Thu, Aug 18, 2022: 5:00 PM-6:30 PM
ESA Exhibit Hall
Background/Question/Methods: The metacommunity concept underpins the hypothesis that regional-scale processes set the context for local community assembly. Current theory suggests that (a) asynchronous spatial fluctuations should lead to enhanced local and regional stability and (b) intermediate levels of dispersal connectivity are most likely to exhibit asynchronous dynamics. Empirical investigations of stream macroinvertebrate community stability have generally focused on the reach scale, and demonstrated that a site’s location within a dendritic network can influence both the biodiversity and stability of its resident assemblage. The application of metacommunity theory can provide a framework to understand how network topology, dispersal dynamics, and environmental filtering may all interact to affect community stability in predictable ways at both local (site) and regional (metacommunity) scales. Here, we used a metacommunity simulation package for R (MCSim, https://sokole.github.io/MCSim/) to create numerical models representing stream macroinvertebrate communities with different dispersal rates in a variety of stream network configurations.
Results/Conclusions: Simulation outcomes showed both local (adj. R2 = 0.33) and regional (adj. R2 = 0.59) measures of compositional variability were higher in more synchronous metacommunities, and synchrony had a stronger effect on variability at the regional scale. Synchrony in community composition was influenced by both network (e.g., branching frequency) and metacommunity (e.g., environmental filter strength) characteristics. The simulations clearly demonstrated that dispersal rates were strongly tied to synchrony, and thus, compositional variability. Further, compositional variability at individual sites within a metacommunity showed strong trends with position in the network, but these trends were contingent on metacommunity characteristics. Generally, compositional variability decreased from headwater to mainstem sites, however, this trend was reversed in simulations with moderate to strong environmental filtering and relatively high dispersal rates. Overall, these results suggest the dynamics that influence both local and metacommunity-wide stability in dendritic networks can be influenced by network topology.
Results/Conclusions: Simulation outcomes showed both local (adj. R2 = 0.33) and regional (adj. R2 = 0.59) measures of compositional variability were higher in more synchronous metacommunities, and synchrony had a stronger effect on variability at the regional scale. Synchrony in community composition was influenced by both network (e.g., branching frequency) and metacommunity (e.g., environmental filter strength) characteristics. The simulations clearly demonstrated that dispersal rates were strongly tied to synchrony, and thus, compositional variability. Further, compositional variability at individual sites within a metacommunity showed strong trends with position in the network, but these trends were contingent on metacommunity characteristics. Generally, compositional variability decreased from headwater to mainstem sites, however, this trend was reversed in simulations with moderate to strong environmental filtering and relatively high dispersal rates. Overall, these results suggest the dynamics that influence both local and metacommunity-wide stability in dendritic networks can be influenced by network topology.