doi 101098rstb20100148 3177-3186365 2010 Phil Trans R Soc B

Abraham J Miller-Rushing Toke Thomas Hoslashye David W Inouye and Eric Post The effects of phenological mismatches on demography

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This journal is copy 2010 The Royal Society

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Phil Trans R Soc B (2010) 365 3177ndash3186

doi101098rstb20100148

Review

AuthoAcadiaBar Har

One conecology

The effects of phenological mismatches ondemography

Abraham J Miller-Rushing12 Toke Thomas Hoslashye3

David W Inouye45 and Eric Post6

1USA National Phenology Network Tucson AZ 85719 USA2The Wildlife Society Bethesda MD 20814 USA

3Department of Wildlife Ecology and Biodiversity National Environmental Research InstituteAarhus University Grenavej 14 8410 Roslashnde Denmark

4Rocky Mountain Biological Laboratory Crested Butte CO 81224 USA5Department of Biology University of Maryland College Park MD 20742 USA6Department of Biology Penn State University University Park PA 16802 USA

Climate change is altering the phenology of species across the world but what are the consequences ofthese phenological changes for the demography and population dynamics of species Time-sensitiverelationships such as migration breeding and predation may be disrupted or altered which may inturn alter the rates of reproduction and survival leading some populations to decline and others toincrease in abundance However finding evidence for disrupted relationships or lack thereof andtheir demographic effects is difficult because the necessary detailed observational data are rare More-over we do not know how sensitive species will generally be to phenological mismatches when theyoccur Existing long-term studies provide preliminary data for analysing the phenology and demogra-phy of species in several locations In many instances though observational protocols may need to beoptimized to characterize timing-based multi-trophic interactions As a basis for future research weoutline some of the key questions and approaches to improving our understanding of the relationshipsamong phenology demography and climate in a multi-trophic context There are many challengesassociated with this line of research not the least of which is the need for detailed long-term dataon many organisms in a single system However we identify key questions that can be addressedwith data that already exist and propose approaches that could guide future research

Keywords climate change demography global warming mismatch phenology

1 INTRODUCTIONClimate-driven shifts in phenology are altering eco-logical relationships and processes around the world(Visser amp Both 2005 Cleland et al 2007 Forrest ampMiller-Rushing 2010) However the effects of theseshifts on the vital rates of populations are not wellunderstood We do not adequately understand howsuch effects will come about how often they mightoccur and how substantial their contributions to popu-lation dynamics will be For example phenologicalmismatches might occur when organisms that typicallyinteract such as predator and prey or plant and polli-nator are no longer active at the same time Or incontrast shifts in phenology could alleviate existingmismatches and promote the exploitation of newlyavailable resources The creation and loss of phenolo-gical mismatches could be quite common given thesubstantial variation in phenological responses to

r and address for correspondence National Park ServiceNational Park Schoodic Education and Research Centerbor ME 04609 USA (abe_miller-rushingnpsgov)

tribution of 11 to a Theme Issue lsquoThe role of phenology inand evolutionrsquo

3177

climate change among taxa (Visser amp Both 2005Primack et al 2009 Thackeray et al 2010)

Although phenological mismatches are mostfrequently discussed in terms of intertrophic relation-ships (Stenseth amp Mysterud 2002 Visser amp Both2005 Durant et al 2007) demographic effects ofchanges in phenology are not restricted to trophic mis-matches Nearly every ecological process andphenomenonmdasheg competitive interactions droughttolerance and nutrient cyclingmdashhas a temporal com-ponent that can affect its function As the timing ofvarious phenological events such as reproductionmigration and diapause change so will relatedfunctional processes such as pollination and primaryproductivity Nevertheless few empirical studiesquantify the relationship between phenology anddemography (but see Inouye 2008 Moslashller et al 2008)

Here we identify some of the key gaps in our under-standing of how climate-driven changes in phenologymay alter demography and we outline approaches tofill in those gaps For example how sensitive willspeciesrsquo demographies be to changes in phenologyWill species with specialist relationships be more sensi-tive to phenological shifts than generalists Will species

This journal is q 2010 The Royal Society

day of year difference in mean timing of event (microb ndash microa)

abun

danc

e or

qua

lity

of a

biot

ic c

ondi

tions

sync

hron

y (i

nteg

ral o

f th

e ov

erla

p be

twee

n fo

cal s

peci

es a

nd e

nvir

onm

ent c

urve

s)

microa microb

(a) (b)

