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Aim: Reconstructing megafauna diversity in the past before anthropogenic impacts is crucial for developing targeted restoration strategies. We estimated the diversity and functional decline of European megafauna in the present compared with the nearest in‐time climate period analogue to the present but prior to the worldwide diffusion of Homo sapiens. Location: Europe. Time Period: Last Interglacial (LIG; ca. 127,000 years ago) to present. Major Taxa Studied: Wild, large (≥10 kg) terrestrial mammals. Methods: We assessed the distribution of 48 European megafauna species during the LIG using hindcasting modelling and fossil records. Then, we estimated the decline in megafauna community diversity and potential trait‐based functional effects from the LIG to the present, accounting for climate differences between the two periods. Results: Species richness and community biomass dropped by 70.8% (±11.7%) and by 94.5% (±9.9%). Functional diversity dropped by 80.3% (±15.3%) for herbivores and by 64.9% (±29.1%) for carnivores, while trait‐informed potential vegetation and meat consumptions dropped by 82.3% (±13.4%) and 60.5% (±26.0%). The loss in megafauna diversity and associated ecological processes were high everywhere, but particularly in western Europe for carnivores and in the East European Plain for herbivores. Potential megafauna richness in the two periods was similar if only climate‐driven differences were considered. Main Conclusions: Severe, size‐biased defaunation has degraded megafauna assemblages and megafauna‐mediated ecological processes across Europe from the LIG to the present. These patterns cannot be explained by climate differences between the two periods, thus were likely driven by prehistoric Homo sapiens. The results suggest that the structure of wild ecosystems of the present strongly deviates from the evolutionary norm, with decreased functional heterogeneity and decreased fluxes of biogeochemical compounds across the trophic networks, highlighting the importance of ambitious policies of megafauna community restoration to support ecosystem functioning. [ABSTRACT FROM AUTHOR]

Classic ecological research into the determinants of biodiversity patterns emphasised the important role of three‐dimensional (3D) vegetation heterogeneity. Yet, measuring vegetation structure across large areas has historically been difficult. A growing focus on large‐scale research questions has caused local vegetation heterogeneity to be overlooked compared with more readily accessible habitat metrics from, for example, land cover maps.Using newly available 3D vegetation data, we investigated the relative importance of habitat and vegetation heterogeneity for explaining patterns of bird species richness and composition across Denmark (42,394 km2).We used standardised, repeated point counts of birds conducted by volunteers across Denmark alongside metrics of habitat availability from land‐cover maps and vegetation structure from rasterised LiDAR data (10 m resolution). We used random forest models to relate species richness to environmental features and considered trait‐specific responses by grouping species by nesting behaviour, habitat preference and primary lifestyle. Finally, we evaluated the role of habitat and vegetation heterogeneity metrics in explaining local bird assemblage composition.Overall, vegetation structure was equally as important as habitat availability for explaining bird richness patterns. However, we did not find a consistent positive relationship between species richness and habitat or vegetation heterogeneity; instead, functional groups displayed individual responses to habitat features. Meanwhile, habitat availability had the strongest correlation with the patterns of bird assemblage composition.Our results show how LiDAR and land cover data complement one another to provide insights into different facets of biodiversity patterns and demonstrate the potential of combining remote sensing and structured citizen science programmes for biodiversity research. With the growing coverage of LiDAR surveys, we are witnessing a revolution of highly detailed 3D data that will allow us to integrate vegetation heterogeneity into studies at large spatial extents and advance our understanding of species' physical niches. [ABSTRACT FROM AUTHOR]

