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Abstract Neoliberal approaches to water governance, pioneered in Chile in the 1980s, are reappearing today on the centerstage of the water policy debate. While advocates claim that strong property rights, limits on government authority, and water markets can enhance environmental sustainability, efficiency, neutrality, and equity in the distribution of water rights, limited empirical evidence exists on whether neoliberal policies have delivered on these key promises. In this paper, we combine hydrological analysis with a nationwide data set on government water rights allocations between 1981 and 2021 to determine when and where water has been allocated beyond sustainable limits. We then integrate water market transaction and agricultural data to assess how allocations and scarcity conditions relate to spatial and temporal patterns in irrigation, crop distribution, and water market activity. Our results indicate that 30% of catchments are overallocated, and that continued government allocations of water rights during scarcity exacerbate already‐high inequalities in the distribution of water. We find no evidence that scarcity or water markets induced improvements in numerous efficiency metrics. Overall, our results support growing claims that the neoliberal water model fails to fulfill its key promises, notably to the detriment of nature and marginalized rural communities.

Abstract Atmospheric nitrogen (N) deposition and climate change are transforming the way N moves through dryland watersheds. For example, N deposition is increasing N export to streams, which may be exacerbated by changes in the magnitude, timing, and intensity of precipitation (i.e., the precipitation regime). While deposition can control the amount of N entering a watershed, the precipitation regime influences rates of internal cycling; when and where soil N, plant roots, and microbes are hydrologically coupled via diffusion; how quickly plants and microbes assimilate N; and rates of denitrification, runoff, and leaching. We used the ecohydrological model RHESSys to investigate (a) how N dynamics differ between N‐limited and N‐saturated conditions in a dryland watershed, and (b) how total precipitation and its intra‐annual intermittency (i.e., the time between storms in a year), interannual intermittency (i.e., the duration of dry months across multiple years), and interannual variability (i.e., variance in the amount of precipitation among years) modify N dynamics and export. Streamflow nitrate (NO3−) export was more sensitive to increasing rainfall intermittency (both intra‐annual and interannual) and variability in N‐limited than in N‐saturated model scenarios, particularly when total precipitation was lower—the opposite was true for denitrification which is more sensitive in N‐saturated than N‐limited scenarios. N export and denitrification increased or decreased more with increasing interannual intermittency than with other changes in precipitation amount. This suggests that under future climate change, prolonged droughts that are followed by more intense storms may pose a major threat to water quality in dryland watersheds.

Abstract The emergence of SARS-like coronaviruses is a multi-stage process from wildlife reservoirs to people. Here we characterize multiple drivers—landscape change, host distribution, and human exposure—associated with the risk of spillover of zoonotic SARS-like coronaviruses to help inform surveillance and mitigation activities. We consider direct and indirect transmission pathways by modeling four scenarios with livestock and mammalian wildlife as potential and known reservoirs before examining how access to healthcare varies within clusters and scenarios. We found 19 clusters with differing risk factor contributions within a single country (N = 9) or transboundary (N = 10). High-risk areas were mainly closer (11-20%) rather than far (

Abstract Non-Technical Summary Human societies are changing where and how water flows through the atmosphere. However, these changes in the atmospheric water cycle are not being managed, nor is there any real sense of where these changes might be headed in the future. Thus, we develop a new economic theory of atmospheric water management, and explore this theory using creative story-based scenarios. These scenarios reveal surprising possibilities for the future of atmospheric water management, ranging from a stock market for transpiration to on-demand weather. We discuss these story-based futures in the context of research and policy priorities in the present day. Technical Summary Humanity is modifying the atmospheric water cycle, via land use, climate change, air pollution, and weather modification. Historically, atmospheric water was implicitly considered a ‘public good’ since it was neither actively consumed nor controlled. However, given anthropogenic changes, atmospheric water can become a ‘common-pool’ good (consumable) or a ‘club’ good (controllable). Moreover, advancements in weather modification presage water becoming a ‘private’ good, meaning both consumable and controllable. Given the implications, we designed a theoretical framing of atmospheric water as an economic good and used a combination of methods in order to explore possible future scenarios based on human modifications of the atmospheric water cycle. First, a systematic literature search of scholarly abstracts was used in a computational text analysis. Second, the output of the text analysis was matched to different parts of an existing economic goods framework. Then, a group of global water experts were trained and developed story-based scenarios. The resultant scenarios serve as creative investigations of the future of human modification of the atmospheric water cycle. We discuss how the scenarios can enhance anticipatory capacity in the context of both future research frontiers and potential policy pathways including transboundary governance, finance, and resource management. Social Media Summary Story-based scenarios reveal novel future pathways for the management of the atmospheric water cycle.