(g)(c) (d)

(e) ( f )

Figure 1 Examples illustrating differing degrees and types of phenological mismatch The left panel (andash f ) illustrates how thesynchrony (or degree of overlap) between a focal species (solid line) and its environment (broken line) diminishes as thespeciesrsquo phenology advances The distribution of suitable environmental conditions can be wide (ab) or narrow (cd) Thedistribution could also be asymmetrical (ef ) The curves could represent relationships between phenological phases of indi-

viduals or populations of the same or different speciesmdasheg flowering and pollinator activity or predator and prey activity Thecurves could also represent the relationship between an individual or population and appropriate abiotic conditionsmdasheg leafdevelopment and frost-free conditions or tadpole development and water level The right panel (g) illustrates how the syn-chrony between a species and its environment varies in response to increasing differences in the timing of activity of a

species and its environment for the three cases shown in the left panel (andash f ) Here we measure synchrony as the area of over-lap between the focal species and environment curves The vertical line indicates the degree of synchrony when the focalspeciesrsquo phenology is advanced relative to its environment (bdf ) The dash and dot pattern in each curve in (g) matchesthe environmental curve (left panel) that it representsmdashdashed (ab) dotted (cd ) and dot-dash (ef )

3178 A J Miller-Rushing et al Review Phenology and demography

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with highly plastic phenologies increase in abundancerelative to species with relatively fixed phenologiesWill changes in phenology affect rates of reproductionmore than offspring survival We emphasize the widerange of mechanisms by which phenology can affectdemography (eg abiotic intraspecific intraguild andintertrophic interactions) and the various scales (eglocal landscape and even continental) at which theseprocesses can operate and discuss why linkingphenology to demography is challenging and important

2 DEFINITIONS SCALES AND SELECTION(a) Demography and synchrony

For the purpose of this paper when we refer to theeffects of phenology on demography we generallyrefer to the effects of phenology on population vitalratesmdashreproduction and survival We also provideexamples that highlight the relationship betweenphenology and population size which is inextricablylinked to population vital rates and is often the primaryvariable of interest to natural resource managers andpolicy-makers

We use the term synchrony to refer to the degree oftemporal match between two events that constitute arelationshipmdashfor example the breeding season of abird and the peak availability of its food source

Phil Trans R Soc B (2010)

Importantly synchrony in this context is not a binarycondition rather it is a measure of the overlap oftwo events each of which has a temporal distribution(figure 1) The synchrony of events can be measuredalong a continuum from highly synchronous inwhich case their temporal distributions overlap signifi-cantly to total mismatch in which case there is nooverlap between their temporal distributions Inbetween there are intermediate levels of synchronyand mismatch where the tails of the distributions over-lap The precision of synchrony required in mostecological relationships is unknown and is a key ques-tion for understanding the effects of phenology ondemography (see sect3)

(b) Abiotic and species interactions

The link between phenology and demography occursat multiple spatial scales and through interactions atthe intraspecific intraguild or intertrophic level orthrough interactions with abiotic factors (figure 2)The most basic interaction is between phenologicalevents and abiotic conditions such as weather Thedemographies of some arthropods for exampledepend on the timing and duration of temperaturesthat are warm enough to allow for foraging and growth(Merckx et al 2006 Hoslashye amp Forchhammer 2008b)

species I species II

species III

trophic level I

trophic level II

abiotic conditions

a

b

c

d

Figure 2 Conceptual model of various levels of interactionthat might be affected by phenological mismatch (a) organ-

ismndashabiotic environment (b) within organism andintraspecific (c) intraguild and (d) intertrophic Arrows rep-resent relationships among abiotic conditions and species atvarious trophic levels relationships that depend on the

phenology of the species involved

Review Phenology and demography A J Miller-Rushing et al 3179

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For instance earlier spring snowmelt and longergrowing seasons are associated with larger adult bodysize in arctic spider species particularly in females(Hoslashye et al 2009 Hoslashye amp Hammel 2010)Large females have higher reproductive output butincreased sexual size dimorphism may also alter com-petition between males and females and thus affectsurvival Longer growing seasons are also correlatedwith increased body mass winter survival andreproduction of yellow-bellied marmots in the Color-ado Rocky Mountains (Ozgul et al in press)Changes in plant phenology particularly at the begin-ning and end of the growing season can also affect therisk of exposure to frost or other abiotic factorsaltering rates of survival and reproduction (Inouye2000 2008)

