is a physical measurement of the body and can be expressed by length, mass or volume of an animal. Body size is a general predictor of physiological processes, such as ingestion, respiration and growth (Peters 1983). Body size scales with many life history traits, such as age at maturity, reproductive output and longevity (Honĕk 1993; Sokolovska; Rowe & Johansson 2000; Ellers & Jervis 2003), as well as resistance to stressors (Dias et al. 2013) and movement (Greenleaf et al. 2007). Body size determines the structure and function of ecological networks (Woodward et al. 2005) and underlies many macroecological patterns, such as sizeabundance relationships and size-diversity relationships (Blackburn & Gaston 1994; Ritchie & Olff 1999) and invertebrate-host plant type (Bell et al. 2012). Body size, especially mass, is also fundamental to several ecosystem processes, such as pollination (Benjamin, Reilly & Winfree 2014), decomposition (Bradford et al. 2002) and nutrient flow through soils (Berg et al. 2001). Moreover, body size has evolutionary implications, as it controls the overall rate of molecular evolution (Martin & Palumbi 1993; Gillooly et al. 2005). What and how to measure There are three approaches to measure body size: actual size, mass or volume measurements, of living or preserved specimens. What to measure is determined by the research question and model organisms. For animals with a particularly flexible body, such as earthworms, some Diptera larvae and Collembola, mass measurements are often more reliable than length measurements. For groups with shells, exoskeletons or large external appendages/structures attached to the body it may be necessary to measure both the soft body and the shell or external structure. Moreover, accurate mass measurements can be very laborious if many specimens have to be measured or when animals have to be kept alive or are subject to chemical preservation that can cause unpredictable mass changes. In most cases, body volume is a non-destructive tool in mass determination (Smit et al. 1993; Berg 2000). In this method body shape is transferred into volume parameters, often followed by the conversion of volume parameters into a mass parameter. Body volume measurements are also particularly useful in animals with variable body length and width due to significant body flexibility, such as in earthworms, enchytraeids and some fly larvae (Abrahamsen 1973; Smit et al. 1993). There are two approaches to measure body volume: actual volume measurements of alive or preserved specimens (especially suitable for large invertebrates), and measuring body length and diameter followed by calculating body volume (especially suitable for small invertebrates). We recommend actual volume measurements when feasible, and to rely only on body volume calculation when necessary (see special cases). Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. Body size can be measured on live animals or on dead and preserved animals. In dead animals, body size depends on the way the animal is preserved. For instance, preservation in ethanol might result in body shrinkage or a decrease in mass due to solubilisation of compounds (den Nijs et al. 1996). As there is no consensus which preservation method to use, we recommend storing animals individually at -20 °C in air tight containers not much bigger than the animal to prevent water loss by sublimation. Prior to body size measurements the animals should be defrosted. It is essential to report the chosen preservation method together with measurements of body size. How to measure body length? Individuals should be placed individually on an inert surface at room temperature. Make sure that the ventral side of the body is flat and fully touches the inert surface over the whole length of the body (not curled up). The _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


length should be measured from the top of the head to the tip of the abdomen. For segmented animals, we recommend to measure the respective length of the segments (e.g. head, thorax and abdomen) and add them. Body appendages, such as legs, cerci, ovipositors, antenna, rostrum and alike should be excluded from the measurement. To enable precise length measurements of tiny individuals a microscope is needed. Individuals should be magnified to the level that they fill >1/2 of the width of the microscope image. It is essential to report the level of magnification. In cases where body length is difficult to obtain, for instance in badly damaged organisms, or is affected by chemical preservation methods, head capsule width (Johnston & Cunjak 1999) or pronotum width (Laparie et al. 2010) have been used as substitutes for length as their dimensions are less affected by chemical preservation methods than body length (Britt 1953, Johnston & Cunjak 1999). How to measure body dry mass? Prior to dry weight measurements, animals should be placed individually in a small container and dried. We recommend freeze-drying or using an oven to dry animals to prevent tissue decomposition by microorganisms, loss of volatile organic matter, and to allow additional measurements on proteins and related compounds, which are denaturated at high temperatures. After adjustment to room temperature in a desiccator, the animals can be weighted individually in a microbalance at room temperature. If animals are dried in an oven it is essential to report the drying temperature. We advise to correct body dry mass for ash content when different taxa are studied simultaneously, as taxa can differ substantially in the amount of structural body components (Pokarzhevskii et al. 2003). If measurements of fresh weight are needed animals should be allowed to clear their gut. Surface-clinging water or preservatives should be removed from the animals by laying them on a tissue for a few seconds. In tiny, softbodied animals desiccation is a source of error in fresh weight determination. Individual fresh weight measurements may be obtained by placing the animals into a small, pre-weighted and nonhygroscopic droplet of silica fluid (Lundkvist 1978). How to measure body volume? Body volume can be measured as the fluid displacement after an organism is immerged in a fluid-filled container (Douglass & Wcislo 2010), and is based on the principle that an object immersed in a fluid displaces an equivalent volume. Prior to measuring body volume, surface-clinging water or preservatives should be removed from the organisms by laying them on a tissue for a few seconds or minutes, depending on their size. Individuals should be placed individually in a volumeter, such as a graduated cylinder, partly filled with fluid. To enable precise fluid displacement measurements, the internal width of the volumeter should be slightly larger than the width of the organism. It is essential to report the volume and width of the volumeter together with the body volume measurements. Additional notes When actual body size measurements are not feasible or give errors due to total body flexibility or chemical preservation, indirect estimates of body size can be obtained using allometric linear regressions of pronotum width-body length (Weiser & Kaspari 2006) or body length-mass (Sample et al. 1993; Cabellero et al. 2004) or volume-mass (Smit et al. 1993; Berg 2000). Allometric regression models should ideally be based on refrigerated animals (at -20 °C as preferred). We recommend estimating regression coefficients for individual species if feasible, due to species-specificity in body size and allometric relationships within and between families (Johnston & Cunjak 1999; Caballero et al. 2004) or between ecosystems (Sabo, Bastow & Power 2002). It is essential to report both the date and the geographical location of the study together with model parameters as allometric functions are sensitive to spatio-temporal variation in body size metrics (Johnston & Cunjak 1999).



Body volume can also be estimated by treating the organism as a cylinder and measuring body length and diameter simultaneously. In animals with a significant flexible body, length and width are related to each other as contraction results in shorter but broader bodies compared to relaxed bodies that are longer and thinner. To calculate body volume (Vc) the following equation can be used: Vc = (π/4) LD2 where L is body length (in mm) and D is the mean body diameter (in mm) (Smit, Dudok van Heel & Wiersma 1993). We recommend to measure body diameter once if individuals are less than 10 times as long as wide, and twice or three times along the body if animals are between 10 to20 times or more than 20 times as long as wide, respectively, or have an oval body shape, to obtain trustable diameter measures. Length and diameter can be measured following the same recommendation described for length and width above. References Abrahamsen, G. (1973) Studies on body-volume, body-surface area, density and live weight of Enchytraeidae (Oligochaeta). Pedobiologia, 13, 6-15. Bell, J.R., Taylor, M.S., Shortall, C.R., Welham, S.J. & Harrington, R. (2012) The trait ecology and host plants of aphids and their distribution and abundance over the United Kingdom. Global Ecology & Biogeography, 21, 405-415 Benjamin, F.E., Reilly, J.R. & Winfree R. (2014) Pollinator body size mediates the scale at which land use drives crop pollination services. Journal of Applied Ecology, 51, 440-449. Berg, M.P. (2000) Mass-length and mass-volume relationships of larvae of Bradysia paupera (Diptera: Sciaridae) in laboratory cultures. European Journal Soil Biology, 36, 127-133. Berg, M.P., de Ruiter, P.C., Didden, W., Janssen, M., Schouten, T. & Verhoef, H.A. (2001) Community food web, decomposition and nitrogen mineralisation in a stratified Scots pine forest soil. Oikos, 94, 130-142. Blackburn, T.M. & Gaston, K.J. (1994) Animal body size distributions: patterns, mechanisms and implications. Trends Ecology and Evolution, 9, 471-474. Bradford, M.A., Tordoff, G.M., Eggers, T., Jones, T.H. & Newington, J.E. (2002) Microbiota, fauna, and mesh size interactions in litter decomposition. Oikos, 99, 317-323. Britt, N.W. (1953) Differences between measurements of living and preserved aquatic nymphs caused by injury and preservation. Ecology, 34, 802-803. Caballero, M., Baquero, E., Arino, A.H. & Jordana, F. (2004) Indirect biomass estimations in Collembola. Pedobiologia, 48, 551-557. Dias, A.T.C., Krab, E.J., Marien, J., Zimmer, M., Cornelissen, J.H.C., Ellers, J. et al. (2013) Traits underpinning desiccation resistance explain distributionpatterns of terrestrial isopods. Oecologia, 172, 667-677. Douglass, J.K. & Wcislo, W.T. (2010) An inexpensive and portable microvolumeter for rapid evaluation of biological samples. BioTechniques, 49, 566-572. Ellers, J. & Jervis, M. (2003) Body size and the timing of egg production in parasitoid wasps. Oikos, 102, 164172. Gillooly, J.F., Allen, A.P., West, G.B. & Brwon, J.H. (2005) The rate of DNA evolution: Effects of body size and temperature on the molecular clock. Proceedings of the National Academy of Sciences of the United States of America, 102, 140-145. Greenleaf, S.S., Williams, N.M., Winfree, R. & Kremen, C. (2007) Bee foraging ranges and their relationship to body size. Oecologia, 153, 589-596. Honĕk A. (1993) Intraspecific variation in body size and fecundity in insects: a general relationship. Oikos, 66, 483-492. Johnston, T.A. & Cunjak, R.A. (1999) Dry-mass length relationships for benthic insects: a review with new data from Catamaran Brook, New Brunswick, Canada. Freshwater Biology, 41, 653-674. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


Laparie, M., Lebouvier, M., Lalouette, L. & Renault, D. (2010) Variation of morphometric traits in populations of an invasive carabid predator (Merizodus soledadinus) within a sub-Antarctic island. Biological Invasions, 12, 3405-3417. Lundkvist, H. (1978) A technique for determining individual fresh weights of live small animals, with special reference to Enchytraeidae. Oecologia, 35, 365-367. Martin, A.P. & Palumbi, S.R. (1993) Body size, metabolic rate, generation time, and the molecular clock. Proceedings of the National Academy of Sciences of the United States of America, 90, 4087-4091. Nijs, L.J.F.M den, Lock, C.A.M., Noorlander, J. & Booij C.J.H. (1996) Search for quality parameters to estimate the condition of Pterostichus cupreus (Col., Carabidae) in view of population dynamic modelling. Journal of Applied Entomology, 120, 147-151. Peters, R.H. (1983) The ecological implications of body size. Cambridge University Press, Cambridge. Pokarzhevskii, A.D., van Straalen, N.M., Zaboev, D.P. & Zaitsev, A.S. (2003) Microbial links and element flows in nested detrital food-webs. Pedobiologia, 47, 213-224. Ritchie, M.E. & Olff, H. (1999) Spatial scaling laws yield a synthetic theory of biodiversity. Nature, 400, 557560. Sabo, J.L., Bastow, J.L. & Power, M.E. (2002) Length-mass relationships for adult aquatic and terrestrial invertebrates in a California watershed. Journal North American Benthological Society, 21, 336-343. Sample, B.E., Cooper, J.R., Greer, R.D. & Whitmore, R.C. (1993) Estimation of insect biomass by length and width. American Midland naturalist, 129, 234-240. Smit, H., Dudok van Heel, E. & Wiersma, S. (1993) Biovolume as a tool in biomass determination of Oligochaeta and Chironomidae. Freshwater Biology, 29, 37-46. Sokolovska, N., Rowe, L. & Johansson, F. (2000) Fitness and body size in mature odonates. Ecological Entomology, 25, 239-248. Weiser, M.D. & Kaspari, M. (2006) Ecological morphospace of New World ants. Ecological Entomology, 31, 131-142. Woodward, G., Ebenman, B., Emmerson, M., Montoya J.M., Olesen, J.M., Valido, A. et al. (2005) Body size in ecological networks. Trends Ecology and Evolution, 20, 402-409.

2.2. EYE MORPHOLOGY Definition and relevance Eye morphology describes the design and anatomy of visual receptors. Eye morphology is related to activity time (Moser et al. 2004; Narendra et al. 2013), diet (Merry, Kemp & Rutowski 2011), detection of prey or resources (Prokopy & Owens 1983; Labhart & Nilsson 1995), predator avoidance (Stevens 2007), motion and flight ability (Taylor 1981). For example, species actively hunting, such as Odonata, jumping spiders, and dayactive carabid beetles have well-developed eyes that are good at capturing movements over broad visual fields. In general, diurnal species tend to have larger and better-developed eyes than nocturnal ones (Ribera et al. 1999). In cavernicolous and soil-dwelling species, the eyes are either of little or no use and there are many examples across the Arthropoda species losing their eyesight entirely. Furthermore, environmental conditions and habitat complexity are strongly associated with eye morphology (Talarico et al. 2007; Gibb & Parr 2013). Many pollinators and predators use their visual perception to find flowers and prey, respectively. What and how to measure There are three aspects to eye morphology: the categorical trait eye type, the number of repeated optical units, and the actual measurement of eye size of alive or preserved specimens.



Pre-treatment Animals should be described according to the standardisation protocol. Eye morphology can be assessed using specimens frozen directly after field collection. The head (and the body in the case of ocelli) of the individual should be carefully positioned on a flat surface to avoid biased measurements. Alternatively, living specimens can be used. How to record eye type? In insects, two types of eyes exist: simple eyes and compound eyes. - Simple eyes: Consist of one of more optical units, called ocelli, each of which generally consists of a lens and a variable number of photoreceptors. They can occur laterally or dorsally on the head or body in adult, pupal and larval stages of invertebrates. - Compound eyes: Composed of up to several thousands of ommatidia. An ommatidium consists of one or several lenses and photoreceptor cells. How to record eye number? The total number of eyes can be obtained by counting all optical units present on the whole body of an individual or by counting the number of ommatidia in a compound eye. The number of ommatidia can be counted on a high resolution picture with appropriate image treatment software such as the open source ImageJ. This is due to their high quantity (e.g., up to 30,000 in some species of Coleoptera). Approximations, such as counting the number of ommatidia in subset areas and upscaling to the whole eye, can be used. But care should be taken when using such methods as the number of ommatidia is not uniform across the eye surface in many species (Land 1997). Measurement of eye size Individuals should be placed individually on an inert surface. Make sure that the eye is positioned horizontally. Eye size can be measured as total eye surface area. For simple eyes it is the sum of the area (in mm2) of each ocellium occurring on the whole body. For compound eyes, surface area can be estimated from total eye dimension. Eyes can best be photographed using a digital camera connected to a stereomicroscope, as direct measurement with an ocular micrometer are less precise and therefore only to be used when no digital camera is available. Digital photographs can be analysed using public domain ImageJ software. Individual eyes should be magnified to the level that they fill >1/2 of the width of the microscope image. It is essential to report the level of magnification. Eye surface area depends on body size and should be standardized before cross-taxa comparisons by dividing by body size or by the total body surface area. Additional notes None. References Gibb, H. & Parr, C.L. (2013) Does Structural Complexity Determine the Morphology of Assemblages? An Experimental Test on Three Continents. PLoS ONE, 8, e64005. Labhart, T. & Nilsson, D.-E. (1995) The dorsal eye of the dragonfly Sympetrum: specializations for prey detection against the blue sky. Journal of Comparative Physiology A, 176, 437-453. Land, M.F. (1997) Visual acuity in insects. Annual Review of Entomology, 42, 147-177. Merry, J.W., Kemp, D.J. & Rutowski, R.L. (2011) Variation in compound eye structure: effects of diet and family. Evolution, 65, 2098-2110. Moser, J.C., Reeve, J.D., Bento, J.M.S., Della Lucia, T.M.C., Cameron, R.S. et al. (2004) Eye size and behaviour of day- and night-flying leafcutting ant alates. Journal of Zoology, 264, 69-75.



Narendra, A., Alkaladi, A., Raderschall, C.A., Robson, S.K. & Ribi, W.A. (2013) Compound eye adaptations for diurnal and nocturnal lifestyle in the intertidal ant, Polyrhachis sokolova. PLoS ONE, 8, e76015. Prokopy, R.J. & Owens, E.D. (1983) Visual detection of plants by herbivorous insects. Annual Review of Entomology, 28, 337-364. Ribera, I., Foster, G., Downie, I., McCracken, D. & Abernethy, V. (1999) A comparative study of the morphology and life traits of Scottish ground beetles (Coleoptera, Carabidae). Annales Zoologici Fennici, 36, 21-37. Stevens, M. (2007) Predator perception and the interrelation between different forms of protective coloration. Proceedings of the Royal Society B: Biological Sciences, 274, 1457-1464. Talarico, F., Romeo, M., Massolo, A., Brandmayr, P. & Zetto, T. (2007) Morphometry and eye morphology in three species of Carabus (Coleoptera: Carabidae) in relation to habitat demands. Journal of Zoological Systematics and Evolutionary Research, 45, 33-38. Taylor, C.P. (1981) Contribution of compound eyes and ocelli to steering of locusts in flight: I. Behavioural analysis. Journal of Experimental Biology, 93, 1-18.

2.3. RESPIRATION SYSTEM Definition and relevance Respiratory system is the anatomical structure of an organism that is involved in transport of oxygen and carbon dioxide between cells and the external environment. The type of respiratory system is of key importance as it determines microhabitat selection, such as the vertical distribution of species across soil profiles (Villani et al. 1999). The type of respiratory system is often coupled with respiration rates (Zinkler 1966). Also, in many invertebrate groups, especially in soil-dwellers, the type of respiratory system determines water loss rate when the animal is exposed to drought and the capacity to cope with inundation or waterlogged conditions (Villani et al. 1999; Hornung 2011). The respiratory structure has therefore a strong adaptive value. What and how to measure There is one approach to describe respiratory systems, which is based on the different types of anatomical structures used by organisms to respire. The type of respiratory structure can be very different across terrestrial species and depends on species’ phylogeny, life history and body size. Pre-treatment A pre-treatment is not necessary. Measurements The following types of respiratory systems are distinguished. Normally species possess one of these types but combinations of respiratory systems can occur, such as book lungs and trachea in some spiders. In general, the different types of respiratory systems can be distinguished from the outer appearance, but in some cases, for instance book lungs and trachea, the animal needs to be dissected. - Integumental respiration: Gas exchange through the outer surface of the body. Gas exchange in species with skin breathing or cutaneous respiration usually takes place all over the body, for instance in earthworms via series of thin-walled blood vessels under their skin. - Gills: Gas exchange through plate-like structures, ventrally on the surface of the abdomen or covered by coxal plates as a protection against drought. Gills can either be simple or be composed of sealed tubes. Gills can be found in land-hoppers and land crabs. - Pleopodal lungs: Gas exchange takes place in the pleopods, the last five abdominal segments of terrestrial isopods, across the ventral integument of the exopodites. There are four types of pleopodal lungs, which differ _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


in the level of folding of the epithelial respiratory surface (Hornung 2011). Type 1 is a thin, unfolded epithelial surface. Type 2 is a simple, open and folded epithelial surface. Type 3 is a weakly wrinkled, partly covered respiratory field. Type 4 is a strongly wrinkled surface, completely internalized lung with spiracles and water repellent surface. - Book lungs: Chitin-lined internal pockets located ventrally in the abdomen containing many plates filled with hemolymph over which air circulates and gas is exchanged. Species can possess one or two book lungs. Booklungs can be found in spiders and scorpions. - Tracheal lungs: The respiratory surfaces are located inside the body and connected to the outside by a series of trachea, small tubes that carry air directly to cells for gas exchange. Trachea are connected to the atmosphere by small, external openings at the body surface, the spiracles. In many large-bodied insects, such as Hymenoptera abdominal contractions speed up the rate of diffusion of gases from tracheae into body cells. Trachea can be found, among others, in insects and myriapods. - Simple lungs: A single opening in the mantle of snails that either remains open, or opens or closes as the animal breaths. The roof of the lung is highly vascularised which enables gas exchange. Additional notes In xeric environments respiratory transpiration via book lung systems in spiders or tracheal systems of myriapods and insects is the major source of water loss at higher temperatures and species have evolved morphological adaptations to minimize respiration. Spiracular openings are often covered by modified scales or setae or depressed below the cuticular surface (Punzo 2000). References Hornung, E. (2011) Evolutionary adaptation of oniscidean isopods to terrestrial life: structure, physiology and behavior. Terrestrial Arthropod Reviews, 4, 95-130. Punzo, F. (2000) Desert arthropods: life history variations. Springer, Heidelberg. Villani, M.G., Allee, L.L., Diaz, A. & Robbins, P.S. (1999) Adaptive strategies of edaphic Arthropods. Annual Review of Entomology, 44, 233-256. Zinkler, D. (1966) Vergleichende Untersuchungen zur Atmungs-physiologie von Collembolen (Apterygota) und anderen Bodenkleinarthropoden. Zeitschrift für vergleichende Physiologie, 52, 99-144.

