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Bird migration and climate: the general picture and beyond

Bird migration and climate: the general picture and beyond
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  CLIMATE RESEARCHClim Res Vol. 35: 177–180, 2007 doi: 10.3354/cr00724 Published December 31 As succinctly stated by Gordo (2007, this issue), thetemporal shifts in migratory phenology have alreadybeen well described (Lehikoinen et al. 2004, Gienappet al. 2007, this issue, Rubolini et al. 2007, this issue), atleast for spring arrival in Europe and North America,and now is the time to delve into the underlying mech-anisms. Before doing that, let us havea closer look atthe (rather) general patterns described so far.Rubolini et al. (2007)analysed available estimates ofchange in first arrival dates and mean/median arrivaldates collected across Europe in the last 40 yr andlooked for spatial and taxonomic variation, as well asintraspecific consistency. Importantly they analyseddata from both passerines and non-passerines. Overallthere were rapid advances in arrival date, especiallyfor first arrival dates in species spending the winter inEurope. The most important finding reported byRubolini et al. (2007)was that change in spring arrivaldate shows a significant degree of intraspecific consis-tency, and can thus be regarded as a species-specifictrait. In other words, different populations of the samespecies respond consistently, which motivates compar-ative analyses of interspecific differences.The general findings reported above are compli-cated by the fact that there is considerable spatial vari-ation in the observed changes in arrival time, which istrue also for changes in the timing of breeding (Both &te Marvelde 2007, this issue). Geographic variation ishowever expected, considering the spatio-temporalvariation in climate change (Klein Tank et al. 2002),which generates spatial variation in selection pres-sures and different possibilities for plastic responsesdepending on the time and route of migration.If we increase the resolution and go beyond thearrival patterns based on the mean response of a pop-ulation, one could think of different segments of a pop-ulation responding differently to climate change. Forinstance, males and females often migrate during dif-ferent times of the season and may also use differenthabitats during winter (Studds & Marra 2007, thisissue). Furthermore, there are different selection pres-sures for arrival time in males and females (Møller2004, 2007). Increased spring temperatures could in-crease pre-breeding survival rate, thereby making itpossible for early arriving males competing for territo-ries to arrive even earlier. Therefore, climate changemay lead to increased time lag between male andfemale arrival, which is exactly what was found in aDanish barn swallow Hirundo rustica population(Møller 2004). However, in this issue Rainio et al.(2007)found a parallel rather than divergent shift inthe timing of male and female migration in 4 songbirdspecies detected at 5 European bird observatories.Hence, we simply need more studies on how malesand females respond to climate change. Phenotypic plasticity, micro-evolution or what? Until quite recently there seemed to be a commonview that species spending the winter in Europe (oftenreferred to as short-distance migrants) are more likelythan long-distance migrants to vary migration timingin response to climate change simply because they areexposed to the warming in Europe all year round(Lehikoinen et al. 2004). The long-distance migrants,on the other hand, are only affected by warming whilemigrating through Europe, and any advancement tocentral or northern Europe can be explained by im-proved environmental conditions en route (e.g. Hüppop © Inter-Research 2007 ·*Corresponding author. Email: Bird migration and climate: the general pictureand beyond Niclas Jonzén 1 , Torbjørn Ergon 2 , Andreas Lindén 3 , Nils Chr. Stenseth 2, * 1 Department of Theoretical Ecology, Ecology Building, Lund University, 22362 Lund, Sweden 2 Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biology, University of Oslo, PO Box 1006 Blindern,0316 Oslo, Norway 3 Department of Biological and Environmental Sciences, Integrative Ecology Unit, PO Box 65 (Viikinkaari 1),University of Helsinki 00014, Finland O PEN EN   A CCESS CESS  Clim Res 35: 177–180, 2007 & Winkel 2006). Therefore, the adaptation of breedingtime to an advancement of optimal conditions may beconstrained by the migration strategy in long-distancemigrants (Both & Visser 2001). We think that it is timeto revise some details of that picture.Though the importance of endogenous control andphotoperiod as a trigger of migratory restlessness isbeyond doubt (e.g. Berthold 1996, Gwinner 1996),there is a growing number of studies pointing at theimportance of interannual variation in winter climateas a predictor of arrival time in the summer quarters(e.g. Cotton 2003, Saino et al. 2004, 2007, this issue,Marra et al. 2005, Gordo 2007). Hence, the timing ofmigration may be quite flexible even in long-distancemigratory birds, and the detailed studies of the Ameri-can redstart Setophaga ruticilla suggest that not onlythe speed of migration, but also the departure date canbe affected by winter climate through its effect