• Energy Research

AbstractPlant phenology research has surged in recent decades, in part due to interest in phenological sensitivity to climate change and the vital role phenology plays in ecology. Many local‐scale studies have generated important findings regarding the physiology, responses, and risks associated with shifts in plant phenology. By comparison, our understanding of regional‐ and global‐scale phenology has been largely limited to remote sensing of green‐up without the ability to differentiate among plant species. However, a new generation of analytical tools and data sources—including enhanced remote sensing products, digitized herbarium specimen data, and public participation in science—now permits investigating patterns and drivers of phenology across extensive taxonomic, temporal, and spatial scales, in an emerging field that we call macrophenology. Recent studies have highlighted how phenology affects dynamics at broad scales, including species interactions and ranges, carbon fluxes, and climate. At the cusp of this developing field of study, we review the theoretical and practical advances in four primary areas of plant macrophenology: (1) global patterns and shifts in plant phenology, (2) within‐species changes in phenology as they mediate species' range limits and invasions at the regional scale, (3) broad‐scale variation in phenology among species leading to ecological mismatches, and (4) interactions between phenology and global ecosystem processes. To stimulate future research, we describe opportunities for macrophenology to address grand challenges in each of these research areas, as well as recently available data sources that enhance and enable macrophenology research.

AbstractClimate change is shifting the environmental cues that determine the phenology of interacting species. Plant–pollinator systems may be susceptible to temporal mismatch if bees and flowering plants differ in their phenological responses to warming temperatures. While the cues that trigger flowering are well‐understood, little is known about what determines bee phenology. Using generalised additive models, we analyzed time‐series data representing 67 bee species collected over 9 years in the Colorado Rocky Mountains to perform the first community‐wide quantification of the drivers of bee phenology. Bee emergence was sensitive to climatic variation, advancing with earlier snowmelt timing, whereas later phenophases were best explained by functional traits including overwintering stage and nest location. Comparison of these findings to a long‐term flower study showed that bee phenology is less sensitive than flower phenology to climatic variation, indicating potential for reduced synchrony of flowers and pollinators under climate change.

Climate change affects not just where species are found, but also when species' key life-history events occur-their phenology. Measuring such changes in timing is often hampered by a reliance on biased survey data: surveys identify that an event has taken place (for example, the flower is in bloom), but not when that event happened (for example, the flower bloomed yesterday). Here, we show that this problem can be circumvented using statistical estimators, which can provide accurate and unbiased estimates from sparsely sampled observations. We demonstrate that such methods can resolve an ongoing debate about the relative timings of the onset and cessation of flowering, and allow us to place modern observations reliably within the context of the vast wealth of historical data that reside in herbaria, museum collections, and written records. We also analyse large-scale citizen science data from the United States National Phenology Network and reveal not just earlier but also potentially more variable flowering in recent years. Evidence for greater variability through time is important because increases in variation are characteristic of systems approaching a state change.

A substantial body of evidence has demonstrated that biodiversity stabilizes ecosystem functioning over time in grassland ecosystems. However, the relative importance of different facets of biodiversity underlying the diversity-stability relationship remains unclear. Here we use data from 39 grassland biodiversity experiments and structural equation modelling to investigate the roles of species richness, phylogenetic diversity and both the diversity and community-weighted mean of functional traits representing the 'fast-slow' leaf economics spectrum in driving the diversity-stability relationship. We found that high species richness and phylogenetic diversity stabilize biomass production via enhanced asynchrony in the performance of co-occurring species. Contrary to expectations, low phylogenetic diversity enhances ecosystem stability directly, albeit weakly. While the diversity of fast-slow functional traits has a weak effect on ecosystem stability, communities dominated by slow species enhance ecosystem stability by increasing mean biomass production relative to the standard deviation of biomass over time. Our in-depth, integrative assessment of factors influencing the diversity-stability relationship demonstrates a more multicausal relationship than has been previously acknowledged.

AbstractAdvancing spring phenology is a well-documented consequence of anthropogenic climate change, but it is not well understood how climate change will affect the variability of phenology year-to-year. Species’ phenological timings reflect adaptation to a broad suite of abiotic needs (e.g. thermal energy) and biotic interactions (e.g. predation and pollination), and changes in patterns of variability may disrupt those adaptations and interactions. Here, we present a geographically and taxonomically broad analysis of phenological shifts, temperature sensitivity, and changes in inter-annual variance encompassing nearly 10,000 long-term phenology time-series representing over 1,000 species across much of the northern hemisphere. We show that early-season species in colder and less seasonal regions were the most sensitive to temperature change and had the least variable phenologies. The timings of leaf-out, flowering, insect first-occurrence, and bird arrival have all shifted earlier and tend to be less variable in warmer years. This has led leaf-out and flower phenology to become moderately but significantly less variable over time. These simultaneous changes in phenological averages and the variation around them have the potential to influence mismatches among interacting species that are difficult to anticipate if shifts in average are studied in isolation.

Abstract Determining when animal populations have experienced stress in the past is fundamental to understanding how risk factors drive contemporary and future species' responses to environmental change. For insects, quantifying stress and associating it with environmental factors has been challenging due to a paucity of time‐series data and because detectable population‐level responses can show varying lag effects. One solution is to leverage historic entomological specimens to detect morphological proxies of stress experienced at the time stressors emerged, allowing us to more accurately determine population responses. Here we studied specimens of four bumblebee species, an invaluable group of insect pollinators, from five museums collected across Britain over the 20th century. We calculated the degree of fluctuating asymmetry (FA; random deviations from bilateral symmetry) between the right and left forewings as a potential proxy of developmental stress. We: (a) investigated whether baseline FA levels vary between species, and how this compares between the first and second half of the century; (b) determined the extent of FA change over the century in the four bumblebee species, and whether this followed a linear or nonlinear trend; (c) tested which annual climatic conditions correlated with increased FA in bumblebees. Species differed in their baseline FA, with FA being higher in the two species that have recently expanded their ranges in Britain. Overall, FA significantly increased over the century but followed a nonlinear trend, with the increase starting c. 1925. We found relatively warm and wet years were associated with higher FA. Collectively our findings show that FA in bumblebees increased over the 20th century and under weather conditions that will likely increase in frequency with climate change. By plotting FA trends and quantifying the contribution of annual climate conditions on past populations, we provide an important step towards improving our understanding of how environmental factors could impact future populations of wild beneficial insects.