# Assessing Habitat Suitability for Phloeosinus aubei Perris in China: A MaxEnt-Based Predictive Analysis

## TL;DR

This study predicts that climate change will expand the suitable habitat for a tree-damaging beetle in China, threatening forests.

## Contribution

The novel use of MaxEnt modeling to predict future habitat suitability of Phloeosinus aubei under climate change scenarios in China.

## Key findings

- Temperature and rainfall are the main factors influencing Phloeosinus aubei's habitat suitability.
- High-suitability areas could expand by 82.29% in southwestern China by the 2050s under high-emission scenarios.
- The model achieved high accuracy (AUC = 0.92) in predicting beetle distribution.

## Abstract

Climate change is shifting where species can survive, and this study explored how it may affect the spread of Phloeosinus aubei, a tree-damaging beetle, in China. Using a computer model, we predicted where this beetle could live now and in the future by analyzing weather patterns and land features. We found that temperature and rainfall are the main factors influencing its spread. By the 2050s, areas highly suitable for the beetle could grow by over 80%, especially in warmer, wetter parts of southwestern China. This poses a threat to forests, as the beetle harms already weakened trees and can cause serious damage to ecosystems. This study highlights the need for early detection and smarter forest management to protect vulnerable areas. These findings can guide future planning to reduce the risks of invasive pests under climate change.

Climate change reshapes species distributions, necessitating proactive measures to mitigate ecological impacts. This study investigates the potential spread of Phloeosinus aubei, a bark beetle with significant ecological consequences, under future climate scenarios in China. Using the MaxEnt model, we integrated occurrence records and scientific literature with bioclimatic and terrain variables to predict habitat suitability. The results reveal that P. aubei’s distribution is highly influenced by precipitation and temperature, with key variables like annual precipitation (bio12, 30.4% contribution) and the minimum temperature of the coldest month (bio6, 29% contribution) driving habitat suitability. Notably, under high-emission scenarios (SSP5-8.5), high-suitability areas could expand by 82.29% by the 2050s due to warming-induced precipitation changes in southwestern China. Model validation confirms a high predictive accuracy, with an AUC value of 0.92, underscoring the reliability of these projections. These findings highlight the beetle’s potential to colonize new regions, posing risks to forest ecosystems. The study underscores the need for adaptive management strategies, including early detection and climate-resilient forestry practices, to safeguard vulnerable ecosystems from invasive species under climate change.