Inference and management of populations in variable environments

Population dynamics in space and time are manifested as changes in the distribution and abundance of organisms. To couple such patterns to the underlying processes is a central question in ecology and also key to successful management. In this thesis, I use theoretical models as well as time series...

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Bibliographic Details
Main Author: Jonzén, Niclas
Format: Doctoral or Postdoctoral Thesis
Language:English
Published: Department of Theoretical Ecology, Ecology Building, SE-223 62 Lund, Sweden 2001
Subjects:
Online Access:https://lup.lub.lu.se/record/42142
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spelling ftulundlup:oai:lup.lub.lu.se:a9858fe0-ac42-481e-8efb-4c9f76e4566b 2023-05-15T16:19:22+02:00 Inference and management of populations in variable environments Jonzén, Niclas 2001 https://lup.lub.lu.se/record/42142 eng eng Department of Theoretical Ecology, Ecology Building, SE-223 62 Lund, Sweden https://lup.lub.lu.se/record/42142 urn:isbn:91-7105-163-5 other:ISRN: SE-LUNBDS/NBTE-01/1013+142pp Biological Sciences habitat selection environmental variability Population dynamics harvesting time series analysis model selection Ecology Ekologi thesis/doccomp info:eu-repo/semantics/doctoralThesis text 2001 ftulundlup 2023-02-01T23:31:30Z Population dynamics in space and time are manifested as changes in the distribution and abundance of organisms. To couple such patterns to the underlying processes is a central question in ecology and also key to successful management. In this thesis, I use theoretical models as well as time series data to analyze population dynamics in environments that are variable in space or time. An example of spatial heterogeneity is when we establish a reserve - where individuals are protected from exploitation - and let individuals distribute themselves between the reserve and the surrounding exploited area. I show that if a population conforms to the ideal free distribution (IFD), the harvest rate resulting in the maximum sustainable yield is unaffected by the size as well as the quality of the reserve. Source-sink systems, where there is a net flow from "good" to "bad" habitats, complicate population management, and optimal harvesting decisions are contingent on dispersal rates and quality differences among habitats. Populations also experience temporal variation within a year (seasonality) as well as between years. By incorporating seasonality in a population harvesting model, I give an explanation to the observation that pre-harvest population densities are sometimes unaffected by harvesting. Between-year variability is studied by building stochastic population models that can be approximated by statistical time series models and applied to real data. In exploited populations, the harvesting process itself is another stochastic factor that influences the dynamics. I demonstrate that under many circumstances, variable harvest can explain a considerable proportion of the variation in population density, sometimes even more than explained by environmental stochasticity. The eastern Baltic cod ( Gadus morhua ) seems to be an example of that. Finally, I show that if the environmental stochasticity is temporally autocorrelated, any attempt to disentangle demographic and environmental impact on population dynamics will be ... Doctoral or Postdoctoral Thesis Gadus morhua Lund University Publications (LUP)
institution Open Polar
collection Lund University Publications (LUP)
op_collection_id ftulundlup
language English
topic Biological Sciences
habitat selection
environmental variability
Population dynamics
harvesting
time series analysis
model selection
Ecology
Ekologi
spellingShingle Biological Sciences
habitat selection
environmental variability
Population dynamics
harvesting
time series analysis
model selection
Ecology
Ekologi
Jonzén, Niclas
Inference and management of populations in variable environments
topic_facet Biological Sciences
habitat selection
environmental variability
Population dynamics
harvesting
time series analysis
model selection
Ecology
Ekologi
description Population dynamics in space and time are manifested as changes in the distribution and abundance of organisms. To couple such patterns to the underlying processes is a central question in ecology and also key to successful management. In this thesis, I use theoretical models as well as time series data to analyze population dynamics in environments that are variable in space or time. An example of spatial heterogeneity is when we establish a reserve - where individuals are protected from exploitation - and let individuals distribute themselves between the reserve and the surrounding exploited area. I show that if a population conforms to the ideal free distribution (IFD), the harvest rate resulting in the maximum sustainable yield is unaffected by the size as well as the quality of the reserve. Source-sink systems, where there is a net flow from "good" to "bad" habitats, complicate population management, and optimal harvesting decisions are contingent on dispersal rates and quality differences among habitats. Populations also experience temporal variation within a year (seasonality) as well as between years. By incorporating seasonality in a population harvesting model, I give an explanation to the observation that pre-harvest population densities are sometimes unaffected by harvesting. Between-year variability is studied by building stochastic population models that can be approximated by statistical time series models and applied to real data. In exploited populations, the harvesting process itself is another stochastic factor that influences the dynamics. I demonstrate that under many circumstances, variable harvest can explain a considerable proportion of the variation in population density, sometimes even more than explained by environmental stochasticity. The eastern Baltic cod ( Gadus morhua ) seems to be an example of that. Finally, I show that if the environmental stochasticity is temporally autocorrelated, any attempt to disentangle demographic and environmental impact on population dynamics will be ...
format Doctoral or Postdoctoral Thesis
author Jonzén, Niclas
author_facet Jonzén, Niclas
author_sort Jonzén, Niclas
title Inference and management of populations in variable environments
title_short Inference and management of populations in variable environments
title_full Inference and management of populations in variable environments
title_fullStr Inference and management of populations in variable environments
title_full_unstemmed Inference and management of populations in variable environments
title_sort inference and management of populations in variable environments
publisher Department of Theoretical Ecology, Ecology Building, SE-223 62 Lund, Sweden
publishDate 2001
url https://lup.lub.lu.se/record/42142
genre Gadus morhua
genre_facet Gadus morhua
op_relation https://lup.lub.lu.se/record/42142
urn:isbn:91-7105-163-5
other:ISRN: SE-LUNBDS/NBTE-01/1013+142pp
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