Phenology may also play an important role in intra-specific interactions For outcrossing plants it is oftenimportant that many individuals of a particular speciesin an area flower synchronously to maximize the likeli-hood of cross-pollination which can have importantfitness benefits (Holtsford amp Ellstrand 1990) Popu-lations of dioecious species of plants for which malesand females are spatially segregated along an environ-mental gradient (Bierzychudek amp Eckhart 1988Dawson amp Ehleringer 1993) could be at risk if thespatial segregation starts to correspond to phenologicalsegregation as well In at least one study sexual differ-ences in reproductive phenology were shown toinfluence demography of a dioecious tropical shrubBaccharis dracunculifolia (Espırito-Santo et al 2003)Similarly flowering synchrony within individualplants can play a key role in attracting pollinatorsand affect rates of self-fertilization (Barrett et al1994 Karron et al 2004) Likewise important intra-guild interactions may be affected by phenologicalvariation through facilitation or competition forresources such as water nutrients pollinators orfood (Moeller 2004) Finally in intertrophic inter-actions such as those between plants and pollinatorsor predators and prey timing is also critical Forexample the timing of food availability must matchan organismrsquos demand for food

Phil Trans R Soc B (2010)

(c) Scale of effects

The critical spatial and temporal scales for a phenologi-cal match vary according to the species in question Forinstance we would expect that the appropriate spatialscale for studying the potential for resource mismatchin solitary bees which have relatively small foragingranges (Zurbuchen et al 2010) differs substantiallyfrom that of hummingbirds which can migrate longdistances Similarly the demographic impacts of achange in phenology such as the timing of leaf-outwill occur at multiple spatial scales Changes in leaf-out at the scale of a single plant can affect the survivaland reproduction of caterpillars (Visser amp Holleman2001) but changes at the scale of hundreds of squarekilometres will be more relevant to large mammalsthat can forage over large areas (Post et al 2008b)

(d) Selection on phenology

Although not particularly well studied in most speciesevidence suggests that the timing of many life-historyevents is heritable and hence able to respond to selec-tion (Pulido et al 2001 Burgess et al 2007) Thefactors that influence selection on phenology are toonumerous to cover in this paper but we touch onsome key points here Phenology is often evaluatedat the population levelmdashie first or mean arrivalwithin a migratory bird populationmdashyet thepopulation-level patterns are essentially cumulativeeffects of generations of natural selection acting onindividuals (Forchhammer amp Post 2004) Individualsoften must make decisions concerning time-sensitivephenological behavioursmdasheg leaf expansion bloom-ing or giving birthmdashprior to the time when thoseevents occur and when selection acts on them (Visseret al 2010) In a changing climate the cues thatspecies used historically to determine the timing oflife-history events might become maladaptive causingphenological events to occur at inopportune times(Iwasa amp Levin 1995 figure 3) The optimal floweringtime for a plant for example can be constrained bythe importance of avoiding poor weather conditionsat the beginning or end of the growing season syn-chronizing reproduction with pollinators minimizingoverlap with florivores and competitors for floralresources avoiding seed predators and maximizingtime for fruit development among other consider-ations Mistiming in relation to any of these factorscould in theory lead to severe consequences for thefitness of individuals and the demography of popu-lations Additionally strong selection as might occurin instances of mismatch often entails demographiccosts in the short term (Kinnison amp Hairston 2007)

Because life-history events are not isolated entitiesobserved phenological variation may not alwaysresult from direct climatic influence or selection on aparticular event For instance reproduction in plantsconsists of several life-history events (eg floweringseed set dispersal and germination) and the timingof those events are often correlated such that theadvancement or delay of one event such as floweringwill often incur a change in the timing of later eventssuch as seed set (Primack 1987) Therefore selectionacting on germination often affects flowering time

impacts of climate change

environment at time ofdecision-making (ie cues)

ndash photoperiodndash temperature

response mechanism

environment at time ofselectionmdasheg conditions attime of egg hatching or fruitmaturation

selection mechanism

breeding or flowering date fitness

Figure 3 A schematic outline of how climate change mayaffect reproduction Changes in the environment at thetime of decision-making may affect the timing of reproduc-tion via the response mechanism For example changes intemperature might affect the timing of breeding or flowering

