We used EMS analysis combined with CCA to identify the relationship between water quality and assembly of algal communities in river-connected lakes. Most of the algal metacommunities for each lake follow a Clementsian structure, characterized by a continual change in algal composition at the genus level along environmental gradients. EMS produced three regional compartments (upstream, midstream and downstream) by reciprocal averaging score. CCA revealed that three compartments were associated with different variables of water quality. Therefore, algal communities along the river were generally assembled depending on the water quality of the region, even though algal communities were dispersed and the species were shared through hydrological connections.
The EMS and the conventional diversity approach were compared to understand the importance of biogeological features on the algal community in river-connected lakes. The alpha diversity (richness) varied significantly depending on individual lakes (Fig. 2a), but the beta diversity and EMS approach could provide clear clustering by biogeographical features (Figs. 2b and 3b). Since beta diversity measures the changes in diversity of species from one site to another 19, beta diversity should provide similar clustering results to the EMS approach. Nevertheless, it is worth noting that the number of regional partitions was different in the two approaches. Because EMS is based on site-by-species incidence, matrices consider whether the community responds to environmental gradients by measuring the proportional species turnover 1, thus the EMS approach could provide discriminatory information compared to beta diversity.
Metacommunities in biogeographical regions or individual lakes were either Clementsian or quasi-Clementsian (Table 1 and S1). Clementsian structures arise when communities are actually changing consistently through groups of species that respond in a similar way to environmental gradients 20. Synchronous species turnover is a phenomenon that occurs in ecosystems that share a significant proportion of species 21. Clementsian structure is not rare, and they have already been reported for other aquatic organisms 8,22. Most species found in riverine ecosystems are generally regulated by species dispersal and sorting 12, so that the downstream sites shared high proportions of species, while upstream sites showed significant differences (Fig. 3b and Fig. S2). The lakes located in midstream (CP, UM, and CC) shared highly similar distributions of algal species but were significantly different from downstream (PD). PD, at the confluence of three rivers, is prone to dispersal of other species from other rivers. These partially explain the quasi-Clementsian structure and distinct patterns compared to midstream.
One of the advantages of the EMS approach is identifying the environmental variables that influence community assembly by correlating reciprocal averaging and environmental variables. CCA, which is based on reciprocal averaging and multiple regression, was used to determine which environmental variables were associated with gradients along which metacommunities were structured 18. The algal communities across broad geographical gradients showed consistent Clementsian structure. Clementsian structure emphasizes discrete ‘community types’ along ecological gradients, such that subgroups of species replace other subgroups in space 20. Such variation also suggests that subgroups of species either respond similarly to environmental variation, or are affected by similar historical effects 23.
Conductivity, COD, and BOD were found to be the most important variables (Loading > |0.5|) of the entire algal community assembly. Previous reports also identify conductivity, COD, and BOD as the main drivers of the algal community composition 13, indicating the importance of these factors as a driver of algal species composition in the rivers. This contradicts, in part, the work of Padisak et al. 24 who found TN and TP to be important drivers of functional groups in the river, while conductivity and COD were not significantly correlated with functional groups. However, untangling these communities and analyzing each lake type classified by the EMS approach revealed that the algal community could be distinguished by presenting a different relationship with temperature. The compositions of algal communities are remarkably influenced by temperature in a single lake 14,25. Since lakes classified through the EMS approach had a similar algal composition (Figs. 2 and 3), it is possible to explain that temperature acted as an important variable, unlike the results where the entire algal community is analyzed. Except for temperature, the variables strongly related to algal communities were conductivity, COD, and BOD, which concurs with the entire algal community analysis, but that importance differs depending on the location of the lake. Depending on land use and population density along the river, the types and concentrations of organic matter flowing into rivers vary, and the algal communities, which are strongly affected by differences in organic matter, are sensitive to regional differences 26. This may explain why environmental variables were found to regionally influence the algal community assembly in river-connected lakes.
The relationship between the main structure of the entire metacommunity and the three lake types classified by biogeographical regions (up-, mid-, and downstream) reveals the role of spatially structured factors on species composition. Previous research on lakes has shown that geographical distance strongly influences the algal community distribution 15. The results of the current study also provide evidence that more than half of the species are shared regardless of the lake position as species dispersal is a main driver of community assembly in a riverine ecosystem. The uniqueness of the algal communities in each lake supports that the assembly of algal community is affected by species sorting. These results are consistent with previous findings that algal communities are determined by species dispersal when habitats are shared in aquatic environments 12. The EMS approach is powerful in detecting compartmentalized structures according to spatial distribution and provides a fruitful interpretation of algal communities at the species and community levels.