Unforeseen plant phenotypic diversity in a dry and grazed world.

Earth harbours an extraordinary plant phenotypic diversity1 that is at risk from ongoing global changes2,3. However, it remains unknown how increasing aridity and livestock grazing pressure-two major drivers of global change4-6-shape the trait covariation that underlies plant phenotypic diversity1,7. Here we assessed how covariation among 20 chemical and morphological traits responds to aridity and grazing pressure within global drylands. Our analysis involved 133,769 trait measurements spanning 1,347 observations of 301 perennial plant species surveyed across 326 plots from 6 continents. Crossing an aridity threshold of approximately 0.7 (close to the transition between semi-arid and arid zones) led to an unexpected 88% increase in trait diversity. This threshold appeared in the presence of grazers, and moved toward lower aridity levels with increasing grazing pressure. Moreover, 57% of observed trait diversity occurred only in the most arid and grazed drylands, highlighting the phenotypic uniqueness of these extreme environments. Our work indicates that drylands act as a global reservoir of plant phenotypic diversity and challenge the pervasive view that harsh environmental conditions reduce plant trait diversity8-10. They also highlight that many alternative strategies may enable plants to cope with increases in environmental stress induced by climate change and land-use intensification.

Multi-model assessment of potential natural vegetation to support ecological restoration.

Ecological restoration is imperative for controlling desertification. Potential natural vegetation (PNV), the theoretical vegetation succession state, can guides near-natural restoration. Although a rising transition from traditional statistical methods to advanced machine learning and deep learning is observed in PNV simulation, a comprehensive comparison of their performance is still unexplored. Therefore, we overview the performance of PNV mapping in terms of 12 commonly used methods with varying spatial scales and sample sizes. Our findings indicate that the methodology should be carefully selected due to the variation in performance of different model types, with Area Under the Curve (AUC) values ranging from 0.65 to 0.95 for models with sample sizes up to 80% of the total sample size. Specifically, semi-supervised learning performs best with small sample sizes (i.e., 10 to 200), while Random Forest, XGBoost, and artificial neural networks perform better with large sample sizes (i.e., over 500). Further, the performance of all models tends to improve significantly as the sample size increases and the grain size of the crystals becomes smaller. Take the downstream Tarim River Basin, a hyper-arid region undergoing ecological restoration, as a case study. We showed that its potential restored areas were overestimated by 2-3 fold as the spatial scale became coarser, revealing the caution needed while planning restoration projects at coarse resolution. These findings enhance the application of PNV in the design of restoration programs to prevent desertification.

Hotspots of biogeochemical activity linked to aridity and plant traits across global drylands.

Perennial plants create productive and biodiverse hotspots, known as fertile islands, beneath their canopies. These hotspots largely determine the structure and functioning of drylands worldwide. Despite their ubiquity, the factors controlling fertile islands under conditions of contrasting grazing by livestock, the most prevalent land use in drylands, remain virtually unknown. Here we evaluated the relative importance of grazing pressure and herbivore type, climate and plant functional traits on 24 soil physical and chemical attributes that represent proxies of key ecosystem services related to decomposition, soil fertility, and soil and water conservation. To do this, we conducted a standardized global survey of 288 plots at 88 sites in 25 countries worldwide. We show that aridity and plant traits are the major factors associated with the magnitude of plant effects on fertile islands in grazed drylands worldwide. Grazing pressure had little influence on the capacity of plants to support fertile islands. Taller and wider shrubs and grasses supported stronger island effects. Stable and functional soils tended to be linked to species-rich sites with taller plants. Together, our findings dispel the notion that grazing pressure or herbivore type are linked to the formation or intensification of fertile islands in drylands. Rather, our study suggests that changes in aridity, and processes that alter island identity and therefore plant traits, will have marked effects on how perennial plants support and maintain the functioning of drylands in a more arid and grazed world.

The global biogeography and environmental drivers of fairy circles.

Fairy circles (FCs) are regular vegetation patterns found in drylands of Namibia and Western Australia. It is virtually unknown whether they are also present in other regions of the world and which environmental factors determine their distribution. We conducted a global systematic survey and found FC-like vegetation patterns in 263 sites from 15 countries and three continents, including the Sahel, Madagascar, and Middle-West Asia. FC-like vegetation patterns are found in environments characterized by a unique combination of soil (including low nutrient levels and high sand content) and climatic (arid regions with high temperatures and high precipitation seasonality) conditions. In addition to these factors, the presence of specific biological elements (termite nests) in certain regions also plays a role in the presence of these patterns. Furthermore, areas with FC-like vegetation patterns also showed more stable temporal productivity patterns than those of surrounding areas. Our study presents a global atlas of FCs and provides unique insights into the ecology and biogeography of these fascinating vegetation patterns.

