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Insects have diversified through more than 450 million y of Earth's changeable climate, yet rapidly shifting patterns of temperature and precipitation now pose novel challenges as they combine with decades of other anthropogenic stressors including the conversion and degradation of land. Here, we consider how insects are responding to recent climate change while summarizing the literature on long-term monitoring of insect populations in the context of climatic fluctuations. Results to date suggest that climate change impacts on insects have the potential to be considerable, even when compared with changes in land use. The importance of climate is illustrated with a case study from the butterflies of Northern California, where we find that population declines have been severe in high-elevation areas removed from the most immediate effects of habitat loss. These results shed light on the complexity of montane-adapted insects responding to changing abiotic conditions. We also consider methodological issues that would improve syntheses of results across long-term insect datasets and highlight directions for future empirical work.

1. The changing climate is altering species distributions with consequences for population dynamics, resulting in winners and losers in the Anthropocene. 2. Agraulis vanillae, the gulf fritillary butterfly, has expanded its range in the past 100 years in the western U.S.A. Time series analysis is combined with species distribution modelling to investigate factors limiting the distribution of A. vanillae and to predict future shifts under warming scenarios. 3. Time series analyses from the western U.S.A. show that urban development has a positive association with year of colonisation (the host plant Passiflora is an ornamental in gardens). Colonisation was also associated positively and to a lesser extent with winter maximum temperatures, whereas a negative impact of minimum temperatures and precipitation was apparent on population growth rates after establishment. 4. Species distribution models vary by region. In the eastern U.S.A., the butterfly is primarily limited by minimum temperatures in the winter and host availability later in the season. Eastern U.S. projected expansion broadly follows the expectation of poleward distributional shifts, especially for the butterfly's maximum annual extent. Western U.S. distributions are limited by the host plant, which in turn is dependent on urban centres. Projected western U.S. expansion is not limited to a single direction and is driven by urban centres becoming more suitable for the host plant. 5. These results demonstrate the value of combining time series with spatial modelling, at the same time as incorporating biotic interactions, aiming to understand and predict shifting geographical ranges in the Anthropocene.

Certain general facets of biotic response to climate change, such as shifts in phenology and geographic distribution, are well characterized; however, it is not clear whether the observed similarity of responses across taxa will extend to variation in other population-level processes. We examined population response to climatic variation using long-term incidence data (collected over 42 years) encompassing 149 butterfly species and considerable habitat diversity (10 sites along an elevational gradient from sea level to over 2,700 m in California). Population responses were characterized by extreme heterogeneity that was not attributable to differences in species composition among sites. These results indicate that habitat heterogeneity might be a buffer against climate change and highlight important questions about mechanisms maintaining interpopulation differences in responses to weather. Despite overall heterogeneity of response, population dynamics were accurately predicted by our model for many species at each site. However, the overall correlation between observed and predicted incidence in a cross validation analysis was moderate (Pearson's r = 0.23, SE 0.01), and 97% of observed data fell within the predicted 95% credible intervals. Prediction was most successful for more abundant species as well as for sites with lower annual turnover. Population-level heterogeneity in response to climate variation and the limits of our predictive power highlight the challenges for a future of increasing climatic variability.

A long-standing challenge for population biology has been to understand why some species are characterized by populations that fluctuate in size independently, while populations of other species fluctuate synchronously across space. The effects of climatic variation and dispersal have been invoked to explain synchronous population dynamics, however an understanding of the relative influence of these drivers in natural populations is lacking. Here we compare support for dispersal- versus climate-driven models of interspecific variation in synchrony using 27 years of observations of 65 butterfly species at 10 sites spanning 2750 m of elevation in Northern California. The degree of spatial synchrony exhibited by each butterfly species was used as a response in a unique approach that allowed us to investigate whether interspecific variation in response to climate or dispersal propensity was most predictive of interspecific variation in synchrony. We report that variation in sensitivity to climate explained 50% of interspecific variation in synchrony, whereas variation in dispersal propensity explained 23%. Sensitivity to the El Niño Southern Oscillation, a primary driver of regional climate, was the best predictor of synchrony. Combining sensitivity to climate and dispersal propensity into a single model did not greatly increase model performance, confirming the primacy of climatic sensitivity for driving spatial synchrony in butterflies. Finally, we uncovered a relationship between spatial synchrony and population decline that is consistent with theory, but small in magnitude, which suggests that the degree to which populations fluctuate in synchrony is of limited use for understanding the ongoing decline of the Northern California butterfly fauna.

