Regional proximity effects of landscape pattern evolution: Evidence from 325 county-level areas in the middle reaches of the Yangtze River, China

Unravelling the evolution of landscape patterns is essential to understand regional socio-ecological processes and to solve conflicts between environment protection and human development. However, the role of landscape transition in regional landscape pattern evolution remains unclear. Taking 325 county-level areas in the middle reaches of the Yangtze River (MRYR) as an example, this study explored the spatiotemporal associations between landscape quantity and pattern from the 1970s to 2020. Employing the methods of landscape metrics and trend and correlation analysis, associations between landscape transition and landscape pattern were found. The main results were as follows: (1) From the 1970s to 2020, urban land nearly doubled from 0.93 to 1.89 million km2. Arable land and forest showed the largest quantity reductions of 0.88 million km2 and 0.28 million km2, respectively. Other landscapes showed both decreasing and increasing trends with a spatial overlap among counties. (2) Transition in landscape quantity drives the change in landscape patches, thus affecting the landscape pattern in counties. The percentage of landscape area at the class level (CPLAND) showed relative changes in the quantities of landscape categories in each observation year, but their extreme outliers presented larger changes. (3) Diverse correlation coefficients in terms of magnitude and direction suggested that the transition from natural landscape to human-influenced landscape and the reverse processes occurred. Aggregation and diversity metrics showed spatial interaction with similar distances and the perimeter-area fractal dimension (PAFRAC) showed spatial autocorrelation at local scale. Optimal bandwidths among arable land, forest, and urban land (129.2 km) revealed direct spatial interactions and causal relationships, as did waters and unused land (66.7 km). The findings explained the evolution of landscape patterns and highlighted key areas where various landscape changes occurred, and can provide scientific support for policy-making in regional landscape transition governance.