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Natural climate solutions (NCS) offer immediate and cost-effective ways to tackle the climate crisis by transforming atmospheric carbon to soil carbon or avoiding greenhouse gas emissions. However, the climate mitigation potential and economic costs of NCS for cropping systems in China remain inconclusive. The major objectives of this study are (i) to estimate the NGHG reduction potential across Chinese main cropping systems caused by NCS, (ii) to quantify the economic costs of adopting optimal management with different abatement potentials. The Denitrification-Decomposition (DNDC) model was used to estimate the NGHG, including SOC sequestration, N 2 O emissions, and CH 4 emissions. After calibration, we ran the DNDC model with derived data at municipality-level. We estimated the NGHG under current management, adopting optimal management individually, and integrated optimal management to project the maximum NGHG reduction potential caused by NCS. We used the marginal abatement cost method to estimate the economic cost. The four natural climate solutions, N fertilization management (NFM), straw returning management (SRM), tillage management (TM), and rice irrigation management (RIM) can reduce national NGHG in main cropping systems by approximately 118.8 Tg CO 2 -eq, 116.3 Tg CO 2 -eq, 35.2 Tg CO 2 -eq, and 74.4 Tg CO 2 -eq, respectively. The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO 2 -eq, equivalent to 90.2% of current NGHG, and 80% of which can be realized at the price of CN¥ 285 (Mg CO 2 -eq)−1. We further identify the priority NCS for different crops and regions and conclude that nitrogen fertilization management should be the priority NCS at the national level. Our findings highlight the great potential of NGHG reduction by adopting NCS precisely and the importance of optimizing agricultural management as a whole, and they will help policy makers to develop smart-agriculture in China. [Display omitted] • Estimating net greenhouse gas emissions (NGHG) reduction potentials of agriculture. • IPCC recommended tier 3 method was applied for seven cropping systems in China. • The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO 2 -eq. • 80% of NGHG mitigation can be realized at the price of CN¥ 285 (Mg CO 2 -eq)−1. • The priority NCS was identified for different crops and regions. [ABSTRACT FROM AUTHOR]

The agrarian society of the Himalayan landscape is experiencing the continuous growing ill impact of climate change. The impacts are compounding due to shifting agriculture, which has jeopardized the ecological balance mainly by reducing the cultivation fallow cycles. Pnar, a hill tribe of the Assam state, Indian sub-Himalayan region, has transitioned shifting agriculture to Piper agroforestry (Piper betle L.), providing them numerous tangible and non-tangible benefits. Over the past three decades, there has been a notable transition from shifting agriculture to Piper agroforestry, driven by the rising demand in the market. Understanding climate change impact on agroforestry is crucial to addressing the climate crisis and to provision the adaptation of the tribe for the successful promotion of Piper agroforestry. To assess the cause and nature of vulnerability in the study region, we surveyed 171 randomly selected households across 15 randomly selected tribe villages using the household-level questionnaire. The present study showed that the villages with lower land holdings, higher loss of crop productivity due to extreme events, disease infestation and lower livelihood diversification were more vulnerable to climate change. The prominent diseases "leaf spot" and "root rot" were identified as a serious concern among the Piper farmers responsible for a decline in crop yield; the severity of losses in productivity leads to economic instability among households. Villages with prominent farm management strategies and greater decision-making abilities contributed explicitly to lower vulnerability. In contrast, villages with lower adaptive strategies were found specifically due to poor social networking and inadequate household infrastructure besides poor literacy levels. Additionally, the lack of multi-cropping farming and livestock management was a major cause of high climate sensitivity. Therefore, appropriate state government support is required to invest in crop diversification, better decision-making capability of tribes through education, and improved infrastructure besides diversifying the rural economy to enhance the adaptive capacity of the farmers to reduce their climate vulnerability and achieve agriculture-livestock-forestry nexus. The sustainable Piper agroforestry farm management practices represent climate-smart agriculture, favouring high tree species diversity while reducing the farmers' vulnerability to climate change. [Display omitted] • Assessing the climate vulnerability of Piper agroforestry farmers is vital for climate action and underlying adaptive strategies. • We followed the IPCC framework for climate vulnerability assessment. • Villages, namely Nagathal and Munchicherra, show greater sensitivity; Aulicherra and Dholaikhal exhibit higher climate adaptability. • Disease outbreaks in Piper agroforestry pose risks, causing economic disparities. • Piper agroforestry can be considered a nature-based solution for land restoration, economic crisis management, and environmental benefits. [ABSTRACT FROM AUTHOR]

