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To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature’s contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions.

Consistent information on the current elemental composition of vegetation at global scale and the variables that determine it is lacking. To fill this gap, we gathered a total of 30912 georeferenced records on woody plants foliar concentrations of N, P, and K from published databases, and produced global maps of foliar N, P and K concentrations for woody plants using neural networks at a resolution of 1 km2 . We used data for climate, atmospheric deposition, soil, and morphoclimatic groups to train the neural networks. Foliar N, P and K do not follow clear global latitudinal patterns but are consistent with the hypothesis of soil substrate age. We additionally built generalized linear mixed models to investigate the evolutionary history effect together with the effects of environmental effects. In this comparison, evolutionary history effects explained most of the variability in all cases (mostly >60%). These results emphasize the determinant role of evolutionary history in foliar elemental composition, which should be incorporated in upcoming dynamic global vegetation models.

Satisfying China’s food demand without harming the environment is one of the greatest sustainability challenges for the coming decades. Here we provide a comprehensive forward-looking assessment of the environmental impacts of China’s growing demand on the country itself and on its trading partners. We find that the increasing food demand, especially for livestock products (~16%–30% across all scenarios), would domestically require ~3–12 Mha of additional pasture between 2020 and 2050, resulting in ~−2% to +16% growth in agricultural greenhouse gas (GHG) emissions. The projected ~15%–24% reliance on agricultural imports in 2050 would result in ~90–175 Mha of agricultural land area and ~88–226 MtCO2-equivalent yr−1of GHG emissions virtually imported to China, which account for ~26%–46% and ~13%–32% of China’s global environmental impacts, respectively. The distribution of the environmental impacts between China and the rest of the world would substantially depend on development of trade openness. Thus, to limit the negative environmental impacts of its growing food consumption, besides domestic policies, China needs to also take responsibility in the development of sustainable international trade.

Studies on ecological stoichiometry (ES) have increased rapidly in number in recent years. Continuous exploration of classical concepts such as the growth-rate hypothesis (GRH), ), which is based on the relationship between the nitrogen:phosphorus (N:P) ratio of organisms and their growth-rate capacity, has identified new patterns and uncertainties, particularly with regard to terrestrial plants and microbial systems. Another concept that has proven to be helpful is the Redfield ratio, which postulates a consistent carbon:nitrogen:phosphorus (C:N:P) molar ratio of 100:16:1 in marine phytoplankton and open oceanic waters, and this ratio is related to the protein:rRNA ratio associated with protein synthesis. ES studies in all types of ecosystems have demonstrated that shifts in the elemental composition of water, soil, organisms, and communities are linked to the spatiotemporal structure and function of the ecosystem communities. The recent trend of also considering additional bio-elements such as potassium (K), magnesium (Mg) and calcium (Ca), has improved our understanding of how resource availability in complex ecosystems affects basic organism functions such as growth, stress responses, and defensive mechanisms. The biogeochemical or bio-elemental niche hypothesis is a novel tool that uses the concentrations and ratios of several bio-elements to define species niches and to scale up processes at the community and ecosystem levels. Global environmental changes, such as an increase in atmospheric CO2, drought, N deposition, and species invasion, change the elemental composition of the growth media (soil and water), organisms, and ecosystems. For example, the growing imbalance between N and P that results from very large anthropogenic inputs of reactive N and smaller inputs of P into the biosphere is increasingly affecting the health of both ecosystems and humans. In this review, we summarise recent advances in ecological stoichiometry and identify key questions for

The remaining carbon budget for limiting global warming to 1.5°C will likely be exhausted within this decade. Carbon debt3 generated thereafter will need to be compensated by net negative emissions4. However, economic policy instruments to guarantee potentially very costly net carbon-dioxide removal (CDR) have not yet been devised. Here, we propose intertemporal instruments to provide the basis for widely applied carbon taxes and emission trading systems to finance a net negative carbon economy5. We investigate an idealized market approach to incentivize repayment of previously accrued carbon debt by establishing emitters’ responsibility for net carbon removal through ‘Carbon Removal Obligations’ (CROs). Inherent risks, such as the default risk of carbon debtors, are addressed by pricing atmospheric CO2 storage through interest on carbon debt. In contrast to the prevailing literature on emission pathways, we find that interest payments for CROs induce substantially more ambitious near-term decarbonization complemented by earlier and less aggressive deployment of CDR. We conclude that CROs will need to become an integral part of the global climate policy mix if we are to ensure the viability of ambitious climate targets and an equitable distribution of mitigation efforts across generations.

