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Chapter 3

Environmental Indicators of Climate Change: Phenological Aspects Anders Pape Møller Abstract Recent climate change has caused an increase in mean temperature on earth by 0.8 C during the last century with spatially heterogeneous change. Patterns of precipitation, wind and extreme weather have likewise changed considerably. These changes have prompted an enormous interest in the potential impact of climate change (and other components of global change) on all living beings. Environmental indicators of climate change should be easy to apply, consistent over time and space, reliable, and informative. The biological impact of climate change has been assessed with the help of environmental indicators such as change in phenology and change in distribution. Indicators of change in phenology include advanced spring arrival date of migratory birds, advanced first date of singing by birds and advanced first flowering date of plants in response to change in temperature. Indicators of change in distribution include change in the northernmost range limit of butterflies and birds. While there is a huge literature on responses to climate change, there is little assessment of the indicator ability of different biological responses to climate change. Here I briefly review environmental indicators of climate change; rank the response of different species in terms of their indicator ability; test for consistency in indicator ability over time; and test for consistency in indicator ability among indicators. Finally, I provide a list of research areas in need of further development. Keywords Birds • Climate change • Phenology • Plants • Range expansion • Repeatability

3.1

Introduction

Climate change has been dramatic during the last three decades with particularly strong responses at high latitudes (IPCC 2007). Climate change has been measured as increased temperature, increasingly extreme temperatures, change in precipitation, change in wind speed and patterns, and change in frequency of storms A.P. Møller (*) Laboratoire d’Ecologie, Syste´matique et Evolution, CNRS UMR 8079, Universite´ Paris-Sud, Bâtiment 362, F-91405 Orsay Cedex, France e-mail: [email protected] © Springer Science+Business Media Dordrecht 2015 R.H. Armon, O. Ha¨nninen (eds.), Environmental Indicators, DOI 10.1007/978-94-017-9499-2_3

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(IPCC 2007). All these changing climatic factors may directly or indirectly affect the distribution and the abundance of animals and plants either through effects on food or effects on interacting species (reviews in Møller et al 2010; Parmesan 2006; Parmesan and Yohe 2003; Root et al 2003), with weaker responses at higher trophic levels in the ecosystem (Thackeray et al 2010). While climatic factors can be measured directly, there is also good reason to measure biological responses to climate change because such responses may reflect the ability of organisms to cope with changing environmental conditions. Such responses may affect the prospects of maintaining viable populations and ultimately communities and ecosystems. Humans may be directly or indirectly impacted by such changes in natural ecosystems through agriculture, forestry and fisheries, but also through changes in the frequency and the distribution of infectious diseases of domestic animals and humans themselves. Responses to climate change are based on decisions by individuals at particular sites. Individuals are the main units of selection, because individuals either die or survive, and because individuals through their reproduction differentially contribute to the nest generation. However, responses to climate change are rarely studied at the level of individuals, but instead typically studied at the population, species or ecosystem levels. As a rare example of the individual-based approach to study responses to climate change Møller (2008a) showed that individual barn swallows Hirundo rustica differed in their response to increasing spring temperatures at individual breeding sites. While barn swallows at some sites advanced their breeding phenology considerably during the last 30 years, breeding date barely changed or was even delayed at phenologically late breeding sites. However, overall across all sites there was a significant advancement in time of breeding. Thus it is the combined response of individuals in a population that represent the population level response to climate change. Responses to climate change can either be phenotypic plasticity or microevolutionary change. A phenotypic plastic response occurs when for example individuals reproduce early in years with warm springs and late in years with cold springs. In contrast, a micro-evolutionary change occurs as a consequence of differences in genotype among individuals, with individuals with alleles coding for early phenology increasing in frequency across generations as a consequence of a selective advantage. Many studies have shown that the extent of change in phenology, for example, is fully explained by the extent of phenotypic plasticity suggesting that there is no reason to invoke additional explanations (e. g. Balbontıń et al. 2009, for an example on spring arrival date of barn swallows), and there is only little direct evidence of micro-evolutionary change so far (Sheldon 2010). Environmental indicators of climate change (or any other factor) should be easy to apply, consistent over time and space, reliable, and informative. While there is already a huge literature of thousands of papers dealing with changes in phenology and distribution range in response to climate change, there are very few papers dealing with methodological aspects including the ability of indicators to provide reliable and relevant information. Environmental indicators that are easy to apply include arrival date of migratory birds or emergence of flowers. The use of these

