Evidence map›Paper›PMID 42120560›Full record

ArticleScientific reports2026

Predicting climate-driven habitat shifts of Varroa destructor using MaxEnt and CMIP6 data.

Peter Njukang Akongte, Owusu Fordjour Aidoo, Daegeun Oh, Kim Jin-Myung, Chang-Hoon Lee, Yong-Soo Choi, Dongwon Kim

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Peter Njukang AkongteDepartment of Agricultural Biology, Honeybee Resource materials Research Laboratory, National Institute of Agricultural Sciences, Wanju, 55365, Republic of Korea.
Owusu Fordjour AidooDepartment of Biological Sciences, University of Environment and Sustainable Development, PMB, Somanya, Ghana.
Daegeun OhDepartment of Agricultural Biology, Honeybee Resource materials Research Laboratory, National Institute of Agricultural Sciences, Wanju, 55365, Republic of Korea.
Kim Jin-MyungDepartment of Agricultural Biology, Honeybee Resource materials Research Laboratory, National Institute of Agricultural Sciences, Wanju, 55365, Republic of Korea.
Chang-Hoon LeeDepartment of Agricultural Biology, Honeybee Resource materials Research Laboratory, National Institute of Agricultural Sciences, Wanju, 55365, Republic of Korea.
Yong-Soo ChoiDepartment of Agricultural Biology, Honeybee Resource materials Research Laboratory, National Institute of Agricultural Sciences, Wanju, 55365, Republic of Korea.
Dongwon KimDepartment of Agricultural Biology, Honeybee Resource materials Research Laboratory, National Institute of Agricultural Sciences, Wanju, 55365, Republic of Korea. dongwonkim@korea.kr.

Funding

Rural Development Administration PJ01779802
6 · The paper itself

Abstract

Climate change is reshaping global temperature, humidity, and precipitation patterns, key factors influencing habitat suitability and facilitating the spread of invasive species. Varroa destructor, a parasitic mite that shifted hosts from Apis cerana to Apis mellifera, has become one of the most destructive threats to apiculture worldwide. Despite existing control measures, the mite continues to expand its range. In this study, we applied the Maximum Entropy (MaxEnt) model to predict current and future global distribution of climatically suitable habitats for V. destructor. Occurrence records were compiled from the Global Biodiversity Information Facility (GBIF), the Center for Agriculture and Bioscience International (CABI), and published literature. The model achieved acceptable predictive accuracy (mean AUC values = 0.87, TSS = 0.60, CBI = 0.86), demonstrating strong robustness and discriminatory power. We found that isothermality (38.3%), precipitation of the driest month (19.8%), maximum temperature of the warmest month (16.4%), precipitation seasonality (14%), and precipitation of the wettest month (7.1%) were the most influential variables. Projections under three future climate scenarios (SSP245, SSP370, and SSP585) indicate a decline in suitable habitats by the 2050s and 2070s, particularly under SSP585, with an estimated 18.38% reduction in suitable areas. However, parts of the Northern Hemisphere, including North America and Europe, are likely to remain highly suitable. These findings highlight the need for region-specific, sustainable management strategies to prevent further spread of V. destructor in high-risk areas.

Indexed as

Climate ChangeEcosystemVarroidaeAnimalsBeesClimateSeasonsTemperatureApis melliferaClimate changeHabitat suitabilityInvasive speciesMaxEnt modelVarroa destructor

Identifiers

PMID42120560
PMCPMC13358152

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