Scenario analysis has emerged as a key tool to analyze complex and uncertain future socio-ecological developments. However, currently existing global scenarios (narratives of how the world may develop) have neglected biological invasions, a major threat to biodiversity and the economy. Here, we use a novel participatory process to develop a diverse set of global biological invasion scenarios spanning a wide range of plausible global futures through to 2050. We adapted the widely used “two axes” scenario analysis approach to develop four families of four scenarios each, resulting in 16 scenarios that were later clustered into four contrasting sets of futures. Our analysis highlights that socioeconomic developments and technological innovation have the potential to shape biological invasions, in addition to well-known drivers, such as climate and human land use change and global trade. Our scenarios partially align with the shared socioeconomic pathways created by the climate change research community. Several factors that drive differences in biological invasions were underrepresented in the shared socioeconomic pathways; in particular, the implementation of biosecurity policies. We argue that including factors related to public environmental awareness and technological and trade development in global scenarios and models is essential to adequately consider biological invasions in global environmental assessments and thereby obtain a more integrative picture of future social–ecological developments.

Growing competition for land, water and energy call for global strategies ensuring affordable food production at minimum environmental impacts. Economic modelling studies suggest trade-off relationships between environmental sustainability and food prices. However, evidence based on empirical cost-functions supporting such trade-offs remains scarce at the global level. Here, based on cost engineering modelling, we show that optimised spatial allocation of 10 major crops, would reduce current costs of agricultural production by approximately 40% while improving environmental performance. Although production inputs per unit of output increase at local scales, a reduction of cultivated land of 50% overcompensates the slightly higher field-scale costs enabling improved overall cost-effectiveness. Our results suggest that long-run food prices are bound to continue to decrease under strong environmental policies. Policies supporting sustainability transitions in the land sector should focus on managing local barriers to the implementation of high-yield regenerative agricultural practices delivering multiple regional and global public goods.

Critical imbalances and threshold exceedances can trigger a disruption in a network of interdependent systems. An insignificant-at-first-glance shock can induce systemic risks with cascading catastrophic impacts. Systemic risks challenge traditional risk assessment and management approaches. These risks are shaped by systemic interactions, risk exposures, and decisions of various agents. The paper discusses the need for the two-stage stochastic optimization (STO) approach that enables the design of a robust portfolio of precautionary strategic and operational adaptive decisions that makes the interdependent systems flexible and robust with respect to risks of all kinds. We established a connection between the robust quantile-based non-smooth estimation problem in statistics and the two-stage non-smooth STO problem of robust strategic-adaptive decisionmaking. The coexistence of complementary strategic and adaptive decisions induces systemic risk aversion in the form of Value-at-Risk (VaR) quantile-based risk constraints. The two-stage robust decision-making is implemented into a large-scale Global Biosphere Management (GLOBIOM) model, showing that robust management of systemic risks can be addressed by solving a system of probabilistic security equations. Selected numerical results emphasize that a robust combination of interdependent strategic and adaptive solutions presents qualitatively new policy recommendations, if compared to a traditional scenario-by-scenario decision-making analysis.

Scenario analysis has emerged as a key tool to analyze complex and uncertain future socio-ecological developments. However, currently existing global scenarios (narratives of how the world may develop) have neglected biological invasions, a major threat to biodiversity and the economy. Here, we use a novel participatory process to develop a diverse set of global biological invasion scenarios spanning a wide range of plausible global futures through to 2050. We adapted the widely used “two axes” scenario analysis approach to develop four families of four scenarios each, resulting in 16 scenarios that were later clustered into four contrasting sets of futures. Our analysis highlights that socioeconomic developments and technological innovation have the potential to shape biological invasions, in addition to well-known drivers, such as climate and human land use change and global trade. Our scenarios partially align with the shared socioeconomic pathways created by the climate change research community. Several factors that drive differences in biological invasions were underrepresented in the shared socioeconomic pathways; in particular, the implementation of biosecurity policies. We argue that including factors related to public environmental awareness and technological and trade development in global scenarios and models is essential to adequately consider biological invasions in global environmental assessments and thereby obtain a more integrative picture of future social–ecological developments.

