Aim: It is widely accepted that biodiversity is influenced by both niche‐related and spatial processes from local to global scales. Their relative importance, however, is still disputed, and empirical tests are surprisingly scarce at the global scale. Here, we compare the importance of area (as a proxy for pure spatial processes) and environmental heterogeneity (as a proxy for niche‐related processes) for predicting native mammal species richness world‐wide and within biogeographical regions.Location: Global.Time period: We analyse a spatial snapshot of richness data collated by the International Union for Conservation of Nature.Major taxa studied: All terrestrial mammal species, including possibly extinct species and species with uncertain presence.Methods: We applied a spreading dye algorithm to analyse how native mammal species richness changes with area and environmental heterogeneity. As measures for environmental heterogeneity, we used elevation ranges and precipitation ranges, which are well‐known correlates of species richness.Results: We found that environmental heterogeneity explained species richness relationships better than did area, suggesting that niche‐related processes are more prevalent than pure area effects at broad scales.Main conclusions: Our results imply that niche‐related processes are essential to understand broad‐scale species–area relationships and that habitat diversity is more important than area alone for the protection of global biodiversity.

Manipulative experiments typically show a decrease in dryland biocrust cover and altered species composition under climate change. Biocrust‐forming lichens, such as the globally distributed Diploschistes diacapsis, are particularly affected and show a decrease in cover with simulated climate change. However, the underlying mechanisms are not fully understood, and long‐term interacting effects of different drivers are largely unknown due to the short‐term nature of the experimental studies conducted so far. We addressed this gap and successfully parameterised a process‐based model for D. diacapsis to quantify how changing atmospheric CO₂, temperature, rainfall amount and relative humidity affect its photosynthetic activity and cover. We also mimicked a long‐term manipulative climate change experiment to understand the mechanisms underlying observed patterns in the field. The model reproduced observed experimental findings: warming reduced lichen cover, whereas less rainfall had no effect on lichen performance. This warming effect was caused by the associated decrease in relative humidity and non‐rainfall water inputs, which are major water sources for biocrust‐forming lichens. Warming alone, however, increased cover because higher temperatures promoted photosynthesis during early morning hours with high lichen activity. When combined, climate variables showed non‐additive effects on lichen cover, and effects of increased CO₂ levelled off with decreasing levels of relative humidity. Synthesis. Our results show that a decrease in relative humidity, rather than an increase in temperature, may be the key factor for the survival of the lichen D. diacapsis under climate change and that effects of increased CO₂ levels might be offset by a reduction in non‐rainfall water inputs in the future. Because of a global trend towards warmer and drier air and the widespread global distribution of D. diacapsis, this will affect lichen‐dominated dryland biocrust communities and their role in regulating ecosystem functions worldwide.

The timing regimes of precipitation can exert profound impacts on grassland ecosystems. However, it is still unclear how the peak aboveground biomass (AGB_peak) of alpine grasslands responds to the temporal variability of growing season precipitation (GSP) on the northern Tibetan Plateau. Here, the temporal variability of precipitation was defined as the number and intensity of precipitation events as well as the time interval between consecutive precipitation events. We conducted annual field measurements of AGB_peak between 2009 and 2016 at four sites that were representative of alpine meadow, meadow-steppe, alpine steppe, and desert-steppe. Thus, an empirical model was established with the time series of the field-measured AGB_peak and the corresponding enhanced vegetation index (EVI) (R² = 0.78), which was used to estimate grassland AGB_peak at the regional scale. The relative importance of the three indices of the temporal variability of precipitation, events, intensity, and time interval on grassland AGB_peak was quantified by principal component regression and shown in a red–green–blue (RGB) composition map. The standardized importance values were used to calculate the vegetation sensitivity index to the temporal variability of precipitation (VSIP). Our results showed that the standardized VSIP was larger than 60 for only 15% of alpine grassland pixels and that AGB_peak did not change significantly for more than 60% of alpine grassland pixels over the past decades, which was likely due to the nonsignificant changes in the temporal variability of precipitation in most pixels. However, a U-shaped relationship was found between VSIP and GSP across the four representative grassland types, indicating that the sensitivity of grassland AGB_peak to precipitation was dependent on the types of grassland communities. Moreover, we found that the temporal variability of precipitation explained more of the field-measured AGB_peak variance than did the total amount of precipitation alone at the site scale, which implies that the mechanisms underlying how the temporal variability of precipitation controls the AGB_peak of alpine grasslands should be better understood at the local scale. We hypothesize that alpine grassland plants promptly respond to the temporal variability of precipitation to keep community biomass production more stable over time, but this conclusion should be further tested. Finally, we call for a long-term experimental study that includes multiple natural and anthropogenic factors together, such as warming, nitrogen deposition, and grazing and fencing, to better understand the mechanisms of alpine grassland stability on the Tibetan Plateau.