2.4. HAIRINESS Definition and relevance Hairiness is the collective presence of any of the fine thread-like protein, notably keratin, filaments (hairs, seta or bristles) growing from the cuticle of invertebrates. Hairiness is of key importance as it provides animals with a hydrophobic layer that repels water and allows species to respond quickly to climatic fluctuations (Worland & Lukešová 2000) and feed on the water surface (Suter, Stratton & Miller 2004; Bush & Hu 2006). A dense hair cover reduces heat loss due to insulation (May 1979), which is especially important for ectotherms that need to reach critical temperatures for activities like flying or egg laying (Heinrich 1971). A fringe of branched hairs is used by bees as pollen baskets and other insects have specialised hairs that may facilitate pollen transport (Thorp 2000). Hairs can be used in defence acting as effective mechanical deterrents against predation and parasites (Eisner, Eisner & Deyrup 1996). Intra-specific hair length and density values differ between populations across latitude, vegetation structure and predatory community composition, with significant consequences for predator perception sensitivity (Dangles et al. 2005). Both hair length and density are under selective pressure and are important to understand because of the adaptive evolution of invertebrate sensory ecology (Humphrey, Barth & Voss 2001). _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


What and how to measure Hairiness is of ecological and evolutionary importance for invertebrates, but no good protocol is available in the literature how to measure hairiness. Here we propose to measure two aspects of hairiness: the density of hairs and the length of hairs. These can be measured on alive or preserved specimens. The absolute hair length is often depending on body size. For a meaningful comparison of hair length across terrestrial invertebrates, hair length should be compared relative to the size of the organisms. We recommend to publish body size measurement together with data on hair length. Pre-treatment Animals should be described according to the standardisation protocol. In liquid-preserved hairy animals, such as bumblebees, spiders and some flies, the hairs may stick to each other when specimens are taken from the liquid prior to the measurement. Care should be taken to dry the specimens thoroughly. If problems arise consider making the measurements in the preservation liquid with submerged animals. Hairiness may differ on different body parts and the exact coordinates of the measurement should always be reported (e.g. tibia, thorax, etc.). How to measure hair length? Specimens or specific body parts should be placed individually on an inert surface. Make sure that the position of hairs is horizontal and that hairs are not curled up. The length should be measured from the top of the hair to the base at the cuticula. The length of hairs can be measured under a dissecting microscope. To enable precise length measurements, the individuals should be magnified to the level that hairs fill >1/2 of the width of the microscope image. Use a calibrated ocular meter to record the length to the nearest μm, or, alternatively, a digital camera attached to the microscope in combination with the public domain ImageJ software estimate length. In both cases it is essential to report the level of magnification. How to measure hair density? Individuals should be prepared for viewing as described in the hair length protocol. Hair density is expressed as number of hairs mm-1 when hairs are counted along a transect of certain length perpendicular to the long axis of the body. Alternatively, hair density is expressed as the number of hairs per surface area (mm-2). We recommend to report the transect length or surface area measured to estimate hair density, along with the part of the body where hair density was estimated if it is not possible to measure the same length or surface area across groups. Additional notes When stored, some species easily loose hairs, in which case we recommend storing animals individually in containers not much bigger than the animals to prevent loss of hairs due to shaking. In case of specific hair types, such as filiform sensory hairs or trichobothria, the total number of hairs can be counted and the length of the hairs can be measured. The length of these hair types is the maximum length measured for a specific branch. Hairs can also be bifurcated or branched and this should be noted. References Bush, J.W.M. & Hu, D.L. (2006) Walking on water: biolocomotion at the interface. Annual Review Fluid Mechanics, 38, 339-369. Dangles, O., Magal, C., Pierre, D., Olivier, A. & Casas, J. (2005) Variation in morphology and performance of predator-sensing system in wild cricket populations. The Journal of Experimental Biology, 208, 461-468. Eisner, T., Eisner, M. & Deyrup, M. (1996) Millipede defense: Use of detachable bristles to entangle ants. Proceedings of the National Academy of Science USA, 93, 10848-10851. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


Heinrich, B. (1971) Temperature regulation of the sphinx moth, Manduca sexta. I. Flight energetics and body temperature during free and tethered flight. Journal of Experimental Biology, 54, 141-152. Humphrey, J.A.C., Barth, F.G. & Voss, K. (2001) The motion-sensing hairs of arthropods: using physics to understand sensory ecology and adaptive evolution. The Ecology of Sensing. (eds. F.G. Barth, A. Schmid). pp 105-125. Springer-Verlag Berlin. May, M.L. (1979) Insect thermoregulation. Annual review of Entomology, 24, 313-349. Suter, R.B., Stratton, G.E. & Miller, P.R. (2004) Taxonomic variation among spiders in the ability to repel water: surface adhesion and hair density. Journal of Arachnology, 32, 11-21. Thorp, R.W. (2000) The collection of pollen by bees. Plant Systematics and Evolution, 222, 211-223. Worland, M.R. & Lukešová, A. (2000) The effect of feeding on specific soil algae on the cold-hardiness of two Antarctic micro-arthropods (Alaskozetes antarcticus and Cryptopygus antarcticus). Polar Biology, 23, 766774.

2.5. COLOUR Definition and relevance Colour is defined as a feature of the animal that results from the light they reflect or emit, and is a mixture of various wave lengths, or spectra. Colour is depending on the deposition of pigments in the cuticula of organisms which absorb certain wave lengths or is created by an optical effect (iridescence) via interference, refraction or diffraction and arise from the arrangement of physical structures, such as scales or hairs, interacting with light (so-called structural colours). Colour is involved in thermoregulation of organisms (Heinrich 1993; Forsman et al. 2002). Dark colouration increases body temperature and activity (de Jong, Gussekloo & Brakefield 1996) and can protect arctic and high altitude arthropods against freezing (Dansk 2004) and high ultraviolet-B radiation (Leinaas 2002; Hodkinson 2005). The spatial distribution and microhabitat selection of species are often associated with its colouration (Ahnesjö & Forsman 2006). Colour can also have a defensive function by presenting a degree of protection from parasites and predators, via crypsis, warning colours and mimicry (Price et al. 1980; Gambralle-Stille, Johansen & Tullberg 2010; Théry & Gomez 2010). Invertebrate colour is a key model system in evolutionary and developmental biology (Mallet & Joron 1999; Wittkopp & Beldade 2009). Colour is an important mate signal, and selection on colour can affect mate preference (Ellers & Boggs 2003), while polymorphism in body colour may translate into selection against thermally inferior phenotypes (Forsman, Ahnesjö & Caesar 2007). What and how to measure Colouration consists of two aspects: spectral colours and colour patterning. Spectral colour can be expressed as a categorical value by using RBG colour codes charts, which construct codes and colour names from the combination of red, blue and green colours. Colour patterning can be either absent or present in the form spots, stripes, blocks or a combination. For each patterning type, the relative proportion of the patterned colour against the background colour can be quantified using image analysis approaches. In the latter approach, colour pattern is quantified by converting the image to a grayscale form and calculating the percentage of pixels above a certain threshold value (Ellers & Boggs 2003; Davis, Farrey & Altizer 2005). Colour measurements based on photographic images of specimens are sensitive to light conditions, so one should take care that both the camera and computer screen are properly calibrated. If specimens are photographed indoors we recommend to publish the colour temperature of the light source used to light the specimens.



Pre-treatment Many soft-bodied species change in colour when dead or become pale or may even loose colour when chemically preserved. Therefore, colour should be measured in live animals or directly after dead. If it is necessary to kill animals we recommend to use freezing or CO2 to prevent discolouration. Measurement of spectral colour. Two basic colour codes are available; the Hex Code and the Decimal Code (based on the level of RBG), and both codes are translated into a colour name. Colours can either be expressed as a category (using RBG colour table) or a value. Colouration may differ on different body parts and the exact location of the measurement should always be reported. Also, coloration can change during the life time of an organism (Gamberalle-Stille et al. 2010) and across the geographical range of species (Hegna & Mappes 2014) and we recommend to publish the life stage and geographic location together with colour measurements. Individual should be sexed as males and females as in some invertebrate groups colouration is a sexual dimorphic trait. Measurement of colour pattern The following four main categories of colour patterning are distinguished. Species can belong to more than one category. - No pattern: No colouration (completely white) or a diffuse colour without sharp shifts in intensity - Spots: Roundish, ellipsoid or irregular marks of a different colour code than the background colouration - Stripes: Elongated marks (linear or curved) of a different colour code than the background colouration - Checkered: Squared marks of a different colour code than the background colouration, often repeated across the body part To quantify the relative proportion of the patterned colour against the background, the area of interest should be photographed on a standard grey background (RBG color code 119, 119, 119) using a digital camera, if necessary mounted on a microscope. Using image analysis software, the image should be converted to a greytone image and standardized through a percentage saturation stretch of the tonal histogram of the image (Wilkie & Finn 1996). This is a commonly used remote sensing technique which ensures that the full range of black tones for each image is used by setting the bottom and top first percentile of the black tonal range to pure black and pure white. Subsequently, a threshold value for contrast can be set to calculate the percentage of pixels that falls below (or above) this threshold value. Additional notes In some arthropod taxa reversible colour change is known to occur in some species depending on the substrate colour (Umbers et al. 2014). We recommend to publish the background colour. The above protocol only measures colours in the visible spectrum, and not ultraviolet reflectance. For instance, many insects can see ultraviolet colours not visible to the human eye (Briscoe & Chittka 2001). For specific research questions it may be necessary to measure colour spectra instead of using colour categorization. This alternative approach of image colour analysis is based on photon counts, and spectral data are compared to colour categorization more precise and objective quantitative measurements. Reflectance spectra give the proportion of the incident light that is reflected by a specific invertebrate colour patch or the background colour, while irradiance spectra give the light intensity available at each wave length (Théry & Gomez 2010). Reflectance spectra of animal body parts can be measured directly, using a spectrophotometer (Théry & Gomez 2010; Hegna & Mappes 2014).



References Ahnesjö, J. & Forsman, A. (2006) Differential habitat selection by pygmy grasshopper colour morphs; interactive effects of temperature and predator avoidance. Evolutionary Ecology, 20, 235-257. Briscoe, A.D. & Chittka L. (2001) The evolution of color vision in insects. Annual Review of Entomology 46, 471-510. Dansk, H.V. (2004) Seasonal adaptations in arctic insects. Integrative and Comparative Biology, 44, 85-94. Davis, A.K., Farrey, B. & Altizer, S. (2005) Variation in thermally induced melanism in Monarch Butterflies (Lepidoptera: Nymphalidae) from three North American populations. Journal of Thermal Biology, 30, 410421. de Jong, P., Gussekloo, S.W.S. & Brakefield, P.M. (1996) Differences in thermal balance, body temperature and activity between non-melanistic two-spot ladybird beetles (Adalia bipunctata) under controlled conditions. Journal of Experimental Biology, 199, 2655-2666. Ellers, J. & Boggs, C.L. (2003) The evolution of wing color: male mate choice opposes adaptive wing colour divergence in Colias butterflies. Evolution, 57, 1100-1106. Forsman, A., Ringblom, K., Civantos, E. & Ahnesjo, J. (2002) Coevolution of color pattern and thermoregulatory behavior in polymorphic pygmy grasshoppers Tetrix undulata. Evolution, 56, 349-360. Forsman, A., Ahnesjö, J. & Caesar, S. (2007) Fitness benefits of diverse offspring in pygmy grasshoppers. Evolutionary Ecology Research, 9, 1305-1318. Gambralle-Stille, G., Johansen, A.I. & Tullberg, B.S. (2010) Change in protective coloration in the striated shieldbug Graphosoma lineatum (Heteroptera: Pentatomidae): predator avoidance and generalization among different life stages. Evolutionary Ecology, 24, 423-432. Hegna, R.H. & Mappes, J. (2014) Influences of geographic differentiation in the forewing warning signal of the wood tiger moth in Alaska. Evolutionary Ecology, 28, 1003-1017. Heinrich, B. (1993) The hot-blooded insects: strategies and mechanisms of thermoregulation. Harvard University Press, Cambridge. Hodkinson, I.D. (2005) Terrestrial insects along elevation gradients: species and community responses to altitude. Biological Reviews, 80, 489-513. Leinaas, H.P. (2002) UV tolerance, pigmentation and life forms in high Arctic Collembola. Ecological Studies, 153, 123-134 Mallet. J. & Joron, M. (1999) Evolution of diversity in warning color and mimicry: Polymorphisms, shifting balance, and speciation. Annual Review of Ecology and Systematics, 30, 201-233. Price, P.W., Bouton, C.E., Gross, P., McPheron, B.A., Thompson, J.N. & Weis, A.E. (1980) Interactions among three trophic levels: influence of plants on interactions between insects herbivores and natural enemies. Annual review of Ecology and Systematics, 11, 41-65. Théry, M. & Gomez, D. (2010) Insect colours and visual appearance in the eye of their predators. Advances in Insect Physiology, 38, 267-353. Umbers, K.D.L. Fabricant, S.A., Gawryszewski, F.M., Seago, A.E. & Herbertstein, M.E. (2014) Reversible colour change in Arthropoda. Biological Review, 89, 820-848. Wilkie, D.S. & Finn, J.T. (1996) Remote sensing imagery for natural resources monitoring. Columbia University Press, New York. Wittkopp, P.J. & Beldade, P. (2009) Development and evolution of insect pigmentation: genetic mechanisms and the potential consequences of pleiotropy. Seminars in Cell & Developmental Biology, 20, 65-71.



3. FEEDING 3.1. FEEDING GUILD Definition and relevance Feeding guild is a group of species that exploit the same resource, often in a similar way. Feeding guild determines the quality of resources, which influences a species growth, reproduction and survival. Feeding guild provides information about “who eats what or whom” and competition, and can be considered a good surrogate for trophic level and position in the food web. Feeding guild is related to morphological, physiological and phenological underlying traits that selected to process different types of food material (Novotny et al. 2010). Feeding guild therefore is an important component shaping the structure of ecological networks (Stang et al. 2009; Ibanez 2012) and has a direct link to ecosystem functions. Several studies have shown that the response to environmental change is often concordant among species in the same feeding guild (Voigt et al. 2003; Hillstrom & Lindroth 2008). What and how to measure Feeding guild is a categorical trait assessed through straightforward field observation. Additionally, other methods, such as stable isotopes, molecular methods or fatty acid composition can be used to establish the feeding guild on field-collected animals (Traugott et al. 2013). Pre-treatment A pre-treatment is not necessary. How to record feeding guild? The following five distinct main categories of feeding guilds are distinguished, and each of these can be subdivided into constituent guilds based on exploitation of species resources or with a specific mode of feeding. We recommend to always allocate species to one of the main categories, and to a constituent guild if necessary or possible. - Herbivores: Species feeding on living vegetable mater. This category can be subdivided, among others, into different constituent guilds such as species feeding on moss (bryophagous), wood (xylophagous), phloem (phloem-sap feeders), leaves (phyllophagous), roots (rhizophagous), seeds (granivores), pollen (pollen feeders) and nectar (nectarivores). - Carnivores: Species feeding on animal matter. This category includes constituent guilds such as the true predators and species having a parasitic life style (parasites and parasitoids). - Microbivores: Species feeding on microorganisms, such as feeding on bacteria (bacterivores), fungi (fungivores, either spores, hyphae or fruiting bodies) or Protozoa. - Detritivores: Species feeding on dead and decaying organic matter, including leaf litter, dead roots, dead wood, dung, and carrion (scavengers) - Omnivores: Species feeding on more than one of the major categories defined above. We recommend to indicate which of the four major feeding guilds the species belongs to. Additional notes Direct observations on feeding should be interpreted with caution because it cannot be observed what part of the food is actually used for consumption. For example, detritivores consume dead organic matter but this also contains a microbial biofilm that may be the target of their foraging efforts. Therefore, much of the determination of diet in invertebrates has shifted from direct observation to molecular methods, stable isotopes and fatty acid



analysis that are likely to more accurately reflect diet (Schneider et al. 2004; Traugott et al. 2013). Some invertebrate species do not feed as an imago, and can therefore not be allocated to one of the feeding guilds. For certain research questions it might be necessary to have more detailed information on the type of diet, the origin of diet items or the overlap in diet composition of invertebrates. DNA metabarcoding can provide information on diet composition, dietary niche partitioning and diet breadth, for instance in herbivores (Kartzinel et al. 2015), using specific markers. Stable isotope labelling studies might be used to investigate food choice, diet selectivity and trophic position or investigate changes in trophic structure during succession, by comparing stable isotope signatures between species (Schneider et al. 2004; Schrama et al. 2013), while feeding strategies can also be inferred from the lipid composition of invertebrates and their food resources, using specific fatty acid markers (Ruess & Chamberlain 2010). References Hillstrom, M.L. & Lindroth, R.L. (2008) Elevated atmospheric carbon dioxide and ozone alter forest insect abundance and community composition. Insect Conservation and Diversity, 1, 233-241. Ibanez, S. (2012) Optimizing size thresholds in a plant-pollinator interaction web: towards a mechanistic understanding of ecological networks. Oecologia, 170, 233-242. Kartzinel. T.R., Chen, P.A., Coverdale, T.C., Erickson, D.L., Kress, W.J. Kuzmina, M.L., Rubenstein, D.I., Wang, W. & Pringle, R.M. (2015) DNA metabarcoding illuminates dietary niche partitioning by African large herbivores. Proceedings National Academy of Science, 112, 8019-8024. Novotny, V., Miller, S.E., Baje, L., Balagawi, S., Basset, Y., Cizek, L., Craft, K.J., Dem, F., Drew, R.A., Hulcr, J., Leps, J., Lewis, O.T., Pokon, R., Stewart, A.J., Samuelson, G.A. & Weiblen, G.D. (2010) Guild-specific patterns of species richness and host specialization in plant-herbivore food webs from a tropical forest. Journal of Animal Ecology, 79, 1193-1203. Ruess, L & Chamberlain P.M. (2010) The fat that matters: soil food web analysis using fatty acids and their carbon stable isotope signature. Soil Biology Biochemistry, 42, 1898-1910. Schrama, M., Jouta, J., Berg, M.P. & Olff, H. (2013) Food web assembly at the landscape scale: Using stable isotopes to reveal changes in trophic structure during succession. Ecosystems, 16, 627-638. Schneider, K., Migge, S., Norton, R.A., Langel, R., Reineking, A. Maraun, A. (2004) Trophic niche differentiation in soil microarthropods (Oribatida, Acari): evidence from stable isotope ratios (N-15/N-14). Soil Biology Biochemistry, 36, 1769-1774. Stang, M., Klinkhamer, P.G.L., Waser, N.M., Stang, I. & van der Meijden, E. (2009) Size-specific interaction patterns and size matching in a plant-pollinator interaction web. Annals of Botany, 103, 1459-1469. Traugott, M., Kamenova, S., Ruess, L, Seeber J. & Plantegenest, M. (2013) Empirically characterizing trophic networks: what DNA-based methods, stable isotope and fatty acid analyses offer. Advances in Ecological Research, 49, 177-224. Voigt, W., Perner J., Davis, A.J., Eggers, T., Schumacher, J., Bährmann, R., Fabian, B., Heinrich, W., Köhler, G., Lichter, D., Marstaller, R. & Sander, F.W. (2003) Trophic levels are differentially sensitive to climate. Ecology, 84, 2444-2453.

3.2. INGESTION RATE Definition and relevance Ingestion rate is defined here as the quantity of a single food source taken up by an animal in a given unit of time. The rate of food ingested by an organism reflects its nutritional and energetic requirements and indicates the potential consumption of a given food type when no food choice is allowed. Ingestion rate varies strongly with the quality of food offered and temperature and is, therefore, related to species response to changes in food _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


quality (Sousa et al. 1998; Roslin & Salminen 2008; Paritsis & Veblen 2010) and climatic conditions (David & Gillon 2002; Levesque, Fortin & Mauffette 2002; Lee & Roth 2010). Additionally, ingestion rates can indicate competitive ability among species feeding on the same food sources (Morton & Yuen 2000). Since some invertebrates affect ecosystem processes and services through their feeding activity, ingestion rate is a surrogate of species effects on ecosystem processes, such as litter decomposition (e.g. Bílá et al. 2014; Heemsbergen et al. 2004) and biological control (Hagler 2009). What and how to measure Ingestion rate is based on measuring the difference between the initial and the final (left after consumption by the animal) dry mass of the food item. Ingestion rate is expressed as the amount of food dry mass taken up per unit animal dry mass per unit of time. Pre-treatment Animals should be described according to the standardisation protocol. Animals should be acclimated at the temperature to be used in the experiment, since ingestion rate changes with metabolic rate and therefore with temperature (Römbke, Römbke & Russell 2001; Zamani et al. 2006; Paritsis & Veblen 2010). During this period, animals should be offered the food to be used to measure ingestion rates, making sure all individuals are exposed to the test food before the experiment begins. To standardize the initial motivation for feeding, before starting the experimental assays to measure ingestion rates, individuals should be starved for a standard period (at least 24 hours) with ad libitum water supply. How to measure ingestion rate? Animals should be kept individually in microcosms. Different taxonomical groups will require different microcosm’s size and configuration to ensure favourable conditions to growth. Animals should be offered ad libitum food and water supply, and special care should be taken that the quality of the food is kept constant over the measuring period. If food quality changes with time it should be replaced regularly. Ingestion rates (IR) is calculated as: 𝐼𝐼𝑅𝑅 =

𝑀𝑀𝑖𝑖 −𝑀𝑀𝑓𝑓 𝑇𝑇. 𝐶𝐶𝑚𝑚�

where Mi is the initial food dry mass, Mf is the final food dry mass, T is the time duration of the feeding assay, and 𝐶𝐶𝑚𝑚� is the average consumer dry mass during the experiment. If the duration of the experiment is short and changes in consumer biomass are considered negligible, consumer dry mass can be recorded at the end only (see body size protocol). Otherwise, the initial dry mass of consumers should be estimated and the average consumer mass calculated as 𝐶𝐶𝑚𝑚� = �𝐶𝐶𝑖𝑖 + 𝐶𝐶𝑓𝑓 �⁄2, where Ci and Cf are the consumer's initial and final dry mass, respectively. To estimate Ci, it is necessary to record the consumer dry to fresh mass ratio (CDM:FM) at the beginning of the assay and use the formula 𝐶𝐶𝑖𝑖 = 𝐶𝐶𝐹𝐹𝐹𝐹 𝐶𝐶𝐷𝐷𝐷𝐷:𝐹𝐹𝐹𝐹 , where CFM is the initial fresh mass of the individual. The CDM:FM is measured in an extra batch of individuals of the same ontogenetic stage as the IR measurements that should be weighed at the beginning of the assay and immediately oven dried for determining the dry mass. Similarly, food often cannot be dried before offering them to consumers (e.g., preys and green leaves). In these cases, the initial food dry mass (Mi) should be estimated using food’s dry to fresh mass ratio and the same approach described above for each consumer. Since methods differ substantially depending on the organism diet, we describe below the protocols for feeding assays according to four broad trophic guilds: Detritivores



A single detritivore should be added to a feeding arena with a moist bottom together with freshly senesced leaf litter, pre-treated leaf litter, dung or another detritus components. Freshly senescent litter should be collected during litter fall to allow for nutrient retention by the plant and air dried at room temperature (PérezHarguindeguy et al. 2013). Care should be taken to avoid leaves with any obvious signs of visible damage, infection or attack by herbivores. A thin layer of moist standard litter layer should be added to the arena as a litter layer is preferable as ingestion rates measured using a few small leaf litter disks underestimate ingestion rates. For some detritivores, such as isopods, it is shown that leaf litter needs to be pre-degraded by fungi to be of suitable quality for consumption. Litter-colonizing and -decomposing microbiota make plant tissues more digestible through the breakdown of recalcitrant and deterrent compounds (Zimmer 2002; Hedde et al. 2007). To precondition leaf litter, freshly senesced litter collected during litter fall should be exposed to a microbial wash for a number of days, following the procedure of Bílá et al. (2014). To make the microbial wash, fresh litter and soil should be collected, preferably in the same type of ecosystem where the animals were collected, and placed to soak in water for three hours. A shaker can be used to help mixing the detritus in water. This solution should be sieved to exclude small animals. The resulting microbial wash should be sprayed in the litter at least two days before adding the detritivores for allowing the initial colonization of microorganisms (Bílá et al. 2014). The number of days of incubation of fresh litter depends on the quality of the litter and is longer for low quality litter. We recommend to stop preconditioning when litter has lost 5% of its initial weight at the start of incubation. Sub-samples of air-dried detritus should be weighed, and again after 48h in the oven (40 °C) so as to calculate the initial oven-dried mass of detritus added to the feeding arenas (Mi). Many detritivores are coprophagous (Zimmer 2002) and, therefore, faeces should not be removed during the experiment. A substantial amount of detritus can be respired by microorganisms during detritivore feeding assays depending on the quality of the litter and the time of the assay. To exclude microbial respiration when estimating ingestion rates, additional detritivore-free controls should be set, subjected to the same environmental conditions as the ones with detritivores. Using initial (Li) and final (Lf) litter dry mass of these controls, it is possible to calculate proportion of litter mass loss due to microbial decomposition (𝐷𝐷 = �𝐿𝐿𝑖𝑖 − 𝐿𝐿𝑓𝑓 �⁄𝐿𝐿𝑖𝑖 ). Detritivore ingestion rate should be calculated using the corrected amount of food ingested (Icor) as proposed by (David 1998): 𝐼𝐼𝑐𝑐𝑐𝑐𝑐𝑐 =

(𝑀𝑀𝑖𝑖 −𝑀𝑀𝑖𝑖 𝐷𝐷 − 𝑀𝑀𝑓𝑓 ) √1 − 𝐷𝐷

This correction for microbial detritus degradation does not account for the indirect stimulation of microbial community by detritivores due to detritus fragmentation, mixing and feces production, which is difficult to disentangle from the direct ingestion of litter. Nonetheless, both direct ingestion and stimulation of microbial activity can be understood as components of the total effect of detritivores on litter decomposition.

