Models of natural pest control: Towards predictions across agricultural landscapes

Research output: Contribution to journalReview articleResearchpeer review

Authors

  • N. Alexandridis
  • G. Marion
  • R. Chaplin-Kramer
  • M. Dainese
  • J. Ekroos
  • H. Grab
  • M. Jonsson
  • D.S. Karp
  • C. Meyer
  • M.E. O'Rourke
  • M. Pontarp
  • K. Poveda
  • R. Seppelt
  • H.G. Smith
  • E.A. Martin
  • Y. Clough

Research Organisations

External Research Organisations

  • Lund University
  • Biomathematics and Statistics Scotland
  • Stanford University
  • University of Minnesota
  • Eurac Research
  • Cornell University
  • Swedish University of Agricultural Sciences
  • University of California at Davis
  • German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
  • Leipzig University
  • Martin Luther University Halle-Wittenberg
  • Virginia Polytechnic Institute and State University (Virginia Tech)
  • Helmholtz Centre for Environmental Research (UFZ)
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Details

Original languageEnglish
Article number104761
JournalBiological control
Volume163
Early online date3 Sept 2021
Publication statusPublished - Nov 2021

Abstract

Natural control of invertebrate crop pests has the potential to complement or replace conventional insecticide-based practices, but its mainstream application is hampered by predictive unreliability across agroecosystems. Inconsistent responses of natural pest control to changes in landscape characteristics have been attributed to ecological complexity and system-specific conditions. Here, we review agroecological models and their potential to provide predictions of natural pest control across agricultural landscapes. Existing models have used a multitude of techniques to represent specific crop-pest-enemy systems at various spatiotemporal scales, but less wealthy regions of the world are underrepresented. A realistic representation of natural pest control across systems appears to be hindered by a practical trade-off between generality and realism. Nonetheless, observations of context-sensitive, trait-mediated responses of natural pest control to land-use gradients indicate the potential of ecological models that explicitly represent the underlying mechanisms. We conclude that modelling natural pest control across agroecosystems should exploit existing mechanistic techniques towards a framework of contextually bound generalizations. Observed similarities in causal relationships can inform the functional grouping of diverse agroecosystems worldwide and the development of the respective models based on general, but context-sensitive, ecological mechanisms. The combined use of qualitative and quantitative techniques should allow the flexible integration of empirical evidence and ecological theory for robust predictions of natural pest control across a wide range of agroecological contexts and levels of knowledge availability. We highlight challenges and promising directions towards developing such a general modelling framework.

Keywords

    Crop, Ecological modelling, Land use, Landscape, Natural control, Pest

ASJC Scopus subject areas

Sustainable Development Goals

Cite this

Models of natural pest control: Towards predictions across agricultural landscapes. / Alexandridis, N.; Marion, G.; Chaplin-Kramer, R. et al.
In: Biological control, Vol. 163, 104761, 11.2021.

