Asynchrony in terrestrial insect abundance corresponds with species traits.

Asynchrony in population abundance can buffer the effects of environmental change leading to greater community and ecosystem stability. Both environmental (abiotic) drivers and species functional (biotic) traits can influence population dynamics leading to asynchrony. However, empirical evidence linking dissimilarity in species traits to abundance asynchrony is limited, especially for understudied taxa such as insects. To fill this knowledge gap, we explored the relationship between pairwise species trait dissimilarity and asynchrony in interannual abundance change between pairs of species for 422 moth, butterfly, and bumblebee species in Great Britain. We also explored patterns differentiating traits that we assumed to capture 'sensitivity to environmental variables' (such as body mass), and traits that may reflect 'diversity in exposure' to environmental conditions and lead to niche partitioning (for example, habitat uses, and intra-annual emergence periods). As expected, species trait dissimilarity calculated overall and for many individual traits representing response and exposure was positively correlated with asynchrony in all three insect groups. We found that 'exposure' traits, especially those relating to the phenology of species, had the strongest relationship with abundance asynchrony from all tested traits. Positive relationships were not simply due to shared evolutionary history leading to similar life-history strategies: detected effects remained significant for most traits after accounting for phylogenetic relationships within models. Our results provide empirical support that dissimilarity in traits linked to species exposure and sensitivity to the environment could be important for temporal dissimilarity in insect abundance. Hence, we suggest that general trait diversity, but especially diversity in 'exposure' traits, could play a significant role in the resilience of insect communities to short-term environmental perturbations through driving asynchrony between species abundances.

Population links between an insectivorous bird and moths disentangled through national-scale monitoring data.

Insects are key components of food chains, and monitoring data provides new opportunities to identify trophic relationships at broad spatial and temporal scales. Here, combining two monitoring datasets from Great Britain, we reveal how the population dynamics of the blue tit Cyanistes caeruleus are influenced by the abundance of moths - a core component of their breeding diet. We find that years with increased population growth for blue tits correlate strongly with high moth abundance, but population growth in moths and birds is less well correlated; suggesting moth abundance directly affects bird population change. Next, we identify moths that are important components of blue tit diet, recovering associations to species previously identified as key food sources such as the winter moth Operoptera brumata. Our work provides new evidence that insect abundance impacts bird population dynamics in natural communities and provides insight into spatial diet turnover at a national-scale.

Abundance trends for river macroinvertebrates vary across taxa, trophic group and river typology.

There is mounting evidence that terrestrial arthropods are declining rapidly in many areas of the world. It is unclear whether freshwater invertebrates, which are key providers of ecosystem services, are also declining. We addressed this question by analysing a long-term dataset of macroinvertebrate abundance collected from 2002 to 2019 across 5009 sampling sites in English rivers. Patterns varied markedly across taxonomic groups. Within trophic groups we detected increases in the abundance of carnivores by 19% and herbivores by 14.8%, while we estimated decomposers have declined by 21.7% in abundance since 2002. We also found heterogeneity in trends across rivers belonging to different typologies based on geological dominance and catchment altitude, with organic lowland rivers having generally higher rates of increase in abundance across taxa and trophic groups, with siliceous lowland rivers having the most declines. Our results reveal a complex picture of change in freshwater macroinvertebrate abundance between taxonomic groups, trophic levels and river typologies. Our analysis helps with identifying priority regions for action on potential environmental stressors where we discover macroinvertebrate abundance declines.

A safe and just operating space for human identity: a systems perspective.