We present a comprehensive modelling framework aimed at quantifying the response of agricultural commodity prices to changes in their potential determinants. The problem of model uncertainty is assessed explicitly by concentrating on specification selection based on the quality of short-term out-of-sample forecasts (1 to 12 months ahead) for the price of wheat, soybeans and corn. Univariate and multivariate autoregressive models (autoregressive [AR], vector autoregressive [VAR] and vector error correction [VEC] specifications, estimated using frequentist and Bayesian methods), specifications with heteroskedastic errors (AR conditional heteroskedastic [ARCH] and generalized AR conditional heteroskedastic [GARCH] models) and combinations of these are entertained, including information about market fundamentals, macroeconomic and financial developments, and climatic variables. In addition, we assess potential non-linearities in the commodity price dynamics along the business cycle. Our results indicate that variables measuring market fundamentals and macroeconomic developments (and, to a lesser extent, financial developments) contain systematic predictive information for out-of-sample forecasting of commodity prices and that agricultural commodity prices react robustly to shocks in international competitiveness, as measured by changes in the real exchange rate.

We provide four data records: 1.The reference data set as a comma-separated file ("reference_data_set.csv") with the following attributes: “ID” is a unique location identifier “Latitude, Longitude” are centroid coordinates of a 100m x 100m pixel. “Land_use_ID “is a land use class: 11 - Naturally regenerating forest without any signs of human activities, e.g., primary forests. 20 - Naturally regenerating forest with signs of human activities, e.g., logging, clear cuts etc. 31 - Planted forest. 32 - Short rotation plantations for timber. 40 - Oil palm plantations. 53 - Agroforestry. “Flag” identifies a data origin: 1- the crowdsourced locations, 2- the control data set, 0 – the additional experts' classifications following the opportunistic approach. 2. The 100 m forest management map in a geoTiff format with the classes presented - "FML_v3.2.tif ". 3. The predicted class probability from the Random Forest classification in a geoTiff format - "ProbaV_LC100_epoch2015_global_v2.0.3_forest-management--layer-proba_EPSG-4326.tif" 4. Validation data set as a comma-separated file ("validation_data_set.csv) with the following attributes: “ID” is a unique location identifier “pixel_center_x” , “pixel_center_y ” are centroid coordinates of a 100m x 100m pixel in lat/lon projection “first_landuse_class “is a land use class, as in (1). “second_landuse_class “is a second possible land use class, as in (1), identified in case it was difficult to assign one class with high confidence.

While nitrogen inputs are crucial to agricultural production, excess nitrogen contributes to serious ecosystem damage and water pollution. Here, we investigate this trade-off using an integrated modelling framework. We quantify how different nitrogen mitigation options contribute to reconciling food security and compliance with regional nitrogen surplus boundaries. We find that even when respecting regional nitrogen surplus boundaries, hunger could be substantially alleviated with 590 million fewer people at risk of hunger from 2010 to 2050, if all nitrogen mitigation options were mobilized simultaneously. Our scenario experiments indicate that when introducing regional N targets, supply-side measures such as the nitrogen use efficiency improvement are more important than demand-side efforts for food security. International trade plays a key role in sustaining global food security under nitrogen boundary constraints if only a limited set of mitigation options is deployed. Policies that respect regional nitrogen surplus boundaries would yield a substantial reduction in non-CO2 GHG emissions of 2.3 GtCO2e yr−1 in 2050, which indicates a necessity for policy coordination.

This data repository contains the results of the NatureMap ( naturemap.earth/) conservation prioritization effort. The maps were created by jointly optimizing biodiversity and NCPs such as carbon and/or water. Maps are supplied at both 10km and 50km resolution and all maps that aim to find priority areas for all species considered in the analysis, utilize a series of representative sets. The ranks for each layer are area-specific and can be used to extract summary statistics by simple subsetting. For example, to obtain the top 30% of land area for biodiversity and carbon, one needs to create a mask of all areas lower than a value of 30 from the respective ranked layers. For convenience two files are supplied that contain the fraction of land area per grid cell times 1000. Multiplying those with the cell area (100km2, respectively 2500km2) gives the exact amount of land area in a given grid cell. These are labelled "globalgrid_mollweide_**km.tif " can be used to create masks for the priority maps. The geographic projection is World Mollweide Equal Area projection.

In the presentation we discuss critical issues related to the design of resilient and robust food, water, energy, environmental systems in the presence of interdependent systemic risks. We introduce the notions of systemic risks, security, resilience and robustness in FWEE systems. We emphasize the need for the two-stage preventive-adaptive stochastic optimization (STO) approaches enabling to design a robust portfolio of precautionary strategic and operational adaptive decisions making the interdependent systems flexible and robust with respect to risks of all kinds. We establish a connection between the robust quantile-based nonsmooth estimation problem in statistics and the two-stage nonsmooth STO problem of robust strategic-adaptive decision making. The coexistence of complementary strategic ex-ante and adaptive ex-post decisions induces systemic risk aversion in the form of Value-at-Risk quantile-based risk constraints. Using examples from research studies on integrated management of catastrophic dependent risks, integrated agricultural-water-energy nexus security, multidisciplinary water resource management we argue that coping with systemic risks can be addressed by solving a system of implicit probabilistic security equations. Selected numerical results from the studies illustrate that a robust combination of interdependent strategic and adaptive solutions presents qualitatively new policy recommendations contributing to the overall welfare increase.

