Publication Type

Journal Article

Journal Name

Ecological Modelling

Name of Author

Henri E.Z. Tonnang, World Agroforestry Centre
Bisseleua D.B. Hervé, World Agroforestry Centre
Lisa Biber-Freudenberger, Zentrum für Entwicklungsforschung
Daisy Salifu, International Centre of Insect Physiology and Ecology Nairobi
Sevgan Subramanian, International Centre of Insect Physiology and Ecology Nairobi
Valentine B. Ngowi, World Agroforestry Centre
Ritter Y.A. Guimapi, International Centre of Insect Physiology and Ecology Nairobi
Bruce Anani, World Agroforestry Centre
Francois M.M. Kakmeni, International Centre of Insect Physiology and Ecology Nairobi
Hippolyte Affognon, International Centre of Insect Physiology and Ecology Nairobi
Saliou Niassy, International Centre of Insect Physiology and Ecology Nairobi
Tobias Landmann, International Centre of Insect Physiology and Ecology Nairobi
Frank T. Ndjomatchoua, International Centre of Insect Physiology and Ecology Nairobi
Sansao A. Pedro, International Centre of Insect Physiology and Ecology Nairobi
Tino Johansson, International Centre of Insect Physiology and Ecology Nairobi
Chrysantus M. Tanga, International Centre of Insect Physiology and Ecology NairobiFollow
Paulin Nana, International Centre of Insect Physiology and Ecology Nairobi
Komi M. Fiaboe, International Centre of Insect Physiology and Ecology Nairobi
Samira F. Mohamed, International Centre of Insect Physiology and Ecology Nairobi
Nguya K. Maniania, International Centre of Insect Physiology and Ecology Nairobi
Sunday Ekesi, International Centre of Insect Physiology and Ecology Nairobi
Christian Borgemeister, Zentrum für Entwicklungsforschung

Publication Date

6-24-2017

Abstract

A wide range of insects affect crop production and cause considerable yield losses. Difficulties reside on the development and adaptation of adequate strategies to predict insect pests for their timely management to ensure enhanced agricultural production. Several conceptual modelling frameworks have been proposed, and the choice of an approach depends largely on the objective of the model and the availability of data. This paper presents a summary of decades of advances in insect population dynamics, phenology models, distribution and risk mapping. Existing challenges on the modelling of insects are listed; followed by innovations in the field. New approaches include artificial neural networks, cellular automata (CA) coupled with fuzzy logic (FL), fractal, multi-fractal, percolation, synchronization and individual/agent-based approaches. A concept for assessing climate change impacts and providing adaptation options for agricultural pest management independently of the United Nations Intergovernmental Panel on Climate Change (IPCC) emission scenarios is suggested. A framework for estimating losses and optimizing yields within crop production system is proposed and a summary on modelling the economic impact of pests control is presented. The assessment shows that the majority of known insect modelling approaches are not holistic; they only concentrate on a single component of the system, i.e. the pest, rather than the whole crop production system. We suggest system thinking as a possible approach for linking crop, pest, and environmental conditions to provide a more comprehensive assessment of agricultural crop production.

Keywords

Climate change, Crop production, Impact assessment, Insect modelling approaches, Integrated pest management, System thinking, Yield losses

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