TY - JOUR

T1 - Modelling potential natural pest control ecosystem services provided by arthropods in agricultural landscapes

AU - Perennes, Marie

AU - Diekötter, Tim

AU - Hoffmann, Hannes

AU - Martin, Emily A.

AU - Schröder, Boris

AU - Burkhard, Benjamin

N1 - Funding Information: This study was partly funded by the BiodivERsA project “IMAGINE”, supported in Germany by the BMBF – Federal Ministry for Research and Education. M.P. was supported by a grant from the Graduate Academy of the Leibniz University of Hannover .

PY - 2023/2/1

Y1 - 2023/2/1

N2 - Natural pest control has the potential to reduce pesticide use. Therefore, it has an essential role to play in the transition towards a more sustainable agriculture. For the prediction of natural pest control, it is essential to understand the distribution of the species providing this ecosystem service. The presence of pests and natural enemies depends on a combination of abiotic and biotic factors, each playing a determining role at different spatial scales. We developed a hierarchical model composed of environmental predictors including bioclimatic and land use variables at the European scale, as well as landscape complexity and biotic interactions at the landscape scale. This paper presents the predicted distribution of 111 species from seven different arthropod families (two pest aphid species and their natural enemy species) in an agricultural region in northern Germany. The hierarchical framework allows determining the capacity of landscapes to support pest control ecosystem services provided by arthropods at the local scale and informs on vulnerable areas or potential mismatches between natural pest control demand and supply. Thereby it can support the design of local scale measures for habitat improvement, biodiversity conservation and the increase of ecosystem services supply. The hierarchical approach can be adapted to other agroecosystems and leaves potential for further adaptations to improve the prediction of pests and their natural enemy distribution, dynamics and factors influencing their spatial distribution.

AB - Natural pest control has the potential to reduce pesticide use. Therefore, it has an essential role to play in the transition towards a more sustainable agriculture. For the prediction of natural pest control, it is essential to understand the distribution of the species providing this ecosystem service. The presence of pests and natural enemies depends on a combination of abiotic and biotic factors, each playing a determining role at different spatial scales. We developed a hierarchical model composed of environmental predictors including bioclimatic and land use variables at the European scale, as well as landscape complexity and biotic interactions at the landscape scale. This paper presents the predicted distribution of 111 species from seven different arthropod families (two pest aphid species and their natural enemy species) in an agricultural region in northern Germany. The hierarchical framework allows determining the capacity of landscapes to support pest control ecosystem services provided by arthropods at the local scale and informs on vulnerable areas or potential mismatches between natural pest control demand and supply. Thereby it can support the design of local scale measures for habitat improvement, biodiversity conservation and the increase of ecosystem services supply. The hierarchical approach can be adapted to other agroecosystems and leaves potential for further adaptations to improve the prediction of pests and their natural enemy distribution, dynamics and factors influencing their spatial distribution.

KW - Arthropod community

KW - Biological control

KW - Ensemble species distribution models

KW - Hierarchical models

KW - Joint species distribution models

KW - Landscape complexity

KW - Natural enemies

KW - Species richness

UR - http://www.scopus.com/inward/record.url?scp=85141341489&partnerID=8YFLogxK

U2 - 10.1016/j.agee.2022.108250

DO - 10.1016/j.agee.2022.108250

M3 - Article

AN - SCOPUS:85141341489

VL - 342

JO - Agriculture, Ecosystems and Environment

JF - Agriculture, Ecosystems and Environment

SN - 0167-8809

M1 - 108250

ER -