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The allocation and stoichiometry of plant nutrients in leaves reflect fundamental ecosystem processes, biotic interactions, and environmental drivers such as water availability. Climate change will lead to increases in drought severity and frequency, but how canopy nutrients will respond to drought, and how these responses may vary with community composition along aridity gradients is poorly understood. We experimentally addressed this issue by reducing precipitation amounts by 66% during two consecutive growing seasons at three sites located along a natural aridity gradient. This allowed us to assess drought effects on canopy nitrogen (N) and phosphorus (P) concentrations in arid and semiarid grasslands of northern China. Along the aridity gradient, canopy nutrient concentrations were positively related to aridity, with this pattern was driven primarily by species turnover (i.e., an increase in the relative biomass of N- and P-rich species with increasing aridity). In contrast, drought imposed experimentally increased N but decreased P concentrations in plant canopies. These changes were driven by the combined effects of species turnover and intraspecific variation in leaf nutrient concentrations. In addition, the sensitivity of canopy N and P concentrations to drought varied across the three sites. Canopy nutrient concentrations were less affected by drought at drier than wetter sites, because of the opposing effects of species turnover and intraspecific variation, as well as greater drought tolerance for nutrient-rich species. These contrasting effects of long-term aridity vs. short-term drought on canopy nutrient concentrations, as well as differing sensitivities among sites in the same grassland biome, highlight the challenge of predicting ecosystem responses to future climate change.

Drylands, comprising land regions characterized by water-limited, sparse vegetation, have commonly been projected to expand globally under climate warming. Such projections, however, rely on an atmospheric proxy for drylands, the aridity index, which has recently been shown to yield qualitatively incorrect projections of various components of the terrestrial water cycle. Here, we use an alternative index of drylands, based directly on relevant ecohydrological variables, and compare projections of both indices in Coupled Model Intercomparison Project Phase 5 climate models as well as Dynamic Global Vegetation Models. The aridity index overestimates simulated ecohydrological index changes. This divergence reflects different index sensitivities to hydroclimate change and opposite responses to the physiological effect on vegetation of increasing atmospheric CO2. Atmospheric aridity is thus not an accurate proxy of the future extent of drylands. Despite greater uncertainties than in atmospheric projections, climate model ecohydrological projections indicate no global drylands expansion under greenhouse warming, contrary to previous claims based on atmospheric aridity.Model projections of future drylands distribution using a proxy based on atmospheric aridity show expansion under climate change, but may not be an accurate representation. An alternative index based on ecohydrological variables such as water limitation shows no global expansion of drylands.

The exchange of carbon between soil organic carbon (SOC) and the atmosphere affects the climate 1 , 2 and—because of the importance of organic matter to soil fertility—agricultural productivity 3 . The dynamics of topsoil carbon has been relatively well quantified 4 , but half of the soil carbon is located in deeper soil layers (below 30 centimetres) 5 – 7 , and many questions remain regarding the exchange of this deep carbon with the atmosphere 8 . This knowledge gap restricts soil carbon management policies and limits global carbon models 1 , 9 , 10 . Here we quantify the recent incorporation of atmosphere-derived carbon atoms into whole-soil profiles, through a meta-analysis of changes in stable carbon isotope signatures at 112 grassland, forest and cropland sites, across different climatic zones, from 1965 to 2015. We find, in agreement with previous work 5 , 6 , that soil at a depth of 30–100 centimetres beneath the surface (the subsoil) contains on average 47 per cent of the topmost metre’s SOC stocks. However, we show that this subsoil accounts for just 19 per cent of the SOC that has been recently incorporated (within the past 50 years) into the topmost metre. Globally, the median depth of recent carbon incorporation into mineral soil is 10 centimetres. Variations in the relative allocation of carbon to deep soil layers are better explained by the aridity index than by mean annual temperature. Land use for crops reduces the incorporation of carbon into the soil surface layer, but not into deeper layers. Our results suggest that SOC dynamics and its responses to climatic control or land use are strongly dependent on soil depth. We propose that using multilayer soil modules in global carbon models, tested with our data, could help to improve our understanding of soil–atmosphere carbon exchange. This study of whole-soil carbon dynamics finds that, of the atmospheric carbon that is incorporated into the topmost metre of soil over 50 years, just 19 per cent reaches the subsoil, in a manner that depends on land use and aridity.

