Tue, Aug 16, 2022: 5:00 PM-6:30 PM
ESA Exhibit Hall
Background/Question/MethodsCrop species diversity has an important role in agricultural landscape sustainability and resilience. In recent decades, the intensification of agriculture in North America has coincided with more homogenous agricultural landscapes, often with fewer crop species being grown in larger fields. This has important implications for the provision of ecosystem services in agroecosystems (e.g., pest and disease regulation), particularly when general landscape diversity is also reduced through conversion of forests and other remnant natural vegetation to agriculture. Although previous research has addressed various aspects of crop diversity at larger (e.g., national) and more local (e.g., single landscape) scales, relatively little work has characterized the relationship between crop diversity, field size, and the configuration of other land covers connecting these two scales. We address this gap through spatial pattern analysis of existing 30-m resolution cropland and land cover datasets for the United States. Our objectives are to: (1) examine how crop diversity relates to land cover composition and configuration across landscapes nationally by producing a classified map of agricultural landscape structure that incorporates crop composition; and (2) statistically assess the relationship between crop diversity and general land cover diversity across landscape cluster types, examining climate and soil type as potential moderating variables.
Results/ConclusionsOur initial findings demonstrate how the use of landscape metrics incorporating both crop diversity and field size reveals distinct agricultural landscape types across the United States. Our preliminary cluster analysis can also help to identify landscapes in different regions with similar patterns of crop diversity, general land cover diversity (including forest and other semi-natural vegetation patches) as well how these features are geographically distributed (based on crop field size and shape, natural land cover size and shape). Based on these results, we develop the hypothesis that agricultural landscapes with greater compositional heterogeneity (incorporating remnant natural land cover and diverse crop rotations) will be characterized by greater configurational heterogeneity (smaller field sizes and increased natural vegetation intermixed with agricultural fields). Our investigation so far suggests that incorporating crop mix alongside the diversity of other vegetation types affects understanding of landscape compositional heterogeneity and thus how to define agricultural landscape structure more generally. Classifying agricultural landscapes into distinct typologies that incorporates the composition and configuration of crop fields as well as other remnant vegetation can improve our understanding of spatial patterns of agrobiodiversity, including the role of crop diversity in agroecosystem resilience and the provision of multiple ecosystem services.
Results/ConclusionsOur initial findings demonstrate how the use of landscape metrics incorporating both crop diversity and field size reveals distinct agricultural landscape types across the United States. Our preliminary cluster analysis can also help to identify landscapes in different regions with similar patterns of crop diversity, general land cover diversity (including forest and other semi-natural vegetation patches) as well how these features are geographically distributed (based on crop field size and shape, natural land cover size and shape). Based on these results, we develop the hypothesis that agricultural landscapes with greater compositional heterogeneity (incorporating remnant natural land cover and diverse crop rotations) will be characterized by greater configurational heterogeneity (smaller field sizes and increased natural vegetation intermixed with agricultural fields). Our investigation so far suggests that incorporating crop mix alongside the diversity of other vegetation types affects understanding of landscape compositional heterogeneity and thus how to define agricultural landscape structure more generally. Classifying agricultural landscapes into distinct typologies that incorporates the composition and configuration of crop fields as well as other remnant vegetation can improve our understanding of spatial patterns of agrobiodiversity, including the role of crop diversity in agroecosystem resilience and the provision of multiple ecosystem services.