Date

2009

Document Type

Master's Thesis

Degree Name

Master of Science (M.S.)

Department

Science & Environmental Policy

Abstract

A rapid, reliable and cost effective means for identifying species-habitat relationships is urgently needed to support management planning to preserve and restore for the federally listed endangered white abalone (Haliotis sorenseni). Despite an ongoing recovery effort for this depleted species, little is known about the distribution of the white abalone. The aim of this study was to develop a predictive white abalone habitat model from high-resolution multibeam bathymetry data by analyzing relationships between occurrence patterns and geomorphology of the seafloor at Tanner Bank in California, where the presence white abalone has been well documented using ROV video transect surveys. We hypothesized that there are predictable relationships between the occurrence of white abalone and measurable seafloor characteristics including depth, slope, rugosity, Topographic Positioning Index (TPI), and substrate types that can be derived from bathymetric digital elevation models (DEM). Analyses were based on a Generalized Linear Model (GLM) and Ecological Niche Factor Analysis (ENFA). ENFA was used to generate pseudo-absences since reliable absences were not available in the dataset. The GLM with ENFA-weighted pseudo-absence was used to derive a predictive habitat map in a geographic information system (GIS). Evaluation by a Receiver Operating Characteristic (ROC) curve indicated a high accuracy of model performance. The initial results from the application of the Tanner Bank derived model to bathymetry data from Carrington Point, Santa Rosa Island, Ca (a different site where white abalone were once abundant but are now absent) supports the broad utility of this model as a tool for identifying potential outplanting sites for white abalone recovery efforts. This modeling approach also has potential utility in the conservation and management planning for the heavily depleted green, pink and pinto abalone, as well as other scarce benthic species.

Comments

Thesis (M.S.) Division of Science and Environmental Policy

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