Transcript Hallerman ch 18

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)?
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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
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
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
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
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 Ne must be to achieve (1)
3. Determine what census population size corresponds to Ne.
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).
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
18.3.1 cont'd Acceptable loss of genetic variability:
Heterozygosity is reduced at a rate of 1/2Ne per generation. The various forces affecting Ne
must be carefully understood and considered vhen estimating VPN.
Short-term horizon: A planning horizon of 50 generations with a 40% loss of heterozygosity is
appropriate. Ne must be determined accordingly.
Hcritical = 1 - (1 - 1/2Ne)50 (corresponds to Ne  50) (NB! Hcritical is a fraction)
Long-term horizon: A planning horizon of 500 generations and the corresponding Ne appears
appropriate.
Hcritical = 1 - (1 - 1/2Ne)500 (corresponds to Ne  500)
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
18.3.2 Relation between census N and effective N
Ratio Ne/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 & Ne) 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 Ne of census-large populations like the
Nort Sea stock has been published (one as low as 20 individuals).
In salmonids, an average fraction Ne/N has been reported to be in the range 20-40
percent.
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
18.3.2 Relation between census N and effective N cont'd
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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.
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
18.3.4 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
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
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.
18.4.1 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).
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
18.4.2 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).
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
18.4.3 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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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability
analysis
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BI 3063
J. Mork H08
Genetic and biologic stock management
Hallerman Ch. 18
Population viability analysis
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