Leaf feeders A single herbivore should be placed on the feeding arena together with fresh and intact leaves or other plant constituents, such as seeds, fruits, roots etc. of the focal species. In case of leaves, individual leaves offered to the herbivore in the feeding arena should be hydrated and stay turgid during the entire feeding assay. To do so, the petiole could be inserted in a small vial filled with water and sealed with parafilm, or wet cotton can be used to wrap the end of the petiole (Ibanez et al. 2013). Initial leaf mass should be recorded for posterior conversion of initial dry mass (Mi) as described above. At the end of the feeding assay, the remaining leaf and the herbivores should be oven dried to record their dry masses (respectively, Cm and Mf). Estimating the initial leaf dry mass might be difficult when the variability of leaf water content is high. In this case, we suggest to visually estimate the area eaten and divide it by the specific leaf area to estimate the mass eaten (Ibanez et al. 2013). Phloem- and xylem-sap feeders _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


For phloem- and xylem-sap feeders it is not possible to directly measure the amount of food ingested. Advanced Electrical Penetration Graph (EPG-DC) techniques can be used to estimate food ingested based on measurements of the sucking activity and timing (e.g., Sandanayaka, Jia & Charles 2013). The volume of fluid sucked per unit time, i.e., V/t (µm3 s-1) can be quantified based on the Poiseuille relationship (Mittler 1967; Cohen 1998): V/t= ΔP πr4 / 8ηL where ΔP is the pressure differential applied to the fluid by the sucking insect (unit: pascal), r is the radius of the fluid canal of the stylet (µm), L is the length of the fluid canal (µm), and η is the dynamic viscosity of the fluid (unit: pascal second). Nectarivores A single nectarivore should be placed in a feeding arena together with a vial containing a standard sugar solution (e.g., Vattala et al. 2006). The time spent feeding on the sugar solution should be recorded and the foraging bout should be finished when the individual leaves the vial. Feeding vials should be weighed immediately before and after each foraging bout to determine the mass of solution ingested by the individual. A control feeding vial, with no access to nectarivores, should be also weighed to discount for evaporation (Winkler et al. 2009). Colorful vials or structures simulating flowers can be used to attract and train visually-oriented nectarivores to feed on the sugar solution and also serve as landing platform for flying insects (Borrel 2006; Nardone, Dey & Kevan 2013). The ingestion rate can be expressed as mass of sugar or energy amount (in Joules) ingested per individual dry weight per time unit. The sugar content and viscosity of the solution should be published together with values on ingestion rate as these can affect ingestion rates (Kim, Gilet & Bush 2011). Predators A single predator should be placed in the feeding arena together with sufficient prey individuals. Caution should be taken to offer standardized preys. Initial prey fresh mass should be recorded for posterior conversion to initial dry (Mi) mass as described above. At the end of the feeding assay, remaining prey should be counted and oven dried to record their dry masses (Mf). In case of small preys, such as aphids or springtails, an alternative would be to count the number of eaten preys and to convert it in a mass unit, based on mass measurements on another set of preys. Additional notes It is difficult to measure ingestion rates of endophagous herbivores, such as leaf mining species, using the approach described above. In such cases, it might be possible to record the volume or area of plant tissue eaten by the animal during a given period of time and covert these measurements to mass eaten. For instance, the area of the track left by leaf-mining insects can be recorded. The difference in mass per area between the track and the uneaten leaf portion can be used to calculate the total mass eaten in a given period of time. When measuring ingestion rate it might be of interest to calculate assimilation efficiency and production efficiency simultaneously. Assimilation efficiency (proportion of ingested food that is assimilated by the animal) and the production efficiency (body mass increment per amount of ingested food) reflect the amount of food processed by an organism and how efficiently it digests and incorporates the food in its own biomass. Assimilation efficiency (AE) is calculated as: 𝐴𝐴𝐸𝐸 =

(𝐼𝐼 − 𝐹𝐹𝑚𝑚 ) 𝐼𝐼



Where I denotes the amount of food ingested and Fm is the fecal dry mass. When measuring AE, feces should be collected every other day and immediately oven dried to avoid mass loss due to microbial respiration.



Production efficiency (PE) is calculated as: 𝑃𝑃𝐸𝐸 =

(𝐶𝐶𝑓𝑓 − 𝐶𝐶𝑖𝑖 ) 𝐼𝐼

Where I denotes the amount of food ingested, and Cf and Ci are the consumer final and initial dry mass, respectively. For very small animals, e.g. springtails, it might be impossible to quantify ingestion rate for isolated individuals. In this case, groups of individuals in each microcosm could be used to increase the detection of changes in the food mass. References Bílá, K., Moretti, M., Bello, F., Dias, A.T.C., Pezzatti, G.B., Van Oosten, A.R. et al. (2014) Disentangling community functional components in a litter-macrodetritivore model system reveals the predominance of the mass ratio hypothesis. Ecology and Evolution, 4, 408-16. Borrell, B.J. (2006) Mechanics of nectar feeding in the orchid bee Euglossa imperialis: pressure, viscosity and flow. The Journal of Experimental Biology, 209, 4901-4907. Cohen, A.C. (1998) Biochemical and morphological dynamics and predatory feeding habits in terrestrial Heteroptera. Predatory Heteroptera in Agroecosystems: Their Ecology and Use in Biological Control. Thomas Say Publ. Entomol., Entomol. Soc. Am., Lanham, MD, 21-32. David, J.-F. (1998) How to calculate leaf litter consumption by saprophagous macrofauna ? European Journal of Soil Biologyopean, 34, 111-115 David J.F. & Gillon D. (2002). Annual feeding rate of the millipede Glomeris marginata on holm oak (Quercus ilex) leaf litter under Mediterranean conditions. Pedobiologia, 46, 42-52. Hagler, J. (2009) Comparative studies of predation among feral, commercially-purchased, and laboratory-reared predators. BioControl, 54, 351-361. Hedde, M., Bureau, F., Akpa-Vinceslas, M., Aubert, M. & Decaëns, T. (2007) Beech leaf degradation in laboratory experiments: effects of eight detritivorous invertebrate species. Applied Soil Ecology, 35, 291301. Heemsbergen, D.A., Berg, M.P., Loreau, M., van Hal, J.R., Faber, J.H. & Verhoef, H.A. (2004) Biodiversity effects on soil processes explained by interspecific functional dissimilarity. Science, 306, 1019-1020. Ibanez, S., Lavorel, S., Puijalon, S. & Moretti, M. (2013) Herbivory mediated by coupling between biomechanical traits of plants and grasshoppers. Functional Ecology, 27, 479-489. Lee, K.P. & Roth, C. (2010) Temperature-by-nutrient interactions affecting growth rate in an insect ecotherm. Entomologia Experimentalis et Applicata, 136, 151-163. Levesque, K.R., Fortin, M. & Mauffette, Y. (2002) Temperature and food quality effects on growth, consumption and post-ingestive utilization efficiencies of the forest tent caterpillar Malacosoma disstria (Lepidoptera Lasiocampidae). Bulletin of Entomological Research, 92, 127-136. Kim, W., Gilet, T. & Bush, J.W.M. (2011) Optimal concentrations in nectar feeding. Proceedings of the National Academy of Sciences of the United States of America, 108, 16618-16621. Mittler, T.E. (1967) Flow Relationships for Hemipterous Stylets. Annals of the Entomological Society of America, 60, 1112-1114. Morton, B. & Yuen, W.Y. (2000) The feeding behaviour and competition for carrion between two sympatric scavengers on a sandy shore in Hong Kong: The gastropod, Nassarius festivus (Powys) and the hermit crab, Diogenes edwardsii (De Haan). Journal of Experimental Marine Biology and Ecology, 246, 1-29. Nardone, E., Dey, T. & Kevan, P.G. (2013) The effect of sugar solution type, sugar concentration and viscosity on the imbibition and energy intake rate of bumblebees. Journal of Insect Physiology, 59, 919-933.



Paritsis, J. & Veblen, T.T. (2010) Temperature and foliage quality affect performance of the outbreak defoliator Ormiscodes amphimone (F.) (Lepidoptera : Saturniidae) in northwestern Patagonia , Argentina. Revista Chilena de Historia Natural, 83, 593-603. Pérez-Harguindeguy, N., Díaz, S., Garnier, E., Lavorel, S., Poorter, H., Jaureguiberry, P., Bret-Harte, M.S., Cornwell, W.K., Craine, J.M., Gurvich, D.E., Urcelay, C., Veneklaas, E.J., Reich, P.B., Poorter, L., Wright, I.J., Ray, P., Enrico, L., Pausas, J.G., de Vos, A.C., Buchmann, N., Funes, G., Quétier, F., Hodgson, J.G., Thompson, K., Morgan, H.D., ter Steege, H., Sack, L., Blonder, B., Poschlod, P., Vaieretti, M.V., Conti, G., Staver, A.C., Aquino, S. & Cornelissen, J.H.C. (2013) New handbook for standardised measurement of plant functional traits worldwide. Australian Journal of Botany, 61, 167-234. Römbke, T., Römbke, J. & Russell, D. (2011) Effects of temperature increases on the feeding activity of two species of isopods (Porcellio scaber, Porcellionides pruinosus) in laboratory tests. Soil Organisms, 83, 211220. Roslin, T. & Salminen, J. (2008) Specialization pays off : contrasting effects of two types of tannins on oak specialist and generalist moth species. Oikos, 117, 1560-1568. Sandanayaka, W.R.M., Jia, Y. & Charles, J.G. (2013) EPG technique as a tool to reveal host plant acceptance by xylem sap-feeding insects. Journal of Applied Entomology, 137, 519-529. Sousa, J.P., Vingada, J.V., Loureiro, S., da Gama, M.M. & Soares, A.M.V.M. (1998) Effects of introduced exotic tree species on growth, consumption and assimilation rates of the soil detritivore Porcellio dilatatus (Crustacea: Isopoda). Applied Soil Ecology, 9, 399-403. Vattala, H.D., Wratten, S.D., Phillips, C.B. & Wäckers, F. L. (2006). The influence of flower morphology and nectar quality on the longevity of a parasitoid biological control agent. Biological Control, 39, 179-185. Winkler, K., Wackers, F.L., Kaufman, L.V., Larraz, V. & van Lenteren, J.C. (2009). Nectar exploitation by herbivores and their parasitoids is a function of flower species and relative humidity. Biological Control, 50, 299-306. Zamani, A., Talebi, A., Fathipour, Y. & Baniameri, V. (2006) Temperature-dependent functional response of two aphid parasitoids, Aphidius colemani and Aphidius matricariae (Hymenoptera: Aphidiidae), on the cotton aphid. Journal of Pest Science, 79, 183-188. Zimmer, M. (2002) Nutrition in terrestrial isopods (Isopoda: Oniscidea): an evolutionary-ecological approach. Biological Reviews of the Cambridge Philosophical Society, 77, 455-493.

3.3. BITING FORCE Definition and relevance Biting force is defined as the biomechanical force exerted on food items or natural enemies by the tip of the mouth-parts, claws or fore legs. Biting force is applied here sensu lato, and includes biting, chewing, grinding, and scraping. Biting force primarily determines which food items can be processed by the organisms, depending on the biophysical properties of the mouth parts (Meyers & Irschick 2015). Biting force can also be of ecological importance against predators or parasitoids (Gentry & Dyer 2002) and against congeneric competitors, especially among males competing for females (Umbers et al. 2012). Biting force behaves as a threshold trait (Santamaría & Rodríguez-Gironés 2007), so that above a given force the exploitation barrier of the food item toughness is circumvented. Biting force is a key trait to predict for instance effects of herbivores on plant primary production (Deraison et al. 2015), as plant toughness determines the structure of plant-herbivore interaction networks (Peeters, Sanson & Read 2007; Ibanez et al. 2013). Similarly, the penetrability of shells also shape predator prey interactions between carabid beetles and snails (Konuma & Chiba 2007). Biting force is subject to selection pressures and trade-offs, as displaying a higher force can negatively affect other functional traits (Konuma & Chiba 2007; Holzman et al. 2012). _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


What and how to measure There is one common approach to measure biting force: the quantification of the amount of mechanical force (in Newton) placed by the tip of the mouth parts, claws or forelegs over a food item when closed. Biting force is estimated using biomechanical models, it is a relative measure allowing comparisons between individuals and species (Ibanez et al. 2013). Pre-treatment Animals should be described according to the standardisation protocol. The cuticle of the body needs to be soft for dissection and measurement of the mouth-parts involved in force. The mouth-parts of dried invertebrates cannot be properly dissected, so individuals should be dissected just after thawing or conserved in 70% ethanol. For measurements, mouth-parts should be placed in fine sand or in small glass beads, so that they are correctly oriented for 2D imaging. How to measure biting force? The biting force Fout (N) of biting and grinding mouth parts can be estimated through a simple biomechanical model based on lever dynamics (Wheater & Evans 1989; Westneat 2003; Clissold 2007): Fout = Fin Lin / Lout where Lout is the length (mm) between the axis of rotation of the mouth-parts and the point at which the biting force is exerted, Lin is the length (mm) between the axis of rotation and the point at which the adductor muscles are attached (see Fig. 1). Fin is the force (N) of the adductor muscles. Fin cannot be easily measured directly, we therefore recommend to use the muscles’ volume as a proxy. The muscle volume is estimated through 2D imaging (e.g., using ImageJ software) by the head volume, the product between head width, head height and head length, given that most of the head volume is occupied by muscles (Ibanez et al. 2013). The biting force Fout can be applied by a point (e.g. carabid mandibles), a line (e.g. incisive region of grasshopper mandibles) or a surface (e.g. molar region of grasshopper mandibles). Fout should then be divided by the length of the incisive region or by the area of the molar region (Ibanez et al. 2013).

Incisive strength

Adductor muscle strength

Axis of rotation

Fig. 1: Lever dynamics model based on the example of the mandible of a grasshopper showing the incisive region (of strength Fout and length Ri) and the molar region (area Rm, in light grey). The incisive (Lout) and adductor muscle (Lin) levers are measured from the axis of rotation defined as the line between the attachment points to the head (dark grey). Draw adapted from Ibanez et al. (2013).

How to measure mandible mass acceleration? The former model applies when the speed of mandible movement is relatively slow and is therefore independent of the mandibular force. However, some organisms are able to close their mandibles extremely rapidly. They display an instantaneous force Fmax which can exceed 30 times the individual’s body weight (Patek et al. 2006). _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


When the mandibles are closed and immobile, the kinetic force becomes null, therefore Fmax is qualitatively different from Fout and deserves a specific measure for some organisms like trap-jaw ants. The maximal instantaneous mandible force Fmax (N 10-9) can be measured on living organisms when they close their mandibles (Patek et al. 2006; Spagna et al. 2008) following: Fmax =1/3 M R αmax where M is the jaw mass (mg), R is the distance from the centre of rotation to the jaw terminus (mm), and αmax is the maximal angular acceleration of the mandibles (radian s–2) (Fig. 2). Axis of rotation

M

R Fmax

Acceleration αmax

Fig. 2: Mandible mass acceleration model based on the example of the mandible of the trap-jaw ant (Odontomachus bauri) (Patek et al. 2006) showing the instantaneous force Fmax generated by the jaw mass M (mg), the distance from the axis of rotation to the jaw terminus, R (mm), and the maximal angular acceleration of the mandibles, αmax (radian s–2).

Additional notes The adductor muscles‘ volume can also be quantified measured by measuring the volume displacement of a fluid where the muscles have been immerged (Douglass & Wcislo 2010). Nonetheless this technique is generally out of reach for ecological studies which need to compare dozens or hundreds of samples. The volume of the adductor muscle of the mouth-parts and can be further precisely measured using 3D imaging following preparation (Gronenberg et al. 1997) and examination under scanning electron microscopy, while the muscle volume estimated with image analysis software (e.g. http://www.jmicrovision.com/). 3D imaging also allow to measure the angles of attachment of each muscle fibre to the apodeme (Paul & Gronenberg 1999). This leads to an estimation of the biting force of the adductor muscle per unit volume, and hence to an absolute measure of Fout, instead of a relative measure as in the lever dynamics model presented above. References Clissold, F.J. (2007) The biomechanics of chewing and plant fracture: mechanisms and implications. Advances in insect physiology, 34, 317-372. Deraison, H., Badenhausser, I., Börger, L. & Gross, N. (2015) Herbivore effect traits and their impact on plant community biomass: an experimental test using grasshoppers. Functional Ecology, 29, 650–661. Douglass, J.K. & Wcislo, W.T. (2010) An inexpensive and portable microvolumeter for rapid evaluation of biological samples. Biotechniques, 49, 566-572. Holzman, R., Collar, D.C., Price, S.A., Hulsey, C.D., Thomson, R.C. & Wainwright, P.C. (2012) Biomechanical trade-offs bias rates of evolution in the feeding apparatus of fishes. Proceedings of the Royal Society B: Biological Sciences, 279, 1287–1292. Gentry, G.L. & Dyer, L.A. (2002) On the conditional, nature of neotropical caterpillar defenses against their natural enemies. Ecology, 83, 3108-3119. Gronenberg, W., Paul, J., Just, S. & Hölldobler, B. (1997) Mandible muscle fibers in ants: fast or powerful? Cell and Tissue Research, 289, 347-361. Ibanez, S., Lavorel, S., Puijalon, S. & Moretti, M. (2013) Herbivory mediated by coupling between biomechanical traits of plants and grasshoppers. Functional Ecology, 27, 479-489. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


Konuma, J. & Chiba, S. (2007) Trade-Offs between Force and Fit: Extreme Morphologies Associated with Feeding Behavior in Carabid Beetles. The American Naturalist, 170, 90-100. Meyers, J.J. & Irschick, D.J. (2015) Does whole-organism performance constrain resource use? A community test with desert lizards. Biological Journal of the Linnean Society, 115, 859-868. Patek, S.N., Baio, J.E., Fisher, B.L. & Suarez, A.V. (2006) Multifunctionality and mechanical origins: Ballistic jaw propulsion in trap-jaw ants. Proceedings of the National Academy of Sciences, 103, 12787-12792. Paul, J. & Gronenberg, W. (1999) Optimizing force and velocity: Mandible muscle fibre attachments in ants. Journal of Experimental Biology, 202, 797-808. Peeters, P.J., Sanson, G. & Read, J. (2007) Leaf biomechanical properties and the densities of herbivorous insect guilds. Functional Ecology, 21, 246-255. Umbers, K.D.L., Tatarnic, N.J., Holwell, G.I. & Herberstein, M.E. (2012) Ferocious Fighting between Male Grasshoppers PLoS ONE, 7, e49600 Santamaría, L. & Rodríguez-Gironés, M.A. (2007) Linkage Rules for Plant–Pollinator Networks: Trait Complementarity or Exploitation Barriers? PLoS Biol, 5, e31. Spagna, J.C., Vakis, A.I., Schmidt, C.A., Patek, S.N., Zhang, X., Tsutsui, N.D. et al. (2008) Phylogeny, scaling, and the generation of extreme forces in trap-jaw ants. Journal of Experimental Biology, 211, 2358-2368. Westneat, M.W. (2003) A biomechanical model for analysis of muscle force, power output and lower jaw motion in fishes. Journal of Theoretical Biology, 223, 269-281. Wheater, C.P. & Evans, M.E.G. (1989) The mandibular forces and pressures of some predacious Coleoptera. Journal of Insect Physiology, 35, 815-820.

4. LIFE HISTORY 4.1. ONTOGENY Definition and relevance Ontogeny (or morphogenesis) is the developmental history of an organism during its lifetime. It is defined here as the development of an organism from egg to the organism’s mature form. Ontogeny is of key importance as ecological relationships change over the life time of an organism, and result in so-called ontogenetic niche shifts. For instance, resistance to environmental stressors shifts across an organism’s life history (Bowler & Terblanche 2008) including phenotypic plasticity in growth and development time (Stillwell et al. 2010). In herbivores, especially in insects with a full metamorphosis, ontogenetic diet shift is rather common (Jensen et al. 2006), while in predators immature stages often differ in prey choice from adults (Luff 1974) or are eaten by adults (Polis, Myers & Holt 1989). On a fine scale, ecosystems may not include the environmental conditions necessary for a specific life stage of an organism to develop, resulting in ontogenetic microhabitat shifts (Cherrill & Brown 1992). Ontogeny has been shown to affect species interactions in size-structured populations (Werner & Gilliam 1984) and trophic position and food web stability (Woodward & Hildrew 2002). What and how to measure There are two aspects that describe developmental history: the type of ontogeny and the number of specific ontogenetic stages. The first aspect categorizes species as belonging to one of three types of developmental history depending on the type of metamorphosis. The latter aspect estimates the number of instars from field or laboratory observations and notes the types of developmental stages. Information on the type of development and number of developmental stages can also be found in handbooks or specific literature.



Pre-treatment Animals should be described according to the standardisation protocol. How to record development type? - Ametabolism (or no apparent metamorphosis): The developmental mode of invertebrates that include two distinct life stages: egg and nymphs (or juveniles) that morphologically closely resemble the adult form. Nymphs lack reproductive organs. Ontogenetic niches are similar or overlapping in successive life stages. - Hemimetabolism (or incomplete metamorphosis): The developmental mode of a group of insects that includes three distinct life stages: embryo or egg, nymph and adult or imago. A nymph differs morphologically from the adult stage because it lacks reproductive organs and wings are absent. Nymphs are often rather similar in appearance to the mature stage and gradually develop into adults. A pupal stage is absent. In most cases ontogenetic niches are overlapping in successive life stages. - Holometabolism (or complete metamorphosis): The developmental mode of a group of insects that include four distinct life stages: embryo or eggs, larvae, pupa and adult or imago. Larvae are distinctively different form adults and often live in a different microhabitat. Distinct life stages exhibit a strong ontogenetic niche shift. How to record type and number of developmental stages? - Egg or embryo: The first developmental stage during metamorphosis. In terrestrial isopods manca’s refer to embryo’s. - Instar: the developmental stage after egg or embryo in hemimetabolic insects (called nymph), holometabolic insects (called larvae) or other groups of invertebrates. The number of instars varies between species. - Pupa: The developmental stage between larvae and imago in holometabolic insects. In some insects, such as lepidopterans the pupa is enclosed by a cocoon, which serves as a protective coverage. In other species the pupa remains within the exoskeleton of the final immature instar, which is called a puparium. - Adult or imago: The last developmental stage during metamorphosis. In insects no more moulting occurs, and wings are functional in winged species. Adults are sexually mature. In some taxa, such as Isopoda, moulting continues after sexual maturity. In Collembola each moult a growth phase alternates with a reproductive phase (Hopkin 1997). - Number of instars. An instar denotes a developmental stage, from hatching of the egg to reaching adulthood, during metamorphosis until sexual maturity is reached. The number of instars is the sum of all developmental stages between egg and adult. A moulting event defines the start of a new developmental stage. Additional notes In some arthropod species a delay in development in response to regularly and recurring periods of adverse environmental conditions occurs, known as diapause (Lees 1955; Danks 1987). The morphological development of species ceases, and in some cases moulting to a specific diapauses stage takes place. Diapause can occur during any stage of development. We recommend reporting if diapause occurs for studied species and in which developmental stage and season it occurs (see also the protocol on Annual activity rhythm). In some insect groups, specifically in social insects, such as termites and many hymenopterans, it may be necessary to differentiate between adult castes, such as queens, males and workers, which can differ in developmental history. In some insect groups species are viviparous, i.e. the embryo develops inside the body of the female, eventually leading to live birth. In these cases an egg stage is missing. We recommend to publish if vivipary occurs in the species of study.



