How Do Sampling Methods Affect the Body Size–Abundance Relationships of Benthic Macroinvertebrates in Freshwater Ecosystems? A Comparative Analysis
Body size is a key trait of species, populations, and organisms; it relates to abundance, home range, metabolic rates, and stressors. As reported by Damuth’s law, the relationship between body size and abundance is negative with a slope value of −0.75. In aquatic ecosystems, particularly for benthic...
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Published in | Water (Basel) Vol. 15; no. 3; p. 386 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Basel
MDPI AG
01.02.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Body size is a key trait of species, populations, and organisms; it relates to abundance, home range, metabolic rates, and stressors. As reported by Damuth’s law, the relationship between body size and abundance is negative with a slope value of −0.75. In aquatic ecosystems, particularly for benthic macroinvertebrates, the slope value deviates from the expected value of −0.75. This variation may depend on abiotic and biotic factors as well as methods that are used to sample benthic macroinvertebrates. “Leaf-bags” and “Surber-net” are the most used methods and they provide different data about the body size structures and abundance of the sampled benthic macroinvertebrates. Here, we used the slope of the body size–abundance relationships to compare the benthic macroinvertebrate assemblages sampled with two sampling methods (Leaf-bags and Surber-net). We found that Leaf-bags sampled a greater number of smaller taxa than Surber-net, which collected individuals of larger sizes. In our study, differences in the benthic macroinvertebrate body size structures collected with these two sampling methods were evident even if the experiment was performed at a limited spatio–temporal scale. Therefore, Leaf-bags and Surber-net should be used as complementary rather than alternative techniques since they sample integrated information from the benthic macroinvertebrate communities. |
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ISSN: | 2073-4441 2073-4441 |
DOI: | 10.3390/w15030386 |