In this study, the aridity index (AI) based on gridded climate data was validated for defining aridity and classifying aridity zones in Iraq through comparison with the results obtained by the station-based aridity index. Gauge-based gridded climate data taken from Climatic Research Unit Timeseries (CRU TS) were used to determine the annual value of four aridity indices (Lang, De Martonne, Ernic and UNEP AI) over the period 1998-2011. The results showed that the aridity distribution maps derived using grid-based aridity indices were reasonably close to those found using station-based ones. The four aridity indices properly identified similar aridity (dryness) classifications in both the station-based and grid-based aridity maps. The area percentage of each aridity class predicted by grid-based AIs was also compared with that obtained by the station-based AIs. The results showed that the variances between the area percentages predicted by grid-based AIs and those estimated using station-based AIs are fairly slight. The Lang AI exhibited the least variance (0.4%) while the De Martonne AI had the biggest variance (-4.8%). Despite these minor variances, it is however possible to conclude that the grid-based aridity index classified the aridity zones of Iraq as properly as the station-based aridity index did.

The paper is devoted to simulation modelling of the arid plant communities (APC) behaviour. Such systems belong to the class of agroecological systems and include a large number of interacting natural factors that contribute to the system’s degradation. We propose a model of APC behaviour based on a weighted oriented graph. The values of weights and other coefficients reflecting the exposure of factors and their mutual relationship are acquired by expert assessments. The proposed model allows predicting the behaviour of APC in response to various biogenic control actions.

Recent observations suggest that repeated fires could drive Mediterranean forests to shrublands, hosting flammable vegetation that regrows quickly after fire. This feedback supposedly favours shrubland persistence and may be strengthened in the future by predicted increased aridity. An assessment was made of how fires and aridity in combination modulated the dynamics of Mediterranean ecosystems and whether the feedback could be strong enough to maintain shrubland as an alternative stable state to forest. A model was developed for vegetation dynamics, including stochastic fires and different plant fire‐responses. Parameters were calibrated using observational data from a period up to 100 yr ago, from 77 sites with and without fires in Southeast Spain and Southern France. The forest state was resilient to the separate impact of fires and increased aridity. However, water stress could convert forests into open shrublands by hampering post‐fire recovery, with a possible tipping point at intermediate aridity. Projected increases in aridity may reduce the resilience of Mediterranean forests against fires and drive post‐fire ecosystem dynamics toward open shrubland. The main effect of increased aridity is the limitation of post‐fire recovery. Including plant fire‐responses is thus fundamental when modelling the fate of Mediterranean‐type vegetation under climate‐change scenarios.

1. The fast-slow plant economics spectrum predicts that because of evolutionary and biophysical constraints, different plant organs must be coordinated to converge in a unique ecological strategy within a continuum that shifts from fast to slow resource acquisition and conservation. Therefore, along a gradient of aridity, taxa with different strategies will be expected to be successful because selection pressures for slow resource acquisition become stronger as the environment becomes drier. In extremely arid and seasonal environments, however, a slow strategy may become disadvantageous because slow traits are costly to maintain. Additionally, as the availability of water decreases, selection pressures increase, reducing the variation in ecological strategies. 2. Using shrub assemblages along an aridity gradient in the Atacama Desert, we test the hypothesis that selection pressures imposed by hyper-aridity act simultaneously on the variation and coordination of trait attributes, leading to an inverse pattern in the fast-slow plant economics spectrum, where strategies shift from slow to fast as the environment becomes drier. 3. We established 20-22 plots at each of four sites along the gradient to estimate plant community structure and functional variation. For all species recorded, we quantified a set of leaf, stem, and root traits. 4. Results revealed an inverse pattern of the fast-slow economics spectrum for leaf and stem traits, but not for root traits; that is, as aridity further increased, aboveground traits exhibited a shift from a slow to a fast strategy with some level of coordination. Below-ground traits, however, did not shift accordingly with our prediction, rather they showed more complex pattern of shift and coordination with above-ground traits along the gradient. We also found that trait variation showed an idiosyncratic pattern of variation along the gradient, indicating that ecological strategies are driven by local processes within sites. 5. Synthesis. Our results increase our understanding of the fast-slow plant econom-ics spectrum by showing that environmental gradients, as well as local process can simultaneously shape different below- and above-ground resource acquisition strategies in extremely poor resource environments.

