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Viruses are omnipresent, yet the knowledge on drivers of viral prevalence in wild host populations is often limited. Biotic factors, such as sympatric managed host species, as well as abiotic factors, such as climatic variables, are likely to impact viral prevalence. Managed and wild bees, which harbor several multi-host viruses with a mostly fecal-oral between-species transmission route, provide an excellent system with which to test for the impact of biotic and abiotic factors on viral prevalence in wild host populations. Here we show on a continental scale that the prevalence of three broad host viruses: the AKI-complex (Acute bee paralysis virus, Kashmir bee virus and Israeli acute paralysis virus), Deformed wing virus, and Slow bee paralysis virus in wild bee populations (bumble bees and solitary bees) is positively related to viral prevalence of sympatric honey bees as well as being impacted by climatic variables. The former highlights the need for good beekeeping practices, including Varroa destructor management to reduce honey bee viral infection and hive placement. Furthermore, we found that viral prevalence in wild bees is at its lowest at the extreme ends of both temperature and precipitation ranges. Under predicted climate change, the frequency of extremes in precipitation and temperature will continue to increase and may hence impact viral prevalence in wild bee communities., (© 2022. The Author(s).)

Identifying patterns in the effects of temperature on species' population abundances could help develop a general framework for predicting the consequences of climate change across different communities and realms. We used long-term population time series data from terrestrial, freshwater, and marine species communities within central Europe to compare the effects of temperature on abundance across a broad range of taxonomic groups. We asked whether there was an average relationship between temperatures in different seasons and annual abundances of species in a community, and whether species attributes (temperature range of distribution, range size, habitat breadth, dispersal ability, body size, and lifespan) explained interspecific variation in the relationship between temperature and abundance. We found that, on average, warmer winter temperatures were associated with greater abundances in terrestrial communities (ground beetles, spiders, and birds) but not always in aquatic communities (freshwater and marine invertebrates and fish). The abundances of species with large geographical ranges, larger body sizes, and longer lifespans tended to be less related to temperature. Our results suggest that climate change may have, in general, positive effects on species' abundances within many terrestrial communities in central Europe while the effects are less predictable in aquatic communities., (© 2017 The Author(s).)

Cross-system studies on the response of different ecosystems to global change will support our understanding of ecological changes. Synoptic views on the planet's two main realms, the marine and terrestrial, however, are rare, owing to the development of rather disparate research communities. We combined questionnaires and a literature review to investigate how the importance of anthropogenic drivers of biodiversity change differs among marine and terrestrial systems and whether differences perceived by marine vs. terrestrial researchers are reflected by the scientific literature. This included asking marine and terrestrial researchers to rate the relevance of different drivers of global change for either marine or terrestrial biodiversity. Land use and the associated loss of natural habitats were rated as most important in the terrestrial realm, while the exploitation of the sea by fishing was rated as most important in the marine realm. The relevance of chemicals, climate change and the increasing atmospheric concentration of CO 2 were rated differently for marine and terrestrial biodiversity respectively. Yet, our literature review provided less evidence for such differences leading to the conclusion that while the history of the use of land and sea differs, impacts of global change are likely to become increasingly similar., (Copyright © 2016 Office national des forêts. Published by Elsevier B.V. All rights reserved.)

Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks.

For many species, geographical ranges are expanding toward the poles in response to climate change, while remaining stable along range edges nearest the equator. Using long-term observations across Europe and North America over 110 years, we tested for climate change-related range shifts in bumblebee species across the full extents of their latitudinal and thermal limits and movements along elevation gradients. We found cross-continentally consistent trends in failures to track warming through time at species' northern range limits, range losses from southern range limits, and shifts to higher elevations among southern species. These effects are independent of changing land uses or pesticide applications and underscore the need to test for climate impacts at both leading and trailing latitudinal and thermal limits for species., (Copyright © 2015, American Association for the Advancement of Science.)

