Biogeographic patterns and drivers of soil microbial diversity have been extensively studied in the past few decades. However, most research has focused on the topsoil, while the subsoil is assumed to have microbial diversity patterns similar to those of the topsoil. Here we compared patterns and drivers of microbial alpha and beta diversity in and between topsoils (0 to 10 cm) and subsoils (30 to 50 cm) of temperate grasslands in Inner Mongolia of China, covering an ∼1,500-km transect along an aridity gradient. Counter to the conventional assumption, we find contrasting biogeographic patterns of diversity and influencing factors for different bacterial and archaeal groups and between depths. While bacterial diversity remains constant or increases with increasing aridity in topsoil and decreases in subsoil, archaeal diversity decreases in topsoil and remains constant in subsoil. Microbial diversity in the topsoil is most strongly influenced by aboveground vegetation and contemporary climate but is most strongly influenced by the factor historical temperature anomaly since the Last Glacial Maximum (LGM) and by soil pH in the subsoil. Moreover, the biogeographic patterns of topsoil-subsoil community dissimilarities vary for different microbial groups and are overall most strongly influenced by soil fertility differences between depths for bacteria and by contemporary climate for archaea. These findings suggest that diversity patterns observed in the topsoil may not be readily applied to the subsoil horizons. For the subsoil in particular, historical climate plays a vital role in the spatial variation of bacterial diversity. Overall, our study provides novel information for understanding and predicting soil microbial diversity patterns at depth.IMPORTANCE Exploring the biogeographic patterns of soil microbial diversity is critical for understanding mechanisms underlying the response of soil processes to climate change. Using top- and subsoils from an ∼1,500-km temperate grassland transect, we find divergent patterns of microbial diversity and its determinants in the topsoil versus the subsoil. Furthermore, we find important and direct legacy effects of historical climate change on the microbial diversity of subsoil yet indirect effects on topsoil. Our findings challenge the conventional assumption of similar geographic patterns of soil microbial diversity along soil profiles and help to improve our understanding of how soil microbial communities may respond to future climate change in different regions with various climate histories.

The use of quantitative measures to select priority areas for conservation has been in practice since the early 1980s. However, the relative efficiency of different methods for identifying priority areas is still the subject of debate. Here, using the distribution data of 556 Rhododendron species in China with high spatial resolution, we evaluated the performance of the two commonly used methods, i.e. hotspot and complementarity and selected the efficient method to select priority areas for the conservation of Rhododendron in China. By overlaying the priority areas map with the locations of protected areas, we also identified the regions not covered by current protected areas (i.e. conservation gaps). We found that the complementarity method selected less number of grid cells to capture an equivalent number of species and hence had higher efficiency and representativeness than the commonly used hotspot method. Moreover, the complementarity method was better at capturing the range-restricted species than the hotspot method. Based on the complementarity method, we identified 61 grid cells of 50 × 50 km as priority areas for Rhododendron conservation in China. Among these priority areas, only about 50% grid cells were located in the hotspot areas (e.g. Hengduan Mountains), and 14% grid cells were outside the current protected area network. Our findings suggest that, despite its popularity and ease of implementation, the sites selected by hotspot algorithm may not necessarily be the best sites to allocate conservation efforts. Since the identification of priority areas in China has largely been based on the hotspot method, the current study has revived the need to reassess the priority areas for other taxonomic groups too. More importantly, our findings have emphasized the need to expand the conservation priorities from Hengduan Mountains to south and southeast China as well.

The means through which microbes and plants contribute to soil organic carbon (SOC) accumulation remain elusive due to challenges in disentangling the complex components of SOC. Here we use amino sugars and lignin phenols as tracers for microbial necromass and plant lignin components, respectively, and investigate their distribution in the surface soils across Mongolian grasslands in comparison with published data for other grassland soils of the world. While lignin phenols decrease, amino sugars increase with SOC contents in all examined grassland soils, providing continental-scale evidence for the key role of microbial necromass in SOC accumulation. Moreover, in contrast to clay’s control on amino sugar accumulation in fine-textured soils, aridity plays a central role in amino sugar accrual and lignin decomposition in the coarse-textured Mongolian soils. Hence, aridity shifts may have differential impacts on microbial-mediated SOC accumulation in grassland soils of varied textures.

