长三角地区景观生态风险与人类活动强度的响应及其时空关联

Scale response and spatiotemporal correlations between landscape ecological risk and human activity intensity in the Yangtze River Delta region

人类活动是诱发区域生态风险的重要因素,但生态风险与人类活动在不同尺度下的表征效果不一,响应程度不同,从多尺度科学地研究区域景观生态风险与人类活动强度的关联特征对于协调区域人地关系地域系统矛盾,推动地区可持续发展具有重要意义。该研究以长三角地区为研究对象,基于1990—2020年4期土地利用、夜间灯光、人口空间分布数据,建立市域、县域、格网三级尺度,构建景观生态风险及人类活动强度评估模型,刻画不同尺度下二者的时空响应特征,并基于Copula函数、双变量空间自相关及耦合协调度模型,揭示景观生态风险与人类活动强度的时空关联性。结果表明:1)1990—2020年间不同尺度下长三角地区景观生态风险均呈现北高南低的空间分布格局,且高风险地区持续减少,低风险区均呈增加趋势,其中市域尺度下高风险地区的减势最明显,而县域尺度下,低及中低风险区总体增势最为显著;2)1990—2020年间不同尺度下长三角地区人类活动强度均呈现东北高西南低的空间分布格局且高强度区域均呈现显著上升趋势,而低强度区域均明显下降,其中格网尺度下高强度区域增幅最大,达13.42个百分点,市域尺度下低强度区域的减幅最为明显,达9.76个百分点;3)1990—2020年间长三角地区人类活动强度与景观生态风险呈现正向相关性,但人类活动强度对于景观生态风险的影响正在削弱。空间上高-高(H-H)集聚区域呈现持续减少趋势,而低-低(L-L)呈现先增后减的变化趋势,低-高(L-H)及高-低(H-L)在2010年后增势明显。研究结果可为长三角地区国土空间优化及生态安全维护提供理论依据,为区域生态风险防范和生态修复提供参考。

Human activity has been one of the most important factors inducing regional ecological risks in recent years. But,there are different visualization and response degree of ecological risks and human activities in different land scales. It is a high demand to scientifically analyze the correlation characteristics of regional Landscape Ecological Risk(LER) and Human Activity Intensity(HAI), in order to coordinate the territorial system of human-environment interaction for better regional high-quality development. The ever-increasing conflict can be found between ecological protection and economic and social development, due mainly to rapid urbanization. The Yangtze River Delta(YRD) is one of the typical regions with intensive human activities, remarkable economic development, and outstanding ecological status. Taking the YRD as the subject, a three-level scale of city, county, and grid was established to construct the LER and HAI assessment models, in order to characterize the spatial and temporal response at different scales. The data was also collected from the land use, nighttime lighting, and population spatial distribution in the four periods from 1990 to 2020. The Copula function, bivariate spatial autocorrelation, and coupled coordination degree models were used to reveal the spatial and temporal correlation between the LER and HAI. The results show that(1) the spatial distribution pattern of LER was high in the north of the study area, and low in the south under different scales. The high risk areas continued to decrease during 1990-2020, whereas, the low risk areas showed an increasing trend. There was the most outstanding reduction in the high risk areas at the city scale, with a decrease of 19.51 percentage points over 30 years. By contrast, there was the most significant increase in the low-medium risk and low risk areas at the county scale, indicating an increase of 16.29 percentage points over 30 years.(2) The spatial distribution pattern of HAI was high in the northeast of the study area during 1990-2020, while low in the southwest under different scales. All the regions with high HAI showed a significant increasing trend. There was a significant decreasing trend in the regions with low HAI. The high intensity region presented the largest increase at 13.42 percentage points on the grid scale, whereas, the low intensity region was the most significant decrease at 9.76 percentage points on the city scale.(3) The correlation between HAI and LER shared a positive correlation between 1990 and 2020, but the correlation between them was weakening, indicating the weak influence of regional HAI on LER. By contrast, the coupling and coordination between them showed an increasing trend from 0.3031 in 1990 to 0.3112 in 2020. It infers that the relationship between them was gradually shifting from conflict to coordination. Spatially, there was a continuous decreasing trend in the H-H clustering area. Furthermore, the L-L clustering area showed an increasing and then decreasing trend with an overall decrease. Both L-H and H-L increased significantly after 2010. The spatial correlation characteristics of regional LER and HAI were combined to manage and control the regional ecological environment. The finding can provide a theoretical basis for land management and landscape planning, together with the spatial guidelines for the regional ecological risk prevention and ecological restoration.