1 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis 18.1 Introduction Maintaining a population's viability - its ability to sustain itself demographically, is a fundamenta goal of conservation biology and increasingly so also for fisheries management. There is a wealth of justifications for doing so, ranging from ecological considerations to legal, economic and sociological arguments to international treaties and acts. In USA, the Endangered Species Act (ESA) of 1973 regulates management measures for species, but is less useful for conservation work at the population level. While treaths to wild populations typically concerns naturally small populations like those in anadromous salmonids, several marine fish species are actually on the Endangered Species List, and their intra-specific populations are highly relevant for inclusion in conservation topics of fisheries management. So, what is Population Viability Analysis (PVA)?

2 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis ESU - Evolutionary significant units: Populations which: are genetically isolated, or nearly so represent evolutionary legacy of a species (i.e. is genetically distinct, occupies unique habitat, exhibits unique adaptation to an environment) if extinct would represent a significant loss of the evolutionary potential of a species

3 BI 3063 J. Mork H08 Genetic and biologic stock management 18.2 Principles underlying Population Viability Analysis Soule (1987): Minimal viable population size is the population size that provides a given probability of persistence of the population for a given amount of time, for example, a 95% expectation of persistence without loss of fitness for several centuries. Maintenance of population viability and evolutionary adaptivity Populations should be managed with the view to support their ability to maintain their viability over an ecological time scale and their potential for continuous adaptation over an evolutionary time scale (evolutionary potential). Factors that affect population persistence Environmental uncertainty (climatic perturbations; temperature, floods) Natural catastrophes (vulcano outbreaks, drought) Man-made catastrophes (hydroelectric plants, dams, toxic discharges) Demographic and genetic uncertainty (factors affecting effective population sizes) Interaction of factors affecting extinction propability Gilpin & Soulé (1986): Extinction vortices =self-inforcing prosesses. There are 4 types: R-vortex: variance in reproductive rate D-vortex: patchiness in species distribution F-vortex: inbreeding A-vortex: random genetic drift and loss f variability Hallerman Ch. 18 Population viability analysis

4 BI 3063 J. Mork H08 Genetic and biologic stock management 18.3 Estimation of VPN: Viable Population Number (size) The classical process: Consider genetic and demographic population size (heterozygosity  adaptability, but allelic diversity would arguably be a better surrogate). The sequence of steps: 1. Identify the maximum rate of genetic variability loss acceptable in the planning horizon 2. Determine what the N e must be to achieve (1) 3. Determine what census population size corresponds to N e. 4. Determine population size needed for maintaining demographic viability (demographic N ) 5. Determine whether genetic N or demographic N is larger. Adopt the larger as the VPN for the population (recognizing that the various risks may change if the N increases). Hallerman Ch. 18 Population viability analysis

5 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis cont'd Acceptable loss of genetic variability: Heterozygosity is reduced at a rate of 1/2N e per generation. The various forces affecting N e must be carefully understood and considered vhen estimating VPN. Short-term horizon: Short-term horizon: A planning horizon of 50 generations with a 40% loss of heterozygosity is appropriate. N e must be determined accordingly. H critical = 1 - (1 - 1/2N e ) 50 (corresponds to N e  50) (NB! H critical is a fraction) Long-term horizon: Long-term horizon: A planning horizon of 500 generations and the corresponding N e appears appropriate. H critical = 1 - (1 - 1/2N e ) 500 (corresponds to Ne  500)

6 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis

7 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis Relation between census N and effective N Ratio N e /N in various models varies considerably. In fish populations, demographic data needed for some models are scarce or not available. Thus, genetic methods are often preferable. The 50/500 (for both generations & N e ) rule is an approximation: Many factors relating to the species biology may affect the "right" numbers in particular organisms ( e.g. pupfishes vs rodents). In Atlantic cod, very diverse estimates of N e of census-large populations like the Nort Sea stock has been published (one as low as 20 individuals). In salmonids, an average fraction N e /N has been reported to be in the range percent.

8 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis Relation between census N and effective N cont'd

9 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis General: Above all, intimate biological knowledge of the general biology of the stock or population is critical for decisions about choise of conservation measures and tools.

10 BI 3063 J. Mork H08 Genetic and biologic stock management PVA from theory to practice Need for: Quality control of models by retrospective studies of known cases Long time series of key parameters in existing populations Comparative studies of genetic/demographis studies in very small and very large populations (re: inbreeding) Studies of metapopulation dynamics Hallerman Ch. 18 Population viability analysis

11 BI 3063 J. Mork H08 Genetic and biologic stock management 18.4 PVA in management practice In recent years, PVA has been implemented in many fisheries and wildlife management progams, and has affected ecosystem management, development of metapopulation theory, and prioritization of of populations for conservation Metapopulation structure A metapopulation is a collection of local populations, or demes, that interact through the change of individuals, that is, through migration. Extincion of one population and the take-over of its habitat by another population is a key part of metapopulation dynamics, which can be investigated by simulation modelling. Lacy (1987): A system of subdivided populations with occasional migrants is more efficient in maintaining genetic variability across populations in the long-term (maybe most relevant for evolutionary potenstial). Hallerman Ch. 18 Population viability analysis

12 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis Ecosystem management VPN are often large, often in the order of thousands of individuals. For practical reasons, conservation of suitable, large enough natural habitats may be the most efficient way of achieving the goals. This might include landscape planning and other local community activities. It has been realised that the old species-by-species management is not realistic, nor efficient. The concept of ecosystem management har emerged from such considerations, and has been implemented in large-scale land use planning in some areas (Cascade mountains, Tongas natural forest in Alsaka, and sother Appalachian ecological region).

13 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis Prioritization of populations for concervation The current situation is critical for many salmonid populations, but limited resources dictate some form of prioritization. Many authors have suggested criteria for prioritization, putting weight on different parts of the threat picture. Allendorf et al. (1997) found that the prioritization process was most likely to work successfully when applied to stocks on which data exist, when several experts carry out the prioritization, and when the results are peer-reviewed. Recovery of priority stocks should begin with those having the highest chance of success. Management actions that prevent a threathened stock from descending near to or below the threshold of viability and that preserve the remaining habitat for priority stocks are important first steps in concervation.

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15 BI 3063 J. Mork H08 Genetic and biologic stock management Hallerman Ch. 18 Population viability analysis