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness.

The butterfly fauna of lowland Northern California has exhibited a marked decline in recent years that previous studies have attributed in part to altered climatic conditions and changes in land use. Here, we ask if a shift in insecticide use towards neonicotinoids is associated with butterfly declines at four sites in the region that have been monitored for four decades. A negative association between butterfly populations and increasing neonicotinoid application is detectable while controlling for land use and other factors, and appears to be more severe for smaller-bodied species. These results suggest that neonicotinoids could influence non-target insect populations occurring in proximity to application locations, and highlights the need for mechanistic work to complement long-term observational data.

Migratory animals pose unique challenges for conservation biologists, and we have much to learn about how migratory species respond to drivers of global change. Research has cast doubt on the stability of the eastern monarch butterfly (Danaus plexippus) population in North America, but the western monarchs have not been as intensively examined. Using a Bayesian hierarchical model, sightings of western monarchs over approximately 40 years were investigated using summer flight records from ten sites along an elevational transect in Northern California. Multiple weather variables were examined, including local and regional temperature and precipitation. Population trends from the ten focal sites and a subset of western overwintering sites were compared to summer and overwintering data from the eastern migration. Records showed western overwintering grounds and western breeding grounds had negative trends over time, with declines concentrated early in the breeding season, which were potentially more severe than in the eastern population. Temporal variation in the western monarch also appears to be largely independent of (uncorrelated with) the dynamics in the east. For our focal sites, warmer temperatures had positive effects during winter and spring, and precipitation had a positive effect during spring. These climatic associations add to our understanding of biotic-abiotic interactions in a migratory butterfly, but shifting climatic conditions do not explain the overall, long-term, negative population trajectory observed in our data.

Understanding the spatial and temporal scales at which environmental variation affects populations of plants and animals is an important goal for modern population biology, especially in the context of shifting climatic conditions. The El Niño Southern Oscillation (ENSO) generates climatic extremes of interannual variation, and has been shown to have significant effects on the diversity and abundance of a variety of terrestrial taxa. However, studies that have investigated the influence of such large-scale climate phenomena have often been limited in spatial and taxonomic scope. We used 23 years (1988-2010) of a long-term butterfly monitoring data set to explore associations between variation in population abundance of 28 butterfly species and variation in ENSO-derived sea surface temperature anomalies (SSTA) across 10 sites that encompass an elevational range of 2750 m in the Sierra Nevada mountain range of California. Our analysis detected a positive, regional effect of increased SSTA on butterfly abundance (wetter and warmer years predict more butterfly observations), yet the influence of SSTA on butterfly abundances varied along the elevational gradient, and also differed greatly among the 28 species. Migratory species had the strongest relationships with ENSO-derived SSTA, suggesting that large-scale climate indices are particularly valuable for understanding biotic-abiotic relationships of the most mobile species. In general, however, the ecological effects of large-scale climatic factors are context dependent between sites and species. Our results illustrate the power of long-term data sets for revealing pervasive yet subtle climatic effects, but also caution against expectations derived from exemplar species or single locations in the study of biotic-abiotic interactions.

1. Ecologists often make predictions about community richness and diversity using climate variables that include seasonal precipitation totals and mean daily temperatures. While means and totals can be effective predictors to a certain extent, the complexities of faunal-climate relationships might be over-simplified through the use of coarse-grained variables. 2. The goal of this study was to investigate less commonly studied climate variables, including indices of intra-annual variation in the timing and intensity of precipitation events that might be used to predict butterfly richness across an elevational gradient. Data from a long-term, single-observer dataset at four sites in California were examined with Bayesian model averaging and structural equation modelling. Species-specific responses to climate were compared with community responses at each site. 3. At lower elevations, it was found that the relative importance of climate variables shifted towards temporal patterns of precipitation, including the timing of the first storm event and the annual number of precipitation events. Heterogeneity among sites was apparent in the importance of specific weather variables, and temporal trends (across years) were detected for a small number of variables. Species-specific results paralleled those obtained from analysis of species richness, thus suggesting a commonality of response to climate across site-specific assemblages. 4. Models were improved by inclusion of the Pacific Decadal Oscillation and El Niño-Southern Oscillation indices, indicating that regional variables can profitably be included in faunal-climate relationship analyses. These results emphasise the need for researchers to examine climate variables beyond the most readily summarised means and totals.

