Assessing the influence of simulated environmental gradients on the spatial heterogeneity of landscape patterns in the Tibetan Plateau

Abstract

Landscape patterns are pivotal in the realms of land use planning and ecological development, yet there remains a dearth of comprehensive research pertaining to the prediction of changes in landscape pattern characteristics. Within this study, we adopt the PLUS-CA-Markov and Fragstats models to forecast landscape patterns on the Tibetan Plateau spanning the period from 2030 to 2050. Through qualitative and quantitative analyses, we explore the spatiotemporal characteristics of landscape pattern changes between 2000 and 2050, concurrently identifying correlations among landscape pattern indices. Moreover, acknowledging the distinctive environmental gradients encompassing the plateau, notably elevation, slope, temperature, and precipitation, we investigate their implications on landscape pattern changes. Our findings indicate that: (1) Grassland degradation exhibited the utmost severity between 2000 and 2020, primarily attributed to overgrazing and climate-induced glacial melt. In contrast, cropland, forest, and water showcased divergent trends from 2020 to 2050 when compared to the preceding two decades, indicative of the efficacy of climate change control measures. (2) The distribution of landscape patterns on the Tibetan Plateau exhibited a considerable level of instability, marked by a decline in aggregation, reduced diversity and complexity, and amplified ecological connectivity between 2000 and 2020, signifying a partial amelioration in ecological quality. Between 2020 and 2050, landscape aggregation decreased alongside landscape fragmentation and the number of connectivity paths, signifying a discernible degradation of the plateau's ecosystem. (3) The most significant trade-off relationship was observed between landscape division index and largest patch index, while the synergistic relationship between landscape shape index and mean shape index was more pronounced. (4) Landscape aggregation, division, and largest patch index demonstrated non-linear quadratic trends in relation to elevation and temperature. Landscape shape index and patch density exhibited irregular non-linear effects. Largest patch index was predominantly influenced by slope, whereas division index was most affected by precipitation.