Agroforestry, a sustainable land-use system that integrates trees with crops and/or livestock, is recognized as an effective strategy for synergizing climate change adaptation and mitigation efforts in India. However, the prevalence of limited land under agroforestry indicates the presence of significant constraints hindering its widespread implementation. To address this challenge, the State Action Plan on Climate Change (SAPCC) represents a potentially potent policy tool for driving the expansion of agroforestry at the sub-national level. The aim of this study was to examine (i) how the SAPCCs recognized and reported the benefits of agroforestry for climate change adaptation and mitigation, and (ii) what policy approaches are put forth to operationalize agroforestry in India. For this study, the information on agroforestry was coded using a hybrid approach (a combination of deductive and inductive coding) followed by thematic analysis and peer debriefing (for validation of the generated codes and themes). Many of the mitigation and adaptation benefits of agroforestry are reflected in the SAPCCs. However, the predominant focus of these SAPCCs has been on tree-based agroforestry, with insufficient attention given to the crop-tree-livestock nexus, which could offer greater scope for reducing agricultural emissions. Furthermore, existing constraints to the expansion of agroforestry have not been adequately addressed, and the strategies proposed lack the necessary precision to enable effective implementation on the ground. These shortcomings are further compounded by the absence of accurate budgetary estimates, thereby hindering the ability to execute meaningful actions at the grassroots level. The results of this study could offer valuable perspectives on how the potential benefits of agroforestry may be harnessed more prudently to realize mitigation and adaptation outcomes in India while aligning with the country's Nationally Determined Contributions and building sustainable livelihood. [Display omitted] • India's sub-national climate change action plans acknowledge agroforestry's potential for climate change adaptation and mitigation. • However, the plans primarily focus on adding trees to expand agroforestry and overlook the potential of agrosilvopastoral systems. • The existing constraints of agroforestry adoption in India are not sufficiently addressed, and budget estimates vary significantly among states. • To address these issues, the plans require revision to incorporate specific actions and a clear implementation roadmap. [ABSTRACT FROM AUTHOR]

Global food security faces increasing challenges from the changing climate. Changes of agricultural output from some of the most productive regions such as the US Corn Belt can largely affect the world's food market. Developing predictive understanding of the agricultural risk of climate change and potential mitigation strategies is critical for the global food security. The objective of this study is to assess the responses of maize and soybean yield to projected climate changes in the Corn Belt, identify the shifting environment stressors on crop yield, and tackle potential climate adaptation strategies. We drive a process-based model, the Decision Support System for Agrotechnology Transfer, with high-resolution statistically downscaled and bias-corrected historical and future climates from ten CMIP5 models in the MACA-2 database. The multi-model ensemble mean suggests a 12% decrease of maize yield by mid-century and 40% by late century, with a high degree of model consensus in the direction of changes; for individual models, the projected decrease of maize yield by late century ranges from <5% to over 80%, with the worst crop outcome corresponding to the most sensitive climate models. Soybean yield is projected to increase by midcentury with a high degree of model consensus, but such consensus is lost by late century as some projections shift to significant decreases. Crop yield in the Corn Belt is currently limited by water stress, but is projected to be increasingly limited by heat stress as well after the midcentury. The mounting heat stress will drive the most productive zone for maize to shift from central to northern part of the Corn Belt, but the projected increase in the northern states cannot fully compensate for the decrease in the south, causing the total production to decrease if agricultural practice stays the same. Earlier planting can alleviate only a small fraction of the heat-induced crop loss in a warmer climate. Climate change will (at least partially) offset the yield boost caused by agricultural technology and intensification. This study advances our predictive understanding of crop yield responses to climate change, and suggests that a multitude of strategies will be needed to address the climate change challenges for the U.S. agriculture. [Display omitted] • Yield decreases of 40% and 22% are projected for rain-fed maize and soybean respectively in the US Corn Belt by late century. • The primary limiting factor for the Corn Belt crop yield is projected to shift from water stress to heat stress after midcentury. • A northward shift or expansion of the most productive zone is projected. • The projected increase of yield and production in the northern states cannot fully compensate for the decrease in the south. • Earlier planting time can partially, but not completely, mitigate the heat-induced crop loss in the southern states. [ABSTRACT FROM AUTHOR]