A safe and just operating space for socioecological systems is a powerful bridging concept in sustainability science. It integrates biophysical earth-system tipping points (ie, thresholds at which small changes can lead to amplifying effects) with social science considerations of distributional equity and justice. Often neglected, however, are the multiple feedback loops between self-identity and planetary boundaries. Environmental degradation can reduce self-identification with nature, leading to decreased pro-environmental behaviours and decreased cooperation with out-groups, further increasing the likelihood of transgressing planetary boundaries. This vicious cycle competes with a virtuous one, where improving environmental quality enhances the integration of nature into self-identity and improves health, thereby facilitating prosocial and pro-environmental behaviour. These behavioural changes can also cascade up to influence social and economic institutions. Given a possible minimum degree of individual self-care to maintain health and prosperity, there would seem to exist an analogous safe and just operating space for self-identity, for which system stewardship for planetary health is crucial.

Where and why are species' range shifts hampered by unsuitable landscapes?

There is widespread concern that species will fail to track climate change if habitat is too scarce or insufficiently connected. Targeted restoration has been advocated to help species adapt, and a "conductance" metric has been proposed, based on simulation studies, to predict effective habitat configurations. However, until now there is very little empirical evidence on how the configuration of habitat is affecting expansion at species' cool range margins. We analysed the colonisation events that have occurred in continuously monitored trap locations for 54 species of southerly distributed moths in Britain between 1985 and 2011. We tested whether the time until colonisation was affected by attributes of each species, and of intervening landcover and climate between the trap and the baseline distribution (1965-1985). For woodland species, the time until colonisation of new locations was predicted by the "conductance" of woodland habitat, and this relationship was general, regardless of species' exact dispersal distances and habitat needs. This shows that contemporary range shifts are being influenced by habitat configuration as well as simple habitat extent. For species associated with farmland or suburban habitats, colonisation was significantly slower through landscapes with a high variance in elevation and/or temperature. Therefore, it is not safe to assume that such relatively tolerant species face no geographical barriers to range expansion. We thus elucidate how species' attributes interact with landscape characteristics to create highly heterogeneous patterns of shifting at cool range margins. Conductance, and other predictors of range shifts, can provide a foundation for developing coherent conservation strategies to manage range shifts for entire communities.

Local adaptation to climate anomalies relates to species phylogeny.

Climatic anomalies are increasing in intensity and frequency due to rapid rates of global change, leading to increased extinction risk for many species. The impacts of anomalies are likely to vary between species due to different degrees of sensitivity and extents of local adaptation. Here, we used long-term butterfly monitoring data of 143 species across six European bioclimatic regions to show how species' population dynamics have responded to local or globally-calculated climatic anomalies, and how species attributes mediate these responses. Contrary to expectations, degree of apparent local adaptation, estimated from the relative population sensitivity to local versus global anomalies, showed no associations with species mobility or reproductive rate but did contain a strong phylogenetic signal. The existence of phylogenetically-patterned local adaptation to climate has important implications for forecasting species responses to current and future climatic conditions and for developing appropriate conservation practices.

The influence of chalk grasslands on butterfly phenology and ecology.

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.

Environmental drivers of annual population fluctuations in a trans-Saharan insect migrant.

Many latitudinal insect migrants including agricultural pests, disease vectors, and beneficial species show huge fluctuations in the year-to-year abundance of spring immigrants reaching temperate zones. It is widely believed that this variation is driven by climatic conditions in the winter-breeding regions, but evidence is lacking. We identified the environmental drivers of the annual population dynamics of a cosmopolitan migrant butterfly (the painted lady Vanessa cardui) using a combination of long-term monitoring and climate and atmospheric data within the western part of its Afro-Palearctic migratory range. Our population models show that a combination of high winter NDVI (normalized difference vegetation index) in the Savanna/Sahel of sub-Saharan Africa, high spring NDVI in the Maghreb of North Africa, and frequent favorably directed tailwinds during migration periods are the three most important drivers of the size of the immigration to western Europe, while our atmospheric trajectory simulations demonstrate regular opportunities for wind-borne trans-Saharan movements. The effects of sub-Saharan vegetative productivity and wind conditions confirm that painted lady populations on either side of the Sahara are linked by regular mass migrations, making this the longest annual insect migration circuit so far known. Our results provide a quantification of the environmental drivers of large annual population fluctuations of an insect migrant and hold much promise for predicting invasions of migrant insect pests, disease vectors, and beneficial species.

