Browsing College of Fisheries and Ocean Sciences by Author "Miller, Katharine Bollinger"
Predicting Distributions of Estuarine Associated Fish and Invertebrates in Southeast AlaskaMiller, Katharine Bollinger; Norcross, Brenda; Iken, Katrin; Weingartner, Tom; Mundy, Phillip; Huettmann, Falk (2013-05)Estuaries in Southeast Alaska provide habitat for juveniles and adults of several commercial fish and invertebrate species; however, because of the area's size and challenging environment, very little is known about the spatial structure and distribution of estuarine species in relation to the biotic and abiotic environment. This study uses advanced machine learning algorithms (random forest and multivariate random forest) and landscape and seascape-scale environmental variables to develop predictive models of species occurrence and community composition within Southeast Alaskanestuaries. Species data were obtained from trawl and seine sampling in 49 estuaries throughout the study area. Environmental data were compiled and extracted from existing spatial datasets. Individual models for species occurrence were validated using independent data from seine surveys in 88 estuaries. Prediction accuracy for individual species models ranged from 94% to 63%, with 76% of the fish species models and 72% of the invertebrate models having a predictive accuracy of 70% or better. The models elucidated complex species-habitat relationships that can be used to identify habitat protection priorities and to guide future research. The multivariate models demonstrated that community composition was strongly related to regional patterns of precipitation and tidal energy, as well as to local abundance of intertidal habitat and vegetation. The models provide insight into how changes in species abundance are influenced by both environmental variation and the co-occurrence of other species. Taxonomic diversity in the region was high (74%) and functional diversity was relatively low (23%). Functional diversity was not linearly correlated to species richness, indicating that the number of species in the estuary was not a good predictor of functional diversity or redundancy. Functional redundancy differed across estuary clusters, suggesting that some estuaries have a greater potential for loss of functional diversity with species removal than others.