Forestry expansion can enhance carbon storage but often reduces water yield, creating trade-offs for catchment-scale water resource management worldwide. In many regions, the rapid expansion of plantation forests has raised concerns about water availability within river basins. Land use management strategies often rely on uniform plantation area thresholds, overlooking the effects of landscape and climate differences on hydrological responses across catchments. Here, we assess the impacts of afforestation using a process-based hydrological model to simulate dynamic land use change, representing 25-year rotations across an ensemble of afforestation scenarios to identify where and when forestry alters the distribution of streamflow probabilities. Using a multi-step calibration (2004–2015) and validation (2016–2019) against monthly satellite evapotranspiration (ET) and streamflow, the SWAT model reproduced streamflow well (KGE = 0.93, R² = 0.88) and reasonably captured ET patterns (KGE = 0.78, R² = 0.81). Scenario analyses show that expanding plantations reduces streamflow, with greater effects in the middle and lower sub-catchments during dry years. Median annual streamflow declined by 26 ± 3 mm yr⁻¹ in middle catchments and 19 ± 2 mm yr⁻¹ in lower catchments per 10-percentage-point increase in upstream forest cover. Increasing the forested area by 62% across all the soils with forestry aptitude reduced mean monthly streamflow by 28% on average, with extremes near 60% (2004–2024). Eucalyptus shows more significant reductions than pine, both with higher flow reductions during wetter periods. This demonstrates that climate variability exerts dominant control over interannual water availability, thereby modulating afforestation impacts. This study highlights that process-based modelling tools are essential for disentangling hydrological responses to land use and climate variability across space and time to support future risk-based planning.

A limited understanding of the potential to reduce emissions and a lack of climate incentives hinder progress toward mitigating greenhouse gas (GHG) emissions from beef production. This study explored the GHG mitigation potential in South America by evaluating nearly 30 beef cattle production systems across five key beef-producing countries (Argentina, Brazil, Colombia, Paraguay, and Uruguay). The study outlined a low-emission beef roadmap for this major beef producing region. Data from this study indicate that the current business-as-usual trajectory of improvements in South America's beef cattle production is insufficient to reduce GHG emissions at a pace that aligns with the urgency of climate crisis. Results from this study show that scaling up existing practices -such as improved forages, rotational grazing, and feed supplementation- to match the performance of the region's lowest-emission systems at 20thpercentile could deliver significant results. Emission intensities could decrease by 33-50% compared to the projected 2050 regional average (35 tons carbon dioxide equivalent/ton of carcass weight). This would flatten the emissions curve, cutting total emissions by 20-40% while simultaneously increasing beef production by 43%. With annual methane (CH4) emission reductions by 1.5%, the warming effect could decrease by 70-90%, offering a transformative pathway to lower GHG emissions from beef production. This emissions trajectory offers a feasible path toward net-zero warming from beef production, primarily through sustained reductions in CH4 emissions intensity and absolute emissions as systems become more production efficient. These findings highlight the need and an opportunity for a drastic reduction in emissions from beef cattle production and can foster collaboration among conservation, industry, and finance stakeholders towards a common climate-oriented beef production agenda.

Simulation modelling is essential for scenario testing but requires careful calibration. Multi-variable calibration improves model realism but implies decisions about variable weighting in the objective function. An alternative is the sequential introduction of calibration variables. An example of this related to water policy is the assessment of forest plantations' impact on streamflow in South America. This requires a realistic implementation of forestry systems, where evapotranspiration and plantation growth are simulated realistically. This study used the La Corona paired catchment experiment to demonstrate how a sequential multi-variable calibration improves Pinus taeda and grasslands representation in a landscape model. The model was based on long-term flow observations and satellite-based ET and LAI data. Results showed that flow prediction performance increased, with a shift in the parameter distributions and decreased uncertainty compared to calibration on streamflow alone. This ultimately resulted in more robust simulation results to assess afforestation and deforestation impacts on streamflow.