However changes in the environment at the time of selection(eg egg hatching or fruit maturation) will affect the fitnessconsequences of breeding at a particular date Conditionsat the time of decision-making may have historically providedreliable cues of conditions at the time of selection Changes

in climate may change the historical relationship and lead tomaladaptive decisions Adapted from Visser et al (2004)

3180 A J Miller-Rushing et al Review Phenology and demography

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Unfortunately we still know little about how fixedthese links among life-history events are (Both ampVisser 2001 Sola amp Ehrlen 2007 Post et al 2008a)

3 SENSITIVITY OF DEMOGRAPHY TOPHENOLOGICAL MISMATCHGiven the amount of variation among speciesrsquo andpopulationsrsquo phenological responses to changes in cli-matemdashie variation in the rates and directions ofchange (Fitter amp Fitter 2002 Miller-Rushing ampPrimack 2008 Thackeray et al 2010)mdashthe likelihoodof phenological mismatches occurring seems high Buthow sensitive are speciesrsquo demographies and populationsizes to phenological mismatches In any particularcase the answer depends on at least two factorsmdashtheimportance of the interaction and the likelihood that asignificant mismatch might occur In this context theimportance of an interaction reflects the degree towhich the demography or population size of one speciesrelies on the interaction occurring The likelihood of asignificant mismatch reflects the probability that theinteraction might fail (at least functionally) because ofa shift in timing often because of a complete loss ofoverlap between the timing of two events (figure 1) Itis not clear how frequently demography-limiting eco-logical interactions are vulnerable to shifts inphenologymdashdata on the temporal distributions of inter-actions are just too rare Here though we describeseveral key factors involved in addressing the question

(a) Importance of interaction

The sensitivity of a speciesrsquo demography or populationsize to a phenological mismatch depends on the degreeto which its survival or reproduction is limited by theother species or factors involved in the interaction Insome cases reproduction or survival may rely entirelyon another species being present and at a particularlife-history stage at the right time For example

Phil Trans R Soc B (2010)

yucca moths depend on yucca flowers and fruits forfood and as habitat for eggs and larvae (Pellmyr ampThompson 1992) If for some reason the flowersare not open when the moths are active in their adultstage an entire cohort of moth offspring could belost In other cases the loss of an interaction mayhave little effect For example the loss of apredatorndashprey interaction may result in a substantialdecline in predation on the prey species However ifsurvival of the prey species is limited by food avail-ability not predation the mismatch may have littleimpact on the demography of the prey species

Similarly a change in a relationship with an abioticfactor could have a very large or very small effect onthe demography or population size of a species Forexample in Colorado some plant species are initiatinggrowth earlier in the spring exposing flower buds tofrosts consequently seed production has declined dra-matically for some species (Inouye 2008) In theorythe effect on the population size of the species couldbe large if recruitment is limited by seed productionbut small if it is not The actual effects on recruitmenthave in fact been large There has been little changein population sizes to date because these species areall long-lived perennials but there is an ongoing shiftin the size- and age-distribution (Inouye 2008)

Additionally many relationships lost through phe-nological mismatches may be replaced by newinteractions For example recent evidence has shownthat plantndashpollinator interactions shift substantiallyeach year based on changes in the phenology andabundance of both plants and pollinators (Alarconet al 2008) The strength and frequency of relation-ships between particular plant and pollinator speciesmay decline from one year to the next but they aregenerally replaced by new relationships Similarlymany herbivores and predators are generalists andeat a variety of foods depending on what is availableat a particular time This generalist tendency wouldprobably decrease the speciesrsquo sensitivity to a phenolo-gical mismatch with any particular species assumingthat there is adequate variation in the phenology ofthe species that constitute the food resource

(b) Likelihood of significant phenological

mismatch

A species will probably be more sensitive to mis-matches and mismatches will more probably occurif the resource it interacts with has a narrow bell-shaped temporal distribution (Durant et al 2007) Anarrow temporal distribution increases the probabilitythat an interaction will be completely lost in any givenyear (figure 1) For example all else being equal a birdspecies is more likely to suffer food shortages duringthe breeding season (and possibly reduced reproduc-tion and offspring survival) in any given year if it isdependent on a food source that is abundant for onlytwo weeks In another example the timing of cariboucalving in Greenland is tightly linked to leaf-outphenology every year but minor deviations fromnear-perfect synchrony translate to very large(four-fold) reductions in calf production (E Post2008 unpublished data)

