Behavioral Ecology Advance Access published April 16, 2015
Behavioral Ecology
The official journal of the
ISBE
International Society for Behavioral Ecology
Behavioral Ecology (2015), 00(00), 1–11. doi:10.1093/beheco/arv036
Original Article
Personality-related survival and sampling bias in wild cricket nymphs Petri T. Niemelä,a Ella Z. Lattenkamp,a and Niels J. Dingemansea,b aBehavioral Ecology, Department of Biology, Ludwig-Maximilians University of Munich, Großhaderner Str.2, 82152 Planegg-Martinsried, Germany and bEvolutionary Ecology of Variation Group, Max Planck Institute for Ornithology, Eberhard-Gwinner-Str., 82319 Seewiesen, Germany Received 9 October 2014; revised 5 March 2015; accepted 10 March 2015.
The study of adaptive individual behavior (“animal personality”) focuses on whether individuals differ consistently in (suites of correlated) behavior(s) and whether individual-level behavior is under selection. Evidence for selection acting on personality is biased toward species where behavioral and life-history information can readily be collected in the wild, such as ungulates and passerine birds. Here, we report estimates of repeatability and syndrome structure for behaviors that an insect (field cricket; Gryllus campestris) expresses in the wild. We used mark-recapture models to estimate personality-related survival and encounter probability and focused on a life-history phase where all individuals could readily be sampled (the nymphal stage). As proxies for risky behaviors, we assayed maximum distance from burrow, flight initiation distance, and emergence time after disturbance; all behaviors were repeatable, but there was no evidence for strong syndrome structure. Flight initiation distance alone predicted both daily survival and encounter probability: bolder individuals were more easily observed but had a shorter life span. Individuals were also somewhat repeatable in the habitat temperature under which they were assayed. Such environment repeatability can lead to upward biases in estimates of repeatability in behavior; this was not the case. Behavioral assays were, however, conducted around the subject’s personal burrow, which could induce pseudorepeatability if burrow characteristics affected behavior. Follow-up translocation experiments allowed us to distinguish individual and burrow identity effects and provided conclusive evidence for individual repeatability of flight initiation distance. Our findings, therefore, forcefully demonstrate that personality variation exists in wild insects and that it is associated with components of fitness. Key words: animal personality, boldness, fitness, invertebrate, sampling bias, survival.
Introduction Animal personality research, the study of among-individual differences in behavior, represents a major current topic in the field of behavioral ecology (Dall et al. 2004; Dingemanse and Wolf 2010; Sih et al. 2012; Wolf and Weissing 2012). Empirical research over the last decade has revealed that animal behavior shows considerable individual repeatability within single populations (Bell et al. 2009), that distinct behaviors are often associated in syndromes (Garamszegi et al. 2012), and that genetic correlation structures underpinning such behavioral syndrome structure (Dochtermann 2011) potentially constrains adaptive evolution (Dochtermann and Dingemanse 2013). Theoreticians have proposed various adaptive explanations for why personality might exist (reviewed by Dingemanse and Wolf 2010; Luttbeg and Sih 2010; Wolf and Weissing 2010; Sih et al. 2015), and empiricists increasingly study associations between personality and life history (Stamps 2007; Biro and Stamps 2008; Réale et al. 2010) to reveal how selection acts on Address correspondence to P.T. Niemelä. E-mail:
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this type of variation (reviewed by Dingemanse and Réale 2005, 2013; Réale et al. 2007; Smith and Blumstein 2008). Despite growing recognition that personality may interact with ecological and evolutionary processes (Sih et al. 2012; Wolf and Weissing 2012), relatively few studies have evaluated patterns of selection acting on personality variation directly in the wild (Dingemanse and Réale 2013). Research on the adaptive nature of among-individual variation in behavior has primarily focused on so-called “risky behaviors” (Stamps 2007; Wolf et al. 2007; Biro and Stamps 2008; Réale et al. 2010), that is, behavioral traits such as aggressiveness, activity, boldness, or exploratory tendency that facilitate resource acquisition at the cost of increased risk of mortality (Dingemanse and Wolf 2010). Life-history theory predicts that alternative strategies exist as to how trade-offs between investment in current versus future reproduction is resolved (Stearns 1989). Concurrently, adaptive personality theory explains risky personality as a coadaption to life-history strategy (Stamps 2007; Wolf et al. 2007). Specifically, individuals with relatively high future fitness expectations (i.e., high residual reproductive value) should behave relatively cautiously