Groundwater, the second largest stock of freshwater on the planet, is an important water source used for municipal water supply, irrigation, or industrial needs. For instance, California’s arid Central Valley relies on groundwater resources to produce a quarter of the United States’ food demand as farmers rely on this precious resource when surface water is scarce. Despite its importance, the nexus between groundwater dynamics and climate drivers remains difficult to quantify, model, and predict because of the lack of a comprehensive observation network. In this study, machine learning techniques were used to predict groundwater levels with a 3-month forecasting horizon for the Sacramento River Basin. For this, publicly available meteorological and hydrological datasets and in-situ well-level measurements were used. Time series, ensemble-based, and deep-learning models including transformers were all tested, with an ensemble-based, XGBoost model, producing the best mean standard deviation percent error (MSPE) of 32.23% and a root mean squared error (RMSE) of 1.05 m (m) when using a 3- month forecasting horizon and when tested using a monthly rolling window over the years 2017–2020. The model proved to be better at predicting into wet months than the dry summer months and was found to be better at extracting seasonality than explaining well-level residuals, with well-specific features, as opposed to exogenous meteorological features specific to the hydrological unit of the well, ranking as the most important features to the model. Though other forecasting horizons were tested, a 3-month look-ahead window resulted in the best balance of precision and accuracy, where smaller forecasting horizons resulted in smaller RMSE but larger MSPE scores and vice-versa for larger forecasting horizons.

Games with environmental feedback have become a crucial area of study across various scientific domains, modelling the dynamic interplay between human decisions and environmental changes, and highlighting the consequences of our choices on natural resources and biodiversity. In this work, we propose a co-evolutionary model for human-environment systems that incorporates the effects of knowledge feedback and social interaction on the sustainability of common pool resources (CPRs). The model represents consumers as agents who adjust their resource extraction based on the resource’s state. These agents are connected through social networks, where links symbolize either affinity or aversion among them. The interplay between social dynamics and resource dynamics is explored, with the system’s evolution analyzed across various network topologies and initial conditions. We find that knowledge feedback can independently sustain CPRs. However, the impact of social interactions on sustainability is dual-faceted: it can either support or impede sustainability, influenced by the network’s connectivity and heterogeneity. A notable finding is the identification of a critical network mean degree, beyond which a depletion/repletion transition parallels an absorbing/active state transition in social dynamics, i.e. individual agents and their connections are/are not prone to being frozen in their social states. Furthermore, the study examines the evolution of the social network, revealing the emergence of two polarized groups where agents within each community have the same affinity. Finally, we observe an inverse relationship between system complexity and sustainability. Comparative analyses using Monte–Carlo simulations and rate equations are employed, along with analytical arguments, to reinforce the study’s findings. The model successfully captures key aspects of the human-environment system, offering valuable insights to understand how both the spread of information and social dynamics may impact the sustainability of CPRs.

Although land degradation is a worldwide challenge and a destructive phenomenon, little studies have been done on the application of new numerical methods (data mining and statistically), for spatial simulation of this phenomenon and identification of areas sensitive to land degradation. The aim of this study is to spatially simulate land degradation in the Qazvin plain using the frequency ratio model to identify areas prone to land degradation. For this purpose, using the trend of changes in net primary production during the years 2001 to 2020, the points of occurrence of land degradation in the Qazvin plain were determined. Approximately 70% and 30% of the points were used to prepare the land degradation vulnerability map and validate the model's efficiency, respectively. For this research, 15 parameters affecting land degradation (directly and indirectly) including temperature, rainfall, slope, aspect, elevation, EC and SAR of ground water, ground water level, annual ground water decline, land use, normalized difference vegetation index, normalize difference salinity index, vegetation soil salinity index, normalized difference moisture index, and visible and shortwave infrared drought index, were introduced into the model as predictors factors or independent parameters. Finally, using the area under the ROC curve, the effectiveness of the frequency ratio model for spatial simulation of land degradation was assessed. The map of land degradation susceptibility shows that the areas prone to degradation are located in the northeast, north, northwest, west, southwest, and south of the Qazvin plain, which mainly includes good, moderate and poor rangelands. For the land use parameter, the highest frequency ratio was associated with the sum of good, moderate, and poor rangeland (5.66). The value of AUC = 0.7 indicates the good performance of the frequency ratio model in spatial simulation of land degradation.

Water scarcity associated with large-scale land acquisitions is exacerbated by adoption of water-intensive crops and expansion of irrigation, which in turn increases rival water uses.

