Understanding South Dakota Farmers’ Intentions to and Adoption of Conservation Practices: An Examination of the Theory of Planned Behavior

Conservation agriculture practice is a sustainable farming method based on three principle: crop diversification, minimal soil disturbance or movement and permanent or semi-permanent of soil cover. Government and stakeholders within the agricultural sector in the United States are promoting conservation farming practices but limited voluntary adoption still exists among producers at the farm level. This research study investigated the factors that influence the adoption of conservation practices among producers in the eastern and central parts of South Dakota (SD). A modified theory of planned behavior (TPB) is used as a framework alongside socioeconomic and demographic indicators to understand farmers’ current behavior and future intentions towards the adoption of conservation practices. Data were gathered from a sample of 3000 farming operations whose main crops are corn, soybeans, and wheat. Respondents were contacted three times using a modified tailored design approach by Don A. Dillman. The results from the Pearson correlation and the binary logistic regression confirms that TPB is a useful framework for understanding the behavior of farmers. Most of the three constructs of the TPB correlated significantly to the adoption of cover crops, conservation tillage, and diversified crop rotation. The binary logistic regression model also suggests that attitude and perceived behavioral control predicted farmers\u27 likelihood of adopting conservation tillage. This study also provided empirical evidence of the conservation practices producers currently use and those that they don’t use but intend to use in the future. This will help policymakers and conservation practitioners to develop policy measures that will help increase the voluntary adoption of conservation practices among farmers in SD

Chesapeake Bay Watershed Residents’ and Farmers’ Views on Water Quality

Poor water quality is an issue in the Chesapeake Bay Watershed (CBW). In this rapidly urbanizing landscape, both farmers and non-farm residents contribute to nutrient pollution of rivers and streams. Understanding these important stakeholders’ views of water quality problems and how to address them is essential for creating an economically thriving and environmentally beneficial agricultural system that all residents depend upon. To understand stakeholder views on water quality both locally and regionally, researchers from Utah State University and the Pennsylvania State University surveyed residents of the CBW and agricultural producers of the southern part of the CBW (Maryland, Delaware, and Virginia) in 2021 and 2022, respectively

Chesapeake Bay Watershed Residents’ and Farmers’ Concerns and Perceptions of Water Quality

Poor water quality is an issue in the Chesapeake Bay Watershed (CBW). In this rapidly urbanizing landscape, both farmers and non-farm residents contribute to nutrient pollution of rivers and streams. Understanding these important stakeholders’ views of water quality problems and how to address them is essential for creating an economically thriving and environmentally beneficial agricultural system that all residents depend upon. To understand key stakeholders’ views on water quality both locally and regionally, researchers from Utah State University and the Pennsylvania State University surveyed residents of the CBW and agricultural producers of the southern part of the CBW (Maryland, Delaware, and Virginia) in 2021 and 2022, respectively

Chesapeake Bay Watershed Residents’ and Farmers’ Views on Urban and Suburban Growth

What the future of agriculture in the Chesapeake Bay Watershed (CBW) will look like is uncertain due to issues such as the loss of farmland to sprawling suburban development. In this rapidly urbanizing landscape, tension can also arise between farmers and their non-farm neighbors due to their proximity to each other. Understanding the concerns of these stakeholders regarding the urban and suburban growth and the potential problems that are likely to occur with farmers being in close contact with their non-farm neighbors is a good step in ensuring an economically thriving and environmentally beneficial agricultural system that all residents depend upon

An Inventory and Assessment of Sample Sources for Survey Research with Agricultural Producers in the U.S.

