Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards
Implementing integrated pest management programs to limit agricultural pest damage requires an understanding of the interactions between the environmental variability and population demographic processes. However, identifying key environmental drivers of spatio-temporal pest population dynamics rema...
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2024-07-01
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| Online Access: | https://peercommunityjournal.org/articles/10.24072/pcjournal.438/ |
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| author | Caumette, Cécile Diatta, Paterne Piry, Sylvain Chapuis, Marie-Pierre Faye, Emile Sigrist, Fabio Martin, Olivier Papaïx, Julien Brévault, Thierry Berthier, Karine |
| author_facet | Caumette, Cécile Diatta, Paterne Piry, Sylvain Chapuis, Marie-Pierre Faye, Emile Sigrist, Fabio Martin, Olivier Papaïx, Julien Brévault, Thierry Berthier, Karine |
| author_sort | Caumette, Cécile |
| collection | DOAJ |
| description | Implementing integrated pest management programs to limit agricultural pest damage requires an understanding of the interactions between the environmental variability and population demographic processes. However, identifying key environmental drivers of spatio-temporal pest population dynamics remains challenging as numerous candidate factors can operate at a range of scales, from the field (e.g. agricultural practices) to the regional scale (e.g. weather variability). In such a context, data-driven approaches applied to pre-existing data may allow identifying patterns, correlations, and trends that may not be apparent through more restricted hypothesis-driven studies. The resulting insights can lead to the generation of novel hypotheses and inform future experimental work focusing on a limited and relevant set of environmental predictors. In this study, we developed an ecoinformatics approach to unravel the multi-scale environmental conditions that lead to the early re-infestation of mango orchards by a major pest in Senegal, the oriental fruit fly Bactrocera dorsalis (BD). We gathered abundance data from a three-year monitoring conducted in 69 mango orchards as well as environmental data (i.e. orchard management, landscape structure and weather variability) across a range of spatial scales. We then developed a flexible analysis pipeline centred on a recent machine learning algorithm, which allows the combination of gradient boosting and grouped random effects models or Gaussian processes, to hierarchize the effects of multi-scale environmental variables on the onset of annual BD population growth in orchards. We found that physical factors (humidity, temperature), and to some extent landscape variables, were the main drivers of the spatio-temporal variability of the onset of population growth in orchards. These results suggest that favourable microclimate conditions could provide refuges for small BD populations that could survive, with little or no reproduction, during the mango off-season and, then, recolonize neighbouring orchards at the beginning of the next mango season. Confirmation of such a hypothesis could help to prioritize surveillance and preventive control actions in refuge areas. |
| format | Article |
| id | doaj-art-59b94d9b37b4491083566c97c79f2802 |
| institution | Kabale University |
| issn | 2804-3871 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Peer Community In |
| record_format | Article |
| series | Peer Community Journal |
| spelling | doaj-art-59b94d9b37b4491083566c97c79f28022025-02-07T10:17:18ZengPeer Community InPeer Community Journal2804-38712024-07-01410.24072/pcjournal.43810.24072/pcjournal.438Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards Caumette, Cécile0Diatta, Paterne1https://orcid.org/0000-0003-1639-5521Piry, Sylvain2https://orcid.org/0000-0002-7717-7555Chapuis, Marie-Pierre3https://orcid.org/0000-0003-4405-7722Faye, Emile4https://orcid.org/0000-0001-7764-3256Sigrist, Fabio5Martin, Olivier6https://orcid.org/0009-0009-6727-8510Papaïx, Julien7https://orcid.org/0000-0003-2273-5334Brévault, Thierry8https://orcid.org/0000-0003-0159-3509Berthier, Karine9https://orcid.org/0000-0002-2260-7968CBGP, Montpellier SupAgro, INRAE, IRD, CIRAD, University of Montpellier, Montpellier, France; CIRAD, UPR Hortsys, Montpellier, FranceISRA/CRA de Djibélor, Ziguinchor, SénégalCBGP, Montpellier SupAgro, INRAE, IRD, CIRAD, University of Montpellier, Montpellier, FranceCBGP, Montpellier SupAgro, INRAE, IRD, CIRAD, University of Montpellier, Montpellier, FranceCIRAD, UPR Hortsys, Montpellier, FranceSeminar for Statistics, ETH Zurich, SwitzerlandINRAE, BioSP, Avignon, FranceINRAE, BioSP, Avignon, FranceCIRAD, UPR AIDA, Montpellier, FranceINRAE, Pathologie Végétale, Montfavet, FranceImplementing integrated pest management programs to limit agricultural pest damage requires an understanding of the interactions between the environmental variability and population demographic processes. However, identifying key environmental drivers of spatio-temporal pest population dynamics remains challenging as numerous candidate factors can operate at a range of scales, from the field (e.g. agricultural practices) to the regional scale (e.g. weather variability). In such a context, data-driven approaches applied to pre-existing data may allow identifying patterns, correlations, and trends that may not be apparent through more restricted hypothesis-driven studies. The resulting insights can lead to the generation of novel hypotheses and inform future experimental work focusing on a limited and relevant set of environmental predictors. In this study, we developed an ecoinformatics approach to unravel the multi-scale environmental conditions that lead to the early re-infestation of mango orchards by a major pest in Senegal, the oriental fruit fly Bactrocera dorsalis (BD). We gathered abundance data from a three-year monitoring conducted in 69 mango orchards as well as environmental data (i.e. orchard management, landscape structure and weather variability) across a range of spatial scales. We then developed a flexible analysis pipeline centred on a recent machine learning algorithm, which allows the combination of gradient boosting and grouped random effects models or Gaussian processes, to hierarchize the effects of multi-scale environmental variables on the onset of annual BD population growth in orchards. We found that physical factors (humidity, temperature), and to some extent landscape variables, were the main drivers of the spatio-temporal variability of the onset of population growth in orchards. These results suggest that favourable microclimate conditions could provide refuges for small BD populations that could survive, with little or no reproduction, during the mango off-season and, then, recolonize neighbouring orchards at the beginning of the next mango season. Confirmation of such a hypothesis could help to prioritize surveillance and preventive control actions in refuge areas.https://peercommunityjournal.org/articles/10.24072/pcjournal.438/Bactrocera dorsalismango cropweatherlandscapeagricultural practicesGPBoostpopulation dynamicsabundance time seriesecoinformaticsmachine learning |
| spellingShingle | Caumette, Cécile Diatta, Paterne Piry, Sylvain Chapuis, Marie-Pierre Faye, Emile Sigrist, Fabio Martin, Olivier Papaïx, Julien Brévault, Thierry Berthier, Karine Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards Peer Community Journal Bactrocera dorsalis mango crop weather landscape agricultural practices GPBoost population dynamics abundance time series ecoinformatics machine learning |
| title | Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards
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| title_full | Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards
|
| title_fullStr | Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards
|
| title_full_unstemmed | Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards
|
| title_short | Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards
|
| title_sort | hierarchizing multi scale environmental effects on agricultural pest population dynamics a case study on the annual onset of bactrocera dorsalis population growth in senegalese orchards |
| topic | Bactrocera dorsalis mango crop weather landscape agricultural practices GPBoost population dynamics abundance time series ecoinformatics machine learning |
| url | https://peercommunityjournal.org/articles/10.24072/pcjournal.438/ |
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