Aim: To evaluate three phylogeographical models associated with the presence of mountains (montane vicariance, sky island and parapatry) as drivers of intraspecific diversification in the sandhill skipper, Polites sabuleti (Lepidoptera: Hesperiidae), a morphologically variable species found in a variety of habitats from sea level to the alpine zone. Location: Western North America. Methods: The mitochondrial cytochrome c oxidase subunit II region was sequenced in 189 P. sabuleti individuals. Mitochondrial sequences were used in a spatial analysis of molecular variance (SAMOVA) to evaluate geographical population structure. AFLP markers were also generated for 347 individuals in order to estimate admixture proportions and examine population differentiation based on the nuclear genome. Results: Twenty-five mitochondrial haplotypes and 42 anonymous AFLP loci were found across 36 collection localities. Mitochondrial variation suggests a degree of regional population structure, although at least one of the inferred population groups extends over nearly the entire geographical range of the species. Analyses of nuclear data (AFLPs) identified five genetic clusters, including one restricted to high elevations in the Sierra Nevada. Main conclusions: The distribution of genetic variation within Polites sabuleti, a species with a broad elevational range, does not strictly support either mountain-associated vicariance or 'sky island' isolation as the dominant process. Instead, we find complex population structure, including evidence for divergence between high- and low-elevation populations in the Sierra Nevada mountains.

Climatic variation has been invoked as an explanation of population dynamics for a variety of taxa. Much work investigating the link between climatic forcings and population fluctuation uses single-taxon case studies. Here, we conduct comparative analyses of a multi-decadal dataset describing population dynamics of 50 co-occurring butterfly species at 10 sites in Northern California. Specifically, we explore the potential commonality of response to weather among species that encompass a gradient of population dynamics via a hierarchical Bayesian modelling framework. Results of this analysis demonstrate that certain weather conditions impact volatile, or irruptive, species differently as compared with relatively stable species. Notably, precipitation-related variables, including indices of the El Niño Southern Oscillation, have a more pronounced impact on the most volatile species. We hypothesize that these variables influence vegetation resource availability, and thus indirectly influence population dynamics of volatile taxa. As one of the first studies to show a common influence of weather among taxa with similar population dynamics, the results presented here suggest new lines of research in the field of biotic-abiotic interactions.

An important and largely unaddressed issue in studies of biotic-abiotic relationships is the extent to which closely related species, or species living in similar habitats, have similar responses to weather. We addressed this by applying a hierarchical, Bayesian analytical framework to a long-term data set for butterflies which allowed us to simultaneously investigate responses of the entire fauna and individual species. A small number of variables had community-level effects. In particular, higher total annual snow depth had a positive effect on butterfly occurrences, while spring minimum temperature and El Niño-Southern Oscillation (ENSO) sea-surface variables for April-May had negative standardized coefficients. Our most important finding was that variables with large impacts at the community-level did not necessarily have a consistent response across all species. Species-level responses were much more similar to each other for snow depth compared to the other variables with strong community effects. This variation in species-level responses to weather variables raises important complications for the prediction of biotic responses to shifting climatic conditions. In addition, we found that clear associations with weather can be detected when considering ecologically delimited subsets of the community. For example, resident species and non-ruderal species had a much more unified response to weather variables compared to non-resident species and ruderal species, which suggests local adaptation to climate. These results highlight the complexity of biotic-abiotic interactions and confront that complexity with methodological advances that allow ecologists to understand communities and shifting climates while simultaneously revealing species-specific variation in response to climate.

