Abstract

Under ever intensifying pressures from land use, climate change, and erosion, tropical islands are among the most vulnerable systems in the world. Terrestrial systems are weakened by intensifying land use patterns, the weakening of which is highlighted when high intensity rainfall events erode sediment and leads to sediment deposition on the marine system. The deposition of sediment on the marine system is a major stressor that can lead to weakened coral reefs and a decrease in marine resources commonly gathered for food. These interactions have led to the emergence of biocultural resource management strategies, one of which is the ahupua'a system. The ahupua'a system, at some scales, is an example of a resilient resource management strategy that has held up despite the pressures and challenges of living on a tropical island. Here we utilize a combination of unmanned aerial vehicles (UAVs or drones) and autonomous surface vehicles (ASV) to gather imagery that is then used in geospatial analyses to better understand the ahupua'a of Ka'amola as well as evaluate coral reef structure along the south shore of Molokai. Our terrestrial work using UAVs and geospatial analyses supports qualitative data from community members and local land managers regarding sediment movement trends they have noticed. Steep slopes coupled with a weakened landscape and decreasing vegetative cover due to ungulate grazing has primed the area for erosion during high intensity rainfall events. Our marine work matches trends observed in previous studies and highlights the value in utilizing an ASV to perform marine remote sensing while also acknowledging the limitations associated with a system such as the one built for our research work.

Degree

MS

College and Department

Life Sciences; Biology

Rights

https://lib.byu.edu/about/copyright/

Date Submitted

2022-12-15

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd12616

Keywords

Molokai, marine remote sensing, biocultural resource management, unmanned aerial vehicle, autonomous surface vehicle

Language

english

Included in

Life Sciences Commons

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