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Aim The former continental‐scale studies modelled coarse‐grained plant species‐richness patterns (gamma diversity). Here we aim to refine this information for European forests by (a) modelling the number of vascular plant species that co‐occur in local communities (alpha diversity) within spatial units of 400 m2; and (b) assessing the factors likely determining the observed spatial patterns in alpha diversity. Location Europe roughly within 12°W–30°E and 35–60°N. Taxon Vascular plants. Methods The numbers of co‐occurring vascular plant species were counted in 73,134 georeferenced vegetation plots. Each plot was classified by an expert system into deciduous broadleaf, coniferous or sclerophyllous forest. Random Forest models were used to map and explain spatial patterns in alpha diversity for each forest type separately using 19 environmental, land‐use and historical variables. Results Our models explained from 51.0% to 70.9% of the variation in forest alpha diversity. The modelled alpha‐diversity pattern was dominated by a marked gradient from species‐poor north‐western to species‐rich south‐eastern Europe. The most prominent richness hotspots were identified in the Calcareous Alps and adjacent north‐western Dinarides, the Carpathian foothills in Romania and the Western Carpathians in Slovakia. Energy‐related factors, bedrock types and terrain ruggedness were identified as the main variables underlying the observed richness patterns. Alpha diversity increases especially with temperature seasonality in deciduous broadleaf forests, on limestone bedrock in coniferous forests and in areas with low annual actual evapotranspiration in sclerophyllous forests. Main conclusions We provide the first predictive maps and analyses of environmental factors driving the alpha diversity of vascular plants across European forests. Such information is important for the general understanding of European biodiversity. This study also demonstrates a high potential of vegetation‐plot databases as sources for robust estimation of the number of vascular plant species that co‐occur at fine spatial grains across large areas.

Although we understand how species evolve, we do not appreciate how this process has filled an empty world to create current patterns of biodiversity. Here, we conduct a numerical experiment to determine why biodiversity varies spatially on our planet. We show that spatial patterns of biodiversity are mathematically constrained and arise from the interaction between the species’ ecological niches and environmental variability that propagates to the community level. Our results allow us to explain key biological observations such as (a) latitudinal biodiversity gradients (LBGs) and especially why oceanic LBGs primarily peak at midlatitudes while terrestrial LBGs generally exhibit a maximum at the equator, (b) the greater biodiversity on land even though life first evolved in the sea, (c) the greater species richness at the seabed than at the sea surface, and (d) the higher neritic (i.e., species occurring in areas with a bathymetry lower than 200 m) than oceanic (i.e., species occurring in areas with a bathymetry higher than 200 m) biodiversity. Our results suggest that a mathematical constraint originating from a fundamental ecological interaction, that is, the niche–environment interaction, fixes the number of species that can establish regionally by speciation or migration. We show that spatial patterns of biodiversity are mathematically constrained and arise from the interaction between the species' ecological niches and environmental variability that propagates to the community level. Our results allow us to explain key biological observations such as (a) latitudinal biodiversity gradients in the terrestrial and the marine (surface and bottom) domains, (b) the greater biodiversity on land even though life first evolved in the sea, (c) the greater species richness at the seabed than at the sea surface, and (d) higher neritic than oceanic biodiversity.

The idea that the number of species within an area is limited by a specific capacity of that area to host species is old yet controversial. Here, we show that the concept of carrying capacity for species richness can be as useful as the analogous concept in population biology. Many lines of empirical evidence indicate the existence of limits of species richness, at least at large spatial and phylogenetic scales. However, available evidence does not support the idea of diversity limits based on limited niche space; instead, carrying capacity should be understood as a stable equilibrium of biodiversity dynamics driven by diversity-dependent processes of extinction, speciation and/or colonization. We argue that such stable equilibria exist even if not all resources are used and if increasing species richness increases the ability of a community to use resources. Evaluating the various theoretical approaches to modelling diversity dynamics, we conclude that a fruitful approach for macroecology and biodiversity science is to develop theory that assumes that the key mechanism leading to stable diversity equilibria is the negative diversity dependence of per-species extinction rates, driven by the fact that population sizes of species must decrease with an increasing number of species owing to limited energy availability. The recently proposed equilibrium theory of biodiversity dynamics is an example of such a theory, which predicts that equilibrium species richness (i.e., carrying capacity) is determined by the interplay of the total amount of available resources, the ability of communities to use those resources, environmental stability that affects extinction rates, and the factors that affect speciation and colonization rates. We argue that the diversity equilibria resulting from these biodiversity dynamics are first-order drivers of large-scale biodiversity patterns, such as the latitudinal diversity gradient.

