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The potential for climate change to disrupt phenology-mediated interactions in interaction networks has attracted considerable attention in recent decades. Frequently, studies emphasize the fragility of ephemeral seasonal interactions, and the risks posed by phenological asynchrony. Here, we argue that the fitness consequences of asynchrony in phenological interactions may often be more buffered than is typically acknowledged. We identify three main forms that buffering may take: (i) mechanisms that reduce asynchrony between consumer and resource; (ii) mechanisms that reduce the costs of being asynchronous; and (iii) mechanisms that dampen interannual variance in performance across higher organizational units. Using synchrony between the hatching of winter moth caterpillars and the leafing of their host-plants as a case study, we identify a wide variety of buffers that reduce the detrimental consequences of phenological asynchrony on caterpillar individuals, populations, and meta-populations. We follow this by drawing on examples across a breadth of taxa, and demonstrate that these buffering mechanisms may be quite general. We conclude by identifying key gaps in our knowledge of the fitness and demographic consequences of buffering, in the context of phenological mismatch. Buffering has the potential to substantially alter our understanding of the biotic impacts of future climate change-a greater recognition of the contribution of these mechanisms may reveal that many trophic interactions are surprisingly resilient, and also serve to shift research emphasis to those systems with fewer buffers and towards identifying the limits of those buffers., (© 2024 John Wiley & Sons Ltd.)

The Arctic is undergoing dramatic environmental change with rapidly rising surface temperatures, accelerating sea ice decline and changing snow regimes, all of which influence tundra plant phenology. Despite these changes, no globally consistent direction of trends in spring phenology has been reported across the Arctic. While spring has advanced at some sites, spring has delayed or not changed at other sites, highlighting substantial unexplained variation. Here, we test the relative importance of local temperatures, local snow melt date and regional spring drop in sea ice extent as controls of variation in spring phenology across different sites and species. Trends in long-term time series of spring leaf-out and flowering (average span: 18 years) were highly variable for the 14 tundra species monitored at our four study sites on the Arctic coasts of Alaska, Canada and Greenland, ranging from advances of 10.06 days per decade to delays of 1.67 days per decade. Spring temperatures and the day of spring drop in sea ice extent advanced at all sites (average 1°C per decade and 21 days per decade, respectively), but only those sites with advances in snow melt (average 5 days advance per decade) also had advancing phenology. Variation in spring plant phenology was best explained by snow melt date (mean effect: 0.45 days advance in phenology per day advance snow melt) and, to a lesser extent, by mean spring temperature (mean effect: 2.39 days advance in phenology per °C). In contrast to previous studies examining sea ice and phenology at different spatial scales, regional spring drop in sea ice extent did not predict spring phenology for any species or site in our analysis. Our findings highlight that tundra vegetation responses to global change are more complex than a direct response to warming and emphasize the importance of snow melt as a local driver of tundra spring phenology., (© 2019 John Wiley & Sons Ltd.)

One consequence of rising spring temperatures is that the optimum timing of key life-history events may advance. Where this is the case, a population's fate may depend on the degree to which it is able to track a change in the optimum timing either via plasticity or via adaptation. Estimating the effect that temperature change will have on optimum timing using standard approaches is logistically challenging, with the result that very few estimates of this important parameter exist. Here we adopt an alternative statistical method that substitutes space for time to estimate the temperature sensitivity of the optimum timing of 22 plant species based on >200 000 spatiotemporal phenological observations from across the United Kingdom. We find that first leafing and flowering dates are sensitive to forcing (spring) temperatures, with optimum timing advancing by an average of 3 days °C -1 and plastic responses to forcing between -3 and -8 days °C -1 . Chilling (autumn/winter) temperatures and photoperiod tend to be important cues for species with early and late phenology, respectively. For most species, we find that plasticity is adaptive, and for seven species, plasticity is sufficient to track geographic variation in the optimum phenology. For four species, we find that plasticity is significantly steeper than the optimum slope that we estimate between forcing temperature and phenology, and we examine possible explanations for this countergradient pattern, including local adaptation., (© 2017 The Authors Global Change Biology Published by John Wiley & Sons Ltd.)