Behavior underpins the predictive power of a trait-based model of butterfly movement.

Dispersal ability is key to species persistence in times of environmental change. Assessing a species' vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or an index of mobility derived from expert opinion, or a mechanistic modeling approach that extrapolates displacement rates from empirical data on short-term movements.Here, we compare and evaluate the success of the correlative and mechanistic approaches using a mechanistic random-walk model of butterfly movement that incorporates relationships between wingspan and sex-specific movement behaviors.The model was parameterized with new data collected on four species of butterfly in the south of England, and we observe how wingspan relates to flight speeds, turning angles, flight durations, and displacement rates.We show that flight speeds and turning angles correlate with wingspan but that to achieve good prediction of displacement even over 10 min the model must also include details of sex- and species-specific movement behaviors.We discuss what factors are likely to differentially motivate the sexes and how these could be included in mechanistic models of dispersal to improve their use in ecological forecasting.

The importance of including habitat-specific behaviour in models of butterfly movement.

Dispersal is a key process affecting population persistence and major factors affecting dispersal rates are the amounts, connectedness and properties of habitats in landscapes. We present new data on the butterfly Maniola jurtina in flower-rich and flower-poor habitats that demonstrates how movement and behaviour differ between sexes and habitat types, and how this effects consequent dispersal rates. Females had higher flight speeds than males, but their total time in flight was four times less. The effect of habitat type was strong for both sexes, flight speeds were ~ 2.5 × and ~ 1.7 × faster on resource-poor habitats for males and females, respectively, and flights were approximately 50% longer. With few exceptions females oviposited in the mown grass habitat, likely because growing grass offers better food for emerging caterpillars, but they foraged in the resource-rich habitat. It seems that females faced a trade-off between ovipositing without foraging in the mown grass or foraging without ovipositing where flowers were abundant. We show that taking account of habitat-dependent differences in activity, here categorised as flight or non-flight, is crucial to obtaining good fits of an individual-based model to observed movement. An important implication of this finding is that incorporating habitat-specific activity budgets is likely necessary for predicting longer-term dispersal in heterogeneous habitats, as habitat-specific behaviour substantially influences the mean (> 30% difference) and kurtosis (1.4 × difference) of dispersal kernels. The presented IBMs provide a simple method to explicitly incorporate known activity and movement rates when predicting dispersal in changing and heterogeneous landscapes.

Phenological responses in a sycamore-aphid-parasitoid system and consequences for aphid population dynamics: A 20 year case study.

Species interactions have a spatiotemporal component driven by environmental cues, which if altered by climate change can drive shifts in community dynamics. There is insufficient understanding of the precise time windows during which inter-annual variation in weather drives phenological shifts and the consequences for mismatches between interacting species and resultant population dynamics-particularly for insects. We use a 20 year study on a tri-trophic system: sycamore Acer pseudoplatanus, two associated aphid species Drepanosiphum platanoidis and Periphyllus testudinaceus and their hymenopteran parasitoids. Using a sliding window approach, we assess climatic drivers of phenology in all three trophic levels. We quantify the magnitude of resultant trophic mismatches between aphids and their plant hosts and parasitoids, and then model the impacts of these mismatches, direct weather effects and density dependence on local-scale aphid population dynamics. Warmer temperatures in mid-March to late-April were associated with advanced sycamore budburst, parasitoid attack and (marginally) D. platanoidis emergence. The precise time window during which spring weather advances phenology varies considerably across each species. Crucially, warmer temperatures in late winter delayed the emergence of both aphid species. Seasonal variation in warming rates thus generates marked shifts in the relative timing of spring events across trophic levels and mismatches in the phenology of interacting species. Despite this, we found no evidence that aphid population growth rates were adversely impacted by the magnitude of mismatch with their host plants or parasitoids, or direct impacts of temperature and precipitation. Strong density dependence effects occurred in both aphid species and probably buffered populations, through density-dependent compensation, from adverse impacts of the marked inter-annual climatic variation that occurred during the study period. These findings explain the resilience of aphid populations to climate change and uncover a key mechanism, warmer winter temperatures delaying insect phenology, by which climate change drives asynchronous shifts between interacting species.