Research output: Contribution to journalReview articleResearchpeer review

Alexandridis, N, Marion, G, Chaplin-Kramer, R, Dainese, M, Ekroos, J, Grab, H, Jonsson, M, Karp, DS, Meyer, C, O'Rourke, ME, Pontarp, M, Poveda, K, Seppelt, R, Smith, HG, Martin, EA & Clough, Y 2021, 'Models of natural pest control: Towards predictions across agricultural landscapes', Biological control, vol. 163, 104761. https://doi.org/10.1016/j.biocontrol.2021.104761
Alexandridis, N., Marion, G., Chaplin-Kramer, R., Dainese, M., Ekroos, J., Grab, H., Jonsson, M., Karp, D. S., Meyer, C., O'Rourke, M. E., Pontarp, M., Poveda, K., Seppelt, R., Smith, H. G., Martin, E. A., & Clough, Y. (2021). Models of natural pest control: Towards predictions across agricultural landscapes. Biological control, 163, Article 104761. https://doi.org/10.1016/j.biocontrol.2021.104761
Alexandridis N, Marion G, Chaplin-Kramer R, Dainese M, Ekroos J, Grab H et al. Models of natural pest control: Towards predictions across agricultural landscapes. Biological control. 2021 Nov;163:104761. Epub 2021 Sept 3. doi: 10.1016/j.biocontrol.2021.104761
Alexandridis, N. ; Marion, G. ; Chaplin-Kramer, R. et al. / Models of natural pest control: Towards predictions across agricultural landscapes. In: Biological control. 2021 ; Vol. 163.
Download
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title = "Models of natural pest control: Towards predictions across agricultural landscapes",
abstract = "Natural control of invertebrate crop pests has the potential to complement or replace conventional insecticide-based practices, but its mainstream application is hampered by predictive unreliability across agroecosystems. Inconsistent responses of natural pest control to changes in landscape characteristics have been attributed to ecological complexity and system-specific conditions. Here, we review agroecological models and their potential to provide predictions of natural pest control across agricultural landscapes. Existing models have used a multitude of techniques to represent specific crop-pest-enemy systems at various spatiotemporal scales, but less wealthy regions of the world are underrepresented. A realistic representation of natural pest control across systems appears to be hindered by a practical trade-off between generality and realism. Nonetheless, observations of context-sensitive, trait-mediated responses of natural pest control to land-use gradients indicate the potential of ecological models that explicitly represent the underlying mechanisms. We conclude that modelling natural pest control across agroecosystems should exploit existing mechanistic techniques towards a framework of contextually bound generalizations. Observed similarities in causal relationships can inform the functional grouping of diverse agroecosystems worldwide and the development of the respective models based on general, but context-sensitive, ecological mechanisms. The combined use of qualitative and quantitative techniques should allow the flexible integration of empirical evidence and ecological theory for robust predictions of natural pest control across a wide range of agroecological contexts and levels of knowledge availability. We highlight challenges and promising directions towards developing such a general modelling framework.",
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AU - Alexandridis, N.

AU - Marion, G.

AU - Chaplin-Kramer, R.

AU - Dainese, M.

AU - Ekroos, J.

AU - Grab, H.

AU - Jonsson, M.

AU - Karp, D.S.

AU - Meyer, C.

AU - O'Rourke, M.E.

AU - Pontarp, M.

AU - Poveda, K.

AU - Seppelt, R.

AU - Smith, H.G.

AU - Martin, E.A.

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N1 - Funding Information: We thank Scott C. Merrill and an anonymous reviewer for critically reading the manuscript and suggesting substantial improvements. N.A. was supported by the 2013–2014 BiodivERsA/FACCE‐JPI joint call for research proposals (project ECODEAL), with the national funders ANR, BMBF, FORMAS, FWF, MINECO, NWO and PT‐DLR. The work was supported by two workshops at Lund University funded by the strategic research area Biodiversity and Ecosystem services in a Changing Climate (BECC) and a workshop funded and hosted by UFZ. G.M. is supported by the Scottish Government's Rural and Environment Science and Analytical Services Division (RESAS). M.J. acknowledges support from SLU Centre for Biological Control. C.M. acknowledges funding by the Volkswagen Foundation through a Freigeist Fellowship (A118199), and additional support by iDiv, funded by the German Research Foundation (DFG–FZT 118, 202548816).

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N2 - Natural control of invertebrate crop pests has the potential to complement or replace conventional insecticide-based practices, but its mainstream application is hampered by predictive unreliability across agroecosystems. Inconsistent responses of natural pest control to changes in landscape characteristics have been attributed to ecological complexity and system-specific conditions. Here, we review agroecological models and their potential to provide predictions of natural pest control across agricultural landscapes. Existing models have used a multitude of techniques to represent specific crop-pest-enemy systems at various spatiotemporal scales, but less wealthy regions of the world are underrepresented. A realistic representation of natural pest control across systems appears to be hindered by a practical trade-off between generality and realism. Nonetheless, observations of context-sensitive, trait-mediated responses of natural pest control to land-use gradients indicate the potential of ecological models that explicitly represent the underlying mechanisms. We conclude that modelling natural pest control across agroecosystems should exploit existing mechanistic techniques towards a framework of contextually bound generalizations. Observed similarities in causal relationships can inform the functional grouping of diverse agroecosystems worldwide and the development of the respective models based on general, but context-sensitive, ecological mechanisms. The combined use of qualitative and quantitative techniques should allow the flexible integration of empirical evidence and ecological theory for robust predictions of natural pest control across a wide range of agroecological contexts and levels of knowledge availability. We highlight challenges and promising directions towards developing such a general modelling framework.

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