Research on the Response of Ecosystem Service Function to Landscape Pattern Changes Caused by Land Use Transition: A Case Study of the Guangxi Zhuang Autonomous Region, China

Abstract

Land use transitions cause reconfigurations of regional landscape patterns which can further change the regional ecosystem service functions and its values, especially in environmentally fragile regions. Firstly, this paper theoretically examines the relationships between land use transitions, landscape pattern evolution and the responses of ecosystem service functions in the Guangxi Zhuang Autonomous Region (Guangxi). Then, it explores the spatio-temporal evolution features of land use transition by using land use change matrices, examines landscape patterns by using the landscape pattern index, and studies ecosystem service value (ESV) by revising the coefficients of ESV per unit area. Finally, focus is placed on the empirical analysis of ESV responses to landscape pattern evolution caused by land use transitions in Guangxi. The results show that: (1) Guangxi has undergone an overall intensity-changing process of land use transition at a moderate rate during 1990–2010 and at a drastic rate during 2010–2018. In general, the area of construction land and waterbodies has increased, while forested land, grassland and farmland have decreased. Landscape fragmentation and heterogeneity are higher in the central area than that in the surrounding areas, while patch aggregation and connectivity show an opposite trend. Forested land patches are highly clustered, while grassland and farmland are fragmented and scattered and construction land patches tend to have aggregated. (2) The total loss of ESV has reached 20.56 billion RMB in Guangxi, and all areas’ single ESVs have decreased to different degrees during the past 28 years. Spatially, the ESV distribution shows a differentiated pattern of low in the central plain and high in the surrounding mountain regions which are mainly dominated by high-value zones. (3) The total ESV has significant positive correlations with the largest patch index (LPI), COHESION and the Aggregation Index (AI), and significant negative correlations with the Number of Patches (NP) and the Shannon Diversity Index (SHDI), while the correlation with the Landscape Shape Index (LSI) is not significant, indicating that the influence on ESV caused by landscape pattern evolution varies greatly. (4) The change of land area and multi-directional shifts among different land use types caused by land use transitions in Guangxi could both lead to the evolution of landscape patterns. Further, ecological service function responded obviously to the landscape pattern evolution in Guangxi, causing significant changes in strengthening or weakening of the ecological service function and its value. This systematic analysis should help coordinate the relationship of regional land use regulation, landscape pattern optimization and ecosystem operation in Guangxi or even China.

Tick‐tock… says the moon and the sun: Daily activity patterns of mid‐large‐sized mammals in grassland‐dominated landscapes afforested with Eucalyptus

“…Landscape patterns and dynamics, and mainly the alterations induced by humans, are important drivers of change for mammal's populations and communities, affecting, for example, species distribution and abundance patterns, as well as species diversity and composition (Iglesias‐Carrasco et al, 2022; Liu et al, 2022; Liu & Andersson, 2004; Norris et al, 2010; Wong & Candolin, 2015). Although less studied, the relevance of landscape alterations on animal behaviour has been recently emphasized (Alves et al, 2020; Iglesias‐Carrasco et al, 2022; Presley et al, 2019; Silva et al, 2020; Vallejo‐Vargas et al, 2022).…”

Comprehensive Eco-Environmental Effects Caused by Land Use Transition from the Perspective of Production–Living–Ecological Spaces in a Typical Region: A Case Study of the Guangxi Zhuang Autonomous Region, China

“…The mountainous and hilly regions in Guangxi constitute almost 70% of its total area and are prone to ecological issues, namely soil and water losses and rocky desertification; hence, its ecological environment is relatively fragile [27]. In the past 28 years, Guangxi has undergone a drastic land use transition process, one accompanied by changing dynamics of PLES and a reshaping of its landscape pattern, which has further affected the regional ecological environment.…”

“…Contemporary studies of eco-environmental effects caused by land use transition can be divided into two main domains: (1) those that analyze the effects of single environmental elements, such as the water environment [23], soil environment [24], atmospheric environment [25], and climatic hazards [26], etc. ; and (2) those in which the researcher constructs various indices to gauge ecosystem quality based on the land use cover change, by relying on methods and tools such as a valuation of ecosystem services [27,28], landscape ecological risk index [29][30][31], eco-environmental quality index [32][33][34], and habitat quality index [35,36], etc. Among them, according to the ecological differences of land use types, the eco-environmental quality assessment evaluates the ecological quality of place by assigning values to its secondary land use types, thereby trying to express the impact on the environmental quality arising from changes in the quantitative structure of land use caused by land use transition [5].…”

Impact of land use and land cover change on the landscape pattern and service value of the village ecosystem in the karst desertification control

“…Zhao et al, 2020). These studies show that the characteristics, trends, and drivers of change vary over time and across regions (Shi et al, 2018;Li et al, 2022;Liu et al, 2022). Therefore, research on specific periods and regions is key to guiding practice by theory and is a necessary requirement for global sustainable development.…”

“…Firstly, the research scale is generally significant. Most studies take provinces (Wang et al, 2022a;Liu et al, 2022;Zhang et al, 2022), cities (Hou et al, 2020;Chen and Huang, 2021) (Li et al, 2022), counties (Zhang et al, 2020;Zhang et al, 2021), watersheds (Yushanjiang et al, 2018;Wang et al, 2022b), ecological functional areas (Su et al, 2012), and specific landscape types areas (Zhang et al, 2011;Hou et al, 2020;Zhang et al, 2020) as research units. The data sources are mainly low-resolution remote sensing products.…”