| 京津冀生态屏障区植被NPP时空演变驱动力定量解析 |
| 摘要点击 1545 全文点击 156 投稿时间：2024-02-01 修订日期：2024-04-07 |
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| 中文关键词 植被净初级生产力（NPP） 时空变化 人类活动 驱动因素 京津冀生态屏障区 |
| 英文关键词 net primary productivity of vegetation（NPP） spatial and temporal variability human activities drivers Beijing-Tianjin-Hebei ecological barrier area |
| 作者 | 单位 | E-mail | | 闫丰 | 中国地质大学(北京)水资源与环境学院, 北京 100083
河北农业大学国土资源学院, 保定 071001 | yanfeng@hebau.edu.cn | | 李晨阳 | 河北农业大学国土资源学院, 保定 071001 | | | 王靖 | 河北农业大学国土资源学院, 保定 071001 | | | 鲁志雪 | 河北农业大学国土资源学院, 保定 071001 | | | 黄雪寒 | 河北农业大学国土资源学院, 保定 071001 | | | 王敏丽 | 河北农业大学国土资源学院, 保定 071001 | | | 王文迪 | 河北农业大学国土资源学院, 保定 071001 | | | 李若茜 | 河北农业大学国土资源学院, 保定 071001 | | | 庞娇 | 河北农业大学渤海学院, 黄骅 061100 | | | 陈亚恒 | 河北农业大学国土资源学院, 保定 071001 | chenyaheng@126.com |
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| 中文摘要 |
| 太行山-燕山地区是京津冀三省的重要生态屏障区,探究其植被净初级生产力（NPP）的空间分布格局和驱动机制对生态修复工作具有重要指导意义. 依托GEE获取 MOD17A3HGF.061 NPP数据集,运用Sen趋势、变异系数、偏相关、复相关和残差分析等方法探究研究区植被NPP时空演替规律,并定量分离了气候变化与人类活动的相对贡献. 结果表明：①研究区2003~2021年植被NPP整体呈现增加趋势,速率（以C计）为2.57 g·（m2·a）-1,同时空间上呈现太行山地区“四周低、中间高”、燕山地区“北部高,南部低”的分布特征,近70%的区域植被NPP波动性在中等及以下,80%左右的区域未来变化趋势与过去相反. ②绝大部分地区NPP与降水呈正相关,与气温呈负相关,但显著性不强；仅有23%的地区植被NPP变化与气象因子具有较强的相关性,且集中在燕山中部,其余地区主要受气候因素之外的其他原因驱动. ③潜在改善区（NPPH>0）和潜在退化区（NPPH<0）约各占一半,但人类起正向作用的区域占多数（79%）；在实际改善区受人类活动主导的区域有76%,实际退化区中占58%,人类活动是主导研究区植被NPP演替的主要因素. 研究结果为京津冀生态屏障区制定精准植被生态保护与修复政策提供重要参考. |
| 英文摘要 |
| 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·（m2·a）-1 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 （NPPH>0） and potentially degraded （NPPH<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. |
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