Evolutionary and demographic consequences of phenological mismatches

Visser, Marcel E.; Gienapp, Phillip

doi:10.1038/s41559-019-0880-8

Cited by 302 publications

(374 citation statements)

References 89 publications

(125 reference statements)

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“…Organisms occupying seasonal environments have evolved mechanisms for the timing of their life cycles (i.e., phenology) to match with optimal environmental conditions and resources at their location (Bradshaw & Holzapfel, 2007;Williams, Henry, & Sinclair, 2015). Such phenological mismatches are becoming increasingly common under climate change (Cohen, Lajeunesse, & Rohr, 2018;Parmesan & Yohe, 2003;Thackeray et al, 2010), which in the absence of adaptive responses could lead to population declines and local extinctions (Visser & Gienapp, 2019). Such phenological mismatches are becoming increasingly common under climate change (Cohen, Lajeunesse, & Rohr, 2018;Parmesan & Yohe, 2003;Thackeray et al, 2010), which in the absence of adaptive responses could lead to population declines and local extinctions (Visser & Gienapp, 2019).…”

Section: Introductionmentioning

confidence: 99%

Local climate determines vulnerability to camouflage mismatch in snowshoe hares

Zímová

Sirén

Nowak

et al. 2019

Global Ecol Biogeogr

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Aim: Phenological mismatches, when life-events become mistimed with optimal environmental conditions, have become increasingly common under climate change.Population-level susceptibility to mismatches depends on how phenology and phenotypic plasticity vary across a species' distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal.Major taxa studied: Snowshoe hare (Lepus americanus). Methods:We used > 5,500 by-catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high-resolution climate data. We estimated occurrence of camouflage mismatch between hares' coat colour and the presence and absence of snow over 7 years of monitoring.Results: Spatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low-snow years in regions characterized by shallow, short-lasting snowpack.Main conclusions: Long-term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species' range. Our results underscore the population-specific susceptibility to climate change-induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change. ACK N OWLED G M ENTSWe are grateful to the many field technicians and volunteers who managed the remote camera sites and photographs. Next, we thank Sean T. Giery, Zac A. Cheviron and two anonymous referees for their comments on earlier drafts.

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Section: Introductionmentioning

confidence: 99%

Local climate determines vulnerability to camouflage mismatch in snowshoe hares

Zímová

Sirén

Nowak

et al. 2019

Global Ecol Biogeogr

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“…Chevin et al, 2015;Reed et al, 2013;Visser & Both, 2005;Visser et al, 1998). Since the reproductive fitness of the great tits depends strongly on the mismatch with food phenology, mistiming in our case therefore equals mismatch, even though the food resource phenology is not considered in our study (see Visser and Gienapp (2019) for the difference between mistiming and mismatch).…”

Section: Stabilizing Selection Via the Mean Number Of Fledglingsmentioning

confidence: 91%

A time‐series model for estimating temporal variation in phenotypic selection on laying dates in a Dutch great tit population

2019

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Temporal and spatial variation in phenotypic selection due to changing environmental conditions is of great interest to evolutionary biologists, but few existing methods estimating its magnitude take into account the temporal autocorrelation. We use state‐space models (SSMs) to analyse phenotypic selection processes that cannot be observed directly and use Template Model builder (TMB), an R package for computing and maximizing the Laplace approximation of the marginal likelihood for SSM and other complex, nonlinear latent variable model via automatic differentiation. Using a long‐term great tit (Parus major) dataset, we fit several SSMs and conduct model selection based on Akaike information criterion (AIC) to assess the support for fluctuated directional or autocorrelated stabilizing selection on breeding time of the great tit population. Our results show that there is directional selection on the probability of breeding failure, and stabilizing selection on the mean number of fledglings. This selection for early laying date is consistent with a previous study of the same population. We also estimate the variation and autocorrelation in other parameters of the fitness functions, including the width and height, and found the height and location of annual fitness function are autocorrelated with significant variation, while the width can be assumed to constant over time. Using TMB to fit SSMs, we are able to estimate additional parameters compared to previous methods, all without requiring a substantial increase in computational resources. Furthermore, our specification of complex nonlinear model structure benefits greatly from the flexibility of model formulation with TMB. Therefore, our approach could be directly applied to estimating even more complicated phenotypic selection processes induced by environmental change for other species.

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“…Typically, warming springs lead to an advancement in phenological events and these advancements occur at different rates between different trophic levels (Kharouba et al, ; Thackeray et al, , ). The unequal shift in phenology between consumers and their resources, referred to as ‘phenological mismatch’ (Cushing, ; Durant et al, ; Stenseth & Mysterud, ; Visser & Gienapp, ), has in some cases been linked to directional selection on consumer phenology (Marrot, Charmantier, Blondel, & Garant, ; Reed, Jenouvrier, & Visser, ; Visser et al, ) and negative effects on consumer demography (Plard et al, ).…”

Section: Introductionmentioning

confidence: 99%

Comparing two measures of phenological synchrony in a predator–prey interaction: Simpler works better

Ramakers

Gienapp

Visser

2019

Journal of Animal Ecology

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Global climate change has sparked a vast research effort into the demographic and evolutionary consequences of mismatches between consumer and resource phenology. Many studies have used the difference in peak dates to quantify phenological synchrony (match in dates, MD), but this approach has been suggested to be inconclusive, since it does not incorporate the temporal overlap between the phenological distributions (match in overlap, MO). We used 24 years of detailed data on the phenology of a predator–prey system, the great tit (Parus major) and the main food for its nestlings, caterpillars, to estimate MD and MO at the population and brood levels. We compared the performance of both metrics on two key demographic parameters: offspring recruitment probability and selection on the timing of reproduction. Although MD and MO correlated quadratically as expected, MD was a better predictor for both offspring recruitment and selection on timing than MO. We argue—and verify through simulations—that this is because quantifying MO has to be based on nontrivial, difficult‐to‐verify assumptions that likely render MO too inaccurate as a proxy for food availability in practice. Our results have important implications for the allocation of research efforts in long‐term population studies in highly seasonal environments.

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Evolutionary and demographic consequences of phenological mismatches

Cited by 302 publications

References 89 publications

Local climate determines vulnerability to camouflage mismatch in snowshoe hares

Local climate determines vulnerability to camouflage mismatch in snowshoe hares

A time‐series model for estimating temporal variation in phenotypic selection on laying dates in a Dutch great tit population

Comparing two measures of phenological synchrony in a predator–prey interaction: Simpler works better

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