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Understanding the process of dryland degradation is crucial to combating desertification and maintaining land sustainability. To identify important indicators of dryland degradation, we conducted a field survey of 46 drylands spanning an aridity gradient across the Tibetan Plateau. Our random forest model suggested that soil sand content was the most important predictor of variation in soil fertility (carbon, nitrogen, and phosphorus). Most soil fertility showed a nonlinear and abrupt decline with increasing soil sand content, and displayed three sequential thresholds. First, soil organic carbon sharply decreased beyond a soil sand content threshold of 47%. Second, exceeding a subsequent threshold of 70%, the total nitrogen and light fraction carbon declined dramatically with increasing soil sand content. Finally, soil heavy fraction carbon, inorganic carbon, and total carbon were drastically reduced when the soil sand content exceeded 80%. The three soil fertility thresholds along the gradient of the soil sand content indicated a sequence of dryland degradation phases. Our findings provide an approach for detecting the severity of dryland degradation and suggest vulnerable areas of degradation on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Many uncertainties exist in our quest to understand and predict how terrestrial ecosystems will respond to climate change. A particularly challenging issue is how increases in extreme precipitation regimes, which are characterized by larger but fewer individual precipitation events, will impact ecosystems. Based on a wide-ranging review of empirical studies of both hydrological and ecological processes, Knapp et al. (2008) generated a suite of hypotheses positing how these processes would respond to an increase in extreme precipitation regimes and, from this, concluded that mesic ecosystems would be more detrimentally impacted than xeric ones. In this study we present the first thorough test of these hypotheses by examining how forest, shrubland, grassland and desert ecosystems of the Tibetan Plateau, having very different vegetation and climate characteristics, respond to more extreme rainfall regimes. We accomplished this by using a simulation model (Biome-BGC) to examine the integrated behavior of these ecosystems based on the simultaneous responses and interactions of 10 hydrological and ecological processes: runoff, canopy evaporation, soil evaporation, soil water storage, transpiration, net primary productivity, soil respiration, net ecosystem exchange, nitrogen [N] mineralization, and N leaching. We ran forty-year simulations (1986–2008) where we manipulated mean growing season precipitation to create more extreme intra-annual precipitation regimes characterized by lower precipitation frequencies, longer dry periods, and larger individual (daily) precipitation events. When compared to ambient conditions, our simulations showed that increases in extreme rainfall regimes (1) impacted all hydrological processes in mesic ecosystems, resulting in a reduction of soil mineral N due to increased leaching; and (2) enhanced plant growth in xeric ecosystems, leading to larger and denser canopies and higher light interception. The responses of hydrological processes tended to follow Knapp et al.’s hypotheses more so than ecological responses. Overall, responses of mesic ecosystems closely followed the hypotheses but xeric ecosystems were highly variable and only weakly consistent with them. Our findings provide new insights as to how more extreme rainfall regimes may potentially affect the functioning of terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

• Precipitation-lagged ecosystems in the Tibetan Plateau are more sensitive to biotic and environmental factors than unlagged ecosystems. • The precipitation regimes, instead of temperature and VPD, primarily drive the GPP variabilities in the Tibetan Plateau at the grid scale. • Precipitation might have a stronger impact on carbon uptake via variations in intra-distribution under future warming scenarios. Warming and precipitation variations have significant impacts on carbon uptake in the Tibetan Plateau. However, which climatic variable or process primarily drives the inter-annual variations of carbon uptake is not clear. Using multiple gross primary productivity (GPP) estimates, we study the controlling factors of the previous-year lagged effect and evaluate the effects of climate variables on GPP in the Tibetan Plateau. Results show that the lagged ecosystems in which productivity is significantly associated with previous-year precipitation are more sensitive to biotic and environmental factors than unlagged ones. In addition, previous-year precipitation as a whole has a positive impact on GPP over the Tibetan Plateau. Furthermore, precipitation regimes including precipitation intensity and dry-days fraction, and current-year precipitation amount primarily drive the GPP variabilities instead of temperature, vapor pressure deficit (VPD), and radiation at the grid scale. Future projections suggest that precipitation amount and intensity will increase, and dry-days fraction will decrease, which indicates that precipitation might have a more complicated impact on carbon uptake via variations in intra-distribution. Our study reveals the primary climatic factors that influence the variations of carbon uptake in the Tibetan Plateau, offering valuable insights for accurate carbon cycle modeling. [ABSTRACT FROM AUTHOR]