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Statistical Modeling of Climate Change Impacts on Ecosystems and Wildfire in the Western U.S.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Statistical Modeling of Climate Change Impacts on Ecosystems and Wildfire in the Western U.S./
作者:	Coffield, Shane Riley.
面頁冊數:	1 online resource (201 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-04, Section: B.
Contained By:	Dissertations Abstracts International84-04B.
標題:	Climate change. -
電子資源:	click for full text (PQDT)
ISBN:	9798352939604

Statistical Modeling of Climate Change Impacts on Ecosystems and Wildfire in the Western U.S.
Coffield, Shane Riley.

Statistical Modeling of Climate Change Impacts on Ecosystems and Wildfire in the Western U.S. - 1 online resource (201 pages)

Source: Dissertations Abstracts International, Volume: 84-04, Section: B.

Thesis (Ph.D.)--University of California, Irvine, 2022.

Includes bibliographical references

Ecosystems in the Western US face a combination of climate-driven threats including warming temperature, drought, and wildfire. How ecosystems respond to these threats is directly relevant for human health, water availability, and carbon storage toward climate mitigation, among other services. However, there currently exist large uncertainties regarding the impact of a changing climate on ecosystems and the reliability of these ecosystems to serve as carbon sinks going forward. In my dissertation I used statistical and machine learning techniques along with large-scale geospatial datasets to explore several questions at the intersection of climate change and ecosystems. In my first study, I developed a new framework for wildfire prediction. I found that vapor pressure deficit at the time of ignition and the density of black spruce trees surrounding ignition sites could be used to predict in Alaskan ecosystems whether a fire would become large. These two pieces of information could help managers triage wildfires to protect vulnerable ecosystems given limited resources. In my second chapter, I quantified the future impacts of climate change on carbon storage in California ecosystems, finding that warming temperatures are likely to drive a net loss of carbon and increase the challenges associated with meeting the State's climate mitigation goals. Projected losses were greatest for the mid-elevation mountains, northern coast region, and locations of current forest carbon offset projects. This study also revealed the largest sources of uncertainty to future ecosystem projections, most notably the uncertainty in future precipitation for California and uncertainty in tree species migration rates relative to the climate velocity. In my third chapter, I focused on California's forest carbon offset projects and used remote sensing datasets to assess whether these projects have led to additional carbon sequestration in the 5-10 years since their initiation. Five lines of evidence related to carbon trends, harvest rates, and species composition in projects relative to similar forests suggested that in general our portfolio of projects has not led to detectable carbon sequestration beyond what would have otherwise occurred. Finally, in my fourth chapter, I quantified future wildfire risk across California based on climate and vegetation projections from my second chapter. I found that California is likely to see substantial increases in wildfire over this century, especially in scenarios with increased precipitation and/or shrub cover. The collective results of my research highlight key scientific uncertainties related to the future of ecosystems, particularly the uncertainty in future precipitation. The results of each chapter also offer key insights which are relevant for effective ecosystem management in a rapidly changing climate. These insights include (1) predicting large fires from the time of ignition, (2) identifying areas of ecosystem vulnerability for carbon sequestration and conservation goals, (3) building a more reliable and systematic framework for assessing additionality of carbon offsets, and (4) identifying areas of greatest future fire risk, where fuels management could have the greatest impact on reducing extreme wildfire outcomes.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798352939604Subjects--Topical Terms:

1009004
Climate change.
Subjects--Index Terms:

Machine learningIndex Terms--Genre/Form:

554714
Electronic books.

Statistical Modeling of Climate Change Impacts on Ecosystems and Wildfire in the Western U.S.
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