Butterfly abundance in a warming climate: patterns in space and time are not congruent

We present a model of butterfly abundance on transects in England. The model indicates a significant role for climate, but the direction of association is counter to expectation: butterfly population density is higher on sites with a cooler climate. However, the effect is highly heterogeneous, with one in five species displaying a net positive association. We use this model to project the population-level effects of climate warming for the year 2080, using a medium emissions scenario. The results suggest that most populations and species will decline markedly, but that the total number of butterflies will increase as communities become dominated by a few common species. In particular, Maniola jurtina is predicted to make up nearly half of all butterflies on UK Butterfly Monitoring Scheme (UKBMS) transects by 2080. These results contradict the accepted wisdom that most insect populations will grow as the climate becomes warmer. Indeed, our predictions contrast strongly with those derived from inter-annual variation in abundance, emphasizing that we lack a mechanistic understanding about the factors driving butterfly population dynamics over large spatial and temporal scales. Our study underscores the difficulty of predicting future population trends and reveals the naivety of simple space-for-time substitutions, which our projections share with species distribution modelling

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

Are neonicotinoid insecticides driving declines of widespread butterflies?

There has been widespread concern that neonicotinoid pesticides may be adversely impacting wild and managed bees for some years, but recently attention has shifted to examining broader effects they may be having on biodiversity. For example in the Netherlands, declines in insectivorous birds are positively associated with levels of neonicotinoid pollution in surface water. In England, the total abundance of widespread butterfly species declined by 58% on farmed land between 2000 and 2009 despite both a doubling in conservation spending in the UK, and predictions that climate change should benefit most species. Here we build models of the UK population indices from 1985 to 2012 for 17 widespread butterfly species that commonly occur at farmland sites. Of the factors we tested, three correlated significantly with butterfly populations. Summer temperature and the index for a species the previous year are both positively associated with butterfly indices. By contrast, the number of hectares of farmland where neonicotinoid pesticides are used is negatively associated with butterfly indices. Indices for 15 of the 17 species show negative associations with neonicotinoid usage. The declines in butterflies have largely occurred in England, where neonicotinoid usage is at its highest. In Scotland, where neonicotinoid usage is comparatively low, butterfly numbers are stable. Further research is needed urgently to show whether there is a causal link between neonicotinoid usage and the decline of widespread butterflies or whether it simply represents a proxy for other environmental factors associated with intensive agriculture

Butterfly abundance is determined by food availability and is mediated by species traits

1. Understanding the drivers of population abundance across species and sites is crucial for effective conservation management. At present, we lack a framework for predicting which sites are likely to support abundant butterfly communities. 2. We address this problem by exploring the determinants of abundance among 1111 populations of butterflies in the UK, spanning 27 species on 54 sites. Our general hypothesis is that the availability of food resources is a strong predictor of population abundance both within and between species, but that the relationship varies systematically with species’ traits. 3. We found strong positive correlations between butterfly abundance and the availability of food resources. Our indices of host plant and nectar are both significant predictors of butterfly population density, but the relationship is strongest for host plants, which explain up to 36% of the inter-site variance in abundance for some species. 4. Among species, the host plant–abundance relationship is mediated by butterfly species traits. It is strongest among those species with narrow diet breadths, low mobility and habitat specialists. Abundance for species with generalist diet and habitat associations is uncorrelated with our host plant index. 5. The host plant–abundance relationship is more pronounced on sites with predominantly north-facing slopes, suggesting a role for microclimate in mediating resource availability. 6. Synthesis and applications. We have shown that simple measures can be used to help understand patterns in abundance at large spatial scales. For some butterfly species, population carrying capacity on occupied sites is predictable from information about the vegetation composition. These results suggest that targeted management to increase host plant availability will translate into higher carrying capacity. Among UK butterflies, the species that would benefit most from such intervention have recently experienced steep declines in both abundance and distribution. The host plant–abundance relationship we have identified is likely to be transferrable to other systems characterized by strong interspecific interactions across trophic levels. This raises the possibility that the quality of habitat patches for specialist species is estimable from rapid assessment of the host plant resource

