Drivers of β-diversity and its component-dependence along the natural restoration in an extremely heterogeneous forest ecosystem

Abstract

β-diversity usually refers to species turnover along a gradient or changes in species diversity between communities. It is a key concept in understanding the mechanisms of biodiversity pattern formation. However, the component dependence and the driving factors of β-diversity during natural restoration remain unclear. In this study, a series of forest dynamic plots (FDPs) were established through the natural restoration stages in degraded karst forests, including the shrub-canopy mixed forest stage (SC), the secondary-growth forest stage (SG), and the old-growth forest stage (OG). After comparing species composition during natural restoration and its dependence on species turnover and nestedness, it was found that natural restoration significantly influenced the species composition by altering the species turnover in degraded karst forests rather than the nestedness. The contribution of turnover to β-diversity gradually increased, while the contribution of nestedness decreases gradually. Furthermore, the PER-SIMPER method was used to quantify the first-order assembly process that drives variations in species composition during restoration stages. To identify the factors influencing β-diversity, both variation partitioning analysis and a random forest model were employed. The results suggested that differences in species compositions across restoration stages were mainly driven by stochastic processes, and the deterministic processes were strengthened during the natural restoration. In addition, topographic factors contributed more to β-diversity than soil nutrient factors. This study highlighted changes in component dependence of degraded karst forests during natural restoration and emphasized the importance of a more comprehensive framework in assessing the restoration of degraded forest ecosystems. More attention should be paid to topographic structure in understanding biodiversity patterns, especially in highly heterogeneous forest ecosystems.