Feeding Ecology of the Cuvier's Gazelle (Gazella cuvieri, Ogilby, 1841) in the Sahara Desert.

Knowledge of the feeding ecology of ungulates in arid biomes offers an interesting model for understanding the drought resistance of large desert-adapted herbivores, a crucial issue in the face of increasing desertification due to climate change. To assess the feeding ecology of the endangered Cuvier's gazelle (Gazella cuvieri) in the Sahara desert, we used a multi-method approach combining faecal samples, direct observations, and the recording of indirect signs of feeding. We hypothesised that browser behaviour is the best foraging strategy for species living in hyper-arid environments, mainly due to long periods without grazing opportunities. Complementarily, we explored the effects of the main environmental descriptors (rainfalls and NDVI) on feeding patterns and diet quality. We found that Cuvier's diets are based mainly on acacias (Vachellia tortilis, V. flava) and occasionally on the annual forb Anastatica hierochuntica. In total, eighteen species (five trees, nine shrubs, three herbs, and one grass) belonging to fifteen families were recorded. Our result confirmed the browsers' characteristic of this species, reaffirming its ability to settle in a hostile environment. Acacias stand out as key species consumed at the southernmost limit of their range; hence, future conservation plans and strategies should take this into account for the survival of Cuvier's gazelle in desert environments.

Implementing climate change projections in System Dynamics models.

Desertification is the degradation of drylands, which occupy an increasing proportion of the Earth's surface due to global warming. It is currently the most extensive biome on Earth, occupying 45% and one out of every three inhabitants of the planet live in them. One of the most effective ways to face desertification, as Land Degradation Neutrality points out, is prevention. For this purpose, simulation models are very useful tools. Specifically, System Dynamics models are particularly effective, since they allow bringing together the biophysical and socioeconomic variables involved in the formation of the problem. These integrative models, coupled with other tools such as sensitivity analyses, are used to generate desertification early warning indicators. The objective of this programming routine is to implement climate change scenarios in these simulation models. The script presented here was used to evaluate the sensitivity of dehesa rangelands productivity to the increase in the frequency and intensity of droughts due to climate change.•Integrated simulation models are useful tools to understand complex socioecosystems.•Land-use changes foster the alteration of key hydro-bio-geochemical processes.•By means of automated import processes and data analysis programming, it is possible to implement desertification early warning systems.

Grazing and ecosystem service delivery in global drylands.

Grazing represents the most extensive use of land worldwide. Yet its impacts on ecosystem services remain uncertain because pervasive interactions between grazing pressure, climate, soil properties, and biodiversity may occur but have never been addressed simultaneously. Using a standardized survey at 98 sites across six continents, we show that interactions between grazing pressure, climate, soil, and biodiversity are critical to explain the delivery of fundamental ecosystem services across drylands worldwide. Increasing grazing pressure reduced ecosystem service delivery in warmer and species-poor drylands, whereas positive effects of grazing were observed in colder and species-rich areas. Considering interactions between grazing and local abiotic and biotic factors is key for understanding the fate of dryland ecosystems under climate change and increasing human pressure.

Climate legacies drive the distribution and future restoration potential of dryland forests.

Knowing the extent and environmental drivers of forests is key to successfully restore degraded ecosystems, and to mitigate climate change and desertification impacts using tree planting. Water availability is the main limiting factor for the development of forests in drylands, yet the importance of groundwater resources and palaeoclimate as drivers of their current distribution has been neglected. Here we report that mid-Holocene climates and aquifer trends are key predictors of the distribution of dryland forests worldwide. We also updated the global extent of dryland forests to 1,283 million hectares and showed that failing to consider past climates and aquifers has resulted in ignoring or misplacing up to 130 million hectares of forests in drylands. Our findings highlight the importance of a wetter past and well-preserved aquifers to explain the current distribution of dryland forests, and can guide restoration actions by avoiding unsuitable areas for tree establishment in a drier world.

Mask R-CNN and OBIA Fusion Improves the Segmentation of Scattered Vegetation in Very High-Resolution Optical Sensors.