onhabitat quality and, thus, the time needed to preparefor migration (Marra et al. 1998, Studds & Marra 2007).There are also observations that are not easily ex-plained by a simple phenotypic response. For instance,the earlier arrival of African migrants on Capri (Jonzénet al. 2006) cannot be fully explained by the climaticvariables investigated so far (Saino et al. 2007). It hasbeen suggested that the lack of explanation for theadvanced arrival on Capri may be an indication ofmicro-evolution (Jonzén et al. 2006, 2007b), but thereare potential pitfalls to make any claims about micro-evolution premature (Both 2007). Another interestingobservation that is not easily attributed to phenotypicplasticity only is the increased response to temperaturein SW Europe in the sand martin Riparia riparia , whichhas resulted in earlier arrival in the UK at the sametemperature as before (Sparks & Tryjanowski 2007,this issue). Again, the data at hand do not allow anyformal test of the involvement of any micro-evolutionaryprocesses (Møller & Merilä 2004), but they cannot beexcluded either.One may ask why we still lack conclusive evidencefor evolutionary change despite selection for earlierarrival and the presence of genetic variation in the tim-ing of migration, and plausible answers to this criticalquestion are given by Pulido (2007, this issue). To someextent it is a data problem. Based on arrival data frombird observatories, we are not in position to dif-ferentiate between the relative roles of phenotypicplasticity and evolutionary responses, data do notunambiguously support or refute either of the two (notmutually exclusive) hypotheses (Gienapp et al. 2007).Interannual arrival data on individual birds, measuredwith high precision, would be useful for this purpose.Unfortunately, that kind of data is very scarce. How-ever, there are other reasons why it is inherently diffi-cult to find conclusive evidence for micro-evolution.For instance, to what extent changes in wind directionsand speed can explain the earlier arrival of migratorybirds is largely unexplored (but see Sinelschikova etal.2007). Furthermore, since the physical condition ofbirds can affect departure time, we clearly need exper-imental studies on the wintering grounds (Studds &Marra 2007) to better understand the importance ofcarry-over effects that may persist over several gener-ations (Pulido 2007). Hence, we need to appreciate thewhole life cycle of events and not only to study springmigration as an isolated phenomenon (Coppack &Both 2002, Hedenström et al. 2007, this issue). In thatrespect the timing of autumn migration and how itrelates to the timing of spring migration (Péron et al.2007, this issue), and the selection pressures involved,is of course of interest and has not received the atten-tion it deserves. On theory, statistics and the need for detailed data It should now be clear that an impressive body ofwork exists demonstrating how avian phenology pat-terns—especially spring arrival time in temperateareas—have changed over the last decades. Thoughpotentially important also for demography and popula-tion change, without any theoretical guidance thesepatterns cannot be interpreted and the ecological con-sequences remain elusive. We must start asking ques-tions such as: If increased spring temperatures havecaused an advance of the food peak date by x  days,what would be the optimal shift in spring arrival time?As a first approximation it may be tempting to assumea 1:1 relationship (Visser & Both 2005), but addingopposing selection pressures (e.g. higher mortality riskearly in season) would give a different answer (Jonzénet al. 2007a).An appealing theoretical framework for interpreta-tion of the patterns we find and predicting what to lookfor in the future is given by so-called annual routinemodels, a general approach for studying the optimalscheduling of events in a seasonal environment(Houston & McNamara 1999, McNamara & Houston2007).The annual routine models are based on state-dependent reproductive values and, by incorporatingthe whole annual cycle, explicitly incorporate carry-over effects from previous seasons (Studds & Marra2007). These models are just starting to be used in thecontext of climate change and the timing of biologicalevents such as migration and breeding. The modelsprovide testable predictions based on a sound treat-ment of the complex life cycles of migratory birds(Hedenström et al. 2007).Testing any predictions of expected shifts in the tim-ing of events requires that we can estimate the sea- 178  Jonzén et al.: Bird migration and climate sonal distribution of that event (e.g. migration), whichis not always straightforward. The data at hand areoften collected for other purposes, and even long-term,standardized monitoring data from bird observatoriesmay require special handling (Knudsen et al. 2007, thisissue). Bird observatory data are typically character-ized by weather-dependent, day-to-day variation thatdoes not only reflect migration, but also the actual prob-ability of trapping. Sample quantiles may be largelyinfluenced by a few days of trapping because of thisstrong day-to-dayvariation.Furthermore,weather tendsto affect trapping numbers of different species simi-larly, thereby violating any assumptions about inde-pendent observations of species on a