Incorporating biotic interactions in the distribution models of African wild silk moths (Gonometa species,Lasiocampidae) using different representations of modelled host tree distributions

Biotic interactions influence species niches and may thus shape distributions. Nevertheless, species distribution modelling has traditionally relied exclusively on environmental factors to predict species distributions, while biotic interactions have only seldom been incorporated into models. This study tested the ability of incorporating biotic interactions, in the form of host plant distributions, to increase model performance for two host‐dependent lepidopterans of economic interest, namely the African silk moth species, Gonometa postica and Gonometa rufobrunnea (Lasiocampidae). Both species are dependent on a small number of host tree species for the completion of their life cycle. We thus expected the host plant distribution to be an important predictor of Gonometa distributions. Model performance of a species distribution model trained only on abiotic predictors was compared to four species distribution models that additionally incorporated biotic interactions in the form of four different representations of host plant distributions as predictors. We found that incorporating the moth–host plant interactions improved G. rufobrunnea model performance for all representations of host plant distribution, while for G. postica model performance only improved for one representation of host plant distribution. The best performing representation of host plant distribution differed for the two Gonometa species. While these results suggest that incorporating biotic interactions into species distribution models can improve model performance, there is inconsistency in which representation of the host tree distribution best improves predictions. Therefore, the ability of biotic interactions to improve species distribution models may be context‐specific, even for species which have obligatory interactions with other organisms.     

Biotic predictors with phenological information improve range estimates for migrating monarch butterflies in Mexico

Although long-standing theory suggests that biotic variables are only relevant at local scales for explaining the patterns of species' distributions, recent studies have demonstrated improvements to species distribution models (SDMs) by incorporating predictor variables informed by biotic interactions. However, some key methodological questions remain, such as which kinds of interactions are permitted to include in these models, how to incorporate the effects of multiple interacting species, and how to account for interactions that may have a temporal dependence. We addressed these questions in an effort to model the distribution of the monarch butterfly Danaus plexippus during its fall migration (September–November) through Mexico, a region with new monitoring data and uncertain range limits even for this well-studied insect. We estimated species richness of selected nectar plants (Asclepias spp.) and roosting trees (various highland species) for use as biotic variables in our models. To account for flowering phenology, we additionally estimated nectar plant richness of flowering species per month. We evaluated three types of models: climatic variables only (abiotic), plant richness estimates only (biotic) and combined (abiotic and biotic). We selected models with AICc and additionally determined if they performed better than random on spatially withheld data. We found that the combined models accounting for phenology performed best for all three months, and better than random for discriminatory ability but not omission rate. These combined models also produced the most ecologically realistic spatial patterns, but the modeled response for nectar plant richness matched ecological predictions for November only. These results represent the first model-based monarch distributional estimates for the Mexican migration route and should provide foundations for future conservation work. More generally, the study demonstrates the potential benefits of using SDM-derived richness estimates and phenological information for biotic factors affecting species distributions.     

Local‐scale biotic interactions embedded in macroscale climate drivers suggest Eltonian noise hypothesis distribution patterns for an invasive grass

A hierarchical view of niche relations reconciles the scale‐dependent effects of abiotic and biotic processes on species distribution patterns and underlies most current approaches to distribution modeling. A key prediction of this framework is that the effects of biotic interactions will be averaged out at macroscales – an idea termed the Eltonian noise hypothesis (ENH). We test this prediction by quantifying regional variation in local abiotic and biotic niche relations and assess the role of macroclimate in structuring biotic interactions, using a non‐native invasive grass, Microstegium vimineum, in its introduced range. Consistent with hierarchical niche relations and the ENH, macroclimate structures local biotic interactions, while local abiotic relations are regionally conserved. Biotic interactions suppress M. vimineum in drier climates but have little effect in wetter climates. A similar approach could be used to identify the macroclimatic conditions under which biotic interactions affect the accuracy of local predictions of species distributions.     

