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Bees provide a vital ecosystem service to agriculture by contributing to the pollination of many leading global crops. Human wellbeing depends not only on the quantity of agricultural yields, but also on the stability and resilience of crop production. Yet a broad understanding of how the diversity and composition of pollinator communities may influence crop pollination service has previously been hindered by a scarcity of standardized data. We used outputs from Bayesian occupancy detection models to examine patterns in the inter-annual occupancy dynamics of the bee pollinator communities of four contrasting crops (apples, field bean, oilseed and strawberries) in Great Britain between 1985 and 2015. We compared how the composition and species richness of different crop pollinator communities may affect the stability of crop pollinator occurrence. Across the four crops, we found that the inter-annual occupancy dynamics of the associated pollinator communities tended to be more similar in smaller communities with closely related pollinator species. Our results indicate that crop pollinator communities composed of a small number of closely related bee species show greater variance in mean occupancy compared to crops with more diverse pollinator communities. Lower variance in the occurrence of crop pollinating bee species may lead to more stable crop pollination services. Finally, whilst our results initially indicated some redundancy within most crop pollinator communities, with no, or little, increase in the variance of overall mean occupancy when species were initially removed, this was followed by a rapid acceleration in the variance of crop pollinator occurrence as each crop's bee pollinator community was increasingly depreciated. High inter-annual variations in pollination services have negative implications for crop production and food security. High bee diversity could ensure more stable and resilient crop pollination services, yet current agri-environment schem

The influence of large-scale variables such as climate change on phenology has received a great deal of research attention. However, local environmental factors also play a key role in determining the timing of species life cycles. Using the meadow brown butterfly Maniola jurtina as an example, we investigate how a specific habitat type, lowland calcareous grassland, can affect the timing of flight dates. Although protracted flight periods have previously been reported in populations on chalk grassland sites in the south of England, no attempt has yet been made to quantify this at a national level, or to assess links with population genetics and drought tolerance. Using data from 539 sites across the UK, these differences in phenology are quantified, and M. jurtina phenology is found to be strongly associated with both site geology and topography, independent of levels of abundance. Further investigation into aspects of M. jurtina ecology at a subset of sites finds no genetic structuring or drought tolerance associated with these same site conditions.

The influence of large-scale variables such as climate change on phenology has received a great deal of research attention. However, local environmental factors also play a key role in determining the timing of species life cycles. Using the meadow brown butterfly Maniola jurtina as an example, we investigate how a specific habitat type, lowland calcareous grassland, can affect the timing of flight dates. Although protracted flight periods have previously been reported in populations on chalk grassland sites in the south of England, no attempt has yet been made to quantify this at a national level, or to assess links with population genetics and drought tolerance. Using data from 539 sites across the UK, these differences in phenology are quantified, and M. jurtina phenology is found to be strongly associated with both site geology and topography, independent of levels of abundance. Further investigation into aspects of M. jurtina ecology at a subset of sites finds no genetic structuring or drought tolerance associated with these same site conditions.

Understanding how environmental change affects ecosystem function delivery is of primary importance for fundamental and applied ecology. Current approaches focus on single environmental driver effects on communities, mediated by individual response traits. Data limitations present constraints in scaling up this approach to predict the impacts of multivariate environmental change on ecosystem functioning. We present a more holistic approach to determine ecosystem function resilience, using long‐term monitoring data to analyze the aggregate impact of multiple historic environmental drivers on species' population dynamics. By assessing covariation in population dynamics between pairs of species, we identify which species respond most synchronously to environmental change and allocate species into “response guilds.” We then use “production functions” combining trait data to estimate the relative roles of species to ecosystem functions. We quantify the correlation between response guilds and production functions, assessing the resilience of ecosystem functioning to environmental change, with asynchronous dynamics of species in the same functional guild expected to lead to more stable ecosystem functioning. Testing this method using data for butterflies collected over four decades in the United Kingdom, we find three ecosystem functions (resource provisioning, wildflower pollination, and aesthetic cultural value) appear relatively robust, with functionally important species dispersed across response guilds, suggesting more stable ecosystem functioning. Additionally, by relating genetic distances to response guilds we assess the heritability of responses to environmental change. Our results suggest it may be feasible to infer population responses of butterflies to environmental change based on phylogeny—a useful insight for conservation management of rare species with limited population monitoring data. Our approach holds promise for overcoming the impasse in predicting th

Understanding how environmental change affects ecosystem function delivery is of primary importance for fundamental and applied ecology. Current approaches focus on single environmental driver effects on communities, mediated by individual response traits. Data limitations present constraints in scaling up this approach to predict the impacts of multivariate environmental change on ecosystem functioning. We present a more holistic approach to determine ecosystem function resilience, using long‐term monitoring data to analyze the aggregate impact of multiple historic environmental drivers on species' population dynamics. By assessing covariation in population dynamics between pairs of species, we identify which species respond most synchronously to environmental change and allocate species into “response guilds.” We then use “production functions” combining trait data to estimate the relative roles of species to ecosystem functions. We quantify the correlation between response guilds and production functions, assessing the resilience of ecosystem functioning to environmental change, with asynchronous dynamics of species in the same functional guild expected to lead to more stable ecosystem functioning. Testing this method using data for butterflies collected over four decades in the United Kingdom, we find three ecosystem functions (resource provisioning, wildflower pollination, and aesthetic cultural value) appear relatively robust, with functionally important species dispersed across response guilds, suggesting more stable ecosystem functioning. Additionally, by relating genetic distances to response guilds we assess the heritability of responses to environmental change. Our results suggest it may be feasible to infer population responses of butterflies to environmental change based on phylogeny—a useful insight for conservation management of rare species with limited population monitoring data. Our approach holds promise for overcoming the impasse in predicting th