Graduation Date
Fall 2023
Document Type
Thesis
Program
Master of Science degree with a major in Natural Resources: option Environmental Science and Management
Committee Chair Name
Dr. James Graham
Committee Chair Affiliation
HSU Faculty or Staff
Second Committee Member Name
Dr. Ho Yi Wan
Second Committee Member Affiliation
HSU Faculty or Staff
Third Committee Member Name
Dr. Patrick Biber
Third Committee Member Affiliation
Community Member or Outside Professional
Fourth Committee Member Name
Dr. Wei Wu
Fourth Committee Member Affiliation
Community Member or Outside Professional
Keywords
Humboldt Bay, Saltmarsh, Sea Level Rise, GIS, Modeling
Subject Categories
Environmental Science and Management
Abstract
Saltmarsh habitat is vulnerable to Sea Level Rise (SLR) and requires long-term management plans for communities to continue to benefit from their ecosystem services. This study analyzed the variation of above-ground vegetation biomass throughout I Street Marsh, using multiple variables, including classified vegetative community types, elevation and remote sensing indexes comprised of both visual (Red, Green, Blue) and non-visual (Red Edge, Near Infrared) bands. Plant community types were classified using a cluster analysis, and distinguished three communities, based on dominant species: Salicornia, Spartina, and a mixed type (diverse floristic makeup, with no dominant species). Above-ground biomass was significantly higher in Spartina communities. Above-ground biomass was modeled using simple linear regression and was most successful when used within vegetative communities; Salicornia was best predicted using Blue band, Spartina was best predicted with elevation, and mixed was best predicted using Visible Atmospherically Resistant Index (VARI). A saltmarsh platform elevation model was used to predict saltmarsh persistence under expected SLR scenarios, classified as Low (5.8-6.4 mm/yr), Medium (6.0-6.8 mm/yr) and High (6.2-8.5 mm/yr) coupled with various rates of total suspended solids (TSS) (0.006-0.016 g/m3). Scenarios that used current TSS (0.006 g/m3) found 61%, 59% and 53% persistence, under Low, Medium and High SLR scenarios, respectively. Scenarios under historical TSS (0.016 g/m3) found 71%, 70% and 67% persistence under Low, Medium and High SLR rates, respectively. Findings suggest that an increase in available sediment will reduce habitat loss, highlighting the importance sediment management decisions will play on saltmarsh resiliency throughout Humboldt Bay.
Citation Style
APA
Recommended Citation
McNerthney, Madeline Kay, "Modeling current and future saltmarsh distribution in Arcata Marsh" (2023). Cal Poly Humboldt theses and projects. 716.
https://digitalcommons.humboldt.edu/etd/716