Aim: To identify hotspots of endemic and non-endemic avian diversity in the mountains of south-west China and delineate biodiversity corridors that connect the faunas of northern and southern Asia. To understand how biodiversity and endemism in this region has been maintained through palaeoclimate change. Location: The mountains of south-west China, spanning an elevational gradient > 7000 m. Methods: We used the distributional data of 752 breeding birds to investigate current patterns of diversity across elevational and geographical space. We simulated species richness under palaeoclimate models of global temperature change, assessing changes in species richness. Results: Contemporary species richness of non-endemic birds peaked at 800-1800 m elevation, while endemic richness peaked at 2000-3000 m. Richness of non-endemic birds was highest in the southern Hengduan Mountains and Yungui Plateau, while endemic richness peaked further north, extending into the mountains along the western edge of the Sichuan Basin. Under global warming models, species richness remained high throughout the Hengduan Mountains region. Under global cooling models, the Sichuan Basin showed increased richness. Conclusions: Endemism peaked in the mountains along the western edge of the Sichuan Basin, highlighting the importance of this region in promoting and maintaining diversity. This region has likely functioned as a biodiversity corridor, bridging the Palaearctic and Oriental biotas to the north and south. Climate simulations suggest that the mountains of south-west China can accommodate upslope range shifts in response to warming, but low elevation specialists may have experienced increased extinction probabilities during cold periods in the recent past, which may in part explain the current mid-elevation diversity peak. During glacial periods the Sichuan Basin likely served as a warm refugium for montane birds. Steep environmental heterogeneity has been a key to maintaining high diversity and endemism in the region during palaeoclimate change. These same features will likely shape the effects of future climate change on biodiversity in the region.

Aim: To examine the global distribution, endemicity, and latitudinal gradients of species richness of razor clams, family Solenidae. Location: Global. Methods: A total of 3105 distribution records for 77 Solen and Solena species were used. Species richness was plotted in 5° latitude-longitude cells and related to environmental variables. Results: The north-west Pacific and the Indo-West Pacific have the highest species richness (about 85% of all species)–mostly in the Sea of Japan, China Sea, the Gulf of Thailand and the Andaman Sea. Cluster analysis of similarity patterns of species composition (i.e., presence of Solenidae species) for 5° latitudinal-longitudinal grid cells showed 16 significant biogeographical regions that concur with existing marine biogeographical hypotheses. More than half of the species were endemic to specific biogeographical regions. The geographical distribution of species in 5° latitudinal bands showed a significant bimodal pattern. Global patterns of species richness increased from the poles to intermediate latitudes and dipped near the equator. A non-linear relationship between species richness and mean sea-surface temperature (SST) values was compatible with this bimodal pattern. Two inflection points of species richness with correlation of SST at 12° C (low species richness) and 28° C (high species richness) were coincident with the bimodal latitudinal species richness pattern. Species richness was highly positively correlated with mean SST over all latitudes, and within the Northern and Southern Hemispheres. Species richness decreased with SST range over all latitudes and in the Northern Hemisphere. Species richness also decreased with chlorophyll-á concentration and primary productivity, but increased with ocean area in the Northern Hemisphere (only). Main conclusions: The latitudinal distribution in species richness of Solenidae peaked at 10° N and 25° S rather than at the equator, exhibiting a strongly bimodal pattern that is likely to be temperature driven.

Most studies examining continental-to-global patterns of species richness rely on the overlaying of extent-of-occurrence range maps. Because a species does not occur at all locations within its geographic range, range-map-derived data represent actual distributional patterns only at some relatively coarse and undefined resolution. With the increasing availability of high-resolution climate and land-cover data, broad-scale studies are increasingly likely to estimate richness at high resolutions. Because of the scale dependence of most ecological phenomena, a significant mismatch between the presumed and actual scale of ecological data may arise. This may affect conclusions regarding basic drivers of diversity and may lead to errors in the identification of diversity hotspots. Here, we examine avian range maps of 834 bird species in conjunction with geographically extensive survey data sets on two continents to determine the spatial resolutions at which range-map data actually characterize species occurrences and patterns of species richness. At resolutions less than 2° ([almost equal to]200 km), range maps overestimate the area of occupancy of individual species and mischaracterize spatial patterns of species richness, resulting in up to two-thirds of biodiversity hotspots being misidentified. The scale dependence of range-map accuracy poses clear limitations on broad-scale ecological analyses and conservation assessments. We suggest that range-map data contain less information than is generally assumed and provide guidance about the appropriate scale of their use.

Climate change has significant impacts on species' distributions and diversity patterns. Understanding range shifts and changes in richness gradients under climate change is crucial for conservation. The Tibetan Plateau, home to wild yak, chiru, and kiang, contains a biome with many endemic ungulates. It is highly sensitive to climate change and a region that merits particular attention with regard to the impacts of global climate change on its biomes. Maximum entropy approaches were used to estimate current and future potential distributions, in response to climate change, for 22 ungulate species. We used three general circulation (MK3, HADCM3, MIROC3_2-MED) and three emissions scenarios (B1, A1B, A2) to derive estimated future measurements of 14 environmental variables over three time periods (2020, 2050, 2080), and then modeled species distributions using these predicted environmental measurements for each time period under two dispersal hypotheses (full and zero, respectively). This resulted in a total of 6160 prediction models. We found that these ungulates, on average, may lose 30-50% of their distributional areas, depending on the dispersal scenarios. In addition, 55-68% of the ungulate species were predicted to become locally endangered under the different dispersal assumptions, 23-32% to become locally critically endangered, and 4-7 endemic species to become globally endangered. Furthermore, ungulate species ranges may experience average poleward shifts of ~300 km. We also predict west-to-east reductions in species richness: southeastern mountainous areas currently have the highest species richness, but are predicted to face the greatest diversity losses, whereas the northern areas are predicted to see increasing numbers of ungulate species in the 21st century. Our study indicates much more severe range reductions of ungulates on the Tibetan Plateau than those anticipated elsewhere in the world, and species richness patterns will change dramatically with climate change. For conservation, we suggest (1) securing existing protected areas, and (2) establishing new nature reserves to counterbalance climate change impacts.

