Applications of behavioral science to biodiversity management in agricultural landscapes: conceptual mapping and a California case study

Environ Monit Assess. 2021 May 14;193(Suppl 1):270. doi: 10.1007/s10661-020-08815-z.

Abstract

The plot-level decisions of land managers (i.e., farmers, ranchers, and forest owners) influence landscape-scale environmental outcomes for biodiversity in agricultural landscapes. The impacts of their decisions often develop in complex, non-additive ways that unfold over time and space. Behavioral science offers insights into ways decision-makers manage complexity, uncertainty, choice over time, and social influence. We review such insights to understand the plot-level conservation actions of farmers that impact biodiversity. To make these connections concrete, we provide a case study of the decision to adopt biodiversity management practices in the heavily cultivated region of the Central Valley, California, USA. We use results from a survey of 122 farmers in the region to test whether adoption is related to farm tenure arrangements or peer influence. We find farmers who are more sensitive to peer influence are three times more likely to adopt practices that support biodiversity, including wildflowers, native grasses, cover crops, hedgerows, and wetlands. This relationship could have important implications for how plot-level decisions aggregate to landscape-scale outcomes. Finally, we suggest priorities for future research and program design to integrate behavioral science into biodiversity conservation in agricultural landscapes. By considering land managers' plot-level conservation decisions with the lens of behavioral science, we identify barriers and opportunities to promote environmental benefits.

Keywords: Behavioral science; Biodiversity conservation; Farmer decision-making; Working landscapes.

Publication types

  • Review

MeSH terms

  • Agriculture
  • Behavioral Sciences*
  • Biodiversity
  • California
  • Conservation of Natural Resources*
  • Environmental Monitoring