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1. Are Glyphosate‐Resistant Weeds a Threat to Conservation Agriculture? Evidence from Tillage Practices in Soybeans

   https://doi.org/10.1111/ajae.12243  

   Van Deynze, Braeden; Swinton, Scott M.; Hennessy, David A. (June 2021, American Journal of Agricultural Economics)

   null (Ed.)

   Conservation tillage in American soybean production has become increasingly common, improving soil health while reducing soil erosion and fuel consumption. This trend has been reinforced by the widespread adoption of glyphosate-based weed control systems. Many weed species have since evolved to resist glyphosate, reducing its effectiveness. We provide evidence that the spread of glyphosate-resistant weeds is responsible for significant reductions in the use of conservation tillage in soybean production. We estimate reduced-form and structural probit models of tillage choice, using a large panel of field-level soybean management decisions from across the United States spanning 1998-2016. We find that the first emergence of glyphosate-resistant weed species has little initial effect on tillage practices, though by the time that eight glyphosate-resistant weed species are identified, conservation tillage and no-till use fall by 3.9 percentage points and 7.6 percentage points, respectively. We further find that when ten glyphosate-resistant species are present, the predicted adoption rate of non-glyphosate herbicides rises 50 percentage points, and that the availability of non-glyphosate herbicides facilitates continued use of conservation tillage as glyphosate-resistant weeds proliferate. Using a simple benefits transfer model, we conservatively estimate that between 2008 and 2016 farmers' tillage responses to the spread of glyphosate-resistant weeds have caused water quality and climate damages via fuel emissions valued at nearly $245 million. This value does not account for climate damages due to carbon released during soil disruptions and is likely to grow as glyphosate resistance becomes more widespread and more farmers turn to tillage for supplemental weed control. 

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2. Monitoring the Spatial Distribution of Cover Crops and Tillage Practices Using Machine Learning and Environmental Drivers across Eastern South Dakota

   https://doi.org/10.1007/s00267-024-02021-0  

   Jain, Khushboo; John, Ranjeet; Torbick, Nathan; Kolluru, Venkatesh; Saraf, Sakshi; Chandel, Abhinav; Henebry, Geoffrey M; Jarchow, Meghann (October 2024, Environmental Management)

   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. 

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3. Scaling up conservation agriculture: An exploration of challenges and opportunities through a stakeholder engagement process

   https://doi.org/10.1002/jeq2.20317  

   Reimer, A.; Doll, J_E; Boring, T_J; Zimnicki, T. (January 2022, Journal of Environmental Quality)

   Abstract Increasing the resilience of agricultural landscapes requires fundamental changes to the dominant commodity production model, including incorporating practices such as reduced tillage, cover cropping, and extended rotations that reduce soil disturbance while increasing biological diversity. Increasing farmer adoption of these conservation systems offers the potential to transform agriculture to a more vibrant, resilient system that protects soil, air, and water quality. Adoption of these resilience practices is not without significant challenges. This paper presents findings from a participatory effort to better understand these challenges and to develop solutions to help producers overcome them. Through repeated, facilitated discussions with farmers and agricultural and conservation professionals across the U.S. state of Michigan, we confronted the policy, economic, and structural barriers that are inhibiting broader adoption of conservation systems, as well as identified policies, programs, and markets that can support their adoption. What emerged was a complex picture and dynamic set of challenges at multiple spatial scales and across multiple domains. The primary themes emerging from these discussions were barriers and opportunities, including markets, social networks, human capital, and conservation programs. Exacerbating the technical, agronomic, and economic challenges farmers face at the farm level, there are a host of community constraints, market access and availability problems, climatic and environmental changes, and policies (governmental and corporate) that cross‐pressure farmers when it comes to making conservation decisions. Understanding these constraints is critical to developing programs, policies, and state and national investments that can drive adoption of conservation agriculture. 

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4. SOMOSPIE: A Modular SOil MOisture SPatial Inference Engine Based on Data-Driven Decisions

   https://doi.org/10.1109/eScience.2019.00008  

   Rorabaugh, Danny; Guevara, Mario; Llamas, Ricardo; Kitson, Joy; Vargas, Rodrigo; Taufer, Michela (September 2019, 15th International Conference on eScience, eScience 2019, San Diego, CA, USA, September 24-27, 2019)

   The current availability of soil moisture data over large areas comes from satellite remote sensing technologies (i.e., radar-based systems), but these data have coarse resolution and often exhibit large spatial information gaps. Where data are too coarse or sparse for a given need (e.g., precision farming), one can leverage machine-learning techniques coupled with other sources of environmental information (e.g., topography) to generate gap-free information at a finer spatial resolution (i.e., increased granularity). To this end, we develop a spatial inference engine consisting of modular stages for processing spatial environmental data, generating predictions with machine-learning techniques, and analyzing these predictions. We demonstrate the functionality of this approach and the effects of data processing choices via multiple prediction maps over a United States ecological region with a highly diverse soil moisture profile (i.e., the Middle Atlantic Coastal Plains). The relevance of our work derives from a pressing need to improve the spatial representation of soil moisture for applications in environmental sciences (e.g., ecological niche modeling, carbon monitoring systems, and other Earth system models) and precision farming (e.g., optimizing irrigation practices and other land management decisions). 

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5. Farmer perceived challenges toward conservation practice usage in the margins of the Corn Belt, USA

   https://doi.org/10.1017/S1742170523000042  

   Adhikari, Ram Kumar; Wang, Tong; Jin, Hailong; Ulrich-Schad, Jessica D.; Sieverding, Heidi L.; Clay, David (January 2023, Renewable Agriculture and Food Systems)

   While conservation practices promote soil health and reduce the negative environmental effects from agricultural production, their adoption rates are generally low. To facilitate farmer adoption, we carried out a survey to identify potential challenges faced by farmers regarding conservation tillage and cover crop adoption in the western margin of the US Corn Belt. We found farmers' top two concerns regarding conservation tillage were delayed planting, caused by slow soil warming in spring, and increased dependence on herbicide and fungicides. Narrow planting window and lack of time/labor were perceived by farmers as the two primary challenges for cover crop adoption. Some sense of place factors, including the commonly included dimensions of attachment, identity and dependence, played a role in farmers' perceived challenges. For example, respondents more economically dependent on farming perceived greater challenges. We found that farmers' challenge perceptions regarding reduced yield and lack of time/labor significantly decreased as years of usage increased, implying that time and experience could dilute some challenges faced by farmers. Our findings indicate that social network use, technical guidance and economic subsidies are likely to address the concerns of farmers and facilitate their adoption of conservation practices. 

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