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Phenological responses to climate change frequently vary among trophic levels, which can result in increasing asynchrony between the peak energy requirements of consumers and the availability of resources. Migratory birds use multiple habitats with seasonal food resources along migration flyways. Spatially heterogeneous climate change could cause the phenology of food availability along the migration flyway to become desynchronized. Such heterogeneous shifts in food phenology could pose a challenge to migratory birds by reducing their opportunity for food availability along the migration path and consequently influencing their survival and reproduction. We develop a novel graph-based approach to quantify this problem and deploy it to evaluate the condition of the heterogeneous shifts in vegetation phenology for 16 migratory herbivorous waterfowl species in Asia. We show that climate change-induced heterogeneous shifts in vegetation phenology could cause a 12% loss of migration network integrity on average across all study species. Species that winter at relatively lower latitudes are subjected to a higher loss of integrity in their migration network. These findings highlight the susceptibility of migratory species to climate change. Our proposed methodological framework could be applied to migratory species in general to yield an accurate assessment of the exposure under climate change and help to identify actions for biodiversity conservation in the face of climate-related risks., (© 2024 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Climate warming has caused the seasonal timing of many components of ecological food chains to advance. In the context of trophic interactions, the match-mismatch hypothesis postulates that differential shifts can lead to phenological asynchrony with negative impacts for consumers. However, at present there has been no consistent analysis of the links between temperature change, phenological asynchrony and individual-to-population-level impacts across taxa, trophic levels and biomes at a global scale. Here, we propose five criteria that all need to be met to demonstrate that temperature-mediated trophic asynchrony poses a growing risk to consumers. We conduct a literature review of 109 papers studying 129 taxa, and find that all five criteria are assessed for only two taxa, with the majority of taxa only having one or two criteria assessed. Crucially, nearly every study was conducted in Europe or North America, and most studies were on terrestrial secondary consumers. We thus lack a robust evidence base from which to draw general conclusions about the risk that climate-mediated trophic asynchrony may pose to populations worldwide.

Changes in the timing of life-history events (phenology) are a widespread consequence of climate change. Predicting population resilience requires knowledge of how phenology is likely to change over time, which can be gained by identifying the specific environmental cues that drive phenological events. Cue identification is often achieved with statistical testing of candidate cues. As the number of methods used to generate predictions increases, assessing the predictive accuracy of different approaches has become necessary. This study aims to (a) provide an empirical illustration of the predictive ability of five commonly applied statistical methods for cue identification (absolute and relative sliding time window analyses, penalized signal regression, climate sensitivity profiles and a growing degree-day model) and (b) discuss approaches for implementing cue identification methods in different systems. Using a dataset of mean clutch initiation timing in wild great tits (Parus major), we explored how the days of the year identified as most important, and the aggregate statistic identified as a cue, differed between statistical methods and with respect to the time span of data used. Each method's predictive capacity was tested using cross-validation and assessed for robustness to varying sample size. We show that the identified critical time window of cue sensitivity was consistent across four of the five methods. The accuracy and precision of predictions differed by method with penalized signal regression resulting in the most accurate and most precise predictions in our case. Accuracy was maximal for near-future predictions and showed a relationship with time. The difference between predictions and observations systematically shifted across the study from preceding observations to lagging. This temporal trend in prediction error suggests that the current statistical tools either fail to capture a key component of the cue-phenology relationship, or the relationship itself is changing through time in our system. These two influences need to be teased apart if we are to generate realistic predictions of phenological change. We recommend future phenological studies to challenge the idea of a static cue-phenology relationship and should cross-validate results across multiple time periods., (© 2019 The Authors. Journal of Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)

The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long‐term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad‐scale global issues (e.g. climate change).To solve data integration issues and enable a new scale of ecological and evolutionary research based on long‐term studies of birds, we have created the SPI‐Birds Network and Database (www.spibirds.org)—a large‐scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI‐Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting.SPI‐Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community‐derived data and meta‐data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta‐data language).The encouraging community involvement stems from SPI‐Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI‐Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community‐specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much‐needed large‐scale ecological data integration. [ABSTRACT FROM AUTHOR]

