Lessons learned from using a decision-support tool for precision placement of conservation practices in six agricultural watersheds in the US midwest

2019 
Abstract While conservation of natural resources on agricultural landscapes has been a priority for public agencies for more than 80 years, the ability of conservation planners to place conservation practices for enhanced environmental benefits remains elusive. To increase both adoption of conservation practices and efficient use of conservation funding, conservation planners are turning to decision support tools (DSTs), such as the Agricultural Conservation Planning Framework (ACPF). However, less is known about how DSTs facilitate a whole-landscape approach to conservation planning, and the strategies that are employed by conservation planners to engage with producers using new GIS-enabled planning technologies. With the goal of contributing to both the policy and practice of precision conservation, we present findings from semi-structured in-depth interviews conducted with 21 conservation professionals in six watersheds in the US Midwest. Results suggest that the ACPF encourages conservation professionals to think at a watershed scale, supports their approach to conservation planning, and helps them in watershed planning and stakeholder engagement. Results also highlight the importance of conservation professionals employing a suite of strategies, such as being mindful of the scale of producer engagement (i.e., single farm vs community based) and accounting for producers' personalities, to create ‘enabling conditions’ for producer engagement when adopting a precision approach to conservation. Policy recommendations for precision conservation technologies include the need to streamline and expedite the process of conservation delivery, and that DSTs are a means to an end, but not a universal remedy, because conservation planning is most effective when localized interactions of rural landscapes and social dynamics are considered in an adaptive approach.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    26
    References
    14
    Citations
    NaN
    KQI
    []