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Abstract The adoption of conservation agriculture methods, such as conservation tillage and cover cropping, is a viable alternative to conventional farming practices for improving soil health and reducing soil carbon losses. Despite their significance in mitigating climate change, there are very few studies that have assessed the overall spatial distribution of cover crops and tillage practices based on the farm’s pedoclimatic and topographic characteristics. Hence, the primary objective of this study was to use multiple satellite-derived indices and environmental drivers to infer the level of tillage intensity and identify the presence of cover crops in eastern South Dakota (SD). We used a machine learning classifier trained with in situ field samples and environmental drivers acquired from different remote sensing datasets for 2022 and 2023 to map the conservation agriculture practices. Our classification accuracies (>80%) indicate that the employed satellite spectral indices and environmental variables could successfully detect the presence of cover crops and the tillage intensity in the study region. Our analysis revealed that 4% of the corn (Zea mays) and soybean (Glycine max) fields in eastern SD had a cover crop during either the fall of 2022 or the spring of 2023. We also found that environmental factors, specifically seasonal precipitation, growing degree days, and surface texture, significantly impacted the use of conservation practices. The methods developed through this research may provide a viable means for tracking and documenting farmers’ agricultural management techniques. Our study contributes to developing a measurement, reporting, and verification (MRV) solution that could help used to monitor various climate-smart agricultural practices. 

Interdisciplinary environmental and sustainability (IES) programs are different from other fields because they focus on a complex integration of humanities, social, and natural sciences concepts centered on the interactions of coupled human and natural systems. The interdisciplinary nature of IES programs does not lend itself to traditional discipline-specific concept inventory frameworks for critically evaluating preconceptions and learning. We discuss the results of the first phase of a research project to develop a next generation concept inventory for evaluating interdisciplinary concepts important for introductory IES courses. Using the Food-Energy-Water (FEW) Nexus (the intersections/interdependencies of food, energy, and water sectors) as our focus, we conducted a content analysis of eight representative college-level introductory environmental course syllabi and course materials (e.g., textbooks, journal articles, print media) to identify common interdisciplinary FEW Nexus concepts taught in introductory IES courses. Results demonstrate that all IES introductory course materials reference the FEW Nexus. Food, energy, and/or water resources as individual elements of the FEW Nexus are frequently described, but connections between these resource systems are included less often. Biology, energy systems, waste and pollution in the natural environment, agriculture, earth sciences and geology, climate change, behavioral social sciences, and economics concepts are most associated with FEW concepts, hinting at commonalities across IES topics that anchor systems thinking. Despite differences in IES programs, there appears to be some alignment between core concepts being taught at the FEW Nexus in introductory courses. 

Abstract Achieving food security is a critical challenge of the Anthropocene that may conflict with environmental and societal goals such as increased energy access. The “fuel versus food” debate coupled with climate mitigation efforts has given rise to next-generation biofuels. Findings of this systematic review indicate just over half of the studies (56% of 224 publications) reported a negative impact of bioenergy production on food security. However, no relationship was found between bioenergy feedstocks that are edible versus inedible and food security ( P value = 0.15). A strong relationship was found between bioenergy and type of food security parameter ( P value < 0.001), sociodemographic index of study location ( P value = 0.001), spatial scale ( P value < 0.001), and temporal scale ( P value = 0.017). Programs and policies focused on bioenergy and climate mitigation should monitor multiple food security parameters at various scales over the long term toward achieving diverse sustainability goals.