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利用大数据集对韩国爬行动物区系的功能群进行分析。

Functional group analyses of herpetofauna in South Korea using a large dataset.

机构信息

Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08802, South Korea.

Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, 47906, USA.

出版信息

Sci Data. 2023 Jan 5;10(1):15. doi: 10.1038/s41597-022-01924-z.

DOI:10.1038/s41597-022-01924-z
PMID:36604446
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9816106/
Abstract

Functional traits are characteristics of species that affect their fitness and ecosystem, and they greatly influence ecological niches. Thus, biodiversity assessment based on functional groups rather than species per se can more realistically reflect the ecological niche space. As essential players of ecosystem functions, herpetofauna are appropriate subjects of functional trait-based analyses. In this study, using a nationwide dataset and applying trait information and ecological niche modeling, the richness within each functional group, and the taxonomic and functional diversity indices of South Korean herpetofauna were visualized to identify and compare the geographic distributions. The results revealed that the reptile community seemed more locally diverse with more overlapping randomized patterns among groups than amphibians, while amphibians showed wider distributions and a higher within-grid occurrence ratio. Functional diversity indices of reptiles also showed more randomized geographic patterns with higher levels at Jejudo Island than amphibians. The findings of this study may help to identify biodiversity hot spots and understand its ecosystem health. Increasing survey data and trait information will improve the assessment.

摘要

功能特征是影响物种适应性和生态系统的特征,它们极大地影响生态位。因此,基于功能组而非物种本身的生物多样性评估可以更真实地反映生态位空间。作为生态系统功能的重要参与者,爬行动物和两栖动物是基于功能特征分析的合适对象。在这项研究中,使用全国性数据集并应用特征信息和生态位模型,可视化了韩国爬行动物和两栖动物每个功能组的丰富度以及分类和功能多样性指数,以识别和比较地理分布。结果表明,与两栖动物相比,爬行动物群落的局部多样性似乎更高,组间重叠随机模式更多,而两栖动物的分布范围更广,网格内出现的比例更高。爬行动物的功能多样性指数也表现出更随机的地理模式,济州岛的水平高于两栖动物。本研究的结果可能有助于识别生物多样性热点地区,并了解其生态系统健康状况。增加调查数据和特征信息将提高评估的准确性。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ace1/9816106/20b0bf95fb75/41597_2022_1924_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ace1/9816106/61837b20de9e/41597_2022_1924_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ace1/9816106/49f53025a696/41597_2022_1924_Fig9_HTML.jpg
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