The livestock sector in Sub-Saharan Africa (SSA) is under increasing pressure to define its role in jointly addressing food security and climate change. Climate-smart agriculture (CSA) has been widely leveraged as an approach to achieving both food security and climate change outcomes through suites of interventions that maximize synergies and reduce tradeoffs among three pillars: productivity, climate change resilience, and climate change mitigation. However, operationalization of the CSA approach in the livestock sector is hindered by a lack of clarity around what the pillars mean for livestock systems, given their fundamental attributes compared to crops and the spatial and temporal dimensions of these attributes. A conceptual framework is also lacking for assessing and comparing the potential CSA synergies and tradeoffs that different livestock systems and interventions may generate. In this paper we aim to offer guidance on the operationalization of the CSA approach in the livestock sector. We draw on a literature review to explore the essential attributes of livestock systems in SSA as they relate to CSA objectives over different temporal and spatial scales. Based on this review, we propose a practical and flexible framework for assessing and comparing the synergies and tradeoffs that different livestock systems may generate among food security and climate change objectives over different spatial and temporal scales. The framework consists of four elements: CSA pillars, spatial-temporal scales, CSA objectives mapped to each spatial-temporal scale, and indicator guidance. Using farm survey data and national statistics, an illustrative application of the framework to two dairy farms in Rwanda is presented and discussed. The illustrative application demonstrates how the framework can be used to identify important, spatial-temporal CSA synergies and tradeoffs that otherwise may go unrecognized. Additional applications are needed to assess the utility, practicality, and potential of the framework to guide CSA operationalization in the livestock sector in SSA. Maximizing synergies and reducing tradeoffs among food security and climate change outcomes in the livestock sector is critical for a sustainable food future. With an emphasis on flexibility for tailoring to specific development contexts and compatibility with varying levels of data availability and methodological complexity, the framework is intended to support diverse stakeholders involved in policy and development seeking to identify those livestock systems that contribute most to food security and climate change objectives over time and space. [Display omitted] • Maximizing synergies among food security & climate change in the livestock sector is critical for a sustainable future. • However, the climate-smart agriculture (CSA) approach has not been fully operationalized in livestock sector development. • Spatial & temporal dimensions determine when, where, and for whom CSA synergies & tradeoffs in the livestock sector arise. • We propose a spatial-temporal framework to assess and compare the CSA synergies & tradeoffs of different livestock systems. • Applying the framework can help identify important CSA synergies & tradeoffs that otherwise may go unrecognized. [ABSTRACT FROM AUTHOR]

Cropland soil organic carbon (SOC) stock can be increased by agricultural management, but is subject to various factors. The extent and rates of SOC sequestration potential, as well as the controlling factors, under different climate and management practices across a region or country are important for policy-makers and land managers, however have been rarely known. We aim to investigate the extent and rates of SOC sequestration potential over 2021–2040 under different scenarios of climate change and Sustainable Soil Management (SSM) practices, and quantify the impacts of climate change and SSM practices on the SOC sequestration potential, for croplands across Finland at a spatial resolution of 1 km. RothC model is run iteratively to equilibrium to calculate the size of the SOC pools and the annual plant carbon inputs. Then, it is applied to investigate the SOC sequestration potential over 2021–2040 under different scenarios of climate change and SSM practices. Finally, facorial simulation experiments are conducted to quantify the impacts of climate change and SSM practices, alone and in combination, on SOC sequestration potential. Under the combined impacts of climate change and SSM practices, the SOC sequestration potential during 2021–2040 relative to 2020 will be on average − 0.03, 0.007, 0.05, and 0.13 t C ha−1 yr−1, respectively, with carbon input being business as usual, 5%, 10%, and 20% increase. This is equivalent to an annual change rate of −0.04%, 0.009%, 0.07%, and 0.17%, respectively. Therefore, a 20% increase in C input to soil will not be enough to obtain a 4‰ increase per year over the 20-year period in Finland. Carbon input will promote SOC sequestration potential; however, climate change will reduce it on average by 0.28 t C ha−1 yr−1. Across the cropland in Finland, on average, the relative contributions of C input, temperature, and precipitation to SOC sequestration potential in 2021–2040 will be 56%, 24%, and 20%, respectively, however