References Bowler, K. & Terblanche, J.S. (2008) Insect thermal tolerance: what is the role of ontogeny, ageing and senescence? Biological Reviews, 83, 339-355. Cherrill, A.J. & Brown, V.K. (1992) Ontogenetic changes in the micro-habitat preferences of Decticus verrucivorus (Orthoptera: Tettigoniidae) at the edge of its range. Ecography, 15, 37-44. Danks, H.V. (1987) Insect dormancy: An ecological perspective. Biological Survey of Canada, Ottawa Monograph. Entomological Society of Canada. Hopkin, S.P. (1997) Biology of the Springtails (Insecta: Collembola). Oxford University Press. Jensen, T.C., Leinaas, H.P. & Hessen, D.O. (2006) Age-dependent shift in response to food element composition in Collembola: contrasting effects of dietary nitrogen. Oecologia, 149, 583-592. Lees, A.D. (1955) The Physiology of Diapause in Arthropods. Cambridge University Press. Luff, M.L. (1974) Adult and larval feeding habits of Pterostichus madidus (F.) (Coleoptera, carabidae). Journal of Natural History, 8, 403-409. Polis, G.A., Myers, C.A. & Holt, R.D. (1989) The ecology and evolution of intraguild predation. Annual Review of Ecology and Systematics, 20, 297-330. Stillwell, R.C., Blanckenhorn, W.U., Teder, T., Davidowitz, G. & Fox, C.W. (2010) Sex differences in phenotypic plasticity affect variation in sexual size dimorphism in insects: From physiology to evolution. Annual Reviews, 55, 227-245. Werner, E.E. & Gilliam, E.F. (1984) The ontogenetic niche and species interactions in size-structured populations. Annual Review of Ecology and Systematics, 15, 393-425. Woodward, G. & Hildrew, A.G. (2002) Body-size determinants of niche overlap and intraguild predation within complex food web. Journal of Animal Ecology, 71, 1063-1074.

4.2. CLUTCH SIZE Definition and relevance Clutch size is defined as the number of offspring produced in discrete groups or clutches in a single reproductive event. If clutch size is larger than one, offspring are placed together in a cluster. Clutch size differs tremendously among species: from a single offspring produced at a time (e.g. in some parasitic wasps) up to hundreds of eggs laid simultaneously (e.g. in some snails). Clutch size is influenced by a complex of ecological factors such as predation pressure on eggs and juveniles, quality of the habitat, and population density (Godfray, Partridge & Harvey 1991). Optimal clutch size is certainly not always the same as maximum clutch size, as large clutches can suffer from competition between siblings leading to slow growth and result in weaker offspring. Most importantly, clutch size is not independent of other life history traits. The trade-off between egg size and number of eggs is particularly common, often resulting from the allocation of limited nutrients (Smith & Fretwell 1974; Roff 2002). What and how to measure Measuring clutch size basically consists of counting the number of eggs or juveniles in a clutch laid by a single female. A clutch may consist of a cluster of uncovered eggs (e.g. butterfly on leafs), eggs covered with sand or fine organic soil particles (some soil fauna groups) or eggs secluded in a silk envelope (success as cocoons in most spiders) or a surrounded by a protein foam (mantis or cockroach oothecae).



Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. We recommend choosing similar conditions as those during the reproductive season in the field for the specific species in order to enhance the chances of reproduction in the laboratory and to ensure ecological relevance. How to measure clutch size? Females should be kept individually and monitored daily for egg laying or juvenile production. For species that lay eggs in or on a given substrate, e.g. soil, wood, bark, dung, or stems the specific lay substrate should be presented. Also for parasitoid species sufficient and suitable hosts should be offered. Clutch size should be counted as soon as possible after laying, to avoid underestimating of clutch size through egg mortality. For endoparasitoids, hosts will need to be dissected in order to count the number of eggs laid. When reporting clutch size, it is important to specify the time and space limits that were used to delimit the clutch, e.g. all eggs laid within a single host, or eggs deposited in a single location without locomotion of the female. These specifics will vary for each species. Additional notes In eusocial species, only the queen reproduces and it is impossible to isolate her. Observations on clutch size can be made by bringing the colonies into the laboratory in glass nests. If one is unable to get the species of choice to reproduce in the laboratory, clutch size can also be measured in the field under specific conditions. Most importantly, the researcher needs to be able to attribute each clutch to a single female, and clutch reduction by predation should be excluded. References Godfray, H.C.J., Partridge, L. & Harvey P.H. (1991) Clutch Size. Annual Review of Ecology and Systematics, 22, 409-429. Roff, D. (2002) Life History Evolution. Sinauer Associates, Inc, Sunderland, MA. Smith, C.C. & Fretwell, S.D. (1974) Optimal balance between size and number of offspring. American Naturalist, 108, 499-506.

4.3. EGG SIZE Definition and relevance Egg size is a physical measurement of the egg and can be expressed by mass or volume of an egg. Egg size is a general predictor of the maternal investment in reproduction, and determines hatching success (Fox & Czesak 2000; Fischer, Brakefield & Zwaan 2003), hatchling size (Fox 1994), and resistance to desiccation (Fischer et al. 2006). Egg size varies enormously between species, with larger-bodied species generally laying larger eggs (Fox & Czesak 2000). Egg size has been found to trade-off with the number of eggs produced (Smith & Fretwell 1974; Roff 2002). Within species variation in egg size is strongly dependent on age (Fox & Czesak 2000) and mating history (Hoffer, Ellers & Koene 2010) and on environmental conditions such as temperature (Ernsting & Isaaks 1997; Fischer, Brakefield & Zwaan 2003), food availability (Bauerfeind & Fischer 2005) and, in herbivores, host plant quality (Braby 1994; Mizumoto & Nakasuji 2007). What and how to measure There are two aspects that can be measured of egg size: egg mass and egg volume. Differences in egg size can be caused by changes in egg water content or the quantity of resources the mother invests. Therefore, when measuring egg size it is important to measure both egg dry mass and egg volume. Egg mass is the dry weight of _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


an average egg of a species, whereas egg volume is the three dimensional space, consisting of width length and height. The absolute egg size is often depending on body size. For a meaningful comparison of egg size across terrestrial invertebrates, egg size should be compared relative to the size of the organisms. We recommend to publish body size measurement together with data on egg size. Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. Preferably, collected females should be of a standard age. How to measure egg volume? To get a reliable estimate of egg volume, at least 5-10 randomly chosen eggs should be collected per clutch or per female. Eggs can best be photographed using a digital camera connected to a stereomicroscope, as direct measurement with an ocular micrometer is less precise and therefore only to be used when no digital camera is available. Digital photographs can be analysed using public domain ImageJ software. For spherical eggs it suffices to measure the diameter (d) of the egg and calculate volume according to the equation V = (πd3)/6. When eggs are of an ellipsoid shape, volume can often be approximated as two joint cones according to the equation V = 2/3π*(L/2)*((w/2)2), where L is egg length and w is egg width. How to measure egg dry mass? The number of eggs necessary to get a reliable estimate of egg mass depends strongly on the weight of the eggs. With individual egg dry weight in the range of 3-5 μg, we recommend to pool at least 20 eggs. The eggs should be collected in small pre-weighed aluminium foil cups and placed in a desiccator until completely dry before taking dry weight measurements. For larger eggs one can obtain individual dry weight measurement, following the same procedure as described above. Additional notes In species with a marsupium (e.g. isopods) or that have viviparous reproduction (e.g. tsetse fly) eggs are not oviposited. In these species an alternative measure is to dissect gravid females and measure egg size while the eggs are still inside the reproductive organs at a predetermined developmental stage. In some species eggs may change shape or size shortly after oviposition, as is the case in parasitoids with hydropic eggs that swell up after oviposition. In these species, egg size can better be measured through dissection. A female should be placed in a drop of Ringer’s solution (Cold Spring Harb Protoc 2007; doi:10.1101/pdb.rec10919 ) and dissected under a stereoscope. The ovaries should be removed and fully provisioned eggs collected, photographed, and weighed. References Bauerfeind, S.S. & Fischer, K. (2005) Effects of food stress and density in different life stages on reproduction in a butterfly. Oikos, 111, 514-524. Braby, M.F. (1994) The significance of egg size variation in butterflies in relation to host plant quality. Oikos, 71, 119-129. Ernsting, G. & Isaaks, J.A. (1997) Effects of temperature and season on egg size, hatchling size and adult size in Notiophilus biguttatus. Ecological Entomology, 22, 32-40. Fischer, K., Brakefield, P.M. & Zwaan, B.J. (2003) Plasticity in butterfly egg size: why larger offspring at lower temperatures? Ecology, 84, 3138-3147. Fischer, K., Bot, A.N.M., Brakefield, P.M. & Zwaan, B.J. (2006) Do mothers producing large offspring have to sacrifice fecundity? Journal of Evolutionary Biology, 19, 380-391. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


Fox, C.W. (1994) The influence of egg size on offspring performance in the seed beetle Callosobruchus maculatus. Oikos, 71, 321-325. Fox, C.W. & Czesak M.E. (2000) Evolutionary ecology of progeny size in arthropods. Annual Review of Entomology, 45, 341-369. Hoffer, J.N.A., Ellers, J. & Koene, J.M. (2010) Costs of receipt and donation of ejaculates in a simultaneous hermaphrodite. BMC Evolutionary Biology, 10, 393. Mizumoto, M. & Nakasuji, F. (2007) Egg size manipulation in the migrant skipper, Parnara guttata guttata (Lepidoptera: Hesperiidae), in response to different host plants. Population Ecology, 49, 135-140. Roff, D. (2002) Life History Evolution. Sinauer Associates, Inc, Sunderland, MA. Smith, C.C. & Fretwell, S.D. (1974) Optimal balance between size and number of offspring. American Naturalist, 108, 499-506.

4.4. LIFE SPAN Definition and relevance Life span is defined as the amount of time an adult individual actually lives, encompassing the entire period from emergence from last instar until death. Life span critically depends on environmental conditions such as temperature with higher temperatures shortening life span due to the effect of temperature on metabolic rate (Gillooly et al. 2001; Brown et al. 2004). Life span is known to differ between sexes in many species (Bonduriansky et al. 2008). In addition, life span is known to be negatively correlated with reproductive investment due to the trade-off between reproduction and survival (Chippindale et al. 1993; Ellers & van Alphen 1997). Survival is one of the main components of Darwinian fitness, as a long life span can increase the probability of producing viable offspring. What and how to measure There are two approaches to estimate life span under laboratory conditions: measurement of longevity and measurement of starvation resistance. Longevity is the average potential life span under optimal conditions, while starvation resistance measures the time until death in the absence of food. Both of these are only proxies for life span in the field, as various sources of mortality, such as predation or pathogens can significantly reduce realized life span in the field compared to the potential life span measured in the laboratory (Christe, Keller & Roulin 2006). Animals should be maintained at a chosen temperature (regime) for the entire duration of the life span experiment and we recommend publishing experimental conditions together with values for life span. Pre-treatment Animals should be described and acclimatized according to the standardisation protocol, as carry over effects from larvae to adults could influence adult life span. Individuals should be collected directly after emergence from last instar or immediately after reaching the adult stage. Ideally, body size should be measured as some studies find that larger individuals live longer (Ellers, van Alphen & Sevenster 1998; Taylor, Anderson & Peckarsky 1998). How to measure longevity? To measure longevity, animals should be provided ad libitum with water and food for the entire duration of the experiment. Usually this means that water and food are replaced frequently enough to ensure that the animal never experience food shortage or a reduction in food quality. Individual animals should preferably be maintained in separate vials, corresponding to the body size of the animals. Interaction with conspecifics can potentially reduce longevity. Animals should be regularly monitored to determine if they are still alive. Typically, _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


the frequency of monitoring depends on the expected life span; the shorter the life span the higher the required frequency of monitoring. It can be difficult to establish if the animal is still alive, especially in the final stages of life. If the animal does not show any visible activity by disturbing them gently, e.g. after taping the vial or gently touching with a soft brush it can be considered dead. Longevity is most likely to be measured in days, although it may be necessary to revise this downwards for certain groups (e.g. Ephemeroptera). How to measure starvation resistance? Starvation resistance is expressed in days and measured in a similar set-up as life span, but no food is provided. However, access to water is necessary to avoid effects of desiccation. Note that starvation resistance is usually much shorter than life span and therefore the frequency of monitoring should be higher, in some cases even in terms of hours rather than days. Additional notes In case there are different castes within a species, longevity should be reported separately for each caste. Overestimates of longevity may be produced for certain insect groups. For example, large winged insects (e.g. Odonata) that cannot fly during the experiment because of containment will have a reduced metabolic rate, which results in an increase in longevity. Another complication is that reproduction cannot be halted for parthenogenetic invertebrates. Reproduction and longevity are known to trade-off, which may result in underestimation of longevity in parthenogenetic species when compared to sexual reproducing species with haltered reproduction. For eggs or juvenile stages, survival probability is a more appropriate measure for life span, because the duration of these life stages is usually determined by ontogeny. For larger invertebrates, such as Tarantula spiders, dragonflies, or field crickets that can be marked, estimates of life span in the field are possible (Rodríguez-Muñoz et al. 2010). References Bonduriansky, R., Maklakov, A., Zajitschek, F. & Brooks, R. (2008) Sexual selection, sexual conflict and the evolution of ageing and life span. Functional Ecology, 22, 443-453 Brown, J.H., Gillooly, J.F., Allen, A.P., Savage, V.M. & West, G.B. (2004) Toward a metabolic theory of ecology. Ecology, 85, 1771-1789. Chippindale, A.K., Leroi, A.M., Kim, S.B. & Rose, M.R. (1993) Phenotypic plasticity and selection in Drosophila life-history evolution .1. Nutrition and the cost of reproduction. Journal of Evolutionary Biology, 6, 171-193. Christe, P., Keller, L. & Roulin, A. (2006) The predation cost of being a male: implications for sex-specific rates of ageing. Oikos, 114, 381-384. Ellers, J., van Alphen, J.J.M. & Sevenster, J.G. (1998) A field study of the size-fitness relationships in the solitary parasitoid Asobara tabida. Journal of Animal Ecology, 67, 318-324. Ellers, J. & van Alphen, J.J.M. (1997) Life history evolution in Asobara tabida: Plasticity in the allocation of fat reserves to survival and reproduction. Journal of Evolutionary Biology, 10, 771-785. Gillooly, J.F., Brown, J.H., West, G.B., Savage, V.M. & Charnov, E.L. (2001) Effects of size and temperature on metabolic rate. Science, 293, 2248-2251. Rodríguez- Muñoz, R., Bretman, A., Slate, J., Walling, C.A. & Tregenza, T. (2010) Natural and sexual selection in a wild insect population. Science, 328, 1269-1272. Taylor, B.W., Anderson, C.Z. & Peckarsky, B.L. (1998) Effects of size at metamorphosis on stonefly fecundity, longevity, and reproductive success. Oecologia, 114, 494-502.



4.5. AGE AT MATURITY Definition and relevance Age at maturity is the age at which an individual can reproduce expressed as units of time from egg laying or birth up to the onset of adulthood. Life history theory makes a number of predictions about the selective pressures on age at maturity. For instance, age at maturity shows variation across latitude and altitude as a response to differences in thermal regimes (Folguera et al. 2008). In growing populations early maturity is favored in order to maximize the number of offspring at early ages (Lewontin 1965). Early maturation also gives individuals a competitive advantage, for example in species that have to rely on ephemeral resources (Prasad et al. 2001) or in species subjected to high intraguild predation (Gegner et al. 2015). Selection for early maturity can also be found when seasonality imposes time constraints on development or when predation during the juvenile period is high (Blanckenhorn 1998), while delayed maturity may be favoured if reproductive success depends on size or status of the adult (Rowe & Ludwig 1991). What and how to measure Age at maturity is measured on the offspring of field-collected individuals. Adults should be allowed to reproduce in the laboratory under standardized conditions, as a variety of environmental factors, such as temperature, food availability and density of conspecifics or predators can affect the afterlife effects of parents on their offspring traits. Measuring age of maturity of offspring under favourable conditions in the laboratory will produce a minimum estimate compared to age at maturity in the field. Pre-treatment Animals should be collected from the field before the reproductive season, and described and acclimatized according to the standardisation protocol prior to reproduction. We recommend choosing similar conditions as those during the reproductive season in the field for the specific species in order to enhance the chances of reproduction in the laboratory and to ensure ecological relevance. Many species need specific environmental conditions and/or feeding to ensure the maturation of gonads and subsequent reproduction. We recommend publishing the selected standardized environmental conditions together with values on age at maturity. How to measure age at maturity? Individuals should be acclimatized according to the standardisation protocol. The offspring of field collected individuals should be provided with water and food ad libitum for the entire duration of the experiment. Offspring should be monitored regularly to determine if the adult stage has been reached (see Ontogeny protocol for the description of adult stage). Typically, the frequency of monitoring depends on the length of the development time: a faster development requires a higher frequency of monitoring, for example every hour or every day. Usually age at maturity is expressed in number of days, but this may be months or years in case of a very long life cycle. Additional notes If age at maturity is used as a proxy for age at first reproduction, then it must be taken into account that some species need to fulfil addition requirements before reproduction can take place, e.g. mating, feeding, hibernation et cetera. References Blanckenhorn, W.U. (1998) Adaptive phenotypic plasticity in growth, development, and body size in the yellow dung fly. Evolution, 52, 1394-1407. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


Folguera, G., Ceballos, S., Spezzi, L, Fanara, J.J. & Hasson, E. (2008) Clinal variation in developmental time and viability, and the response to thermal treatments in two species of Drosophila. Biological Journal of the Linnean Society, 95, 233-245. Gegner, T., Otti, O., Tragust, S. & Feldhaar H. (2015) Do microsporidia function as "biological weapon" for Harmonia axyridis under natural conditions? Insect Science, 22, 353-359. Lewontin, R.C. (1965) Selection for colonizing ability. Genetics of colonizing species (eds H. Baker & G.L. Stebbins), Academic Press, New York. Prasad, N.G., Shakarad, M., Anitha, D., Rajamani, M. & Joshi, A. (2001) Correlated responses to selection for faster development and early reproduction in Drosophila : the evolution of larval traits. Evolution, 55, 1363-1372. Rowe, L. & Ludwig, D. (1991) Size and timing of metamorphosis in complex life cycles: time constraints and variation. Ecology, 72, 413-427.

4.6. PARITY Definition and relevance Parity refers to the number of times a female lays eggs or gives birth and describes if reproduction takes place in a single life time event or is partitioned among multiple events (Cole 1954). The number of reproductive events is usually a species characteristic, but there are several species in which alternative modes of parity coexist (Meunier et al. 2012). The number of reproductive events is variable within clades of species (Fritz, Stamp & Halverson 1982; Siepel 1994). The spreading of reproductive events over a life time has fitness consequences that are related to the trade-off between current and future reproduction (Meunier et al. 2012). An association exists between the mode of parity and parental care in nesting invertebrates (Tallamy & Brown 1999; Trumbo 2013), suggesting that parity determines the evolution of social behaviour. What and how to measure Parity is a categorical trait which is usually assessed through field observations. Parity can be recorded in the laboratory if the category of parity is unknown for a specific species. Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. For actual measurement of parity we recommend that animals are collected from the field prior to the reproductive season. Females should already have mated or immature individuals (or eggs) should be collected. In the latter case, after reaching the mature stage females should get the opportunity to mate with (multiple) males in captivity. Laboratory conditions should be chosen similar to those during the reproductive season in the field for the specific species in order to enhance the chances of reproduction in the laboratory and to ensure ecological relevance. We recommend publishing the experimental conditions together with parity measurements. How to record parity? Animals can be divided over two categories of parity, i.e. semelparity and iteroparity. Here we use the temporal pattern of reproduction to define the two categories following Fritz, Stamp, & Halverson (1982). - Semelparity: Species with a single reproductive event, even though this may stretch out over several days, after which the females die. Semelparous animals are, for instance, mayflies as well as several species of beetles, spiders, and butterflies. - Iteroparity: Species with multiple reproductive events that are separated by non-reproductive periods during which e.g. renewed mating takes place, new eggs are matured, parental care is given to the young, or the _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


animal is searching for a new patch for reproduction. Iteroparity is the predominant reproductive strategy in animals. The method we propose to categorize this trait is a clear compromise between rapid assessment and level of precision. This method requires direct observation of reproductive events and can easily be combined with the protocols for other reproductive traits proposed in the handbook, such as clutch size or reproductive mode. Mated females should be kept in the laboratory under conditions that allow reproduction and monitored daily to record reproductive events for an extended period of time. The duration of the period of observation may vary for different species and requires some prior knowledge on the reproductive biology of the species under the given environmental conditions. If the first reproductive event has been observed, but the females do not die, a subset of the females can be dissected to check the status of the ovaries. If new eggs/embryos are in the process of maturation, this provides additional indirect evidence for iteroparity. Additional notes Although semelparity and iteroparity are considered to be separate life-history strategies, there are several cases in which the distinction is challenged. For instance, some semelparous species can be reproductively active for a longer period of time before dying. In some species females need to mate again after the first reproductive event before being able to reproduce again (e.g. in Collembola). In this case it is important to provide a number of males to the female. In social insects reproduction includes the production of workers as well as the production of new fertile individuals (males or new queens). When describing parity in social insects one should distinguish between the two castes. References Cole, L. 1954. The population consequences of life history phenomena. The Quarterly Review of Biology, 29, 103-137. Fritz, R.S., Stamp, N.E. & Halverson, T.G. (1982) Iteroparity and semelparity in insects. American Naturalist, 120, 264-268. Meunier, J., Wong, J.W.Y., Gómez, Y., Kuttler, S., Röllin, L., Stucki,D. & Kölliker, M. (2012) One clutch or two clutches? Fitness correlates of coexisting alternative female life-histories in the European earwig. Evolutionary Ecology, 26, 669-682. Siepel, H. (1994) Life-history tactics of soil microarthropods. Biology and Fertility of Soils, 18, 263-278 Tallamy, D.W. & Brown, W.P. (1999) Semelparity and the evolution of maternal care in insects. Animal Behaviour, 57, 727-730 Trumbo, S.T. (2013) Maternal care, iteroparity and the evolution of social behavior. A critique of the semelparity hypothesis. Evolutionary Biology, 40, 613-626.