Climate risk is a critical challenge for smallholder farmers in Guatemala, and weather and climate information services (WCIS) are a growing policy solution. Using a survey of 330 farming households in Guatemala's Dry Corridor, this research examines farmers' ability to access and utilize WCIS for agricultural decision-making, as well as the association between WCIS and food insecurity. Our observational study found that while reported access to one approach, Local Technical Agro-Climatic Committees (LTACs) and agro-climatic bulletins (ACBs), was lower than expected among a representative sample of communities, nearly half of respondents reported accessing weather and climate information more generally. In an observational comparison, those accessing information implemented significantly more climate-resilient agricultural practices and were significantly more food secure than those not receiving the information; however, accessing information was correlated with household wealth and education, and its effect on food insecurity was not statistically identifiable in a multiple regression test with controls. Our study also provides empirical evidence that a lack of information is not the primary barrier to the adoption of adaptation practices. While farmers expressed a desire to adapt certain farming practices in response to climate risk, they faced financial and other barriers to implementing these strategies. Thus, while WCIS have potential for informing agricultural decisions, this study underscores the challenges associated with effectively delivering information to farmers, as well as highlights obstacles to their use when farmers do receive them. These insights are crucial for refining WCIS design and delivery. Recommendations include investing in more farmer-centric communication channels and coupling information with resources to strengthen farmers' adaptive capacity. Practical implications: Guatemala's Dry Corridor is a region highly susceptible to drought and climate variability. For smallholder farmers who depend on rain-fed maize and bean cultivation, these climate risks intensify vulnerability and threaten livelihoods. Acute food insecurity is also a significant concern in Guatemala and the Dry Corridor. Weather and climate information services (WCIS) are offered as a policy solution in Guatemala, and globally, to aid in climate risk management and climate change adaptation. Timely and relevant climate information can inform adaptive agricultural practices, potentially helping to mitigate climate risks, reduce negative coping strategies, and safeguard household well-being. This study explores the reach of WCIS and the socioeconomic factors associated with its use among a population of smallholder farmers in Guatemala's Dry Corridor, using a contextual assessment of decision-making processes, adaptive practices, and local constraints. We investigate the differences between those who access WCIS and those who do not, and assess whether access to WCIS and the implementation of adaptive agricultural practices is associated with greater household food security. In particular, the study examines the role of Local Technical Agro-Climatic Committees (LTACs; known as Mesas Tecnicas Agroclimaticas, or MTAs in Spanish) and agro-climatic bulletins (ACBs). The LTACs are a nationally scaled climate services initiative, backed by a governmental coordination strategy that engages numerous organizations and agricultural intermediaries. Through dialogue, knowledge exchange, and the development of participatory climate-informed recommendations for farmers, this initiative aims to improve the accessibility and tailoring of climate information to support climate resilience among farmers. Our study finds that among randomly surveyed farming households, very few farmers are attending LTACs or directly accessing information/recommendations from the ACBs in this region. Instead, most farmers rely on personal observations, radio, and neighbors to identify climate risks; and radio, smartphones, and television to access weather and climate information. Decisions about planting, harvesting, crop varieties, inputs, and water management are most often informed by personal experience, family tradition, and advice from neighbors. Noteable, only 50 % of the sampled farmers report access to any weather or climate information. Those who do, primarily access short-term weather forecasts (1-5 days) rather than seasonal climate predictions. The study also found that farmers who accessed WCIS implemented more climate-resilient practices compared to those without access, but financial limitations remain a substantial barrier to broader adoption. We also find that nearly a quarter of the households in our sample report changing food consumption and dietary choices in response to climate impacts. Over 25% were scored as being moderately food insecure and 17% as severely food insecure. While the study found that farmers who access some form of WCIS have lower food insecurity scores and tend to implement more adaptive agricultural practices, the direct effects of access to WCIS and the adoption of adaptive agricultural practices on food security were not statistically significant when controlling for socioeconomic factors. This study highlights several opportunities to improve the delivery and impact of WCIS. Raising awareness of LTACs and ACBs through locally trusted channels such as radio broadcasts and effective outreach by climate intermediaries, can enhance accessibility. Integrating scientific data with farmers' traditional knowledge and priorities, while ensuring their meaningful end-to-end participation in the LTAC process, is key to creating actionable, context-relevant recommendations. Further research is needed to understand how climate information and advisories from LTACs and ACBs are shared, with whom, and how farmer networks can enhance spillover. The success of WCIS in this region depends on a multifaceted approach that goes beyond information dissemination to address the structural barriers limiting farmers' adaptive capacity. Tailoring WCIS delivery to local contexts, providing financial and capacity-building support, and fostering more inclusive, participatory mechanisms can enhance the role of WCIS as a tool for building resilience to climate risks among Guatemala's smallholder farmers, as has been shown with similar models in West Africa and Latin America. However, climate services alone are not enough; broader interventions are needed to reduce vulnerability and strengthen rural livelihoods. In Guatemala's Dry Corridor, where drought is a primary risk, farmers would greatly benefit from improved water storage systems and irrigation access.