Non-technical summary Environmental threats to shelter, livelihoods, and food security are often considered push factors for intra-African human migration. Research in this field is often fragmented into a myriad of case studies on specific subregions or events, thus preventing a more comprehensive understanding of the phenomenon. This paper examines environmental drivers reported in the literature as push factors for human displacement across 32 sub-Saharan African countries between 1990 and 2021. Extensive consultation of past studies and reports with analytical methods shows that environmental migration is complex and influenced by multiple direct and indirect factors. Non-environmental drivers compound the effects of environmental change. Technical summary Intra-African environmental migration is a bleak reality. Warming trends, aridification, and the intensification of extreme climate events, combined with underlying non-environmental drivers, may set millions of people on the move. Despite previous studies and meta-analyses on environmental migration within sub-Saharan Africa (SSA), conclusive empirical evidence of the relationship between environmental change and migration is still missing. Here we draw on 87 case studies published in the scholarly literature (from fields ranging from the environmental sciences to development economics and migration research) or documented by research databases, reports, and international disaster datasets to develop a meta-analysis investigating the relationship between environmental changes and migration across SSA. A combination of quantitative, Qualitative Comparative Analyses (QCA), and statistical correlation methods are used to analyze the metadata and investigate the complex web of environmental drivers of environmental migration in SSA while highlighting subregional differences in the predominant environmental forcing. We develop a new conceptual framework for investigating the cascading flow of interdependences among environmental change drivers of human displacement while reconstructing the main migration patterns across SSA. We also present new insights into the way non-environmental factors are exposing communities in SSA to high vulnerability and reduced resilience to environmental change. Social media summary Human displacement in sub-Saharan Africa is often associated with the effects of climate change and environmental degradation.

Jiao et al. conducted a comprehensive evaluation of changes in water constraint on vegetation growth in the extratropical Northern Hemisphere between 1982 and 2015. They document a significant increase in vegetation water constraint over the last three decades.

Huang et al. use satellite imagery spanning over 40 years to investigate the spatial patterning of vegetation patches in a North American coastal ecosystem. They find that woody plant encroachment follows a power law when approaching critical transition points, which may inform future ecological monitoring of coastal systems.

The global agrarian transition is characterized by a rise in large-scale land acquisitions (LSLAs), whose energy impacts are unknown. Here, the authors assess how LSLAs change land use, finding that they necessitate greater investment in energy to meet demands, and greater greenhouse gas emissions.

Summary: One of the outstanding problems in complexity science and engineering is the study of high-dimensional networked systems and of their susceptibility to transitions to undesired states as a result of changes in external drivers or in the structural properties. Because of the incredibly large number of parameters controlling the state of such complex systems and the heterogeneity of its components, the study of their dynamics is extremely difficult. Here we propose an analytical framework for collapsing complex N-dimensional networked systems into an S+1-dimensional manifold as a function of S effective control parameters with S << N. We test our approach on a variety of real-world complex problems showing how this new framework can approximate the system's response to changes and correctly identify the regions in the parameter space corresponding to the system's transitions. Our work offers an analytical method to evaluate optimal strategies in the design or management of networked systems.

The year 2017 saw the rise and fall of the crypto-currency market, followed by high variability in the price of all crypto-currencies. In this work, we study the abrupt transition in crypto-currency residuals, which is associated with the critical transition (the phenomenon of critical slowing down) or the stochastic transition phenomena. We find that, regardless of the specific crypto-currency or rolling window size, the autocorrelation always fluctuates around a high value, while the standard deviation increases monotonically. Therefore, while the autocorrelation does not display the signals of critical slowing down, the standard deviation can be used to anticipate critical or stochastic transitions. In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, which could have served as the early warning signals of two major price collapses that have happened in the following periods. We finally propose a mean-field phenomenological model for the price of crypto-currency to show how the use of the standard deviation of the residuals is a better leading indicator of the collapse in price than the time-series' autocorrelation. Our findings represent a first step towards a better diagnostic of the risk of critical transition in the price and/or volume of crypto-currencies.

Higher temperatures expected by midcentury increase the risk of shocks to crop production, while the interconnected nature of the current global food system functions to spread the impact of localized production shocks throughout the world. In this study, we analyze the global potential impact of a present-day event of equivalent magnitude to the US Dust Bowl, modeling the ways in which a sudden decline in US wheat production could cascade through the global network of agricultural trade. We use observations of country-level production, reserves, and trade data in a Food Shock Cascade model to explore trade adjustments and country-level inventory changes in response to a major, multiyear production decline. We find that a 4-year decline in wheat production of the same proportional magnitude as occurred during the Dust Bowl greatly reduces both wheat supply and reserves in the United States and propagates through the global trade network. By year 4 of the event, US wheat exports fall from 90.5 trillion kcal before the drought to 48 trillion to 52 trillion kcal, and the United States exhausts 94% of its reserves. As a result of reduced US exports, other countries meet their needs by leveraging their own reserves, leading to a 31% decline in wheat reserves globally. These findings demonstrate that an extreme production decline would lead to substantial supply shortfalls in both the United States and in other countries, where impacts outside the United States strongly depend on a country's reserves and on its relative position in the global trade network.