3 Environmental Indicators of Climate Change: Phenological Aspects

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phenology indicators dates back to the days of Linnaeus, when they were used as early indicators of the appropriate time for sowing crops (Lehikoinen et al 2004), and they are still widely used today. Environmental indicators should be consistent over time and space if they reliable reflect change in environmental conditions. Statistically, this implies that they are repeatable among sites and periods. Repeatability is an estimate of the amount of variation among individuals relative to the total variance, with estimates ranging from one when subjects show complete consistency across samples to zero when subjects show no consistency (Falconer and Mackay 1996). When subjects are individuals, repeatability provides an upper limit to the heritability of a given trait. For example, Rubolini et al. (2007) tested for and found consistency in response to climate change as reflected by change in spring arrival date among European populations of migratory birds. Environmental indicators should be reliable so there is little bias due to low detection probability (so-called false negatives) although such effects could be controlled statistically (e.g. Mackenzie et al 2004). For example, sessile organisms may be less prone to false negatives than mobile species because the former can be found in the same area in subsequent years. A different problem applies to migrants that live in different environments at different times of the year. Such species may be exposed to different climate systems that partly fluctuate independently of each other, making it difficult to pinpoint whether an environmental indicator reflects changing climate at the breeding grounds, on migration or during winter, or all of these combined. In contrast, resident species should be superior indicators of local climatic change because they are exposed to the same climate system year-round (Rubolini et al 2010) for an example of change in song phenology of resident, short distance and long distance migratory birds). Reliability of environmental indicators also implies that they are specific to the impact of a given environmental factor. For example, Gregory et al. (2009) presented information on the reliability of the European breeding bird monitoring program showing consistency between population trends and the predicted change in potential range forecasted by climate envelope models. However, many other factors such as urbanization, intensified agriculture, forestry and fisheries, and pollution also change simultaneously. Therefore, the null hypothesis is that there will be linear trends, and that the partial influence of other factors should be controlled statistically in tests of the reliability of climate change indicators. Finally, environmental indicators should be informative in the sense that they should provide information that is relevant in the biological context. Early phenology is associated with considerable increased reproductive success because early phenology (be it arrival date of migratory birds or emergence of insects or plants in spring) equates with early start of reproduction, which is advantageous in terms of probability of recruitment to the next generation (Møller 1994). Likewise a distributional range under favorable climatic conditions is associated with a larger total population size and hence greater standing genetic variation, which will allow greater microevolutionary response to selection (Wakeley 1998). Thus if we can rank species with respect to their indicator ability, this will be helpful in terms of our continued ability to monitor the biological consequences of altered climatic conditions.

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The objectives of this chapter are to (1) identify environmental indicators of climate change; (2) rank the response of different species in terms of their indicator ability; and (3) test for consistency in indicator ability over time. Here we attempt to address these issues mainly relying on birds as study organisms, although we cite the literature on other organisms whenever possible.

3.2 3.2.1

Environmental Indicators of Climate Change Identification of Environmental Indicators of Climate Change

The most commonly used environmental indicators of climate change are change in phenology and range expansion. Figure 3.1 shows the frequency distribution of responses to climate change as an example of these two indicators. It is evident from the frequency distributions that there has been a mean change over time, but also that there is considerable variation among species, and some species have even shown trends that are opposite to the predicted response. However, these are far from the only possible indicators. Body condition, reproductive output, survival and change in population size are indicators that are supposed to be more closely related to fitness. A list of advantages and disadvantages of different environmental indicators of climate change is provided in Table 3.1. Generally, indicators that are more closely associated with fitness and maintenance of stable populations such as indices of reproduction, survival and population size are the most difficult and costly to obtain, while the easiest indices like change in phenology and range margin are easy to obtain, but less closely associated with fitness components. However, the observation that bird species that have responded the least to climate change are also the species that have the most negative future population trend suggests that change in phenology can be an informative indicator (Møller et al. 2008).