there is a spatially explicit pattern. The SOC sequestration potential will be relatively high and dominated by C input in west and southwest Finland. By contrast, it will be relatively low and dominated by climate in north and east Finland, and the central part of southern Finland. Our findings provide the information as to where, how much, and which SSM practices could be applied for enhancing SOC sequestration at a high spatial resolution, which is essential for stakeholders to increase cropland SOC sequestration efficiently. • IPCC tier 3 approach was applied to quantify cropland SOC sequestration potential. • 20% increase in C input would not be enough to meet the 4‰ target over 2021–2040. • Climate change would reduce SOC sequestration on average by 0.28 t C ha−1 yr−1. • 20% additional C input is not enough to compensate climate change impact on SOC. • Contribution of C input, temperature, precipitation to SOC sequestration is 56%, 24%, and 20%. [ABSTRACT FROM AUTHOR]

Climate change mitigation in the agricultural sector is a key policy goal. Marginal abatement cost curves allow comparing the cost-effectiveness of agricultural greenhouse gas mitigation measures. Existing studies often do not account for the heterogeneity of farms and interactions between mitigation measures. The objective of this study is to present a new approach that allows the calculation of a marginal abatement cost curve that considers farm level interaction effects of climate change mitigation measures. We assess the influence of farm structural heterogeneity on the greenhouse gas abatement potential and the corresponding abatement costs when measures are implemented jointly on the farm level. We use the bio-economic farm model FarmDyn to simulate farm-specific abatement potential and mitigation costs for a set of mixed dairy farms in a Swiss case study region (n = 66) and develop an approach to calculate a bottom-up, marginal abatement cost curve based on our sample of farms. Simulation results are used to identify and quantify the effect of heterogeneous farm structures (e.g., size, land use, etc.) on the interactions of climate change mitigation measures using regression analysis. In our study, interaction effects reduce marginal abatement costs by 7% and the overall greenhouse gas abatement potential by 3% compared to a stand-alone consideration of four climate change mitigation measures. Our analysis of how the underlying farm structures affect interaction effects between climate change mitigation measures shows that complex processes on the farm level can have ambiguous effects (i.e., increasing or decreasing greenhouse gas emissions). We conclude that our approach can provide important knowledge about how heterogeneity affects marginal abatement costs when mitigation measures interact with each other. Knowledge about the effectiveness and efficiency of climate change mitigation measures and their interaction effects improves our understanding and development of bottom-up marginal abatement cost curves, which represent an important and widely used tool to inform policymakers and stakeholders on cost-efficient and cost-effective climate change mitigation in agriculture. [Display omitted] • We calculate a marginal abatement cost curve for agricultural greenhouse gas emissions. • Our approach allows to consider interactions between mitigation measures. • The results permit to identify the heterogeneity in marginal abatement costs across farms. • A bio-economic farm level model is used for mixed dairy farms in a Swiss case study region. • Interactions are important for abatement potential and cost-effectiveness. [ABSTRACT FROM AUTHOR]

Climate models project higher temperatures and a substantial net water deficit during the summer months over Germany until the end of the 21st century. The agricultural sector is particularly vulnerable to changing weather and climate conditions. In this study, we examine the role of irrigation for potato yields as a climate change adaptation measure in Northeast Lower Saxony (Germany). The region represents the largest irrigated area in Germany and is one of the main growing areas of potatoes. We develop a statistical multivariate regression model to investigate whether regional climate and irrigation data at the monthly and county level are suitable to describe potato yield variability from 1978 to 2018. Irrigation is estimated based on the climatic water balance and crop water demand. These estimates are calibrated against irrigation data from local agencies to account for realistic monthly water withdrawals. We analyze future yield changes based on climate model projections for the 21st century and different irrigation scenarios. We find that the potato yield will decrease significantly by 18% on average until 2050 with climate projection uncertainty of ±6.4% under the high emission scenario RCP 8.5 and without irrigation. Irrigation at current levels could compensate for about 54% of these yield losses. Doubling the amount of irrigation minimizes yield losses by as much as 80%. Under the low (middle) emission scenario RCP 2.6 (RCP 4.5), potato yield are projected to decrease moderately by 4.5% ± 3.4% (5.4% ± 2.8%) with irrigation at current levels. We show that the yield losses mainly originate from higher temperatures during the summer. Our analysis indicates that the capacity of irrigation to minimize yield losses