Summary: In many regions of the world pollinator populations are rapidly declining, a trend that is expected to disrupt major ecosystem functions and services. These changes in pollinator abundance may be prone to critical transitions with abrupt shifts to a state strongly depleted both in pollinator and vegetation abundance. Here we develop a process-based model to investigate the effect of a positive pollinator-vegetation feedback, whereby an initial decline in plant density increases selfing thereby reducing floral resources and negatively affecting pollinators. We show that a decline in resource availability and an increase in disturbance intensity can induce an abrupt shift in vegetation and pollinator dynamics and potentially lead to the collapse of plant-pollinator systems. Thus, endogenous feedbacks can induce strong non-linearities in plant-pollinator dynamics, making them vulnerable to critical transitions to a state depleted of both plants and pollinators in response to resource deficiency and natural or anthropogenic disturbance. : Environmental Science; Ecology; Mathematical Biosciences Subject Areas: Environmental Science, Ecology, Mathematical Biosciences

Agriculture strongly relies on irrigation. While irrigated land accounts for roughly 20% of the global cultivated area, it contributes to about 40% of crop production. In the last few decades, the growing demand for agricultural commodities has translated into an increasing pressure on the global freshwater resources, often leading to their unsustainable use. Here we investigate the sustainability of irrigation, balancing farmers' profit generation objectives and the needs of ecological systems. We ask the question “sustainability of what?” to stress how the sustainability of irrigation is often evaluated with respect the opposing needs of humans and nature. While from the farmers' perspective irrigation is sustainable when it provides uninterrupted access to water resources at a price not exceeding the marginal revenue they generate (clearly without accounting for environmental externalities), from the standpoint of water resources, irrigation is sustainable if it does not deplete freshwater stocks or environmental flows. We invoke the notions of “weak” and “strong” sustainability to develop a novel framework for the evaluation of tradeoffs between human needs and the conservation of natural capital. Through the analysis of criteria of performance, we relate water deficit and irrigation overuse to the reliability and resilience of irrigation. This approach is applied to the case of Australia, a major agricultural country affected by water scarcity. The application of the framework to the case of Australia shows how this approach can be used to highlight areas in which irrigation contributes to a weakly sustainable use of water resources with impacts on environmental flows and groundwater stocks. Solutions, such as increasing efficiencies or reducing water applications through the adoption of deficit irrigation, can enhance water sustainability in some water scarce locations.

Agricultural transformations have significantly contributed to the global market’s year-round supply of capital-intensive greenhouse-grown crops. For instance, berry production in México is increasingly relying on greenhouse systems to meet the growing demand of international markets, particularly in the USA. It is still unclear to what extent these transformations are related to land tenure, as data on greenhouse distribution often do not exist, are incomplete, or lack spatial resolution. This paper presents a support vector machine learning algorithm tool to map greenhouse expansion using satellite images. The tool is applied to the major berry-growing region of Michoacán, México. Here agricultural areas are transforming to satisfy foreign demand for berries, altering local land and water resource use patterns. We use this tool and a unique land tenure dataset to investigate (a) the spatially explicit extent to which high-input commercial agriculture (mainly the production of berries) has expanded in this region since 1989; and (b) the extent to which smallholder ( ejidal ) land has been incorporated into the highly capitalized agro-export sector. We combine a national dataset on ejidal land (which includes both communal and parcel land) with geospatial agricultural data to quantify the land-use changes in six municipalities in the berry-growing region of Michoacán between 1989 and 2021. We find that the development of the greenhouse berry boom can be quantified and shown with spatially-explicit detail, growing from zero to over 9,500 ha over the period, using almost one-quarter of all regional agricultural land in 2020. We further find that the capital-intensive market-oriented berry industry has been widely integrated into smallholder ejidal lands, so much so that over half of greenhouses are found there.

Abstract Plants with crassulacean acid metabolism (CAM) are increasing in distribution and abundance in drylands worldwide, but the underlying drivers remain unknown. We investigate the impacts of extreme drought and CO2 enrichment on the competitive relationships between seedlings of Cylindropuntia imbricata (CAM species) and Bouteloua eriopoda (C4 grass), which coexist in semiarid ecosystems across the Southwestern United States. Our experiments under altered water and CO2 water conditions show that C. imbricata positively responded to CO2 enrichment under extreme drought conditions, while B. eriopoda declined from drought stress and did not recover after the drought ended. Conversely, in well‐watered conditions B. eriopoda had a strong competitive advantage on C. imbricata such that the photosynthetic rate and biomass (per individual) of C. imbricata grown with B. eriopoda were lower relative to when growing alone. A meta‐analysis examining multiple plant families across global drylands shows a positive response of CAM photosynthesis and productivity to CO2 enrichment. Collectively, our results suggest that under drought and elevated CO2 concentrations, projected with climate change, the competitive advantage of plant functional groups may shift and the dominance of CAM plants may increase in semiarid ecosystems.