Host plant availability potentially limits butterfly distributions under cold environmental conditions

Species ranges are shaped by both climatic factors and interactions with other species. The stress gradient hypothesis predicts that under physiologically stressful environmental conditions abiotic factors shape range edges while in less stressful environments negative biotic interactions are more important. Butterflies provide a suitable system to test this hypothesis since larvae of most species depend on biotic interactions with a specific set of host plants, which in turn can shape patterns of occurrence and distribution. Here we modelled the distribution of 92 butterfly and 136 host plant species with three different modelling algorithms, using distribution data from the Swiss biodiversity monitoring scheme at a 1 × 1 km spatial resolution. By comparing the ensemble prediction for each butterfly species and the corresponding host plant(s), we assessed potential constraints imposed by host plant availability on distribution of butterflies at their distributional limits along the main environmental gradient, which closely parallels an elevational gradient. Our results indicate that host limitation does not play a role at the lower limit. At the upper limit 50% of butterfly species have a higher elevational limit than their primary host plant, and 33% have upper elevational limits that exceed the limits of both primary and secondary hosts. We conclude that host plant limitation was not relevant to butterfly distributional limits in less stressful environments and that distributions are more likely limited by climate, land use or antagonistic biotic interactions. Obligatory dependency of butterflies on their host plants, however, seems to represent an important limiting factor for the distribution of some species towards the cold, upper end of the environmental gradient, suggesting that biotic factors can shape ranges in stressful environments. Thus, predictions by the stress gradient hypothesis were not always applicable.     

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km² to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.     

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub‐disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species’ presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.     

Improving species distribution models using biotic interactions: a case study of parasites,pollinators and plants

Biotic interactions have been considered as an important factor to be included in species distribution modelling, but little is known about how different types of interaction or different strategies for modelling affect model performance. This study compares different methods for including interspecific interactions in distribution models for bees, their brood parasites, and the plants they pollinate. Host–parasite interactions among bumble bees (genus Bombus: generalist pollinators and brood parasites) and specialist plant–pollinator interactions between Centris bees and Krameria flowers were used as case studies. We used 7 different modelling algorithms available in the BIOMOD R package. For Bombus, the inclusion of interacting species distributions generally increased model predictive accuracy. The improvement was better when the interacting species was included with its raw distribution rather than with its modeled suitability. However, incorporating the distributions of non‐interacting species sometimes resulted in similarly increased model accuracy despite their being no significance of any interaction for the distribution. For the Centris‐Krameria system the best strategy for modelling biotic interactions was to include the interacting species model‐predicted values. However, the results were less consistent than those for Bombus species, and most models including biotic interactions showed no significant improvement over abiotic models. Our results are consistent with previous studies showing that biotic interactions can be important in structuring species distributions at regional scales. However, correlations between species distributions are not necessarily indicative of interactions. Therefore, choosing the correct biotic information, based on biological and ecological knowledge, is critical to improve the accuracy of species distribution models and forecast distribution change.     

Inclusion of trophic interactions increases the vulnerability of an alpine butterfly species to climate change

Climate change is expected to have significant and complex impacts on ecological communities. In addition to direct effects of climate on species, there can also be indirect effects through an intermediary species, such as in host–plant interactions. Indirect effects are expected to be more pronounced in alpine environments because these ecosystems are sensitive to temperature changes and there are limited areas for migration of both species (i.e. closed systems), and because of simpler trophic interactions. We tested the hypothesis that climate change will reduce the range of an alpine butterfly (Parnassius smintheus) because of indirect effects through its host plant (Sedum sp.). To test for direct and indirect effects, we used the simulations of climate change to assess the distribution of P. smintheus with and without Sedum sp. We also compared the projected ranges of P. smintheus to four other butterfly species that are found in the alpine, but that are generalists feeding on many plant genera. We found that P. smintheus gained distributional area in climate‐only models, but these gains were significantly reduced with the inclusion of Sedum sp. and in dry‐climate scenarios which resulted in a reduction in net area. When compared to the more generalist butterfly species, P. smintheus exhibited the largest loss in suitable habitat. Our findings support the importance of including indirect effects in modelling species distributions in response to climate change. We highlight the potentially large and still neglected impacts climate change can have on the trophic structure of communities, which can lead to significant losses of biodiversity. In the future, communities will continue to favour species that are generalists as climate change induces asynchronies in the migration of species.     