Aim: Theory suggests that increasing productivity and climate stability towards the tropics favours specialization, thus contributing to the latitudinal richness gradient. A positive relationship between species richness and specialization should therefore emerge as a fundamental biogeographical pattern. However, land‐use and climate changes disproportionally increase the local extirpation risk for specialists, potentially weakening the relationship between richness and specialization. Here, we quantify empirically the richness–specialization prediction and test how 50 years of climate and land‐use change has affected the richness–specialization relationship. Location: USA. Time period: 1966–2015. Major taxa studied: Birds. Methods: We used the North American Breeding Bird Survey to quantify bird community richness and specialization to habitat and climate. We (a) quantify temporal change in the slope of the richness–specialization relationship, using a generalized mixed model; (b) assess how this change translates spatially, using generalized additive models; and (c) attribute spatio‐temporal change in the richness–specialization relationship to land use, climate and topographic drivers. Results: We found evidence for a positive but weak richness–specialization relationship in bird communities that greatly weakened over time. Given that specialization was not the main driver of richness, this relationship did not translate spatially into a linear spatial covariation between richness and specialization. Instead, the spatial covariation in richness and specialization followed a unimodal pattern, the peak of which shifted towards less specialized communities over time. These temporal changes were associated with precipitation change, decreasing temperature stability and land use. Main conclusions: Recent climate and land‐use changes have induced two contrasting types of community responses. In human‐dominated areas, the decoupling of richness and specialization drove a general trend for biotic homogenization. In areas of low human impact experiencing increasing climate harshness, specialization increased, whereas richness decreased. Our results offer new support for specialization as a key driver of macroecological diversity patterns and show that global changes are weakening this fundamental macroecological pattern. [ABSTRACT FROM AUTHOR]

Arctic plant communities are altered by climate changes. The magnitude of these alterations depends on whether species distributions are determined by macroclimatic conditions, by factors related to local topography, or by biotic interactions. Our current understanding of the relative importance of these conditions is limited due to the scarcity of studies, especially in the High Arctic. We investigated variations in vascular plant community composition and species richness based on 288 plots distributed on three sites along a coast-inland gradient in Northeast Greenland using a stratified random design. We used an information theoretic approach to determine whether variations in species richness were best explained by macroclimate, by factors related to local topography (including soil water) or by plant-plant interactions. Latent variable models were used to explain patterns in plant community composition. Species richness was mainly determined by variations in soil water content, which explained 35% of the variation, and to a minor degree by other variables related to topography. Species richness was not directly related to macroclimate. Latent variable models showed that 23.0% of the variation in community composition was explained by variables related to topography, while distance to the inland ice explained an additional 6.4 %. This indicates that some species are associated with environmental conditions found in only some parts of the coast-inland gradient. Inclusion of macroclimatic variation increased the model's explanatory power by 4.2%. Our results suggest that the main impact of climate changes in the High Arctic will be mediated by their influence on local soil water conditions. Increasing temperatures are likely to cause higher evaporation rates and alter the distribution of late-melting snow patches. This will have little impact on landscape-scale diversity if plants are able to redistribute locally to remain in areas with sufficient soil water. [ABSTRACT FROM AUTHOR]

Arthropods form a major part of the terrestrial species diversity in the Arctic, and are particularly sensitive to temporal changes in the abiotic environment. It is assumed that most Arctic arthropods are habitat generalists and that their diversity patterns exhibit low spatial variation. The empirical basis for this assumption, however, is weak. We examine the degree of spatial variation in species diversity and assemblage structure among five habitat types at two sites of similar abiotic conditions and plant species composition in southwest Greenland, using standardized field collection methods for spiders, beetles and butterflies. We employed non-metric multidimensional scaling, species richness estimation, community dissimilarity and indicator species analysis to test for local (within site)- and regional (between site)-scale differences in arthropod communities. To identify specific drivers of local arthropod assemblages, we used a combination of ordination techniques and linear regression. Species richness and the species pool differed between sites, with the latter indicating high species turnover. Local-scale assemblage patterns were related to soil moisture and temperature. We conclude that Arctic arthropod species assemblages vary substantially over short distances due to local soil characteristics, while regional variation in the species pool is likely influenced by geographic barriers, i.e., inland ice sheet, glaciers, mountains and large water bodies. In order to predict future changes to Arctic arthropod diversity, further efforts are needed to disentangle contemporary drivers of diversity at multiple spatial scales. [ABSTRACT FROM AUTHOR]

