Graduation Date
Fall 2020
Document Type
Thesis
Program
Master of Science degree with a major in Natural Resources, option Fisheries
Committee Chair Name
Dr. Andre Buchheister
Committee Chair Affiliation
HSU Faculty or Staff
Second Committee Member Name
Dr. Mark Henderson
Second Committee Member Affiliation
HSU Faculty or Staff
Third Committee Member Name
Dr. Brian Tissot
Third Committee Member Affiliation
HSU Faculty or Staff
Fourth Committee Member Name
Dr. Tim Bean
Fourth Committee Member Affiliation
Community Member or Outside Professional
Subject Categories
Fisheries
Abstract
Deep-Sea Coral and Sponge (DSCS) species are signature taxa of deep-water habitats, however understanding the ecological mechanisms that drive their geographic distributions can be difficult to uncover due to the challenges of surveying deep-water ecosystems. A recent study on benthic assemblages in Southern California revealed statistical associations between several DSCS and demersal fishes, many of which are important to management agencies due to commercial or conservation concerns. Maps that predict where these DSCS may occur are needed for the management and protection of these DSCS taxa and the fauna that rely on them for habitat. In this thesis, I develop predictive models and maps for three DSCS in the Southern California Bight, Antipathes dendochristos, Plumarella longispina, and an unidentified Porifera sponge. Two of the taxa, P. longispina and Porifera have been identified to be associated with young-of-the-year rockfish in a previous study. Predictive maps were created using species distribution models developed with habitat-related variables (e.g. food availability, depth, and bathymetry). Generalized Additive Models (GAMs) were created using the best practices for developing DSCS species distribution models, which includes accounting for spatial auto-correlation and model uncertainty. I provide a comparison of how these model results differ from the results of a commonly used modeling approach, Maxent, that relies on presence-only data. Both GAMs and Maxent models performed well when predicting known occurrences, but the variables deemed most important in those models differed. Predictions using GAMs found that all three taxa were distributed in patches across the study region and that the covariates that predicted species distributions were similar between the three taxa. Specifically, species distributions primarily relied on depth, northern currents, and eastern currents. Maxent predictions were much more constrained throughout the study area, with high suitability found mostly on the fringes of the islands off the coast, and covariates relationships were more variable between species. When the GAMs were constrained to the areas where the model had low uncertainty (Bayesian credible interval ranges < 0.25), the predicted species distributions were more similar between the two modeling methods. High probability of DSCS occurrence exist both inside and outside the Channel Islands National Marine Sanctuary (CINMS), with large areas occurring beyond sanctuary boundaries, mostly north of Santa Barbara Island, around Santa Catalina and San Clemente Islands, and along the coast near San Diego. These areas may be important for future explorations and conservation considerations.
Citation Style
Front. Mar. Sci.
Recommended Citation
Kreidler, Nissa, "Species distribution models for three deep-sea coral and sponge taxa in the Southern California Bight" (2020). Cal Poly Humboldt theses and projects. 431.
https://digitalcommons.humboldt.edu/etd/431
Included in
Natural Resources and Conservation Commons, Natural Resources Management and Policy Commons, Oceanography Commons