The role of abiotic and biotic factors in determining coexistence of multiple pollinators in the yucca–yucca moth mutualism

The determinants of a species' geographic distribution are a combination of both abiotic and biotic factors. Environmental niche modeling of climatic factors has been instrumental in documenting the role of abiotic factors in a species' niche. Integrating this approach with data from species interactions provides a means to assess the relative roles of abiotic and biotic components. Here, we examine whether the high host specificity typically exhibited in the active pollination mutualism between yuccas and yucca moths is the result of differences in climatic niche requirements that limit yucca moth distributions or the result of competition among mutualistic moths that would co‐occur on the same yucca species. We compared the species distribution models of two Tegeticula pollinator moths that use the geographically widespread plant Yucca filamentosa. Tegeticula yuccasella occurs throughout eastern North America whereas T. cassandra is restricted to the southeastern portion of the range, primarily occurring in Florida. Species distribution models demonstrate that T. cassandra is restricted climatically to the southeastern United States and T. yuccasella is predicted to be able to live across all of eastern North America. Data on moth abundances in Florida demonstrate that both moth species are present on Y. filamentosa; however, T. cassandra is numerically dominant. Taken together, the results suggest that moth geographic distributions are heavily influenced by climate, but competition among pollinating congeners will act to restrict populations of moth species that co‐occur.     

Condition-specific competition governs the geographic distribution and diversity of ectoparasites

Understanding how environmental parameters interact to govern species distributions is a shared goal of ecology and biogeography. Biotic and abiotic conditions can change distributions by affecting the nature of interspecific interactions. Although documented in free-living systems, this context dependency has been neglected in parasite interactions. We investigated the influence of condition-specific competition on the specificity of two species of feather lice (Phthiraptera: Ischnocera) that share a host, the mourning dove (Zenaida macroura). We show that relative humidity restricts the range of one species, Columbicola macrourae3 (i.e., the C. macrourae lineage found on mourning doves), to the more humid eastern United States. The second species, Columbicola baculoides, an arid-adapted species, is restricted to drier regions of the western United States by C. macrourae3, which outcompetes it in experiments. Thus, arid conditions in the West provide C. baculoides with a climatic refuge from the competitively superior C. macrourae3, effectively doubling parasite diversity on one host species. These results support the hypothesis that abiotic factors can determine species distributions on the stressful end of an environmental gradient while interspecific competition governs distributions at the benign end. The balance between these factors is subject to change as environmental conditions change, even if the host distribution remains unaffected.     

Incorporating biotic factors in species distribution modeling: are interactions with soil microbes important?

It is increasingly recognized that species distributions are driven by both abiotic factors and biotic interactions. Despite much recent work incorporating competition, predation, and mutualism into species distribution models (SDMs), the focus has been confined to aboveground macroscopic interactions. Biotic interactions between plants and soil microbial communities are understudied as potentially important drivers of plant distributions. Some soil bacteria promote plant growth by cycling nutrients, while others are pathogenic; thus they have a high potential for influencing plant occurrence. We investigated the influence of soil bacterial clades on the distributions of bryophytes and 12 vascular plant species in a high elevation talus‐field ecosystem in the Rocky Mountain Front Range, Colorado, USA. We used an information‐theoretic criterion (AICc) modeling approach to compare SDMs with the following different sets of predictors: abiotic variables, abiotic variables and other plant abundances, abiotic variables and soil bacteria clade relative abundances, and a full model with abiotic factors, plant abundances, and bacteria relative abundances. We predicted that bacteria would influence plant distributions both positively and negatively, and that these interactions would improve prediction of plant species distributions. We found that inclusion of either plant or bacteria biotic predictors generally improved the fit, deviance explained, and predictive power of the SDMs, and for the majority of the species, adding information on both other plants and bacteria yielded the best model. Interactions between the modeled species and biotic predictors were both positive and negative, suggesting the presence of competition, parasitism, and facilitation. While our results indicate that plant–plant co‐occurrences are a stronger driver of plant distributions than plant–bacteria co‐occurrences, they also show that bacteria can explain parts of plant distributions that remain unexplained by abiotic and plant predictors. Our results provide further support for including biotic factors in SDMs, and suggest that belowground factors be considered as well.     