Global analyses have revealed virtual drains and gains of water between trading countries, with Mexico ranking as one of the countries with the fastest increase in unsustainable water consumption in agriculture for export markets, since 2000. It is unclear, however, how Mexico has reshaped its crop production and associated reliance on freshwater resources to satisfy growing domestic and international markets, especially the United States (US). While the Mexico-US partnership has been identified as one supported by unsustainable irrigation water, the spatial understanding of its strain on water resources has remained at the national scale and without context of the crops driving the change. In this analysis, we focus on the evolution of Mexican agriculture since 1994, the year the North American Free Trade Agreement was enacted, to identify hotspots of water unsustainability in crop production in the domestic and US supply chain. Using a global process-based crop water model, we find that between 1994 and 2015, rainwater (or ‘green’ water) and irrigation (or ‘blue’) water consumed in the production of crops increased by one fourth nationally, while water in crops exported to the US doubled. Virtual export of blue water embodied in the trade of berries increased five orders of magnitude; a substantial growth in blue water export was also associated with trade to the US of cereals, fruits, nuts, vegetables, pulses, and tubers. Our results show that in Mexico irrigated water plays an increasingly prominent role in export agriculture, and that many healthy crops that dominate US imports from the world are grown in water scarce Mexican municipalities relying on unsustainable irrigation practices. This serves as a warning for the sustainability of future Mexican healthy food supplies, both for the domestic market and for export to the US.

We convened a workshop to enable scientists who study water systems from both social science and physical science perspectives to develop a shared language. This shared language is necessary to bridge a divide between these disciplines' different conceptual frameworks. As a result of this workshop, we argue that we should view socio-hydrological systems as structurally co-constituted of social, engineered, and natural elements and study the "characteristic management challenges" that emerge from this structure and reoccur across time, space, and socioeconomic contexts. This approach is in contrast to theories that view these systems as separately conceptualized natural and social domains connected by bi-directional feedbacks, as is prevalent in much of the water systems research arising from the physical sciences. A focus on emergent characteristic management challenges encourages us to go beyond searching for evidence of feedbacks and instead ask questions such as: What types of innovations have successfully been used to address these challenges? What structural components of the system affect its resilience to hydrological events and through what mechanisms? Are there differences between successful and unsuccessful strategies to solve one of the characteristic management challenges? If so, how are these differences affected by institutional structure and ecological and economic contexts? To answer these questions, social processes must now take center stage in the study and practice of water management. We also argue that water systems are an important class of coupled systems with relevance for sustainability science because they are particularly amenable to the kinds of systematic comparisons that allow knowledge to accumulate. Indeed, the characteristic management challenges we identify are few in number and recur over most of human history and in most geographical locations. This recurrence should allow us to accumulate knowledge to answer the above questions by studying the long historical record of institutional innovations to manage water systems.

Meeting the increasing global demand for agricultural products without depleting the limited resources of the planet is a major challenge that humanity is facing. Most studies on global food security do not make projections past the year 2050, just as climate change and increasing demand for food are expected to intensify. Moreover, past studies do not account for the water sustainability limits of irrigation expansion to presently rainfed areas. Here we perform an integrated assessment that considers a range of factors affecting future food production and demand throughout the 21st century. We evaluate the self-sufficiency of 165 countries under sustainability, middle-of-the-road, and business-as-usual scenarios considering changes in diet, population, agricultural intensification, and climate. We find that under both the middle-of-the-road and business-as-usual trajectories global food self-sufficiency is likely to decline despite increased food production through sustainable agricultural intensification since projected food demand exceeds potential production. Contrarily, under a sustainability scenario, we estimate that there will be enough food production to feed the global population. However, most countries in Africa and the Middle East will continue to be heavily reliant on imports throughout the 21st century under all scenarios. These results highlight future hotspots of crop production deficits, reliance on food imports, and vulnerability to food supply shocks.

Savannas are extremely important socio-economic landscapes, with pastoralist societies relying on these ecosystems to sustain their livelihoods and economy. Globally, there is an increase of woody vegetation in these ecosystems, degrading the potential of these multi-functional landscapes to sustain societies and wildlife. Several mechanisms have been invoked to explain the processes responsible for woody vegetation composition; however, these are often investigated separately at scales not best suited to land-managers, thereby impeding the evaluation of their relative importance. We ran six transects at 15 sites along the Kalahari transect, collecting data on species identity, diversity, and abundance. We used Poisson and Tobit regression models to investigate the relationship among woody vegetation, precipitation, grazing, borehole density, and fire. We identified 44 species across 78 transects, with the highest species richness and abundance occurring at Kuke (middle of the rainfall gradient). Precipitation was the most important environmental variable across all species and various morphological groups, while increased borehole density and livestock resulted in lower bipinnate species abundance, contradicting the consensus that these managed features increase the presence of such species. Rotating cattle between boreholes subsequently reduces the impact of trampling and grazing on the soil and maintains and/or reduces woody vegetation abundance.

