James Gerber’s research while affiliated with University of Minnesota Duluth and other places

Yield gaps, here defined as the difference between actual and attainable yields, provide a framework for assessing opportunities to increase agricultural productivity. Previous global assessments, centred on a single year, were unable to identify temporal variation. Here we provide a spatially and temporally comprehensive analysis of yield gaps for ten major crops from 1975 to 2010. Yield gaps have widened steadily over most areas for the eight annual crops and remained static for sugar cane and oil palm. We developed a three-category typology to differentiate regions of ‘steady growth’ in actual and attainable yields, ‘stalled floor’ where yield is stagnated and ‘ceiling pressure’ where yield gaps are closing. Over 60% of maize area is experiencing ‘steady growth’, in contrast to ∼12% for rice. Rice and wheat have 84% and 56% of area, respectively, experiencing ‘ceiling pressure’. We show that ‘ceiling pressure’ correlates with subsequent yield stagnation, signalling risks for multiple countries currently realizing gains from yield growth.

Working paper analysing the economic implications of the proposed 30% target for areal protection in the draft post-2020 Global Biodiversity Framework

Agricultural and livestock production involves significant trade-offs between multiple sustainable development goals, including reducing hunger and poverty, and reducing emissions of greenhouse gasses. Here we describe a multi-objective optimization tool for livestock production to evaluate trade-offs among environmental and economic objectives with high spatial granularity and the capability to be aggregated to national or global scales. We illustrate the use of this tool analysing how and where to produce beef to optimize the weighted sum of environmental and economic objectives, in this case minimizing greenhouse gas emissions and minimizing costs of production. We present how the outputs of this model can inform a sustainable transition of the industry and policy decisions, with a focus on inherent trade-offs. By comparing optimal production with current production, we highlight the potential environmental and economic efficiencies that can be made by changing the location or methods of production. As such, this tool provides a platform to identify trade-offs and synergies among multiple diverse sustainability goals, critical in the livestock and agricultural sectors.

Beef production represents a complex global sustainability challenge including reducing poverty and hunger and the need for climate action. Understanding the trade-offs between these goals at a global scale and at resolutions to inform land use is critical for a global transition towards sustainable beef. Here we optimize global beef production at fine spatial resolution and identify trade-offs between economic and environmental objectives interpretable to global sustainability ambitions. We reveal that shifting production areas, compositions of current feeds and informed land restoration enable large emissions reductions of 34–85% annually (612–1,506 MtCO2e yr−1) without increasing costs. Even further reductions are possible but come at a trade-off with costs of production. Critically our approach can help to identify such trade-offs among multiple sustainability goals, produces fine-resolution mapping to inform required land-use change and does so at the scale necessary to shift towards a globally sustainable industry for beef and to sectors beyond. Producing beef sustainably at a global level is a challenge given the multiple trade-offs between the economic and environmental objectives involved. This study presents an approach that helps to identify such trade-offs at the scale needed for the beef industry to become more sustainable.

Background: Animal pollination supports agricultural production for many healthy foods, such as fruits, vegetables, nuts, and legumes, that provide key nutrients and protect against noncommunicable disease. Today, most crops receive suboptimal pollination because of limited abundance and diversity of pollinating insects. Animal pollinators are currently suffering owing to a host of direct and indirect anthropogenic pressures: land-use change, intensive farming techniques, harmful pesticides, nutritional stress, and climate change, among others. Objectives: We aimed to model the impacts on current global human health from insufficient pollination via diet. Methods: We used a climate zonation approach to estimate current yield gaps for animal-pollinated foods and estimated the proportion of the gap attributable to insufficient pollinators based on existing research. We then simulated closing the "pollinator yield gaps" by eliminating the portion of total yield gaps attributable to insufficient pollination. Next, we used an agriculture-economic model to estimate the impacts of closing the pollinator yield gap on food production, interregional trade, and consumption. Finally, we used a comparative risk assessment to estimate the related changes in dietary risks and mortality by country and globally. In addition, we estimated the lost economic value of crop production for three diverse case-study countries: Honduras, Nepal, and Nigeria. Results: Globally, we calculated that 3%-5% of fruit, vegetable, and nut production is lost due to inadequate pollination, leading to an estimated 427,000 (95% uncertainty interval: 86,000, 691,000) excess deaths annually from lost healthy food consumption and associated diseases. Modeled impacts were unevenly distributed: Lost food production was concentrated in lower-income countries, whereas impacts on food consumption and mortality attributable to insufficient pollination were greater in middle- and high-income countries with higher rates of noncommunicable disease. Furthermore, in our three case-study countries, we calculated the economic value of crop production to be 12%-31% lower than if pollinators were abundant (due to crop production losses of 3%-19%), mainly due to lost fruit and vegetable production. Discussion: According to our analysis, insufficient populations of pollinators were responsible for large present-day burdens of disease through lost healthy food consumption. In addition, we calculated that low-income countries lost significant income and crop yields from pollinator deficits. These results underscore the urgent need to promote pollinator-friendly practices for both human health and agricultural livelihoods. https://doi.org/10.1289/EHP10947.