Grasslands absorb and release carbon dioxide (CO2), emit methane (CH4) from grazing livestock and emit nitrous oxide (N2O) from soils. Little is known about how the fluxes of these three greenhouse gases, from managed and natural grasslands worldwide, have contributed to past climate change, or the roles of managed pastures versus natural grasslands. Here, global trends and regional patterns of the full greenhouse gas balance of grasslands are estimated for the period 1750 to 2012. A new spatially explicit land surface model is applied, to separate the direct effects of human activities from land management and the indirect effects from climate change, increasing CO2 and regional changes in nitrogen deposition. Direct human management activities are simulated to have caused grasslands to switch from a sink to a source of GHG, because of increased livestock numbers and accelerated conversion of natural lands to pasture. However, climate change drivers contributed a net carbon sink in soil organic matter, mainly from the increased productivity of grasslands due to increased CO2 and nitrogen deposition. The net radiative forcing of all grasslands is currently close to neutral, but has been increasing since the 1960s. Here, we show that the net global climate warming caused by managed grassland cancels the net climate cooling from carbon sinks in sparsely grazed and natural grasslands. In the face of future climate change and increased demand for livestock products, these findings highlight the need to use sustainable management to preserve and enhance soil carbon storage in grasslands and to reduce GHG emissions from managed grasslands. A full description of the files is available in the README of the dataset.

This Excel file contains the data used in the plotting of the figures in the manuscript titled "The environmental challenge and trade implications of China’s future food demand"​ to be published in Nature Sustainability in 2021. In the data file you can find 1) bilateral trade quantity, 2) domestic environmental impact, 3), virtual environmental trade flows, 4) sensitivity results of environmental impacts in 2050.​

Industrial phosphorus (P) fertilizer has substantially improved global food production, but has also led to environmental impacts. Intensive global agricultural trade has increased and the impacts of trade on aggravating or alleviating future P scarcity must be examined, especially for the most vulnerable countries. We combined data to estimate the global P trade among countries and its impacts on global P flows, based on global agricultural trade, cropland soil P budgets and crop P fertilizer footprints (the amount of industrial P fertilizer applied for producing one unit of P in the harvested crop). The global agricultural P trade represented a fraction of 16% of P in harvested crops in 2014, half of which was exported from the United States of America, Brazil and the European Union and one fifth imported by China. Virtual P fertilizer flows (about 2.60 Tg P y-1) referred to industrial P fertilizers applied to traded crops by exporting countries; thus, 1/3 of global virtual P fertilizer flows were associated with the international soybean trade. P use efficiency (PUE), the ratio of the harvested crop-P to the total external P inputs, is a larger problem for tropical than temperate countries. Global crop trade had brought in a net 0.2 Tg P y-1 savings of industrial P fertilizers globally, compared to crop production in export and import countries. >0.50 Tg y-1 of the gross global accumulation of soil P and P in freshwater were associated with global agricultural trade. Global PUE, however, could be improved considerably, and thus global cooperation and improving PUE could help to solve the problem of future P scarcity. Vulnerable countries should also propose urgent national plans to address their own situations of P scarcity or low PUE.

The global socio-economic and agricultural expansion is accompanied by large inputs of nitrogen (N) and phosphorus (P) on land and by a serious alteration of the water cycle and water quality. The Mediterranean basin represents a paradigmatic region to study the entangled nutrient and water challenges because the region, where many of the world's climatic and socio-economic gradients are present, is predicted to suffer severe water stress in the coming decades yet at the same time agricultural intensification and population are increasing in many rim countries. We here describe the biogeochemical budgets of N and P in 549 river basins for the 2000–2009 period, analyzing how the climatic gradient and water management practices affect the fluxes of N and P and their stoichiometric ratios. Average land inputs are 3,600 kg N km−2 yr−1 and 470 kg P km−2 yr−1, with a significant variation between basins (>100 times) closely related to the stage of agricultural intensification. Moreover, the combination of aridity and water regulation can strongly alter the final balances, not only by changing the export of nutrients by rivers (riverine export is ca. 10% for N and 8% for P in arid basins), but also decoupling the N:P ratios between terrestrial and freshwater compartments.

