Models of natural pest control: Towards predictions across agricultural landscapes

Publikation: Beitrag in FachzeitschriftÜbersichtsarbeitForschungPeer-Review

Autoren

  • 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

Organisationseinheiten

Externe Organisationen

  • 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
  • Deutsches Zentrum für integrative Biodiversitätsforschung (iDiv) Halle-Jena-Leipzig
  • Universität Leipzig
  • Martin-Luther-Universität Halle-Wittenberg
  • Virginia Polytechnic Institute and State University (Virginia Tech)
  • Helmholtz-Zentrum für Umweltforschung (UFZ)
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Aufsatznummer104761
FachzeitschriftBiological control
Jahrgang163
Frühes Online-Datum3 Sept. 2021
PublikationsstatusVeröffentlicht - 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.

Zitieren

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

Publikation: Beitrag in FachzeitschriftÜbersichtsarbeitForschungPeer-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, Jg. 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, Artikel 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 Sep 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 ; Jahrgang 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.",
keywords = "Crop, Ecological modelling, Land use, Landscape, Natural control, Pest",
author = "N. Alexandridis and G. Marion and R. Chaplin-Kramer and M. Dainese and J. Ekroos and H. Grab and M. Jonsson and D.S. Karp and C. Meyer and M.E. O'Rourke and M. Pontarp and K. Poveda and R. Seppelt and H.G. Smith and E.A. Martin and Y. Clough",
note = "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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month = nov,
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journal = "Biological control",
issn = "1049-9644",
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Download

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T1 - Models of natural pest control: Towards predictions across agricultural landscapes

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.

AU - Clough, Y.

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).

PY - 2021/11

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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.

AB - 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.

KW - Crop

KW - Ecological modelling

KW - Land use

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KW - Natural control

KW - Pest

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U2 - 10.1016/j.biocontrol.2021.104761

DO - 10.1016/j.biocontrol.2021.104761

M3 - Review article

VL - 163

JO - Biological control

JF - Biological control

SN - 1049-9644

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