Fig. 3.1 Frequency distributions of (a) change in mean spring arrival date of migratory bird species (days year1) in Europe and (b) change in range margin of breeding bird species in Finland. Arrows indicate mean values


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Table 3.1 Environmental indicators of climate change and their properties in terms of ease of use, consistency in response over time and space, reliability and degree of informative properties Indicator

Ease of use

Consistency over time and space

Reliability

Informative

Change in phenology Change in distribution range Change in body condition Change in reproductive success Change in survival

Easy Easy

Yes Yes, weakly

Partly Partly

Weakly Weakly

Relatively easy Time consuming Time consuming Time consuming

?

Yes

Partly

No

Yes

Yes

?

Yes

Yes

Yes

Yes

Yes

Change in population size

3.2.2

Ranking of Indicators in Terms of Their Indicator Ability

A first step in analyzing the indicator ability of an index of response to climate change is that there has been a response. Indeed mean arrival date of migratory birds has advanced considerably in recent years (mean (SE) ¼ 0.16 (0.02) days year1, t ¼ 7.58, P < 0.0001). The species with the strongest response to climate change are the short distance migratory stock dove Columba oenas 0.971 days year1, jackdaw Corvus monedula 0.833 days year1 and snow bunting Plectrophenax nivalis 0.739 days year1. The species that have delayed arrival the most are the long distance migrants common tern Sterna hirundo +0.605 days year1, wood warbler Phylloscopus sibilatrix +0.249 days year1 and common cuckoo Cuculus canorus +0.249 days year1. Which factors determine the response of indicators to climate change? We can predict that advance in arrival date and other indicators of environmental change will increase with increasing population size for at least two different reasons. First, large populations will have larger amounts of standing genetic variation (Wakeley 1998), and they may hence respond more readily to climate change and other major selection pressures. Second, large populations are generally denser (Brown and Lomolino 1998), and since dispersal is density-dependent (Clobert et al 2001), we can expect greater dispersal distances in such populations resulting in greater range expansion. Mean arrival date has advanced the most in species with large population sizes (Fig. 3.2a; F ¼ 10.17, df ¼ 1,106, r2 ¼ 0.09, P ¼ 0.0019, estimate (SE) ¼ 0.07 (0.02) in a model that accounted for effects of body mass). There was no improvement in fit by addition of total range size (F ¼ 6.55, df ¼ 1,105, r2 ¼ 0.06, P ¼ 0.012, estimate (SE) ¼ 0.06 (0.02)). Thus there is evidence for a significant effect of population size. Migratory species of birds spend part of their annual cycle in the breeding area and part in the winter quarters that may be more than 10,000 km away, and significant

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Fig. 3.2 Change in mean spring arrival date of migratory birds (days year1) in Europe in relation to (a) mean population size in the Western Palearctic, (b) migration distance ( latitude) and (c) flight initiation distance (m)

amounts of time is spent in between on migration. Migratory birds are known to respond less to climate change in the breeding areas than residents (Rubolini et al 2007, 2010; Lehikoinen and Sparks 2010). Indeed, in the European database spring arrival date advanced the most in resident and short distance migratory species, with long distance migrants showing little or no response (Fig. 3.2b; F ¼ 18.75, df ¼ 1,110, r2 ¼ 0.15, P < 0.0001, estimate (SE) ¼ 0.16 (0.04). Flight initiation distance is an important behavioral estimate of the risk that individual animals are willing to take when confronted with a potential predator (Hediger 1934; Burger and Gochfeld 1981). Different species of birds have average flight initiation distances that reflect their population trends with declining species having relatively long flight distances apparently because they require large tracts of undisturbed habitat, while stable or increasing populations of birds have relatively short flight distances for their body size (Møller 2008b). Indeed, species with long flight initiation distances have hardly changed their mean arrival date, while species with short flight distances have advanced their arrival date (Fig. 3.2c; F ¼ 7.40, df ¼ 1,74, r2 ¼ 0.09, P ¼ 0.008, estimate (SE) ¼ 0.26 (0.09)). Therefore, there is evidence of a significant effect of flight initiation distance.