Predicting resilience of ecosystem functioning from co-varying species' responses to environmental change.

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 the responses of ecosystem functions to environmental change. Quantifying co-varying species' responses to multivariate environmental change should enable us to significantly advance our predictions of ecosystem function resilience and enable proactive ecosystem management.

Data on the movement behaviour of four species of grassland butterfly.

This Data in Brief article describes data on the movement behaviour of four species of grassland butterflies collected over three years and at four sites in southern England. The datasets consist of the movement tracks of Maniola jurtina, Aricia agestis, Pyronia tithonus, and Melanargia galathea, recorded using standard methods and presented as steps distances and turning angles. Sites consisted of nectar-rich field margins, meadows, and mown short turf grasslands with minimal flowers. In total, 783 unique movement tracks were collected. The data were used for analysing the movement behaviour of the species and for parameterising individual-based movement models.

Habitat availability explains variation in climate-driven range shifts across multiple taxonomic groups.

Range shifting is vital for species persistence, but there is little consensus on why individual species vary so greatly in the rates at which their ranges have shifted in response to recent climate warming. Here, using 40 years of distribution data for 291 species from 13 invertebrate taxa in Britain, we show that interactions between habitat availability and exposure to climate change at the range margins explain up to half of the variation in rates of range shift. Habitat generalists expanded faster than more specialised species, but this intrinsic trait explains less of the variation in range shifts than habitat availability, which additionally depends on extrinsic factors that may be rare or widespread at the range margin. Similarly, while climate change likely underlies polewards expansions, we find that more of the between-species variation is explained by differences in habitat availability than by changes in climatic suitability. A model that includes both habitat and climate, and their statistical interaction, explains the most variation in range shifts. We conclude that climate-change vulnerability assessments should focus as much on future habitat availability as on climate sensitivity and exposure, with the expectation that habitat restoration and protection will substantially improve species' abilities to respond to uncertain future climates.

Integrating the influence of weather into mechanistic models of butterfly movement.

BACKGROUND: Understanding the factors influencing movement is essential to forecasting species persistence in a changing environment. Movement is often studied using mechanistic models, extrapolating short-term observations of individuals to longer-term predictions, but the role of weather variables such as air temperature and solar radiation, key determinants of ectotherm activity, are generally neglected. We aim to show how the effects of weather can be incorporated into individual-based models of butterfly movement thus allowing analysis of their effects. METHODS: We constructed a mechanistic movement model and calibrated it with high precision movement data on a widely studied species of butterfly, the meadow brown (Maniola jurtina), collected over a 21-week period at four sites in southern England. Day time temperatures during the study ranged from 14.5 to 31.5 °C and solar radiation from heavy cloud to bright sunshine. The effects of weather are integrated into the individual-based model through weather-dependent scaling of parametric distributions representing key behaviours: the durations of flight and periods of inactivity. RESULTS: Flight speed was unaffected by weather, time between successive flights increased as solar radiation decreased, and flight duration showed a unimodal response to air temperature that peaked between approximately 23 °C and 26 °C. After validation, the model demonstrated that weather alone can produce a more than two-fold difference in predicted weekly displacement. CONCLUSIONS: Individual Based models provide a useful framework for integrating the effect of weather into movement models. By including weather effects we are able to explain a two-fold difference in movement rate of M. jurtina consistent with inter-annual variation in dispersal measured in population studies. Climate change for the studied populations is expected to decrease activity and dispersal rates since these butterflies already operate close to their thermal optimum.