Integrated crop–pasture rotational systems can store larger soil organic carbon (SOC) stocks in the topsoil (0–20 cm) than continuous grain cropping. The aim of this study was to identify if the main determinant for this difference may be the avoidance of old C losses in integrated systems or the higher rate of new C incorporation associated with higher C input rates. We analyzed the temporal changes of 0–20 cm SOC stocks in two agricultural treatments of different intensity (continuous annual grain cropping and crop–pasture rotational system) in a 60-year experiment in Colonia, Uruguay. We incorporated this information into a process of building and parameterizing SOC compartmental dynamical models, including data from SOC physical fractionation (particulate organic matter, POM > 53 µm > mineral-associated organic matter, MAOM), radiocarbon in bulk soil, and CO2 incubation efflux. This modeling process provided information about C outflow rates from pools of different stability, C stabilization dynamics, and the age distribution and transit times of C. The differences between the two agricultural systems were mainly determined by the dynamics of the slow-cycling pool (∼MAOM). The outflow rate from this compartment was between 3.68 and 5.19 times higher in continuous cropping than in the integrated system, varying according to the historical period of the experiment considered. The avoidance of old C losses in the integrated crop–pasture rotational system resulted in a mean age of the slow-cycling pool (∼MAOM) of over 600 years, with only 8.8 % of the C in this compartment incorporated during the experiment period (after 1963) and more than 85 % older than 100 years old in this agricultural system. Moreover, half of the C inputs to both agricultural systems leave the soil in approximately 1 year due to high decomposition rates of the fast-cycling pool (∼POM). Our results show that the high capacity to preserve old C of integrated crop–pasture systems is the key for SOC preservation of this sustainable intensification strategy, while their high capacity to incorporate new C into the soil may play a second role. Maintaining high rates of C inputs and relatively high stocks of labile C appear to be a prerequisite for maintaining low outflow rates of the MAOM pool.

IntroductionInterannual climate variability in the Asian mega deltas has been posing a wide range of climate risks in the aquaculture systems of the region. Water temperature variation is one of the key risks related to disease outbreak, fish health, and loss and damage in fish production. However, Climate information can improve the ability to predict changes in pond water quality parameters at the farm level using publicly available weather and climate data. Little research has been done to translate weather data into water temperature forecasts using mechanistic models in order to provide farmers with relevant forecasting information in the context of climate services.MethodsThe advantage of mechanistic models over statistical models is that they are based on physical processes and can therefore be used in a wider range of environmental conditions. In this study, we used an energy balance model to investigate its ability to simulate pond water temperature at daily and seasonal timescales in the southwest and northeast regions of Bangladesh. The model was able to adequately simulate pond water temperature at a daily timescale using publicly available weather data, and the accuracy of the model was lower at the study site with very heavy rainfall events.ResultsSensitivity analyses showed that the model was also able to simulate the impact of air temperature cold and hot spells on the pond water temperature. Connecting the model with seasonal air temperature forecasts resulted in very small variations in the forecasted seasonal pond water temperature, in large part due to the low variability observed in water temperature at seasonal scale in the study sites.DiscussionClimate information can improve the ability to predict changes in pond water quality parameters at the farm level using publicly available weather and climate data. Hence, these improved predictions are important to help fish-farmers make informed decisions for managing associated climate risks.

