Integrating MaxEnt and copula models to assess plague-associated ecological suitability under climate change in Northern Tianshan, China
4 affiliations
- 1Xinjiang Key Laboratory of Vector-borne Infectious Diseases, Urumqi, Xinjiang Uygur Autonomous Region, China
- 2The Center for Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang Uygur Autonomous Region, China
- 3National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Chinese Academy of Preventive Medicine, Beijing, China
- 4The Center for Disease Control and Prevention of Yining County, Yining, Xinjiang Uygur Autonomous Region, China
Abstract
Background: Plague, a paradigmatic zoonotic disease, depends on the intricate interplay among ecological environments, climatic conditions, and host-vector-pathogen interactions for its transmission. Climate change is reshaping the ecological distribution and transmission risks of plague. However, a systematic understanding of the future epidemiological trends for the Northern Tianshan Natural Plague Focus in Xinjiang remains limited. Methods: By employing an optimized maximum entropy model (MaxEnt) integrated with joint distribution Copula functions, the spatiotemporal dynamics of Marmota baibacina, Yersinia pestis, and plague transmission risk under both current and future climate change scenarios were evaluated. Results: The results revealed that the high-suitability habitats for both M. baibacina and Y. pestis within the focus were projected to exhibit trends of contraction and expansion in the future. These patterns could be attributed to the distinct environmental factors shaping their distributions. Specifically, the distribution of M. baibacina was primarily determined by temperature (Bio6 and Bio7) and precipitation (Bio15), whereas the distribution of Y. pestis was predominantly influenced by Bio15 and elevation. The spatial distribution of high-risk areas for plague transmission was projected to undergo dynamic changes, characterized by phases of stability, contraction, and expansion. Furthermore, the centroid of these high-risk regions may shift from Wusu City to Nileke County. Conclusions: Under future climate scenarios, the distribution and transmission risk of plague in the focus may be influenced by environmental factors, resulting in scenario- and period-dependent spatial changes. The western region of the focus is anticipated to experience the most pronounced shifts and is projected to remain at elevated risk of epizootic plague. Author summary: Plague, a deadly zoonotic disease and potential bioterrorism threat, remains a major risk to rural, resource-poor communities—especially as climate change reshapes its spread. We focused on the Northern Tianshan Mountain plague focus in China, one of the world’s most active, to understand how future climate shifts will affect disease transmission. Using an improved ecological modeling approach combined with statistical tools to characterize statistical dependence between the modelled suitability outputs, we mapped suitable habitats for Yersinia pestis and its main host (Marmota baibacina) under different climate scenarios. We found that climate change may drive temporal shifts in predicted high-risk areas, with the center of transmission moving between key regions. The western part of the study area may experience the most pronounced changes and maintain persistently high risk long-term. Importantly, we identified unrecognized high-risk zones (like Xinyuan County) that need surveillance. This approach may inform surveillance prioritization, subject to local validation..
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BibTeX
@article{li2026integrating,
title = {{Integrating MaxEnt and copula models to assess plague-associated ecological suitability under climate change in Northern Tianshan, China}},
author = {Fang Li and Guoyu Zhao and Abulimiti Moming and Xiaobo Liu and Ping Ma and Shang Zhan and Huiqian Wang and Jianhui Chen and Wuliken Tuerdali and Qiguo Wang and Tao Luo and Haiyan Wu and Yujiang Zhang},
journal = {PLOS Neglected Tropical Diseases},
year = {2026},
month = oct,
doi = {10.1371/journal.pntd.0014818},
url = {https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0014818},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Integrating MaxEnt and copula models to assess plague-associated ecological suitability under climate change in Northern Tianshan, China
AU - Fang Li
AU - Guoyu Zhao
AU - Abulimiti Moming
AU - Xiaobo Liu
AU - Ping Ma
AU - Shang Zhan
AU - Huiqian Wang
AU - Jianhui Chen
AU - Wuliken Tuerdali
AU - Qiguo Wang
AU - Tao Luo
AU - Haiyan Wu
AU - Yujiang Zhang
PY - 2026
DA - 2026/10/26
JO - PLOS Neglected Tropical Diseases
DO - 10.1371/journal.pntd.0014818
UR - https://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0014818
AB - Background: Plague, a paradigmatic zoonotic disease, depends on the intricate interplay among ecological environments, climatic conditions, and host-vector-pathogen interactions for its transmission. Climate change is reshaping the ecological distribution and transmission risks of plague. However, a systematic understanding of the future epidemiological trends for the Northern Tianshan Natural Plague Focus in Xinjiang remains limited. Methods: By employing an optimized maximum entropy model (MaxEnt) integrated with joint distribution Copula functions, the spatiotemporal dynamics of Marmota baibacina, Yersinia pestis, and plague transmission risk under both current and future climate change scenarios were evaluated. Results: The results revealed that the high-suitability habitats for both M. baibacina and Y. pestis within the focus were projected to exhibit trends of contraction and expansion in the future. These patterns could be attributed to the distinct environmental factors shaping their distributions. Specifically, the distribution of M. baibacina was primarily determined by temperature (Bio6 and Bio7) and precipitation (Bio15), whereas the distribution of Y. pestis was predominantly influenced by Bio15 and elevation. The spatial distribution of high-risk areas for plague transmission was projected to undergo dynamic changes, characterized by phases of stability, contraction, and expansion. Furthermore, the centroid of these high-risk regions may shift from Wusu City to Nileke County. Conclusions: Under future climate scenarios, the distribution and transmission risk of plague in the focus may be influenced by environmental factors, resulting in scenario- and period-dependent spatial changes. The western region of the focus is anticipated to experience the most pronounced shifts and is projected to remain at elevated risk of epizootic plague. Author summary: Plague, a deadly zoonotic disease and potential bioterrorism threat, remains a major risk to rural, resource-poor communities—especially as climate change reshapes its spread. We focused on the Northern Tianshan Mountain plague focus in China, one of the world’s most active, to understand how future climate shifts will affect disease transmission. Using an improved ecological modeling approach combined with statistical tools to characterize statistical dependence between the modelled suitability outputs, we mapped suitable habitats for Yersinia pestis and its main host (Marmota baibacina) under different climate scenarios. We found that climate change may drive temporal shifts in predicted high-risk areas, with the center of transmission moving between key regions. The western part of the study area may experience the most pronounced changes and maintain persistently high risk long-term. Importantly, we identified unrecognized high-risk zones (like Xinyuan County) that need surveillance. This approach may inform surveillance prioritization, subject to local validation..
SN - 1935-2735
SN - 1935-2727
ER -