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AimThe relative importance of traits and phylogeny to predict species extinction risk is unclear and it depends on which traits are measured and their phylogenetic conservatism. Here, we evaluate the power of functional traits, ecological characteristics, such as range size and specialization, and phylogeny to predict climatic risks in European butterflies.LocationEurope.Time PeriodDistribution data from 1981 to 2002 was used to project range shifts up to 2080.Major Taxa StudiedIn total, 268 European butterfly species (Rhopalocera).MethodsWe extracted information on climatic risk for each species from the literature. Two hypothetical conditions were assumed: full climate tracking and no climate tracking. We used variation partitioning to quantify and disentangle the effects of phylogeny, four traits (wingspan, voltinism, overwintering and egg volume) and two ecological characteristics (range size and specialization) on climatic risk. We used Random Forest as an imputation method to predict climatic risk values for additional European butterfly species that have not been previously modelled.ResultsRange size and degree of specialization strongly predicted climatic risk of European butterflies, but only for no climate tracking scenarios. Overall, more generalist species have larger ranges and are less vulnerable to climate change. Furthermore, we found that phylogenetic information adds strong power to explain climatic risk, especially, but not exclusively for scenarios that assume full climate tracking.Main ConclusionsConsidering current scenarios of habitat fragmentation in Europe, it is likely that species with smaller ranges and high degree of specialization will be unable to track their climates and thus be more at risk. However, our results imply that assisting dispersal and colonization might allow small ranged species to cope with climate change. Our analysis also indicate that phylogeny can be used as a proxy of unmeasured traits to predict climatic risk unde

Aim Species ranges are highly dynamic, shifting in space and time as a result of complex ecological and evolutionary processes. Disentangling the relative contribution of both processes is challenging but of primary importance for forecasting species distributions under climate change. Here, we use the spectacular range expansion (ca. 1000 km poleward shift within 10 years) of the butterfly Pieris mannii to unravel the factors underlying range dynamics, specifically the role of (i) niche evolution (changes in host-plant preference and acceptance) and (ii) ecological processes (climate change). Location Provence-Alpes-Côte d’Azur, France; North Rhine-Westphalia, Rhineland-Palatinate and Hesse, Germany. Taxon Insect and angiosperms. Methods We employed a combination of (i) common garden experiments, based on replicated populations from the species’ historical and newly established range and host-plant species representative for each distribution range, co-occurrence analyses and (ii) grid-based correlative species distribution modelling (SDM) using Maxent. Results We observed changes in oviposition preference, with females from the newly established populations showing reduced host-plant specialization and also an overall increased fecundity. These changes in behaviour and life history may have enabled using a broader range of habitats and thus facilitated the recent range expansion. In contrast, our results indicate that the range expansion is unlikely to be directly caused by anthropogenic climate change, as the range was not constrained by climate in the first place. Main conclusions We conclude that evolution of a broader dietary niche rather than climate change is associated with the rapid range expansion, and discuss potential indirect consequences of climate change as trigger for the genetic differences found. Our study thus illustrates the importance of species interactions in shaping species distributions and range shifts, and draws attention to indirect effe

Aim Occurrence data are fundamental to macroecology, but accuracy is often compromised when multiple units are lumped together (e.g., in recently separated cryptic species or in citizen science records). Using amalgamated data leads to inaccuracy in species mapping, to biased beta‐diversity assessments and to potentially erroneously predicted responses to climate change. We provide a set of R functions (biodecrypt) to objectively attribute unidentified occurrences to the most probable taxon based on a subset of identified records. Innovation Biodecrypt assumes that unidentified occurrences can only be attributed at certain distances from areas of sympatry. The function draws concave hulls based on the subset of identified records; subsequently, based on hull geometry, it attributes (or not) unidientified records to a given taxon. Concavity can be imposed with an alpha value and sea or land areas can be excluded. A cross‐validation function tests attribution reliability and another function optimises the parameters (alpha, buffer, distance ratio between hulls). We applied the procedure to 16 European butterfly complexes recently separated into 33 cryptic species for which most records were amalgamated. We compared niche similarity and divergence between cryptic taxa, and re‐calculated and contributed updated climatic niche characteristics of the butterflies in Europe (CLIMBER). Main conclusions Biodecrypt showed a cross‐validated correct attribution of known records always ≥ 98% and attributed more than 80% of unidientified records to the most likely taxon in parapatric species. The functions determined where records can be assigned even for largely sympatric species, and highlighted areas where further sampling is required. All the cryptic taxa showed significantly diverging climatic niches, reflected in different values of mean temperature and precipitation compared to the values originally provided in the CLIMBER database. The substantial fraction of cryp

Aim: Niche-based models often ignore spatial variation in the climatic niche of a species across its occupied range and the related variation in the response to changing climate conditions. This assumption may lead to inaccurate predictions of species distribution shifts under climate change. Models have been developed to address this issue, but most of them depend upon prior knowledge on evolutionary lineages, phenotypic traits or ecological processes underlying local adaptation or adaptive plasticity. As such information is often lacking, these models are not frequently used to predict distribution shifts for many species. This limits our ability to explore general patterns of change across species. Innovation: Here, we propose a modelling framework that can be applied across a large sample of species to assess their distribution shifts under future climate while exploring the effect of intraspecific spatial variation in the response to climate conditions. The proposed approach does not require a detailed understanding of the processes underlying such variation. The geographical distribution of a species is split into spatial subsets along the gradient of occupied climate conditions. These subsets are considered as proxies for intraspecific spatial niche variation. Local models are built with each subset and their predictions are assembled across the study area under different dispersal assumptions. Using European butterflies as an example, we show that this approach can be used to explore the uncertainty about predicted distribution shifts arising from intraspecific spatial variation in sensitivity and response to changing climate conditions. Main conclusions: Our modelling approach is not intended to replace advanced modelling methods based on species-specific knowledge of ecological and evolutionary processes, but it is useful as an exploratory tool to detect species for which detailed information on intraspecific responses to climate conditions is likely to ma