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Similarly a species is likely to be more sensitive toan abiotic factor if there is a threshold beyond whichthe effect of the abiotic factor becomes substantialFor example some insects might suffer complete mor-tality if they have not yet entered diapause whenfreezing temperatures arrive in the autumn or winterThus if they enter diapause too late in the seasonthe effects on survival could be substantial

Abundance of the species involved in an interactioncan also compensate for a phenological mismatch(Durant et al 2005) Typically mismatches are morelikely to occur when abundance of a species is lowwhich can narrow the temporal duration of particularphenophases (ie particular life-history stages or beha-viours) at the population level and reduce thelikelihood of encounters with individuals at the lsquotailsrsquoof the distribution In contrast increases in abundancecan broaden the temporal duration of the availability ofa phenophase (Durant et al 2005) potentially reducingthe impact of a slight loss in synchrony between species

4 PHENOLOGICAL EFFECTS ON SURVIVALAND REPRODUCTIVE SUCCESSUnder what circumstances will phenological changesalter rates of survival (offspring and adult) versus repro-duction Three general patterns come to bear on thisquestion First reproduction tends to require moreresources than survival so that in the absence of ade-quate resources rates of reproduction will tend todecline before rates of survival (Barboza et al 2009)Second general life-history theory postulates that allthings being equal individuals will tend to abandontheir offspring before they risk their own lives Thirdrelative to adults young offspring tend to have lowerreserves and tolerances for unfavourable conditionsand have a diminished capacity to seek out newresources (Barboza et al 2009) Together these gener-alities suggest that there will be a succession of effectson demography starting with effects on reproductionthen offspring survival and finally adult survival

However there are certainly exceptions to this con-clusion For some species phenology is less critical forreproduction than for survival particularly for the sur-vival of offspring (Williams 1966) For these speciesthe succession of effects and their order may vary Insystems where mates and food are plentiful timingmay not be important for a species to mate and raiseyoungmdashbut timing may be important for its offspringto avoid predation pests and harmful abioticconditions like freezing and drought

In addition the relative role of phenology in affect-ing reproduction and survival will differ betweenspecies with income or capital breeding systemsmdashthat is those that provision offspring with resourcesavailable during the reproductive period versus thosethat provision with resources gained prior to reproduc-tion (Houston et al 2007) The reproductive successand offspring survival of income breeders are likelyto depend much more on the availability of foodresources at the proper time and place Capital bree-ders on the other hand rely primarily on storedenergy reserves that can buffer them against the effectsof changing food availability

Phil Trans R Soc B (2010)

Clearly much more work is required to distinguishbetween cases in which changes in phenology mightaffect survival and when they might affect reproduc-tion and when these will in turn affect populationsizes To illustrate the complexity of this question wepresent examples of how phenology can alter demo-graphy in temperate and arctic plants To emphasizethe diversity of mechanisms by which phenologyaffects survival and reproduction we present theexamples according to the levels of interactioninvolved

(a) Reproduction

(i) Interactions between plants and abiotic factorsFlowering too early can expose plants to cold weatherconditions and damaging frosts (Inouye 2000 2008Hoslashye et al 2007) Flowering too late can leave toolittle time for fruits to develop or for germination tooccur before the end of the growing season

(ii) Interactions within an individual and a populationProducing a large number of flowers synchronouslywithin an individual may increase the chances of self-pollination and decrease the chances of outcrossing(Williams 2007) Extended floral longevity or durationof flowering can increase the chances of receivingpollen from another plant and enhance fitness throughoutcrossing (Ashman amp Schoen 1994) Howeverextended flowering within an individual may alsoincrease the chances of being infected or being eatenby flower herbivores (Shykoff et al 1996 McCall ampIrwin 2006) Flowering synchronously withconspecific individuals can improve the chancesof outcrossing and may reduce the incidence ofseed predation

(iii) Intraguild interactionsIn the case of animal-pollinated species flowering syn-chronously can create competition for pollinatorsalthough a long flowering period may help to minimizethe effects (Campbell amp Motten 1985 Mitchell et al2009) In some cases co-flowering with other speciesmay facilitate the attraction of pollinators(Moeller 2004)