The relationship between large-scale gradients in species richness and functional diversity provides important information regarding the mechanisms driving patterns of biodiversity. A classic hypothesis in ecology is that strong interspecific interactions should result in an increase in the functional volume of assemblages as the species richness increases, whereas climatic constraints may result in no change in functional volume. Most research of this kind examines latitudinal gradients in species richness, but the results are likely confounded by underlying gradients in climate and phylogenetic composition. We take an alternative approach that examines functional richness across a tree species richness anomaly where species richness doubles from Europe to eastern North America. The results demonstrate that the functional richness on both continents saturates at a similar point as species richness increases and that the packing of functional space becomes tighter. Further, the species richness anomaly is driven primarily by genera unique to North America, but those genera contribute less than expected functional richness to the region, indicating a high level of redundancy with genera shared between the continents. Taken together, the results indicate that the species richness anomaly is associated with diversification within a climatically constrained trait space. More generally, the work demonstrates the power of utilizing species richness anomalies in biodiversity research, particularly when they are coupled with information regarding organismal function. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim To identify potential source and sink locations for climate-driven species range shifts in Europe since the Last Glacial Maximum (LGM). Location Europe. Methods We developed a new approach combining past-climate simulations with the concept of analogous climate space. Our index gives a continuous measure of the potential of a location to have acted as a source or a sink for species that have shifted their ranges since the LGM. High glacial source potential is indicated by LGM climatic conditions that are widespread now; high post-glacial sink potential is indicated by current climatic conditions that were widespread at the LGM. The degree of isolation of source and sink areas was calculated as the median distance to areas with analogous climate conditions. Results We identified areas of high glacial source potential in the previously recognized refugial areas in the southern European peninsulas, but also in large areas in central-western Europe. The most climatically isolated source areas were located in northern Spain, in north-western Europe and in eastern Turkey. From here species would have had to cover substantial distances to find current climate conditions analogous to LGM conditions of these areas. Areas with high post-glacial sink potential were mainly located in Fennoscandia and in central and south-eastern Europe. Some of the most isolated sink areas were located in the Spanish highlands and around the Baltic Sea. Main conclusions Our species-independent approach successfully identified previously recognized glacial refugial areas with high source potential for species range shifts in southern Europe and in addition highlighted other potential source areas in central Europe. This study offers new insights into how the distribution of past and current climatic conditions may have influenced past species range shifts and current large-scale biodiversity patterns. [ABSTRACT FROM AUTHOR]

Effective planning and nature management require spatially accurate and comprehensive measures of the factors important for biodiversity. Light detection and ranging (LIDAR) can provide exactly this, and is therefore a promising technology to support future nature management and related applications. However, until now studies evaluating the potential of LIDAR for this field have been highly limited in scope. Here, we assess the potential of LIDAR to estimate the local diversity of four species groups in multiple habitat types, from open grasslands and meadows over shrubland to forests and across a large area (~43,000 km2), providing a crucial step toward enabling the application of LIDAR in practice, planning, and policy‐making. We assessed the relationships between the species richness of macrofungi, lichens, bryophytes, and plants, respectively, and 25 LIDAR‐based measures related to potential abiotic and biotic diversity drivers. We used negative binomial generalized linear modeling to construct 19 different candidate models for each species group, and leave‐one‐region‐out cross validation to select the best models. These best models explained 49%, 31%, 32%, and 28% of the variation in species richness (R2) for macrofungi, lichens, bryophytes, and plants, respectively. Three LIDAR measures, terrain slope, shrub layer height and variation in local heat load, were important and positively related to the richness in three of the four species groups. For at least one of the species groups, four other LIDAR measures, shrub layer density, medium‐tree layer density, and variations in point amplitude and in relative biomass, were among the three most important. Generally, LIDAR measures exhibited strong associations to the biotic environment, and to some abiotic factors, but were poor measures of spatial landscape and temporal habitat continuity. In conclusion, we showed how well LIDAR alone can predict the local biodiversity across habitats. We also showed that several LIDAR measures are highly correlated to important biodiversity drivers, which are notoriously hard to measure in the field. This opens up hitherto unseen possibilities for using LIDAR for cost‐effective monitoring and management of local biodiversity across species groups and habitat types even over large areas. [ABSTRACT FROM AUTHOR]