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Abstract Microbes are the drivers of soil phosphorus (P) cycling in terrestrial ecosystems; however, the role of soil microbes in mediating P cycling in P‐rich soils during primary succession remains uncertain. This study examined the impacts of bacterial community structure (diversity and composition) and its functional potential (absolute abundances of P‐cycling functional genes) on soil P cycling along a 130‐year glacial chronosequence on the eastern Tibetan Plateau. Bacterial community structure was a better predictor of soil P fractions than P‐cycling genes along the chronosequence. After glacier retreat, the solubilization of inorganic P and the mineralization of organic P were significantly enhanced by increased bacterial diversity, changed interspecific interactions, and abundant species involved in soil P mineralization, thereby increasing P availability. Although 84% of P‐cycling genes were associated with organic P mineralization, these genes were more closely associated with soil organic carbon than with organic P. Bacterial carbon demand probably determined soil P turnover, indicating the dominant role of organic matter decomposition processes in P‐rich alpine soils. Moreover, the significant decrease in the complexity of the bacterial co‐occurrence network and the taxa‐gene‐P network at the later stage indicates a declining dominance of the bacterial community in driving soil P cycling with succession. Our results reveal that bacteria with a complex community structure have a prominent potential for biogeochemical P cycling in P‐rich soils during the early stages of primary succession. 

Abstract Microbial carbon (C) use efficiency (CUE) delineates the proportion of organic C used by microorganisms for anabolism and ultimately influences the amount of C sequestered in soils. However, the key factors controlling CUE remain enigmatic, leading to considerable uncertainty in understanding soil C retention and predicting its responses to global change factors. Here, we investigate the global patterns of CUE estimate by stoichiometric modeling in surface soils of natural ecosystems, and examine its associations with temperature, precipitation, plant‐derived C and soil nutrient availability. We found that CUE is determined by the most limiting resource among these four basic environmental resources within specific climate zones (i.e., tropical, temperate, arid, and cold zones). Higher CUE is common in arid and cold zones and corresponds to limitations in temperature, water, and plant‐derived C input, while lower CUE is observed in tropical and temperate zones with widespread limitation of nutrients (e.g., nitrogen or phosphorus) in soil. The contrasting resource limitations among climate zones led to an apparent increase in CUE with increasing latitude. The resource‐specific dependence of CUE implies that soils in high latitudes with arid and cold environments may retain less organic C in the future, as warming and increased precipitation can reduce CUE. In contrast, oligotrophic soils in low latitudes may increase organic C retention, as CUE could be increased with concurrent anthropogenic nutrient inputs. The findings underscore the importance of resource limitations for CUE and suggest asymmetric responses of organic C retention in soils across latitudes to global change factors. 

Abstract Decomposition is the transformation of dead organic matter into its inorganic constituents. In most biomes, decomposition rates can be accurately predicted with simple mathematical models, but these models have long under‐predicted decomposition in globally extensive drylands.We posit that the exposed surface conditions characteristic of drylands make litter decomposition uniquely subject to microsite‐specific environmental controls and spatially variable microbial communities. As such, decomposition in dryland ecosystems—which are characterized by extremes in temporal heterogeneity of climate conditions and spatial heterogeneity of vegetation cover with corresponding microclimate variability—is a prime example of a macrosystems process that can be addressed by merging field data with new predictive process models operating across a hierarchical continuum of spatial scales and process resolutions.A macrosystems approach offers promise to reconcile model‐measurement discrepancies by integrating observations and experiments across multiple scales, from microsites (e.g. shrub sub‐canopy or intercanopy) to regions (e.g. across a 100s of km²study site with complex topography, precipitation and temperature) and ultimately to a continental perspective (e.g. North American drylands).Recent developments in technology and data availability position the scientific community to integrate laboratory, field, modelling and remote sensing approaches across a hierarchical range of scales to capture the spatiotemporal distribution of litter and environmental conditions needed to predict decay dynamics at the micro‐to‐macroscale. This multi‐scale approach promises a path forward to resolving a longstanding disconnect between measured data and modelled processes in dryland litter decomposition.Dryland litter decomposition presents an excellent case study for resolving spatially and temporally complex biogeochemical dynamics through a hierarchical, multidisciplinary macrosystems approach.We focus on dryland litter decomposition, but the hierarchical, multidisciplinary macrosystems approach we outline shows great potential for resolving other spatially and temporally complex biogeochemical processes across a wide range of ecosystems. Read the freePlain Language Summaryfor this article on the Journal blog.