Vegetation generally appears scattered in drylands. Its structure, composition and spatial patterns are key controls of biotic interactions, water, and nutrient cycles. Applying segmentation methods to very high-resolution images for monitoring changes in vegetation cover can provide relevant information for dryland conservation ecology. For this reason, improving segmentation methods and understanding the effect of spatial resolution on segmentation results is key to improve dryland vegetation monitoring. We explored and analyzed the accuracy of Object-Based Image Analysis (OBIA) and Mask Region-based Convolutional Neural Networks (Mask R-CNN) and the fusion of both methods in the segmentation of scattered vegetation in a dryland ecosystem. As a case study, we mapped Ziziphus lotus, the dominant shrub of a habitat of conservation priority in one of the driest areas of Europe. Our results show for the first time that the fusion of the results from OBIA and Mask R-CNN increases the accuracy of the segmentation of scattered shrubs up to 25% compared to both methods separately. Hence, by fusing OBIA and Mask R-CNNs on very high-resolution images, the improved segmentation accuracy of vegetation mapping would lead to more precise and sensitive monitoring of changes in biodiversity and ecosystem services in drylands.

Exploring the economic, social and environmental prospects for commercial natural annual grasslands by performing a sensitivity analysis on a multidisciplinary integrated model.

This paper presents an integrated modelling study aimed at exploring the possible effects of drivers of change in commercial natural annual grasslands. We consider drivers as factors that affect the rangeland but are not affected by it. Thus, the stocking rate is not treated as a driver, but as an endogenous factor ultimately determined by drivers. This approach, which call for integrated multidisciplinary studies, is rare in the rangeland literature. We try to alleviate this lack by presenting and utilizing a novel multidisciplinary integrated system-dynamics model (108 equations) which represents an area of privately owned extensive farms, its farmers (their numbers and decisions), herds or flocks, herbage production, soil erosion and the linked local markets. By means of a global sensitivity analysis of this model we evaluated the sensitivities of key endogenous factors to the same percentage variation in 70 factors, including economic and climate drivers. The analysis considered the behaviours of 288,000 variants of the modelled system, each under a different 300-year driver scenario. We found that the environmental component of the model was almost exclusively sensitive to biophysical factors, whereas the socio-economic component was almost exclusively sensitive to socio-economic factors, despite the model takes account of key feedbacks connecting both components. Our results suggest that cautiously-managed commercial natural grasslands could socially and economically cope with climate change, especially in a scenario of rising prices of animal products, and also that, even though stocking rates would increase due to an increase in the demand for livestock products, the main threat to the provision of ecosystem services in the studied system would be climate change.

Global effectiveness of group decision-making strategies in coping with forage and price variabilities in commercial rangelands: A modelling assessment.

This paper presents a modelling study that evaluated the global effectiveness of a range of group decision-making strategies for commercial farming areas in rangelands affected by temporal variations in forage production. The assessment utilised an integrated system dynamics model (86 equations) to examine the broad and long-term group decision outcomes. This model considers aspects usually neglected in related studies, such as the dynamics of the main local prices, the dynamics of the number of active farmers, the supplementary feeding of livestock, and certain behavioural traits of farmers and traders. The assessment procedure was based on an analysis of the outcomes of the model under 330,000 simulation scenarios. The results indicated that only if all the farmers in an area are either opportunistic or conservative that is, are either responsive or unresponsive to expected profits, the exploitation of the grazing resources were optimal in some senses. A widespread opportunism proved optimal only from an economic viewpoint. However, it is very unlikely that most of the farmers would agree to be opportunistic in practice. By contrast, a widespread conservatism, which in principle is perfectly feasible, proved optimal from economic, social, and ecological perspectives. Notably, it was found that the presence of a relatively small number of opportunistic farmers would suffice to considerably reduce the economic results of widespread conservatism.

A feasible methodology for groundwater resource modelling for sustainable use in sparse-data drylands: Application to the Amtoudi Oasis in the northern Sahara.

In a previous paper, the Amtoudi Oasis, a remote area in the northern Sahara in southern Morocco, was chosen to model the dynamics of groundwater-dependent economics under different scenarios of water availability, both the wet 2009-2010 and the average 2010-2011 hydrological years. Groundwater imbalance was reflected by net aquifer recharge (R) less than groundwater allotment for agriculture and urban uses in the average year 2010-2011. Three key groundwater sustainability issues from the hydrologic perspective were raised for future research, which are addressed in this paper. Introducing a feasible methodology for groundwater resource modelling for sustainable use in sparse-data drylands, this paper updates available databases, compiles new databases, and introduces new formulations to: (1) refine the net groundwater balance (W) modelling for years 2009-2010 and 2010-2011, providing the magnitude of net lateral inflow from adjacent formations (RL), the largest R component contributing to the oasis; (2) evaluate the non-evaporative fraction of precipitation (P) (B) from 1973 onward as a proxy of the potential renewable water resource available for use; and (3) define the critical balance period for variables to reach a comparable stationary condition, as prerequisite for long-term modelling of W. RL was about 0.07-fold P and 0.85-fold R. Historical yearly B-to-P ratios were 0.02 for dry, 0.04 for average, and 0.07 for wet hydrological years; the average yearly P being 124mm. A critical 17-year balance period with stable relative error below 0.1 was defined from the 44-year P and B time-series statistical study. This is the monitoring period proposed for the stationary evaluation of the variables involved in the long-term modelling of W. This paper seeks to offer a feasible methodology for groundwater modelling addressed for planning sustainable water policies in sparse-data drylands.