Global change may substantially affect biodiversity and ecosystem functioning but little is known about its effects on essential biotic interactions. Since different environmental drivers rarely act in isolation it is important to consider interactive effects. Here, we focus on how two key drivers of anthropogenic environmental change, climate change and the introduction of alien species, affect plant-pollinator interactions. Based on a literature survey we identify climatically sensitive aspects of species interactions, assess potential effects of climate change on these mechanisms, and derive hypotheses that may form the basis of future research. We find that both climate change and alien species will ultimately lead to the creation of novel communities. In these communities certain interactions may no longer occur while there will also be potential for the emergence of new relationships. Alien species can both partly compensate for the often negative effects of climate change but also amplify them in some cases. Since potential positive effects are often restricted to generalist interactions among species, climate change and alien species in combination can result in significant threats to more specialist interactions involving native species., (© 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society.)

Aim: The 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. Location: Europe. Time Period: Distribution data from 1981 to 2002 was used to project range shifts up to 2080. Major Taxa Studied: In total, 268 European butterfly species (Rhopalocera). Methods: We 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. Results: Range 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 Conclusions: Considering 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 under certain circumstances. [ABSTRACT FROM AUTHOR]

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 cryptic taxa existing across different taxonomic groups and their divergence in climatic niches highlight the importance of using reliably assigned occurrence data in macroecology. [ABSTRACT FROM AUTHOR]

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 a difference for prediction of future distribution shifts. [ABSTRACT FROM AUTHOR]

Climate change and biological invasions are two major global environmental challenges. Both may interact, e.g. via altered impact and distribution of invasive alien species. Even though invasive species play a key role for compromising the health of honey bees, the impact of climate change on the severity of such species is still unknown. The small hive beetle (SHB, Aethina tumida, Murray) is a parasite of honey bee colonies. It is endemic to sub‐Saharan Africa and has established populations on all continents except Antarctica. Since SHBs pupate in soil, pupation performance is governed foremost by two abiotic factors, soil temperature and moisture, which will be affected by climate change. Here, we investigated SHB invasion risk globally under current and future climate scenarios. We modelled survival and development time during pupation (=pupal performance) in response to soil temperature and soil moisture using published and novel experimental data. Presence data on SHB distribution were used for model validation. We then linked the model with global soil data in order to classify areas (resolution: 10 arcmin; i.e. 18.6 km at the equator) as unsuitable, marginal and suitable for SHB pupation performance. Under the current climate, the results show that many areas globally yet uninvaded are actually suitable, suggesting considerable SHB invasion risk. Future scenarios of global warming project a vehement increase in climatic suitability for SHB and corresponding potential for invasion, especially in the temperate regions of the Northern hemisphere, thereby creating demand for enhanced and adapted mitigation and management. Our analysis shows, for the first time, effects of global warming on a honey bee pest and will help areas at risk to prepare adequately. In conclusion, this is a clear case for global warming promoting biological invasion of a pest species with severe potential to harm important pollinator species globally. [ABSTRACT FROM AUTHOR]

Aim: Conventional species distribution models (SDMs) usually focus on the species level but disregard intraspecific variability. Phylogeographic structure and evolutionary significant units (ESU) have been proposed as pragmatic proxies to incorporate intraspecific differentiation in SDMs. Nevertheless, the efficiency of using these proxies in SDMs has been poorly investigated. We analysed how the projections of current and future climatically suitable areas can be affected when using ESU‐based or lineage‐based models compared to a species‐level model. Location: West‐Palaearctic region. Methods: As examples, we used three bumblebee species (133,787 observations). We assessed potential climatic niche differentiation between species level, lineages and ESUs, by determining the niche position and niche breadth for each classification level by outlying mean index analyses. Subsequently, we developed SDMs for each species and classification level separately using boosted regression trees prior to a comparison of their performances. Finally, we used the alternative models to project the extent of climatically suitable areas in 2070. Results: We found that in spite of highly similar overall model accuracy, integrating intraspecific variability significantly increases model sensitivity (i.e., better predicting presences) while decreased model specificity (i.e., over‐predicting the range). Consequently, both predictions of current and projections of future suitable conditions differed among the three approaches. Main conclusions: We showed that although integrating lineage or ESU information did not improve the accuracy of conventional species‐level SDMs, it led to considerably different conclusions. As SDM‐based climatic risk assessments are increasingly used to help and improve conservation plans, divergences and limitations of each modelling approach should be taken into account for developing efficient biodiversity management strategies. Lineage and ESU‐based SDMs offer the advantage to draw attention to species in which allopatric populations could display physiologically different responses to climate change when they lead to different results than species‐based models. [ABSTRACT FROM AUTHOR]

