Spatially explicit cropland greenhouse gas (GHG) emissions and management data are crucial for developing effective climate change mitigation strategies and promoting sustainable agricultural practices. This study presents high-resolution (5 arc-minute) global maps of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) emissions from agricultural activities across 46 crops circa 2020, referred to as emissions from croplands. Emission sources include synthetic nitrogen fertilizer use, manure application, crop residue incorporation, in-field residue burning, rice cultivation, and drained peatlands for cropping. Our findings indicate that global GHG emissions from croplands reached 2.7 Gt CO₂e in 2020, with drained peatlands (35%), rice paddies (35%), and synthetic N fertilizer (22%) as the primary contributors. The four major crop contributors-rice, maize, oil palm, and wheat-accounted for about 60% of total emissions. These results provide critical insights for effectively targeting GHG mitigation efforts and identifying key regions and crops within high-emission countries, enabling more precise and impactful climate action.

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.

Quantifying the effect of thermal stress on milk yields is essential to effectively manage present and future risks in dairy systems. Despite the existence of numerous heat indices designed to communicate stress thresholds, little information is available regarding the accuracy of different indices in estimating milk yield losses from both cold and heat stress at large spatiotemporal scales. To address this gap, we comparatively analyzed the performance of existing thermal indices in capturing US milk yield response to both cold and heat stress at the national scale. We selected 4 commonly used thermal indices: the temperature-humidity index (THI), black globe humidity index (BGHI), adjusted temperature-humidity index (THIadj), and comprehensive climate index (CCI). Using a statistical panel regression model with observational and reanalysis weather data from 1981 to 2020, we systematically compared the patterns of yield sensitivities and statistical performance of the 4 indices. We found that the US state-level milk yield variability was better explained by the THIadj and CCI, which combine the effects of temperature, humidity, wind, and solar radiation. Our analysis also reveals continuous and nonlinear responses of milk yields to a range of cold to heat stresses across all 4 indices. This implies that solely relying on fixed thresholds of these indices to model milk yield changes may be insufficient to capture cumulative thermal stress. Cold extremes reduced milk yields comparably to those affected by heat extremes on the national scale. Additionally, we found large spatial variability in milk yield sensitivities, implying further limitations to the use of fixed thresholds across locations. Moreover, we found decreased yield sensitivity to thermal stress in the most recent 2 decades, suggesting adaptive changes in management to reduce weather-related risks.

Agriculture’s global environmental impacts are widely expected to continue expanding, driven by population and economic growth and dietary changes. This Review highlights climate change as an additional amplifier of agriculture’s environmental impacts, by reducing agricultural productivity, reducing the efficacy of agrochemicals, increasing soil erosion, accelerating the growth and expanding the range of crop diseases and pests, and increasing land clearing. We identify multiple pathways through which climate change intensifies agricultural greenhouse gas emissions, creating a potentially powerful climate change–reinforcing feedback loop. The challenges raised by climate change underscore the urgent need to transition to sustainable, climate-resilient agricultural systems. This requires investments that both accelerate adoption of proven solutions that provide multiple benefits, and that discover and scale new beneficial processes and food products.

Hydroclimatic stresses can negatively impact crop production via water deficits (low soil water supply and high atmospheric demand) or surpluses (high soil water supply and low atmospheric demand). However, the impact of both stresses on crop yields at regional scales is not well understood. Here we quantified yield sensitivities and corresponding spatio-temporal yield losses of US rainfed maize, soybeans, sorghum, and spring wheat to hydroclimatic stresses by considering the joint impacts of root-zone soil moisture and atmospheric evaporative demand from 1981 to 2020. We show that crop yields can be reduced similarly by two major hydroclimatic hazards, which are defined as the most yield damaging conditions over time: ‘Low Supply + High Demand’ and ‘High Supply + Low Demand’. However, more exposure to ‘Low Supply + High Demand’ hazard led to the largest annual yield losses (7%–17%) across all four crops over time. Modeled yield losses due to these hazards were significantly associated with crop insurance lost costs. The extent of yield losses varies considerably by crop and location, highlighting the need for crop-specific and regionally tailored adaptation strategies.

