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Models of natural pest control : Towards predictions across agricultural landscapes

Alexandridis, Nikolaos LU ; Marion, Glenn ; Chaplin-Kramer, Rebecca ; Dainese, Matteo ; Ekroos, Johan LU ; Grab, Heather ; Jonsson, Mattias ; Karp, Daniel S. ; Meyer, Carsten and O'Rourke, Megan E. , et al. (2021) In Biological Control 163.
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... (More)

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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publishing date
type
Contribution to journal
publication status
published
subject
keywords
Crop, Ecological modelling, Land use, Landscape, Natural control, Pest
in
Biological Control
volume
163
article number
104761
pages
11 pages
publisher
Elsevier
external identifiers
  • scopus:85114792960
ISSN
1049-9644
DOI
10.1016/j.biocontrol.2021.104761
language
English
LU publication?
yes
additional info
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). Publisher Copyright: © 2021 The Authors Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
id
f69cabad-4898-4f78-b742-cef75f2cc9d1
date added to LUP
2021-09-19 15:51:54
date last changed
2024-03-08 17:39:59
@article{f69cabad-4898-4f78-b742-cef75f2cc9d1,
  abstract     = {{<p>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.</p>}},
  author       = {{Alexandridis, Nikolaos and Marion, Glenn and Chaplin-Kramer, Rebecca and Dainese, Matteo and Ekroos, Johan and Grab, Heather and Jonsson, Mattias and Karp, Daniel S. and Meyer, Carsten and O'Rourke, Megan E. and Pontarp, Mikael and Poveda, Katja and Seppelt, Ralf and Smith, Henrik G. and Martin, Emily A. and Clough, Yann}},
  issn         = {{1049-9644}},
  keywords     = {{Crop; Ecological modelling; Land use; Landscape; Natural control; Pest}},
  language     = {{eng}},
  month        = {{09}},
  publisher    = {{Elsevier}},
  series       = {{Biological Control}},
  title        = {{Models of natural pest control : Towards predictions across agricultural landscapes}},
  url          = {{http://dx.doi.org/10.1016/j.biocontrol.2021.104761}},
  doi          = {{10.1016/j.biocontrol.2021.104761}},
  volume       = {{163}},
  year         = {{2021}},
}