The respiratory release of carbon dioxide (CO2) from soil is a major yet poorly understood flux in the global carbon cycle. Climatic warming is hypothesized to increase rates of soil respiration, potentially fueling further increases in global temperatures. However, despite considerable scientific attention in recent decades, the overall response of soil respiration to anticipated climatic warming remains unclear. We synthesize the largest global dataset to date of soil respiration, moisture, and temperature measurements, totaling >3,800 observations representing 27 temperature manipulation studies, spanning nine biomes and over 2 decades of warming. Our analysis reveals no significant differences in the temperature sensitivity of soil respiration between control and warmed plots in all biomes, with the exception of deserts and boreal forests. Thus, our data provide limited evidence of acclimation of soil respiration to experimental warming in several major biome types, contrary to the results from multiple single-site studies. Moreover, across all nondesert biomes, respiration rates with and without experimental warming follow a Gaussian response, increasing with soil temperature up to a threshold of ∼25 °C, above which respiration rates decrease with further increases in temperature. This consistent decrease in temperature sensitivity at higher temperatures demonstrates that rising global temperatures may result in regionally variable responses in soil respiration, with colder climates being considerably more responsive to increased ambient temperatures compared with warmer regions. Our analysis adds a unique cross-biome perspective on the temperature response of soil respiration, information critical to improving our mechanistic understanding of how soil carbon dynamics change with climatic warming.

As communities and populations become increasingly fragmented, much theoretical and some empirical research has focused on the dynamics of metapopulations. Many metapopulation models describe dynamics among populations in a region, yet the scale of the ''region'' to which different models apply often is undefined. Because the spatial scale is undefined, testing predictions and assumptions of these models is problematic. Our goal is to present two scaling concepts relevant to these models, distance scaling and organismal scaling, and to apply these scaling notions to patterns of species distribution. To determine distance effects, we analyzed patterns of distribution of four taxonomic groups in tallgrass prairie (grasshoppers, small mammals, vascular plants, and breeding birds) at two spatial scales. To assess organismal effects, we held spatial scale constant and we compared patterns of distribution and abundance among these taxonomic groups.Using long-term data from Konza Prairie, Kansas, there were significant differences in the pattern of distribution of grasshoppers, small mammals, vascular plants, and breeding birds within a single spatial scale. The number of core species (species occupying Ͼ90% of the sites in a region) of plants and birds was less than the number of satellite species (those occupying Ͻ10% of the sites in a region). The opposite was true for grasshoppers and small mammals. All four distribution patterns were significantly nonrandom, but only grasshoppers and small mammals were significantly bimodal at this scale. Plants and birds were unimodal. The patterns of distribution within these taxonomic groups at two spatial scales were significantly different as well. In all cases, the percentage of species in the core group declined, and the percentage of species in the satellite group increased as spatial scale increased. These results demonstrate the difficulty of testing theoretical models with only one taxonomic group at a single spatial scale. One should not accept or reject a model until the spatial domains of organismal and distance scaling have been properly evaluated.

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Ecology has emerged as a global science, and there is a pressing need to identify ecological rules – general principles that will improve its predictive capability for scientists and its usefulness for managers and policy makers. Ideally, the generality and limits of these ecological rules should be assessed using extensive, coordinated experiments that ensure consistency in design and comparability of data. To improve the design of these large‐scale efforts, existing data should be used to test prospective ecological rules and to identify their limits and contingencies. As an example of this approach, we describe prospective rules for grassland responses to fire and rainfall gradients, identified from long‐term studies of North American grasslands and tested with existing data from long‐term experiments in South African savanna grasslands. Analyses indicated consistent effects of fire on the abundance of the dominant (grasses) and subdominant (forbs) flora on both continents, but no common response of grass or forb abundance across a rainfall gradient. Such analyses can inform future research designs to refine and more explicitly test ecological rules.

