R language-based methods for revealing taxonomic and functional diversity and tracing process of fish fauna

Bin Kang; Xiaoxia Huang; Yunzhi Yan; Yunrong Yan; Hungdu Lin

doi:10.1016/j.mex.2018.11.003

R language-based methods for revealing taxonomic and functional diversity and tracing process of fish fauna

MethodsX. 2018 Nov 7:5:1498-1502. doi: 10.1016/j.mex.2018.11.003. eCollection 2018.

Authors

Bin Kang¹, Xiaoxia Huang², Yunzhi Yan³, Yunrong Yan⁴, Hungdu Lin⁴

Affiliations

¹ College of Fisheries, Ocean University of China, Qingdao, 266003, China.
² Key Laboratory of Atmospheric Environment and Processes in the Boundary Layer Over the Low-latitude Plateau Region, School of Earth Science, Yunnan University, Kunming, 650091, China.
³ College of Life Sciences, Anhui Normal University, Wuhu, 241002, China.
⁴ College of Fisheries, Guangdong Ocean University, Zhanjiang, 524088, China.

Abstract

This paper presented the fish species richness at geographical unit of the Yangtze River. According to the fish taxonomic catalogs and biological traits, R language method was used to determine taxonomic diversity and functional diversity and the components of each unit. Regression analysis was used to test the varying tendency of taxonomic and functional diversity corresponding to the change of species richness. •Functional diversity is compared against taxonomic diversity in capturing the structure of dynamic ecosystem.•The β-diversity indices of taxonomy and function were calculated and decomposed to evaluate the role of species turnover and nestedness in the formation process of fish spatial pattern.•An integrated diversity index, balancing α and β diversity of species richness, taxonomic and functional diversity, is used to screen the prior conservation zone.

Keywords: Conservation; Functional diversity; GIS; R language; Regression analysis; Species richness; Species turnover/nestedness; Taxonomic diversity.