Yan Feng, Li Chen-Yang, Wang Jing, Lu Zhi-Xue, Huang Xue-Han, Wang Min-Li, Wang Wen-di, Li Ruo-Xi, Pang Jiao, Chen Ya-Heng
School of Water Resources and Environment, China University of Geosciences (Beijing), Beijing 100083, China.
College of Land and Resources, Hebei Agricultural University, Baoding 071001, China.
Huan Jing Ke Xue. 2025 Jan 8;46(1):327-339. doi: 10.13227/j.hjkx.202402008.
The Taihangshan-Yanshan Region is an important ecological barrier area in Beijing-Tianjin-Hebei, and it is of great importance to investigate the spatial distribution pattern and driving mechanism of net primary productivity (NPP) of vegetation for ecological restoration. The MOD17A3HGF.061 NPP dataset was obtained using the Google earth engine(GEE), and Sen trend, coefficient of variation, partial correlation, complex correlation, and residual analysis were applied to investigate the spatial and temporal patterns of vegetation NPP in the study area and to quantitatively isolate the relative contributions of climate change and human activities. The results showed that: ① The vegetation NPP in the study area showed an overall increasing trend from 2003 to 2021, with a rate of(C-based)2.57 g·(m·a) and the distribution characteristics of "low in the surroundings and high in the middle" in the Taihangshan area, "high in the north and low in the south" in the Yanshan area, and "low in the north and low in the south" in the Yanshan area. At the same time, the spatial distribution characteristics of "low around and high in the middle" in the Taihangshan area and "high in the north and low in the south" in the Yanshan area were shown. Nearly 70% of the regions had medium or low volatility of vegetation NPP, and 80% of the regions had the opposite trend of future changes. ② The vast majority of NPP changes were positively correlated with precipitation and negatively correlated with temperature, but the significance was not strong; only 23% of the area had a strong correlation between vegetation NPP changes and meteorological factors, and it was concentrated in the central Yanshan Mountains, while the rest of the area was mainly driven by reasons other than climatic factors. ③ Potentially improved (NPP>0) and potentially degraded (NPP<0) areas were roughly equally distributed, but human activities played a positive role in most of the areas (79%); 76% of the areas were dominated by human activities in the actual improved areas and 58% in the actual degraded areas, and human activities were the main factor dominating the NPP succession of vegetation in the study area. The results of this study provide an important reference for the formulation of precise vegetation ecological protection and restoration policies in the Beijing-Tianjin-Hebei ecological barrier area.
太行—燕山地区是京津冀重要的生态屏障区,研究植被净初级生产力(NPP)的空间分布格局及驱动机制对生态修复具有重要意义。利用谷歌地球引擎(GEE)获取MOD17A3HGF.061 NPP数据集,并运用Sen趋势分析、变异系数、偏相关分析、复相关分析和残差分析等方法,研究该区域植被NPP的时空格局,并定量分离气候变化和人类活动的相对贡献。结果表明:①研究区植被NPP在2003—2021年总体呈上升趋势,速率为(以碳计)2.57 g·(m²·a)⁻¹,太行山区呈现“周边低中间高”的分布特征,燕山地区呈现“北高南低”的分布特征。同时,太行山区呈现“周边低中间高”、燕山地区呈现“北高南低”的空间分布特征。近70%的区域植被NPP波动为中等或较低,80%的区域未来变化趋势相反。②绝大多数NPP变化与降水呈正相关,与气温呈负相关,但显著性不强;仅有23%的区域植被NPP变化与气象因子相关性较强,且集中在燕山山脉中部,其余区域主要受气候因子以外的因素驱动。③潜在改善区(NPP>0)和潜在退化区(NPP<0)大致呈均匀分布,但人类活动在大部分区域(79%)发挥了积极作用;实际改善区中76%的区域受人类活动主导,实际退化区中58%的区域受人类活动主导,人类活动是研究区植被NPP演替的主要主导因素。本研究结果为京津冀生态屏障区精准制定植被生态保护与修复政策提供了重要参考。