A generalised abundance index for seasonal invertebrates

At a time of climate change and major loss of biodiversity, it is important to have efficient tools for monitoring populations. In this context, animal abundance indices play an important role. In producing indices for invertebrates, it is important to account for variation in counts within seasons. Two new methods for describing seasonal variation in invertebrate counts have recently been proposed; one is nonparametric, using generalized additive models, and the other is parametric, based on stopover models. We present a novel generalized abundance index which encompasses both parametric and nonparametric approaches. It is extremely efficient to compute this index due to the use of concentrated likelihood techniques. This has particular relevance for the analysis of data from long-term extensive monitoring schemes with records for many species and sites, for which existing modeling techniques can be prohibitively time consuming. Performance of the index is demonstrated by several applications to UK Butterfly Monitoring Scheme data. We demonstrate the potential for new insights into both phenology and spatial variation in seasonal patterns from parametric modeling and the incorporation of covariate dependence, which is relevant for both monitoring and conservation. Associated R code is available on the journal website

Dynamic models for longitudinal butterfly data

There has been recent interest in devising stochastic models for seasonal insects, which respond rapidly to climate change. Fitted to count data, these models are used to construct indices of abundance, which guide conservation and management. We build upon Dennis et al. (2014, under review) to produce dynamic models, which provide succinct descriptions of data from all years simultaneously. They produce estimates of key life-history parameters such as annual productivity and survival. Analyses for univoltine species, with only one generation each year, extend to bivoltine species, with two annual broods. In the latter case we estimate the productivities of each generation separately, and also devise extended indices which indicate the contributions made from different generations. We demonstrate the performance of the models using count data for UK butterfly species, and compare with current procedures which use generalized additive models. We may incor- orate relevant covariates within the model, and illustrate using northing and measures of temperature. Consistent patterns are demonstrated for multiple species. This generates a variety of hypotheses for further investigation, which have the potential to illuminate features of butterfly phenology and demography which are at present poorly understood

Developing a national indicator of functional connectivity

Habitat loss is a significant driver of biodiversity loss, causing fragmentation into small, isolated patches of suitable land cover. This reduces the permeability of landscapes to the movement of individuals and reduces the likelihood of metapopulation persistence. Quantifying functional connectivity, the ability of a focal species to move between resource patches, is therefore essential for conservation management. There is substantial evidence supporting a technique based on ‘population synchrony’- the degree of correlation in time-series of annual population growth rates between different long-term monitoring sites, to provide a measure of functional connectivity. However, synchronised population dynamics are not only driven by the movement of individuals between sites, but also shared environmental conditions which must be accounted for. Here, we use species survey data from over four decades to investigate average levels and temporal trends in population synchrony for 58 British bird and butterfly species. We first show that population synchrony is significantly associated with synchrony in some seasonal climatic variables. Once we accounted for spatiotemporal climatic patterns, we found that synchrony in butterflies declined over time by 71% between 1985 and 2000 but increased by 64% in recent years. Synchrony in birds showed some decline between 1999 and 2005, after which there appears to being recovery, however most species (74%) show no significant overall change in synchrony. Our proposed indicator provides a ‘species-eye-view’ of functional connectivity using widely available abundance data. Developing such indicators of functional connectivity, which can be updated annually, is crucial to improve the effectiveness of land management strategies for conservation under increasing environmental change

Grizzled skippers stuck in the south: population‐level responses of an early‐successional specialist butterfly to climate across its UK range over 40 years

