Incorporating ecosystem services into functional zoning and adaptive management of natural protected areas as case study of the Shennongjia region in China.

Against the background of global climate change and anthropogenic interference, studying the spatial and temporal heterogeneity of ecosystem services in important ecological function regions and rationally dividing the functional zones will help to promote the construction of the natural protected areas system dominated by national parks. The Shennongjia Region is an important candidate for China's national parks and one of the key pilots. Integrating the InVEST model, Getis-Ord Gi* index, hotspot analysis, GeoDetector and K-means clustering algorithm, we measured five ecosystem services interactions and delineate the functional zones. The results show that the spatial and temporal evolution of various ecosystem services in the Shennongjia Region between 2000 and 2020 was significant. All ecosystem services showed a decreasing and then increasing trend, except for carbon storage, which slowly declined. The ecological status of the region is in the process of polarization, with the local environment showed a trend of continuous deterioration. Water yield-habitat quality and carbon storage-water purification showed synergistic relationships; soil conservation showed trade-offs with water yield, carbon storage and water purification over a wide spatial range. The interaction between land surface temperature and vegetation cover was the most significant dominant factor. Hot spots for the comprehensive ecosystem services index were mainly located in the central and southern parts of the Shennongjia region and four types of ecosystem service functional zones were identified accordingly. This study is of great significance for maximizing the benefits of ecosystem service functions, the efficient allocation of environmental resources and the rational formulation of management policies in natural protected areas.

Spatial and temporal evolution of ecological vulnerability based on vulnerability scoring diagram model in Shennongjia, China.

Shennongjia is one of the most important ecological function areas and ecologically vulnerable zones in the world. With the rapid development of social economies, especially tourism, the ecological environment of Shennongjia has experienced profound changes. Exploring the characteristics and changing trends of ecological environment in Shennongjia will help to analyze the causes of the damage to the ecological environment, and build a vulnerability analysis framework with multi-scale, multi-element, multi-flow, and multi-circulation characteristics, which provides an effective research paradigm and analysis tool for the study of regional ecological vulnerability. With the support of RS and GIS technology, this study uses spatial principal component analysis (SPCA) and the vulnerability scoring diagram (VSD) model to comprehensively and quantitatively analyze the spatial and temporal evolution characteristics and driving forces of ecological vulnerability in Shennongjia from 1996 to 2018. The VSD model was selected to decompose the vulnerability into three components of "exposure-sensitivity-adaptation", and 16 indicators were selected to construct an ecological vulnerability evaluation system in Shennongjia, and the evaluation data were organized in a progressive and detailed way. (1) During the study period, the overall ecological vulnerability of Shennongjia is in a mild vulnerability level, exhibiting differentiation characteristics of high in the northeast and low in the southwest. High vulnerability zones are mainly distributed in the main towns and roads. (2) The risk of ecological vulnerability of the entire region presents the characteristics of continuous decline. (3) Land-use types, population density, and vegetation coverage are the main factors driving the evolution of ecological vulnerability. (4) A high level of coupling coordination exists between ecological vulnerability and landscape patterns. Analyses of the ecological vulnerability of Shennongjia shows that the entire region is in a mild vulnerability level. The extreme vulnerability risk of the ecological environment shows polarization. The evolution of ecological environment in Shennongjia is the result of the interaction between human activities and natural environment. This study offers an effective way to assess ecological vulnerability and provides some strategies and guidance for improving ecological security.

Remote sensing inversion and spatial variation of land surface temperature over mining areas of Jixi, Heilongjiang, China.

BACKGROUND: Jixi is a typical mining city in China that has undergone dramatic changes in its land-use pattern of mining areas over the development of its coal resources. The impacts of coal mining activities have greatly affected the regional land surface temperature and ecological system. METHODS: The Landsat 8 Operational Land Imager (OLI) data from 2015 and 2019 were used from the Jiguan, Didao, and Chengzihe District of Jixi in Heilongjiang, China as the study area. The calculations to determine the land-use classification, vegetation coverage, and land surface temperature (LST) were performed using ArcGIS10.5 and ENVI 5.3 software packages. A correlation analysis revealed the impact of land-use type, vegetation coverage, and coal mining activities on LSTs. RESULTS: The results show significant spatial differentiation in the LSTs of Jixi City. The LSTs for various land-use types were ranked from high to low as follows: mining land > construction land > grassland > cultivated land > forest land > water area. The LST was lower in areas with high vegetation coverage than in other areas. For every 0.1 increase in vegetation coverage, the LST is expected to drop by approximately 0.75 °C. An analysis of mining land patches indicates that the patch area of mining lands has a significant positive correlation with both the average and maximum patch temperatures. The average patch temperature shows a logarithmic increase with the growth of the patch area, and within 200,000 m2, the average patch temperature increases significantly. The maximum patch temperature shows a linear increase with the patch area growth, and for every 100,000 m2 increase in the patch area of mining lands, the maximum patch temperature increases by approximately 0.81 °C. The higher the average patch temperature of mining land, the higher the temperature in its buffer zone, and the greater its influence scope. This study provides a useful reference for exploring the warming effects caused by coal mining activities and the definition of its influence scope.