Fire can induce long-lived changes to land-surface albedo, an important aspect of the Earth’s energy budget, but the temporal evolution of these anomalies is poorly understood. Due to the widespread presence of fire in Africa, this represents uncertainty in the continental energy budget, which has important implications for regional climate and hydrologic cycling. In this study, we present the first object-based accounting of albedo anomalies induced by larger (>1 km2) individual wildfires in sub-Saharan Africa. We group spatially contiguous wildfire pixels into fire objects and track the albedo anomaly for five years after the burn. We find that albedo anomalies all have the same general temporal signature: An immediate, brief period of darkening followed by persistent brightening. The strongest brightening is found in the Kalahari region while more intense and long-lived initial darkening is found in the Sahel region. The average southern hemisphere albedo anomaly is +1.50 × 10−3 in the year following wildfire, representing a statistically significant negative surface energy balance forcing on a continental scale. This study challenges an existing paradigm surrounding the physical effects of fire on the landscape. Our results suggest that models of albedo that assume a darkening and recovery to baseline are overly simplistic in almost all circumstances. Furthermore, the presumption that immediate darkening is the only meaningful effect on albedo is incorrect for the majority of the African continent.

The increasing global demand for farmland products is placing unprecedented pressure on the global agricultural system and its water resources. Many regions of the world, that are affected by a chronic water scarcity relative to their population, strongly depend on the import of agricultural commodities and associated embodied (or virtual ) water. The globalization of water through virtual water trade (VWT) is leading to a displacement of water use and a disconnection between human populations and the water resources they rely on. Despite the recognized importance of these phenomena in reshaping the patterns of water dependence through teleconnections between consumers and producers, their effect on global and regional water resources has just started to be quantified. This review investigates the global spatiotemporal dynamics, drivers, and impacts of VWT through an integrated analysis of surface water, groundwater, and root-zone soil moisture consumption for agricultural production; it evaluates how virtual water flows compare to the major ‘physical water fluxes’ in the Earth System; and provides a new reconceptualization of the hydrologic cycle to account also for the role of water redistribution by the hidden ‘virtual water cycle’.

Recent studies have highlighted the reliance of global food production on unsustainable irrigation practices, which deplete freshwater stocks and environmental flows, and consequently impair aquatic ecosystems. Unsustainable irrigation is driven by domestic and international demand for agricultural products. Research on the environmental consequences of trade has often concentrated on the global displacement of pollution and land use, while the effect of trade on water sustainability and the drying of over-depleted watercourses has seldom been recognized and quantified. Here we evaluate unsustainable irrigation water consumption (UWC) associated with global crop production and determine the share of UWC embedded in international trade. We find that, while about 52% of global irrigation is unsustainable, 15% of it is virtually exported, with an average 18% increase between year 2000 and 2015. About 60% of global virtual transfers of UWC are driven by exports of cotton, sugar cane, fruits, and vegetables. One third of UWC in Mexico, Spain, Turkmenistan, South Africa, Morocco, and Australia is associated with demand from the export markets. The globalization of water through trade contributes to running rivers dry, an environmental externality commonly overlooked by trade policies. By identifying the producing and consuming countries that are responsible for unsustainable irrigation embedded in virtual water trade, this study highlights trade links in which policies are needed to achieve sustainable water and food security goals in the coming decades.

Climate change is expected to impact the habitability of many places around the world in significant and unprecedented ways in the coming decades. While previous studies have provided estimates of populations potentially exposed to various climate impacts, little work has been done to assess the number of people that may actually be displaced or where they will choose to go. Here we modify a diffusion-based model of human mobility in combination with population, geographic, and climatic data to estimate the sources, destinations, and flux of potential migrants as driven by sea level rise (SLR) in Bangladesh in the years 2050 and 2100. Using only maps of population and elevation, we predict that 0.9 million people (by year 2050) to 2.1 million people (by year 2100) could be displaced by direct inundation and that almost all of this movement will occur locally within the southern half of the country. We also find that destination locations should anticipate substantial additional demands on jobs (594 000), housing (197 000), and food (783 × 10 ^9 calories) by mid-century as a result of those displaced by SLR. By linking the sources of migrants displaced by SLR with their likely destinations, we demonstrate an effective approach for predicting climate-driven migrant flows, especially in data-limited settings.