Meeting Brazil’s ambitious national commitments on both climate change mitigation and biodiversity conservation depends on securing its reserves of forest carbon and biodiversity. Brazil’s ‘Forest Code’ is a key tool to reconcile environmental preservation and agricultural production; it limits deforestation and requires forest restoration in illegally deforested areas. However, not all provisions of the law’s 2012 revision have yet been implemented and some are facing new challenges. Using modelled land use change projections for the whole of the country, we show that full implementation and enforcement of the law has the potential to contribute to conserving biodiversity. Biodiversity outcomes will be especially positive if (i) deforested areas are restored in ways that support recolonization by native species and (ii) additional measures are implemented to protect native vegetation in areas like Caatinga dry forests and Cerrado savannas, which may experience added pressure displaced from other regions by Forest Code implementation.

Negative emission technologies underpin socioeconomic scenarios consistent with the Paris Agreement. Afforestation and bioenergy coupled with carbon dioxide (CO2) capture and storage are the main land negative emission technologies proposed, but the range of nature-based solutions is wider. Here we explore soil amendment with powdered basalt in natural ecosystems. Basalt is an abundant rock resource, which reacts with CO2 and removes it from the atmosphere. Besides, basalt improves soil fertility and thereby potentially enhances ecosystem carbon storage, rendering a global CO2 removal of basalt substantially larger than previously suggested. As this is a fully developed technology that can be co-deployed in existing land systems, it is suited for rapid upscaling. Achieving sufficiently high net CO2 removal will require upscaling of basalt mining, deploying systems in remote areas with a low carbon footprint and using energy from low-carbon sources. We argue that basalt soil amendment should be considered a prominent option when assessing land management options for mitigating climate change, but yet unknown side-effects, as well as limited data on field-scale deployment, need to be addressed first.

Solar PV has seen a spectacular market development in recent years and has become a cost competitive source of electricity in many parts of the world. Yet, prospective observations show that the coronavirus pandemic could impact renewable energy projects, especially in the distributed market. Tracking and attributing the economic footprint of COVID-19 lockdowns in the photovoltaic sector poses a significant research challenge. Based on millions of financial transaction records and 44 thousand photovoltaic installation records, we tracked the spatio-temporal sale network of the distributed photovoltaic market and explored the extent of market slowdown. We found that a two-month lockdown duration can be assessed as a high-risk threshold value. When the lockdown duration exceeds the threshold value, the monthly value-added loss reaches 67.7%, and emission reduction capacity is cut by 64.2% over the whole year. We show that risks of a slowdown in PV deployment due to COVID-19 lockdowns can be mitigated by comprehensive incentive strategies for the distributed PV market amid market uncertainties.

To respect the Paris agreement targeting a limitation of global warming below 2°C by 2100, and possibly below 1.5 °C, drastic reductions of greenhouse gas emissions are mandatory but not sufficient. Large-scale deployment of other climate mitigation strategies are also necessary. Among these, increasing soil organic carbon (SOC) stocks is an important lever because carbon in soils can be stored for long periods and land management options to achieve this already exist and have been widely tested. However, agricultural soils are also an important source of nitrous oxide (N2 O), a powerful greenhouse gas, and increasing SOC may influence N2 O emissions, likely causing an increase in many cases, thus tending to offset the climate change benefit from increased SOC storage. Here, we review the main agricultural management options for increasing SOC stocks. We evaluate the amount of SOC that can be stored as well as resulting changes in N2 O emissions to better estimate the climate benefits of these management options. Based on quantitative data obtained from published meta-analyses and from our current level of understanding, we conclude that the climate mitigation induced by increased SOC storage is generally overestimated if associated N2 O emissions are not considered but, with the exception of reduced tillage, is never fully offset. Some options (e.g, biochar or non-pyrogenic C amendment application) may even decrease N2 O emissions.

Grasslands absorb and release carbon dioxide (CO2), emit methane (CH4) from grazing livestock, and emit nitrous oxide (N2O) from soils. Little is known about how the fluxes of these three greenhouse gases, from managed and natural grasslands worldwide, have contributed to past climate change, or the roles of managed pastures versus natural grasslands. Here, global trends and regional patterns of the full greenhouse gas balance of grasslands are estimated for the period 1750 to 2012. A new spatially explicit land surface model is applied, to separate the direct effects of human activities from land management and the indirect effects from climate change, increasing CO2 and regional changes in nitrogen deposition. Direct human management activities are simulated to have caused grasslands to switch from a sink to a source of greenhouse gas, because of increased livestock numbers and accelerated conversion of natural lands to pasture. However, climate change drivers contributed a net carbon sink in soil organic matter, mainly from the increased productivity of grasslands due to increased CO2 and nitrogen deposition. The net radiative forcing of all grasslands is currently close to neutral, but has been increasing since the 1960s. Here, we show that the net global climate warming caused by managed grassland cancels the net climate cooling from carbon sinks in sparsely grazed and natural grasslands. In the face of future climate change and increased demand for livestock products, these findings highlight the need to use sustainable management to preserve and enhance soil carbon storage in grasslands and to reduce greenhouse gas emissions from managed grasslands.

