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Abstract

Eucalyptus has become one of the most widely cultivated tree genera in subtropical China, generating significant economic returns but raising land-use conflicts with agriculture. Understanding the driving mechanisms behind this expansion is crucial for sustainable land-use management. To inform strategies for balancing wood production and agricultural stability, we investigated the spatiotemporal expansion dynamics and predicted the potential suitable habitat distribution of Eucalyptus plantations using a Boosted Regression Tree (BRT) model. Our analysis revealed three distinct spatiotemporal expansion phases. Crucially, this expansion has progressively shifted from marginal sloped terrain onto flat valley bottoms, intensifying the agriculture-forestry conflict in the region. Climatic conditions consistently emerged as the dominant large-scale regulatory driver across all expansion stages. The BRT model identified critical precipitation thresholds that dictate suitability, demonstrating Eucalyptus's strong sensitivity to the precipitation of the driest quarter (> 110 mm) and mean annual precipitation (1000–1700 mm). Under current climatic scenarios, a large suitable habitat area is predicted in the central and southern parts of the study region. This study provides spatially explicit evidence of how meteorological factors shape the expansion patterns of short-rotation forestry and contribute to land-use tensions. Our findings offer actionable scientific insights crucial for developing climate-informed site selection and management policies to achieve a viable equilibrium between timber economic objectives and the protection of prime agricultural resources in subtropical China.

Document Type

Article

Publication Date

2026

Notes/Citation Information

2666-7193/© 2026 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Digital Object Identifier (DOI)

https://doi.org/10.1016/j.tfp.2026.101292

Funding Information

This research was funded by the National Natural Science Foundation of China (Project No. 32460289, 42561019, 42001216, and 41961037), and by the 2025 “Bagui Talent” Visiting & Research Program of the Guangxi Science and Technology Project. The authors also acknowledge the Guangxi Zhuang Autonomous Region Forest Resources and Eco-Environmental Monitoring Center for their assistance in field investigations and their expert interpretation of forest management policies.

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