Local environmental and spatial factors are associated with multiple facets of riverine fish β‐diversity across spatial scales and seasons

Abstract

Disentangling the factors governing community structure across various spatial and temporal scales is a core task in community ecology and biogeography, because it could provide valuable insights into biodiversity conservation and management. The relative role of environmental (a proxy for niche‐based mechanism) and spatial (a proxy for dispersal) effects in shaping ecological communities depends on diversity facets, network positions, seasonality and biological characteristics of the focal organisms. However, such patterns are not well understood for fish communities in large river systems, especially if all of these patterns are examined simultaneously. We investigated fish taxonomic, functional and phylogenetic total β‐diversity (and their turnover and nestedness phenomena) at different spatial scales (basin vs. section scales) and seasons (wet vs. dry seasons) in a subtropical river system (the Chishui River basin, China). We also quantified the relative importance of environmental variables and spatial factors in shaping fish β‐diversity by using generalised dissimilarity modelling. At the basin scale, fish taxonomic and phylogenetic β‐diversity across seasons mainly reflected turnover, yet turnover and nestedness contributed likewise to total functional β‐diversity. Taxonomic and phylogenetic β‐diversity were strongly correlated (r from 0.39 to 0.87), whereas functional and both taxonomic and phylogenetic facets were relatively weakly correlated (r from 0.27 to 0.65). Generalised dissimilarity modelling suggested that phylogenetic β‐diversity phenomena were consistently more influenced by environmental variables (wet 16.1%, dry 22.4%) than by spatial factors (wet 6.7%, dry 4.8%). However, for both taxonomic and functional facets, environmental variables (turnover 13.8%, nestedness 6.4%) and spatial factors (turnover 4.3%, nestedness 9.4%) accounted for a greater proportion of variations in turnover and nestedness, respectively. At the section scale, only phylogenetic total β‐diversity and nestedness, as well as taxonomic nestedness significantly differed between the headwater and downstream sections. Furthermore, headwater communities were primarily explained by spatial (15.7%) and environmental (12.7%) variables in the wet season, while environmental factors (25.9%; spatial 7.7%) dominated in the dry season. By contrast, downstream communities were more influenced by environmental factors (17.9%; spatial 8.3%) in the wet season, whereas environmental (11.0%) and spatial variables (11.5%) contributed likewise to β‐diversity in the dry season. Our results highlight that, compared with taxonomic β‐diversity, accounting for turnover and nestedness of functional and phylogenetic β‐diversity helps to reveal distinct biodiversity patterns, and potential environmental and spatial controls. Given that community–environment relationships and the relative contribution of environmental and spatial factors varied between seasons and between the basin and section scales, our study underlines the importance of long‐term dynamics and spatial scales in metacommunity studies. Our findings also suggest that maintaining environmental heterogeneity and adequate hydrological connectivity would be essential for the conservation of fish diversity. Overall, our study advances current knowledge of fish biodiversity patterns and their maintenance mechanisms by adding insights from multi‐faceted diversity and seasonality, which has rarely been done in large subtropical rivers.

Elevational patterns of fish functional and phylogenetic community structure in a monsoon climate river basin

“…Basin, the Chishui River basin shows an extensive elevational gradient and complex river morphology (Wu et al, 2011), which could act as a filter selecting specific lineages to occur in certain sites. The important role of environmental filtering for fish biodiversity dynamics has been recognized in this system (Xia et al, 2023) and other rivers (Erős et al, 2012;Roa-Fuentes et al, 2019;Wu et al, 2022).…”

“…Vertical position reflects fish mobility, occurrence, and habitat preference (Winemiller et al., 2015). We chose these traits because of their sensitivity to environmental variations (Villéger et al., 2017), and widespread usage in studies of fish FD (Dai et al., 2020; Kirk et al., 2022; Xia et al., 2023). Fish functional trait for collected species was obtained from FishBase (Froese & Pauly, 2014).…”

“…In non-wadable riverine sites (i.e., midstream and downstream sites), passive fishing gears, including gillnets (mesh size: 4, 5, 10, and 12 cm between alternate knots), shrimp cages (mesh size: 1.1-1.2 cm; length: 13 m), and trotline (800 hooks baited with earthworms), were deployed for 12 h. Following our fishermen's experience, these gears were only inspected and emptied at the dawn of the next day to avoid disturbing fishes. By fitting a samplesized-based sampling curve, we have illustrated that sampling coverage reached more than 97% across seasons, indicating adequate sampling (Xia et al, 2023). All collected fish individuals were identified to species level, and then measured (1 mm) and weighed (0.1 g) before releasing from the sites.…”

“…Nevertheless, most previous works on fish community assembly are based on a single‐season survey, which may limit our understanding as to how communities are assembled over time (Fitzgerald et al., 2017; He et al., 2022). This is especially true for large rivers, exhibiting significant seasonal variations in hydrology and nutrients (Li et al., 2020; Xia et al., 2023). Environmental filtering is expected to be more prominent during the wet season since fishes can more freely track suitable habitats (Heino et al., 2021).…”

“…In addition, the influence of limiting similarity and environmental filtering should be strengthened in the dry and wet seasons, respectively (H2b, Figure 1) (Montaña et al., 2014). Finally, we anticipated that each environmental variable should explain variations in fish diversity differently (Xia et al., 2023).…”