The environmental toll of protein production systems, such as greenhouse gas (GHG) emissions and land use associated with the production of livestock-derived foods, poses a substantial challenge for global agricultural sustainability. At the same time, livestock possess significant cultural and economic value for billions, while providing essential macro- and micronutrients. Such tensions fuel a debate on how to optimize livestock production systems, with implications for global nutrition, the environment, and society. Here, we introduce the Protein for Nutrition, Environment, and Society (ProNES) framework to address challenges related to the holistic evaluation of livestock-derived protein systems. ProNES uses publicly available data to comprehensively assess livestock-derived commodities in terms of their nutritional, social, economic, and environmental aspects. The exercise underscores areas where data gaps must be filled for more precise assessments, such as the contributions of livestock production systems to livelihoods across a range of geographic, economic, and sociocultural contexts.

Global food systems are closely interconnected with contemporary challenges such as food security, environmental crises, and inclusive development. Protein production, in particular, is strongly associated with these issues, as the resource-intensive predominant production models can lead to environmental pressures and food inequity. Alternative proteins (APs) have been proposed as part of the solution to meeting future global protein demand while keeping modes of production and consumption within planetary boundaries. Here, we stress that the potential of APs to address this crucial food-environment-livelihoods trilemma hinges on collective social choices made early in the sociotechnical transition. We therefore call for a managed and socially embedded transition in which public agents together with civil society and private actors work to ensure balanced outcomes, with global and domestic food inequities in mind. Our emphasis on AP adoption as an open-ended process highlights the underlying political economy of food systems transitions and technological development.

CONTEXT: A challenge facing the livestock sector is improving beef production while mitigating negative environmental impacts. Analyzing its past productive and environmental performance may elucidate strategies for improving efficiency of grassland-based systems and identify future research and public policy priorities. OBJECTIVES: Describe past and current dynamics and assess potential future scenarios of the Uruguayan beef production sector, considering historical beef production growth rate (kg carcass), partitioning in land use by the cattle sector (ha), cattle animal performance (kg carcass animal-1 year-1) and stocking rate (animal ha-1) since 1966. METHODS: We quantified drivers of beef production and total enteric methane (CH4) emissions and modeled the gap between their current and potential levels by applying new management practices at country scale. Potential systems included reduced age of replacement heifers at first pregnancy and greater cow weaning rates. Results AND CONCLUSIONS: Cattle land area expansion and increased animal performance explained most of beef production growth (33 and 52%, respectively), while stocking rate had a negligible effect. We identified that recent beef production was driven by improved pasture area (R2 = 0.42), which represented only 21% of cattle area. This disproportionate effect showed a dependency of national beef production on improved pastures. The current weaning rate (65%) and the number of replacement heifers that have first pregnancy by 36 months of age (480,000 heads) revealed a national inefficiency, falling short of the potential of grazing systems based on native pastures. When concepts and principles of ecological intensification of native pasture grazing systems are applied optimally, weaning rate can be increased from 65 to 85% and age of first pregnancy reduced from 36 to 24 months, decreasing national enteric CH4 emissions by 13%. The weaknesses identified in the national beef production sector support re-focusing research, public policy, and technologies applied by farmers to shift the paradigm of beef production to greater ecological intensification based on native pastures. In this way, it will be possible to increase beef production and mitigate environmental impacts of grazing systems. SIGNIFICANCE: We demonstrate that re-focusing beef production from improved pastures to native pastures, while enhancing their management, will mitigate the CH4 emissions of the beef sector at large scales and will underpin the annual beef production, leading to a stable annual production, reducing the dependency on improved pasture area and providing ecosystem services.

