TY - JOUR

T1 - Applying generic landscape-scale models of natural pest control to real data

T2 - Associations between crops, pests and biocontrol agents make the difference

AU - Bonato, Marta

AU - Martin, Emily A.

AU - Cord, Anna F.

AU - Seppelt, Ralf

AU - Beckmann, Michael

AU - Strauch, Michael

N1 - Funding Information: The authors would like to thank the data owners of the case studies for allowing us to use the high-resolution land use maps they produced: Mario V. Balzan, Berta Caballero-López, Matteo Dainese, Marina Kaiser, Adrien Rusch, Henrik Smith, Christof Schüepp, Martin Entling, Louis Sutter, Matthias Albrecht, Giovanni Tamburini. The authors would also like to thank Bartosz Bartkowski for support in writing this paper, Carlo Rega and Maria Luisa Paracchini for initial exchange on the Pest Control Potential model, Viviana Alarcón Segura for discussions on crop-pest-biocontrol agents associations and Mick Wu for statistical advice. This work was carried out within the framework of the UFZ PhD consortium INTERCEDE.

PY - 2023/2/1

Y1 - 2023/2/1

N2 - Managing agricultural land to maximize the supply of natural pest control can help reduce pesticide use. Tools that are able to represent the relationship between landscape structure, field management and natural pest control can help in deciding which management practices should be used and where. However, the reliability and the predictive power of generic models of natural pest control is largely unknown. We applied an existing generic model of natural pest control potential based on landscape structure to nine sites in five European countries and tested the resulting values against field measurements of natural pest control. Subsequently, we added information on local level factors to test the possibility of improving model performance and predictive power. The results showed that there is generally little or no evidence of correlation between modeled and field-measured values of natural pest control. Moreover, we found high variability in the results, depending on the associations of crops, pests and biocontrol agents considered (e.g. Oilseed rape-Pollen beetle-Parasitoids) and on the different case studies. Factors at the local level, such as conservation tillage, had an overall positive effect on natural pest control, and their inclusion in the models typically increased their predictive power. Our results underline the importance of developing predictive models of natural pest control which are tailored towards specific associations between crops, pests and biocontrol agents, consider local level factors and are trained using field measurements. They would serve as important tools within farmers' decision making, ultimately supporting the shift toward a low-pesticide agriculture.

AB - Managing agricultural land to maximize the supply of natural pest control can help reduce pesticide use. Tools that are able to represent the relationship between landscape structure, field management and natural pest control can help in deciding which management practices should be used and where. However, the reliability and the predictive power of generic models of natural pest control is largely unknown. We applied an existing generic model of natural pest control potential based on landscape structure to nine sites in five European countries and tested the resulting values against field measurements of natural pest control. Subsequently, we added information on local level factors to test the possibility of improving model performance and predictive power. The results showed that there is generally little or no evidence of correlation between modeled and field-measured values of natural pest control. Moreover, we found high variability in the results, depending on the associations of crops, pests and biocontrol agents considered (e.g. Oilseed rape-Pollen beetle-Parasitoids) and on the different case studies. Factors at the local level, such as conservation tillage, had an overall positive effect on natural pest control, and their inclusion in the models typically increased their predictive power. Our results underline the importance of developing predictive models of natural pest control which are tailored towards specific associations between crops, pests and biocontrol agents, consider local level factors and are trained using field measurements. They would serve as important tools within farmers' decision making, ultimately supporting the shift toward a low-pesticide agriculture.

KW - Agricultural management

KW - Landscape complexity

KW - Natural pest control

KW - Predictive modeling

UR - http://www.scopus.com/inward/record.url?scp=85140302884&partnerID=8YFLogxK

U2 - 10.1016/j.agee.2022.108215

DO - 10.1016/j.agee.2022.108215

M3 - Article

AN - SCOPUS:85140302884

VL - 342

JO - Agriculture, Ecosystems and Environment

JF - Agriculture, Ecosystems and Environment

SN - 0167-8809

M1 - 108215

ER -