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Brommer and Møller (2010) reviewed evidence that the southernmost ranges of birds are significantly moving northwards based on studies in Finland, UK and USA, while there was less evidence for a change in northernmost ranges.

3.2.3

Testing for Consistency in Indicator Ability Across Spatial Scales

Environmental indicators of response to climate change may differ in indicator ability. Even change in phenology can be strongly affected by the choice of indicator. For example, first arrival date is difficult to estimate with any precision because it is a point estimate at the extreme left tail of a normal frequency distribution. Rubolini et al. (2010) have shown that first arrival date of migrating birds is repeatable across study sites, although much less so than a central estimate such as mean or median arrival date. This finding is as expected because a mean or a median is based on numerous point estimates that add up to a more reliable central estimate. This result mirrors the old saying that one swallow does not make a summer! It is also possible to investigate the relationship between first arrival date and mean arrival date across species to quantify the ability of these two indices to reflect the same phenomenon. Across 112 species of birds analyzed by Rubolini et al. (2007) first arrival date did not significantly predict mean arrival date (F ¼ 0.13, df ¼ 1,110, r2 ¼ 0.001, P ¼ 0.72).

3.2.4

Testing for Consistency in Indicator Ability Over Time

If particular species are superior colonizers, then we should see consistent similarities in range expansion previously and now. This prediction has never been tested. Voous (1960) provided the first major atlas of the worldwide distribution of any group of organisms in his treatise of the birds of Europe. Cramp and Perrins (1977–1994) provided a second atlas of the breeding birds of the Western Palearctic. There was a significant increase towards the north in breeding distribution between the period before 1960 and the period before 1990 (mean change in northernmost distribution: +0.67 latitude, SE ¼ 0.20, N ¼ 168 species) differing significantly from zero (t ¼ 3.33, df ¼ 167, r2 ¼ 0.06, P ¼ 0.0011), while there was no consistent change for the southernmost distribution range (0.25 latitude, 0.43, t ¼ 0.59, df ¼ 167, r2 ¼ 0.002, P ¼ 0.56). The indicator ability of northernmost range expansion estimated as the difference in northernmost latitude between 1960 and 1990 was positively correlated with range expansion in Finland between 1974–1979 and 1986–1989 (the latter data reported by Brommer and Møller (2010); F ¼ 5.04, df ¼ 1,53, r2 ¼ 0.09, P ¼ 0.029, estimate (SE) ¼ 2.40 (1.94)) after controlling for change in abundance. To conclude, there is weak, but significant consistency in range expansion over time. There are no similar data currently available for phenology.

