Predicting the habitat suitability of the invasive white mango scale, Aulacaspis tubercularis; Newstead, 1906 (Hemiptera: Diaspididae) using bioclimatic variables.
Mangifera indica L.
climate change
ecological niche modelling
habitat suitability
machine-learning algorithms
scale insects
Journal
Pest management science
ISSN: 1526-4998
Titre abrégé: Pest Manag Sci
Pays: England
ID NLM: 100898744
Informations de publication
Date de publication:
Oct 2022
Oct 2022
Historique:
revised:
16
05
2022
received:
19
01
2022
accepted:
03
06
2022
pubmed:
4
6
2022
medline:
8
9
2022
entrez:
3
6
2022
Statut:
ppublish
Résumé
The white mango scale, Aulacaspis tubercularis (Hemiptera: Diaspididae), is an invasive pest that threatens the production of several crops of commercial value including mango. Though it is an important pest, little is known about its biology and ecology. Specifically, information on habitat suitability of A. tubercularis occurrence and potential distribution under climate change is largely unknown. In this study, we used four ecological niche models, namely maximum entropy, random forest, generalized additive models, and classification and regression trees to predict the habitat suitability of A. tubercularis under current and future [representative concentration pathways (RCPs): RCP4.5 and RCP8.5 of the year 2070] climatic scenarios, using bioclimatic variables. Models' performance was evaluated using the true skill statistic (TSS), the area under the curve (AUC), correlation (COR), and the deviance. All models sufficiently predicted the occurrence of A. tubercularis with high accuracy (AUC ≥ 0.93, TSS ≥ 0.81 and COR ≥ 0.77). The random forest algorithm had the highest accuracy among the four models (AUC = 0.99, TSS = 0.93, COR = 0.90, deviance = 0.26). Temperature seasonality (Bio4), mean temperature of the driest quarter (Bio9), and precipitation seasonality (Bio15) were the most important variables influencing A. tubercularis occurrence. Models' predictions showed that countries in east, south, and west Africa are highly suitable for A. tubercularis establishment under current conditions. Similarly, Mexico, Brazil, India, Myanmar, Bangladesh, Thailand, Laos, Vietnam, and Cambodia are also highly suitable for the pest to thrive. Under future conditions, the suitable areas might slightly decrease in many countries of sub-Saharan Africa under both RCPs. However, the range of expansion of A. tubercularis is projected to be higher in Australia, Brazil, Spain, Italy, and Portugal under the future climatic scenarios. The results reported here will be useful for guiding decision-making, developing an effective management strategy, and serving as an early warning tool to prevent further spread toward new areas. © 2022 Society of Chemical Industry.
Sections du résumé
BACKGROUND
BACKGROUND
The white mango scale, Aulacaspis tubercularis (Hemiptera: Diaspididae), is an invasive pest that threatens the production of several crops of commercial value including mango. Though it is an important pest, little is known about its biology and ecology. Specifically, information on habitat suitability of A. tubercularis occurrence and potential distribution under climate change is largely unknown. In this study, we used four ecological niche models, namely maximum entropy, random forest, generalized additive models, and classification and regression trees to predict the habitat suitability of A. tubercularis under current and future [representative concentration pathways (RCPs): RCP4.5 and RCP8.5 of the year 2070] climatic scenarios, using bioclimatic variables. Models' performance was evaluated using the true skill statistic (TSS), the area under the curve (AUC), correlation (COR), and the deviance.
RESULTS
RESULTS
All models sufficiently predicted the occurrence of A. tubercularis with high accuracy (AUC ≥ 0.93, TSS ≥ 0.81 and COR ≥ 0.77). The random forest algorithm had the highest accuracy among the four models (AUC = 0.99, TSS = 0.93, COR = 0.90, deviance = 0.26). Temperature seasonality (Bio4), mean temperature of the driest quarter (Bio9), and precipitation seasonality (Bio15) were the most important variables influencing A. tubercularis occurrence. Models' predictions showed that countries in east, south, and west Africa are highly suitable for A. tubercularis establishment under current conditions. Similarly, Mexico, Brazil, India, Myanmar, Bangladesh, Thailand, Laos, Vietnam, and Cambodia are also highly suitable for the pest to thrive. Under future conditions, the suitable areas might slightly decrease in many countries of sub-Saharan Africa under both RCPs. However, the range of expansion of A. tubercularis is projected to be higher in Australia, Brazil, Spain, Italy, and Portugal under the future climatic scenarios.
CONCLUSION
CONCLUSIONS
The results reported here will be useful for guiding decision-making, developing an effective management strategy, and serving as an early warning tool to prevent further spread toward new areas. © 2022 Society of Chemical Industry.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
4114-4126Subventions
Organisme : International Development Research Centre (IDRC-Canada)
Organisme : Government of the Republic of Kenya
Organisme : Swiss Agency for Development and Cooperation
Organisme : Swedish International Development Cooperation Agency
Organisme : Australian Centre for International Agricultural Research
Organisme : International Development Research Centre
Organisme : Norwegian Agency for Development Cooperation
Informations de copyright
© 2022 Society of Chemical Industry.
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