TY - THES
T1 - Inference and management of populations in variable environments
AU - Jonzén, Niclas
N1 - Defence details
Date: 2001-12-14
Time: 10:15
Place: Blue Hall, Ecology Building
External reviewer(s)
Name: Mangel, Marc
Title: Prof
Affiliation: University of California, Santa Cruz
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PY - 2001
Y1 - 2001
N2 - 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 problematic. I nevertheless try to get around some of the difficulties and present a case study on how winter climate patterns are visible in time series of passerine birds wintering in northern Europe. In conclusion, my thesis shows the need to, and potential of, using ecological theory expressed as mathematical models, to guide our thinking and analysis of population patterns and processes. I have analyzed mathematical models with the purpose of understanding the structure of real systems and what it takes to analyze data from them. The two case studies presented, explicitly couple observed dynamics to the underlying processes with some success.
AB - 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 problematic. I nevertheless try to get around some of the difficulties and present a case study on how winter climate patterns are visible in time series of passerine birds wintering in northern Europe. In conclusion, my thesis shows the need to, and potential of, using ecological theory expressed as mathematical models, to guide our thinking and analysis of population patterns and processes. I have analyzed mathematical models with the purpose of understanding the structure of real systems and what it takes to analyze data from them. The two case studies presented, explicitly couple observed dynamics to the underlying processes with some success.
KW - habitat selection
KW - environmental variability
KW - Population dynamics
KW - harvesting
KW - time series analysis
KW - model selection
KW - Ecology
KW - Ekologi
M3 - Doctoral Thesis (compilation)
SN - 91-7105-163-5
PB - Department of Theoretical Ecology, Ecology Building, SE-223 62 Lund, Sweden
ER -