Uncertainties, risks, and disequilibrium are pervasive characteristics of modern socio-economic, technological, and environmental systems involving interactions between humans, economics, technology and nature. The systems are characterized by interdependencies, discontinuities, endogenous risks and thresholds, requiring nonsmooth quantile-based performance indicators, goals and constraints for their analysis and planning. The paper discusses the need for the two-stage stochastic optimization and the stochastic quasigradient (SQG) procedures to manage such systems. The two-stage optimization enables designing a robust portfolio of interdependent precautionary strategic and adaptive operational decisions making the systems robust with respect to potential uncertainty and risks. The SQG iterative algorithms define a “searching” process, which resembles a sequential adaptive learning and improvement of decisions from data and simulations, i.e. the so-called Adaptive Monte Carlo optimization. The SQG methods are applicable in cases when traditional stochastic approximation, gradient or stochastic gradient methods do not work, in particular, to general two-stage problems with implicitly defined goals and constraints functions, nonsmooth and possibly discontinuous performance indicators, risk and uncertainties shaped by decision of various agents. Stylized models from statistics, machine learning, robust decision making are presented to illustrate the two-stage (strategic-adaptive) modeling concept and the SQG procedures. The stylized models are parts of larger integrated assessment models developed at IIASA, e.g. Global Biosphere Management model (GLOBIOM) and Integrated Catastrophe Risk Management model (ICRIM).

The possibility of using the elemental compositions of species as a tool to identify species/genotype niche remains to be tested at a global scale. We investigated relationships between the foliar elemental compositions (elementomes) of trees at a global scale with phylogeny, climate, N deposition and soil traits. We analysed foliar N, P, K, Ca, Mg and S concentrations in 23,962 trees of 227 species. Shared ancestry explained 60–94% of the total variance in foliar nutrient concentrations and ratios whereas current climate, atmospheric N deposition and soil type together explained 1–7%, consistent with the biogeochemical niche hypothesis which predicts that each species will have a specific need for and use of each bio-element. The remaining variance was explained by the avoidance of nutritional competition with other species and natural variability within species. The biogeochemical niche hypothesis is thus able to quantify species-specific tree niches and their shifts in response to environmental changes.

To meet the ambitious objectives of biodiversity and climate conventions, countries and the international community require clarity on how these objectives can be operationalized spatially, and multiple targets be pursued concurrently1. To support governments and political conventions, spatial guidance is needed to identify which areas should be managed for conservation to generate the greatest synergies between biodiversity and nature’s contribution to people (NCP). Here we present results from a joint optimization that maximizes improvements in species conservation status, carbon retention and water provisioning and rank terrestrial conservation priorities globally. We found that, selecting the top-ranked 30% (respectively 50%) of areas would conserve 62.4% (86.8%) of the estimated total carbon stock and 67.8% (90.7%) of all clean water provisioning, in addition to improving the conservation status for 69.7% (83.8%) of all species considered. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to improve the conservation status of 86.3% of plant and vertebrate species on Earth. Our results provide a global baseline on where land could be managed for conservation. We discuss how such a spatial prioritisation framework can support the implementation of the biodiversity and climate conventions.

Contains fulltext : 228862.pdf (Publisher’s version ) (Open Access)

