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Leaf water potential regulation is a key process in whole plant and ecosystem functioning. While low water potentials induced by open stomata may initially be associated with greater CO 2 supply and a higher water flux from the rhizosphere to the canopy, they also inhibit cell growth, photosynthesis and ultimately water supply. Here, we show that plants regulate their leaf water potential in an optimal manner under given constraints using a simple leaf water status regulation model and data from a global dryland leaf water potential database. Model predictions agree strongly with observations across locations and species and are further supported by experimental data. Leaf water potentials non-linearly decline with soil water potential, underlining the shift from maximizing water supply to avoiding stress with declining water availability. Our results suggest that optimal regulation of the leaf water status under varying water supply and stress tolerance is a ubiquitous property of plants in drylands. The proposed model moreover provides a novel quantitative framework describing how plants respond to short- and long-term changes in water availability and may help elaborating models of plant and ecosystem functioning.

Drylands cover 40% of the global terrestrial surface and provide important ecosystem services. While drylands as a whole are expected to increase in extent and aridity in coming decades, temperature and precipitation forecasts vary by latitude and geographic region suggesting different trajectories for tropical, subtropical, and temperate drylands. Uncertainty in the future of tropical and subtropical drylands is well constrained, whereas soil moisture and ecological droughts, which drive vegetation productivity and composition, remain poorly understood in temperate drylands. Here we show that, over the twenty first century, temperate drylands may contract by a third, primarily converting to subtropical drylands, and that deep soil layers could be increasingly dry during the growing season. These changes imply major shifts in vegetation and ecosystem service delivery. Our results illustrate the importance of appropriate drought measures and, as a global study that focuses on temperate drylands, highlight a distinct fate for these highly populated areas. Future stress on water resources, and on temperate drylands in particular, remains uncertain. Here, the authors show that climate in the late twenty first century may reduce the extent of temperate drylands, dry deep soils, and create intra-regional and intercontinental differences in ecological drought.

The distribution of rainfed agriculture, which accounts for approximately ¾ of global croplands, is expected to respond to climate change and human population growth and these responses may be especially pronounced in water limited areas. Because the environmental conditions that support rainfed agriculture are determined by climate, weather, and soil conditions that affect overall and transient water availability, predicting this response has proven difficult, especially in temperate regions that support much of the world’s agriculture. Here, we show that suitability to support rainfed agriculture in temperate dryland climates can be effectively represented by just two daily environmental variables: moist soils with warm conditions increase suitability while extreme high temperatures decrease suitability. 21 st century projections based on daily ecohydrological modeling of downscaled climate forecasts indicate overall increases in the area suitable for rainfed agriculture in temperate dryland regions, especially at high latitudes. The regional exception to this trend was Europe, where suitability in temperate dryland portions will decline substantially. These results clarify how rising temperatures interact with other key drivers of moisture availability to determine the sustainability of rainfed agriculture and help policymakers, resource managers, and the agriculture industry anticipate shifts in areas suitable for rainfed cultivation.

1. Sustainable land use under climate change requires detailed knowledge of the system dynamics. This applies particularly for the management of domestic livestock in semi-arid and arid grazing systems, where the risk of degradation is high and likely climate change may have a strong impact. A suitable way to assess potential future trends of these complex systems is through the application of simulation models. 2. We reviewed 41 models published between 1995 and 2005 simulating semi-arid and arid livestock grazing systems. The models were categorized according to the model aim and type, their temporal and spatial scale, and several indicators of model complexity. Additionally, we developed a list of model requirements for adequately simulating the effects of climate change. Based on these requirements, we evaluated the potential of current models to simulate impacts of climate change and determine important shortcomings. 3. Three general model types could be distinguished, namely state and transition, difference and differential equation, and rule-based models. Over time, we found that the number of models aiming to improve management strategies increased, while there were fewer models that aimed to understand system dynamics. This was accompanied by a trend to simplify model descriptions of hydrological relationships. 4. Important shortcomings of current models included the impact of increased CO₂ levels on plant productivity and the ability to resolve changes in intra-annual precipitation patterns. The consideration of both external drivers is crucial under climate change, hence sustainable long-term decision making is currently lacking important information. 5. Synthesis and applications. Sustainable livestock management in semi-arid and arid systems requires knowledge about effects of future climate change to adjust livestock density adequately. Producers' experiences from current weather conditions are not necessarily transferable to future conditions, thus models could help to support management. However, an analysis of current models has shown that few existing models are able to assess the impacts of the predicted climate change. Therefore, we call for the development of new dynamic grazing models that provide land managers with the necessary tools to face the threat of future climate changes.

