Ecological and biogeographical drivers of freshwater green algae biodiversity: from local communities to large-scale species pools of desmids

Abstract

Dispersal limitation, niche-based processes as well as historical legacies shape microbial biodiversity, but their respective influences remain unknown for many groups of microbes. We analysed metacommunity structure and functional trait variation in 148 communities of desmids, freshwater green algae, distributed throughout Europe. We delineated biogeographic modules for both taxa and sites using bipartite network analysis given that the taxa of a module co-occurred more often than expected by chance in sites of the same module. The network analysis distinguished two main acidic and neutral habitats, reflecting environmental filtering, and within each habitat separated species pools with distinct geographic locations, representing a plausible influence of historical biogeography. The geographic differentiation was consistent with a hypothesis of glacial refugia on Atlantic coast. Distance decay in community composition in addition to environmental influence further suggested a role of dispersal limitation. Next, we quantified the variation in cell volume and surface-to-volume of taxa within and among communities, to examine morphological and physiological adaptations of desmids in varying environments. Communities from continental climate contained larger desmids. Conversely, we found a functional convergence of smaller, fast-growing, desmids in oceanic regions. Overall, our findings suggest that niche-based processes, dispersal limitation, and historical legacy together drive the distribution and structure of desmid communities. Combining trait- and network-based analyses can resolve long-lasting questions in microbial ecology and biogeography, and could be successfully used in macrobial ecology too.

Generalist plants are more competitive and more functionally similar to each other than specialist plants: insights from network analyses

“…By identifying preferential associations between nodes in a bipartite network, modularity analysis identified groups of species and sites that have consistent environmental conditions and functional traits. It thus depicts the overall influence of the abiotic conditions and biogeographical background of sites as well as functional traits on the ability of species to establish and persist at different sites (Bestová et al, 2018;Carstensen et al, 2013;Dormann et al, 2017). We distin- Conversely, mesic grasslands in less stressful conditions can more easily share generalists with other modules.…”

“…This analysis is based only on how occurrences are distributed among communities. Ecologically, the modules in a metacommunity network ( Figure 1) represent different abiotic habitats (Dormann et al, 2017), biogeographical pools (Bestová, Munoz, Svoboda, Škaloud, & Violle, 2018;Holt et al, 2013;Kreft & Jetz, 2010) and functional groups (Carstensen, Lessard, Holt, Krabbe Borregaard, & Rahbek, 2013). Although similar to other clustering techniques, modularity analysis is not influenced by the choice of a distance metric between communities and thus classifies habitat types better than distance-based clustering techniques (Bloomfield, Knerr, & Encinas-Viso, 2018).…”

Loss of pollinator specialization revealed by historical opportunistic data: Insights from network-based analysis

“…We compared networks built on observations made during two large time periods in order to reduce the noise from the short-term natural turnover in community composition [ 30 , 39 ], to overcome subsampling, and thus to highlight large shifts that may have appeared over time. Scaling-up local interactions to a large-scale pollination network can help identify consistent patterns of plant-pollinator interactions across a biogeographical area [ 40 , 41 ], revealing species specialization over distinct ecological contexts. More specifically, we explored changes in network structure over time through the specialization of species within and between modules.…”

Intraspecific Variation in Protists: Clues for Microevolution from Poteriospumella lacustris (Chrysophyceae)

“…Corresponding to these considerations, limited distribution and geographic separation have been shown to apply also to protist populations (Fernandez et al. 2017; Bestová et al. 2018; Boenigk et al.…”