That climate variability and change can potentially force multiple simultaneous breadbasket crop yield shocks has been established. But research quantifying the mechanisms behind such simultaneous shocks has been constrained by short records of crop yields. Here we compile a dataset of subnational crop yields in 25 countries dating back to 1900 to study the frequency and trends in multiple breadbasket yield shocks and how large-scale climate anomalies on interannual timescales have affected multiple breadbasket yield shocks over the last century. We find that major simultaneous breadbasket yield shocks have occurred in at least three, four, or five of nine breadbaskets 10.3%, 2.3% and 1.1% of the time for maize and 18.4%, 4.6% and 2.3% of the time for wheat. Furthermore, we find that multiple breadbasket yield shocks decreased in frequency even as those breadbaskets experience increasingly frequent climate-related shocks. For both maize and wheat breadbaskets, there were fewer simultaneous yield shocks during the 1975-2017 time period as compared to 1931-1975. Finally, we find that interannual modes of climate variability - such as the El Nin similar to o Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the North Atlantic Oscillation (NAO) - have all affected the relative probability of simultaneous yield shocks in pairs of breadbaskets by up to 20-40% in both maize and wheat breadbaskets. While past literature has focused on the effects of ENSO, we find that at the global scale the NAO affects the overall number of wheat yield shocks most strongly despite only affecting northern hemisphere breadbaskets.

Carbon net emission is a critical aspect of the environmental footprint in agricultural systems. However, the alternatives to describe soil organic carbon (SOC) changes associated with different agricultural management practices/land uses are limited. Here we provide an overview of carbon (C) stocks of non-forested areas of Uruguay to estimate SOC changes for different soil units affected by accumulated effects of crop and livestock production systems in the last decades. For this, we defined levels based on SOC losses relative to the original (reference) SOC stocks: 25% or less, between 25% and 50%, and 50% or more. We characterized the reference SOC stocks using three approaches: (1) an equation to derive the potential SOC capacity based on the clay and fine silt soil content, (2) the DayCent model to estimate the SOC stocks based on climate, soil texture and C inputs from the natural grasslands of the area, (3) an estimate of SOC using a proxy derived from remote sensing data (i.e., the Ecosystem Services Supply Index) that accounts for differences in C inputs. Depending on the used reference SOC, the soil units had different distributions of SOC losses within the zones defined by the thresholds. As expected, the magnitude of SOC changes observed for the different soil units was related to the relative frequency of annual crops, however, the high variability observed along the gradient of land uses suggests a wide space for increasing SOC with agricultural management practices. The assessment of the C stock preserved (CSP) belowground and the potential for increasing C accumulation or sequestration (CAP) are critical components of the C footprint of a given system. Thus, we propose a methodological road map to derive indicators of CSP and CAP at the farm level combining both, biogeochemical simulation models and conceptual models based on remote sensing data. We recognize at least three critical issues that require scientific and political consensus to implement the use of this propose: (1) how to define reference C stocks, (2) how to estimate current C stocks over large areas and in heterogeneous agricultural landscapes, and (3) what is a reasonable/acceptable threshold of C stocks reduction.

Rainfed agriculture in Senegal is heavily affected by weather-related risks, particularly timing of start/end of the rainy season. For climate services in agriculture, the National Meteorological Agency (ANACIM) of Senegal has defined an onset of rainy season based on the rainfall. In the field, however, farmers do not necessarily follow the ANACIM’s onset definition. To close the gap between the parallel efforts by a climate information producer (i.e., ANACIM) and its actual users in agriculture (e.g., farmers), it is desirable to understand how the currently available onset definitions are linked to the yield of specific crops. In this study, we evaluated multiple onset definitions, including rainfall-based and soil-moisture-based ones, in terms of their utility in sorghum production using the DSSAT–Sorghum model. The results show that rainfall-based definitions are highly variable year to year, and their delayed onset estimation could cause missed opportunities for higher yields with earlier planting. Overall, soil-moisture-based onset dates determined by a crop simulation model produced yield distributions closer to the ones by semi-optimal planting dates than the other definitions, except in a relatively wet southern location. The simulated yields, particularly based on the ANACIM’s onset definition, showed statistically significant differences from the semi-optimal yields for a range of percentiles (25th, 50th, 75th, and 90th) and the means of the yield distributions in three locations. The results emphasize that having a good definition and skillful forecasts of onset is critical to improving the management of risks of crop production in Senegal.

