Odonata species are sensitive to environmental changes, particularly those caused by humans, and provide valuable ecosystem services as intermediate predators in food webs. We aimed: (i) to investigate the distribution patterns of Odonata in streams on a nationwide scale across South Korea; (ii) to evaluate the relationships between the distribution patterns of odonates and their environmental conditions; and (iii) to identify indicator species and the most significant environmental factors affecting their distributions. Samples were collected from 965 sampling sites in streams across South Korea. We also measured 34 environmental variables grouped into six categories: geography, meteorology, land use, substrate composition, hydrology, and physicochemistry. A total of 83 taxa belonging to 10 families of Odonata were recorded in the dataset. Among them, eight species displayed high abundances and incidences. Self-organizing map (SOM) classified sampling sites into seven clusters (A–G) which could be divided into two distinct groups (A–C and D–G) according to the similarities of their odonate assemblages. Clusters A–C were characterized by members of the suborder Anisoptera, whereas clusters D–G were characterized by the suborder Zygoptera. Non-metric multidimensional scaling (NMDS) identified forest (%), altitude, and cobble (%) in substrata as the most influential environmental factors determining odonate assemblage compositions. Our results emphasize the importance of habitat heterogeneity by demonstrating its effect on odonate assemblages.
Numerous community indices have been developed to quantify the various aspects of communities. However, indices including functional aspects have been less focused on. Here, we examined how community composition varies in response to the environment and discovered the relationship between taxonomic diversity and functional diversity while considering the environment. Macroinvertebrate communities were collected from 20 reservoirs in South Korea. To characterize functional diversity, functional traits in four categories were considered: generation per year, adult lifespan, adult size, and functional feeding groups. Based on their community composition, we classified the reservoirs using hierarchical cluster analysis. Physicochemical and land use variables varied considerably between clusters. Non-metric multidimensional scaling indicated differences between reservoirs and clusters in terms of structure, functional diversity, and environmental variables. A self-organizing map was used to categorize functional traits, and network association analysis was used to unravel relationships between functional traits. Our results support the characteristics of species’ survival strategies such as r- and K-selection. Functional richness exhibited a relationship with taxonomic diversity. Our findings suggest that different types of diversity could play complementary roles in identifying biodiversity. Our findings should prove useful in developing new criteria for assessing freshwater ecosystem health, as well as in evaluating and predicting future alteration of benthic macroinvertebrate communities facing anthropogenic disturbances.
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