4.7. REPRODUCTION MODE Definition and relevance Reproduction mode is the biological process by which new offspring are produced. The mode of reproduction is of ecological importance because it influences population dynamics. For instance, the population growth rate of asexual or parthenogenetic species can be twice as high when compared to sexual species, a function of the 'twofold cost of sex' (Maynard Smith 1978), which may determine the speed of recovery of species after a disturbance (Lindberg & Bengtsson 2005). Moreover, sexual and parthenogenetic species differ in sensitivity toward fluctuating habitat conditions (Domes, Scheu & Maraun 2007). In sexual populations, sexual dimorphism _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


in morphology, life history and behaviour may increase intraspecific variation (Nylin & Gotthard 1998; Teder & Tammaru 2005; Stillwell et al. 2010; Le Lann et al. 2011). What and how to measure Mode of reproduction is a categorical trait. The easiest way to infer the reproductive mode of a species is through direct field observation of the number of males and females in a population. Since asexual reproduction produces only females (except for haplodiploids, see under special cases), the presence of males in a population is strong indirect evidence for sexual reproduction. If the sex ratio is zero, i.e. only females occur, this may indicate asexual reproduction. However, species can be polymorphic for reproductive mode, i.e. only part of the population reproduces sexually (for instance, aphids), which requires observations on individual females to determine mode of reproduction. Similarly, in some species asexual individuals are more common in marginal habitat or at range margins (Haag & Ebert 2004). A second method is to rear females from eggs in the laboratory and separate them before they can mate. The conditions under which reproduction is favoured differ per species, and in some species asexual reproduction occurs only after a prolonged non-reproductive period, so experiments should be continued for sufficient time. If reproduction from unmated females is observed this is conclusive evidence for (facultative) parthenogenesis. Pre-treatment A pre-treatment is not necessary. How to record reproduction mode? There are two categories of mode of reproduction: - Sexual: Sexual reproduction involves the fusion of gametes from two individuals, a female and a male. - Asexual (or parthenogenesis or autotoky): Asexual reproduction involves a single female parent. Asexual reproduction also includes self-fertilization in e.g. hermaphroditic molluscs. Additional notes Aphids can reproduce asexually (i.e. anholocycly - permanent parthenogenesis) or sexually (i.e. holocycly parthenogenesis is broken by a sexual phase). These reproductive modes can occur within the same species and have been shown to have profound effects on their migration (Bell et al. 2015). Therefore we recommend to sample and observe multiple populations of species with these multiple reproduction modes in various seasons, and publish this information with the information on reproduction mode. References Bell, J.R., Alderson, L., Izera, D., Kruger, T., Parker, S., Pickup et al. (2015) Long-term phenological trends, species accumulation rates, aphid traits and climate: five decades of change in migrating aphids. Journal of Animal Ecology, 84, 21-34. Domes, K., Scheu, S. & Maraun, M. (2007) Resources and sex: Soil re-colonization by sexual and partheogenetic oribatid mites. Pedobiologia, 51, 1-11. Haag, C.R. & Ebert, D. (2004) A new hypothesis to explain geographic parthenogenesis. Annales Zoologici Fennici, 41, 539-544. Le Lann, C., Roux, O., Serain, N., Van Alphen, J.J.M., Vernon, P., & Van Baaren, J. (2011) Thermal tolerance of sympatric hymenopteran parasitoid species: does it match seasonal activity? Physiological Entomology, 36, 21-28. Lindberg, N. & Bengtsson, J. (2005) Population responses of oribatid mites and collembolans after drought. Applied Soil Ecology, 28, 163-174. Maynard Smith, J. (1978) The Evolution of Sex. Cambridge University Press. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


Nylin, S. & Gotthard, K. (1998) Plasticity in life history traits. Annual Review of Entomology, 43, 63-83. Stillwell, R.C., Blanckenhorn, W.U., Teder, T., Davidowitz, G. & Fox, C.W. (2010) Sex differences in phenotypic plasticity affect variation in sexual size dimorphism in insects: From physiology to evolution. Annual Review of Entomology, 55, 227-245. Teder, T. & Tammaru, T. (2005) Sexual size dimorphism within species increases with body size in insects. Oikos, 108, 321-334.

4.8. VOLTINISM Definition and relevance Voltinism describes the number of generations (or broods) an organism completes in a unit of time, usually within a single year (Danks 2007). Voltinism and investment into each generation determines population growth or adaptation to local conditions (e.g., Steinbauer et al. 2004), under a trade-off with reproductive effort (Kivelä et al. 2009). Voltinism is under environmental and genetic control. The expression of voltinism mostly depends on latitude or altitude, as this determines photoperiod and local climatic conditions, especially temperature (e.g., Scoble 1995). Species in warm habitats often have the capacity to produce more than one generation in a year, whereas those in cooler habitats often require one year or more to complete a single generation (Bentz & Powell 2014). Populations with wide geographical ranges can differ in voltinism across their range, with more generations at lower latitudes/altitudes than at higher latitudes/altitudes (Tauber et al. 1986; Välimäki et al. 2008). While some species/populations are completely fixed to a specific voltinism, some species/populations are relatively undetermined, and can produced different number of generations depending on the yearly annual conditions (e.g., Altermatt 2010a,b). Voltinism can also change depending on diet, with an increase in the number of generations with higher food quality (Hunter & McNeil 1997; Cizek, Fric & Konvicka 2006; Altermatt 2010a) and seasonal productivity, with an increase in the number and size of generations in particular years with high productivity (see Kivelä et al. 2009; Gordo, Sanz & Lobo 2010). Climate change can induce adjustment of voltinism (Porter, Parry & Carter 1991; Yamamura & Kiritani 1998; Altermatt 2010b), with can for example impact trophic interactions through phenological mismatches (e.g., Altermatt 2010b), or, in case of pest species, increase pest-outbreak and infestation (Berg & Ellers 2010; Knell & Thackeray 2016). Overall, the production of multiple generations per year involves trade-off between direct development and diapause. If the dormant stage cannot be reached in time, or if environmental conditions become adverse as the season proceeds, individuals may not survive (van Asch & Visser 2007). What and how to measure There are two aspects to voltinism: 1) the number of generations within a unit of time, typically one year, and 2) the distribution of the generations over a unit of time. The first aspect categorizes species as belonging to one of four types of voltinism, i.e., uni-voltine (one generation per year), bi-voltine (two generations per year), multivoltine (more than two generations per year), and semi-voltine (organism that take more than one year to complete its life cycle). The latter aspect estimates the length and frequency of each generation during the year. Both can either be assessed from museum collections, field or laboratory observations, or data can be also found in handbooks or specific literature. Importantly, data on voltinism for a given species/populations may change within a few decades due to adaptation to environmental conditions (Altermatt 2010b), thus it is important that the data used for assigning the type of voltinism reflects the right spatial and temporal scale.



Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. How to measure voltinism? Measuring voltinism basically consists in monitoring the activity of the individuals and thereafter examining the rate at which adults emerge over a year. Since no good protocol is available in the literature on how to measure voltinism under standardized laboratory conditions across different taxa, and since it is always an interplay with the populations genetic predisposition and the local environmental conditions, voltinism is more often measured in the field based on the observation of the activity of individuals from distinct populations. Typically 50% of adult emergence is used, although for some groups that are fecund and have overlapping generations (e.g. aphids), have complex life cycles (e.g. gall wasps), or have more than one year to complete its life cycle (e.g., several xylophagous beetles), these metrics can be difficult to estimate (Altermatt 2010). For robust estimates, voltinism is thus best measured over at least two or more years per location. In some groups, the effect of latitude and altitude on voltinism is very strong and care must be taken to estimate well the number of generations, particularly when these overlap. Additional notes Field-based protocols to measure voltinism often use traps but these may produce biased data due to differences in activity of adult individuals and species over their individual adult lifespan rather than adult emergence, especially when using passive survey methods, such as pitfall traps, interception traps or pheromone traps. Trapbased data may not necessarily indicate that two or more peaks are related to two or more generations, as there are often differences in life cycle longevity between generations and between the sexes. Applying more quantitative sampling methods, such as vacuum sampling by D-Vac and emergence traps for soil- or wooddwelling organisms are often more reliable. Historical records and observations by non-specialists and common citizens have already been used to recover the voltinism patterns of species with particularly long and/or erratic life cycles, such as cicadas (e.g. Cooley et al. 2013). In case of laboratory observations are necessary, egg or larvae individuals are collected in the field and individually placed in tubes under controlled environment conditions at fixed temperature (inclusive overwintering at low temperature), humidity and photoperiod. Development and emergence is examined daily. The voltinism in the lab is measured as the number of adult generations emerged. The methods used in the laboratory could be adapted to establish the optimal rate at which generations are produced (potential voltinism), but this is unlikely to relate to what will be observed in the field. References Altermatt, F. (2010a) Tell me what you eat and I'll tell you when you fly: diet can predict phenological changes in response to climate change. Ecology Letters, 13, 1475-1484. Altermatt, F. (2010b) Climatic warming increases voltinism in European butterflies and moths. Proceedings of the Royal Society B, 277, 1281-1287. Bentz, B.J. & Powell, J.A. (2014) Mountain Pine Beetle Seasonal Timing and Constraints to Bivoltinism (A Comment on Mitton and Ferrenberg, "Mountain Pine Beetle Develops an Unprecedented Summer Generation in Response to Climate Warming"). American Naturalist, 184, 787-796. Berg, M.P. & Ellers, J. (2010) Trait plasticity in species interactions: a driving force of community dynamics. Evolutionary Ecology, 24, 617-629. Cizek, L., Fric, Z. & Konvicka, M. (2006) Host plant defences and voltinism in European butterflies. Ecological Entomology, 31, 337-344.



Cooley, J.R., Marshall, D.C., Simon, C., Neckermann, M.L. & Bunker, G. (2013) At the limits: habitat suitability modelling of northern 17-year periodical cicada extinctions (Hemiptera: Magicicada spp.). Global Ecology and Biogeography, 22, 410-421. Danks, H.V. (2007) The elements of seasonal adaptations in insects. Canadian Entomologist, 139, 1-44. Gordo, O., Sanz, J.J. & Lobo, J.M. (2010) Determining the environmental factors underlying the spatial variability of insect appearance phenology for the honey bee, Apis mellifera, and the small white, Pieris rapae. Journal of Insect Science, 10, 1-21. Hunter, M.D. & McNeil, J.N. (1997) Host-plant quality influences diapause and voltinism in a polyphagous insect herbivore. Ecology, 78, 977-986. Kivelä, S.M., Välimäki, P., Oksanen, J., Kaitala, A. & Kaitala, V. (2009) Seasonal clines of evolutionarily stable reproductive effort in insects. American Naturalist, 174, 526-536. Knell, R.J. & Thackeray, S.J. (2016) Voltinism and resilience to climate-induced phenological mismatch. Climatic Change, 137, 525-539. Porter, J.H., Parry, M.L. & Carter, T.R. (1991) The potential effects of climate-changeon agricultural insect pests. Agricultural and Forest Meteorology, 57, 221-240. Scoble, M.J. (1995) The Lepidoptera: Form, Function and Diversity. Natural History Museum, London. Steinbauer, M.J., Kriticos, D.J., Lukacs, Z. & Clarke, A.R. (2004) Modelling a forest lepidopteran: phenological plasticity determines voltinism which influences population dynamics. Forest Ecology and Management, 198, 117-131. Tauber, M.J., Tauaber, C.A. & Masaki, S. (1986) Seasonal Adaptations of Insects. Oxford University Press, New York. Valimaki, P., Kivela, S.M., Jaaskelainen, L., Kaitala, A., Kaitala, V. & Oksanen, J. (2008) Divergent timing of egg-laying may maintain life history polymorphism in potentially multivoltine insects in seasonal environments. Journal of Evolutionary Biology, 21, 1711-1723. van Asch, M. & Visser, M.E. (2007) Phenology of forest caterpillars and their host trees: The importance of synchrony. Annual Review of Entomology, 52, 37-55. Yamamura, K. & Kiritani, K. (1998) A simple method to estimate the potential increase in the number of generations under global warming in temperate zones. Applied Entomology and Zoology, 33, 289-298.

5. PHYSIOLOGY 5.1. STANDARD METABOLIC RATE Definition and relevance Standard metabolic rate is the uptake, transformation and allocation of energy of animals at rest per unit of time, indicating the minimal energy necessary for an inactive animal to sustain itself (Withers 1992). Standard metabolic rate is related to several organism features including behaviour, longevity and reproduction output (Brown et al. 2004; Le Lann et al. 2011). Additionally, the reaction norm of standard metabolic rate with temperature can indicate how organisms differ in their response to environmental changes, and can explain disruption of species interactions under global warming (Berg et al. 2010). For instance, the strength of insect's standard metabolic rate response to temperature is related to species susceptibility to desiccation, as much of their water loss happens via respiration (Chown 2002).



What and how to measure Standard metabolic rate can be measured either by direct or indirect calorimetry. A comprehensive overview of the theory, techniques, empirical pitfalls and appropriate equations for calorimetry is provided by Lighton (2008). Direct calorimetry is a direct measure of heat production and is much less commonly deployed than the latter, though microcalorimeters are widely available (e.g. Hansen, Ramløv & Westh 2004). Indirect calorimetry estimates either the consumption of O2 or the production of CO2 and either by constant pressure or constant volume methods, though other approaches are also common. There are basically two types of respirometers. Closed-system respirometers measure O2 consumption within a closed chamber. This is a constant volume technique. Measurements can be made continuously or at intervals using an appropriate gas analyser. Opensystem or flux respirometers create an air flux in the chamber and calculate the O2 consumption or CO2 by measuring the difference in O2 concentration in the air before and after passing through the chamber containing the animal. For species that are sensitive to dehydration, either a closed system respirometer should be used, or the air stream should be humidified, though the latter needs to be factored into both design of the system and analysis of the data (Lighton 2008). A key decision to be made when measuring standard metabolic rate of ectotherms is the choice of temperature. As biological reaction rates increase exponentially with temperature up to some optimum, whereafter they decline (Cossins & Bowler 1987), it is necessary to establish standard conditions to compare metabolic rates between species. For single temperature comparisons, a non-stressful temperature should be used, which may vary depending on the species and the environment from which it has been collected. It is essential to report the chosen temperature, the animal’s fresh mass or dry mass, and the conditions (level of activity, time since feeding) when providing estimates of metabolic rate. Recent work has suggested however, that given the ease of measuring metabolic rates, the full rate-temperature curve, including the maximum rate and its temperature, should be reported. Pre-treatment Animals should be described according to the standardisation protocol. How to measure standard metabolic rate? Chambers should be cleaned well to avoid any O2 consumption or CO2 production due to microbial respiration. In flow through systems, consideration should be given to the volume of the chamber relative to the flow rate, especially if patterns of gas exchange are of interest. Large chambers relative to slow flow rates result in delayed response times (Lighton 2008). Each chamber should only hold one individual for the period of standard metabolic rate measurement and before starting the measurements, animals should be allowed to accustom to the chamber and return to a resting state. An independent measure of activity, such as by infrared activity detection, or by video image, should also be obtained to verify a resting state. The measurements should start only when the animals are inactive. Both before and after the measurements, animals should be weighed. Because mass has such a significant influence on metabolic rate, later analyses should use mass as a covariate to enable comparisons to be made on a mass-corrected basis. Measurements before and after a trial can also provide a measure of water loss experienced by the animal if measures are made in dry environments. Additional notes When working with small animals (e.g., collembolan and mites), it can be difficult to accurately measure O2 consumption. Smaller chambers than provided with commercial respirometers might be necessary. Here, closedsystem respirometry may be most useful and multiple individuals may have to be used (Lighton 2008). An important convention is simply to report in detail the conditions used. Species from environments with strong seasonality might show distinct physiological status along the year, such as hibernation. In these cases, it is important to define and standardize the period of collection of the animals. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


References Berg, M.P., Kiers, E.T., Driessen, G., van der Heijden, M., Kooi, B.W., Kuenen, F., Liefting, M., Verhoef, H.A. & Ellers, J. (2010) Adapt or disperse: understanding species persistence in a changing world. Global Change Biology, 16, 587-598. Brown, J.H., Gillooly, J.F., Allen, A.P., van Savage, M. & West, G.B. (2004) Toward a metabolic theory of ecology. Ecology, 85, 1771-1789. Chown, S.L. (2002) Respiratory water loss in insects. Comparative Biochemistry and Physiology A, 133, 791804. Cossins, A.R. & Bowler, K. (1987) Temperature biology of animals. Chapman & Hall, New York. Hansen, L.L., Ramløv, H. & Westh, P. (2004) Metabolic activity and water vapour absorption in the mealworm Tenebrio molitor L. (Coleoptera, Tenebrionidae): real-time measurements by two-channel microcalorimetry. Journal of Experimental Biology, 207, 545-552. Le Lann, C., Wardziak, T., van Baaren, J. & van Alphen, J.J.M. (2011) Thermal plasticity of metabolic rates linked to life history traits and foraging behaviour in a parasitic wasp. Functional Ecology, 25, 641-651. Lighton, J.R.B. (2008) Measuring metabolic rates: a manual for scientists. Oxford University Press, Oxford. Withers, P.C. (1992) Comparative Animal Physiology. Saunders, Orlando.

5.2. RELATIVE GROWTH RATE Definition and relevance The relative growth rate is defined as the rate of increase in body size (length or weight) of an individual per unit of body size and time. Relative growth rate is related to several life history traits, such as body size and age at maturity (Gotthard 2000; Angilletta, Steury & Sears 2004) and can influence different fitness components such as fecundity and survival. Relative growth rate complements other traits such as ingestion rate, assimilation efficiency, and production efficiency in response to changes in food quality (Weiser & Stamp 1998; Talaei 2009; Faberi et al. 2011). Relative growth rate determines an individual’s susceptibility to environmental stress (Fordyce & Shapiro 2003) and predation (slow-growth-high-mortality hypothesis; Williams 1999). What and how to measure Relative growth rate is based on measuring the growth rate of an individual under standardized conditions, which is the increase in body size, either length or mass, over a given unit of time. When growth rate is expressed per unit of body size the relative growth rate is obtained. Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. The relative growth rate can change during ontogenetic development. Growth rate of specific ontogenetic stages should be measured during the whole duration of a particular stage of interest, and information on the ontogenetic stage should be published together with the growth rate measurements. How to measure relative growth rate? Animals should be kept individually in microcosms. Different taxonomical groups will require different microcosm’s size and configuration to ensure favourable conditions to growth. Animals should be offered ad libitum food and water supply, and special care should be taken that the quality of the food is kept constant over the measuring period.



Animals’ initial fresh mass should be recorded for posterior conversion to initial dry mass (DMi) as described below. At the end of the assay, animals should be dried to record their final dry mass (DMf) (see body size protocol). The relative growth rate (RGR) is calculated as: 𝑅𝑅𝑅𝑅𝑅𝑅 =

�𝐷𝐷𝐷𝐷𝑓𝑓 − 𝐷𝐷𝐷𝐷𝑖𝑖 � 𝐷𝐷𝐷𝐷𝑖𝑖 ∗ 𝑇𝑇

where DMi is the initial dry mass of the animal, DMf is the final dry mass of the animal and T is the duration time of the assay. To calculate DMi, it is necessary to record the species’ fresh to dry mass ratio (RDM:FM) which should be measured in an extra batch of individuals of the same ontogenetic stage as the RGR measurements. The formula 𝐷𝐷𝐷𝐷𝑖𝑖 = 𝑅𝑅𝐷𝐷𝐷𝐷:𝐹𝐹𝐹𝐹 ∗ 𝐹𝐹𝐹𝐹, can be used to calculate DMi, where FM is the initial fresh mass of the individual. Additional notes None.

References Angilletta, M.J., Steury, T.D. & Sears, M.W. (2004) Temperature, growth rate , and body size in ectotherms : Fitting pieces of a life history puzzle. Integrative and Comparative Biology, 44, 498-509. Faberi, A.J., López, A.N., Clemente, N.L. & Manet, P.L. (2011) Importance of diet in the growth, survivorship and reproduction of the no-tillage pest Armadillidium vulgare ( Crustacea : Isopoda). Revista Chilena de Historia Natural, 84, 407-417. Fordyce, J.A. & Shapiro A.M. (2003) An other perspective on slow-growth/high-mortality hypothesis: Chilling effects on swallowtail larvae. Ecology, 84, 263-268. Gotthard, K. (2000) Increased risk of predation as a cost of high growth rate: an experimental test in a butter. Journal of Animal Ecology, 69, 896-902. Talaei, R. (2009) Influences of plant species on life history traits of Cotesia rubecula (Hymenoptera: Braconidae) and its host Pieris rapae (Lepidotera: Pieridae). Biological Control, 51, 72-75. Weiser, L.A. & Stamp, N.E. (1998) Combined effects of allelochemicals, prey availability, and supplemental plant material on growth of a generalist insect predator. Entomologia Experimentalis et Applicata, 87, 181189. Williams, I.S. (1999) Slow-growth, high-mortality - a general hypothesis, or is it? Ecological Entomology, 24, 490-495.

