Optimized MaxEnt Model Predicts Future Suitable Habitats for Chinese Caterpillar Fungus Under Climate Change

The Chinese Caterpillar Fungus (CCF) is a precious and rare traditional Chinese medicinal material that is extremely sensitive to environmental changes, making wild resources scarce. Therefore, studying the impact of climate change on the potential distribution and changes of the CCF is of great significance. Employing an enhanced MaxEnt approach (optimized with ENMeval), this study determined the primary ecological constraints on CCF and mapped its potential present and future ranges. The results indicated that elevation, bio05, bio04, bio12, bio11, slope, d1_ph_water, and hf were the driving environmental factors influencing the survival of the CCF. The ideal habitat zones for the CCF were mainly distributed in the plateau and alpine climate zones of northwestern and southwestern China, covering an area of 7.42 × 104 km2. Compared with the current climate scenario, the area of suitable habitats for the CCF was expected to increase in the future. In the 2090s, under the SSP1–2.6 scenario, the highly suitable areas for the CCF will have increased the most, by 67.54%, while the low–suitability areas will have decreased by 6.87%. Overall, the highly suitable areas for the CCF will shift towards higher latitudes. The outcomes of this study can inform subsequent conservation strategies for CCF resources and facilitate research on other ecological variables affecting CCF distribution patterns.

Authors

Institutions

Publication Details

Journal
Agriculture
Published
2025-05-26
DOI
https://doi.org/10.3390/agriculture15111144
Citations
4
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
7.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimized MaxEnt Model Predicts Future Suitable Habitats for Chinese Caterpillar Fungus Under Climate Change

Zhihang Zhuo, Danping Xu, Qianqian Qian, Yaqin Peng
4 citations
Agriculture
Species Distribution and Climate Change
7.35
article

Optimized MaxEnt Model Predicts Future Suitable Habitats for Chinese Caterpillar Fungus Under Climate Change

Zhihang Zhuo, Danping Xu, Qianqian Qian, Yaqin Peng
article en
4 citations

Abstract

The Chinese Caterpillar Fungus (CCF) is a precious and rare traditional Chinese medicinal material that is extremely sensitive to environmental changes, making wild resources scarce. Therefore, studying the impact of climate change on the potential distribution and changes of the CCF is of great significance. Employing an enhanced MaxEnt approach (optimized with ENMeval), this study determined the primary ecological constraints on CCF and mapped its potential present and future ranges. The results indicated that elevation, bio05, bio04, bio12, bio11, slope, d1_ph_water, and hf were the driving environmental factors influencing the survival of the CCF. The ideal habitat zones for the CCF were mainly distributed in the plateau and alpine climate zones of northwestern and southwestern China, covering an area of 7.42 × 104 km2. Compared with the current climate scenario, the area of suitable habitats for the CCF was expected to increase in the future. In the 2090s, under the SSP1–2.6 scenario, the highly suitable areas for the CCF will have increased the most, by 67.54%, while the low–suitability areas will have decreased by 6.87%. Overall, the highly suitable areas for the CCF will shift towards higher latitudes. The outcomes of this study can inform subsequent conservation strategies for CCF resources and facilitate research on other ecological variables affecting CCF distribution patterns.

AgricultureVol. 15(11)
China West Normal University (CN)
China West Normal University, Fundamental Research Funds of China West Normal University
Openalex Percentile: Top 3%
Species Distribution and Climate Change
7.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Optimized MaxEnt Model Predicts Future Suitable Habitats for Chinese Caterpillar Fungus Under Climate Change — Zhihang Zhuo, Danping Xu, et al. · Agriculture (2025) | TGRS Research Map | TGRS