Landscape composition and configuration have scale-dependent effects on agricultural pest suppression
Abstract
Increasing landscape heterogeneity (composition and configuration) can enhance natural enemy populations and support pest suppression in agricultural landscapes. Using a network-based data mining approach, we examined independent gradients of landscape composition and configuration at six spatial scales that were associated with pest suppression services measured at 32 sites in Michigan and Wisconsin, USA. We compared the relative effects of landscape composition and configuration across scales with those of local crop type (corn or grassland). We found that multiple gradients of configurational heterogeneity were independent of composition and strongly associated with pest suppression, with different configuration metrics being predictive of pest suppression depending on the spatial scales and regions considered. Landscapes that were more configurationally heterogeneous at smaller spatial scales consistently supported higher pest suppression. In Michigan, pest suppression increased in landscapes with high edge contrast between annual crops and surrounding habitats and high edge density of grassland within 250-500 m radii. In Wisconsin, pest suppression increased with large core area of grassland and high field density within a 250 m radius. The main compositional effect we found was a positive relationship between grassland cover and pest suppression occurring at larger spatial scales (1000-1500 m) and occurring in Wisconsin but notmore »
- Authors:
-
[1];
[1]
- Michigan State Univ., East Lansing, MI (United States). Great Lakes Bioenergy Research Center
- Publication Date:
- Research Org.:
- Michigan State Univ., East Lansing, MI (United States). Great Lakes Bioenergy Research Center
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF)
- OSTI Identifier:
- 1682302
- Alternate Identifier(s):
- OSTI ID: 1776962
- Grant/Contract Number:
- SC0018409
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Agriculture, Ecosystems and Environment
- Additional Journal Information:
- Journal Volume: 302; Journal ID: ISSN 0167-8809
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Landscape configuration; Landscape composition; Multiscale; Natural enemies; Natural pest suppression; Weighted correlation network analysis (WGCNA)
Citation Formats
Zhang, Yajun, Haan, Nathan L., and Landis, Douglas A. Landscape composition and configuration have scale-dependent effects on agricultural pest suppression. United States: N. p., 2020.
Web. doi:10.1016/j.agee.2020.107085.
Zhang, Yajun, Haan, Nathan L., & Landis, Douglas A. Landscape composition and configuration have scale-dependent effects on agricultural pest suppression. United States. https://doi.org/10.1016/j.agee.2020.107085
Zhang, Yajun, Haan, Nathan L., and Landis, Douglas A. Tue .
"Landscape composition and configuration have scale-dependent effects on agricultural pest suppression". United States. https://doi.org/10.1016/j.agee.2020.107085. https://www.osti.gov/servlets/purl/1682302.
@article{osti_1682302,
title = {Landscape composition and configuration have scale-dependent effects on agricultural pest suppression},
author = {Zhang, Yajun and Haan, Nathan L. and Landis, Douglas A.},
abstractNote = {Increasing landscape heterogeneity (composition and configuration) can enhance natural enemy populations and support pest suppression in agricultural landscapes. Using a network-based data mining approach, we examined independent gradients of landscape composition and configuration at six spatial scales that were associated with pest suppression services measured at 32 sites in Michigan and Wisconsin, USA. We compared the relative effects of landscape composition and configuration across scales with those of local crop type (corn or grassland). We found that multiple gradients of configurational heterogeneity were independent of composition and strongly associated with pest suppression, with different configuration metrics being predictive of pest suppression depending on the spatial scales and regions considered. Landscapes that were more configurationally heterogeneous at smaller spatial scales consistently supported higher pest suppression. In Michigan, pest suppression increased in landscapes with high edge contrast between annual crops and surrounding habitats and high edge density of grassland within 250-500 m radii. In Wisconsin, pest suppression increased with large core area of grassland and high field density within a 250 m radius. The main compositional effect we found was a positive relationship between grassland cover and pest suppression occurring at larger spatial scales (1000-1500 m) and occurring in Wisconsin but not in Michigan. Our findings demonstrate that effects of landscape composition and configuration on pest suppression differ across spatial scales and vary regionally. The network-based data mining techniques used here could be useful for disentangling intercorrelated landscape metrics in a variety of other contexts in landscape ecology.},
doi = {10.1016/j.agee.2020.107085},
journal = {Agriculture, Ecosystems and Environment},
number = ,
volume = 302,
place = {United States},
year = {Tue Jul 28 00:00:00 EDT 2020},
month = {Tue Jul 28 00:00:00 EDT 2020}
}
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Fig. 1: Overview of multiscale modeling process combined with weighted gene correlation network analysis (WGCNA) used to address our research questions (gray boxes). Detailed interpretation of correlation networks, modules, and module representatives is presented in Fig. S1.
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