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Sustainable agriculture requires cooperative and coordinated action across multiple sectors and policy domains. However, farmer-stakeholder behaviors and action remain pivotal to sustainable food system management in many rural development contexts. We assess farmer pro-environmental behavioral intention through the development and application of a novel integrated approach combining two dominant psychological theories of behavior change: the Norm Activation Model (NAM) and Theory of Planned Behavior (TPB). We apply this framework to targeted research with potato growers of Kerman Province in southeastern Iran, using survey data (sample n = 381) analyzed through structural equation modeling (SEM). The integrated NAM-TPB model provides insight into both pro-social and self-interested motivations for farmer pro-environmental behavioral intention, with the model explaining 77% of total variance. We found that three variables, Awareness of Consequence (AC), Perceived Behavioral Control (PBC), and Subjective Norms (SN) were the strongest indicators of pro-environmental behavioral intention. We recommend therefore that agricultural extension and state-led farmer education should first emphasize awareness-raising of negative environmental impacts of current farming practices within training programs, and second, improve social learning amongst farmer communities through sustained farmer community engagement, thus “stabilizing” a social norm of environmental protection amongst peer networks of agricultural workers.

Estimates of long-term change and land cover changes using satellite imagery update data about effects erosion on the destruction. This is relevant on semi-arid land where soil resources are scarce, and proper management requires matching LULC to the conditions to achieve sustainability. This study evaluates the impact of LULC changes on soil erosion using Landsat satellite images and the RUSLE model on plains around the Jarahi River and Shadegan International Wetlands. The maps of LULC were prepared with supervised classification and maximum-likelihood methods applied to pre-processed TM, ETM, and OLI images for 1989, 2003, and 2017. This study investigated the impacts of LULC changes on soil erosion. Based on the results, we observe that an assessment of LULC changes from 1989 to 2003 revealed diminishing bare land and wetland vegetation with increases in agricultural land and water features. The areas of agricultural lands and wetlands decreased from 2003 to 2017, while bare lands increased in the area. The areas with soil erosion rates < 1 Mg ha -1 y -1 have diminished, and areas having rates >1 Mg ha -1 y -1 increased in extent.We conclude that LULC changes led to increased soil erosion in Shadegan International Wetlands.Our study highlights the need to plan LULC changes to reduce soil erosion rates to achieve sustainable management. We argue that nature-based solutions can effectively reduce soil losses.

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