Abstract Aim Is high diversity in tropical and subtropical mountains due to topographical complexity alone or a combination of topography and temperature seasonality? Here, we aim to assess the contribution of these two factors on Rhododendron diversity in China. Specifically, we evaluate how low temperature seasonality in subtropical China jointly with heterogeneous environment accounts for increased species diversity across montane landscapes relative to those of the more seasonal temperate zone in north China. Location China. Methods We compiled distributional data for all Rhododendron species in China and then estimated the species richness patterns of rare versus common species, and of shrubs versus trees at spatial resolutions of 50 × 50 km. Bivariate regressions were performed to evaluate the effects of environmental variables on species richness followed by stepwise regression to select the best set of predictors. Results The variables of habitat heterogeneity and climate seasonality were consistently the strongest predictors of species richness for all species groups, while the contribution of water and energy variables was proportionately much lower. Winter coldness had very low predictive power, which indicated that unlike other woody plants, the northward dispersal of Rhododendron is not limited by cold winter temperature. Main conclusions High Rhododendron diversity in south-west China appears to be influenced jointly by the climatic gradients induced by topographical complexity and temperature seasonality as suggested by Janzen's hypothesis. The increased topographical complexity in combination with low temperature seasonality in south-west China might have promoted species accumulation by offering more niche space, preventing extinction and providing increased opportunities for allopatric speciation. While our findings strongly indicate the effect of habitat heterogeneity on species diversity, they also suggest the role of seasonal uniformity of temperature for increased diversity towards the tropics. The effect of seasonality may, however, be more pronounced in plants because of their limited ability to use behaviour to avoid environmental influences.

Abstract Aim Understanding the evolution of the latitudinal diversity gradient (i.e. increase in species diversity towards the tropics) is a prominent issue in ecology and biogeography. Disentangling the relative contributions of environment and evolutionary history in shaping this gradient remains a major challenge because their relative importance has been found to vary across regions and taxa. Here, using the global distributions and a molecular phylogeny of Rhododendron, one of the largest genera of flowering plants, we aim to compare the relative contributions of contemporary environment, evolutionary time and diversification rates in generating extant species diversity patterns. Location Global. Time period Undefined. Major taxa studied Rhododendron. Methods We compiled the global distributions of all Rhododendron species, and constructed a dated molecular phylogeny using nine chloroplast genes and seven nuclear regions. By integrating these two datasets, we estimated the temporal trends of Rhododendron diversification, and explored the global patterns of its species diversity, net diversification rates, and species ages. Next, we reconstructed the geographical ancestral area of the clade. Finally, we compared the relative contribution of contemporary environment, time-for-speciation, and diversification rates on the species diversity pattern of Rhododendron. Results In contrast to the predictions of the time-for-speciation hypothesis, we found that although Rhododendron originated at a temperate latitude, its contemporary species diversity is highest in the tropics/subtropics, suggesting an into-the-tropics colonization for this genus. We found that the elevated diversification induced by heterogeneous environmental conditions in the tropics/subtropics shapes the global pattern of Rhododendron diversity. Main conclusions Our findings support tropical and subtropical mountains as not only biodiversity and endemism hotspots, but also as cradles for the diversification of Rhododendron. Our study emphasizes the need of unifying ecological and evolutionary approaches in order to gain comprehensive understanding of the mechanisms underlying the global patterns of plant diversity.