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3.2.5

A.P. Møller

Testing for Consistency in Indicator Ability Among Indicators

If there were multiple traits that all reliably indicated response to climate change, the task of assessing the response of living beings to climate change would be rendered much easier. From a theoretical point of view it is fully possible that characters that promote dispersal and hence range expansion would also promote change in phenology. For example, longer-winged insects have shown a greater response to climate change in terms of range expansion compared to species without or with shorter wings (Thomas et al 2001). It would not be difficult to argue that specific wing morphology in birds would facilitate range expansion, but also early arrival in spring from the tropical winter quarters. Surprisingly, there has been no empirical test of whether species that have advanced phenology are the same species that have expanded their range the most. Change in spring phenology in terms of mean arrival date for different species of birds was not significantly related to range expansion in Finland (models that included mean distribution as a covariate and models that were weighted by number of mean arrival estimates; southernmost distribution: F ¼ 1.99, df ¼ 1,51, r2 ¼ 0.04, P ¼ 0.16; northernmost distribution: F ¼ 2.09, df ¼ 1,9, r2 ¼ 0.19, P ¼ 0.18). A similar conclusion was reached for range expansion in the UK (southernmost distribution: F ¼ 2.41, df ¼ 1,24, r2 ¼ 0.09, P ¼ 0.13; northernmost distribution: F ¼ 0.58, df ¼ 1,67, r2 ¼ 0.01, P ¼ 0.34). These tests provide no evidence for a species-specific indicator ability to respond to climate change. I conducted a second test of the prediction by relating mean change in spring arrival date to mean change in winter range of birds in Germany according to temporal changes in locations of banded birds (Fiedler et al 2004). Indeed there was a weak, but significant relationship (F ¼ 4.58, df ¼ 1,21, r2 ¼ 0.18, P ¼ 0.044, estimate (SE) ¼ 0.185 (0.086)). Therefore, bird species that now winter closer to their breeding grounds in Germany have advanced their spring arrival date the most.

3.3

General Discussion

The main findings of this chapter were that different environmental indicators of climate change were weakly consistent across spatial and temporal scales, and that different indicators were at best only weakly positively correlated. This implies that there is little evidence of general indicators. Weak effects as reported in this chapter for environmental indicators of climate change are typical of biological research. On average biologists typically have r2 ¼ 0.05–0.07 in meta-analyses of biological phenomena as diverse as plant responses to increasing CO2, intensity of sexual selection and parasite manipulation of hosts (Møller and Jennions 2002). Although such effects may seem small compared to effects in other natural sciences than biology, on an evolutionary


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time scale of thousands or more generations they can readily result in considerable phenotypic change. Repeatability of environmental indicators of climate change across spatial and temporal scales is weak at best and often almost completely lacking. An absence of repeatability can be attributed to a lack of response in one area/period, but not the other. Alternatively, it can be attributed to the lack of a species-specific response with changes in response differing among areas/periods. In general phenotypic traits of species are highly consistent across spatial and temporal scales with external phenotype, life history, physiology, ecology and behavior of say Japanese and Irish great tits Parus major being more similar than say Irish great tits and closely related Irish blue tits Cyanistes caeruleus. This similarity is the basis for why bird watchers can readily distinguish between species with a pair of binoculars. The lack of repeatability for indicators of environmental change is all the more surprising. Advancing spring phenology and range expansion are statistically largely independent environmental indicators according to the analyses reported here. Although there is a clear average biological signal in the predicted direction for both spring phenology and range expansion, this signal is specific for a particular location or a particular period. Many aspects of global change such as urbanization, intensified agriculture, forestry and fisheries, and pollution all change simultaneously as does climate change. Thus there is a good reason for testing if environmental indicators of climate change are specific to climate, or whether such indicators reflect other components of global change. Surprisingly only few such tests exist, suggesting that there is reason for caution when assessing the effect of climate change on biological phenomena (Møller 2013).

3.4

Future Prospects

Future studies should attempt to pinpoint the reliability of environmental indicators, but should also further investigate the information content of such indicators. It would be interesting to test a range of different indicators for their ability to indicate climate change. Such a test should rely on reliability, but also on cost effectiveness. Given that indicators of climate change are poorly correlated with each other we need to better understand what they are reflecting. We also need to quantify to which extent these indicators reliably reflect the reproductive potential and hence the persistence of populations. It is generally assumed, although not explicitly tested, that species with the strongest response to climate change will be the species that suffer the least from climate change. This may not always be the case because different taxa may respond at a different rate. Indeed, predators may fare better when exploiting populations of prey that have an inferior condition due to negative effects of climate change. The same may apply to parasites. It is clear that natural environments have always been affected by environmental change including

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climate change although the rate of change has rarely if ever been greater than today. Thus, there is every reason to identify the taxa that will be most affected by climate change, and the phenotypic traits of such taxa that will provide the most reliable information on future response to climate change. Acknowledgments J. A. Shykoff helped crystallize some of the ideas presented here.

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