Abstract
AbstractDeterministic and stochastic processes are two major factors shaping community dynamics, but their relative importance remains unknown for many aquatic systems, including those in the high‐elevation Qinghai–Tibet Plateau. Here, we explored the causes of multidimensional beta diversity patterns (i.e., taxonomic, functional, and phylogenetic) of a macroinvertebrate metacommunity in this large aquatic system by using multiple approaches (i.e., null models, phylogenetic signal testing, and ordination‐based approaches). To obtain insights into community assembly mechanisms, we also analyzed beta diversity in two deconstructed sub‐metacommunities (e.g., different tributaries and the main lake body). We found that most functional traits showed significant phylogenetic signals, indicating that the functional traits were profoundly influenced by evolutionary history. The null models showed randomness of functional and phylogenetic beta diversities for the whole basin and its tributaries, confirming the importance of stochasticity over deterministic processes in controlling community structure. However, both phylogenetic and functional community structures were clustered in the Qinghai Lake, probably reflecting the importance of environmental filtering. Ordination‐based approaches also revealed that both environmental factors and spatial processes accounted for variation in taxonomic, functional, and phylogenetic beta diversity. More specifically, environmental filtering was more important than spatial processes for the functional dimension, but the opposite was true for the taxonomic and phylogenetic dimensions. The paleogeographic history of the Qinghai Lake basin may have contributed substantially to the prevalence of stochastic processes. Overall, this study provides a better understanding of ecological patterns and assembly mechanisms of macroinvertebrate communities across this poorly known high‐elevation aquatic system that is highly sensitive to climate warming.
Highlights
21 taxa were shared between Qinghai Lake and the tributary streams studied
When we considered the entire basin, Redundancy analysis (RDA) and associated variation partitioning showed that the sets of environmental and spatial v www.esajournals.org variables selected as significant predictors of the three beta diversity dimensions were similar (Appendix S3: Table S2)
V www.esajournals.org the entire basin and across the surrounding rivers were merely random draws from the regional pool of traits and taxa
Summary
Integrating the multiple dimensions (i.e., taxonomic, functional, and phylogenetic) of biodiversity to examine the degree to which stochastic and deterministic processes structure ecological communities is a modern framework in community ecology ( Garcia-Giron et al 2019).v www.esajournals.orgJuly 2021 v Volume 12(7) v Article e03675 GE ET AL.Empirical evidence suggests that either deterministic processes, such as environmental filtering and biotic interactions (Chase and Myers 2011, Isabwe et al 2018, Garcia-Giron et al 2020), or stochastic processes, such as dispersal, extinction, or speciation (Hubbell 2001, Gronroos et al 2013, Tonkin et al 2017), drive community assembly at different spatial and temporal scales. Integrating the multiple dimensions (i.e., taxonomic, functional, and phylogenetic) of biodiversity to examine the degree to which stochastic and deterministic processes structure ecological communities is a modern framework in community ecology ( Garcia-Giron et al 2019). Modern theoretical frameworks emphasize the importance of integrating these two processes when exploring the assembly mechanisms of ecological communities (Leibold and McPeek 2006, Adler et al 2007). The existing sets of functional traits in a community is the result of the selection differences of abiotic and biotic factors among species, which provides crucial clues for understanding the relative importance of different processes in community assembly (Kraft et al 2008, Lebrija-Trejos et al 2010). Limited numbers of functional traits cannot fully represent the actual ecological niche of each species in the community, so that relevant ecological processes can usually be deduced only partially (Swenson et al 2013)
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