Climate services can help address a range of climate-sensitive development challenges, including agricultural production and food security. However, generating empirical evidence of impact is challenging. In this paper, we synthesize published evidence of pathways by which climate services contribute to improved food security. A summary of key mechanisms by which climate risk drives food insecurity provides a context for understanding potential climate risk management interventions. Our review of available evaluation literature finds moderately strong evidence that climate services contribute to improvements in food security or its precursors through farmers' risk management decisions and index-based agricultural insurance; and a weaker body of emerging evidence of impacts through timelier humanitarian and adaptive social protection interventions. There are gaps in the available evidence of anticipated food security impacts through agricultural value chain actors, government agricultural planning, nutrition interventions and policy. Attributing SDG2 impact to climate services is particularly challenging for initiatives that aim to build an enabling environment to scale and sustain impacts of climate services through capacity development and policy engagement with national institutions. In such cases, employing a theory of change approach grounded in the evolving body of evidence included in this review can provide confidence that improved production and use of climate services by actors along hypothesized impact pathways will contribute towards improved food security.

CONTEXT Global climate change is resulting in more frequent and more damaging extreme events affecting the performance of production systems. It is imperative to develop good season-specific crop management recommendations to help farmers to improve their adaptive capacity to a changing climate one season at a time. OBJECTIVE: We aimed to evaluate the skill of the International Research Institute for Climate and Society (IRI) seasonal precipitation forecasts and the interaction between the forecasted seasonal precipitation scenarios and management practices for rainfed soybean cropping systems using a crop simulation model. METHODS: We used a crop simulation model (CROPGRO-Soybean) coupled with weather data to assess the potential use of the IRI seasonal precipitation forecasts as a tool to optimize season-specific management strategies for rainfed soybean in Uruguay. We used a total of 620-668 IRI seasonal precipitation forecasts released from 2003 to 2016 for each of the five weather stations located in the main soybean producing area. The analysis was performed for two soybean cropping systems (i.e., sown as a single crop or as double-cropped soybean), for which we considered combinations of sowing dates and maturity groups (11 sowing dates x 3 maturity groups combinations for each soybean cropping system). RESULTS AND CONCLUSIONS: The IRI seasonal precipitation forecasts were able to successfully forecast belownormal precipitation scenarios in 77% of the total predictions developed for this scenario considering all weather stations during the study period (2003-2016), while it was less accurate in forecasting above-normal precipitation scenarios (60% of success). We found that earlier sowing dates were a better strategy for years when an above-normal precipitation forecast was released for the December-January-February period (4.7 Mg ha(-1) average seed yield). In contrast, delayed sowing dates were more appropriate for below-normal precipitation forecasts (3.7 Mg ha(-1) average seed yield). Applying season-specific management practices farmers could potentially increase their soybean yields by up to 0.6 and 1.6 Mg ha(-1), in years with below- or above-normal forecasted precipitations, respectively. The benefit of season-specific management will depend on the interaction among all management practices, the effective capacity of farmers to implement it, and the risk profile the farmer adopts and it is exposed to. SIGNIFICANCE: Here we built a novel approach to assess the impact of considering seasonal precipitation forecasts for optimizing crop production. This assessment provided insights on how farmers can use seasonal precipitation forecasts to optimize rainfed soybean yield for a specific cropping season.