Potential landscape-scale pollinator networks across Great Britain: structure, stability and influence of agricultural land cover.

Understanding spatial variation in the structure and stability of plant-pollinator networks, and their relationship with anthropogenic drivers, is key for maintaining pollination services and mitigating declines. Constructing sufficient networks to examine patterns over large spatial scales remains challenging. Using biological records (citizen science), we constructed potential plant-pollinator networks at 10 km resolution across Great Britain, comprising all potential interactions inferred from recorded floral visitation and species co-occurrence. We calculated network metrics (species richness, connectance, pollinator and plant generality) and adapted existing methods to assess robustness to sequences of simulated plant extinctions across multiple networks. We found positive relationships between agricultural land cover and both pollinator generality and robustness to extinctions under several extinction scenarios. Increased robustness was attributable to changes in plant community composition (fewer extinction-prone species) and network structure (increased pollinator generality). Thus, traits enabling persistence in highly agricultural landscapes can confer robustness to potential future perturbations on plant-pollinator networks.

The importance of landscape characteristics for the delivery of cultural ecosystem services.

The importance of Cultural Ecosystem Services (CES) to human wellbeing is widely recognised. However, quantifying these non-material benefits is challenging and consequently they are often not assessed. Mapping approaches are increasingly being used to understand the spatial distribution of different CES and how this relates to landscape characteristics. This study uses an online Public Participation Geographic Information System (PPGIS) to elicit information on outdoor locations important to respondents in Wiltshire, a dynamic lowland landscape in southern England. We analysed these locations in a GIS with spatial datasets representing potential influential factors, including protected areas, land use, landform, and accessibility. We assess these characteristics at different spatial and visual scales for different types of cultural engagement. We find that areas that are accessible, near to urban centres, with larger views, and a high diversity of protected habitats, are important for the delivery of CES. Other characteristics including a larger area of woodland and the presence of sites of historic interest in the surrounding landscape were also influential. These findings have implications for land-use planning and the management of ecosystems, by demonstrating the benefits of high quality ecological sites near to towns. The importance of maintaining and restoring landscape features, such as woodlands, to enhance the delivery of CES were also highlighted.

National scale evaluation of the InVEST nutrient retention model in the United Kingdom.

A wide variety of tools aim to support decision making by modelling, mapping and quantifying ecosystem services. If decisions are to be properly informed, the accuracy and potential limitations of these tools must be well understood. However, dedicated studies evaluating ecosystem service models against empirical data are rare, especially over large areas. In this paper, we report on the national-scale assessment of a new ecosystem service model for nutrient delivery and retention, the InVEST Nutrient Delivery Ratio model. For 36 river catchments across the UK, we modelled total catchment export of phosphorus (P) and/or nitrogen (N) and compared model outputs to measurements derived from empirical water chemistry data. The model performed well in terms of relative magnitude of nutrient export among catchments (best Spearman's rank correlation for N and P, respectively: 0.81 and 0.88). However, there was wide variation among catchments in the accuracy of the model, and absolute values of nutrient exports frequently showed high percentage differences between modelled and empirically-derived exports (best median absolute percentage difference for N and P, respectively: ±64%, ±44%). The model also showed a high degree of sensitivity to nutrient loads and hydrologic routing input parameters and these sensitivities varied among catchments. These results suggest that the InVEST model can provide valuable information on nutrient fluxes to decision makers, especially in terms of relative differences among catchments. However, caution is needed if using the absolute modelled values for decision-making. Our study also suggests particular attention should be paid to researching input nutrient loadings and retentions, and the selection of appropriate input data resolutions and threshold flow accumulation values. Our results also highlight how availability of empirical data can improve model calibration and performance assessment and reinforce the need to include such data in ecosystem service modelling studies.

A national-scale model of linear features improves predictions of farmland biodiversity.

Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications. This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.