is limited. Strengthening climate change mitigation efforts may be more effective in preventing yield losses. However, the effect of elevated CO 2 might buffer the high yield losses, especially in RCP 8.5. The studies supports farmers and decision makers in assessing future risks in potato yields. It can guide policymakers in allocating economic resources to cope with climate change. [Display omitted] • Potato yields in Germany will decrease sharply under climate change for RCP8.5. • Irrigation at current levels mitigates about half of the yield losses. • Irrigation potential is limited because it can not buffer high temperatures. • Climate change mitigation and other adaption actions need to complement irrigation. • The effect of elevated CO2 might buffer high yield losses, especially in RCP8.5. [ABSTRACT FROM AUTHOR]

Farming systems face dual pressures of reducing greenhouse gas (GHG) emissions to mitigate climate change and safeguarding food security to adapt to climate change. Building soil organic carbon (SOC) is proposed as a key strategy for climate change mitigation and adaptation. However, practices that increase SOC may also increase nitrous oxide (N 2 O) emissions, and impact crop yields and on-farm income. A comprehensive assessment of the effects of different management practices on trade-offs between GHG emissions and agricultural systems profitability under climate change is needed. We aimed to: (1) analyze the long-term trends of SOC and N 2 O emissions, and ascertain whether the croplands of the study region are net GHG sources or sinks under climate change; (2) quantify the GHG abatement on a gross margin basis; (3) identify effective management practices that could achieve a win-win strategy; and (4) investigate sources of uncertainty in estimates of GHG emissions and gross margins under climate change. APSIM was used to simulate the effects of three crop residue retention rates (10%, 50% and 100%), and six representative crop rotations (wheat-canola, wheat-field pea-wheat-canola, wheat-field pea-wheat-oats, wheat-wheat-barley, wheat-wheat-canola, and wheat-wheat-oats) under two Shared Socio-economic Pathways scenarios (SSP245 and SSP585) using climate projections from 27 GCMs. GHG emissions and gross margins from 1961 to 2092 were assessed across 204 study sites in southeastern Australia. Our results showed that residue retention can turn the soil from a carbon source (10% retention, 304–450 kg CO 2 -eq ha−1 yr−1) to a carbon sink (100% retention, −269 ∼ −57 kg CO 2 -eq ha−1 yr−1), and the potential of carbon sequestration was partly offset by concomitantly increased N 2 O emissions. The wheat-wheat-canola rotation with full residue retention was shown to be a win-win solution with both large potential of GHG abatement and high gross margin compared with other rotations. Spatial analysis showed that the southeastern part of the study region, with higher rainfall, had higher gross margins, while the drier northwestern part had greater GHG emission reduction potentials. Although climate change led to increased GHG emissions and decreased yields for some crops, these adverse effects were overweighed by the higher SOC and yield advantages from full residue retention. This study emphasizes the significant potential for agronomic management to maximize gross margin and reduce GHG emissions under climate change in southeast Australia. Results from this study could be used by farmers and policymakers to mitigate climate change without compromising agroecosystem profitability. [Display omitted] • APSIM was used to simulate the effects of residue retention and crop rotation on GHG emissions and gross margins. • Retaining all crop residues could turn the soil from a carbon source to a carbon sink, and benefit gross margins. • Enhancement of residue retention on GHG abatement overweighed adverse effects of climate change under SSP245 and SSP585. • The wheat-wheat-canola rotation was the most beneficial in terms of GHG mitigation and profitability compared with others. [ABSTRACT FROM AUTHOR]

The development of methods for improving the assessment of resilience of socio-ecological systems has become increasingly important as the severity and variability of global climate patterns continue to compound and intensify. The present study was conducted with the aim of using a dynamically-coupled bio-physical and socioeconomic model to test the efficacy of stakeholder-defined policy measures in conferring resilience to two agroecological variables, farm income and water-table depth, experiencing both socio-ecological shocks and climatic stress in the Rechna Doab basin of northeastern Pakistan. The objective was accomplished by using a dynamically-coupled physical and group-built system dynamics modelling framework for scenario testing and output generation, including three NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-DGGP), two relevant socio-ecological shock scenarios (market inflation and canal water supply variability), and three stakeholder-defined policy measures. Resilience was assessed using the following system functionality metrics: 1) The degree of return for each variable after a perturbation, i.e., the extent to which the observed variable returns to baseline functioning; 2) The return time of the variable to baseline functioning; 3) The rate of variable return to baseline; 4) Overall perturbation of the system