基于InVEST模型的共和县生境质量时空变化及驱动因素
收稿日期: 2023-08-10
修回日期: 2023-11-01
网络出版日期: 2024-03-11
基金资助
青海省重大科技专项(2021-SF-A7-2);青海省自然地理与环境过程重点实验室(2020-ZJ-Y06)
Analysis of spatial and temporal changes in habitat quality and driving factors in Gonghe County using the InVEST model
Received date: 2023-08-10
Revised date: 2023-11-01
Online published: 2024-03-11
在新型城镇化背景下,青海省共和县作为兰西城市群建设的关键节点和典型的荒漠生态脆弱区,其经济和生态的协调发展对建设海南州可持续发展议程创新示范区具有重要意义。本研究基于2000年、2010年、2020年三期土地利用数据,利用InVEST模型,对2000—2020年共和县生境质量时空分布及效应变化特征进行探究,进而对生境质量的影响因子及其作用进行地理探测器和局部空间回归。结果表明:(1)2000—2020年共和县生境质量整体呈上升趋势,生境质量均值分别为0.612(2000年)、0.626(2010年)、0.627(2020年),生境质量空间分布存在明显的区域差异,空间格局上呈现北高南低的态势。(2)影响共和县生境质量的主驱动因子为年平均气温(TEM)和归一化植被指数(NDVI),因子间的交互作用对生境质量空间分异的影响大于单一因子,TEM与香农均匀度指数(SHEI)、香农多样性指数(SHDI)交互作用强烈。(3)TEM对生境质量呈负向效应,负向影响区域主要集中在共和北部与东部地区;NDVI呈正向效应,正向影响区域主要集中在共和中部与南部地区;国民生产总值(GDP)对生境质量的正向效应较2000年上升了30%,塔拉滩光伏促进了共和县生态产业协同发展。研究结果可为干旱区推动地方经济建设和生态环境保护提供科学的决策依据。
严莉 , 曹广超 , 康利刚 , 刘梦琳 , 叶得力 . 基于InVEST模型的共和县生境质量时空变化及驱动因素[J]. 干旱区研究, 2024 , 41(2) : 314 -325 . DOI: 10.13866/j.azr.2024.02.14
In the context of Gonghe County’s role as a pivotal node in Lanxi urban agglomeration and its position as a representative desert area within the new urbanized framework, maintaining a delicate balance between economic and ecologic development is crucial. This balance holds great significance for China in advancing the new development paradigm and implementing the Sustainable Development Agenda’s Innovation Demonstration Zone in Hainan Prefecture. Based on the land use data of 2000, 2010, and 2020, this study utilizes the InVEST model to explore spatial and temporal distribution and habitat quality dynamics in Republican County from 2000 to 2020. Additionally, it investigates influencing factors and their effects on habitat quality using geographic probes and GWR methods. Key results are as follows: (1) Overall habitat quality in Republican County showed an upward trend from 2000 to 2020, with mean values of 0.612, 0.626, and 0.627, respectively. Regional disparities in the spatial distribution of habitat quality were evident, portraying a high-to-low spatial pattern from north to south. (2) Mean annual temperature (TEM) and normalized vegetation index (NDVI) were the main driving factors impacting habitat quality in Gonghe County. The interaction between these factors had a greater influence on spatial differentiation than a single factor, with TEM interacting strongly with Shannon’s evenness index (SHEI) and Shannon’s diversity index (SHDI). (3) The GWR model quantified different driving characteristics and strengths of each driver on habitat quality at the spatial level. TEM exhibited a negative impact on habitat quality, primarily concentrated in the republic’s northern and eastern areas. Gross domestic product (GDP) positively influenced habitat quality, showing a 30% increase compared to 2000, while the photovoltaic system at Tala Shoal promoted synergistic eco-industry development in Gonghe County. This study’s findings offer a scientific basis for decision-making processes aimed at promoting local economic construction and ecological protection in arid areas.
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