Water is a major factor limiting crop production in many regions around the world. Irrigation can greatly enhance crop yields, but the local availability and timing of freshwater resources constrains the ability of humanity to increase food production. Innovations in irrigation infrastructure have allowed humanity to utilize previously inaccessible water resources, enhancing water withdrawals for agriculture while increasing pressure on environmental flows and other human uses. While substantial additional water will be required to support future food production, it is not clear whether and where freshwater availability is sufficient to sustainably close the yield gap in cultivated lands. The extent to which irrigation can be expanded within presently rainfed cropland without depleting environmental flows remains poorly understood. Here we perform a spatially explicit biophysical assessment of global consumptive water use for crop production under current and maximum attainable yield scenarios assuming current cropping practices. We then compare these present and anticipated water consumptions to local water availability to examine potential changes in water scarcity. We find that global water consumption for irrigation could sustainably increase by 48% (408 km ^3 H _2 O yr ^−1 )—expanding irrigation to 26% of currently rainfed cultivated lands (2.67 × 10 ^6 km ^2 ) and producing 37% (3.38 × 10 ^15 kcal yr ^−1 ) more calories, enough to feed an additional 2.8 billion people. If current unsustainable blue water consumption (336 km ^3 yr ^−1 ) and production (1.19 × 10 ^15 kcal yr ^−1 ) practices were eliminated, a sustainable irrigation expansion and intensification would still enable a 24% increase in calorie (2.19 × 10 ^15 kcal yr ^−1 ) production. Collectively, these results show that the sustainable expansion and intensification of irrigation in selected croplands could contribute substantially to achieving food security and environmental goals in tandem in the coming decades.

Ensuring food security requires food production and distribution systems function throughout disruptions. Understanding the factors that contribute to the global food system’s ability to respond and adapt to such disruptions (i.e. resilience) is critical for understanding the long-term sustainability of human populations. Variable impacts of production shocks on food supply between countries indicate a need for national-scale resilience indicators that can provide global comparisons. However, methods for tracking changes in resilience have had limited application to food systems. We developed an indicator-based analysis of food systems resilience for the years 1992–2011. Our approach is based on three dimensions of resilience: socio-economic access to food in terms of income of the poorest quintile relative to food prices, biophysical capacity to intensify or extensify food production, and the magnitude and diversity of current domestic food production. The socio-economic indicator has a large variability, but with low values concentrated in Africa and Asia. The biophysical capacity indicator is highest in Africa and Eastern Europe, in part because of a high potential for extensification of cropland and for yield gap closure in cultivated areas. However, the biophysical capacity indicator has declined globally in recent years. The production diversity indicator has increased slightly, with a relatively even geographic distribution. Few countries had exclusively high or low values for all indicators. Collectively, these results are the basis for global comparisons of resilience between countries, and provide necessary context for developing generalizations about resilience in the global food system.

Spatially diverse trends in population growth, climate change, industrialization, urbanization and economic development are expected to change future food supply and demand. These changes may affect the suitability of land for food production, implying elevated risks especially for resource-constrained, food-importing countries. We present the evolution of biophysical redundancy for agricultural production at country level, from 1992 to 2012. Biophysical redundancy, defined as unused biotic and abiotic environmental resources, is represented by the potential food production of ‘spare land’, available water resources (i.e., not already used for human activities), as well as production increases through yield gap closure on cultivated areas and potential agricultural areas. In 2012, the biophysical redundancy of 75 (48) countries, mainly in North Africa, Western Europe, the Middle East and Asia, was insufficient to produce the caloric nutritional needs for at least 50% (25%) of their population during a year. Biophysical redundancy has decreased in the last two decades in 102 out of 155 countries, 11 of these went from high to limited redundancy, and nine of these from limited to very low redundancy. Although the variability of the drivers of change across different countries is high, improvements in yield and population growth have a clear impact on the decreases of redundancy towards the very low redundancy category. We took a more detailed look at countries classified as ‘Low Income Economies (LIEs)’ since they are particularly vulnerable to domestic or external food supply changes, due to their limited capacity to offset for food supply decreases with higher purchasing power on the international market. Currently, nine LIEs have limited or very low biophysical redundancy. Many of these showed a decrease in redundancy over the last two decades, which is not always linked with improvements in per capita food availability.

Human societies rely on food reserves and the importation of agricultural goods as means to cope with crop failures and associated food shortage. While food trade has been the subject of intensive investigations in recent years, food reserves remain poorly quantified. It is unclear how food stocks are changing and whether they are declining. In this study we use food stock records for 92 products to reconstruct 50 years of aggregated food reserves, expressed in caloric equivalent (kcal), at the regional and global scales. A detailed statistical analysis demonstrates that the overall regional and global per-capita food stocks are stationary, challenging a widespread impression that food reserves are shrinking. We develop a statistically-sound stochastic representation of stock dynamics and take the stock-halving probability as a measure of the natural variability of the process. We find that there is a 20% probability that the global per-capita stocks will be halved by 2050. There are, however, some strong regional differences: Western Europe and the region encompassing North Africa and the Middle East have smaller halving probabilities and smaller per-capita stocks, while North America and Oceania have greater halving probabilities and greater per-capita stocks than the global average. Africa exhibits low per-capita stocks and relatively high probability of stock halving by 2050, which reflects a state of higher food insecurity in this continent.