Irrigation reduces crop vulnerability to drought and heat stress and thus is a promising climate change adaptation strategy. However, irrigation also produces greenhouse gas emissions through pump energy use. To assess potential conflicts between adaptive irrigation expansion and agricultural emissions mitigation efforts, we calculated county-level emissions from irrigation energy use in the US using fuel expenditures, prices, and emissions factors. Irrigation pump energy use produced 12.6 million metric tonnes CO 2 e in the US in 2018 (90% CI: 10.4, 15.0), predominantly attributable to groundwater pumping. Groundwater reliance, irrigated area extent, water demand, fuel choice, and electrical grid emissions intensity drove spatial heterogeneity in emissions. Due to heavy reliance on electrical pumps, projected reductions in electrical grid emissions intensity are estimated to reduce pumping emissions by 46% by 2050, with further reductions possible through pump electrification. Quantification of irrigation-related emissions will enable targeted emissions reduction efforts and climate-smart irrigation expansion.

Over the next three decades rising population and changing dietary preferences are expected to increase food demand by 25%–75%. At the same time climate is also changing—with potentially drastic impacts on food production. Breeding new crop characteristics and adjusting management practices are critical avenues to mitigate yield loss and sustain yield stability under a changing climate. In this study, we use a mechanistic crop model (MAIZSIM) to identify high-performing trait and management combinations that maximize yield and yield stability for different agroclimate regions in the US under present and future climate conditions. We show that morphological traits such as total leaf area and phenological traits such as grain-filling start time and duration are key properties that impact yield and yield stability; different combinations of these properties can lead to multiple high-performing strategies under present-day climate conditions. We also demonstrate that high performance under present day climate does not guarantee high performance under future climate. Weakened trade-offs between canopy leaf area and reproductive start time under a warmer future climate led to shifts in high-performing strategies, allowing strategies with higher total leaf area and later grain-filling start time to better buffer yield loss and out-compete strategies with a smaller canopy leaf area and earlier reproduction. These results demonstrate that focused effort is needed to breed plant varieties to buffer yield loss under future climate conditions as these varieties may not currently exist, and showcase how information from process-based models can complement breeding efforts and targeted management to increase agriculture resilience.

Irrigation effectively increases yields and buffers against intensifying climatic stressors to crop productivity but also produces greenhouse gas (GHG) emissions through several pathways including energy use for pumping (on farm and for interbasin water transfers), N2O emissions from increased denitrification under elevated soil moisture, and degassing of groundwater supersaturated in CO2. Despite irrigation's climate adaptation potential, associated GHG emissions remain unquantified. Here we conduct a comprehensive, county-level assessment of US GHG emissions from these irrigation-related pathways, estimating that irrigation produces 18.9 MtCO2e annually (95% confidence interval 15.2-23.5 Mt), with 12.6 Mt from on-farm pumping, 1.1 Mt from pumping for interbasin transfers, 2.9 Mt from elevated N2O and 2.4 Mt from groundwater degassing. These emissions are highly spatially concentrated, revealing opportunities for geographically targeted and source-specific GHG mitigation actions. These findings enable strategic consideration of GHG emissions in decision-making associated with irrigation expansion for climate adaptation.

Projected increases in food demand driven by population growth coupled with heightened agricultural vulnerability to climate change jointly pose severe threats to global food security in the coming decades, especially for developing nations. By providing real-time and low-cost observations, satellite remote sensing has been widely employed to estimate crop yield across various scales. Most such efforts are based on statistical approaches that require large amounts of ground measurements for model training/calibration, which may be challenging to obtain on a large scale in developing countries that are most food-insecure and climate-vulnerable. In this paper, we develop a generalizable framework that is mechanism-guided and practically parsimonious for crop yield estimation. We then apply this framework to estimate crop yield for two crops (corn and wheat) in two contrasting regions, the US Corn Belt US-CB, and India’s Indo–Gangetic plain Wheat Belt IGP-WB, respectively. This framework is based on the mechanistic light reactions (MLR) model utilizing remotely sensed solar-induced chlorophyll fluorescence (SIF) as a major input. We compared the performance of MLR to two commonly used machine learning (ML) algorithms: artificial neural network and random forest. We found that MLR-SIF has comparable performance to ML algorithms in US-CB, where abundant and high-quality ground measurements of crop yield are routinely available (for model calibration). In IGP-WB, MLR-SIF significantly outperforms ML algorithms. These results demonstrate the potential advantage of MLR-SIF for yield estimation in developing countries where ground truth data is limited in quantity and quality. In addition, high-resolution and crop-specific satellite SIF is crucial for accurate yield estimation. Therefore, harnessing the mechanism-guided MLR-SIF and rapidly growing satellite SIF measurements (with high resolution and crop-specificity) hold promise to enhance food security in developing countries towards more effective responses to food crises, agricultural policies, and more efficient commodity pricing.