Background Animal pollination supports agricultural production for many healthy foods, such as fruits, vegetables, nuts, and legumes, which provide key nutrients and protect against non-communicable diseases. Today, most crops receive suboptimal pollination because of reduced abundance and diversity of pollinating insects. Methods We modelled the effects on current global human health from insufficient pollination by quantifying the pollinator-related crop yield gap and lost consumption of pollination-dependent foods by country and region, after accounting for global trade, economic behaviours, and food waste. We also estimated the lost economic value of crop production for the following three diverse case-study countries: Honduras, Nepal, and Nigeria. Findings Globally, we found that we are currently losing 3–5% of fruit, vegetable, and nut production per year because of inadequate pollination, leading to a median estimated 427 000 (95% uncertainty interval 86 000–691 000) excess deaths annually from lost healthy food consumption and associated diseases. Effects are unevenly distributed; lost food production is concentrated in low-income countries, while impacts on food consumption and mortality attributable to insufficient pollination are greater in middle-income and high-income countries with higher rates of non-communicable diseases. Furthermore, in our three case-study countries, we found that the economic value of crop production was 12–31% lower than if pollinators were abundant (because of crop production losses of 3–19%), mainly due to lost fruit and vegetable production. Interpretation Insufficient populations of pollinators are responsible for large burdens of disease through lost healthy food consumption. Furthermore, low-income countries are losing substantial income and crop yields from pollinator deficits. These results underscore the urgent need to promote pollinator-friendly practices for both human health and agricultural livelihoods. Funding Gordon & Betty Moore Foundation, Weston Foods, Fifth Generation, CGIAR, United States Agency for International Development, Bill & Melinda Gates Foundation, and Wellcome Trust.

Greenhouse gas emissions embodied in international trade have risen sharply over the last few decades because of the globalization of economies and countries’ productive specialization. We have built a model able to trace all agro-food emissions along global value chains for 1986–2013. The results show that while the domestic fraction of food emissions has slightly decreased, the foreign fraction has grown by 75%, accounting for 24% of all agro-food emissions today. A few supply chains concentrate most of this increase, with consumption of animal products explaining 70% of all embodied emissions in trade. It was also found that higher incomes resulted in higher percentages of foreign agro-food emissions, and that increasing the proportion of imports in these footprints can be associated with lower per capita emissions. Because trade increasingly redistributes agro-food emissions around the world, national mitigation efforts should be complemented with strong international and coordinated cooperation actions.

Extreme events, such as those caused by climate change, economic or geopolitical shocks, and pest or disease epidemics, threaten global food security. The complexity of causation, as well as the myriad ways that an event, or a sequence of events, creates cascading and systemic impacts, poses significant challenges to food systems research and policy alike. To identify priority food security risks and research opportunities, we asked experts from a range of fields and geographies to describe key threats to global food security over the next two decades and to suggest key research questions and gaps on this topic. Here, we present a prioritization of threats to global food security from extreme events, as well as emerging research questions that highlight the conceptual and practical challenges that exist in designing, adopting, and governing resilient food systems. We hope that these findings help in directing research funding and resources toward food system transformations needed to help society tackle major food system risks and food insecurity under extreme events.

Agriculture contributes nearly a quarter of global greenhouse gas (GHG) emissions, which is motivating interest in certain farming practices that have the potential to reduce GHG emissions or sequester carbon in soil. The related GHG emission (including N2O and CH4) and changes in soil carbon stock are defined here as “agricultural carbon outcomes”. Accurate quantification of agricultural carbon outcomes is the basis for achieving emission reductions for agriculture, but existing approaches for measuring carbon outcomes (including direct measurements, emission factors, process-based modeling) fall short of achieving the required accuracy and scalability necessary to support credible, verifiable, and cost-effective measurement and improvement of these carbon outcomes. Here we propose a foundational and scalable framework to quantify field-level carbon outcomes for farmland, which is based on the holistic carbon balance of the agroecosystem: Agroecosystem Carbon Outcomes = Crops (C) × Management (M) × Environment (E). Following a comprehensive review of the scientific challenges associated with existing approaches, as well as their tradeoffs between cost and accuracy, we propose that the most viable path for the quantification of field-level carbon outcomes in agricultural land is through an effective integration of various approaches (e.g. diverse observations, sensor/in-situ data, modeling), defined as the “system- of-systems” solution. Such a “system-of-systems” solution should simultaneously comprise the following components: (1) scalable collection of ground truth data and cross-scale sensing of crop conditions (C), management practices (M), and environment (E) at the local field level; (2) advanced modeling with necessary processes to support the quantification of carbon outcomes; (3) systematic Model-Data Fusion (MDF), i.e. robust and efficient methods to integrate sensing data and models at each local farmland level; (4) high computation efficiency and artificial intelligence (AI) to scale to millions of individual fields with low cost; and (5) robust and multi-tier validation systems and infrastructures to ensure solution fidelity and true scalability, i.e. the ability of a solution to perform robustly with accepted accuracy on all targeted fields. In this regard, we provide here the detailed scientific rationale, current progress, and future R&D priorities to achieve different components of the “system-of-systems” solution, thus accomplishing the Crop×Management×Environment framework to quantify field-level agricultural carbon outcomes.