Abstract
Phytoplankton taxonomic α-diversity indices are useful tools to characterize the trophic states in freshwater ecosystems. However, the application of these indices to assess trophic states in large barrier lakes is rare, especially in China. To test the usefulness of phytoplankton taxonomic α-diversity indices in trophic state assessments, we investigated the taxonomic α-diversity-Comprehensive Trophic Level Index (TLI) relationships in the second largest alpine lava barrier lake (Jingpo Lake, China) in the rainy and dry season from 2017 to 2018. Based on a two-year dataset, we found that there was a significant difference in the phytoplankton community, α-diversity indices, and TLI dynamic between the rainy season and the dry season. First, there was significant variation in phytoplankton abundance, the Margalef index, and the Shannon-Wiener index in different hydrological periods (p < 0.05). Second, the mean TLI in the rainy season (44 ± 5) was higher than in the dry season (41 ± 5) (p < 0.05). Lastly, the response characteristics of the Margalef and Shannon-Wiener index with TLI were different in different hydrological periods, and the relationship between the Pielou evenness index and TLI was weak. This study highlights that phytoplankton taxonomic α-diversity indices are relevant tools in water quality assessments but selecting the fit index is necessary. The current study provides key information about phytoplankton community, α-diversity, and trophic states in the largest alpine lava barrier lake, and the results of the study will benefit water quality management and biodiversity conservation in barrier lakes.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Heilongjiang, China
Innovative talent training program of Heilongjiang
Harbin Normal University Doctoral Innovation Fund Project
Science and Technology Innovation Climbing Program of Harbin Normal University
Subject
Nature and Landscape Conservation,Agricultural and Biological Sciences (miscellaneous),Ecological Modeling,Ecology
Cited by
4 articles.
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