Evidence map›Paper›PMID 42423767›Full record

ArticleExperimental & applied acarology2026

Identification of suitable habitats for the six-spotted mite on rubber trees using multi-source data and MaxEnt modeling.

Yanan You, Huichun Ye, Donghua Wang, Chaojia Nie, Jingjing Wang, Bingsun Wu, Fengzheng Cai, Jiajian Deng, Lixia Shen, Fu Wen

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Article in Experimental & applied acarology, 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

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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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

10 authors.

Yanan YouCollege of Water Resources Science and Engineering, Taiyuan University of Technology, Taiyuan, 030024, China.
Huichun YeKey Laboratory of Earth Observation of Hainan, Hainan Aerospace Information Research Institute, Sanya, 572029, China. yehc@aircas.ac.cn.
Donghua WangCollege of Water Resources Science and Engineering, Taiyuan University of Technology, Taiyuan, 030024, China.
Chaojia NieKey Laboratory of Earth Observation of Hainan, Hainan Aerospace Information Research Institute, Sanya, 572029, China.
Jingjing WangSchool of Tropical Agriculture and Forestry, Hainan University, Haikou, 570228, China.
Bingsun WuRubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, China.
Fengzheng CaiSchool of Tropical Agriculture and Forestry, Hainan University, Haikou, 570228, China.
Jiajian DengHainan Nongfeike Agricultural Technology Co., Ltd., Haikou, 570105, China.
Lixia ShenCollege of Water Resources Science and Engineering, Taiyuan University of Technology, Taiyuan, 030024, China.
Fu WenInternational Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.

Funding

Hainan Provincial Major Science and Technology Program of China ZDKJ2019006Project of Hainan Province Science and Technology Special Fund ZDYF2024XDNY196, ZDYF2025XDNY112Youth Innovation Promotion Association CAS 2021119
6 · The paper itself

Abstract

The six-spotted mite (SSM), Eotetranychus sexmaculatus (Acari: Tetranychidae), is one of the most destructive pests threatening rubber tree plantations. Accurately identifying its suitable regions is essential for implementing targeted pest management and establishing early warning systems. This study, focusing on Hainan Island, China, innovatively integrates multi-source data, including field survey points, topography, meteorology, and remote sensing vegetation indices, to develop a high-precision method for extracting SSM suitable regions based on the maximum entropy algorithm implemented in the MaxEnt. The results demonstrate that the model exhibits excellent performance (Area Under Curve [AUC] = 0.907, True Skill Statistic [TSS] = 0.803), with 93.9% of pest occurrence points accurately located within the predicted suitable regions, and all cross-replicate prediction standard deviations are lower than 0.3. Elevation, slope, annual precipitation, minimum land surface temperature from May to July, and average renormalized difference vegetation index from May to July were identified as the primary driving factors influencing SSM distribution. The spatial distribution of SSM suitable regions in Hainan Island revealed a 'core-edge' pattern, with the total suitable area covering approximately 92% of the island's rubber plantations. Of this, the high suitable region accounts for 27.9%, and is predominantly located in the central and northwestern regions of the island. Furthermore, the total suitable area has expanded by approximately 5.8% over the past decade. This research not only provides a scientific paradigm for the large-scale dynamic monitoring and regionalized precision control of SSM but also offers forward-looking decision support for addressing future agricultural biosecurity challenges.

Indexed as

Animal DistributionEcosystemHeveaTetranychidaeAnimalsChinaMaximum entropy modelRemote sensingRubber treeSuitable regionThe six–spotted mite

Identifiers

PMID42423767

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