Soil carbon sequestration plays an important role in mitigating anthropogenic increases in atmospheric CO2 concentrations. Recent studies have shown that biodiversity increases soil organic carbon (SOC) storage in experimental grasslands. However, the effects of species diversity on SOC storage in natural ecosystems have rarely been studied, and the potential mechanisms are yet to be understood. The results presented here show that favorable climate conditions, particularly high precipitation, tend to increase both species richness and belowground biomass, which had a consistent positive effect on SOC storage in forests, shrublands, and grasslands. Nitrogen deposition and soil pH generally have a direct negative effect on SOC storage. Ecosystem management that maintains high levels of plant diversity can enhance SOC storage and other ecosystem services that depend on plant diversity.Despite evidence from experimental grasslands that plant diversity increases biomass production and soil organic carbon (SOC) storage, it remains unclear whether this is true in natural ecosystems, especially under climatic variations and human disturbances. Based on field observations from 6,098 forest, shrubland, and grassland sites across China and predictions from an integrative model combining multiple theories, we systematically examined the direct effects of climate, soils, and human impacts on SOC storage versus the indirect effects mediated by species richness (SR), aboveground net primary productivity (ANPP), and belowground biomass (BB). We found that favorable climates (high temperature and precipitation) had a consistent negative effect on SOC storage in forests and shrublands, but not in grasslands. Climate favorability, particularly high precipitation, was associated with both higher SR and higher BB, which had consistent positive effects on SOC storage, thus offsetting the direct negative effect of favorable climate on SOC. The indirect effects of climate on SOC storage depended on the relationships of SR with ANPP and BB, which were consistently positive in all biome types. In addition, human disturbance and soil pH had both direct and indirect effects on SOC storage, with the indirect effects mediated by changes in SR, ANPP, and BB. High soil pH had a consistently negative effect on SOC storage. Our findings have important implications for improving global carbon cycling models and ecosystem management: Maintaining high levels of diversity can enhance soil carbon sequestration and help sustain the benefits of plant diversity and productivity.

Abstract Aim We examined the effects of space, climate, phylogeny and species traits on module composition in a cross-biomes plant–hummingbird network. Location Brazil, except Amazonian region. Methods We compiled 31 local binary plant–hummingbird networks, combining them into one cross-biomes metanetwork. We conducted a modularity analysis and tested the relationship between species’ module membership with traits, geographical location, climatic conditions and range sizes, employing random forest models. We fitted reduced models containing groups of related variables (climatic, spatial, phylogenetic, traits) and combinations of groups to partition the variance explained by these sets into unique and shared components. Results The Brazilian cross-biomes network was composed of 479 plant and 42 hummingbird species, and showed significant modularity. The resulting six modules conformed well to vegetation domains. Only plant traits, not hummingbird traits, differed between modules, notably plants’ growth form, corolla length, flower shape and colour. Some modules included plant species with very restricted distributions, whereas others encompassed more widespread ones. Widespread hummingbirds were the most connected, both within and between modules, whereas widespread plants were the most connected between modules. Among traits, only nectar concentration had a weak effect on among-module connectivity. Main conclusions Climate and spatial filters were the main determinants of module composition for hummingbirds and plants, potentially related to resource seasonality, especially for hummingbirds. Historical dispersal-linked contingency, or environmental variations not accounted for by the explanatory factors here evaluated, could also contribute to the spatial component. Phylogeny and morphological traits had no unique effects on the assignment of species to modules. Widespread species showed higher within- and/or among-module connectivity, indicating their key role connecting biomes, and, in the case of hummingbirds, communities within biomes. Our results indicate that biogeography and climate not only determine the variation of modularity in local plant–animal networks, as previously shown, but also affect the cross-biomes network structure.

Evergreen broadleaved woody plants (EBWPs) are dominant components in forests and savanna of the global tropic and subtropic regions. Southern China possesses the largest continuous area of subtropical EBWPs distribution, harboring a high proportion of endemic species. Hotspot and gap analyses are effective methods for analyzing the spatial pattern of biodiversity and conservation and were used here for EBWPs in China. Based on a distribution data set of 6,265 EBWPs with a spatial resolution of 50 × 50 km, we measured diversity of EBWPs in China using four indices: species richness, corrected weighted endemism, relative phylogenetic diversity, and phylogenetic endemism. According to the results based on 10% threshold, 15.73% of China’s land area was identified as hotspots using at least one diversity index. Only 2.14% of China’s land area was identified as hotspots for EBWPs by all four metrics simultaneously. Most of the hotspots locate in southern mountains. Moreover, we found substantial conservation gaps for Chinese EBWPs. Only 25.43% of the hotspots are covered by existing nature reserves by more than 10% of their area. We suggest to promote the establishment and management of nature reserve system within the hotspot gaps.