Regional monitoring, reporting and verification of soil organic carbon change occurring in managed cropland are indispensable to support carbon-related policies. Rapidly evolving gridded agronomic models can facilitate these efforts throughout Europe. However, their performance in modelling soil carbon dynamics at regional scale is yet unexplored. Importantly, as such models are often driven by large-scale inputs, they need to be benchmarked against field experiments. We elucidate the level of detail that needs to be incorporated in gridded models to robustly estimate regional soil carbon dynamics in managed cropland, testing the approach for regions in the Czech Republic. We first calibrated the biogeochemical Environmental Policy Integrated Climate (EPIC) model against long-term experiments. Subsequently, we examined the EPIC model within a top-down gridded modelling framework constructed for European agricultural soils from Europe-wide datasets and regional land-use statistics. We explored the top-down, as opposed to a bottom-up, modelling approach for reporting agronomically relevant and verifiable soil carbon dynamics. In comparison with a no-input baseline, the regional EPIC model suggested soil carbon changes (~0.1–0.5 Mg C ha−1 y−1) consistent with empirical-based studies for all studied agricultural practices. However, inaccurate soil information, crop management inputs, or inappropriate model calibration may undermine regional modelling of cropland management effect on carbon since each of the three components carry uncertainty (~0.5–1.5 Mg C ha−1 y−1) that is substantially larger than the actual effect of agricultural practices relative to the no-input baseline. Besides, inaccurate soil data obtained from the background datasets biased the simulated carbon trends compared to observations, thus hampering the model's verifiability at the locations of field experiments. Encouragingly, the top-down agricultural management derived from regional land-use statis

The Social Cost of Carbon (SCC) is estimated by integrated assessment models and is widely used by government agencies to value the climate impacts of rulemakings, however, the core discussion around SCC so far was focused on validity of obtained numerical estimates and related uncertainties while largely neglecting a deeper discussion of the SCC applicability limits stemming from the calculation method. This work provides a conceptual mathematical background and the economic interpretation that is behind the SCC calculation in the three widely used integrated assessment models. Policy makers need to be aware of the difference between the commonly implied and the actual meaning of SCC that substantially limits its applicability in practice. The presented results call for a critical revision of the SCC concept and the SCC calculation methods in integrated assessment models.

Background: The quantity, quality, and type (e.g., animal and vegetable) of human food have been correlated with human health, although with some contradictory or neutral results. We aimed to shed light on this association by using the integrated data at country level. Methods: We correlated elemental (nitrogen (N) and phosphorus (P)) compositions and stoichiometries (N:P ratios), molecular (proteins) and energetic traits (kilocalories) of food of animal (terrestrial or aquatic) and vegetable origin, and alcoholic beverages with cancer prevalence and mortality and life expectancy (LE) at birth at the country level. We used the official databases of United Nations (UN), Food and Agriculture Organization of the United Nations (FAO), Organization for Economic Co-operation and Development (OECD), World Bank, World Health Organization (WHO), U.S. Department of Agriculture, U.S. Department of Health, and Eurobarometer, while also considering other possibly involved variables such as income, mean age, or human development index of each country. Results: The per capita intakes of N, P, protein, and total intake from terrestrial animals, and especially alcohol were significantly and positively associated with prevalence and mortality from total, colon, lung, breast, and prostate cancers. In contrast, high per capita intakes of vegetable N, P, N:P, protein, and total plant intake exhibited negative relationships with cancer prevalence and mortality. However, a high LE at birth, especially in underdeveloped countries was more strongly correlated with a higher intake of food, independent of its animal or vegetable origin, than with other variables, such as higher income or the human development index. Conclusions: Our analyses, thus, yielded four generally consistent conclusions. First, the excessive intake of terrestrial animal food, especially the levels of protein, N, and P, is associated with higher prevalence of cancer, whereas equivalent intake from vegetables is associat

Traditional agricultural extension services rely on extension workers, especially in countries with large agricultural areas. In order to increase adoption of sustainable agriculture, the recommendations given by such services must be adapted to local conditions and be provided in a timely manner. The AgroTutor mobile application was built to provide highly specific and timely agricultural recommendations to farmers across Mexico and complement the work of extension agents. At the same time, AgroTutor provides direct contributions to the United Nations Sustainable Development Goals, either by advancing their implementation or providing local data systems to measure and monitor specific indicators such as the proportion of agricultural area under productive and sustainable agriculture. The application is freely available and allows farmers to geo-locate and register plots and the crops grown there, using the phone’s in-built GPS, or alternatively, on top of very high-resolution imagery. Once a crop and some basic data such as planting date and cultivar type have been registered, the app provides targeted information such as weather, potential and historical yield, financial benchmarking information, data-driven recommendations as well as commodity price forecasts. Farmers are also encouraged to contribute in-situ information, e.g., soils, management, and yield data. The information can then be used by crop models, which, in turn, would send tailored results back to the farmers. Initial feedback from farmers and extension agents has already improved some of the app’s characteristics. More enhancements are planned for inclusion in the future to increase the app’s function as a decision support tool.