(iv) Intertrophic interactionsSpecies that rely on animals for pollination have anadditional hurdle to flower synchronously with effec-tive pollinators For plants with specialistpollinatorsmdashsuch as Ipomopsis aggregata which reliesprimarily on hummingbirds for pollination (Caruso1999)mdashor for plants that flower particularly earlybefore many pollinators are active synchronizing flow-ering with pollinator activity can be especiallyimportant (Thomson 2010) For other species thathost a variety of pollinators it is of less importanceIn some cases mistiming may in theory lead to ayear in which an individual or an entire populationfails to reproduce Coincidence with herbivores orseed predators however can negate the benefits ofsynchrony with pollinators (Brody 1997)

3182 A J Miller-Rushing et al Review Phenology and demography

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(b) Survival

(i) Interactions between plants and abiotic factorsIn addition to affecting reproduction abiotic factorssuch as frost and drought can alter rates of mortalityYoung plants are often more susceptible to unfavour-able abiotic conditions than are older more vigorousplants (Graae et al 2009) In cases where a speciesrsquophenology is shifting at a different rate than these abio-tic conditions mismatches can develop (Inouye 2008)Young and older parts of a plant can also exhibit differ-ential susceptibility to abiotic factors like frost withnew growth or reproductive parts often being moresusceptible

(ii) Intertrophic interactionsPlantndashherbivore relationships are often time-sensi-tive and depend on the timing of many factorsincluding leaf emergence the emergence of herbi-vores and the development of defence compoundsin leaves For example climate-driven changes inthe phenologies of spruce trees and spruce budwormhave led to increased synchrony between the lifecycle of the budworm and the spruce growingseason in the Pacific Northwest of North America(Chen et al 2001 2003) As a result the level ofspruce mortality in the region has dramaticallyincreased Many other plantndashherbivore relationshipsare similarly dependent on the match betweenplant and herbivore phenology (Visser amp Holleman2001 Post amp Forchhammer 2008 Jepsen et al2009 Singer amp Parmesan 2010)

5 KEY CHALLENGES(a) Data limitations

The demographic consequences of phenologicalchanges are still largely unknown (Visser amp Both2005) The most significant reason for this gap inour understanding is that demonstrating demographicconsequences of phenological variation typicallyrequires an intensive monitoring effort which iscostly and time-consuming It involves long-termmonitoring of the phenology and demography ofpopulations generally for 5 years (preferably 10years) or more depending on the variability of thesystem in question ( J Che-Castaldo amp D Inouye2010 unpublished data) Researchers attempting togenerate time series long enough to make inferencesabout climate-driven changes often accumulate justone data point per year However latitudinal or eleva-tional gradients can sometimes substitute for timeseries (see sect6b) Most of the long-term studies withdata relevant to the links between climate-drivenchanges in phenology and demography were startedprior to the widespread recognition of recent phenolo-gical changes they were typically begun for otherreasons Therefore much of our current understand-ing of phenological impacts on demography is basedon serendipitous results As more investigations ofphenology and demography begin and as researchersidentify new historical datasets like those held inmuseums and botanical gardens (Miller-Rushinget al 2006) more data are slowly becoming available

Phil Trans R Soc B (2010)

(b) Imperfect knowledge of species ecology

Despite the rapid progression of studies of phenologi-cal and demographic responses to climate changemuch of the basic ecology of species remains largelyunknown (Hoslashye amp Forchhammer 2008a) This is par-ticularly true of alpine polar and tropical speciessome of which might be most vulnerable to recentchanges in climate (Rodenhouse et al 2008 Postet al 2009) However even the demography of mostcommon species (eg plants birds amphibians andmammals) in the best-studied locations (eg easternNorth America and western Europe) is poorly under-stood The areas in which we lack adequateinformation range from a basic understanding of inter-annual variation in ecological interactions and climate-driven changes taking place to more complex topicssuch as identifying the consequences conservationimplications and management decisions dictated bythose changes

(c) Estimating the strength of ecological

relationships

Species with specialist relationships are among thosemost likely to show significant demographic effects ofphenological shifts Species that depend on particularresources that are available for limited times aremore vulnerable than are generalists which may beable to switch to sources to meet their needs as phenol-ogies change Any difference in nutritional value (orother aspects) of that new resource may causeincreases or declines in survival and reproductionbut subsequent changes in abundance will likely beslower than in specialists

Yet specialist interactions are rare in most biomesand establishing the existence of a specialist or verystrong interaction can be difficult especially if thespecies in question are rare In most cases species inter-actions occur as a network of interactions rather than asa one-to-one relation (Ings et al 2009) Even in the caseof apparent specialist interactions a speciesrsquo behaviourmay be plastic enough to interact with another speciesor resource when one becomes rare or disappearsThis potential presence of latent plasticity poses a par-ticular challenge for forecasting the vulnerability ofspecies to phenological mismatches

