A Simple Index of Lake Ecosystem Health Based on Species-Area Models of Macrobenthos

Junyan Wu, Yajing He, Yongjing Zhao, Kai Chen, Yongde Cui () and Hongzhu Wang
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Junyan Wu: State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
Yajing He: State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
Yongjing Zhao: State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
Kai Chen: State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China
Yongde Cui: State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
Hongzhu Wang: State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China

IJERPH, 2022, vol. 19, issue 15, 1-13

Abstract: An effective biological index should meet two criteria: (1) the selected parameters have clear relationships with ecosystem health and can be measured simply by standard methods and (2) reference conditions can be defined objectively and simply. Species richness is a widely used estimate of ecosystem condition, although it is increased by nutrient enrichment, a common disturbance. Based on macrobenthos data from 91 shallow Yangtze lakes disconnected from the mainstem, we constructed an observed species ( S O )-area ( A ) model to predict expected species richness ( S E ), and then developed an observed to expected index (O/E- SA ) by calculating the S O / S E ratio. We then compared O/E- SA with three other commonly used indices regarding their ability to discriminate cultivated and urban lakes: (1) River Invertebrate Prediction and Classification System (RIVPACS; O/E- RF ), (2) Benthic Index of Biotic Integrity (B-IBI), and (3) Average Score Per Taxon (ASPT). O/E- SA showed significant positive linear relationships with O/E- RF , B-IBI and ASPT. Quantile regressions showed that O/E- SA and O/E- RF had hump-shape relationships with most eutrophication metrics, whereas B-IBI and ASPT had no obvious relationships. Only O/E- SA , O/E 50 and B-IBI significantly discriminated cultivated from urban lakes. O/E- SA had comparable or higher performance with O/E- RF , B-IBI and ASPT, but was much simpler. Therefore, O/E- SA is a simple and reliable index for lake ecosystem health bioassessment. Finally, a framework was proposed for integrated biological assessment of Yangtze-disconnected lakes.

Keywords: ecosystem health assessment; biological index; quantile regression model; shallow lakes; Yangtze River basin (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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