Aim Niche‐based models often ignore spatial variation in the climatic niche of a species across its occupied range and the related variation in the response to changing climate conditions. This assumption may lead to inaccurate predictions of species distribution shifts under climate change. Models have been developed to address this issue, but most of them depend upon prior knowledge on evolutionary lineages, phenotypic traits or ecological processes underlying local adaptation or adaptive plasticity. As such information is often lacking, these models are not frequently used to predict distribution shifts for many species. This limits our ability to explore general patterns of change across species. Innovation Here, we propose a modelling framework that can be applied across a large sample of species to assess their distribution shifts under future climate while exploring the effect of intraspecific spatial variation in the response to climate conditions. The proposed approach does not require a detailed understanding of the processes underlying such variation. The geographical distribution of a species is split into spatial subsets along the gradient of occupied climate conditions. These subsets are considered as proxies for intraspecific spatial niche variation. Local models are built with each subset and their predictions are assembled across the study area under different dispersal assumptions. Using European butterflies as an example, we show that this approach can be used to explore the uncertainty about predicted distribution shifts arising from intraspecific spatial variation in sensitivity and response to changing climate conditions. Main conclusions Our modelling approach is not intended to replace advanced modelling methods based on species‐specific knowledge of ecological and evolutionary processes, but it is useful as an exploratory tool to detect species for which detailed information on intraspecific responses to climate conditions is likely to make

Understanding the dynamics of biodiversity, including the spatial distribution of genetic diversity, is critical for predicting responses to environmental changes, as well as for effective conservation measures. This task requires tracking changes in biodiversity at large spatial scales and correlating with species functional traits. We provide three comprehensive resources to understand the determinants for mitochondrial DNA differentiation represented by (a) 15,609 COI sequences and (b) 14 traits belonging to 307 butterfly species occurring in Western‐Central Europe and (c) the first multi‐locus phylogenetic tree of all European butterfly species. By applying phylogenetic regressions we show that mitochondrial DNA spatial differentiation (as measured with GST, G′ST, D and DST) is negatively correlated with species traits determining dispersal capability and colonization ability. Thanks to the high spatial resolution of the COI data, we also provide the first zoogeographic regionalization maps based on intraspecific genetic variation. The overall pattern obtained by averaging the spatial differentiation of all Western‐Central European butterflies shows that the paradigm of long‐term glacial isolation followed by rapid pulses of post‐glacial expansion has been a pervasive phenomenon in European butterflies. The results and the extensive data sets we provide here constitute the basis for genetically‐informed conservation plans for a charismatic group in a continent where flying insects are under alarming decline.

AimSpecies distribution models built with geographically restricted data often fail to capture the full range of conditions experienced by species across their entire distribution area. Using such models to predict distribution shifts under future environmental change may, therefore, produce biased projections. However, restricted-scale models have the potential to include a larger sample of taxa for which distribution data are available and to provide finer-resolution projections that are better applied to conservation planning than the forecasts of broad-scale models. We examine the circumstances under which the projected shifts in species richness patterns derived from restricted-scale and broad-scale models are most likely to be similar.LocationEurope.MethodsThe distribution of butterflies in Finland, Belgium/Netherlands and Spain was modelled based on restricted-scale (local) and broad-scale (continental) distribution and climate data. Both types of models were projected under future climate change scenarios to assess potential changes in species richness.ResultsIn Finland, species richness was projected to increase strongly based on restricted-scale models and to decrease slightly with broad-scale models. In Belgium/Netherlands, restricted-scale models projected a larger decrease in richness than broad-scale models. In Spain, both models projected a slight decrease in richness. We obtained similar projections based on restricted-scale and broad-scale models only in Spain because the climatic conditions available here covered the warm part of the distributions of butterflies better than in Finland and Belgium/Netherlands.Main conclusionsRestricted-scale models that fail to capture the warm part of species distributions produce biased estimates of future changes in species richness when projected under climatic conditions with no modern analogue in the study area. We recommend the use of distribution data beyond the boundaries of the study area to capture the pa

AimBiological invasions are today the second-largest global threat for biodiversity. Once introduced, exotic plant species can modify ecosystem composition, structure and dynamics, eventually driving native species to local extinction. Among the groups of organisms, most likely to be directly affected by exotic invasive plants are herbivorous insects, such as butterflies, which strongly depend on plants throughout their life cycle. However, it remains unclear whether invasive plants have a negative or a positive effect on butterfly diversity at a landscape scale.LocationSwitzerland.MethodsUsing an extensive inventory (393 sites across Switzerland) of both butterfly and invasive plants, we explore the impact of 31 invasive black listed plant species on local butterfly richness. We further identify each butterfly species’ response to invasive plants (i.e. positive, neutral or negative) and analyse the functional and phylogenetic characteristics of these different groups of species.ResultsOur results indicate that butterfly richness negatively correlates with an increase in invasive plant richness. When studying the individual response of each butterfly species to the number of invasive plants, we found that no single butterfly is profiting from invasive plant species, while 28 butterfly species (24%) suffer from the presence of invasive plants. We further show that the species negatively affected are on average less mobile than the unaffected species and that they are phylogenetically clustered.Main conclusionsOur results present evidences of the influence of invasive species on other trophic levels and interaction networks. We further highlight that a lack of management efforts for mitigating invasive plant impacts threatens specific sections of the functional and phylogenetic diversity of butterflies.