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(Dingemanse and Wolf 2010). Indeed, experimental evidence from wild bird populations supports this prediction (Nicolaus et al. 2012). Theory predicts that bold, active, or explorative individuals consequently invest more heavily in resource acquisition at the cost of increased risk of mortality (Stamps 2007), predation (Kortet et al. 2010), or parasitization (Barber and Dingemanse 2010). Even though above-mentioned behaviors have frequently been linked to survival, and empirical evidence appears to support theory (review: Smith and Blumstein 2008), personality-related differences in longevity (i.e., survival) have rarely been estimated in the wild (review: Dingemanse and Réale 2013). Moreover, the existing empirical research on the effects of personality on survival comes from few well-studied model species such as ungulates and passerine birds (with somewhat mixed results; Dingemanse et al. 2004; Boon et al. 2007; Quinn et al. 2009; Réale et al. 2009). There is growing awareness that both the expression of personality and selection pressures acting on this variation may vary distinctly between laboratory and natural populations (Herborn et al. 2010; Niemelä and Dingemanse 2014). Consequently, both personality and its fitness consequences should best be studied under natural conditions to avoid biased interpretation of how selection acts on this variation in nature. This represents a challenging task for various reasons. First, personality is defined as differences in average behavior of individuals over repeated observations (cf. Dingemanse and Dochtermann 2013); such repeated measures data are difficult to collect in the wild. Second, estimates of personality derived from the wild might often represent “pseudopersonality” (sensu Westneat et al. 2011). Pseudopersonality occurs when environmental conditions influencing the phenotype within individuals vary among sampled individuals—a common situation in field studies (where animals are typically assayed in their habitat of choice; Martin and Réale 2008; Westneat et al. 2011). The amount of among-individual variance (hence repeatability) would be overestimated if this bias was ignored (Westneat et al. 2011; Dingemanse and Dochtermann 2013). Third, individuals often differ in capture, detection, and postrelease encounter probability; there is increasing evidence for sampling bias toward active, aggressive, or bold individuals (Biro and Dingemanse 2009; Biro 2013; Stuber et al. 2013). Such effects likely bias both estimates of individual repeatability and selection acting on this variation. In this article, we report estimates of repeatability and syndrome structure among a number of behavioral traits indicative of risky behavior (activity, maximum distance from burrow, flight initiation distance [FID], postdisturbance emergence time) in a wild insect population. This study thereby helps alleviate bias in our knowledge of personality structure in the wild because most empirical studies to date focus on birds, mammals, or fish (meta-analysis: Bell et al. 2009; Garamszegi et al. 2012). Much of the work on personality structure has been conducted under the laboratory conditions, including work with close relatives of our model species (Kortet and Hedrick 2007; Wilson, Whattam, et al. 2010; Niemelä, Vainikka, Hedrick, et al. 2012; Niemelä, Vainikka, Lahdenpera, et al. 2012). We studied the European field cricket (Gryllus campestris), a flightless annual insect that is extremely common within much of its range, and inhabits meadows where it is easily observed (Rodríguez-Muñoz et al. 2011). Field crickets hatch from eggs in summer (June–July) and hibernate as nymphs in closed burrows (October–March) (Ritz and Köhler 2007). We studied near-final instar nymphs that emerged from their burrows in early spring (during April in 2013) and followed them for the remainder of their lives (ca. 2 months).
Cricket nymphs emerging in spring are stationary, staying in close proximity of their burrow. We assayed cricket nymphs in their natural habitat every other day during their entire postwinter nymphal life, enabling us to determine long-term repeatability of risky behavior. Cricket behavior, however, can vary strongly as a function of temperature (Loher and Wiedenmann 1981; Pires and Hoy 1992; Martin et al. 2000); we, therefore, measured habitat temperature during every observation and investigated the occurrence of pseudopersonality by 1) assessing whether average habitat temperatures differed among habitats surrounding individual burrows and 2) estimating the extent to which among-individual variance in behavior was biased by among-individual variance in habitat temperature during the behavioral assay (Westneat et al. 2011; Dingemanse and Dochtermann 2013). We observed each burrow for a fixed amount of time per day over the entire season and recorded daily whether the focal individual was encountered or not. We then estimated each individual’s average behavioral value (“personality”) and used mark-recapture models to simultaneously estimate personality-related daily survival probabilities while controlling for personality-related encounter probabilities. We expected that risky behavioral types would enjoy a higher encounter probability (Biro and Dingemanse 2009; Biro 2013) but suffer reduced survival because of their increased vulnerability to predation and parasitism (Stamps 2007; Smith and Blumstein 2008; Barber and Dingemanse 2010).