Extreme drought decreases aboveground net primary production (ANPP) in most grasslands, but the magnitude of ANPP reductions varies especially in C3‐dominated grasslands. Because the mechanisms underlying such differential ecosystem responses to drought are not well resolved, we experimentally imposed an extreme 4‐yr drought (2015–2018) in two C3 grasslands that differed in aridity. These sites had similar annual precipitation and dominant grass species (Leymus chinensis) but different annual temperatures and thus water availability. Drought treatments differentially affected these two semiarid grasslands, with ANPP of the drier site reduced more than at the wetter site. Structural equation modeling revealed that community‐weighted means for some traits modified relationships between soil moisture and ANPP, often due to intraspecific variation. Specifically, drought reduced community mean plant height at both sites, resulting in a reduction in ANPP beyond that attributable to reduced soil moisture alone. Higher community mean leaf carbon content enhanced the negative effects of drought on ANPP at the drier site, and ANPP–soil‐moisture relationships were influenced by soil C:N ratio at the wetter site. Importantly, neither species richness nor functional dispersion were significantly correlated with ANPP at either site. Overall, as expected, soil moisture was a dominant, direct driver of ANPP response to drought, but differential sensitivity to drought in these two grasslands was also related to soil fertility and plant traits.

Biodiversity can stabilise productivity through different mechanisms, such as asynchronous species responses to environmental variability and species stability. Global changes, like intensified drought, could negatively affect species richness, species asynchrony and species stability, but it is unclear how changes in these mechanisms will affect the stability of above‐ground primary productivity (ANPP) across ecosystems. We studied the effects of a 4‐year extreme drought on ANPP stability and the underlying mechanisms (species richness, species asynchrony and species stability) across six grasslands in Northern China. We also assessed the relative importance of these mechanisms in determining ANPP stability under extreme drought. We found that extreme drought decreased ANPP stability, species richness, species asynchrony and species stability across the six grasslands. However, structural equation modelling revealed that species asynchrony, not species richness or species stability, was the most important mechanism promoting stability of ANPP, regardless of drought across the six grasslands. Synthesis. Our results suggest that species asynchrony, not species richness and species stability, consistently buffers ecosystem stability against extreme drought across and within grasslands spanning a broad precipitation gradient. Thus, species asynchrony may be a more general mechanism for promoting stability of ANPP in grasslands in the face of intensified drought.

As communities and populations become increasingly fragmented, much theoretical and some empirical research has focused on the dynamics of metapopulations. Many metapopulation models describe dynamics among populations in a region, yet the scale of the region to which different models apply often is undefined. Because the spatial scale is undefined, testing predictions and assumptions of these models is problematic. Our goal is to present two scaling concepts relevant to these models, distance scaling and organismal scaling, and to apply these scaling notions to patterns of species distribution. To determine distance effects, we analyzed patterns of distribution of four taxonomic groups in tallgrass prairie (grasshoppers, small mammals, vascular plants, and breeding birds) at two spatial scales. To asses organismal effects, we held spatial scale constant and we compared patterns of distribution and abundance among these taxonomic groups. Using long—term data from Konza Prairie, Kansas, there were significant differences in the pattern of distribution of grasshoppers, small mammals, vascular plants, and breeding birds within a single spatial scale. The number of core species (species occupying >90% of the sites in a region) of plants and birds was less than the number of satellite species (those occupying <10% of the sites in a region). The opposite was true for grasshoppers and small mammals. All four distribution patterns were significantly nonrandom, but only grasshoppers and small mammals were significantly bimodal at this scale. Plants and birds were unimodal. The patterns of distribution within these taxonomic groups at two spatial scales were significantly different as well. In all cases, the percentage of species in the core group declined, and the percentage of species in the satellite group increased as spatial scale increased. These results demonstrate the difficulty of testing theoretical models with only one taxonomic group at a single spatial scale. One should not accept or reject a model until the spatial domains of organismal and distance scaling have been properly evaluated. As communities and populations become increasingly fragmented, much theoretical and some empirical research has focused on the dynamics of metapopulations. Many metapopulation models describe dynamics among populations in a region, yet the scale of the “region” to which different models apply often is undefined. Because the spatial scale is undefined, testing predictions and assumptions of these models is problematic. Our goal is to present two scaling concepts relevant to these models, distance scaling and organismal scaling, and to apply these scaling notions to patterns of species distribution. To determine distance effects, we analyzed patterns of distribution of four taxonomic groups in tallgrass prairie (grasshoppers, small mammals, vascular plants, and breeding birds) at two spatial scales. To assess organismal effects, we held spatial scale constant and we compared patterns of distribution and abundance among these taxo...