Researchers need probability samples to collect representative survey data about the behaviors and attitudes of agricultural producers they study in relation to the natural resources that they manage, yet obtaining accurate and complete sampling frames is challenging. We extract data from a publication database to identify the most commonly used sampling frame sources in survey research of agricultural producers in the U.S., finding that government program participant lists are used most often, while private vendor samples are increasingly being purchased. Based on our research experience, we find that for many projects, private vendors can provide the most rigorous samples. Given that survey methods remain a useful and popular method for studying the behaviors and attitudes of producers on a variety of topics, such an assessment and guide is needed for researchers and practitioners

Farmer Adoption of Efficient Inorganic Nitrogen Fertilizer Management Practices in South Dakota

Nitrogen (N) fertilizer use has led to reductions in air and water quality but is essential for increasing crop production. Following the 4Rs of nutrient management (right: source, rate, timing, and placement), specifically following university N rate guidelines, proper urea fertilizer management, use of enhanced efficiency fertilizers, and splitting up inorganic fertilizer-N applications can minimize potential negative environmental effects. Data from a 2019 probability sample survey of 465 South Dakota farmers were used to examine how local and operational characteristics (geographic location, tillage practice, and farm size) are related to the adoption of these four Rs of nutrient management practices. Factors included in inorganic N rate decisions from most to least were use of preplant soil test N (74%), yield potential (68%), previous crop credit (48%), manure credit (25%), and tillage type (16%). Of all the factors used to make fertilizer-N rate decisions, only the use of previous crop and manure credit factors were influenced by farm location and tillage method but not farm size. Of all respondents, 30% used urease inhibitors to minimize ammonia (NH3 ) loss and 31% applied urea before predicted precipitation. However, farms in drier, central South Dakota and no-till farms used urease inhibitors and applied before predicted precipitation more often than farms in wetter, eastern South Dakota and conventional- and reduced-tillage farms, who were more likely to use tillage to incorporate urea. To minimize leaching and denitrification loss, farms in eastern South Dakota where normal rainfall is greater used nitrification inhibitors or slow-release fertilizers and split-N applications (48% and 53%, respectively), while fewer farms in central South Dakota where normal rainfall is less used these technologies (34% and 36%, respectively). Larger farms more frequently used urease and nitrification inhibitors, and/ or slow-release fertilizer technologies to minimize N loss. These results indicate that local and operational characteristics including geographic location, tillage, and farm size influence on-farm decisions concerning the adoption of these 4R management practices and should be considered when investigating and promoting 4R practices

An Examination of Best Practices for Survey Research with Agricultural Producers

To improve the economic and environmental sustainability of agriculture, information is needed on how to target research, teaching, and outreach programs. However, conducting survey research in general, and with agricultural producers specifically, is increasingly challenging given issues such as declining response rates and limited resources. While studies examining the best practices for promoting higher response rates exist, few focus explicitly on agricultural producers. In three separate surveys conducted with agricultural producers in South Dakota in 2018 and 2019, we included experiments testing how token pre-incentives, a research partnership, and response mode options impacted response rates. We also examined how sample source and email augmentations influence survey responses. The study findings indicate that providing pre-incentives and multiple simultaneous response options can increase response rates with agricultural producers. On the other hand, email augmentation to mail surveys, sample source, and identification of select institutional research partnerships appear to have minimal effects

An Inventory and Assessment of Sample Sources for Survey Research with Agricultural Producers in the U.S.

Researchers need probability samples to collect representative survey data about the behaviors and attitudes of agricultural producers they study in relation to the natural resources that they manage, yet obtaining accurate and complete sampling frames is challenging. We extract data from a publication database to identify the most commonly used sampling frame sources in survey research of agricultural producers in the U.S., finding that government program participant lists are used most often, while private vendor samples are increasingly being purchased. Based on our research experience, we find that for many projects, private vendors can provide the most rigorous samples. Given that survey methods remain a useful and popular method for studying the behaviors and attitudes of producers on a variety of topics, such an assessment and guide is needed for researchers and practitioners.This article is published as Ulrich-Schad, Jessica D., Shuang Li, J. G. Arbuckle, Edem Avemegah, Kathryn J. Brasier, Morey Burnham, Anil Kumar Chaudhary et al. "An Inventory and Assessment of Sample Sources for Survey Research with Agricultural Producers in the US." Society & Natural Resources 35 (2022): 804-812. doi:https://doi.org/10.1080/08941920.2022.2081392. Posted with permission.This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way