Species range shifts under climate change have predominantly been projected by models correlating species observations with climatic conditions. However, geographic range shifting may depend on biotic factors such as demography, dispersal and species interactions. Recently suggested hybrid models include these factors. However, parameterization of hybrid models suffers from lack of detailed ecological data across many taxa. Further, it is methodologically unclear how to upscale ecological information from scales relevant to ecological processes to the coarser resolution of species distribution data (often 100 km 2 or even 2500 km 2 ). We tackle these problems by developing a novel modelling and calibration framework, which allows hybrid model calibration from (static) presence-absence data that is available for many species. The framework improves understanding of the influence of biotic processes on range projections and reveals critical sources of uncertainty that limit projection reliability. We demonstrate its performance for the case of the butterfly Titania’s Fritillary ( Boloria titania) . [ABSTRACT FROM AUTHOR]

Identifying patterns in the effects of temperature on species' population abundances could help develop a general framework for predicting the consequences of climate change across different communities and realms. We used long-term population time series data from terrestrial, freshwater, and marine species communitieswithin central Europe to compare the effects of temperature on abundance across a broad range of taxonomic groups.We askedwhether there was anaverage relationship betweentemperatures in different seasons andannual abundances of species in a community, and whether species attributes (temperature range of distribution, range size, habitat breadth, dispersal ability, body size, and lifespan) explained interspecific variation in the relationship between temperature and abundance. We found that, on average, warmer winter temperatureswere associatedwith greater abundances in terrestrial communities (ground beetles, spiders, and birds) but not always in aquatic communities (freshwater and marine invertebrates and fish). The abundances of species with large geographical ranges, larger body sizes, and longer lifespans tended to be less related to temperature. Our results suggest that climate changemay have, in general, positive effects on species' abundanceswithinmany terrestrial communities in central Europe while the effects are less predictable in aquatic communities. [ABSTRACT FROM AUTHOR]

The effect of climate change on wild bee communities is of major concern since the decline of bee species could imperil the provision of pollination services. Additionally, habitat loss and fragmentation are major threats to wild bee populations, but improvements to the landscape structure could also improve the general conditions for wild bees. However, potential interactive effects of climate change and landscape structure on wild bee communities remain unknown., In this study, we assessed the potential of semi-natural areas to maintain robust communities under changing weather conditions. We used bee monitoring data from six 4 × 4 km field sites across Germany. Almost 30 000 bee specimens were collected from 2010 to 2012 in 16 local communities per site at six sampling occasions per year. Following a multimodel inference approach, we identified the most important weather and landscape variables as well as interaction terms that affect wild bee species richness and total abundance., Correcting for overall phenology, we found a strong negative relationship between bee species richness and temperature, indicating that future increasing temperatures will lead to a decrease in species richness. However, a high proportion of semi-natural habitats can considerably decrease the detrimental effect of warmer temperatures on bee species richness and abundance., Synthesis and applications. Semi-natural areas and green infrastructure elements within agricultural landscapes become even more important under changing temperature conditions to mitigate the negative effects of increasing temperatures on wild bee species richness and total abundance. This has important implications for conservation decision making, suggesting that maintaining or restoring a fair amount of semi-natural areas could serve as a countermeasure against climate change for wild bees. [ABSTRACT FROM AUTHOR]