Doomed to collapse: Why Algerian steppe rangelands are overgrazed and some lessons to help land-use transitions.

This work illustrates the application of a simulation model to analyse how swiftly large-scale land-use changes can drive broad territories to collapse. In this sense, the economic needs of a population should not clash with the natural environment but rather be reconciled with it. Abundant literature deals with the integration of socioeconomic drivers, ecological aspects, farming management, and climatology related to Algerian rangeland degradation. The present study seeks to compare the time course of Alfa grass biomass and the livestock raised on these distinctive rangelands under two different land-use strategies. The traditional one has nomads as the main inhabitants of these lands. For centuries, their strategy for alleviating pressure on resources was to move from one area to other. The more recent sedentary land-use leads to overgrazing supported by the massive use of cheap supplemental feed. Additionally, the model was used as a platform to launch scenarios for sustainable land-use management under a competitive market-economy. A key finding for preserving grazing resources was the increment of supplemental feed prices, which is compatible with stocking rates higher than the historical ones.

Present and future of desertification in Spain: Implementation of a surveillance system to prevent land degradation.

Mitigation strategies are crucial for desertification given that once degradation starts, other solutions are extremely expensive or unworkable. Prevention is key to handle this problem and solutions should be based on spotting and deactivating the stressors of the system. Following this topic, the Spanish Plan of Action to Combat Desertification (SPACD) created the basis for implementing two innovative approaches to evaluate the threat of land degradation in the country. This paper presents tools for preventing desertification in the form of a geomatic approach to enable the periodic assessments of the status and trends of land condition. Also System Dynamics modelling has been used to integrate bio-physical and socio-economic aspects of desertification to explain and analyse degradation in the main hot spots detected in Spain. The 2dRUE procedure was implemented to map the land-condition status by comparing potential land productivity according to water availability, the limiting factor in arid lands, with plant-biomass data. This assessment showed that 20% of the territory is degraded and an additional 1% is actively degrading. System Dynamics modelling was applied to study the five desertification landscapes identified by the SPACD. The risk analysis, implemented on these models, concluded that 'Herbaceous crops affected by soil erosion' is the landscape most at risk, while the Plackett-Burman sensitivity analysis used to rank the factors highlighted the supremacy of climatic factors above socioeconomic drivers.

A hydrological-economic model for sustainable groundwater use in sparse-data drylands: Application to the Amtoudi Oasis in southern Morocco, northern Sahara.

A hydrological-economic model is introduced to describe the dynamics of groundwater-dependent economics (agriculture and tourism) for sustainable use in sparse-data drylands. The Amtoudi Oasis, a remote area in southern Morocco, in the northern Sahara attractive for tourism and with evidence of groundwater degradation, was chosen to show the model operation. Governing system variables were identified and put into action through System Dynamics (SD) modeling causal diagrams to program basic formulations into a model having two modules coupled by the nexus 'pumping': (1) the hydrological module represents the net groundwater balance (G) dynamics; and (2) the economic module reproduces the variation in the consumers of water, both the population and tourists. The model was operated under similar influx of tourists and different scenarios of water availability, such as the wet 2009-2010 and the average 2010-2011 hydrological years. The rise in international tourism is identified as the main driving force reducing emigration and introducing new social habits in the population, in particular concerning water consumption. Urban water allotment (PU) was doubled for less than a 100-inhabitant net increase in recent decades. The water allocation for agriculture (PI), the largest consumer of water, had remained constant for decades. Despite that the 2-year monitoring period is not long enough to draw long-term conclusions, groundwater imbalance was reflected by net aquifer recharge (R) less than PI+PU (G<0) in the average year 2010-2011, with net lateral inflow from adjacent Cambrian formations being the largest recharge component. R is expected to be much less than PI+PU in recurrent dry spells. Some low-technology actions are tentatively proposed to mitigate groundwater degradation, such as: wastewater capture, treatment, and reuse for irrigation; storm-water harvesting for irrigation; and active maintenance of the irrigation system to improve its efficiency.