Mutualist‐mediated effects on species' range limits across large geographic scales

Understanding the processes determining species range limits is central to predicting species distributions under climate change. Projected future ranges are extrapolated from distribution models based on climate layers, and few models incorporate the effects of biotic interactions on species' distributions. Here, we show that a positive species interaction ameliorates abiotic stress, and has a profound effect on a species' range limits. Combining field surveys of 92 populations, 10 common garden experiments throughout the range, species distribution models and greenhouse experiments, we show that mutualistic fungal endophytes ameliorate drought stress and broaden the geographic range of their native grass host Bromus laevipes by thousands of square kilometres (~ 20% larger) into drier habitats. Range differentiation between fungal‐associated and fungal‐free grasses was comparable to species‐level range divergence of congeners, indicating large impacts on range limits. Positive biotic interactions may be underappreciated in determining species' ranges and species' responses to future climates across large geographic scales.     

Host plant distributions and climate interact to affect the predicted geographic distribution of a Neotropical termite

Species distribution models (SDMs) have been widely used in the scientific literature. The majority of SDMs use climate data or other abiotic variables to forecast the potential distribution of a species in geographic space. Biotic interactions can affect the predicted spatial distribution of a species in many ways across multiple spatial scales, and incorporating these predictors in an SDM is a current topic in the scientific literature. Constrictotermes cyphergaster is a widely distributed termite in the Neotropics. This termite species nests in plants and more frequently nests in some arboreal species. Thus, this species is an excellent model to evaluate the influence of biotic interactions in SDMs. We evaluate the influences of climate and the geographic distribution of host plants on the potential distribution of C. cyphergaster. Three correlative models (MaxEnt) were built to predict the geographic distribution of the termite: (1) climate data, (2) biotic data (i.e., the geographic distribution of host plants), and (3) climate and biotic data. The models that were generated indicate that the potential geographic distribution of C. cyphergaster is concentrated in the Cerrado and Caatinga regions. In addition, path analysis and multiple regression revealed the importance of the direct effects of biological interactions in the geographic distribution of the termite, while climate affected the distribution of the termite mainly through indirect effects by influencing the geographic distributions of host plants. The current study endorses the importance of including biological interactions in SDMs. We recommend using biotic predictors in SDM studies of insect species, mainly because insects have important environmental services and biotic interaction data can improve the macroecological studies of this group.     

Physiology in ecological niche modeling: using zebra mussel's upper thermal tolerance to refine model predictions through Bayesian analysis

Climate change and human-mediated dispersal are increasingly influencing species’ geographic distributions. Ecological niche models (ENMs) are widely used in forecasting species’ distributions, but are weak in extrapolation to novel environments because they rely on available distributional data and do not incorporate mechanistic information, such as species’ physiological response to abiotic conditions. To improve accuracy of ENMs, we incorporated physiological knowledge through Bayesian analysis. In a case study of the zebra mussel Dreissena polymorpha, we used native and global occurrences to obtain native and global models representing narrower and broader understanding of zebra mussel’ response to temperature. We also obtained thermal limit and survival information for zebra mussel from peer-reviewed literature and used the two types of information separately and jointly to calibrate native models. We showed that, compared to global models, native models predicted lower relative probability of presence along zebra mussel's upper thermal limit, suggesting the shortcoming of native models in predicting zebra mussel's response to warm temperature. We also found that native models showed improved prediction of relative probability of presence when thermal limit was used alone, and best approximated global models when both thermal limit and survival data were used. Our result suggests that integration of physiological knowledge enhances extrapolation of ENM in novel environments. Our modeling framework can be generalized for other species or other physiological limits and may incorporate evolutionary information (e.g. evolved thermal tolerance), thus has the potential to improve predictions of species’ invasive potential and distributional response to climate change.     

