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The Global Spatial Co‐Variation Between Crop Diversity and Landscape Heterogeneity

Erin Gleeson,Graham K. MacDonald

Published 2025 in Global Change Biology

ABSTRACT

The influence of crop and landscape heterogeneity on different components of biodiversity in agricultural landscapes has been assessed at multiple scales. However, how crop species diversity relates to landscape heterogeneity remains underexplored at the global scale. We apply independent global spatial datasets to test the relationship between crop and landscape heterogeneity across 19,505 agricultural landscapes worldwide. We first examine the spatial patterns in crop diversity and landscape diversity (compositional heterogeneity), defined as the effective number of crop species and land cover types, respectively, based on Shannon entropy. Median crop diversity increases on average by 0.36–0.48 effective species for each unit increase in land cover diversity globally. We use quantile generalized additive models (QGAM) to statistically test this relationship. The QGAM approach confirms that crop diversity has a positive but complex relationship with landscape diversity, particularly for landscapes with ≥ 4–5 non‐crop cover types. However, this positive trend is context‐dependent, as the clearest median response generally corresponds to landscapes with moderate cropland extents (25%–75% cropland). We also examine how other components of landscape compositional and configurational heterogeneity, including dominant agricultural field size and patch size, as well as topographic heterogeneity are associated with crop diversity. The relatively highest crop diversity tends to correspond to very small dominant agricultural field sizes (crop configurational heterogeneity) when controlling for cropland extent and non‐agricultural land cover diversity. Mean patch area (landscape configurational heterogeneity) has a strong negative association with crop diversity until patch sizes of > 150 km2 while topographic heterogeneity has a consistent positive association with crop diversity. Our findings therefore demonstrate how the diversity of non‐agricultural land covers in conjunction with configurational heterogeneity has relevance to understanding existing patterns of spatial crop diversity. Such insights could help inform efforts to design more multifunctional agricultural landscapes, including landscape‐scale farm diversification strategies.

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