6 RECOMMENDATIONS FOR FUTURERESEARCH(a) Optimize monitoring protocols

The impact of climate-driven phenological changes onspecies abundance and persistence will be importantas natural-resource managers and policy-makers tryto anticipate mitigate or adapt to the challenges pre-sented by climate change Thus enhanced efforts togather data on both phenology and demography ofinteracting species are needed In many cases theeasiest approach may be to add phenological anddemographic observations at sites where investigationsof ecological interactions are already taking place (egForchhammer et al 2008)

In many instances though observational protocolscan be optimized to characterize timing-based multi-trophic interactions These optimizations include

Review Phenology and demography A J Miller-Rushing et al 3183

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actions such as monitoring the temporal distributionof phenological events like flowering rather thansimply the onset of them as is often done (Miller-Rushing et al 2008ab van Strien et al 2008)Temporal distributions reflect the behaviour of theentire population and allow for comparisons of thedegree of overlap between one species and another(eg Forrest et al 2010 figure 1) whereas first obser-vations do not necessarily reflect population-levelphenology (Miller-Rushing et al 2008b Moussuset al 2010) Additionally in many cases following asample of randomly chosen individual plants andanimals will yield higher-quality data than willpopulation-level observations although observationsof individuals will also require much more effort

The timing of observations of demographicparameters is also important For example there maybe a relatively short period during the growingseason when the effects of seasonal frost on inflores-cence production or seedling survival can be madeA single population census in midsummer could missmortality that results from a late-summer drought orheat wave Because phenology is time-sensitive by itsnature repeated observations of demographicparameters are necessary to understand the linkagesbetween many aspects of phenology and demographyMoreover the timing of these observations may needto change over time as conditions change Forexample the Zackenberg Research Station hasexpanded its field season of comprehensive ecosystemmonitoring in response to earlier springs and longergrowing seasons (M Rasch 2010 personalcommunication)

For measuring changes in interactions within andamong species we need observations of interactionnetworks their variability and reliable measures ofthe strength of interactions (Basilio et al 2006)Often frequency of interaction is substituted forstrength of interaction because the former is easier tomeasure Vazquez et al (2005) show that the relation-ship between interaction frequency and total effect aregenerally strongly correlated despite the fact thatinteraction frequency is not correlated with per-inter-action effect Thus although it is not idealobservations of the frequencies of interactions couldyield key insights into the strengths of interactions incommunities

(b) Identify hidden data sources

Despite the need for enhanced monitoring effortsthere are still many questions that can be answeredwith data that have already been collected Long-term ecological research sites bird observatoriesbotanical gardens farms field stations and universityextension facilities for example may host relevantdata sources and provide ideal locations for furtherwork on the impacts of phenological responses to cli-mate change on demography Data from museumand herbarium collections have been useful inreconstructing historical phenological patterns(Miller-Rushing et al 2006 MacGillivray et al2010) Data currently being collected by nationaland international phenology networks and through

Phil Trans R Soc B (2010)

remote sensing via satellites and cameras (Zhanget al 2004 Betancourt et al 2005 Menzel et al2006 Primack et al 2009 Richardson et al 2009)could provide additional phenological data that couldbe combined with demographic data collected by indi-vidual sites or from large networks like the MonitoringAvian Productivity and Survivorship (MAPS) program(Saracco et al 2008) Together these sources of datacould be used to identify species and locations forwhich temporal relationships are likely to change

Substituting space for time along latitudinal orelevational gradients can also provide data to explorethe relationships among climate variables phenologyand demography Although it can be difficult to isolatethe effects of particular factors along these gradientsmdashincluding genetic factors (ie local adaptation)mdashtheyprovide among the most powerful lsquonatural exper-imentsrsquo available to ecologists and are currentlyunderused (Korner 2007)