While a growing proportion of global food consumption is obtained through international trade, there is an ongoing debate on whether this increased reliance on trade benefits or hinders food security, and specifically, the ability of global food systems to absorb shocks due to local or regional losses of production. This paper introduces a model that simulates the short-term response to a food supply shock originating in a single country, which is partly absorbed through decreases in domestic reserves and consumption, and partly transmitted through the adjustment of trade flows. By applying the model to publicly-available data for the cereals commodity group over a 17 year period, we find that differential outcomes of supply shocks simulated through this time period are driven not only by the intensification of trade, but as importantly by changes in the distribution of reserves. Our analysis also identifies countries where trade dependency may accentuate the risk of food shortages from foreign production shocks; such risk could be reduced by increasing domestic reserves or importing food from a diversity of suppliers that possess their own reserves. This simulation-based model provides a framework to study the short-term, nonlinear and out-of-equilibrium response of trade networks to supply shocks, and could be applied to specific scenarios of environmental or economic perturbations.

How much could farm water management interventions increase global crop production? This is the central question posed in a global modelling study by Jägermeyr et al (2016 Environ. Res. Lett. http://dx.doi.org/10.1088/1748-9326/11/2/025002 11 http://dx.doi.org/10.1088/1748-9326/11/2/025002 ). They define the biophysical realm of possibility for future gains in crop production related to agricultural water practices—enhancing water availability to crops and expanding irrigation by reducing non-productive water consumption. The findings of Jägermeyr et al offer crucial insight on the potential for crop water management to sustainably intensify agriculture, but they also provide a benchmark to consider the broader role of sustainable intensification targets in the global food system. Here, we reflect on how the global crop water management simulations of Jägermeyr et al could interact with: (1) farm size at more local scales, (2) downstream water users at the river basin scale, as well as (3) food trade and (4) demand-side food system strategies at the global scale. Incorporating such cross-scale linkages in future research could highlight the diverse pathways needed to harness the potential of farm-level crop water management for a more productive and sustainable global food system.

The global distribution of food production is unequal relative to the distribution of human populations. International trade can increase or decrease inequality in food availability, but little is known about how specific countries and commodities contribute to this redistribution. We present a method based on the Gini coefficient for evaluating the contributions of country and commodity specific trade to inequality in the global food system. We applied the method to global food production and trade data for the years 1986–2011 to identify the specific countries and commodities that contribute to increasing and decreasing inequality in global food availability relative to food production. Overall, international trade reduced inequality in food availability by 25%–33% relative to the distribution of food production, depending on the year. Across all years, about 58% of the total trade links acted to reduce inequality with ∼4% of the links providing 95% of the reduction in inequality. Exports from United States of America, Malaysia, Argentina, and Canada are particularly important in decreasing inequality. Specific commodities that reduce inequality when traded include cereals and vegetables. Some trade connections contribute to increasing inequality, but this effect is mostly concentrated within a small number of commodities including fruits, stimulants, and nuts. In terms of specific countries, exports from Slovenia, Oman, Singapore, and Germany act to increase overall inequality. Collectively, our analysis and results represent an opportunity for building an enhanced understanding of global-scale patterns in food availability.

Human demand for animal products has risen markedly over the past 50 years with important environmental impacts. Dairy and cattle production have disproportionately contributed to greenhouse gas (GHG) emissions and land use, while crop demands of more intensive systems have increased fertilizer use and competition for available crop calories. At the same time, chicken and pig production has grown more rapidly than for ruminants, indicating a change in the environmental burden per animal calorie (EBC) with time. How EBCs have changed and to what extent resource use efficiency (RUE), the composition of animal production and the trade of feed have played a role in these changes have not been examined to date. We employ a calorie-based perspective, distinguishing animal calorie production between calories produced from feedcrop sources—directly competing with humans for available calories—and those from non-feed sources—plant biomass unavailable for direct human consumption. Combining this information with data on agricultural resource use, we calculate EBCs in terms of land, GHG emissions and nitrogen. We find that EBCs have changed substantially for land (−62%), GHGs (−46%) and nitrogen (+188%). Changes in RUE (e.g., selective breeding, increased grain-feeding) have been the primary contributor to these EBC trends, but shifts in the composition of livestock production were responsible for 12%–41% of the total EBC changes. In addition, the virtual trade of land for feed has more than tripled in the past 25 years with 77% of countries currently relying on virtual land imports to support domestic livestock production. Our findings indicate that important tradeoffs have occurred as a result of livestock intensification, with more efficient land use and emission rates exchanged for greater nitrogen use and increased competition between feed and food. This study provides an integrated evaluation of livestock’s impact on food security and the environment.