given day (Knapeet al. 2008).These complexities, not to mention missing days andtruncated seasons, call for robust approaches to themodelling of the seasonal distribution and its change.Some options are reviewed by Knudsen et al. (2007). Inparticular, they discuss fitting of parametric functionsand smoothing methods as alternative ways for model-ling the seasonal distribution of phenological events.Some of the suggested modelling approaches are diffi-cult to handle in a frequentist setting. One option is touse Markov chain Monte-Carlo (MCMC) methods andBayesian inference (Gilks et al. 1996). This is a flexibleapproach gaining in popularity in the most quantita-tive branches of ecology (Meyer & Millar 1999,Link etal. 2002,Clark & Gelfand 2006) and has recently beenused to estimate spring arrival time in passerine birds(Jonzén et al. 2006,Saino et al. 2007). Until recently,ecologists had to select models on the basis of statisti-cal rather than ecological considerations. This is nolonger the case. When MCMC, having its srcin in sta-tistical physics, penetrated mainstream statistics in theearly 1990s, it resulted in a ‘model liberation move-ment’ (Gilks et al. 1996). Not only can rather complex-structured population models be fitted to a givendataset, but also qualitatively different data sources(e.g. a time series of population density, mark–recap-ture data, breeding success data, etc.) can be broughttogether within the same statistical framework. Notsurprisingly, we think this approach might be a fruitfulavenue for making maximum use of available data andincorporating uncertainty and ecological complexity ina more appropriate way than what has been done inthe past.Based on the majority of the contributed papers andthe discussion above, one may think that the shiftedtiming of biological events is the only ecological effectof climate change. However, some of the most strikingpatterns are species-range shifts in parallel with cli-mate change (reviewed by Parmesan 2006). The cur-rent approach for predicting range shifts is to use so-called climate-envelope models (e.g. Pearson & Dawson2003) that connect current species distributions to cli-matic variables and predict future distributions basedon climate change models and the estimated relation-ship between species occurrence and the climaticfactors. The last contribution in this issue (Mustin et al.2007) questions the usefulness of climate-envelopemodels for individual species, especially when non-cli-matic factors such as socio-economic factors and policyresponses are important for the habitat quality andhabitat dynamics. Mustin et al. (2007)further arguethat such details are unfortunately difficult to includein predictive models of species distribution under cli-mate change, thereby casting some doubt on what wecan really achieve. The importance of the problemshould, however, provide enough motivation for futurework in this area.In conclusion, we are now—as this CR Specialshows—moving beyond the mere description of pat-terns and starting to think about the underlying mech-anisms. Therefore, it is not surprising that we findourselves in a situation where the importance of differ-entprocesses (e.g. phenotypic plasticity and micro-evolution) are being discussed, but no consensus hasyet emerged. Theoretical modelling may help us to geta better idea about the selection pressures involvedinadapting to climate change and to know what toexpect. However, as several of the contributed papershave pointed out, what we also need is more individ-ual-based data and clever experiments to reveal therelative importance of the range of processes affectinghow climate change shapes the timing of biologicalevents and, consequently, the distribution and abun-dance of organisms. LITERATURE CITEDBertholdP(1996) Control of bird migration. Chapman & Hall,LondonBothC(2007) Comment on ‘Rapid advance of spring arrivaldates in long-distance migratory birds’.Science315:598bBothC, te MarveldeL(2007) Climate change and timing ofavian breeding and migration throughout Europe.ClimRes 35:93–105BothC, VisserME(2001) Adjustment to climate change isconstrained by arrival date in a long-distance migrantbird.Nature411:296–298ClarkJS, GelfandAE(eds) (2006) Hierarchical modelling forthe environmental sciences. Oxford University Press,OxfordCoppackT, BothC(2002) Predicting life-cycle adaptationofmigratory birds to global climate change.Ardea90:369–378CottonPA(2003) Avian migration phenology and global cli-mate change.Proc Natl Acad Sci USA100:12219–12222GienappP, LeimuR, MeriläJ(2007) Responses to climatechange in avian migration time—microevolution versusphenotypic plasticity.Clim Res35:25–35GilksW, RichardsonS, SpiegelhalterD(eds) (1996) Markovchain Monte Carlo in practice. Chapman & Hall, London179  Clim Res 35: 177–180, 2007GordoO(2007) Why are bird-migration dates shifting? Areview of weather and climate effects on avian migratoryphenology.Clim Res35:37–58GwinnerE(1996) Circadian and circannual programmes inavian migration.J Exp Biol199:39–48HedenströmA, BartaZ, HelmB, HoustonAI, McNamaraJM,JonzénN(2007) Migration speed and scheduling ofannual events by migrating birds in relation to climatechange.Clim Res35:79–91HoustonAI, McNamaraJM(1999) Models of adaptive be-haviour. 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