Aim: Climate change has been predicted to facilitate poleward expansion of many early‐successional specialist invertebrates. The Grizzled Skipper, Pyrgus malvae, is a threatened butterfly in long‐term decline that has not met expectations of northern expansion in Britain, possibly indicating that climate change has not improved northern habitat suitability or that another driver (e.g. land use change) is masking its effects. Here, we explore the effect of climate on population size trends over four decades, and whether any regions show an improving population trend that may be a precursor to northern expansion. Examining detailed spatio‐temporal abundance data can reveal unexpected limitations to population growth that would not be detectable in widely used climate envelope models. Location: Central and southern England. Methods: Mixed models were used to investigate P. malvae population size in relation to time and monthly climate measures across its UK range since 1976, based on repeated transect walks. Results: We found that P. malvae population size declined more over time in the north and west of its UK range than in the south and east, and was negatively related to high December temperature and summer rainfall. However, the effect sizes of temperature and rainfall were minimal. Main Conclusions: The last 40 years of climate change have not ameliorated climate suitability for P. malvae at its range edge, contrary to expectations from spatial‐only climate envelope models. The clear long‐term downward trends in population size are independent of climate change and we propose probably due to habitat deterioration. Our findings highlight potential hazards in predicting species range expansions from spatial models alone. Although some climate variables may be associated with a species’ distribution, other factors may be more dominant drivers of trends and therefore more useful predictors of range changes

Consistent concentrations of critically endangered Balearic shearwaters in UK waters revealed by at-sea surveys

Aim: Europe’s only globally critically endangered seabird, the Balearic shearwater (Puffinus mauretanicus), is thought to have expanded its post-breeding range northwards into UK waters, though its distribution there is not yet well understood. This study aims to identify environmental factors associated with the species’ presence, and map the probability of presence of the species across the western English Channel and southern Celtic Sea, and estimate the number of individuals in this area. Location: The western English Channel and southern Celtic Sea. Methods: This study analyses strip transect data collected from vessel-based surveys in the western English Channel and southern Celtic Sea during the shearwater’s post-breeding period between 2013 and 2017. Using environmental data collected directly and from remote sensors both Generalized Additive Models (GAMs) and the Random Forest (RF) machine learning model were used to determine shearwater presence at different locations. Results: Both models indicated that oceanographic features were better predictors of shearwater presence than fish abundance. Seafloor aspect, sea surface temperature, depth, salinity, and maximum current speed were the most important predictors. Based on the timing of the surveys (mainly in October) it is probable that most of the sighted shearwaters were immatures. Main conclusions: Areas with consistently high probabilities of shearwater presence were identified at the Celtic Sea front. Our estimates suggest that the study area in southwest Britain supports between 2% and 23% of the global population of Balearic shearwaters. This study provides the most complete understanding of Balearic shearwater distribution in UK waters available to date, information that will help inform any future UK conservation actions concerning this endangered 38 species

Trends and indicators for quantifying moth abundance and occupancy in Scotland

Moths form an important part of Scotland’s biodiversity and an up-to-date assessment of their status is needed given their value as a diverse and species-rich taxon, with various ecosystem roles, and the known decline of moths within Britain. We use long-term citizen-science data to produce species-level trends and multi-species indicators for moths in Scotland, to assess population (abundance) and distribution (occupancy) changes. Abundance trends for moths in Scotland are produced using Rothamsted Insect Survey count data, and, for the first time, occupancy models are used to estimate occupancy trends for moths in Scotland, using opportunistic records from the National Moth Recording Scheme. Species-level trends are combined to produce abundance and occupancy indicators. The associated uncertainty is estimated using a parametric bootstrap approach, and comparisons are made with alternative published approaches. Overall moth abundance (based on 176 species) in Scotland decreased by 20% for 1975-2014 and by 46% for 1990-2014. The occupancy indicator, based on 230 species, showed a 16% increase for 1990-2014. Alternative methods produced similar indicators and conclusions, suggesting robustness of the results, although rare species may be under-represented in our analyses. Species abundance and occupancy trends were not clearly correlated; in particular species with negative population trends showed varied occupancy responses. Further research into the drivers of moth population changes is required, but increasing occupancy is likely to be driven by a warming summer climate facilitating range expansion, whereas population declines may be driven by reductions in habitat quality, changes in land management practices and warmer, wetter winters