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Spatial hierarchical partitioning of macrobenthic diversity of clam (Ruditapes) fishing grounds over a large geographical range of Japan
Ecological Research ( IF 2 ) Pub Date : 2020-09-21 , DOI: 10.1111/1440-1703.12172
Yoshitake Takada 1 , Motoharu Uchida 2 , Naoaki Tezuka 2 , Mutsumi Tsujino 2 , Shuhei Sawayama 3 , Hiroaki Kurogi 3 , Yuka Ishihi 4 , Satoshi Watanabe 4
Affiliation  

Studies on biodiversity management and conservation have often focused on tidal flats and estuaries. Macrobenthic assemblages in these habitats generally show local and geographical variations. Therefore, understanding about their spatial structure is important in assessing their biodiversity. This study aims to examine the spatial hierarchical composition of macrobenthic diversity in Ruditapes philippinarum fishery grounds covering a large (1,700 km) geographic range of Japan. Four diversity measures according to the sensitivity parameter q = 0, 1, 2 and Inf were used to evaluate the contribution of four spatial levels (site, area, region and total). Observed assemblages had a few abundant and many rare taxonomic units. Although the abundant taxonomic units, including Ruditapes, occurred over larger spatial levels, the between‐region β diversity (diversity increment from the region to the total level) contributed most to the diversity of the total area. Comparisons of four diversity measures further revealed that the contributions of the between‐region β diversity were more pronounced in the rare taxonomic units than the abundant ones. Null model analysis confirmed these results although different null models generated some variations in the hierarchical composition of the diversities.

中文翻译:

日本大地理范围内蛤类(Ruditapes)渔场大型底栖动物多样性的空间分层划分

关于生物多样性管理和保护的研究通常集中在滩涂和河口。这些生境中的大型底栖动物组合通常表现出局部和地理差异。因此,了解它们的空间结构对于评估其生物多样性很重要。这项研究旨在研究菲律宾大面积(1,700公里)地理范围的菲律宾蛤仔渔业基地大型底栖生物多样性的空间层次组成。根据灵敏度参数q = 0、1、2和Inf的四个分集度量用于评估四个空间水平(位置,面积,区域和总面积)的贡献。观察到的组合具有一些丰富且稀有的分类单位。虽然分类单元丰富,包括Ruditapes发生在较大的空间水平上,区域之间的β多样性(从区域到总水平的多样性增加)对总面积的多样性贡献最大。四种多样性测度的比较进一步表明,在稀有分类单元中,区域间β多样性的贡献要比丰富的分类单元更为明显。零模型分析证实了这些结果,尽管不同的零模型在多样性的层次构成中产生了一些变化。
更新日期:2020-09-21
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