Methods The experiments were conducted at the Max Planck Institute for Ornithology (Seewiesen, southern Germany: 47°58′35.5″N, 11°14′04.5″E), from April through July in 2013. Prior to the onset of the experiment, we fenced off a 10 m × 12 m area of suitable habitat. Nymphs emerging in early spring stay in close proximity of their burrow (max. ~10–20 cm distance) until they reach maturation (Rodríguez-Muñoz et al. 2011). Crickets can easily be trapped, marked, and their daily behavior recorded (Rodríguez-Muñoz et al. 2011). They thus represent an ideal model for studying personality-related longevity. We trapped and marked all individuals that emerged in the study area (n = 24). Individuals were marked with a small circular numbered and colored mark (2.8 mm in diameter). This enabled us to identify each individual with binoculars.
Behavioral data collection A single observer (P.T.N.) assayed the 4 different behavioral traits in the field: 1) baseline activity, 2) furthest distance from the burrow during an observation, 3) escape distance from an approaching observer, and 4) latency to emerge from the burrow following the disturbance. We refer to these variables as activity, maximum distance, FID, and emergence time, respectively, throughout the remaining text. Following Réale et al. (2007), the first variable was considered a measure of activity, whereas the latter 3 were considered measures of boldness. All behavioral assays were taken prior to adulthood (between 09h00 and 17h00; 3–23 May 2013) and in randomized order each day. Each burrow was subjected to 2 assays once every other day, one during the morning (9h00–12h00) and one during the afternoon (13h00–17h00). A focal trial began with the observer carefully approaching a focal pole (20 cm in height) that was positioned 120 cm in front of the entrance of the focal burrow. One such pole was fitted in front of every burrow, and poles approached such that the subject was not disturbed. The subsequent assay consisted of 3 parts. First,
Niemelä et al. • Personality-related survival and sampling bias
we monitored the subject’s activity for 300 s by recording the total amount of time (in s) spent moving. During this time, we also noted the maximum distance (in cm) between the subject and the entrance of its burrow. If the subject was not observed within this time period (300 s), the assay was terminated and the subject recorded as “not encountered”. For such cases, the behavioral data were regarded as “missing” because we did not know whether the individual was inside its burrow or outside (out of view) in the vegetation. Second, FID was measured directly afterward. For this, we used a 150-cmlong wooden, circular stick with a diameter of 1 cm. The observer tapped the stick on the ground (approximate frequency: 2 taps/s) while moving it toward the burrow at a stable speed (approximately 10 cm/s); at the same time, the observer remained stationary at the pole (120 cm away from the burrow). This “tapping” procedure was used because pilot experiments showed that the crickets responded primarily to moving objects that cause vibrations and visual stimulation (such as Mistle trush, Turdus pilaris, birds that were typically observed hopping through the vegetation while hunting for crickets; Niemelä PT, personal observation). Crickets are also preyed on by other ground predators like shrews, other birds, and insects (Rodríguez-Muñoz et al. 2010, 2011). FID was defined as the distance (in cm) between the tip of the stick and the burrow entrance at the time at which the cricket initiated its escape. Third, we measured the time (in s) that it took the subject to emerge fully from its burrow after the disturbance. Habitat temperature (to the closest 0.1 °C; TFA Dostmann digital thermometer, Germany) was measured at the focal pole (120 cm from the burrow) at the onset of the trial. A total number of 310 behavioral assays were conducted; 33 assays were excluded from the data set either because we failed to observe the subject (see above), failed to read its identity tag, or because the assay was prematurely terminated due to bad weather. The remaining 277 assays (89.4%) provided us with 12.04 repeated observations per subject (n = 23 of 24 marked individuals; 1 individual died prior to the behavioral trials). Seventeen (6%) of these assays had missing data in 1 of the 4 recorded variables. This combination of sample size of individuals and repeated measurements per individual resulted in sufficient power (≥0.8) to detect repeatabilities above 0.10 (see Fig. 3 in Dingemanse and Dochtermann 2013) and among-individual correlations (i.e., syndrome structure) above 0.5 (see Fig. 1 in Dingemanse and Dochtermann 2013).
