Thu, Aug 18, 2022: 5:00 PM-6:30 PM
ESA Exhibit Hall
Background/Question/Methods: Spatial synchrony is the tendency for fluctuations in populations to be correlated among different locations. Spatial synchrony is a ubiquitous feature of population dynamics, but aspects of this phenomenon are not well understood. In particular, it is largely unknown how dispersal determines synchrony in real ecosystems and across spatial and temporal scales. We studied synchrony in giant kelp–a major coastal foundation species worldwide–and how it is influenced by propagule dispersal (spores), resources (seawater nitrate), and disturbance (large waves) in southern California. Dispersal was estimated using several metrics based on a spatiotemporally dynamic ocean circulation model. We characterized the geography of kelp synchrony by testing for clusters of populations having high within-group and low between-group synchrony. To test our central hypothesis, we used matrix regression models on matrices of pairwise spatial synchrony in kelp populations, of dispersal, and of synchrony in environmental drivers. We evaluated the robustness of this result to different representations of dispersal and other statistical choices.
Results/Conclusions: There were three distinct geographic clusters of giant kelp populations based on patterns of synchrony across timescales (i.e., periods of fluctuations) that corresponded with three regions: Santa Barbara, Palos Verdes (Los Angeles), and San Diego / Orange County. Analyses showed that, regardless of the dispersal metric used or statistical model, dispersal was by far the best predictor of giant kelp synchrony (P < 0.003). Nutrients and waves were also significant drivers of synchrony in some models (P < 0.25). Because propagule dispersal is a common phenomenon across a diversity of taxa, we expect the patterns and mechanisms of synchrony we find for giant kelp are likely widespread.
Results/Conclusions: There were three distinct geographic clusters of giant kelp populations based on patterns of synchrony across timescales (i.e., periods of fluctuations) that corresponded with three regions: Santa Barbara, Palos Verdes (Los Angeles), and San Diego / Orange County. Analyses showed that, regardless of the dispersal metric used or statistical model, dispersal was by far the best predictor of giant kelp synchrony (P < 0.003). Nutrients and waves were also significant drivers of synchrony in some models (P < 0.25). Because propagule dispersal is a common phenomenon across a diversity of taxa, we expect the patterns and mechanisms of synchrony we find for giant kelp are likely widespread.