Agricultural irrigation induces greenhouse gas emissions directly from soils or indirectly through the use of energy or construction of dams and irrigation infrastructure, while climate change affects irrigation demand, water availability and the greenhouse gas intensity of irrigation energy. Here, we present a scoping review to elaborate on these irrigation-climate linkages by synthesizing knowledge across different fields, emphasizing the growing role climate change may have in driving future irrigation expansion and reinforcing some of the positive feedbacks. This Review underscores the urgent need to promote and adopt sustainable irrigation, especially in regions dominated by strong, positive feedbacks.

Heat stress (HS) during the dry period can affect animal welfare, health, dry matter intake (DMI), and milk production in the subsequent lactation, which will negatively affect the profitability of dairy farms. In this study, the objective was to model the changes in DMI in pregnant nonlactating heat-stressed dairy cows with or without access to evaporative cooling systems. A database was built, composed of individual DMI re-cords from 244 pregnant nonlactating dairy cows from an average -29.3 d (range: -42 to -21 d; SD: +/- 7.54 d) to -1 d relative to calving (DRC) and housed in en-vironmental conditions in which temperature-humidity index (THI) ranged from 58.4 to 83.3, with or without access to evaporative cooling systems. Generalized ad-ditive mixed-effects models were used to describe the relationships of DMI with HS and DRC. Changes in DMI with the increase in THI and the progression of pregnancy in cows with or without evaporative cooling systems were estimated using differential equations. On average, cows housed in barns without evaporative cooling systems had a reduction in DMI of 1.30 kg/d and increased rectal temperature in 0.22 degrees C in relation to those housed in barns with evaporative cooling sys-tems. Dry matter intake decreased as THI increased, but the reduction was greater for noncooled cows as THI values increased. In addition, regardless of the THI, DMI started to decrease at -14 DRC for cooled cows, whereas for noncooled cows it already started at -30 DRC, relative to the previous days evaluated. The intensity of the reduction was lesser for cows that had access to evaporative cooling systems or were in the dry period in May to June as compared with those that were in the dry period in July to August or September to October. The models generated in this study, which include environmental variables, should lead to more accurate predictions of DMI during HS that can be used to formulate diets to meet the needs of the late pregnant cow because it is possible to predict changes in DMI as the heat load and DRC change. Such models are also expected to help dairy nutritionists to decide when and how to apply the dietary strategies available to attenuate the reductions in DMI with the intensity of HS and progression of pregnancy.

Earthworms are critical soil ecosystem engineers that support plant growth in numerous ways; however, their contribution to global agricultural production has not been quantified. We estimate the impacts of earthworms on global production of key crops by analyzing maps of earthworm abundance, soil properties, and crop yields together with earthworm-yield responses from the literature. Our findings indicate that earthworms contribute to roughly 6.5% of global grain (maize, rice, wheat, barley) production and 2.3% of legume production, equivalent to over 140 million metric tons annually. The earthworm contribution is especially notable in the global South, where earthworms contribute 10% of total grain production in Sub-Saharan Africa and 8% in Latin America and the Caribbean. Our findings suggest that earthworms are important drivers of global food production and that investment in agroecological policies and practices to support earthworm populations and overall soil biodiversity could contribute greatly to sustainable agricultural goals.