Encounter data Encounter data were collected daily by a single observer (P.T.N.) between 08h00 and 09h00, that is, prior to the behavioral assays of a focal day. Daily encounter data were collected from 2 May 2013 to 8 July 2013, that is, throughout nymphal and adult life. For a number of days (n = 13) in this 67-day period, no data were collected due to bad weather (when all the crickets would be inside their burrows; typically due to heavy rain), resulting in a total of 54 days with encounter data. The procedure consisted of carefully moving, in a randomized order per day, from burrow to burrow and checking (with binoculars) the identity of each cricket that was observed from the pole located 1.20 m from the burrow (see above). Each burrow was monitored for 60 s; if the focal subject was observed versus not observed in this time, it was noted as “encountered” versus “not encountered,” respectively. At the end of the season, we encountered 2 (adult) individuals that had lost their identity tags as adults and gave them new identity tags; we could not assign identities of these individuals with certainty and therefore removed this data (n = 5 encounter observations in total) from our data set.
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Post hoc translocation experiment In spring 2014, we conducted a translocation experiment aimed at separating effects of individual and burrow identity on FID. We focused on FID alone because this was the only repeatable behavioral trait that explained survival and encounter probability in the primary experiment (see Results). The experiment was conducted between 6 and 16 May in a field adjacent to the study site described for the primary experiment. Prior to the onset of this experiment, we enclosed 69 occupied burrows with a circular (radius 30 cm) and transparent plastic fence of a height of 25 cm as part of another experiment. Twenty of the enclosed 69 adult crickets (age 1–3 weeks after maturation) were randomly chosen and used for the translocation experiment. Those individuals were assayed for their FID prior to translocation, once on each of 2 days (6 and 8 May). All individuals were then translocated to a randomly chosen burrow previously occupied by another cricket. We translocated 20 crickets on 10 May and subsequently assayed them for their FID twice again in the introduced burrows (once on each of 2 days; 12 and 15 May). We used the same methodology as detailed in the methods for the primary experiment. A total number of 80 behavioral assays were conducted; in 9 of these 80 behavioral assays, the cricket was not observed, and these data were therefore not included in the analyses.
Statistical analyses Sources of variation in behavior We applied a mixed-effect modeling framework to estimate sources of variation in behavior within and among individuals (following Dingemanse and Dochtermann 2013). We used a 2-step approach. First, we investigated sources of variation in each of the 4 focal behaviors separately. We thus constructed 4 univariate mixed-effect models (one for each behavior; Table 1). Random intercepts were included for individual identity and date, enabling us to partition the total variance into variance attributable to individual, date, and residual. Sex (factor: male vs. female), time of day (factor: morning vs. afternoon trial), test sequence (covariate; within-individual test-day number; first test day, second test day, third test day, etc.), and habitat temperature (covariate; °C) were fitted as fixed effects. Those fixed effects were included to control for variation introduced by the experimental design that could otherwise bias our estimates of among-individual variance and individual repeatability (Westneat et al. 2011; Dingemanse and Dochtermann 2013). Individual repeatability estimated as the among-individual variance divided by the total variance not attributable to fixed effects thus represented the “adjusted” repeatability (Nakagawa and Schielzeth 2010). Importantly, we considered that effects of habitat temperature, and test sequence, could vary within versus among individuals (van de Pol and Wright 2009). For example, within-individual changes in behavior with test sequence are caused by the combined effects of habituation, learning, seasonal changes, and aging (e.g., Martin and Réale 2008; Dingemanse, Bouwman, et al. 2012), where among-individual effects of test sequence also include effects of personality-related sampling bias or selective disappearance (van de Pol and Verhulst 2006). Similarly, within-individual changes in behavior with habitat temperature imply within-individual phenotypic plasticity in response to temperature (or its correlates) (sensu van de Pol and Wright 2009; Westneat et al. 2011), whereas among-individual effects of habitat temperature are also attributable to repeatable spatial variation in vegetation patterns, altitude, etc. Following van de Pol and Wright (2009), we therefore calculated 1) each individual’s average value for
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Table 1 Sources of variation in (a) maximum distance, (b) activity, (c) FID, and (d) emergence time (a) Maximum distance
(b) Activity
β (SE)
FNUMdf, DENdf
P
β (SE)
Intercept Sexb Time of dayb Test sequence Within individuals Among individuals Δ (among − within) Temperature Within individuals Among individuals Δ (among − within)
0.193 (0.208) 0.076 (0.268) −0.521 (0.098)
0.001,23.9 0.081,19.4 28.031,234.4
0.960 0.780