5.3. DESICCATION RESISTANCE Definition and relevance Desiccation resistance refers to the time dry conditions can be tolerated by an organism before death ensues (Edney 1977; Addo-Bediako, Chown & Gaston 2001). Invertebrates lose water mainly through excretion, cuticular transpiration and respiratory loss (Gibbs, Fukuzato & Matzkin 2003). Desiccation resistance measured under standard laboratory conditions are frequently useful general predictor of species responses to changes in water availability and can explain current or future abundance patterns (White & Zar 1968; Addo-Bediako, Chown & Gaston 2001; Kellermann et al. 2009; David & Handa 2010; Dias et al. 2013). What and how to measure Desiccation resistance is the survival time (hours or minutes) of an organism when exposed typically to standard, relatively dry air conditions, though the value of relative humidity (RH) may vary given the organisms _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


concerned (see e.g. Kærsgaard et al. 2004). Desiccation stress is related to the air saturation deficit, which is a function of temperature and air humidity. As temperature can be a stress factor by itself, it is preferable to keep temperature around the organism’s optimum and use low air relative humidity (RH) to induce desiccation stress. The RH should be low enough to induce desiccation stress, otherwise experiments will take too long and other stress factors, such as starvation, may influence the measurements. However, if conditions are too harsh, animals will die too fast for accurate measurements. So far, there is no consensus in the literature about the RH animals should be exposed to, which might reflect differences in susceptibility among groups. Many studies use ~ 0% RH, which seems appropriate for highly mobile or flying arthropods, but for groups inhabiting soils 85% RH and 15 °C have been suggested as standard conditions (Dias et al. 2013; Shapiro-Ilan, Brown & Lewis 2013). Whatever the conditions chosen, it is essential that temperature and RH are reported along with trait values. Whenever possible, the same levels of RH and temperature shall be used consistently for a given group, to allow comparison with other measurements in the literature. Because body size is such an important determinant of water content, and body mass at the start and end of the experiment should always be reported. Pre-treatment Animals should be described and acclimatized according to the standardization protocol. Before exposing animals to dry conditions, any possible water deficit should be replenished, so measurements can start when they have approximately the maximal possible body water content. How to provide water will depend on the taxonomic group as they can differ considerably on the way of acquiring water. For instance, groups that absorb water vapour can be exposed ~100% relative humidity (RH), while animals that actively drink should be additionally provided with some water source (e.g., wet cotton). This procedure to replenish water content should be done in absence of food. This will induce animals to empty their gut and reduce faeces production during the experiment, so that changes in body mass not related to water loss are avoided. How to measure desiccation resistance? Different concentrations of glycerol-water solution can be used to establish RH ranging from 0% (pure glycerol) to 100% (pure water). The desiccation chamber should have a platform for the animal made of mesh to allow air exchange between the solution and the headspace (for a schematic drawing of a desiccation chamber, see online supplementary material in Dias et al. 2013). Before starting the measurements, carrying chambers should be acclimatized inside the desiccation chambers with the glycerol–water solution overnight. Animals should be individually added to the carrying chambers inside the desiccation chambers and followed until they die. If the animal does not show any visible activity when disturbing them gently, e.g. after tapping the vial or gently touching with a soft brush it can be considered dead. Desiccation resistance is estimated as survival time (hours or days). If individuals die overnight, the median of the values of the last measurement in the afternoon and the first in the morning should be used to calculate desiccation resistance. Additional notes There are two alternative approaches to measure traits related to desiccation: water loss rate and the amount of water loss tolerated before death. Water loss rate refers to a trait describing the rate of water loss from an individual over a given period of time (measured in mg h-1 or equivalent units), often between the start of the experiment and the time interval prior to death. For water loss measures, it is often advisable to weigh the animals regularly. This approach can be automated with modern balances and recording software or be undertaken manually. In the latter case, conditions of weighing should be maintained as close to experimental conditions as possible. Water loss rate can be estimated as the slope of the linear regression between water mass and time and expressed as the proportion of initial body water content that was lost per unit of time (Dias et al. 2013). Moreover, modern infra-red detection methods also enable water loss to be measured continuously along with metabolic rate (e.g. Chown & Davis 2003). These methods, in turn, provide the basis either for measuring _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


the relative contributions of respiratory and cuticular water loss to the total water lost (Quinlan & Hadley 1993; Chown & Davis 2003), or for estimating them (Gibbs & Johnson 2004; Gray & Chown 2008). Fatal water loss is estimated as the amount of water that can be lost before death (typically as mass unit). Absolute amount of water loss tolerated often does not vary greatly within particular taxa (such as the insects – Edney 1977). All approaches can be applied to a wide range of terrestrial invertebrates (Clusella-Trullas & Chown 2008) and enable humidity and temperature to be varied continuously in the airstream. References Addo-Bediako, A., Chown, S.L. & Gaston, K.J. (2001). Revisiting water loss in insects: a large scale view. Journal of Insect Physiology, 47, 1377-1388. Chown, S.L. & Davis, A.L.V. (2003) Discontinuous gas exchange and the significance of respiratory water loss in scarabaeine beetles. Journal of Experimental Biology, 206, 3547-3556. Clusella-Trullas, S. & Chown, S.L. (2008) Investigating onychophoran gas exchange and water balance as a means to inform current controversies in arthropod physiology. Journal of Experimental Biology, 211, 3139-3146. David, J.F. & Handa, I.T. (2010). The ecology of saprophagous macroarthropods (millipedes, woodlice) in the context of global change. Biological Review, 85, 881-895. Dias, A.T.C., Krab, E.J., Mariën, J., Zimmer, M., Cornelissen, J.H.C., Ellers, J. et al. (2013). Traits underpinning desiccation resistance explain distribution patterns of terrestrial isopods. Oecologia, 172, 667-677. Edney, E.B. (1977) Water Balance in Land Arthropods. Springer, Berlin. Gibbs A.G., Fukuzato F. & Matzkin L.M. (2003) Evolution of water conservation mechanism in Drosophila. Journal of Experimental Biology, 206, 1183-1192. Gibbs, A.G. & Johnson, R.A. (2004) The role of discontinuous gas exchange in insects: the chthonic hypothesis does not hold water. Journal of Experimental Biology, 207, 3477-3482. Gray, E.M. & Chown, S.L. (2008) Bias, precision and accuracy in the estimation of cuticular and respiratory water loss: A case study from a highly variable cockroach, Perisphaeria sp. Journal of Insect Physiology, 54, 169-179. Kærsgaard, C.W., Holmstrup, M., Malte, H. & Bayley, M. (2004) The importance of cuticular permeability, osmolyte production and body size for the desiccation resistance of nine species of Collembola. Journal of Insect Physiology, 50, 5-15. Kellermann V., van Heerwaarden B., Sgrò C. & Hoffmann A.A. (2009) Fundamental evolutionary limits in ecological traits drive Drosophila species distributions. Science, 325, 1244–1246 Quinlan, M.C. & Hadley, N.F. (1993) Gas exchange, ventilatory patterns, and water loss in two lubber grasshoppers: quantifying cuticular and respiratory transpiration. Physiological Zoology, 66, 628-642. Shapiro-Ilan D., Brown I. & Lewis E.E. (2014) Freezing and desiccation tolerance in entomopathogenic nematodes: diversity and correlation of traits. Journal of Nematology, 46, 27-34. White, J.J. & Zar, J.H. (1968). Relationships between saturation deficit and survival and distribution of terrestrial isopods. Ecology, 49, 556-559.

5.4. INUNDATION RESISTANCE Definition and relevance Inundation resistance is the capacity of a terrestrial organism to survive submergence underwater for a set period of time without direct access to atmospheric oxygen (i.e., via structures such as siphons, diving bells, etc.). The survival time underwater is related to the ability of acquiring sufficient oxygen to meet the basic metabolic rate and/or by reducing the metabolic rate. Inundation resistance measured under standard laboratory conditions, _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


although excluding avoidance behaviours, has been successfully used to understand distribution patterns of soil organisms and community composition in relation to flooding. For instance, inundation resistance is a good proxy explaining dominance on soil communities of river floodplains (Tufová & Tuf 2003) and can explain distribution patterns and responses to increased precipitation or flooding (Basson & Terblanche 2010). What and how to measure Inundation resistance can be measured as survival time when individuals are submerged in water under standardised water temperatures. Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. The choice of temperature is especially important because with increasing temperature oxygen solubility in water decreases and metabolic rate of ectotherms increases. To produce comparable results among species, we recommend using a standard temperature of 15 °C. Water of 15 °C provides relatively high amounts of oxygen and is in the range of temperature tolerance of most invertebrates. Additional temperatures could be used if ecologically relevant. For instance the higher incidence of flooding during early spring in large part of the temperate regions may suggest that lower temperatures, around 5 °C could reflect more realistic conditions in which invertebrates are facing flooding. It is essential to report the chosen temperature together with measurements of inundation resistance. How to measure inundation resistance? The submergence experiment should be carried out in a deep tray filled with water. Water should be aerated during the whole experiment by using an air pump. The water tray should be placed inside a climatic chamber overnight before starting the experiment, ensuring that water is at the desired temperature. To start the measurements, animals should be placed individually in small containers, which have a mesh at the top and bottom, within the tray. These are then submerged laterally to allow water circulation whilst at the same time avoiding trapping air bubbles. Survival should be recorded at regular intervals. The frequency of observations can vary between species, ranging from several times per day for sensitive species to once a day for resistant species. Animals should be followed until they die. It can be difficult to establish if the animal is still alive, especially in the final stages of life. If the animal does not show any visible activity by disturbing them gently, e.g. after tapping the vial or gently touching with a soft brush, it can be considered dead. Dead animals should be frozen for posterior recording of accessory data (e.g., body length, dry weight). Inundation resistance is estimated as survival time (hours or days). If individuals die overnight, the median of the values of the last measurement in the afternoon and the first in the morning should be used to calculate inundation resistance. Additional notes Species adapted to brackish and salt environment can experience significant osmotic problems when submerged into tap water, showing reduced survival time (Taylor & Carefoot 1992). Therefore, it is necessary to adjust the water salinity when measuring inundation resistance for these species. In some places, tap water receives high amounts of chemicals (e.g., chlorine and chloramine or heavy metals from piping) that can affect invertebrate survival. In this case, it is desirable to remove these chemicals from the water, by using charcoal filters or boiling the water, before using for measuring inundation resistance. It can also be relevant to measure inundation resistance for eggs or pupae, but the above protocol is not suitable because for these life stages survival cannot be recorded instantaneously during inundation. Instead one should record percentage survival for a batch of eggs and pupae that are reared to eclosion under optimal conditions after inundation for a certain period of time, compared to a control batch without inundation. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


A more mechanistic but laborious approach to inundation resistance is to measure the rate of oxygen uptake by animals when submerged in water at maximum oxygen solubility, in comparison to the aerial oxygen uptake rate at the same temperature. Sufficient oxygen uptake from water can sustain aerobic metabolism, and play an important role for survival of animals during flooding events. Oxygen consumption of individual animals is measured in a closed respiration chamber, either in air or submerged (Zerm, Zinkler & Adis 2004). References Basson, C.H. & Terblanche, J.S. (2010) Metabolic responses of Glossina pallidipes (Diptera: Glossinidae) puparia exposed to oxygen and temperature variation: Implications for population dynamics and subterranean life. Journal of Insect Physiology, 56, 1789-1797. Taylor, B.E. & Carefoot, T. (1993) Terrestrial life in isopods: evolutionary loss of gas-exchange and survival capability in water. Canadian Journal of Zoology, 71, 1372-1378. Tufová, J. & Tuf, I.H. (2003) Survival under water – comparative study of millipedes (Diplopoda), centipedes (Chilopoda) and terrestrial isopods (Oniscidea). Contributions to Soil Zoology in Central Europe I (eds. K. Tajovský, J. Schlaghamerský & V. Pižl), pp. 195-198. Academy of Sciences of the Czech Republic, České Budějovice, Czech Republic. Zerm, M., Zinkler, D. & Adis, J. (2004) Oxygen uptake and local PO2 profiles in submerged larvae of Phaeoxantha klugii (Coleoptera: Cicindelidae), as well as their metabolic rate in air. Physiological and Biochemical Zoology: Ecological and Evolutionary Approaches, 7, 378-389.

5.5. SALINITY RESISTANCE Definition and relevance Salinity resistance is the ability of an organism to withstand saline conditions. A soil is considered saline if it contains an excess in soluble salt with a lower limit of electrical conductivity of the saturation soil extract being 4 deci Siemens per meter (dSm-1) (Richards 1954). The area of saline soils worldwide is increasing (IPCC 2007; Abbas et al. 2011; Wang & Li 2012), and soil invertebrates from coastal and semi-arid areas will be potentially more exposed to saline conditions with consequent negative effects on growth, reproduction and survival (Coulson et al. 2002; Owojori et al. 2009; Pereira et al. 2015). Salinity resistance determines metabolic rate (Foucreau et al. 2012; Hidalgo et al. 2013), habitat preference (Pétillon et al. 2011) and abundance structure and range limits of species (Pétillon et al. 2008; La Sorte et al. 2009). What and how to measure Salinity resistance is measured as “time-to-death”, i.e. the time it takes to an individual to die when exposed to selected saline conditions. The selected salt concentration should be based on preliminary trials to be able to provide a reasonable range of “time-to-death” values, allowing discriminating individuals and/or species. Based on the results of Pereira et al. (2015) and Owojori & Reinecke (2009) we recommend a concentration of NaCl around 4 g kg-1 (equivalent to an electrical conductivity around 1.5 dSm-1).The selection of the test substrate is of paramount importance since substrate properties (e.g., pH, organic matter content and texture) can act as an extra stress factor for the individuals (Chelinho et al. 2011; Domene et al. 2012). We recommend using a suitable natural soil or the artificial OECD soil (70% quartz sand, 20% kaolinite clay, 10% peat) taking into account that soil properties are within the suitable ecological range for the species of interest. All organisms to be compared should be exposed to the same soil type. Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


How to measure salinity resistance To measure salinity resistance, the organisms should be exposed to the substrate spiked with a pre-determined lethal concentration of NaCl. The concentration of NaCl used (in g kg-1), pH and electrical conductivity in the test substrate after spiking (in dSm-1) should be reported with the measurement. To spike the soil it should be dried completely and then rewetted with the appropriate saline concentration. Exposure of the organisms to the test soil should be done in appropriate test vessels (one organism per vessel) according to their body size. Small petri dishes (5 cm diameter) are suitable for micro-arthropods, small molluscs and small oligochaetes, whereas larger pots (10cm diameter) could be used for larger invertebrates. Survival should be recorded at regular intervals. Animals should be followed until they die. If the animal does not show any visible activity by disturbing them gently, e.g. after taping the vial or gently touching with a soft brush it can be considered dead. If it is not possible to make observations overnight, and if individuals die during this period, the median of the values of the last measurement in the afternoon and the first in the morning should be used to calculate the “time-to-death”. Dead animals should be frozen for posterior recording of accessory data (e.g., dry weight, surface-to-volume ratio). Salinity resistance is estimated as survival time (hours or days). Control treatments on non-spiked soil should be performed to control for possible confounding factors. Additional notes For those organisms that cannot be easily checked for their life status in soil, such as enchytraeids, an alternative medium to perform the test could be a NaCl solution since these organisms endure quite well in water. Very small test vessels should be used with one individual each. The experimental conditions reported and measurements should be the same as described above. Some salt or brackish specialists might need a minimum salinity to maintain growth, reproduction and survival. In such cases, it might be relevant to quantify their resistance to both saline and non-saline conditions. For measuring resistance to non-saline conditions, the same approach described above can be used but spiking soil with fresh water instead of salt solutions. An alternative but more laborious approach to salinity resistance is to measure the salinity tolerance range. This approach refers to the range in substrate salt content within which individuals of a species are able to survive, i.e. the salt content threshold values below and above which individuals are not able to survive. A fixed number of animals are exposed to standard substrate with a range of NaCl content from fresh, to brackish to saline condition for a given period of time, after which the number of surviving individuals at each NaCl content is noted. References Abbas, A., Khan, S., Hussain, N., Hanjra, M. A. & Akbar, S. (2011) Characterizing soil salinity in irrigated agriculture using a remote sensing approach. Physics and Chemistry of the Earth, 55-57, 43-52. Chelinho, S., Domene, X., Campana, P., Natal-da-Luz, T., Scheffczyk, A., Rombke, J., Andres, P. & Sousa, J.P. (2011) Improving ecological risk assessment in the mediterranean area: selection of reference soils and evaluating the influence of soil properties on avoidance and reproduction of the Oligochaetes Eisenia andrei and Enchytra euscrypticus. Environmental Toxicology and Chemistry, 30, 1050-1058 Coulson, S.L., Hodkinson I.D., Webb N.R. & Harrison, A. (2002) Survival of terrestrial soil-dwelling arthropods on and in seawater: implications for trans-oceanic dispersal. Functional Ecology, 16, 353–356 Domene, X., Chelinho, S., Campana, P., Natal-da-Luz, T., Alcañiz, J., Römbke, J. et al. (2012) Applying a GLM-based approach to model the influence of soil properties on the toxicity of phenmedipham to Folsomia candida. Journal of Soils and Sediments, 12, 888-899



Foucreau, N., Renault, D., Hidalgo, K., Lugan, R. & Pétillon, J. (2012) Effects of diet and salinity on the survival, egg laying and metabolic fingerprints of the ground-dwelling spider Arctosa fulvolineata (Aranea, Lycosidae). Comparative Biochemistry and Physiology, Part A, 162, 388-395. Hidalgo, K., Laparie, M., Bical, R., Larvor, V., Bouchereau, A., Siaussat, D. et al. (2013) Metabolic fingerprinting of the responses to salinity in the invasive ground beetle Merizodussoledadinus at the Kerguelen Islands. Journal of Insect Physiology, 59, 91-100. IPCC (2007) Climate Change: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds. M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden, C.E. Hanson), Cambridge University Press, Cambridge, UK. La Sorte, F.A., Lee T.M., Wilman H. & Jetz W. (2009) Disparities between observed and predicted impacts of climate change on winter bird assemblages, Proceedings of the Royal Society B-Biological Sciences, 276, 3167-3174. Owojori, O.J. & Reinecke, A.J. (2009) Avoidance behavior of two exo-physiologically different earthworms (Eiseniafetida and Aporrectodea caliginosa) in natural and artificial saline soils. Chemosphere, 75, 279283. Owojori, O.J., Reinecke, A.J., Voua-Otomo, P. & Reinecke, S.A. (2009) Comparative study of the effects of salinity on life-cycle parameters of four soil-dwelling species (Folsomia candida, Enchytraeus doerjesi, Eisenia fetida and Aporrectodea caliginosa). Pedobiologia, 52, 351-360. Pereira, C.S., Lopes, I., Sousa, J.P. & Chelinho, S. (2015) Effects of NaCl and seawater induced salinity on survival and reproduction of three soil invertebrates. Chemosphere, 135, 116-122. Pétillon, J.,Georges, A., Canarda, A., Lefeuvrec, J.C., Bakkerd, J.P. & Ysnel, F. (2008) Influence of abiotic factors on spider and ground beetle communities in different salt-marsh systems. Basic and Applied Ecology, 9, 743-751 Pétillon J., Lambeets K., Ract-Madoux B., Vernon P. & Renault D. (2011). Saline stress tolerance partly matches with habitat preference in ground-living wolf spiders. Physiological Entomology, 36, 165-172 Richards, L.A. (1954) Diagnosis and improvements of saline and alkali soils. USDA. Agriculture Handbook 60. Wang, Y. & Li, Y. (2012) Land exploitation resulting in soil salinization in a desert-oasis ecotone. Catena, 100, 50-56.

5.6. TEMPERATURE TOLERANCE Definition and relevance A widely used definition of thermal tolerance is the broadest range of temperatures over which an organism can survive (Willmer, Stone &Johnston 2005). Thermal tolerance is related to climate and geographical distribution (Sunday, Bates & Dulvy 2011; Kellerman et al. 2012). According to the climate variability hypothesis, a species’ thermal tolerance is linked to its latitudinal range, in particular to average temperature (Addo-Bekiako, Chown & Gaston 2000; Sunday, Bates & Dulvy 2011), thermal fluctuations (van Dooremalen, Berg & Ellers 2013) and extreme temperatures (Hoffmann, Sørensen & Loeschcke 2003) in its habitat. Interspecific differences in thermal tolerance can have important ecological effects, for instance through reduction in the intensity of competition (Cerdá, Retana & Cros 1998; Bestelmeyer 2000), interaction strength between predators and prey (Berg et al. 2010) and can perturb mutualistic interactions if one of the partner succumbs to extreme temperatures (Hegland et al. 2009). What and how to measure Patterns of thermal tolerance can strongly depend on the assay method (Terblanche et al. 2007; Chown et al. 2009; Mitchell & Hoffmann 2010; Rezende, Tejedo & Santos 2011), as exposure time is often inversely related _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


with tolerance (Chown et al. 2009). There are two approaches to measure thermal tolerance: static exposure to constant stressful temperatures (e.g., Hoffmann, Anderson & Hallas 2002), and dynamic or ramping exposure to gradually increasing or decreasing temperature (Terblanche et al. 2007). In the latter method, temperature is changed gradually at a rate ΔT (°C min−1) from an initial non-stressful temperature T0. As temperature in nature tends to change gradually, we recommend using the dynamic method to investigate thermal tolerance. At low temperatures, critical thermal minimum (CTmin) is the temperature at which coordination is lost and the animal has insufficient strength or coordination to remain standing (often referred to as ‘knockdown’; Hazell & Bale 2011). It is equivalent to the onset of chill coma. At high temperatures, heat knockdown temperature (HKD) can be recorded as a proxy for heat tolerance. It is defined as the temperature at which individuals lose body control (knockdown temperature; Terblanche et al. 2007). Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. If possible individuals should be of standard age or developmental stage. Acclimation temperature should be the same as the initial temperature used during the temperature ramping. How to measure low temperature (cold) tolerance? Individuals should be placed individually into empty glass vials and submerged into a water bath set at 20 °C. The temperature should be gradually decreased at a constant rate ΔT, which is generally 0.1 to 0.5 °C min-1 (Sinclair, Alvarado & Ferguson 2015) and the individuals should be checked at regular intervals to record if loss of coordinated movement has occurred. CTmin is recorded when coordinated muscle function is lost. It is essential to report the chosen temperature decrease rate together with measurements of low thermal tolerance. An excellent review of this and other methods measuring cold tolerance is Sinclair, Alvarado & Ferguson (2015). How to measurement high temperature (heat) tolerance? Individuals should be placed individually into glass vials and submerged into a water bath set at 20°C. The bottom of the vials should be covered with moist filter paper to avoid desiccation during the exposure to high temperatures. The temperature should be gradually increased at a constant rate ΔT, which is generally taken to be between 0.06°C min-1 and 0.25°C min-1 (Terblanche et al. 2007; Kellermann et al. 2012). Generally, heat knockdown temperature is higher in animals exposed to a faster ramping rate (Sørensen, Loeschcke & Kristensen 2013). The individuals should be checked at regular intervals to record if knock down has occurred. Knock down is only recorded if the animals have lost the ability to move any body part (e.g. after tapping on the vial). The temperature at which knockdown occurs is noted as knock down temperature. It is essential to report the chosen temperature increase rate together with measurements of high thermal tolerance. Additional notes Please note that thermal history effects may last over a prolonged period of time, especially if different seasons produce physiologically acclimated forms, such as winter hardened individuals. In these cases, it is important to define and standardize the period of collection of the animals to be appropriate to the research question. References Addo-Bekiako, A., Chown, S.L. & Gaston, K.J. (2000) Thermal tolerance, climatic variability and latitude. Proceedings of the Royal Society London B, 267, 739-745. Berg, M.P., Kiers, E.T., Driessen, G., van der Heijden, M., Kooi, B.W., Kuenen, F., Liefting, M., Verhoef, H.A. & Ellers, J. (2010). Adapt or disperse: understanding species persistence in a changing world. Global Change Biology, 16, 587-598.



