太行山和燕山地区碳源/汇时空变化驱动因素分析[j]。

Q2 Environmental Science
Peng-Fei Tian, Feng Yan, Zong-Chao Wang, Yuan-Hang Li, Ze-Hua Wen, Ya-Heng Chen
{"title":"太行山和燕山地区碳源/汇时空变化驱动因素分析[j]。","authors":"Peng-Fei Tian, Feng Yan, Zong-Chao Wang, Yuan-Hang Li, Ze-Hua Wen, Ya-Heng Chen","doi":"10.13227/j.hjkx.202406227","DOIUrl":null,"url":null,"abstract":"<p><p>As an extremely important characteristic of ecosystems, clarifying the spatial and temporal patterns and driving mechanisms of net ecosystem productivity (NEP) is of great significance for the protection and restoration of the Taihang and Yanshan Mountains ecosystem. The net ecosystem productivity (NEP) was estimated using MODIS remote sensing data. By integrating natural and human-related data, we used methods such as trend analysis, Hurst exponent, optimal parameters-based geographical detector, and multi-scale geographically weighted regression to estimate regional NEP and analyzed its spatiotemporal variation characteristics and the impact of driving factors on this change. The results showed that: ① In terms of time, the NEP in the Taihang and Yanshan Mountains Region showed a fluctuating upward trend from 2002 to 2020, with a growth rate of 4.96 g·(m<sup>2</sup>·a)<sup>-1</sup>. In terms of space, the Taihang Mountains Region was characterized by \"low surrounding areas and high central areas\", while the Yanshan Mountains Region was characterized by \"high northern areas and low southern areas\". ② The factor detection results showed that temperature, GDP density, and elevation were the main influencing factors for the spatial differentiation of the Taihang and Yanshan Mountains NEP. The degree of explanation of NEP by each factor after an interaction was much higher than that of a single factor, and the interaction between temperature and fractional vegetation cover was the largest. ③ There were significant differences in the effects of various factors on NEP. Among them, temperature, GDP density, and nighttime light intensity had a negative impact on NEP as a whole; vegetation coverage had a positive effect on NEP; and precipitation, elevation, slope, and population density had bidirectional effects on NEP.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 7","pages":"4403-4415"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Analysis of Driving Factors for Spatiotemporal Changes in Carbon Sources/Sinks in Taihang and Yanshan Mountains].\",\"authors\":\"Peng-Fei Tian, Feng Yan, Zong-Chao Wang, Yuan-Hang Li, Ze-Hua Wen, Ya-Heng Chen\",\"doi\":\"10.13227/j.hjkx.202406227\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>As an extremely important characteristic of ecosystems, clarifying the spatial and temporal patterns and driving mechanisms of net ecosystem productivity (NEP) is of great significance for the protection and restoration of the Taihang and Yanshan Mountains ecosystem. The net ecosystem productivity (NEP) was estimated using MODIS remote sensing data. By integrating natural and human-related data, we used methods such as trend analysis, Hurst exponent, optimal parameters-based geographical detector, and multi-scale geographically weighted regression to estimate regional NEP and analyzed its spatiotemporal variation characteristics and the impact of driving factors on this change. The results showed that: ① In terms of time, the NEP in the Taihang and Yanshan Mountains Region showed a fluctuating upward trend from 2002 to 2020, with a growth rate of 4.96 g·(m<sup>2</sup>·a)<sup>-1</sup>. In terms of space, the Taihang Mountains Region was characterized by \\\"low surrounding areas and high central areas\\\", while the Yanshan Mountains Region was characterized by \\\"high northern areas and low southern areas\\\". ② The factor detection results showed that temperature, GDP density, and elevation were the main influencing factors for the spatial differentiation of the Taihang and Yanshan Mountains NEP. The degree of explanation of NEP by each factor after an interaction was much higher than that of a single factor, and the interaction between temperature and fractional vegetation cover was the largest. ③ There were significant differences in the effects of various factors on NEP. Among them, temperature, GDP density, and nighttime light intensity had a negative impact on NEP as a whole; vegetation coverage had a positive effect on NEP; and precipitation, elevation, slope, and population density had bidirectional effects on NEP.</p>\",\"PeriodicalId\":35937,\"journal\":{\"name\":\"环境科学\",\"volume\":\"46 7\",\"pages\":\"4403-4415\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"环境科学\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://doi.org/10.13227/j.hjkx.202406227\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Environmental Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"环境科学","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.13227/j.hjkx.202406227","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 0

摘要

净生态系统生产力(NEP)作为生态系统的一个极其重要的特征,阐明其时空格局及其驱动机制对太行山和燕山生态系统的保护与恢复具有重要意义。利用MODIS遥感数据估算净生态系统生产力(NEP)。利用趋势分析、Hurst指数、基于最优参数的地理探测器、多尺度地理加权回归等方法,综合自然和人文数据估算区域新经济政策的时空变化特征,并分析了驱动因素对区域新经济政策变化的影响。结果表明:①从时间上看,2002 - 2020年,太行区和燕山区NEP呈波动上升趋势,增长率为4.96 g·(m2·a)-1;在空间上,太行山区呈现出“周边低、中心高”的特征,燕山地区呈现出“北部高、南部低”的特征。②因子检测结果表明,温度、GDP密度和海拔是影响太行山和燕山新经济政策空间分异的主要因素。各因子相互作用后对NEP的解释程度远高于单个因子,其中温度与植被覆盖度的相互作用最大。③各因素对NEP的影响有显著性差异。其中,气温、GDP密度、夜间光照强度对NEP整体有负向影响,植被覆盖度对NEP有正向影响,降水、高程、坡度、人口密度对NEP有双向影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Analysis of Driving Factors for Spatiotemporal Changes in Carbon Sources/Sinks in Taihang and Yanshan Mountains].

As an extremely important characteristic of ecosystems, clarifying the spatial and temporal patterns and driving mechanisms of net ecosystem productivity (NEP) is of great significance for the protection and restoration of the Taihang and Yanshan Mountains ecosystem. The net ecosystem productivity (NEP) was estimated using MODIS remote sensing data. By integrating natural and human-related data, we used methods such as trend analysis, Hurst exponent, optimal parameters-based geographical detector, and multi-scale geographically weighted regression to estimate regional NEP and analyzed its spatiotemporal variation characteristics and the impact of driving factors on this change. The results showed that: ① In terms of time, the NEP in the Taihang and Yanshan Mountains Region showed a fluctuating upward trend from 2002 to 2020, with a growth rate of 4.96 g·(m2·a)-1. In terms of space, the Taihang Mountains Region was characterized by "low surrounding areas and high central areas", while the Yanshan Mountains Region was characterized by "high northern areas and low southern areas". ② The factor detection results showed that temperature, GDP density, and elevation were the main influencing factors for the spatial differentiation of the Taihang and Yanshan Mountains NEP. The degree of explanation of NEP by each factor after an interaction was much higher than that of a single factor, and the interaction between temperature and fractional vegetation cover was the largest. ③ There were significant differences in the effects of various factors on NEP. Among them, temperature, GDP density, and nighttime light intensity had a negative impact on NEP as a whole; vegetation coverage had a positive effect on NEP; and precipitation, elevation, slope, and population density had bidirectional effects on NEP.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
期刊介绍:
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信