Earth's life-support systems are in flux, yet no centralized system to monitor and report these changes exists. Recognizing this, 77 nations agreed to establish the Group on Earth Observations (GEO). The GEO Biodiversity Observation Network (GEO BON) integrates existing data streams into one platform in order to provide a more complete picture of Earth's biological and social systems. We present a conceptual framework envisioned by the GEO BON Ecosystem Services Working Group, designed to integrate national statistics, numerical models, remote sensing, and in situ measurements to regularly track changes in ecosystem services across the globe. This information will serve diverse applications, including stimulating new research and providing the basis for assessments. Although many ecosystem services are not currently measured, others are ripe for reporting. We propose a framework that will continue to grow and inspire more complete observation and assessments of our planet's life-support systems.

The timing regimes of precipitation can exert profound impacts on grassland ecosystems. However, it is still unclear how the peak aboveground biomass (AGBpeak) 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 AGBpeak 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 AGBpeak and the corresponding enhanced vegetation index (EVI) (R2 = 0.78), which was used to estimate grassland AGBpeak at the regional scale. The relative importance of the three indices of the temporal variability of precipitation, events, intensity, and time interval on grassland AGBpeak 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 AGBpeak 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 AGBpeak 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 AGBpeak 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 AGBpeak 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.

Grassland biodiversity is vulnerable to land use change. How to best manage semi-natural grasslands for maintaining biodiversity is still unclear in many cases because land-use processes may depend on environmental conditions and the indirect effects of land-use on biodiversity mediated by altered abiotic and biotic factors are rarely considered. Here we evaluate the relative importance of the direct and indirect effects of grazing intensity on plant communities along an elevational gradient on a large topographic scale in the Eastern Carpathians in Ukraine. We sampled for two years 31 semi-natural grasslands exposed to cattle grazing. Within each grassland site we measured plant community properties such as the number of species, functional groups, and the proportion of species undesirable for grazing. In addition, we recorded cattle density (as a proxy for grazing intensity), soil properties (bare soil exposure, soil organic carbon, and soil pH) and densities of soil decomposers (earthworms and soil microorganisms). We used structural equation modelling to explore the direct and indirect effects of grazing intensity on plant communities along the elevation gradient. We found that cattle density decreased plant species and functional diversity but increased the proportion of undesirable species. Some of these effects were directly linked to grazing intensity (i.e., species richness), while others (i.e., functional diversity and proportion of undesirable species) were mediated via bare soil exposure. Although grazing intensity decreased with elevation, the effects of grazing on the plant community did not change along the elevation gradient. Generally, elevation had a strong positive direct effect on plant species richness as well as a negative indirect effect, mediated via altered soil acidity and decreased decomposer density. Our results indicate that plant diversity and composition are controlled by the complex interplay among grazing intensity and changing environmental conditions along an elevation gradient. Furthermore, we found lower soil pH, organic carbon and decomposer density with elevation, indicating that the effects of grazing on soil and related ecosystem functions and services in semi-natural grasslands may be more pronounced with elevation. This demonstrates that we need to account for environmental gradients when attempting to generalize effects of land-use intensity on biodiversity.

