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Ecosystems around the globe are enduring wildfires with greater frequency, intensity, and severity and this trend is projected to continue as a result of climate change. Climate-smart agriculture (CSA) has been proposed as a strategy to prevent wildfires and mitigate climate change impacts; however, it remains poorly understood as a strategy to prevent wildfires. Therefore, the authors propose a multimethod approach that combines mapping of wildfire susceptibility and social surveys to identify priority areas, main factors influencing the adoption of CSA practices, barriers to their implementation, and the best CSA practices that can be implemented to mitigate wildfires in Belize's Maya Golden Landscape (MGL). Farmers ranked slash and mulch, crop diversification, and agroforestry as the main CSA practices that can be implemented to address wildfires caused by agriculture in the MGL. In order to reduce wildfire risk, these practices should, be implemented in agricultural areas near wildlands with high wildfire susceptibility and during the fire season (February-May), in the case of slash and mulch. However, socio-demographic and economic characteristics, together with a lack of training and extension services support, inadequate consultation by agencies, and limited financial resources, hinder the broader adoption of CSA practices in the MGL. Our research produced actionable and valuable information that can be used to design policies and programs to mitigate the impacts of climate change and wildfire risk in the MGL. This approach can also be used in other regions where wildfires are caused by agricultural practices to identify priority areas, barriers and suitable CSA practices that can be implemented to mitigate wildfires.

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This data article provides spatially explicit data on greenhouse gas (GHG) emissions and mitigation potential at various administrative levels for the whole of Bangladesh. The results arising from analysis of this database are presented in research article "Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh" [1]. We collected crop and livestock management data and associated soil and climatic data from variety of primary and secondary sources outlined below in our methodology. The datafiles on crops and livestock contain model outputs for three greenhouse gases (CO2, CH4 and N2O) and their global warming potential, which are linked, to the information on crop/livestock management, soil and climatic conditions presented in the supplementary data of the associated manuscript. The datafiles on mitigation potential contain district-level annual GHG mitigation potential by 2030 and 2050 segregated by different crops/livestock types and mitigation options. This dataset is useful for Bangladesh's GHG accounting from the agricultural sector, and can be used to update its nationally determined contributions. Administrative level emissions and mitigation potential estimates segregated by crop-livestock types and mitigation options are useful to prioritize agricultural research and development interventions consistent with food security and environmental goals and to organize agricultural extension and support services to better inform farmers on food production and move towards GHG mitigation goals.

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Agriculture and soil management practices are closely related to CO2 emissions in crop fields. These practices directly interfere on the carbon dynamics between the land and atmosphere. In this study, we investigated the temporal variability of the column-averaged dry-air mole fraction of atmospheric CO2 (xCO2), solar-induced chlorophyll fluorescence (SIF), and the normalized difference vegetation index (NDVI) in areas with the main agroecosystems in southern-central Brazil as a way to understand if and how crops cycle and agricultural management could be associated with the temporal variability of NDVI, SIF and xCO2. The study was carried out in areas corresponding to the three agroecosystems': sugarcane (Pradópolis, State of São Paulo, Brazil), cropland with soybean-corn succession (Santo Antônio do Paraíso, State of Paraná, Brazil), and grassland (Águas Claras, State of Mato Grosso do Sul, Brazil). Air temperature, precipitation, NDVI, and SIF and xCO2 were retrieved from NASA-POWER, NASA-GIOVANNI, SATVeg-EMBRAPA, and OCO-2, respectively, during a two-year study. Trends were removed from the NDVI, SIF, and xCO2 time series applying the regression method. A negative correlation between SIF and xCO2 was found in sugarcane and cropland areas, but in grasslands, no correlation showed up. Higher SIF values were observed in grassland (2.24 W m-2 sr-1 µm-1), and lower xCO2 values were observed above grains, which varied from 396.8 to 404.2 ppm. Both xCO2 and SIF followed more a seasonal pattern in sugarcane and annual crops, but over pasture this presented an unusual pattern related to higher precipitation events. Our results indicate a potential use of SIF and xCO2 which could help identifying potential sources and sinks of the main additional greenhouse gas over agricultural areas.

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Fall armyworm (FAW), a voracious agricultural pest native to North and South America, was first detected on the African continent in 2016 and has subsequently spread throughout the continent and across Asia. It has been predicted that FAW could cause up to $US13 billion per annum in crop losses throughout sub-Saharan Africa, thereby threatening the livelihoods of millions of poor farmers. In their haste to respond to FAW governments may promote indiscriminate use of chemical pesticides which, aside from human health and environmental risks, could undermine smallholder pest management strategies that depend to a large degree on natural enemies. Agro-ecological approaches offer culturally appropriate low-cost pest control strategies that can be readily integrated into existing efforts to improve smallholder incomes and resilience through sustainable intensification. Such approaches should therefore be promoted as a core component of integrated pest management (IPM) programmes for FAW in combination with crop breeding for pest resistance, classical biological control and selective use of safe pesticides. Nonetheless, the suitability of agro-ecological measures for reducing FAW densities and impact need to be carefully assessed across varied environmental and socio-economic conditions before they can be proposed for wide-scale implementation. To support this process, we review evidence for the efficacy of potential agro-ecological measures for controlling FAW and other pests, consider the associated risks, and draw attention to critical knowledge gaps. The evidence indicates that several measures can be adopted immediately. These include (i) sustainable soil fertility management, especially measures that maintain or restore soil organic carbon; (ii) intercropping with appropriately selected companion plants; and (iii) diversifying the farm environment through management of (semi)natural habitats at multiple spatial scales. Nevertheless, we recommend embedding trials into upscaling programmes so that the costs and benefits of these interventions may be determined across the diverse biophysical and socio-economic contexts that are found in the invaded range.

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