Tracing the origin of disjunct distributions: a case of biogeographical convergence in Pyrgus butterflies

Aim To study the biogeographical factors responsible for the current disjunct distributions of two closely related species of butterflies (Pyrgus cinarae and Pyrgus sidae, Lepidoptera: Hesperioidea). Both species have small populations in the Iberian Peninsula that are isolated by more than 1000 km from their nearest conspecifics. Because these species possess similar ecological preferences and geographical distributions, they are excellent candidates for congruent biogeographical histories. Location The Palaearctic region, with a special focus on the Mediterranean peninsulas as glacial refugia. Methods We integrated phylogeography and population genetic analyses with ecological niche modelling. The mitochondrial gene cytochrome c oxidase subunit 1 (COI) and the non‐coding nuclear marker internal transcribed spacer 2 (ITS2) were analysed for 62 specimens of P. cinarae and for 80 of P. sidae to infer phylogeography and to date the origin of disjunct distributions. Current and ancestral [Last Glacial Maximum using MIROC (Model for Interdisciplinary Research on Climate) and CCSM (Community Climate System Model) circulation models] distribution models were calculated with Maxent . Using present climatic conditions, we delimited the ecological space for each species. Results The genetic structure and potential ancestral distribution of the two species were markedly different. While the Iberian population of P. cinarae had an old origin (c. 1 Ma), that of P. sidae was closely related to French and Italian lineages (which jointly diverged from eastern populations c. 0.27 Ma). Ecological niche modelling showed that minor differences in the ecological preferences of the two species seem to account for their drastically different distributional response to the last glacial to post‐glacial environmental conditions. Although the potential distribution of P. cinarae was largely unaffected by climate change, suitable habitat for P. sidae strongly shifted in both elevation and latitude. This result might explain the early origin of the disjunct distribution of P. cinarae, in contrast to the more recent disjunction of P. sidae. Main conclusions We show that convergent biogeographical patterns can be analysed with a combination of genetic and ecological niche modelling data. The results demonstrate that species with similar distributional patterns and ecology may still have different biogeographical histories, highlighting the importance of including the temporal dimension when studying biogeographical patterns.     

Ecological interactions among insect herbivores,ants and the host plant Baccharis dracunculifolia in a Brazilian mountain ecosystem

Insect–plant interactions occur in several ways and have considerable environmental and ecological importance. Many feeding strategies have evolved among herbivorous insects, with host–herbivore systems likely being influenced by trophobionts with ants. We investigated how these interactions vary across elevation gradients by evaluating the structure of the herbivorous insect community and ants associated with Baccharis dracunculifolia at three distinct elevations (800, 1100, and 1400 m a.s.l.) on a mountain in southeastern Brazil. Moreover, we evaluated the diversity and specialisation of interactions between herbivores and host plants along the elevational gradient. We sampled herbivores and ants on 60 plants at each elevation (totalling 180 plant individuals). Herbivore species composition differed among elevations, as did interaction diversity and specialisation. Richness and abundance of chewing insects increased with elevation, while β‐diversity among patches of the host plant was higher at the lowest elevation, probably due to the patchy occurrence of B. dracunculifolia. Richness and abundance of sap‐sucking insects were higher at the intermediate elevation, possibly due to local environmental conditions. We observed a positive relationship between ant and herbivore trophobiont richness on B. dracunculifolia. We found that interactions were more specialised and less diverse at higher elevations compared to the lowest elevation. Changes in vegetation and environmental variables shaped species distributions and their ecological interactions along the elevation gradient. Our study demonstrates that increased elevation changes the structure and patterns of interactions of the herbivore insect guilds associated with the host plant B. dracunculifolia. Ant effects depend on the context, the environment, and the species of ants involved, and are essential for the presence of insect trophobionts.     