Bestelmeyer, B.T. (2000) The trade-off between thermal tolerance and behavioural dominance in a subtropical South American ant community. Journal of Animal Ecology, 69, 998-1009. Cerdá, X., Retana, J. & Cros, S. (1998) Critical thermal limits in Mediterranean ant species: Trade-off between mortality risk and foraging performance. Functional Ecology, 12, 45-55. Chown, S.L., Jumbam, K.R., Sørensen, J.G. & Terblanche, J.S. (2009) Phenotypic variance, plasticity and heritability estimates of critical thermal limits depend on methodological context. Functional Ecology, 23, 133-140. Hazell, S.P. & Bale, J.S. (2011) Low temperature thresholds: Are chill coma and CTmin synonymous? Journal of Insect Physiology, 57, 1085-1089 Hegland, S.J., Nielsen, A., Lázaro, A., Bjerknes, A.L. & Totland, Ø. (2009) How does climate warming affect plant-pollinator interactions? Ecology Letters, 12, 184-95. Hoffmann, A.A., Anderson, A.A. & Hallas, R. (2002) Opposing clines for high and low temperature resistance in Drosophila melanogaster. Ecology Letters, 5, 614-618. Hoffmann, A.A., Sørensen, J.G. & Loeschcke, V. (2003) Adaptation of Drosophila to temperature extremes: bringing together quantitative and molecular approaches. Journal of Thermal Biology, 28, 175-216. Kellermann, V., Overgaard, J., Hoffmann, A.A., Fløjgaard, C., Svenning, J.C. & Loeschcke, V. (2012) Upper thermal limits of Drosophila are linked to species distributions and strongly constrained phylogenetically. Proceedings of the National Academy of Sciences USA, 109, 16228-16233. Mitchell, K.A. & Hoffmann, A.A. (2010) Thermal ramping rate influences evolutionary potential and species differences for upper thermal limits in Drosophila. Functional Ecology, 24, 694-700. Rezende, E.L., Tejedo, M. & Santos, M. (2011) Estimating the adaptive potential of critical thermal limits: methodological problems and evolutionary implications. Functional Ecology, 25, 111-121. Sinclair, B. J., Alvarado, L. E. C., & Ferguson, L. V. (2015). An invitation to measure insect cold tolerance: methods, approaches, and workflow. Journal of Thermal Biology, 53, 180-197. Sørensen, J.G., Loeschcke, V. & Kristensen, T.N. (2013) Cellular damage as induced by high temperature is dependent on rate of temperature change - investigating consequences of ramping rates on molecular and organismal phenotypes in Drosophila melanogaster. Journal of Experimental Biology, 216, 809-814. Sunday, J.M., Bates, A.E. & Dulvy, N.K. (2011) Global analysis of thermal tolerance and latitude in ectotherms. Proceedings of the Royal Society London B, 278, 1823-1830. Terblanche, J.S., Deere, J.A., Clusella Trullas, S., Janion, C. & Chown, S.L. (2007). Critical thermal limits depend on methodological context. Proceedings of the Royal Society London B, 274, 2935-2942. van Dooremalen, C., Berg, M.P. & Ellers, J. (2013) Acclimation responses to temperature vary with vertical stratification: implications for vulnerability of soil-dwelling species to climate change. Global Change Biology, 19, 975-984. Willmer, P., Stone, G. & Johnston, I. (2005) Environmental Physiology of Animals (2nd ed.). Oxford, UK, Blackwell Science Ltd

5.7. PH RESISTANCE Definition and relevance pH resistance is the ability of an organism to withstand acidic or alkaline conditions. Many invertebrates live in close contact with substrates, e.g., soil, mosses and lichens and tree bark, which can show a substantial variation in pH. Additionally, substrate pH can change due to pollution and land use change, restricting abundance and distribution of fauna (Rusek & Marshall 2000; Loranger et al. 2001; Chan & Mead 2003; Chapman, Dave & Murimboh 2013), and affecting the composition of soil communities (Bååth et al. 1980; Korthals et al. 1996). pH resistance varies considerably among species both between and within taxonomical groups (Kaplan et al. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


1980; Loranger et al. 2001; Chan & Mead 2003; Jänsch, Amorim & Römbke 2005; Chapman, Dave & Murimboh 2013). However, long-term exposure to unfavourable pH conditions can lead to evolution of increased pH tolerance, resulting in higher survival and growth rate under low or high pH conditions (Doroszuk, Wojewodzic & Kammenga 2006). What and how to measure There are two aspects to pH resistance: acidity resistance and alkaline resistance. Animals should be exposed individually in microcosms prepared with standard substrate. We recommend to use a standard artificial substrate (OECD substrate: 70% sand, 20% kaolinite clay, 10% peat) or another type of substrates depending on the study system (e.g., invertebrates living in mosses or lichens or under three barks). A description of the substrate composition should be reported with the measurements. Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. How to measure pH resistance? To measure acidity or alkaline resistance it is necessary to expose animals to a standard substrate with predetermined lethal pH values, i.e. pH values that cause mortality of all studied individuals. Therefore, a pilot experiment might be necessary for establishing such lethal pH values. A universal buffer (Britton & Robinson 1931) can be used to adjust soil pH to a broad range of values (Mongay & Cerdá 1974). Table 1 shows buffer recipes providing desirable pH values. Osmolarity should be corrected to the same ionic strength by diluting the concentrated solutions using demineralised water. We recommend using an osmolarity of 150 mOsm kg-1 as the pH does not change much around this value. How much buffer one needs to add is depending on the substrate. The microcosms should be prepared with the chosen substrate and buffer before adding the animals. Before starting the assays, both substrate pH and osmolarity should be measured in the microcosms using a pH-meter and an osmometer, respectively. The resistance is estimated as the survival time (hours or minutes) of animals after exposure to the predetermined lethal pH values. If the animal does not show any visible activity by disturbing them gently, e.g. after taping the vial or gently touching with a soft brush it can be considered dead. Controls with animals exposed to non-lethal pH conditions (determined in the pilot experiment), should be also set. Survival on this control condition ensures that mortality on lethal pH treatments is indeed caused by pH. We recommend publishing the standard pH values used in the assays together with pH resistance measurements. Additional notes An alternative but more laborious approach to pH tolerance is to measure the pH tolerance range. This approach refers to the range in substrate pH at which individuals of a species are able to survive, i.e. the pH threshold values below and above which individuals are not able to survive. A fixed number of animals are exposed to standard substrate with a range of pH values from acidic to alkaline condition for a given period of time, after which the number of surviving individuals at each pH level is noted. References Bååth, E., Berg B., Lohm U., Lundkvis, H. & Rosswall, T. (1980) Effects of experimental acidification and liming on soil organisms and decomposition in a Scots pine forest. Pedobiologia, 20, 85-100. Britton, H.T.S. & Robinson, R.A. (1931) Universal buffer solutions and the dissociation constant of veronal. Journal of the Chemical Society, 98, 1456-1462. Cerdá, X., Retana, J. & Cros, S. (1998). Critical thermal limits in Mediterranean ant species: Trade-off between mortality risk and foraging performance. Functional Ecology, 12, 45-55.



Chan, K.-Y. & Mead, J.A. (2003) Soil acidity limits colonisation by Aporrectodea trapezoides, an exotic earthworm. Pedobiologia, 47, 225-229. Chapman, E.E.V, Dave, G. & Murimboh, J.D. (2013) A review of metal (Pb and Zn) sensitive and pH tolerant bioassay organisms for risk screening of metal-contaminated acidic soils. Environmental pollution, 179, 326-342. Doroszuk, A., Wojewodzic, M. W. & Kammenga, J. E. (2006). Rapid adaptive divergence of life-history traits in response to abiotic stress within a natural population of a parthenogenetic nematode. Proceedings of the Royal Society of London B: Biological Sciences, 273, 2611-2618. Jänsch, S., Amorim, M.J. & Römbke, J. (2005) Identification of the ecological requirements of important terrestrial ecotoxicological test species. Environmental Reviews, 13, 51-83. Kaplan, D.L., Hartenstein, R., Neuhauser, E.F. & Malecki, M.R. (1980) Physicochemical requirements in the environment of the earthworm Eisenia foetida. Soil Biology and Biochemistry, 12, 347-352. Korthals, G. W., Alexiev, A. D., Lexmond, T. M., Kammenga, J. E., & Bongers, T. (1996). Long-term effects of copper and pH on the nematode community in an agroecosystem. Environmental Toxicology and Chemistry, 15, 979-985. Loranger, G., Bandyopadhyaya, I., Razaka, B. & Ponge, J.-F. (2001) Does soil acidity explain altitudinal sequences in collembolan communities? Soil Biology and Biochemistry, 33, 381-393. Mongay, C. & Cerdá, V. (1974) A Britton-Robinson buffer of known ionic strength. Annali di Chimica, 64, 409412. Rusek, J. & Marshall, V.G. (2000) Impacts of airborne pollutants on soil fauna. Annual Review of Ecology and Systematics, 31, 395-423.

Table S1: Universal buffer recipes providing desirable pH values and resulting ionic strength. Modified from Mongay & Cerdá (1974).

pH 1.81 1.89 1.98 2.09 2.21 2.36 2.56 2.87 3.29 3.78 4.10 4.35 4.56 4.78 5.02 5.33 5.72 6.09

NaOH 0.000 0.195 0.381 0.558 0.772 0.889 1.040 1.191 1.333 1.469 1.600 1.725 1.846 1.962 2.074 2.182 2.286 2.386

Universal buffer (Britton-Robinson) Composition (g.l-1) Ionic strength (M) CH3CO2H H3PO4 H3BO3 2.402 3.920 2.473 0.0134 2.343 3.824 2.413 0.0161 2.288 3.733 2.355 0.0180 2.234 3.647 2.301 0.0200 2.184 3.564 2.248 0.0228 2.135 3.484 2.198 0.0246 2.089 3.409 2.151 0.0273 2.044 3.336 2.105 0.0302 2.002 3.267 2.061 0.0331 1.961 3.200 2.019 0.0360 1.922 3.136 1.979 0.0388 1.884 3.075 1.940 0.0417 1.848 3.015 1.902 0.0445 1.813 2.958 1.867 0.0475 1.779 2.904 1.832 0.0506 1.747 2.851 1.799 0.0539 1.716 2.800 1.767 0.0571 1.686 2.751 1.736 0.0603



Continuation Table S1 pH NaOH 6.37 2.483 6.59 2.576 6.80 2.667 7.00 2.754 7.24 2.839 7.54 2.921 7.96 3.000 8.36 3.077 8.69 3.152 8.95 3.224 9.15 3.294 9.37 3.362 9.62 3.429 9.91 3.493 10.38 3.556 10.88 3.616 11.20 3.676 11.40 3.733 11.58 3.789 11.70 3.844 11.82 3.897 11.92 3.949 11.98 4.000

CH3CO2H 1.657 1.628 1.601 1.575 1.550 1.525 1.501 1.478 1.456 1.434 1.413 1.392 1.373 1.353 1.334 1.316 1.298 1.281 1.264 1.248 1.232 1.216 1.201

H3PO4 2.703 2.658 2.613 2.570 2.529 2.489 2.450 2.412 2.376 2.340 2.306 2.272 2.240 2.208 2.178 2.148 2.119 2.091 2.063 2.036 2.010 1.985 1.960

H3BO3 1.706 1.677 1.649 1.622 1.596 1.570 1.546 1.522 1.499 1.477 1.455 1.434 1.413 1.393 1.374 1.355 1.337 1.319 1.302 1.285 1.268 1.252 1.237

Ionic strength (M) 0.0636 0.0671 0.0712 0.7530 0.0815 0.0882 0.0952 0.0993 0.1020 0.1040 0.1060 0.1070 0.1090 0.1100 0.1110 0.1120 0.1140 0.1160 0.1180 0.1210 0.1230 0.1260 0.1280

6. BEHAVIOUR 6.1. ACTIVITY TIME Definition and relevance Activity time is defined as the period within 24h when a species is active. Activity time is correlated to other species’ traits such as morphology and physiological responses to environmental conditions. For example, activity time is associated with visual capacity in ants (Yilmaz et al. 2014) and body size in all insects (Guevara & Avilés 2013). From an ecological view point, differences in activity time leading to temporal niche partitioning may facilitate co-existence between competitors and determine predator-prey interactions (KronfeldSchor & Dayan 2003). Also, activity time has been linked to co-evolution between plants and pollinators where the greater efficiency of nocturnal pollinators has been suggested to explain flowering time (Young 2002). What and how to measure Activity time is of ecological and evolutionary importance for invertebrates, but no good protocol is available in the literature how to measure activity time. Despite activity time being a continuous variable classically expressed as frequency of activity over time, we propose to classify species into categories depending on when the peaks of activity occur. For these reasons measurements need to be taken across a broad range of conditions



to allow accurate estimation of the intra-specific variance in activity time due to environmental and/or biotic conditions. Pre-treatment Animals should be described according to the standardisation protocol. Activity time can be measured under controlled laboratory conditions or in the field. In the field, activity time has to be measured across a broad range of environmental conditions, including different habitat types, to account for the influence of external factors such as temperature and light (Chuang, Lee & Chen 2004) and we recommend to reporting these conditions with the trait category. How to record activity time? Activity includes various processes such as moving, flying, hunting, foraging and thermoregulation. Measurements can be done using visual methods (e.g. observations of behaviour), automated imaging analysis (Carthew & Slater 1991; Allemand et al. 1994; Engenheiro et al. 2005), trapping (e.g. pitfall traps for grounddwelling insects, baited traps for dung or carrion beetles and interception traps for flying insects), and acoustic (Mankin et al. 2000) or optic sensors (Reynolds & Riley 2002). All these methods can be used both in the laboratory and in the field, except for trapping which is exclusively used in the field. The following categories of activity time are distinguished: - Diurnal: individuals are active only during the day - Nocturnal: Individuals are active only during the night - Crepuscular: Individuals are active during twilight, including dawn, dusk, bright moonlit night and dull days. Additional categories can be distinguished: matutinal and vespertine are crepuscular species active only during dawn and dusk, respectively. - Cathemeral: Individuals are repeatedly active over day and night, with either long or short periods of activity across day and or night. A species is classified into one of the categories when the activity of more than 70% of the individuals fits the definition. If the information is available, different proportions of activity time can also be assigned to two or more categories, summing up to 100%. Additional notes The activity of some species might change over time as a response to development stage or to external factors (Desender & Alderweireldt 1990; Tuf, Dedek & Vesely 2012). For instance, some fly species can switch from diurnal to nocturnal as a response to stress (Joplin & Moore 1999). Also males and females can have different activity times. For example, in some moth species, the adult males are active both during the day and during the night, in constant search for females, while females fly only during the night. References Allemand, R., Pompanon, F., Fleury, F., Fouillet, P. & Bouletreau, M. (1994) Behavioural circadian rhythms measured in real-time by automatic image analysis: applications in parasitoid insects. Physiological Entomology, 19, 1-8. Carthew, S.M. & Slater, E. (1991) Monitoring animal activity with automated photography. The Journal of wildlife management, 55, 689-692. Chuang, S.C., Lee, H. & Chen, J.H. (2004) Diurnal rhythm and effect of temperature on oxygen consumption in earthworms, Amynthas gracilis and Pontoscolex corethrurus. Journal of Experimental Zoology Part A: Comparative Experimental Biology, 301A, 737-744. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


Desender, K. & Alderweireldt, M. (1990) Yearly and seasonal-variation of Carabid diel activity in pastures and cultivated fields. Revue d'Ecologie et de Biologie du Sol, 27, 423-433. Engenheiro, E.L., Hankard, P.K., Sousa, J.P., Lemos, M.F., Weeks, J.M. & Soares, A.M. (2005) Influence of dimethoate on acetylcholinesterase activity and locomotor function in terrestrial isopods. Environmental Toxicology and Chemistry, 24, 603-609. Guevara, J. & Avilés, L. (2013) Community-wide body size differences between nocturnal and diurnal insects. Ecology, 94, 537-543. Joplin, K.H. & Moore, D. (1999) Effects of environmental factors on circadian activity in the flesh fly,Sarcophaga crassipalpis. Physiological Entomology, 24, 64-71. Kronfeld-Schor, N. & Dayan, T. (2003) Partitioning of time as an ecological resource. Annual Review of Ecology Evolution and Systematics, 34, 153-181. Mankin, R., Brandhorst-Hubbard, J., Flanders, K., Zhang, M., Crocker, R., Lapointe, S. et al. (2000) Eavesdropping on insects hidden in soil and interior structures of plants. Journal of Economic Entomology, 93, 1173-1182. Reynolds, D. & Riley, J. (2002) Remote-sensing, telemetric and computer-based technologies for investigating insect movement: a survey of existing and potential techniques. Computers and Electronics in Agriculture, 35, 271-307. Tuf, I.H., Dedek, P. & Vesely, M. (2012) Does the diurnal activity pattern of Carabid beetles depend on season, ground temperature and habitat? Archives of Biological Sciences, 64, 721-732. Yilmaz, A., Aksoy, V., Camlitepe, Y. & Giurfa, M. (2014) Eye structure, activity rhythms and visually-driven behavior are tuned to visual niche in ants. Frontiers in Behavioral Neuroscience, 8, 205. Young, H.J. (2002) Diurnal and nocturnal pollination of Silene alba (Caryophyllaceae). American Journal of Botany, 89, 433-440.

6.2. AGGREGATION Definition and relevance Aggregation corresponds to a group of individuals belonging to the same species being gathered at the same place but not socially organised, which leads to a clustered distribution of individuals in their environment (Broly, Deneubourg & Devigne 2013). Two types of aggregation can be distinguished: social and environmental aggregation. Social aggregation result from the presence of conspecifics attracting individuals (Camazine et al. 2001; Jeanson & Deneubourg 2007) and environmental aggregation from environmental heterogeneity in e.g. food, light or humidity (Wiens 1976). Here, we focus on social aggregation as measurements can be done in controlled conditions. Environmental aggregation is related to the distribution of environmental conditions and has thus to be measured in the field (see additional notes). Many benefits of aggregation have been described, including reduced predation risk (Gascoigne & Lipcius 2004), the increased ability to acquire, hold, and make efficient use of resources (Liu et al. 2014; Kouki & Hanski 1995), the higher proximity to sexual partners (Møller & Legendre 2001), the energy saved by huddling during cold weather (Gilbert et al. 2010), as well as the collective modification of environmental properties (Bell & Gosline 1997; Charabidze, Bourel & Gosset 2011). Several costs of aggregation have also been described including exploitative (Reis, Von Zuben & Godoy 1999) and interference competition (Valeix, ChamailléJammes & Fritz 2007), sexual conflict (Pilastro, Benetton & Bisazza 2003), higher disease and parasitism risk (Hirose, Kimoto & Hiehata 1976), increased cannibalism (Polis 1980) and increased visibility to predators (Riipi et al. 2001).



What and how to measure Various indices can be used to estimate aggregation. We recommend Morisita’s index because it is widely used, easily interpretable and among the best measures of aggregation (Hurlbert 1990). The Morisita’s index (𝐼𝐼𝑚𝑚 ) represents the probability that two individual’s chosen at random from the whole population belong to the same sampling unit (Morisita 1959, 1962). This index is relatively independent of the sample size and diversity of samples (Wolda 1981). Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. Experimental arenas have to be designed with standard conditions as close as possible to the environmental conditions where the species was sampled. Arena size depends on the mobility, size and behaviour of the target species and has to be sufficiently large to allow the investigation of aggregation at multiple spatial scales. A species can have a completely random distribution at one scale and a more aggregated distribution at another. We recommend that the spatial scale must be reported alongside aggregation data. How to measure aggregation? The area within the arenas is divided into quadrats of equal dimensions. Ideally, measures should be repeated by varying the size and thus the number of quadrats to assess aggregation at various spatial scales. The minimum dimensions of quadrats should allow all individuals to gather in a single quadrat. It can be of less than 1cm2 for taxa such as Collembola but much larger for predators such as carabid beetles. In parallel, the total number of quadrats should be sufficiently high to allow all tested individuals to occupy single quadrats. This will determine the minimum size of the arena. The number of quadrats per m2, the total area of the arena (in m2) and the number and developmental stage of the tested individuals should be mentioned in publications. The distribution of individuals among quadrats is recorded by visual observations or using automated observation methods such as a time lapse image analyser. Measures have to be repeated to account for the temporal variability of species aggregation. The number and frequency of repetitions depends on the target species and questions. The next step consists of calculating an index of aggregation. Morisita’s index is calculated as follows: 𝐼𝐼𝑚𝑚 = ∑𝑁𝑁 𝑖𝑖=1

𝑛𝑛𝑖𝑖 (𝑛𝑛𝑖𝑖 −1) 𝑛𝑛(𝑛𝑛−1)

N

Where ni is the number of individuals in quadrat i, n is the total number of individuals in all quadrats, N is the total number of quadrats. This index ranges from 0 to x where higher values indicate more aggregated distributions. Additional notes Some species can change their pattern of aggregation during their life cycle, such as locusts. The aggregation behaviour of grasshoppers is characterized by two phases: gregaria and solitaria. Transition from solitaria to gregaria can be induced by the patchiness of the environment and/or strong attractions between individuals (Ellis 1956). Social insects such as ants or bees typically have highly aggregated distributions. In the case of large colonies, the number of individuals can make the measure of aggregation more difficult and/or time consuming. We recommend using measures of sociality and not measures of aggregation in these cases (see the sociality protocol). Finally, environmental aggregation are not easy to test in the laboratory due to high mobility or difficulty in setting up experimental arenas of sufficient size and encompassing a broad gradient of environmental conditions. Measures of environmental aggregation should be preferentially taken in the field using distribution data or



macrocosms (using the same procedure as described above). Distribution data can derive from visual observations, trapping, acoustic and optic sensors and video recording combined with image analyses. Information about the coordinates of sampling locations and the sampling design has to be reported alongside environmental aggregation data. References Bell, E.C. & Gosline, J.M. (1997) Strategies for life in flow: tenacity, morphometry, and probability of dislodgment of two Mytilus species. Marine Ecology Progress Series, 159, 197-208. Broly, P., Deneubourg, J.L. & Devigne, C. (2013) Benefits of aggregation in woodlice: a factor in the terrestrialization process? Insectes Sociaux, 60, 419-435. Camazine, S., Deneubourg, J.L., Franks, N.R., Sneyd, J., Theraulaz, G. & Bonabeau, E. (2001) Self-organization in biological systems. Princeton University Press, New Jersey. Charabidze, D., Bourel, B. & Gosset, D. (2011) Larval-mass effect: characterisation of heat emission by necrophageous blowflies (Diptera: Calliphoridae) larval aggregates. Forensic Science International, 211, 61-66. Ellis, P.E. (1956) Differences in social aggregation in two species of Locust. Nature, 178, 1007-1007. Gascoigne, J.C. & Lipcius, R.N. (2004) Allee effects driven by predation. Journal of Applied Ecology, 41, 801810. Gilbert, C., McCafferty, D., Le Maho, Y., Martrette, J.M., Giroud, S., Blanc, S. et al. (2010) One for all and all for one: the energetic benefits of huddling in endotherms. Biological Reviews, 85, 545-569. Hirose, Y., Kimoto, H. & Hiehata, K. (1976) The effect of host aggregation on parasitism by Trichogramma papilionis Nagarkatti (Hymenoptera: Trichogrammatidae), an egg parasitoid of Papilio xuthus Linne (Lepidoptera: Papilionidae). Applied Entomology and Zoology, 11, 116-125. Hurlbert, S.H. (1990) Spatial distribution of the montane unicorn. Oikos, 58, 257-271. Jeanson, R. & Deneubourg, J.L. (2007) Conspecific attraction and shelter selection in gregarious insects. The American Naturalist, 170, 47-58. Kouki, J. & Hanski, I. (1995) Population aggregation facilitates coexistence of many competing carrion fly species. Oikos, 72, 223-227. Liu, Q.-X., Herman, P.M.J., Mooij, W.M., Huisman, J., Scheffer, M., Olff, H. et al. (2014) Pattern formation at multiple spatial scales drives the resilience of mussel bed ecosystems. Nature communications, 5, 5234. Møller, A.P. & Legendre, S. (2001) Allee effect, sexual selection and demographic stochasticity. Oikos, 92, 2734. Morisita, M. (1959) Measuring of the dispersion of individuals and analysis of the distributional patterns. Memoires of the Faculty of Science, Kyushu University, Series E. Biology, 2, 215-235. Morisita, M. (1962) I σ-Index, a measure of dispersion of individuals. Researches on Population Ecology, 4, 1-7. Pilastro, A., Benetton, S. & Bisazza, A. (2003) Female aggregation and male competition reduce costs of sexual harassment in the mosquitofish Gambusia holbrooki. Animal Behaviour, 65, 1161-1167. Polis, G. (1980) The effect of cannibalism on the demography and activity of a natural population of desert scorpions. Behavioral Ecology and Sociobiology, 7, 25-35. Reis, S.F.d., Von Zuben, C.J. & Godoy, W.A.C. (1999) Larval aggregation and competition for food in experimental populations of Chrysomya putoria (Wied.) and Cochliomyia macellaria (F.) (Dipt., Calliphoridae). Journal of Applied Entomology, 123, 485-489. Riipi, M., Alatalo, R.V., Lindstrom, L. & Mappes, J. (2001) Multiple benefits of gregariousness cover detectability costs in aposematic aggregations. Nature, 413, 512-514. Valeix, M., Chamaillé-Jammes, S. & Fritz, H. (2007) Interference competition and temporal niche shifts: elephants and herbivore communities at waterholes. Oecologia, 153, 739-748.



