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揭示中国生物多样性热点的决定因素:基于昆虫群落多样性测度指标驱动因素的证据及其对保护的启示。

Uncovering the determinants of biodiversity hotspots in China: Evidence from the drivers of multiple diversity metrics on insect assemblages and implications for conservation.

机构信息

The Key Laboratory of Zoological Systematics and Application, School of Life Science, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.

The Key Laboratory of Zoological Systematics and Application, School of Life Science, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.

出版信息

Sci Total Environ. 2023 Jul 1;880:163287. doi: 10.1016/j.scitotenv.2023.163287. Epub 2023 Apr 5.

Abstract

Understanding large-scale biodiversity patterns and underlying mechanisms during the formation process is essential for guiding conservation efforts. However, previous studies on the identification and formation mechanism of diversity hotspots in China were often limited to a single (alpha) diversity metric, while multiple (beta or zeta) diversity has rarely been used for exploring drivers and conservation actions. Here, a comprehensive species distribution dataset consisting of representative families of three insect orders was compiled to explore biodiversity hotspots based on different algorithms. Furthermore, to assess the effects of environmental factors on hotspots, we fitted generalized additive mixed-effects models (GAMMs) for species richness, generalized dissimilarity models (GDMs) and multi-site generalized dissimilarity modeling (MS-GDM) for the total beta and zeta diversity. Our results showed that biodiversity hotspots were mainly concentrated in central and southern China, especially in mountainous areas with complex topography, which indicated the insects' affinity to montane environments. Further analyses based on multiple models showed that water-energy factors exerted the strongest explanatory power for the insect assemblage diversity in hotspots of both alpha and beta (or zeta) levels. Additionally, anthropogenic factors also exerted a significant effect on hotspots, and this effect was higher for beta diversity than for alpha diversity. Overall, our study elucidates a comprehensive analysis of the identification and underlying mechanism of biodiversity hotspots in China. Despite several limitations, we still believe that our findings can provide some new insights for conservation efforts in Chinese hotspots.

摘要

理解大规模生物多样性模式和形成过程中的潜在机制对于指导保护工作至关重要。然而,先前关于中国多样性热点的识别和形成机制的研究往往局限于单一的(α)多样性指标,而很少使用多种(β或ζ)多样性来探索驱动因素和保护措施。在这里,我们根据不同的算法,使用由三个昆虫目代表科的综合物种分布数据集来探索生物多样性热点。此外,为了评估环境因素对热点的影响,我们为物种丰富度拟合了广义加性混合效应模型(GAMMs),为总β和ζ多样性拟合了广义不相似性模型(GDMs)和多站点广义不相似性模型(MS-GDM)。我们的结果表明,生物多样性热点主要集中在中国中部和南部,特别是在地形复杂的山区,这表明昆虫对山地环境的亲和力。基于多种模型的进一步分析表明,水-能源因素对α和β(或ζ)水平热点的昆虫组合多样性具有最强的解释力。此外,人为因素对热点也有显著影响,而且这种影响在β多样性方面比在α多样性方面更高。总体而言,我们的研究阐明了对中国生物多样性热点的识别和潜在机制的综合分析。尽管存在一些局限性,但我们仍然认为我们的研究结果可以为中国热点地区的保护工作提供一些新的见解。

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