post-disturbance; and 5) The corrective impact of the shock on system functionality. Differences in the resilience metrics were subsequently compared based on the behavioral change(s) of the study variables in response to the application of the three selected policy scenarios. The results presented here indicate that rainwater harvesting is the most effective stakeholder-defined policy measure for improving or maintaining resilience of the tested study variables in the Rechna Doab agricultural basin; this holds true for every climate and shock scenario with the exception of water-table depth in the upper and mid-watershed regions under canal supply shock conditions, for which canal lining is the most effective policy measure. The irrigation improvement and canal lining policies were more effective in improving the resilience metrics of water-table depth than those of the farm income variable, as the water-table depth variable is not bound so tightly by economic constraints; although there were regional differences in policy efficacy, these trends hold true, on average, for the entire watershed. The results presented herein align well with previous studies conducted in the region which note similar patterns in spatial resilience of agroecosystem variables (i.e., upper to lower watershed) in the Recha Doab basin as well as regional differences in the efficacy of the stakeholder-defined policy measures. This unique approach for assessing socio-environmental policies can help improve decision-making processes with respect to agro-infrastructure and climate change mitigation strategies in vulnerable agroecosystems. [Display omitted] • Improving the resilience of socio-ecological systems has become crucial with the intensification of global climate patterns • Quantify resilience of climate-stressed socio-agroecological variables via application of stakeholder-defined policies • Rainwater harvesting is the most effective stakeholder-defined policy measure for achieving variable-level resilience • Methods can be utilized in single-system analyses as well as comparative studies across spatial and temporal boundaries • The methods used herein can help improve socio-ecological policy development and climate change mitigation strategy [ABSTRACT FROM AUTHOR]

Colombia has a total of 27.2 million heads of cattle, ranking fourth among the Latin American countries. Identifying sustainable strategies to mitigate greenhouse gas emissions (GHGE) will help the Colombian government meet their goal of a 51% reduction in national emissions by 2030. Estimation of yield gaps for identifying the potential to improve cattle farms productivity and efficiency in Colombia help on reducing the GHGE intensities from the cattle sector. This paper aims to calculate the gap between attainable and actual milk and meat yields for specialized dairy, dual-purpose, cow-calf, and fattening production systems in 3 agro-ecological zones (AEZ) in Colombia; to identify the main aspects that restrict the meat and milk yields in these production systems; and analyze how closing yield gaps affect the carbon footprint (CF) of meat and milk production. The most suitable AEZs for cattle activities were identified by considering environmental, climatic, edaphic, and land characteristics. From a dataset of 1505 surveyed farms, a yield gap benchmarking analysis for estimating the potential to increase meat and milk yields in each of the identified AEZ was applied. The most productive farms were included in the "best farms" while the rest of the farms belonged to the "farms operating below potential". A "cradle to farm-gate" Life Cycle Assessment was used to calculate the CF. Three scenarios were proposed for closing the yield gaps by 50, 75, and 100%, between the two groups of farms. Three AEZs likely to support cattle activities in Colombia were identified. Average milk production from the farms operating below potential was 45–50% of potential production, and meat was 34–51%, indicating that a potential to achieve increases in milk and meat productivity exists. CFs of 1 kg milk or meat were lower in the groups of best-performing farms than in the groups of farms operating below potential. Yield gaps for milk and meat production can be closed by improving cattle management practices and better technologies. As a general trend, closing the yield gaps decreases the CFs. Our findings contribute to understand the farms' current productive performance and provides key insights into the possible technological and managerial changes for improving the productivity of cattle systems in Colombia. In addition, the study showed how milk and meat CFs can be lowered with the adoption of proper cattle management practices, and better technologies. [Display omitted] • Cattle are responsible for 21% of Colombian GHG emissions, identifying sustainable strategies for its mitigation is crucial. • Yield gap analysis is useful for exploring opportunities to increase yields by identifying factors constraining production. • This study calculated the yield gaps for Colombian cattle systems, their carbon footprints, and proposed mitigation options. • Substantial cattle yield gaps were found, hence there is a considerable scope to improve milk and meat yields in Colombia. • Closing the yield gaps by increasing cattle productivity is an important mitigation strategy of climate change in Colombia. [ABSTRACT FROM AUTHOR]