AimsTopography has long been recognized as an important factor in shaping species distributions. Many studies revealed that species may show species–habitat associations. However, few studies investigate how species assemblages are associated with local habitats, and it still remains unclear how the community–habitat associations vary with species abundance class and life stage. In this study, we analyzed the community–habitat associations in a subtropical montane forest.MethodsThe fully mapped 25-ha (500×500 m) forest plot is located in Badagongshan Nature Reserve in Hunan Province, Central China. It was divided into 625 (20×20 m) quadrats. Habitat types were classified by multivariate regression tree analyses that cluster areas with similar species composition according to the topographic characteristics. Indicator species analysis was used to identify the most important species for structuring species assemblages. We also compared the community–habitat associations for two levels of species abundances (i.e. abundant and rare) and three different life stages (i.e. saplings, juveniles and adults), while accounting for sample size effects.Important FindingsThe Badagongshan plot was divided into five distinct habitat types, which explained 34.7% of the variance in tree species composition. Even with sample size taken into account, community–habitat associations for rare species were much weaker than those for abundant species. Also when accounting for sample size, very small differences were found in the variance explained by topography for the three life stages. Indicator species of habitat types were mainly abundant species, and nearly all adult stage indicator species were also indicators in juvenile and sapling stages. Our study manifested that topographical habitat filtering was important in shaping overall local species compositions. However, habitat filtering was not important in shaping rare species’ distributions in this forest. The community–habitat association patterns in this forest were mainly shaped by abundant species. In addition, during the transitions from saplings to juveniles, and from juveniles to adults, the relative importance of habitat filtering was very weak.

AimsThe aim of this guide is to provide practical help for ecologists who analyze data from biodiversity–ecosystem functioning experiments. Our approach differs from others in the use of least squares-based linear models (LMs) together with restricted maximum likelihood-based mixed models (MMs) for the analysis of hierarchical data. An original data set containing diameter and height of young trees grown in monocultures, 2- or 4-species mixtures under ambient light or shade is used as an example.MethodsStarting with a simple LM, basic features of model fitting and the subsequent analysis of variance (ANOVA) for significance tests are summarized. From this, more complex models are developed. We use the statistical software R for model fitting and to demonstrate similarities and complementarities between LMs and MMs. The formation of contrasts and the use of error (LMs) or random-effects (MMs) terms to account for hierarchical data structure in ANOVAs are explained.Important FindingsData from biodiversity experiments can be analyzed at the level of entire plant communities (plots) and plant individuals. The basic explanatory term is species composition, which can be divided into contrasts in many ways depending on specific biological hypotheses. Typically, these contrasts code for aspects of species richness or the presence of particular species. For significance tests in ANOVAs, contrast terms generally are compared with remaining variation of the explanatory terms from which they have been ‘carved out’. Once a final model has been selected, parameters (e.g. means or slopes for fixed-effects terms and variance components for error or random-effects terms) can be estimated to indicate the direction and size of effects.

Analyzing how climate change affects vegetation distribution is one of the central issues of global change ecology as this has important implications for the carbon budget of terrestrial vegetation. Mapping vegetation distribution under historical climate scenarios is essential for understanding the response of vegetation distribution to future climatic changes. The reconstructions of palaeovegetation based on pollen data provide a useful method to understand the relationship between climate and vegetation distribution. However, this method is limited in time and space. Here, using species distribution model (SDM) approaches, we explored the climatic determinants of contemporary vegetation distribution and reconstructed the distribution of Chinese vegetation during the Last Glacial Maximum (LGM, 18,000 14C yr BP) and Middle-Holocene (MH, 6000 14C yr BP). The dynamics of vegetation distribution since the LGM reconstructed by SDMs were largely consistent with those based on pollen data, suggesting that the SDM approach is a useful tool for studying historical vegetation dynamics and its response to climate change across time and space. Comparison between the modeled contemporary potential natural vegetation distribution and the observed contemporary distribution suggests that temperate deciduous forests, subtropical evergreen broadleaf forests, temperate deciduous shrublands and temperate steppe have low range fillings and are strongly influenced by human activities. In general, the Tibetan Plateau, North and Northeast China, and the areas near the 30°N in Central and Southeast China appeared to have experienced the highest turnover in vegetation due to climate change from the LGM to the present.