Climate change has been shown to induce shifts in the timing of life‐history events. As a result, interactions between species can become disrupted, with potentially detrimental effects. Predicting these consequences has proven challenging. We apply structured population models to a well‐characterised great tit‐caterpillar model system and identify thresholds of temporal asynchrony, beyond which the predator population will rapidly go extinct. Our model suggests that phenotypic plasticity in predator breeding timing initially maintains temporal synchrony in the face of environmental change. However, under projections of climate change, predator plasticity was insufficient to keep pace with prey phenology. Directional evolution then accelerated, but could not prevent mismatch. Once predator phenology lagged behind prey by more than 24 days, rapid extinction was inevitable, despite previously stable population dynamics. Our projections suggest that current population stability could be masking a route to population collapse, if high greenhouse gas emissions continue. [ABSTRACT FROM AUTHOR]

Global climate change is altering the timing of life history events for species living in seasonal environments. These shifts in phenology can lead to the disruption of interspecific relationships with implications for individual fitness. Predicting phenological change and its population level consequences can provide insights into population persistence. Achieving this is challenging for labile traits as current structured population models do not explicitly distinguish between the roles of phenotypic plasticity and micro‐evolution, hindering realistic predictions of trait change. In this study we present the first empirical test of a new integral projection model (IPM) framework, which allows phenotypic plasticity and micro‐evolution to be teased apart by incorporating a quantitative genetic inheritance function. We parameterise this model for a population of wild great tits Parus major and test its predictive capabilities through K‐fold cross validation. We test the predictive accuracy of the quantitative genetic IPM in comparison to the standard IPM. We demonstrate that adding genetic inheritance rules maintains high accuracy of projections of phenological change, relative to the standard IPM. In addition, we find almost identical projections of population dynamics in this population for both IPMs, demonstrating that this model formulation allows researchers to investigate the contributions of phenotypic plasticity and micro‐evolution to trait change, without sacrificing predictive accuracy. Modelling in this way reveals that, under directional environmental change, both micro‐evolution and plasticity contribute to an advance of phenology, although the effect of plasticity is an order of magnitude higher than evolution. Despite this, synchrony between great tits and their caterpillar prey was reduced and population declines occurred. Our approach demonstrates that this model framework provides a promising avenue through which to explore the roles of phenotypic plasticity and evolution in trait changes and population dynamics. [ABSTRACT FROM AUTHOR]

For organisms living in seasonal environments, synchronizing the peak energetic demands of reproduction with peak food availability is a key challenge. Understanding the extent to which animals can adjust behavior to optimize reproductive timing, and the cues they use to do this, is essential for predicting how they will respond to future climate change. In birds, the timing of peak energetic demand is largely determined by the timing of clutch initiation; however, considerable alterations can still occur once egg laying has begun. Here, we use a wild population of great tits ( Parus major) to quantify individual variation in different aspects of incubation behavior (onset, duration, and daily intensity) and conduct a comprehensive assessment of the causes and consequences of this variation. Using a 54-year dataset, we demonstrate that timing of hatching relative to peak prey abundance (synchrony) is a better predictor of reproductive success than clutch initiation or clutch completion timing, suggesting adjustments to reproductive timing via incubation are adaptive in this species. Using detailed in-nest temperature recordings, we found that postlaying, birds improved their synchrony with the food peak primarily by varying the onset of incubation, with duration changes playing a lesser role. We then used a sliding time window approach to explore which spring temperature cues best predict variance in each aspect of incubation behavior. Variation in the onset of incubation correlated with mean temperatures just prior to laying; however, incubation duration could not be explained by any of our temperature variables. Daily incubation intensity varied in response to daily maximum temperatures throughout incubation, suggesting female great tits respond to temperature cues even in late stages of incubation. Our results suggest that multiple aspects of the breeding cycle influence the final timing of peak energetic demand. Such adjustments could compensate, in part, for poor initial timing, which has significant fitness impacts. [ABSTRACT FROM AUTHOR]