Detailed information on species' ecological niche characteristics that can be related to declines and extinctions is indispensable for a better understanding of the relationship between the occurrence and performance of wild species and their environment and, moreover, for an improved assessment of the impacts of global change. Knowledge on species characteristics such as habitat requirements is already available in the ecological literature for butterflies, but information about their climatic requirements is still lacking. Here we present a unique dataset on the climatic niche characteristics of 397 European butterflies representing 91% of the European species (see Appendix). These characteristics were obtained by combining detailed information on butterfly distributions in Europe (which also led to the 'Distribution Atlas of Butterflies in Europe') and the corresponding climatic conditions. The presented dataset comprises information for the position and breadth of the following climatic niche characteristics: mean annual temperature, range in annual temperature, growing degree days, annual precipitation sum, range in annual precipitation and soil water content. The climatic niche position is indicated by the median and mean value for each climate variable across a species' range, accompanied by the 95% confidence interval for the mean and the number of grid cells used for calculations. Climatic niche breadth is indicated by the standard deviation and the minimum and maximum values for each climatic variable across a species' range. Database compilation was based on high quality standards and the data are ready to use for a broad range of applications. It is already evident that the information provided in this dataset is of great relevance for basic and applied ecology. Based on the species temperature index (STI, i.e. the mean temperature value per species), the community temperature index (CTI, i.e. the average STI value across the species in a community) was recently adopted as an indicator of climate change impact on biodiversity by the pan-European framework supporting the Convention on Biological Diversity (Streamlining European Biodiversity Indicators 2010) and has already been used in several scientific publications. The application potential of this database ranges from theoretical aspects such as assessments of past niche evolution or analyses of trait interdependencies to the very applied aspects of measuring, monitoring and projecting historical, ongoing and potential future responses to climate change using butterflies as an indicator. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim To describe and explain geographical patterns of false absence and false presence prediction errors that occur when describing current plant species ranges with species distribution models. Location Europe. Methods We calibrated species distribution models (generalized linear models) using a set of climatic variables and gridded distribution data for 1065 vascular plant species from the Atlas Florae Europaeae. We used randomly selected subsets for each species with a constant prevalence of 0.5, modelled the distribution 1000 times, calculated weighted averages of the model parameters and used these to predict the current distribution in Europe. Using a threshold of 0.5, we derived presence/absence maps. Comparing observed and modelled species distribution, we calculated the false absence rates, i.e. species wrongly modelled as absent, and the false presence rates, i.e. species wrongly modelled as present, on a 50 × 50 km grid. Subsequently, we related both error rates to species range properties, land use and topographic variability within grid cells by means of simultaneous autoregressive models to correct for spatial autocorrelation. Results Grid-cell-specific error rates were not evenly distributed across Europe. The mean false absence rate was 0.16 ± 0.12 (standard deviation) and the mean false presence rate was 0.22 ± 0.13. False absence rates were highest in central Spain, the Alps and parts of south-eastern Europe, while false presence rates were highest in northern Spain, France, Italy and south-eastern Europe. False absence rates were high when range edges of species accumulated within a grid cell and when the intensity of human land use was high. False presence rates were positively associated with relative occurrence area and accumulation of range edges. Main conclusions Predictions for various species are not only accompanied by species-specific but also by grid-cell-specific errors. The latter are associated with characteristics of the grid cells but also with range characteristics of occurring species. Uncertainties of predictive species distribution models are not equally distributed in space, and we would recommend accompanying maps of predicted distributions with a graphical representation of predictive performance. [ABSTRACT FROM AUTHOR]

The author reflects on the impact of climate change on biodiversity. The author states that climate change and human modification of the landscape are synergistic, thus, affect biodiversity and the stability of ecosystems. Moreover, the author mentions the ALARM research project funded by European Union which aims to apply best understanding of how terrestrial and freshwater organisms and ecosystems function and to use new ways to assess large scale environmental risks.

