Matching Items (2)
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- All Subjects: biodiversity
- Creators: Polidoro, Beth
Description
As threats to Earth's biodiversity continue to evolve, an effective methodology to predict such threats is crucial to ensure the survival of living species. Organizations like the International Union for Conservation of Nature (IUCN) monitor the Earth's environmental networks to preserve the sanctity of terrestrial and marine life. The IUCN Red List of Threatened Species informs the conservation activities of governments as a world standard of species' risks of extinction. However, the IUCN's current methodology is, in some ways, inefficient given the immense volume of Earth's species and the laboriousness of its species' risk classification process. IUCN assessors can take years to classify a species' extinction risk, even as that species continues to decline. Therefore, to supplement the IUCN's classification process and thus bolster conservationist efforts for threatened species, a Random Forest model was constructed, trained on a group of fish species previously classified by the IUCN Red List. This Random Forest model both validates the IUCN Red List's classification method and offers a highly efficient, supplemental classification method for species' extinction risk. In addition, this Random Forest model is applicable to species with deficient data, which the IUCN Red List is otherwise unable to classify, thus engendering conservationist efforts for previously obscure species. Although this Random Forest model is built specifically for the trained fish species (Sparidae), the methodology can and should be extended to additional species.
ContributorsWoodyard, Megan (Author) / Broatch, Jennifer (Thesis director) / Polidoro, Beth (Committee member) / Mancenido, Michelle (Committee member) / School of Humanities, Arts, and Cultural Studies (Contributor) / School of Mathematical and Natural Sciences (Contributor) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Consumption of seafood poses a substantial threat to global biodiversity. Chemical contamination found in both wild-caught and farmed seafood also presents significant health risks to consumers. Flame retardants, used in textiles, upholstery, plastics, and other products to reduce risk of fire-related injury, are of particular concern as they are commonly found in the marine environment and permeate the tissues of fish that are sold for consumption via multiple pathways. The widespread issue of fishery collapse could be alleviated by demonstrating to stakeholders that many unsustainable fish stocks are also unhealthy and mutually disadvantageous for both human consumers and the environment. To thoroughly investigate the confounding factors and contradictory signals enmeshed in the relationship between ecologically sustainable fisheries and flame retardant contamination, I examined the biological characteristics of regional fish stocks which drive both contamination and perceived sustainability. I found that the biological and spatial aspects of commonly consumed aquatic and marine species best predict contamination when compared with various indices of sustainability. My results confirm that knowledge of flame retardant toxicity will become increasingly more important to consumers because a high percentage of global populations rely on coastal seafood for subsistence, and although dispersal of chemical contamination is still a poorly understood phenomenon, fish harvested closer to land are likely to contain higher concentrations of potentially harmful chemicals. Because some of the same biological traits which facilitate the uptake of chemicals also contribute to how a species responds to fishing pressures, concern for private health increases public consideration for the conservation of species at risk.
ContributorsNoziglia, Andrea (Author) / Gerber, Leah (Thesis advisor) / Abbott, Joshua (Committee member) / Polidoro, Beth (Committee member) / Arizona State University (Publisher)
Created2015