文献类型：期刊文献

英文题名：Multiple dimensions of biodiversity jointly drive community completeness in Baima Snow Mountain typical forest

作者：Huang, Xiaobo[1,2,3] Li, Shuaifeng[1,2,3] Li, Cong[1,2,3] Lai, Jiandong[4] Ge, Sang[4] Gerong, Quzha[4] Tang, Rong[1,2,3] Zhang, Rui[1,2,3] Su, Jianrong[1,2,3]

第一作者：Huang, Xiaobo;黄小波

机构：[1] Institute of Highland Forest Science, Chinese Academy of Forestry, Kunming, 650224, China; [2] Pu'er Forest Ecosystem Research Station, National Forestry and Grassland Administration, Kunming, 650224, China; [3] Pu'er Forest Ecosystem Observation and Research Station of Yunnan Province, Kunming, 650224, China; [4] Baima Snow Mountain National Nature Reserve Administrative Bureau, Diqing, 674500, China

年份：2025

卷号：179

外文期刊名：Ecological Indicators

收录：EI(收录号：20253719147570);Scopus(收录号：2-s2.0-105015513567)

语种：英文

外文关键词：Abiotic - Biodiversity - Ecosystems - Environmental protection - Forest ecology - Forestry - Proven reserves

摘要：Traditional biodiversity measures, such as species richness (SR), are inadequate for accurately capturing the completeness of local plant communities. In contrast, community completeness, derived from the concept of dark diversity offers a more robust framework for cross-ecosystem biodiversity comparisons. Dark diversity and community completeness are gaining prominence in both theoretical and applied ecology. In this study, we assessed SR, dark diversity, and community completeness across four primary forest types, Pinus yunnanensis, Quercus oxyodon, Tsuga dumosa, and Abies georgei, along an elevation gradient of 2300–3588 m. We further investigated the effects of various abiotic factors, multiple biodiversity metrics, and soil nutrients on the community completeness index (CCI) in the Baima Snow Mountain National Nature Reserve. Our results revealed that distinct distribution patterns of SR, dark diversity, and CCI among vegetation types. For example, although both SR and dark diversity were relatively low in P. yunnanensis forest, its CCI was high. Overall, CCI was highest in P. yunnanensis and T. dumosa forests, followed by Q. oxyodon forest, with A. georgei forest having the lowest value. Linear mixed-effects models (LMMs) identified functional diversity (Functional Dispersion index [FDis]), phylogenetic diversity (standardized effect size of mean pairwise distance [SES.MPD]), and soil pH (SpH) as the primary drivers of CCI. Hierarchical partitioning analysis further indicated that biodiversity dimensions—FDis and SES.MPD—jointly explained most of the variation in CCI. For a management perspective, integrating CCI with other ecological indicators can support more effective conservation strategies. We recommend prioritizing T. dumosa forest for protection and focusing, restoration and monitoring efforts on A. georgei forest. Enhancing community completeness will require attention to multiple dimensions diversity and SpH. This study provides new insights into local biodiversity patterns and offers a theoretical scientific basis for biodiversity management in protected areas. ? 2025