Biodiversity conservation measures and biological processes often do not match in scale. The EU funded project SCALES (Securing the Conservation of biodiversity across Administrative Levels and spatial, temporal, and Ecological Scales) is intended to solve this challenge. SCALES analyses how selected pressures (climate change, habitat loss, fragmentation, disturbance), their drivers, and their impacts on biodiversity change with spatial and temporal scale. The project develops methods for a better understanding of scaling properties of biological processes from the genetic level to populations, communities, and ecosystem functions. SCALES also seeks ways to integrate the issue of scale into policy, decision-making, and biodiversity management, focusing on networks of protected areas, regional connectivity, and biodiversity monitoring. [ABSTRACT FROM AUTHOR]

Observed patterns of species richness at landscape scale (gamma diversity) cannot always be attributed to a specific set of explanatory variables, but rather different alternative explanatory statistical models of similar quality may exist. Therefore predictions of the effects of environmental change (such as in climate or land cover) on biodiversity may differ considerably, depending on the chosen set of explanatory variables. Here we use multimodel prediction to evaluate effects of climate, land-use intensity and landscape structure on species richness in each of seven groups of organisms (plants, birds, spiders, wild bees, ground beetles, true bugs and hoverflies) in temperate Europe. We contrast this approach with traditional best-model predictions, which we show, using cross-validation, to have inferior prediction accuracy. Multimodel inference changed the importance of some environmental variables in comparison with the best model, and accordingly gave deviating predictions for environmental change effects. Overall, prediction uncertainty for the multimodel approach was only slightly higher than that of the best model, and absolute changes in predicted species richness were also comparable. Richness predictions varied generally more for the impact of climate change than for land-use change at the coarse scale of our study. Overall, our study indicates that the uncertainty introduced to environmental change predictions through uncertainty in model selection both qualitatively and quantitatively affects species richness projections. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Terrestrial Ecosystem Responses to Species Gains and Losses," by D. A. Wardle and colleagues in the June 10, 2011 issue.

Multiple global change pressures, and their interplay, cause plant–pollinator extinctions and modify species assemblages and interactions. This may alter the risks of pathogen host shifts, intra- or interspecific pathogen spread, and emergence of novel population or community epidemics. Flowers are hubs for pathogen transmission. Consequently, the structure of plant–pollinator interaction networks may be pivotal in pathogen host shifts and modulating disease dynamics. Traits of plants, pollinators, and pathogens may also govern the interspecific spread of pathogens. Pathogen spillover–spillback between managed and wild pollinators risks driving the evolution of virulence and community epidemics. Understanding this interplay between host–pathogen dynamics and global change will be crucial to predicting impacts on pollinators and pollination underpinning ecosystems and human wellbeing. Flower sharing amongst pollinator species represents a conduit for interspecific insect pathogen transmission. Plant–pollinator network structure and species traits shape pathogen dynamics in the pollinator community. Global change (climate change, invasive species, agricultural intensification, and urbanisation) can modulate species interactions, host susceptibility, and pathogen virulence, thereby creating novel epidemiological risks. Multiple global change effects can interact in synergistic or antagonistic ways, creating additional risks and complicating predictions of pathogen dynamics and evolution. Flower-mediated insect pathogen transmission provides a model framework to understand the interplay of interspecific pathogen dynamics under global change. [ABSTRACT FROM AUTHOR]

Pollinators are a key component of global biodiversity, providing vital ecosystem services to crops and wild plants. There is clear evidence of recent declines in both wild and domesticated pollinators, and parallel declines in the plants that rely upon them. Here we describe the nature and extent of reported declines, and review the potential drivers of pollinator loss, including habitat loss and fragmentation, agrochemicals, pathogens, alien species, climate change and the interactions between them. Pollinator declines can result in loss of pollination services which have important negative ecological and economic impacts that could significantly affect the maintenance of wild plant diversity, wider ecosystem stability, crop production, food security and human welfare. [Copyright &y& Elsevier]