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Developing Predictive Stream Fish Productivity Models Using the Metabolic Theory of Ecology and a Size-Based Approach.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Developing Predictive Stream Fish Productivity Models Using the Metabolic Theory of Ecology and a Size-Based Approach./
作者:	Richter, Ian.
面頁冊數:	1 online resource (202 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
Contained By:	Dissertations Abstracts International85-01B.
標題:	Ecology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30242328click for full text (PQDT)
ISBN:	9798379764784

Developing Predictive Stream Fish Productivity Models Using the Metabolic Theory of Ecology and a Size-Based Approach.
Richter, Ian.

Developing Predictive Stream Fish Productivity Models Using the Metabolic Theory of Ecology and a Size-Based Approach. - 1 online resource (202 pages)

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

Thesis (Ph.D.)--University of Toronto (Canada), 2023.

Includes bibliographical references

Secondary production reflects the amount of energy available to higher trophic levels and can provide insight into the dynamics of energy transfer within an ecosystem. Fish production incorporates a wide range of key response metrics such as abundance, biomass, growth, and reproduction, into one quantitative metric but requires resource-intensive data for empirical estimation. While many studies have investigated fish productivity, few have evaluated different methods of estimating production or investigated the key drivers of productivity in riverine ecosystems. Additionally, size spectrum modeling reflects the negative scaling relationship between abundance and body size and has commonly been applied to lake and marine ecosystems to understand trophic dynamics and the transfer of energy for communities and ecosystems. In my thesis, I investigate different approaches to predict the biomass production of stream fish assemblages using the metabolic theory of ecology and size spectrum modeling. By testing the metabolic theory of ecology and published standard production model, I show that precise estimates of total stream fish productivity can be obtained from biomass and body size data. To ensure that fish data are unbiased and accurately represent fish assemblage, I developed a capture probability model using a hierarchical Bayesian framework that corrects the size bias associated with electrofishing removal samples. I then used variance partitioning and model selection to investigate how a combination of abiotic and biotic variables are related to stream fish productivity in wadeable streams. Finally, I investigated the parameterization of size spectrum models at various spatial scales to determine whether site aggregation is a suitable approach for riverine size spectrum modeling. My findings indicate that fish size spectra align better approximate theoretical expectations when multiple sites are aggregated together. Overall, my thesis demonstrates that published standard fish production models can be used to estimate productivity, that productivity is better predicted by biotic than abiotic variables, and that size spectra models at broader spatial scales can be used to investigate the movement of energy at higher trophic levels in river ecosystems.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798379764784Subjects--Topical Terms:

516476
Ecology.
Subjects--Index Terms:

Fish ecologyIndex Terms--Genre/Form:

542853
Electronic books.

Developing Predictive Stream Fish Productivity Models Using the Metabolic Theory of Ecology and a Size-Based Approach.
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