Wiens, J.A. (1976) Population responses to patchy environments. Annual Review of Ecology and Systematics, 7, 81-120. Wolda, H. (1981) Similarity indices, sample size and diversity. Oecologia, 50, 296-302.

6.3. DISPERSAL MODE Definition and relevance Dispersal mode is defined as the form of self-directed movements an animal uses to move from one place to another. This definition includes not only self-propelled movement, but also those types of passive dispersal that require an action of the animal. This excludes passive movement by wind. Dispersal mode influences access to new habitat, resources and suitable environments, mates, and shelters, and opportunities to escape adverse environmental conditions (Begon, Townsend & Harper 2009; Clobert et al. 2012). Dispersal mode can be used to infer relative differences in dispersal ability of species (Fuller 1997). For instance, flying or ballooning insects may generally have a larger dispersal rate than crawling or walking invertebrates which may affect their ability to escape adverse effects of climate change (Berg et al. 2010). What and how to measure Dispersal mode is a categorical trait assessed through straightforward field or laboratory observations. Pre-treatment Animals should be described according to the standardisation protocol. How to record dispersal mode? The following five distinct main categories of dispersal mode are distinguished. Species can belong to more than one category. - Walking: Movement of animals using legs, with a constant contact of the legs with the substrate. - Crawling: Movement primarily using the body itself as a propulsive structure, such as found in earthworms, enchytraeids, fly larvae and some beetle larvae. - Jumping: Movement by using adapted jumping organs, such as legs (grasshoppers, crickets and jumping spiders), the abdomen (bristletails) or specialized fork-like appendages (springtails). In some insects jumping distance can be enhanced by stretching but not beating of wings, such as in grasshoppers and leafhoppers resulting in a gliding. - Flying: Movement of animals using wings and wing muscles by which it can increase and maintain altitude, direction and speed. - Ballooning: Individuals (usually of small body size) produce a long thin thread which is taken by wind. Direction and distance of movement depend on air current. Examples are ballooning in spiders and caterpillars (Dean & Sterling 1985; Bell et al. 2005). - Phoresy: Passive movement of an animal by using another animal exclusively for transportation, for instance in mites and pseudoscorpions. Phoretic species actively attach to the vector. Additional notes Animals like aphids and coleopterans may drop of their support (typically, a plant) when threatened directly by predators (Losey & Denno 1998) or indirectly by large herbivores (Gish, Dafni & Inbar 2010). This may result in a speed of movement that is larger than self-propelled movement.



References Begon, M., Townsend, C.R. & Harper, J.L. (2009) Ecology: From Individuals to Ecosystems. Willy. Bell, J.R., Bohan, D.A., Shaw, E.M. & Weyman, G.S. (2005). Ballooning dispersal using silk: world fauna, phylogenies, genetics and models. Bulletin of Entomological Research, 95, 69-114. Berg, M.P., Kiers, E.T., Driessen, G., van der Heijden, M., Kooi, B.W., Kuenen, F., Liefting, M., Verhoef, H.A. & Ellers, J. (2010). Adapt or disperse: understanding species persistence in a changing world. Global Change Biology, 16, 587-598. Clobert, J., Baguette, M., Benton, T.G. & Bullock, J.M. (2012) Dispersal Ecology and Evolution. Oxford University Press. Dean, D.A. & Sterling, W.L. (1985) Size and phenology of ballooning spiders at 2 locations in Eastern Texas. Journal of Arachnology, 13, 111-120. Fuller, R.J. (1997) Invertebrate locomotor systems. Handbook of physiology (ed. W.H. Danzler), Oxford University Press. Gish, M., Dafni, A. & Inbar, M. (2010) Mammalian herbivore breath alerts aphids to flee host plant. Current Biology, 20, 628-629. Losey, J.E. & Denno, R.F. (1998) The escape response of pea aphids to foliar-foraging predators: factors affecting dropping behaviour. Ecological Entomology, 23, 53-61.

6.4. LOCOMOTION SPEED Definition and relevance Locomotion speed is the pace of self-propelled movement of an organism. The quantification of locomotive speed provides important insight into an organisms’ ability to perform a range of behaviours critical for survival, including foraging, predator avoidance (Hatle & Grimké Faragher1998; Irschick & Garland 2001; Ings & Chittka 2008), and avoidance of stressful conditions through microhabitat seeking. Species-specific locomotion speed depends on the morphology of locomotion organs (e.g. wing loading or leg length) (Hern & Dorn 1999). Intraspecific variation in locomotion speed may exists across the distribution range of a species, as dispersive phenotypes are often more abundant at range margins (Thomas et al. 2001). Evolutionary theory predicts tradeoffs between locomotion and fecundity or competitive ability (Zera & Denno 1997; Samietz & Kohler 2012). Locomotion speed is also linked to the evolution of sensory systems, as animals that obtain higher speeds of locomotion generally have higher temporal resolution in the visual system (Laughlin & Weckström 1993). What and how to measure Methods to measure actual locomotion speed depend on the locomotion mode of species. We describe three separate methods for walking/crawling, jumping and flying organisms. We recommend publishing the experiment environmental conditions together with values for movement speed. Pre-treatment Animals should be described and acclimatized according to the standardisation protocol. How to measure walking speed? A narrow elongated arena can be used for animals that move by walking and crawling. Locomotion speed is calculated as the distance covered on the arena in a single continuous linear movement divided by the movement time. The length of the arena should be adapted to the locomotion mode and expected speed of the focal species. We recommend using an arena width approximately twice the body width of the focal species.



Place the animal at one edge of the arena where the animal can accustom to the arena substrate. Start the measurement by letting the animal walk along the arena and record the time until the animal reaches the opposite side or until the animal stops movement spontaneously. For a reliable estimate of locomotion speed we recommend to only use the movement bouts where the animal moved continuously for a minimum of 10 seconds. If the animal ceases movement before 10 seconds has passed, the animal should be taken of the arena and retested after a short rest. We recommend obtaining measurements from a large number of replicates (three at least) for a minimum of 10 individuals. The environmental conditions should be constant during the entire measurement, with light conditions similar to those expected during the natural activity time of the focal animal. The arena should be cleaned with a humid cloth (use distilled water) after each race to remove possible olfactory and visual traces. How to measure jumping distance? A squared or round arena can be used for jumping animals. Locomotion speed is calculated as the distance covered by a single jump divided by the time from take-off to landing. The distance covered is the linear distance between site of take-off and landing. This can either be located by direct observation or using automated imagebased video tracking systems (Noldus, Spink & Tegelenbosch 2002; Pennekamp & Schtickzelle 2013; Dell et al. 2014) placed perpendicular above the arena. Preparation and cleaning of the arenas, as well as recommended number of measurements are similar to those for walking/crawling animals. How to measure flight speed? Flight mills allow the measurement of locomotion speed for flying insects. Locomotion speed is calculated as the number of revolutions multiplied by the distance covered in a single revolution on the flight mill in a single continuous flight bout, divided by the movement time. Individual insects should be tethered to the flight mill. Depending on the species this can be done by e.g. using an insect pin of which the head is glued to the back of the insect thorax (Schumacher et al. 1997), or by gluing a human hair to the animals thorax (Kaufmann, Reim & Blanckenhorn 2013). Importantly, while preparing the tethered insect it should preferably be held in place with a commercial vacuum pressure on organdy mesh under a microscope. This technique is preferred over cooling or anesthesia with CO2 because it has no known physiological effects ( Schumacher et al. 1997). Time of flight initiation and cessation, as well as the number of mill revolutions within a given time of assay period are recorded by a software system. Additional notes Recent advances in automatic image analysis allows to consider whole movement paths e.g., automatic high speed video (Irschick & Losos 1998; Van Dam, Williams & Taylor 2000; Vanhooydonck & Van Damme 2001). In the field, both harmonic and vertical-looking radar have been used to estimate locomotion traits in the field for a range of taxa including bees, butterflies, flies, beetles and moths (Chapman, Drake & Reynolds 2011; Chapman et al. 2012; Bell et al. 2013; Reynolds, Nau & Chapman 2013). References Bell, J.R., Aralimarad, P., Lim, K.S. & Chapman, J.W. (2013) Predicting insect migration density and speed in the daytime convective boundary layer. PLoS ONE 8, e54202. Chapman, J.W., Bell, J.R., Burgin, L.E., Reynolds, D.R., Pettersson, L.B., Hill, J.K. et al. (2012) Seasonal migration to high latitudes results in major reproductive benefits in an insect. Proceedings of the National Academy of Sciences of the United States of America, 109, 14924-14929. Chapman, J.W., Drake, V.A. & Reynolds, D.R. (2011) Recent insights from radar studies of insect flight. Annual Review of Entomology, 56, 337-356.



Dell, A.I., Bender, J.A., Branson, K., Couzin, I.D., de Polavieja, G.G., Noldus, L.P.J.J. et al. (2014) Automated image-based tracking and its application in ecology. Trends in Ecology & Evolution, 29, 417-428. Hatle, J.D. & Grimké Faragher, S. (1998) Slow movement increases the survivorship of a chemically defended grasshopper in predatory encounters. Oecologia, 115, 260–267. Hern, A. & Dorn, S. (1999) Sexual dimorphism in the olfactory orientation of adult Cydia pomonella in response to alpha-farnesene. Entomologia Experimentalis Et Applicata, 92, 63-72. Ings, T.C. & Chittka, L. (2008) Speed-accuracy tradeoffs and false alarms in bee responses to cryptic predators. Current Biology, 18, 1520–1524. Irschick, D.J. & Garland, T. (2001) Integrating function and ecology in studies of adaptation: Investigations of locomotor capacity as a model system. Annual Review of Ecology and Systematics, 32, 367-396. Irschick, D.J. & Losos, J.B. (1998) A comparative analysis of the ecological significance of maximal locomotor performance in Caribbean Anolis lizards. Evolution, 52, 219-226. Kaufmann, C., Reim, C. & Blanckenhorn, W.U. (2013) Size-dependent insect flight energetics at different sugar supplies. Biological Journal of the Linnean Society, 108, 565–578. Laughlin, S.B. & Weckström, M. (1993) Fast and slow photoreceptors - a comparative study of the functional diversity of coding and conductances in the diptera. Journal of Comparative Physiology A, 172, 593–609. Noldus, L.P.J.J., Spink, A.J. & Tegelenbosch, R.A.J. (2002) Computerised video tracking, movement analysis and behaviour recognition in insects. Computers and electronics in agriculture, 35, 201-227. Pennekamp, F. & Schtickzelle, N. (2013) Implementing image analysis in laboratory-based experimental systems for ecology and evolution: a hands-on guide. Methods in Ecology and Evolution, 4, 483-492. Reynolds, D.R., Nau, B.S. & Chapman, J.W. (2013) High-altitude migration of Heteroptera. European Journal of Entomology, 110, 483-492. Samietz, J. & Kohler, G. (2012) A fecundity cost of (walking) mobility in an insect. Ecology and Evolution,2, 2788-2793. Schumacher, J., Weyeneth, A., Weber, C.D. & Dorn, S. (1997) Long flights in Cydia pomonella L. (Lepidoptera: Tortricidae) measured by a flight mill: influence of sex, mated status and age. Physiological Enthomology, 22, 149-160. Thomas, C.D., Bodsworth, E.J., Wilson, R.J., Simmons, A.D., Davies, Z.G., Musche, M. et al. (2001) Ecological and evolutionary processes at expanding range margins. Nature, 411, 577-581. Van Dam, W.A., Williams, R.N. & Taylor, R.A.J. (2000) Flight performance of some nitidulid beetles (Coleoptera) using a computer-monitored flight mill. Journal of Agricultural and Urban Entomology,17, 143-151. Vanhooydonck, B. & Van Damme, R. (2001) Evolutionary trade-offs in locomotor capacities in lacertic lizards: are splendid sprinters clumsy climbers? Journal of Evolutionary Biology,14, 46-54. Zera, A.J. & Denno, R.F. (1997) Physiology and ecology of dispersal polymorphism in insects. Annual Review of Entomology, 42, 207-231.

6.5. SOCIALITY Definition and relevance Sociality is the tendency of individuals of the same species to live in groups and display reciprocal, cooperative behaviour (Wilson 1975). Sociality has important consequences in terms of reproduction, foraging, defence against predators and kin recognition (Croft, Darden & Ruxton 2009). For example, social spiders forming large colonies tend to catch larger prey (Guevara et al. 2011). Furthermore, sociality might allow otherwise similar species to use different resources and have different reproduction period and, thereby, to coexist in the same habitat (Purcell et al. 2012). Also, based on their high total biomass, social taxa have high impact on ecological _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


processes in the ecosystems and underlying services (e.g. pollination by social bees or pest-control by ants). Finely, sociality affects the evolution of a wide range of behavioural, morphological and life history traits (Krause & Ruxton 2002). What and how to measure Sociality is a categorical trait depending on the degree to which a species forms cooperative societies. It can be observed in the field or under the more controlled conditions in the laboratory. Since sociality can be influenced by elevation, habitat characteristics, disturbance (e.g. fire or floods), we recommend observations on sociality across a broad range of environmental conditions. Pre-treatment A pre-treatment is not necessary. How to measure sociality? The following six categories of sociality are distinguished along a gradient of increasing sociality level ranging from solitary species to eusocial species (Wilson 1971; Costa & Fitzgerald 2005; Schwarz, Richards & Danforth 2007): - Solitary: Animals do not associate with other of their species, except for mating. This category also includes social aggregation where individuals live or sleep in groups but do not share a common nest site (see Aggregation protocol). Many invertebrates belong to this category. - Subsocial: Parents care for their young for some length of time but do not share a nest site with other parents. Examples of species with brood care are some carrion beetles, earwigs and some centipede species. - Communal: Animals share a common nest site and cohabitation of adults occurs but each parent cares for their own young. Examples are bees belonging to the family Halictidae (sweat bees). - Quasisocial: Animals share a common nest site, cohabitation of adults their young occurs and cooperative brood care occurs. Examples are many bee species belonging to the subfamily Xylocopinae (carpenter bees). - Semisocial: Animals share a common nest site, cohabitation of adults and their young, cooperative brood care and a reproductive division of labor with effectively sterile worker castes. Examples are some bee species belonging to the family Halictidae (sweat bees). - Eusocial: Animals share a common nest site, in which adults and their young cohabitate. Adults show cooperative brood care, and a reproductive division of labor with effectively sterile worker castes and overlapping generations. Among others, termites, bumblebees and ants belong to this category. Additional notes Certain species change categories of sociality during ontogeny or as a function of their environments as observed for sweat bees (Halictus rubicundus) (Chapuisat 2010). In those cases we recommend reporting each category with the associated life stage or environment. Recently a quantitative index of sociality was developed by Avilés & Harwood (2012). This index requires observations on multiple social groups as well as individuals within groups which might be costly and time consuming, therefore we do not include this method in the handbook. However, in some cases this quantitative measure of sociality may be more suitable to study correlations between sociality and other aspects of a species’ biology. References Avilés, L. & Harwood, G. (2012) A quantitative index of sociality and its application to group-living spiders and other social organisms. Ethology, 118, 1219-1229. Chapuisat, M. (2010) Evolution: plastic sociality in a sweat bee. Current Biology, 20, R977-R979. _________________ If using, please cite as: Moretti, M., Dias, A.T.C., de Bello, F., Altermatt, F., Chown, S.L., Azcárate, F.M., Bell, J.R., Fournier, B., Hedde, M., Hortal, J., Ibanez, S., Öckinger, E., Sousa, J.P., Ellers, J. and Berg, M.P. (2016), Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits. Functional Ecology doi:10.1111/1365-2435.12776


Costa, J.T. & Fitzgerald, T.D. (2005) Social terminology revisited: where are we ten years later? Annales Zoologici Fennici, 42, 559-564. Croft, D.P., Darden, S.K. & Ruxton, G.D. (2009) Predation risk as a driving force for phenotypic assortment: a cross-population comparison. Proceedings of the Royal Society B: Biological Sciences, 276, 1899-1904. Guevara, J., Gonzaga, M.O., Vasconcellos-Neto, J. & Avilés, L. (2011) Sociality and resource use: insights from a community of social spiders in Brazil. Behavioral Ecology, 22, 630-638. Krause, J. & Ruxton, G.D. (2002) Living in groups. Oxford University Press Oxford. Purcell, J., Vasconcellos-Neto, J., Gonzaga, M.O., Fletcher, J.A. & Avilés, L. (2012) Spatio-temporal differentiation and sociality in spiders. PLoS ONE, 7, e34592. Schwarz, M.P., Richards, M.H. & Danforth, B.N. (2007) Changing paradigms in insect social evolution: insights from halictine and allodapine bees. Annual Review of Entomology, 52, 127-150. Wilson, E.O. (1971) The insect societies. Harvard University Press, Cambridge. Wilson, E.O. (1975) Sociobiology - The New Synthesis. Belknap Press of Harvard University Press, Cambridge.

6.6. ANNUAL ACTIVITY RHYTHM Definition and relevance Annual activity rhythm can be defined as the annual distribution of the active and dormant periods of individuals in a population. The transition between activity and dormancy is usually controlled by a combination of environmental cues (temperature, photoperiod, light intensity, drought) and endocrine regulation (Tauber & Tauber 1976; Wolda 1988). General patterns in annual activity rhythms have been described for different climates and groups of organisms (Wolda 1988). Annual activity rhythm is closely related to other invertebrate life history traits, such as life span, development mode, voltinism and age of maturity (Martin-Vertedor, FerreroGarcia & Torres-Vila 2010; Soendgerath, Rummland & Suhling 2012). The adaptive significance of dormant and activity periods is the avoidance of adverse or lethal abiotic conditions, but biotic factors like predation risk or food availability also play a role (Powell & Logan 2005; Freire et al. 2014). Different annual activity periods can influence the outcome of interspecific competition within communities (Wolda 1988; Gidoin, Roques & Boivin 2015). Annual activity rhythm is also considered a key trait in the response of populations and communities to climate change (Martín-Vertedor et al. 2010; Soendgerath, Rummla & Suhling 2012). What and how to measure Annual activity rhythm is of ecological and evolutionary importance for invertebrates, but no good protocol is available in the literature how to measure annual activity rhythm. Therefore, we propose to measure two aspects of annual activity rhythm: dormancy occurrence and duration. This trait cannot be measured under standardized laboratory conditions since the annual activity rhythm depends on seasonality of (a)biotic variables. Therefore, measurements of annual activity rhythm must rely on field observations. - Dormancy occurrence: (Yes/No/Facultative) Detectable as a period in which no activity predominates. Dormancy occurrence should be observed in at least 50% of the tested individuals. The dormant period can include sporadic days or even sub-periods with some activity, but will be considered as a part of the dormant period if the size (number of days) of the active sub-period is smaller than the size of the inactive sub-periods around it. - Dormancy duration: The period over which dormancy occurs measured in weeks (numbered according to annual week numbers) when at least 50% of the observed individuals shows dormancy.



Pre-treatment A pre-treatment is not necessary. How to record annual activity rhythm? Ideally, annual activity rhythm should be described on a weekly basis. Activity includes various processes such as moving, flying, hunting, foraging and thermoregulation, and can be measured by surveying a population on a fixed location throughout the year. Surveys should integrate multiple sampling methods (e.g., trapping devices, soil core sampling, hand collection or direct observations of active individuals) in order to minimize biases given by the probability to observe or sample an individual. Absence of individuals in traps and samples during certain periods of the year can be used with great precaution as an indirect evidence for dormancy in the population. However, the best evidence for dormancy is to actually observe dormant animals. This is verified by the lack of a behavioural response when touching or stimulating the animals. Additional notes In many species there exists a strong intraspecific segregation of the temporal niche between adults and larvae. We recommend an independent characterization of the annual activity rhythm of the different development stages when this is the case. For very long lived species, a sample of different ages should be observed for the estimation of the activity profile. If very different patterns are observed for different ages, independent characterization can be considered. The observation of activity in cryptic, burrowing, soil dwelling animals, etc. can require specific devices, and the simulation of seasonality can be particularly challenging. A case by case adaptation of the protocol can be necessary for these animals and should be published together with annual activity rhythm values. In social insects, the colony is more adequate than the individual as observation unit. We recommend monitoring several colonies to measure the intensity of the activity (Azcárate, Kovacs & Peco 2007), instead of different individuals of the same colony. References Azcárate, F.M., Kovacs, E. & Peco, B. (2007) Microclimatic conditions regulate surface activity in harvester ants Messor barbarus. Journal of Insect Behavior, 20, 315-329. Freire, G. Jr., Nascimento, A.R., Malinov, I.K. & Diniz, I.R. 2014. Temporal Occurrence of Two Morpho Butterflies (Lepidoptera: Nymphalidae): Influence of Weather and Food Resources. Environmental Entomology, 43, 274-282. Gidoin, C., Roques, L. & Boivin, T. (2015) Linking niche theory to ecological impacts of successful invaders: insights from resource fluctuation-specialist herbivore interactions. Journal of Animal Ecology, 84, 396406. Martín-Vertedor, D., Ferrero-Garcia, J.J. & Torres-Vila, L.M. (2010) Global warming affects phenology and voltinism of Lobesia botrana in Spain. Agricultural and Forest Entomology, 12, 169-176. Powell, J.A. & Logan, J.A. 2005. Insect seasonality: circle map analysis of temperature-driven life cycles. Theoretical Population Biology, 67, 161-179. Soendgerath, D., Rummland, J. & Suhling, F. (2012) Large spatial scale effects of rising temperatures: modelling a dragonfly's life cycle and range throughout Europe. Insect Conservation and Diversity, 5, 461-469. Tauber, M.J. & Tauber, C.A. (1976) Insect seasonality: Diapause maintenance, termination, and postdiapause development. Annual Review of Entomology, 21, 81-107. Wolda, H. (1988) Insect Seasonality: Why? Annual review of Ecology, Evolution, and Systematics, 19, 1-18.


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