Projecting the fates of populations under climate change is one of global change biology's foremost challenges. Here, we seek to identify the contributions that temperature-mediated local adaptation and plasticity make to spatial variation in nesting phenology, a phenotypic trait showing strong responses to warming. We apply a mixed modeling framework to a Britain-wide spatiotemporal dataset comprising >100 000 records of first egg dates from four single-brooded passerine bird species. The average temperature during a specific time period (sliding window) strongly predicts spatiotemporal variation in lay date. All four species exhibit phenological plasticity, advancing lay date by 2-5 days °C(-1) . The initiation of this sliding window is delayed further north, which may be a response to a photoperiod threshold. Using clinal trends in phenology and temperature, we are able to estimate the temperature sensitivity of selection on lay date (B), but our estimates are highly sensitive to the temporal position of the sliding window. If the sliding window is of fixed duration with a start date determined by photoperiod, we find B is tracked by phenotypic plasticity. If, instead, we allow the start and duration of the sliding window to change with latitude, we find plasticity does not track B, although in this case, at odds with theoretical expectations, our estimates of B differ across latitude vs. longitude. We argue that a model combining photoperiod and mean temperature is most consistent with current understanding of phenological cues in passerines, the results from which suggest that each species could respond to projected increases in spring temperatures through plasticity alone. However, our estimates of B require further validation., (© 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.)

Phenology shifts are the most widely cited examples of the biological impact of climate change, yet there are few assessments of potential effects on the fitness of individual organisms or the persistence of populations. Despite extensive evidence of climate-driven advances in phenological events over recent decades, comparable patterns across species' geographic ranges have seldom been described. Even fewer studies have quantified concurrent spatial gradients and temporal trends between phenology and climate. Here we analyse a large data set (~129 000 phenology measures) over 37 years across the UK to provide the first phylogenetic comparative analysis of the relative roles of plasticity and local adaptation in generating spatial and temporal patterns in butterfly mean flight dates. Although populations of all species exhibit a plastic response to temperature, with adult emergence dates earlier in warmer years by an average of 6.4 days per °C, among-population differences are significantly lower on average, at 4.3 days per °C. Emergence dates of most species are more synchronised over their geographic range than is predicted by their relationship between mean flight date and temperature over time, suggesting local adaptation. Biological traits of species only weakly explained the variation in differences between space-temperature and time-temperature phenological responses, suggesting that multiple mechanisms may operate to maintain local adaptation. As niche models assume constant relationships between occurrence and environmental conditions across a species' entire range, an important implication of the temperature-mediated local adaptation detected here is that populations of insects are much more sensitive to future climate changes than current projections suggest., (© 2015 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

The rise in spring temperatures over the past half-century has led to advances in the phenology of many nontropical plants and animals. As species and populations differ in their phenological responses to temperature, an increase in temperatures has the potential to alter timing-dependent species interactions. One species-interaction that may be affected is the competition for light in deciduous forests, where early vernal species have a narrow window of opportunity for growth before late spring species cast shade. Here we consider the Marsham phenology time series of first leafing dates of thirteen tree species and flowering dates of one ground flora species, which spans two centuries. The exceptional length of this time series permits a rare comparison of the statistical support for parameter-rich regression and mechanistic thermal sensitivity phenology models. While mechanistic models perform best in the majority of cases, both they and the regression models provide remarkably consistent insights into the relative sensitivity of each species to forcing and chilling effects. All species are sensitive to spring forcing, but we also find that vernal and northern European species are responsive to cold temperatures in the previous autumn. Whether this sensitivity reflects a chilling requirement or a delaying of dormancy remains to be tested. We then apply the models to projected future temperature data under a fossil fuel intensive emissions scenario and predict that while some species will advance substantially others will advance by less and may even be delayed due to a rise in autumn and winter temperatures. Considering the projected responses of all fourteen species, we anticipate a change in the order of spring events, which may lead to changes in competitive advantage for light with potential implications for the composition of temperate forests., (© 2015 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.)