Simultaneous yield shocks in multiple breadbaskets pose a potential threat to global food security, yet the historical risks and causes of such shocks are poorly understood. Here, we compile a dataset of subnational maize and wheat yield anomalies in 25 countries dating back to 1900 to better characterize the past, present, and future risk of multiple breadbasket shocks. We find that years in which at least half of all maize or wheat breadbaskets fall 10% (5%) below expected yields has occurred in ~2-3% (~14-16%) of years over the last century. Importantly, multiple breadbasket shocks have been decreasing in frequency from 1930 to 2017. The El Niño Southern Oscillation (ENSO) most strongly affects the probability of multiple maize breadbasket shocks, while the North Atlantic Oscillation (NAO) most strongly affects the probability of multiple wheat breadbasket shocks, each influencing the probability by up to 40%. The effect of climate change on climate stress in maize and wheat breadbaskets is mixed; extreme heat will increase uniformly, agricultural soil moisture stress will remain constant or increase, but hydrological stress (as measured by runoff) will remain constant or decrease in breadbasket regions.

The ability to implement climate risk management measures is associated with the availability and effectiveness of climate services to inform decision making. Using the case of agricultural droughts in livestock systems of Uruguay, this paper analyzes the extent in which available climate information is being used for adaptation to droughts. Semi-structured interviews and The Q methodology was applied to farmers, public policy makers and academic researchers. Four different profiles of the use of climate information were obtained: convinced, pragmatic, pessimistic and skeptical. The need of understanding the specific contexts of use of climatic information for tailored climate services elaboration is noted. Translation of information is also necessary, since the lack understanding of the message results in unused information. There was consensus that preventive measure should be taken to minimize the impacts of drought and therefore, developing effective climate services should prioritize preventive measures.

The Century model was used to simulate soil C and N cycling and crop production dynamics in an ongoing field experiment in Uruguay (started in 1963). The model was calibrated using observed data from three treatments (crop or crop–pasture rotations) and validated with a fourth treatment. The model correctly predicted the impact of different treatments on microbial biomass, N mineralization, soil respiration, and crop yields. The model and observed data show that soil respiration, N mineralization, soil C, and crop yields increase with increasing plant-derived C inputs caused by increasing the frequency of pastures in the rotations. This is one of the first papers that show the strong positive correlation of observed soil C with plant C soil inputs to field-observed microbial biomass, soil respiration, and N mineralization. The results also showed that reducing tillage and transitioning to a no-till system increased soil C and reduced soil erosion. The main path of soil C losses was heterotrophic microbial respiration, which accounted for 66% of the total C lost in a continuous crop rotation and no fertilizers, 71% in a continuous crop rotation with fertilizers, and 86% in a crop–pasture rotation with fertilizers. Model results from a degraded cropping system showed that adding grass–clover ( Trifolium spp.) pastures greatly increased plant production and soil C, whereas reducing the frequency of grass–clover pastures in high-fertility cropping systems from 50% of the time to 25% reduces crop yields and soil C. Including cover crops substantially increases crop production and maintains soil C in high-fertility and degraded cropping systems.

Framed experiments and games are a useful medium to understand how context affects individual and group decision-making. They are particularly relevant for field research in agriculture, where alternative experimental designs can be costly and unfeasible. After a systematic review of the literature, we found that the volume of published studies employing coordination and cooperation games increased during the 2000-2020 period. In recent years, there has been greater attention given to natural resource management, conservation, and ecology areas, especially in strategic regions for agriculture sustainability. Other games, such as trust and risk games, have come to be regarded as standards of framed field experiments in agriculture. Regardless of sectoral focus, most games' results are subject to internal and external validity criticism. In particular, a significant portion of the games showed potential recruitment biases against women and no opportunities for a continued impact assessment. However, games' validity should be judged on a case-by-case basis. Specific cultural aspects of games might reflect the real context, and generalizing games' conclusions to different settings is often constrained by cost and utility. Overall, games in agriculture could benefit from more significant, frequent, and inclusive experiments and data – all possibilities offered by digital technology. Present-day physical distance restrictions may accelerate this shift. New technologies and engaging ways to approach farmers might represent a turning point for games in agriculture in the 21st century.