What determines large-scale patterns of species richness remains one of the most controversial issues in ecology. Using the distribution maps of 11 405 woody species in China, we compared the effects of habitat heterogeneity, human activities and different aspects of climate, particularly environmental energy, water–energy dynamics and winter frost, and explored how biogeographic affinities (tropical versus temperate) influence richness–climate relationships. We found that the species richness of trees, shrubs, lianas and all woody plants strongly correlated with each other, and more strongly correlated with the species richness of tropical affinity than with that of temperate affinity. The mean temperature of the coldest quarter was the strongest predictor of species richness, and its explanatory power for species richness was significantly higher for tropical affinity than for temperate affinity. These results suggest that the patterns of woody species richness mainly result from the increasing intensity of frost filtering for tropical species from the equator/lowlands towards the poles/highlands, and hence support the freezing-tolerance hypothesis. A model based on these results was developed, which explained 76–85% of species richness variation in China, and reasonably predicted the species richness of woody plants in North America and the Northern Hemisphere.

Aim: Relatively few models of species richness explicitly consider aspects of environmental heterogeneity, other than topographic heterogeneity. We hypothesized that environmental heterogeneity is an important determinant of species richness, especially in ancient climatically stable environments. Location: South Africa, which accommodates a range of biomes that differ strongly in species richness. Methods: We included measures of climatic, edaphic and biotic variables and their spatial heterogeneities in boosted regression tree models of vascular plant species richness. Species richness was assessed using herbarium records per quarter degree square (QDS). To avoid autocorrelation and problems of variable collection rates we iteratively randomly subsampled 20% of the available QDS. We also verified estimates of species richness using an independent data source. Results: The models predicted 68% of QDS species richness and 95% of biome richness. Spatial variability in diurnal temperature range was the strongest predictor of species richness, and inclusion of edaphic and biotic terms as well as spatial heterogeneities increased the explanatory power of the model considerably. Heterogeneity variables featured strongly (8 of 13) as predictors of species richness, but several resource variables (e.g. precipitation, seasonality and evapotranspiration) were also important. The spatial heterogeneities of some variables (e.g. water availability, fire) were related to their mean values, possibly explaining why some global models that have not explicitly included heterogeneity (other than topographic) perform well. Main conclusions: Environmental heterogeneities are important predictors of species richness, yielding accurate predictions even in the absence of any consideration of diversification rates or environmental stability. Greater heterogeneity of some resource variables when limiting, contributed to modelled species richness, adding to understanding of why species richness of some resource-poor Mediterranean-ecosystems is high. We suggest that species richness in ancient, climatically stable Mediterranean-ecosystems is contingent on resource and environmental heterogeneity that has enabled both the diversification and maintenance of regional species richness.

Aim To evaluate the role of seasonal and non‐seasonal productivity fluctuations in global patterns of species richness. Location Worldwide. Time period 2000–2017. Major taxa studied Amphibians, birds, mammals. Methods We analysed time series of monthly variation of the Normalized Difference Vegetation Index (NDVI), a surrogate of primary productivity, within c. 100 km × 100 km cells across all continents, estimating the mean, periodic seasonal variation and aperiodic unpredictable fluctuations of the NDVI in these cells. We then explored the relationships between mean NDVI and the components of its temporal variation and evaluated the independent effects of the above‐mentioned variables on species richness in the three vertebrate groups by means of variation partitioning. Results There is a hump‐shaped relationship between mean productivity and variation in productivity, so that temporal variation in productivity is lowest in regions with minimum and maximum values of mean productivity. Although mean productivity is a strong determinant of species richness, both seasonal and non‐seasonal productivity variation significantly affect the species richness of all studied taxa when accounting for mean productivity. However, the direction of these effects differs between regions differing in the mean productivity level. High variation in productivity has a negative effect on species richness in regions with moderate to high productivity levels, whereas species richness is higher in arid regions with high variation in productivity. Main conclusions Species richness is affected by temporal variation in productivity, but these effects differ regionally. In productive areas, high environmental stochasticity may increase population extinction rates, whereas arid regions probably benefit from resource fluctuations that promote species coexistence. Our results indicate that contemporary changes in patterns of temporal resource fluctuations may affect future global patterns of biological diversity on Earth.