The continuing loss of global biodiversity has raised questions about the risk that species extinctions pose for the functioning of natural ecosystems and the services that they provide for human wellbeing. There is consensus that, on single trophic levels, biodiversity sustains functions; however, to understand the full range of biodiversity effects, a holistic and multitrophic perspective is needed. Here, we apply methods from ecosystem ecology that quantify the structure and dynamics of the trophic network using ecosystem energetics to data from a large grassland biodiversity experiment. We show that higher plant diversity leads to more energy stored, greater energy flow and higher community-energy-use efficiency across the entire trophic network. These effects of biodiversity on energy dynamics were not restricted to only plants but were also expressed by other trophic groups and, to a similar degree, in aboveground and belowground parts of the ecosystem, even though plants are by far the dominating group in the system. The positive effects of biodiversity on one trophic level were not counteracted by the negative effects on adjacent levels. Trophic levels jointly increased the performance of the community, indicating ecosystem-wide multitrophic complementarity, which is potentially an important prerequisite for the provisioning of ecosystem services. Applying the concept of ecosystem energetics to a grassland biodiversity experiment, the authors show that the storage and flow of energy across the whole trophic network, both above- and belowground, becomes more efficient as plant diversity increases.

Climate models predict the further intensification of global warming in the future. Drylands, as one of the most fragile ecosystems, are vulnerable to changes in temperature, precipitation, and drought extremes. However, it is still unclear how plant traits interact with soil properties to regulate drylands’ responses to seasonal and interannual climate change. The vegetation sensitivity index (VSI) of desert scrubs in the Qaidam Basin (NE Tibetan Plateau) was assessed by summarizing the relative contributions of temperature (SGST), precipitation (SGSP), and drought (temperature vegetation dryness index, STVDI) to the dynamics of the normalized difference vegetation index (NDVI) during plant growing months yearly from 2000 to 2015. Nutrient contents, including carbon, nitrogen, phosphorus, and potassium in topsoils and leaves of plants, were measured for seven types of desert scrub communities at 22 sites in the summer of 2016. Multiple linear and structural equation models were used to reveal how leaf and soil nutrient regimes affect desert scrubs’ sensitivity to climate variability. The results showed that total soil nitrogen (STN) and leaf carbon content (LC), respectively, explained 25.9% and 17.0% of the VSI variance across different scrub communities. Structural equation modeling (SEM) revealed that STN and total soil potassium (STK) mediated desert scrub’s VSI indirectly via SGST (with standardized path strength of −0.35 and +0.32, respectively) while LC indirectly via SGST and SGSP (with standardized path strength of −0.31 and −0.19, respectively). Neither soil nor leave nutrient contents alone could explain the VSI variance across different sites, except for the indirect influences of STN and STK via STVDI (−0.18 and 0.16, respectively). Overall, this study disentangled the relative importance of plant nutrient traits and soil nutrient availability in mediating the climatic sensitivity of desert scrubs in the Tibetan Plateau. Integrating soil nutrient availability with plant functional traits together is recommended to better understand the mechanisms behind dryland dynamics under global climate change.

Vegetation productivity is an essential variable in ecosystem functioning. Vegetation dynamics of dryland ecosystems are most strongly determined by water availability and consequently by rainfall and there is a need to better understand how water limited ecosystems respond to altered rainfall amounts and variability. This response is partly determined by the vegetation functional response to rainfall (β) approximated by the unit change in annual vegetation productivity per unit change in annual rainfall. Here, we show how this functional response from 1983 to 2011 is affected by below and above average rainfall in two arid to semi-arid subtropical regions in West Africa (WA) and South West Africa (SWA) differing in interannual variability of annual rainfall (higher in SWA, lower in WA). We used a novel approach, shifting linear regression models (SLRs), to estimate gridded time series of β. The SLRs ingest annual satellite based rainfall as the explanatory variable and annual satellite-derived vegetation productivity proxies (NDVI) as the response variable. Gridded β values form unimodal curves along gradients of mean annual precipitation in both regions. β is higher in SWA during periods of below average rainfall (compared to above average) for mean annual precipitation <600 mm. In WA, β is hardly affected by above or below average rainfall conditions. Results suggest that this higher β variability in SWA is related to the higher rainfall variability in this region. Vegetation type-specific β follows observed responses for each region along rainfall gradients leading to region-specific responses for each vegetation type. We conclude that higher interannual rainfall variability might favour a more dynamic vegetation response to rainfall. This in turn may enhance the capability of vegetation productivity of arid and semi-arid regions to better cope with periods of below average rainfall conditions.