ORIGINAL RESEARCH article
Front. For. Glob. Change
Sec. Forest Management
Eco-Zoning Management Based on Thresholds of NPP Driving Factors
Provisionally accepted
- Hubei Minzu University, Enshi, China
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The spatiotemporal differentiation of net primary productivity (NPP) is nonlinearly regulated by multiple factors, with the identification of driving factor thresholds and ecological zoning remaining a key challenge in ecosystem research. To address these challenges, this study developed an XGBoost–SHAP–Restricted Cubic Splines (RCS) framework, with RCS dedicated to identifying key ecological thresholds that are subsequently used for zoning. The main conclusions are as follows: (1) Over the past 21 years, NPP in the study area exhibited a fluctuating upward trend with significant spatial heterogeneity (higher in the west, lower in the east), and a potential decline is projected for the future. (2) Driving factors were ranked by importance, and their critical thresholds identified: precipitation (1103.77 mm) > soil organic matter content (4%, 8.31%) > vegetation index (0.44) > elevation (129.99 m) > temperature (13.71 °C) > distance to roads (1.11 km) > distance to water bodies (1.65 km, 8.91 km) > slope (7.24°) > distance to residential areas (4.1 km) > nighttime light intensity (1.55 NW/cm²/sr). Significant nonlinear effects and interactions among the driving factors were identified. (3) Ecological zoning was implemented based on the identified critical thresholds. The results indicate that most areas of Yichang City were classified as key protection zones and key prevention zones, primarily influenced by natural factors; while a small portion was designated as key treatment zones, primarily influenced by anthropogenic factors. This zoning provides a clear scientific basis for implementing differentiated ecosystem management strategies.
Keywords: Ecological zoning, machine learning, net primary productivity, restricted cubic splines, Threshold identification
Received: 24 Sep 2025; Accepted: 02 Dec 2025.
Copyright: © 2025 Jiang, Tang, Yuan and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Diwei Tang
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