Determining Tipping Points and Responses of Macroinvertebrate Traits to Abiotic Factors in Support of River Management

Author:

Forio Marie Anne Eurie1ORCID,Goethals Peter L. M.1,Lock Koen1,Nguyen Thi Hanh Tien123ORCID,Damanik-Ambarita Minar Naomi1,Dominguez-Granda Luis4,Thas Olivier567

Affiliation:

1. Department of Animal Sciences and Aquatic Ecology, Ghent University, Coupure Links 653, 9000 Ghent, Belgium

2. Faculty of Biotechnology, Chemistry and Environmental Engineering, Phenikaa University, Yen Nghia, Ha Dong, Hanoi 10000, Vietnam

3. Bioresource Research Center, Phenikaa University, Yen Nghia, Ha Dong, Hanoi 10000, Vietnam

4. Department of Chemical and Environmental Sciences, Escuela Superior Politécnica del Litoral (ESPOL), Km 30.5, Via Perimetral, Guayaquil P.O. Box 09-01-5863, Ecuador

5. Data Science Institute, I-Biostat, Hasselt University, Agoralaan–Gebouw D, 3590 Diepenbeek, Belgium

6. National Institute for Applied Statistics Research Australia (NIASRA), University of Wollongong, Wollongong, NSW 2522, Australia

7. Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Krijgslaan 281, 9000 Ghent, Belgium

Abstract

Although the trait concept is increasingly used in research, quantitative relations that can support in determining ecological tipping points and serve as a basis for environmental standards are lacking. This study determines changes in trait abundance along a gradient of flow velocity, turbidity and elevation, and develops trait–response curves, which facilitate the identification of ecological tipping points. Aquatic macroinvertebrates and abiotic conditions were determined at 88 different locations in the streams of the Guayas basin. After trait information collection, a set of trait diversity metrics were calculated. Negative binomial regression and linear regression were applied to relate the abundance of each trait and trait diversity metrics, respectively, to flow velocity, turbidity and elevation. Tipping points for each environmental variable in relation to traits were identified using the segmented regression method. The abundance of most traits increased with increasing velocity, while they decreased with increasing turbidity. The negative binomial regression models revealed that from a flow velocity higher than 0.5 m/s, a substantial increase in abundance occurs for several traits, and this is even more substantially noticed at values higher than 1 m/s. Furthermore, significant tipping points were also identified for elevation, wherein an abrupt decline in trait richness was observed below 22 m a.s.l., implying the need to focus water management in these altitudinal regions. Turbidity is potentially caused by erosion; thus, measures that can reduce or limit erosion within the basin should be implemented. Our findings suggest that measures mitigating the issues related to turbidity and flow velocity may lead to better aquatic ecosystem functioning. This quantitative information related to flow velocity might serve as a good basis to determine ecological flow requirements and illustrates the major impacts that hydropower dams can have in fast-running river systems. These quantitative relations between invertebrate traits and environmental conditions, as well as related tipping points, provide a basis to determine critical targets for aquatic ecosystem management, achieve improved ecosystem functioning and warrant trait diversity.

Funder

Vlaamse Interuniversitaire Raad—Universitaire Ontwikkelingssamenwerking

Publisher

MDPI AG

Subject

General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology

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