Despite the scientific consensus on the extinction crisis and its anthropogenic origin, the quantification of historical trends and of future scenarios of biodiversity and ecosystem services has been limited, due to the lack of inter-model comparisons and harmonized scenarios. Here, we present a multi-model analysis to assess the impacts of land-use and climate change from 1900 to 2050. During the 20th century provisioning services increased, but biodiversity and regulating services decreased. Similar trade-offs are projected for the coming decades, but they may be attenuated in a sustainability scenario. Future biodiversity loss from land-use change is projected to keep up with historical rates or reduce slightly, whereas losses due to climate change are projected to increase greatly. Renewed efforts are needed by governments to meet the 2050 vision of the Convention on Biological Diversity.

This archive contains input data and computer code to reproduce land use change outputs for the Maximum Land Sparing scenario of the publication "Folberth et al., The global cropland sparing potential of high-yield farming". Code is written in GAMS and R and requires parallel Windows and Linux environments. Further information and instructions are provided in the enclosed 0-readme.txt.

These webpages document the IIASA Integrated Assessment Modeling (IAM) framework, also referred to as MESSAGEix-GLOBIOM. MESSAGEix-GLOBIOM is a global model, covering 11 world regions and was originally developed for the quantification of the so-called Shared Socio-economic Pathways (SSPs). The documentation includes information on the spatial and temporal structure of the model, the socio-economic drivers, the energy supply and demand sector representation, the agriculture, forest and other land-use component, and the macro-economic and climate modules. It also links to the underlying MESSAGEix mathematical modeling framework which includes information on the equations governing the model dynamics.

Food system innovations will be instrumental to achieving multiple Sustainable Development Goals (SDGs). However, major innovation breakthroughs can trigger profound and disruptive changes, leading to simultaneous and interlinked reconfigurations of multiple parts of the global food system. The emergence of new technologies or social solutions, therefore, have very different impact profiles, with favourable consequences for some SDGs and unintended adverse side-effects for others. Stand-alone innovations seldom achieve positive outcomes over multiple sustainability dimensions. Instead, they should be embedded as part of systemic changes that facilitate the implementation of the SDGs. Emerging trade-offs need to be intentionally addressed to achieve true sustainability, particularly those involving social aspects like inequality in its many forms, social justice, and strong institutions, which remain challenging. Trade-offs with undesirable consequences are manageable through the development of well planned transition pathways, careful monitoring of key indicators, and through the implementation of transparent science targets at the local level.

Leaf-level net photosynthesis (An) estimates and associated photosynthetic parameters are crucial for accurately parameterizing photosynthesis models. For tropical forests, such data are poorly available and collected at variable light conditions. To avoid over- or underestimation of modeled photosynthesis, it is critical to know at which photosynthetic photon flux density (PPFD) photosynthesis becomes light-saturated. We studied the dependence of An on PPFD in two tropical forests in French Guiana. We estimated the light saturation range, including the lowest PPFD level at which Asat (An at light saturation) is reached, as well as the PPFD range at which Asat remained unaltered. The light saturation range was derived from photosynthetic light-response curves, and within-canopy and interspecific differences were studied. We observed wide light saturation ranges of An. Light saturation ranges differed among canopy heights, but a PPFD level of 1,000 µmol m−2 s−1 was common across all heights, except for pioneer trees species that did not reach light saturation below 2,000 µmol m−2 s−1. A light intensity of 1,000 µmol m−2 s−1 sufficed for measuring Asat of climax species at our study sites, independent of the species or the canopy height. Because of the wide light saturation ranges, results from studies measuring Asat at higher PPFD levels (for upper canopy leaves up to 1,600 µmol m−2 s−1) are comparable with studies measuring at 1,000 µmol m−2 s−1. © 2020 The Association for Tropical Biology and Conservation

In recent years, the crop growth modeling community invested immense effort into high resolution global simulations estimating inter alia the impacts of projected climate change. The demand for computing resources in this context is high and expressed in processor core-years per one global simulation, implying several crops, management systems, and a several decades time span for a single climatic scenario. The anticipated need to model a richer set of alternative management options and crop varieties would increase the processing capacity requirements even more, raising the looming issue of computational efficiency. While several publications report on the successful application of the original field-scale crop growth model EPIC (Environmental Policy Integrated Climate) for running on modern supercomputers, the related performance improvement issues and, especially, associated trade-offs have only received, so far, limited coverage. This paper provides a comprehensive view on the principles of the EPIC setup for parallel computations and, for the first time, on those specific to heterogeneous compute clusters that are comprised of desktop computers utilizing their idle time to carry out massive computations. The suggested modification of the core EPIC model allows for a dramatic performance increase (order of magnitude) on a compute cluster that is powered by the open-source high-throughput computing software framework HTCondor.