The 4D disasters (desertification, drought, dust, and dzud, a Mongolian term for severe winter weather) have recently been increasing in Mongolia, and their impacts on the livelihoods of humans has likewise increased. The combination of drought and dzud has caused the loss of livestock on which nomadic herdsmen depend for their well-being. Understanding the spatiotemporal patterns of drought and predicting drought conditions are important goals of scientific research in Mongolia. This study involved examining the trends of the normalized difference vegetation index (NDVI) and satellite-based aridity index (SbAI) to determine why the land surface of Mongolia has recently (2001–2013) become drier across a range of aridity indices (AIs). The main reasons were that the maximum NDVI (NDVImax) was lower than the NDVImax typically found in other arid regions of the world, and the SbAI throughout the year was large (dry), although the SbAI in summer was comparatively small (wet). Under the current conditions, the capacity of the land surface to retain water throughout the year caused a large SbAI because rainfall in Mongolia is concentrated in the summer, and the conditions of grasslands reflect summer rainfall in addition to grazing pressure. We then proposed a method to monitor the land-surface dryness or drought using only satellite data. The correct identification of drought was higher for the SbAI. Drought is more strongly correlated with soil moisture anomalies, and thus the annual averaged SbAI might be appropriate for monitoring drought during seasons. Degraded land area, defined as annual NDVImax < 0.2 and annual averaged SbAI > 0.025, has decreased. Degraded land area was large in the major drought years of Mongolia.

Plant domestication has strongly modified crop morphology and development. Nevertheless, many crops continue to display atavistic characteristics that were advantageous to their wild ancestors but are deleterious under cultivation, such as pod dehiscence (PD). Here, we provide the first comprehensive assessment of the inheritance of PD in the common bean (Phaseolus vulgaris), a major domesticated grain legume. Using three methods to evaluate the PD phenotype, we identified multiple, unlinked genetic regions controlling PD in a biparental population and two diversity panels. Subsequently, we assessed patterns of orthology among these loci and those controlling the trait in other species. Our results show that different genes were selected in each domestication and ecogeographic race. A chromosome Pv03 dirigent-like gene, involved in lignin biosynthesis, showed a base-pair substitution that is associated with decreased PD. This haplotype may underlie the expansion of Mesoamerican domesticates into northern Mexico, where arid conditions promote PD. The rise in frequency of the decreased-PD haplotype may be a consequence of the markedly different fitness landscape imposed by domestication. Environmental dependency and genetic redundancy can explain the maintenance of atavistic traits under domestication.

The changing characteristics of aridity over a larger spatiotemporal scale have gained interest in recent years due to climate change. The long-term (1901–2016) changes in spatiotemporal patterns of annual and seasonal aridity during two major crop growing seasons of Pakistan, Kharif and Rabi, are evaluated in this study using gridded precipitation and potential evapotranspiration (PET) data. The UNESCO aridity index was used to estimate aridity at each grid point for all the years between 1901 and 2016. The temporal changes in aridity and its associations with precipitation and PET are evaluated by implementing a moving window of 50 years of data with an 11-year interval. The modified Mann–Kendall (MMK) trend test is applied to estimate unidirectional change by eliminating the effect of natural variability of climate, and Pettitt's test is used to detect year of change in aridity. The results revealed that the climate over 60 % of Pakistan (mainly in southern parts) is arid. The spatial patterns of aridity trends show a strong influence of the changes in precipitation on the aridity trend. The increasing trend in aridity (drier) is noticed in the southwest, where precipitation is low during Kharif, while there is a decreasing trend (wetter) in the Rabi season in the region which receives high precipitation due to western disturbances. The annual and Kharif aridity is found to decrease (wetter) at a rate of 0.0001 to 0.0002 per year in the northeast, while Kharif and Rabi aridity are found to increase (drier) at some locations in the south at a rate of −0.0019 to −0.0001 per year. The spatial patterns of aridity changes show a shift from arid to the semi-arid (wetter) climate in annual and Kharif over a large area while showing a shift from arid to hyper-arid (drier) region during Rabi in a small area. Most of the significant changes in precipitation and aridity are observed in the years between 1971 and 1980. Overall, aridity is found to increase (drier) in 0.52 %, 4.44 % and 0.52 % of the area and decrease (wetter) in 11.75 %, 7.57 % and 9.66 % of the area for annual, Rabi and Kharif seasons respectively during 1967–2016 relative to 1901–1950.