In our globalized world, local impacts of agricultural production are increasingly driven by consumption in geographi-cally distant places. Current agricultural systems strongly rely on nitrogen (N) fertilization to increase soil fertility and crop yields. Yet, a large portion of N added to cropland is lost through leaching / runoff potentially leading to eutro-phication in coastal ecosystems. By coupling data on global production and N fertilization for 152 crops with a Life Cycle Assessment (LCA)-based model, we first estimated the extent of oxygen depletion occurring in 66 Large Marine Ecosystems (LMEs) due to agricultural production in the watersheds draining into these LMEs. We then linked this in-formation to crop trade data to assess the displacement from consuming to producing countries, in terms of oxygen de-pletion impacts associated to our food systems. In this way, we characterized how impacts are distributed between traded and domestically sourced agricultural products. We found that few countries dominate global impacts and that cereal and oil crop production accounts for the bulk of oxygen depletion impacts. Globally, 15.9 % of total oxygen depletion impacts of crop production are ascribable to export-driven production. However, for exporting countries like Canada, Argentina or Malaysia this share is much higher, often up to three-quarters of their production impacts. In some importing countries, trade contributes to reduce pressure on already highly affected coastal ecosystems. This is the case for countries whose domestic crop production is associated with high oxygen depletion intensities, i.e. the impact per kcal produced, such as Japan or South Korea. Next to these positive effects trade can play in lowering overall environmental burdens, our results also highlight the importance of a holistic food system perspective when aiming to reduce the oxygen depletion impacts of crop production.

Irrigation accounts for ~70% of global freshwater withdrawals and ~90% of consumptive water use, driving myriad Earth system impacts. In this Review, we summarize how irrigation currently impacts key components of the Earth system. Estimates suggest that more than 3.6 million km2 of currently irrigated land, with hot spots in the intensively cultivated US High Plains, California Central Valley, Indo-Gangetic Basin and northern China. Process-based models estimate that ~2,700 ± 540 km3 irrigation water is withdrawn globally each year, broadly consistent with country-reported values despite these estimates embedding substantial uncertainties. Expansive irrigation has modified surface energy balance and biogeochemical cycling. A shift from sensible to latent heat fluxes, and resulting land–atmosphere feedbacks, generally reduce regional growing season surface temperatures by ~1–3 °C. Irrigation can ameliorate temperature extremes in some regions, but conversely exacerbates moist heat stress. Modelled precipitation responses are more varied, with some intensive cropping regions exhibiting suppressed local precipitation but enhanced precipitation downstream owing to atmospheric circulation interactions. Additionally, irrigation could enhance cropland carbon uptake; however, it can also contribute to elevated methane fluxes in rice systems and mobilize nitrogen loading to groundwater. Cross-disciplinary, integrative research efforts can help advance understanding of these irrigation–Earth system interactions, and identify and reduce uncertainties, biases and limitations. Irrigation accounts for a substantial proportion of global water usage and can have biophysical and biogeochemical impacts on Earth systems. This Review outlines key irrigation–Earth system interactions, and discusses the effect of future climate and socioeconomic changes on irrigation patterns and their interaction.

Wildfires are a growing concern to society and the environment in many parts of the world. Within the United States, the land area burned by wildfires has steadily increased over the past 40 years. Agricultural land management is widely understood as a force that alters fire regimes, but less is known about how wildfires, in turn, impact the agriculture sector. Based on an extensive literature review, we identify three pathways of impact—direct, downwind and downstream—through which wildfires influence agricultural resources (soil, water, air and photosynthetically active radiation), labour (agricultural workers) and products (crops and livestock). Through our pathways framework, we highlight the complexity of wildfire–agriculture interactions and the need for collaborative, systems-oriented research to better quantify the magnitude of wildfire impacts and inform the adaptation of agricultural systems to an increasingly fire-prone future.

National-level governments are directing and funding climate adaptation research, which is essential to informing effective and equitable adaptation practices. We sought to understand how United States (US) federal agencies prioritize, direct, and fund research related to climate adaptation and climate resilience through analyzing climate action plans created in 2021 by 13 agencies who are members of the US Global Change Research Program. We examine: (1) agencies' stated climate adaptation research priorities; (2) how agencies address collaboration, outreach, accessibility, and usability of research outcomes; and (3) agencies' adaptation research funding opportunities. We argue that certain research needs, justice and equity considerations, and interdisciplinary research should be emphasized to a greater degree. While adaptation research capacity and funding opportunities are expanding, they remain inadequate for the scale of research needed.Key policy insightsUS federal agencies vary in their integration of research as a core component of their climate adaptation plans, but most prioritize research that is relevant and accessible to stakeholders and decision-makers.While all agencies addressed environmental justice, some could more substantially incorporate justice considerations into their climate adaptation research.Adaptation research and strategies should ensure that collaborations are inclusive and sustainable and would benefit from meaningful and respectful collaboration with tribes and Indigenous Peoples, as well as marginalized and under-represented groups.Multidisciplinary research is key to climate adaptation and should be enhanced through increasing funding support for crosscutting programmes.