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

Junyan WuYajing HeYongjing ZhaoKai ChenYongde CuiHongzhu Wang
Published in: International journal of environmental research and public health (2022)
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.
Keyphrases
  • human health
  • climate change
  • public health
  • healthcare
  • mental health
  • risk assessment
  • health information
  • genetic diversity
  • physical activity
  • machine learning