Modeled global invasive potential of Asian gypsy moths, Lymantria dispar

Asian populations of gypsy moths, Lymantria dispar (L.) (Lepidoptera: Lymantriidae), remain poorly characterized – indeed, they are not presently accorded any formal taxonomic status within the broader species. Their ecology is similarly largely uncharacterized in the literature, except by assumption that it will resemble that of European populations. We developed ecological niche models specific to Asian populations of the species, which can in turn be used to identify a potential geographic distributional area for the species. We demonstrated statistically significant predictivity of distributional patterns within the East Asian range of these populations; projecting the Asian ecological niche model to Europe, correspondence with European distributions was generally good, although some differences may exist; projecting the ecological niche model globally, we characterized a likely potential invasive distribution of this set of populations across the temperate zone of both Northern and Southern Hemisphere.     

Biotic interactions boost spatial models of species richness

Biotic interactions are known to affect the composition of species assemblages via several mechanisms, such as competition and facilitation. However, most spatial models of species richness do not explicitly consider inter‐specific interactions. Here, we test whether incorporating biotic interactions into high‐resolution models alters predictions of species richness as hypothesised. We included key biotic variables (cover of three dominant arctic‐alpine plant species) into two methodologically divergent species richness modelling frameworks – stacked species distribution models (SSDM) and macroecological models (MEM) – for three ecologically and evolutionary distinct taxonomic groups (vascular plants, bryophytes and lichens). Predictions from models including biotic interactions were compared to the predictions of models based on climatic and abiotic data only. Including plant–plant interactions consistently and significantly lowered bias in species richness predictions and increased predictive power for independent evaluation data when compared to the conventional climatic and abiotic data based models. Improvements in predictions were constant irrespective of the modelling framework or taxonomic group used. The global biodiversity crisis necessitates accurate predictions of how changes in biotic and abiotic conditions will potentially affect species richness patterns. Here, we demonstrate that models of the spatial distribution of species richness can be improved by incorporating biotic interactions, and thus that these key predictor factors must be accounted for in biodiversity forecasts.     

Water availability alters the tri-trophic consequences of a plant-fungal symbiosis

Plant–microbe protection symbioses occur when a symbiont defends its host against enemies (e.g., insect herbivores); these interactions can have important influences on arthropod abundance and composition. Understanding factors that generate context-dependency in protection symbioses will improve predictions on when and where symbionts are most likely to affect the ecology and evolution of host species and their associated communities. Of particular relevance are changes in abiotic contexts that are projected to accompany global warming. For example, increased drought stress can enhance the benefits of fungal symbiosis in plants, which may have multi-trophic consequences for plant-associated arthropods. Here, we tracked colonization of fungal endophyte-symbiotic and aposymbiotic Poa autumnalis (autumn bluegrass) by Rhopalosiphum padi (bird-cherry-oat aphids) and their parasitoids (Aphelinus sp.) following manipulations of soil water levels. Endophyte symbiosis significantly reduced plant colonization by aphids. Under low water, symbiotic plants also supported a significantly higher proportion of aphids that were parasitized by Aphelinus and had higher above-ground biomass than aposymbiotic plants, but these endophyte-mediated effects disappeared under high water. Thus, the multi-trophic consequences of plant-endophyte symbiosis were contingent on the abiotic context, suggesting the potential for complex responses in the arthropod community under future climate shifts.     

A winner in the Anthropocene: changing host plant distribution explains geographical range expansion in the gulf fritillary butterfly

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.