Butterfly populations are naturally patchy and undergo extinctions and recolonizations. Analyses based on more than 2 decades of data on California's Central Valley butterfly fauna show a net loss in species richness through time. We analyzed 22 years of phenological and faunistic data for butterflies to investigate patterns of species richness over time. We then used 18-22 years of data on changes in regional land use and 37 years of seasonal climate data to develop an explanatory model. The model related the effects of changes in land-use patterns, from working landscapes (farm and ranchland) to urban and suburban landscapes, and of a changing climate on butterfly species richness. Additionally, we investigated local trends in land use and climate. A decline in the area of farmland and ranchland, an increase in minimum temperatures during the summer and maximum temperatures in the fall negatively affected net species richness, whereas increased minimum temperatures in the spring and greater precipitation in the previous summer positively affected species richness. According to the model, there was a threshold between 30% and 40% working-landscape area below which further loss of working-landscape area had a proportionally greater effect on butterfly richness. Some of the isolated effects of a warming climate acted in opposition to affect butterfly richness. Three of the 4 climate variables that most affected richness showed systematic trends (spring and summer mean minimum and fall mean maximum temperatures). Higher spring minimum temperatures were associated with greater species richness, whereas higher summer temperatures in the previous year and lower rainfall were linked to lower richness. Patterns of land use contributed to declines in species richness (although the pattern was not linear), but the net effect of a changing climate on butterfly richness was more difficult to discern.

Abundance data are widely used to monitor long-term population trends for management and conservation of species of interest. Programs that collect count data are often prohibitively expensive and time intensive, limiting the number of species that can be simultaneously monitored. Presence data, on the other hand, can often be collected in less time and for multiple species simultaneously. We investigate the relationship of counts to presence using 49 butterfly species across 4 sites over 9 years, and then compare trends produced from each index. We also employed simulated datasets to test the effect of reduced sampling on the relationship of counts to presence data and to investigate changes in each index's power to reveal population trends. Presence and counts were highly correlated for most species tested, and population trends based on each index were concordant for most species. The effect of reduced sampling was species-specific, but on a whole, sensitivity of both indices to detect population trends was reduced. Common and rare species, as well as those with a range of life-history and behavioral traits performed equally well. The relationship between presence and count data may break down in cases of very abundant and widespread species with extended flight seasons. Our results suggest that when used cautiously, presence data has the potential to be used as a surrogate for counts. Collection of presence data may be useful for multi-species monitoring or to reduce the duration of monitoring visits without fully sacrificing the ability to infer population trends. © 2013 Springer Science+Business Media Dordrecht.

Pathogens play a key role in insect population dynamics, contributing to short‐term fluctuations in abundance as well as long‐term demographic trends. Two key factors that influence the effects of entomopathogens on herbivorous insect populations are modes of pathogen transmission and larval host plants. In this study, we examined tritrophic interactions between a sequestering specialist lepidopteran, Euphydryas phaeton, and a viral pathogen, Junonia coenia densovirus, on its native host plant, Chelone glabra, and a novel host plant, Plantago lanceolata, to explore whether host plant mediates viral transmission, survival, and viral loads. A two‐factor factorial experiment was conducted in the laboratory with natal larval clusters randomly assigned to either the native or novel host plant and crossed with either uninoculated controls or viral inoculation (20% of individuals in the cluster inoculated). Diapausing clusters were overwintered in the laboratory and checked weekly for mortality. At the end of diapause, all surviving individuals were reared to adulthood to estimate survivorship. All individuals were screened to quantify viral loads, and estimate horizontal transmission postmortem. To test for vertical transmission, adults were mated, and the progeny were screened for viral presence. Within virus‐treated groups, we found evidence for both horizontal and vertical transmission. Larval clusters reared on the native host plant had slightly higher horizontal transmission. Survival probability was lower in clusters feeding on the native host plant, with inoculated groups reared on the native host plant experiencing complete mortality. Viral loads did not differ by the host plant, although viral loads decreased with increased sequestration of secondary compounds on both host plants. Our results indicate that the use of a novel host plant may confer fitness benefits in terms of survival and reduced viral transmission when larvae feeding on it are infected with this pathogen, supporting hypotheses of potential evolutionary advantages of a host range expansion in the context of tritrophic interactions. [ABSTRACT FROM AUTHOR]

