Oral Presentation Freshwater Sciences 2023

River network isolation and flow variability produce functional and taxonomic temporal beta diversity patterns in macroinvertebrate communities. (#459)

Ryan M Conway 1 , Kurt E Anderson 1 , Christopher M Swan 2 , Eric R Sokol 3 , Bryan L Brown 4
  1. Evolution, Ecology, and Organismal Biology, University of California, Riverside, Riverside, California, United States of America
  2. University of Maryland, Baltimore County, Baltimore, Maryland, United States of America
  3. NSF Neon, Boulder, Colorado, United States of America
  4. Department of Biological Sciences, Virginia Tech, Blacksburg, VA, United States of America

The Network Position Hypothesis (NPH) posits that ecological communities in headwater streams are primarily structured by environmental processes due to isolation, while more connected downstream communities are driven by dispersal processes. While studies of the NPH have contributed to insight into how dispersal networks contribute to community dissimilarity across space; the influence of network position on community dissimilarity across time, temporal beta diversity, remains understudied. We utilized an archived California, USA macroinvertebrate community data with multi-year sampling at 145 sites to examine how flow variability and network position influence temporal beta diversity (taxonomic and functional) as well as components of nestedness and turnover. We hypothesized that more connected communities would respond more rapidly to flow disturbances, reducing temporal beta diversity. In addition to traditional Strahler stream order, we calculated river network centrality measures (closeness and betweenness) to quantify the connectivity of habitat. Further, we tested whether the role of deterministic and stochastic processes differed based on network position based on position by building null models to compare against realized biodiversity values. Isolation in river networks produced greater functional and taxonomic temporal beta diversity, while flow variability increased functional variability and taxonomic abundance-based variability. Our findings will contribute to understanding how to focus conservation efforts in rivers with changing flow regimes and dispersal networks.