(c) Integrate observations experiments

and predictive models

Observational data can be very good at reflecting long-term changes taking place but experiments are gener-ally necessary to identify conclusively the mechanismsdriving the changes Much experimental work hasexplored abiotic controls of phenology (Augspurger1981 Berthold amp Terrill 1991 Farnsworth et al1995) but relatively few studies have explored the sub-sequent effects of phenology on demography in partbecause it is difficult to separate the effects of abioticconditions from those of phenology on demography(Galloway amp Burgess 2009) Additionally the demo-graphic effects of experimental manipulations ofphenology are often not realistic because they occurin laboratory conditions or manipulate the phenologyof individuals on a scale much smaller than the scaleof their relevant ecological interactions To understandbetter the effects of changing phenology on demogra-phy we propose better integration of observationalexperimental and modelling approaches An under-standing of long-term population dynamics fromobservational data and mechanistic insights gainedfrom experiments can be combined in models toallow testing of hypotheses that would be impracticalto address with experiments

In particular we believe that it is important to gen-erate models that couple phenological changes tochanges in abundance One approach that may proveuseful is integration of data on phenological responsesto environmental change with models used for popu-lation viability analysis (Marrero-Gomez et al 2007Mondragon 2009) or agent-based models in whichindividual variation and spatio-temporal dynamicscan be explicitly taken into account (Grimm et al2005) Additionally the development of populationmodels that incorporate the timing of life-historyevents (Post et al 2001) will help provide a theoreticalframework for quantifying the role of phenology inshaping demographic consequences of climatechange These models can generate hypotheses thatcan be tested with empirical observations andexperiments

3184 A J Miller-Rushing et al Review Phenology and demography

on September 28 2010rstbroyalsocietypublishingorgDownloaded from

(d) Life-history theory in a climate

change context

No clear theoretical framework exists for addressingquestions regarding the demographic effects of pheno-logical variation For instance longevity can play a rolein how quickly growth rate in a population responds toclimate change (Morris et al 2008) In their meta-analysis of demographic data for 36 plant and animalspecies Morris et al (2008) found that the populationgrowth rates of long-lived species were buffered fromchanges in rates of reproduction and survival relativeto short-lived species Thus long-lived species maybe better equipped to persist in an environment inwhich phenological mismatches become increasinglycommon On the other hand examples of declines inabundance of long-lived species in relation to climaticevents are well known (Vibe 1967 Klein 1968 Vors ampBoyce 2009) Meanwhile the abundance of short-lived species may respond relatively quickly to changesin climate conditionsmdasha relatively short series of yearswith favourable conditions (low mortality and highreproduction) could lead to rapid increases in popu-lation sizes whereas unfavourable conditions couldlead to sharp declines For some populations justone or two unfavourable years could lead to extinction

It is important that we further develop life-historytheory in the context of rapidly shifting phenology toprovide investigators with a framework for understand-ing the interactions and changes taking place and toprovide hypotheses that can be tested empiricallyMany aspects of current theory assume that phenologyis relatively stationary varying from year to yeararound a mean whereas now the phenologies ofmany species are changing directionally because ofchanging climatic conditions (Forrest amp Miller-Rushing 2010) Together new observational studiesexperiments models and theory will help us to clarifythe answers and improve predictions of futureecological responses to climate change

This work was supported by funding from the NationalScience Foundation (grant DEB 0922080 to DWI andAJM-R and ARC 0713994 and ARC 0902125 to EP)We thank Jessica Forrest Elizabeth Wolkovich and twoanonymous reviewers for providing valuable comments onearlier drafts of the manuscript

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Graae B Ejrnaeligs R Marchand F Milbau A ShevtsovaA Beyens L amp Nijs I 2009 The effect of an early-season short-term heat pulse on plant recruitment inthe Arctic Polar Biol 32 1117ndash1126 (doi101007s00300-009-0608-3)

Grimm V et al 2005 Pattern-oriented modeling of agent-based complex systems lessons from ecology Science310 987ndash991 (doi101126science1116681)

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Hoslashye T T amp Hammel J U 2010 Climate change and alti-tudinal variation in sexual size dimorphism in Arctic wolfspiders Clim Res 41 259ndash265 (doi103354cr00855)

Hoslashye T T Ellebjerg S M amp Philipp M 2007 The impactof climate on flowering in the high Arcticmdashthe case of

Dryas in a hybrid zone Arct Antarct Alp Res 39 412ndash421 (doi1016571523-0430(06-018)[HOYE]20CO2)

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Phase-dependent outbreak dynamics of geometrid mothlinked to host plant phenology Proc R Soc B 2764119ndash4128 (doi101098rspb20091148)

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How well do first flowering dates measure plant responsesto climate change The effects of population size andsampling frequency J Ecol 96 1289ndash1296 (doi10

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