Identifying patterns of pathogen infection in natural systems is crucial to understanding mechanisms of host–pathogen interactions. In this study, we explored how Junonia coenia densovirus (JcDV) infection varies over space and time in populations of the Melissa blue butterfly (Lycaeides melissa: Lycaenidae) using two different host plants. Collections of L. melissa adults from multiple populations and years, along with host plant tissue and community samples of arthropods found on host plants, were screened to determine JcDV prevalence and load. Additionally, we sampled at multiple time points within a single L. melissa flight season to investigate intra‐annual variation in infection patterns.We found population‐specific variation in viral prevalence of L. melissa across collection years, with historical samples potentially having higher viral prevalence than contemporary samples, although host plant diet was not informative for these patterns. Patterns of infection across multiple generations within a flight season showed that late‐season samples had a higher proportion of JcDV‐positive individuals, suggesting an accumulation of virus over the season. Sequence data from a segment of the JcDV capsid gene showed a lack of viral genetic diversity between L. melissa collected from different localities, and little to no viral particles were found in the surrounding environment.Our discovery of temporal variation in infection suggests that multiple sampling efforts must be made when describing pathogen prevalence in multivoltine hosts. Our findings represent an important first step towards further exploration of the ecological factors mediating disease prevalence and host‐specific variability of infection in wild insect populations. [ABSTRACT FROM AUTHOR]

Insect herbivory can be an important selective pressure and contribute substantially to local plant richness. As herbivory is the result of numerous ecological and evolutionary processes, such as complex insect population dynamics and evolution of plant antiherbivore defenses, it has been difficult to predict variation in herbivory across meaningful spatial scales. In the present work, we characterize patterns of herbivory on plants in a species‐rich and abundant tropical genus (Piper) across forests spanning 44° of latitude in the Neotropics. We modeled the effects of geography, climate, resource availability, and Piper species richness on the median, dispersion, and skew of generalist and specialist herbivory. By examining these multiple components of the distribution of herbivory, we were able to determine factors that increase biologically meaningful herbivory at the upper ends of the distribution (indicated by skew and dispersion). We observed a roughly twofold increase in median herbivory in humid relative to seasonal forests, which aligns with the hypothesis that precipitation seasonality plays a critical role in shaping interaction diversity within tropical ecosystems. Site level variables such as latitude, seasonality, and maximum Piper richness explained the positive skew in herbivory at the local scale (plot level) better for assemblages of Piper congeners than for a single species. Predictors that varied between local communities, such as resource availability and diversity, best explained the distribution of herbivory within sites, dampening broad patterns across latitude and climate and demonstrating why generalizations about gradients in herbivory have been elusive. The estimated population means, dispersion, and skew of herbivory responded differently to abiotic and biotic factors, illustrating the need for careful studies to explore distributions of herbivory and their effects on forest diversity. [ABSTRACT FROM AUTHOR]

Butterflies in the family Lycaenidac are often the focus of conservation efforts. However, our understanding of lycaenid population dynamics has been limited to relatively few examples of long-term monitoring data that have been reported. Here, factors associated with population regulation are investigated using a complete record of a single population of the silvery blue, Glaucopsyche lygdamus Doubleday (Lepidoptera: Lycaenidae). Adults of G. lygdamus were first observed in an annual grassland near Davis, California, in 1982 and were last seen in 2003. Relationships between inter-annual variation in abundance and climatic variables were examined, accounting for density dependent effects. Significant effects of both negative density dependence and climatic variation were detected, particularly precipitation and temperature during winter months. Variation in precipitation, the strongest predictor of abundance, was associated directly and positively with butterfly abundance in the same year. Winter temperatures had a negative effect in the same year, but had a lagged, positive effect on abundance in the subsequent year. Mechanistic hypotheses are posed that include climatic effects mediated through both larval and adult plant resources.

Climate change and habitat destruction have been linked to global declines in vertebrate biodiversity, including mammals, amphibians, birds, and fishes. However, invertebrates make up the vast majority of global species richness, and the combined effects of climate change and land use on invertebrates remain poorly understood. Here we present 35 years of data on 159 species of butterflies from 10 sites along an elevational gradient spanning 0-2,775 m in a biodiversity hotspot, the Sierra Nevada Mountains of Northern California. Species richness has declined at half of the sites, with the most severe reductions at the lowest elevations, where habitat destruction is greatest. At higher elevations, we observed clear upward shifts in the elevational ranges of species, consistent with the influence of global warming. Taken together, these long-term data reveal the interacting negative effects of human-induced changes on both the climate and habitat available to butterfly species in California. Furthermore, the decline of ruderal, disturbance-associated species indicates that the traditional focus of conservation efforts on more specialized and less dispersive species should be broadened to include entire faunas when estimating and predicting the effects of pervasive stressors.