Transcript Folie 1 - APFORGEN

Let‘s talk about
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Thomas Geburek
Department of Genetics
Federal Research Centre for Forests, Natural Hazards,
and Landscape (BFW)
Austria
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Let‘s talk about
Population Sizes, ESUs, MVP, PVP
Thomas Geburek
Department of Genetics
Federal Research Centre for Forests, Natural Hazards,
and Landscape (BFW)
Austria
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Extinction
Adaptive Genetic Variance
Effective Population Sizes
Heterozygosity
Transfer of FGR
MVP
SLOSS
Population Size
ESU
Fragmentation
Genetic Richness
Inbreeding
Sampling
ex situ
Bottleneck
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
in situ
Population and Metapopulation: some definitions
What is a population ?
What is a local population ?
What is a metapopulation ?
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Population and Metapopulation: some definitions
Population
Population a community of potentially interbreeding
individuals at a given locality sharing a common
gene pool.
Johannsen (1903)
Local population: “Population, subpopulation,
deme”
Set of individuals that live in the same habitat patch
and therefore interact with each other; most
practically applied to “populations” living in such
small patches that all individuals practically share a
common environment and gene pool.
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Hanski and Simberloff (1997)
Population and Metapopulation: some definitions
Metapopulation
“any assemblage of discrete local populations with migration
among them”
Hanski & Gilpin (1997)
Populations that are spatially structured into assemblages of
local breeding populations with migration between them that
affects local population dynamics, including the possibility of
reestablishment following extinction
Hanski & Simberloff (1997)
What is the difference to panmitic populations?
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Population and Metapopulation: some definitions
Metapopulation
“any assemblage of discrete local populations with migration
among them”
Hanski & Gilpin (1997)
Populations that are spatially structured into assemblages of
local breeding populations with migration between them that
affects local population dynamics, including the possibility of
reestablishment following extinction
Hanski & Simberloff (1997)
What is the difference to panmitic populations?
Contrast with panmictic population where every individual has
equal likelihood of interacting with every other one !
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Metapopulation: types
Levins’ metapopulation: “classical metapopulation”
• A large network of similar small patches, with local
dynamics occurring at a fast time scale; sometimes used to
describe a system in which all local populations have a high
risk of extinction
Mainland-island metapopulation: “Boorman-Levitt metapopulation”
• System of habitat patches located within dispersal distance
from a very large habitat patch where the local population
never goes extinct (hence, M-I metapopulations never go
extinct)
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Metapopulation: types
Harrison & Taylor (1997)
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Effective population size: three concepts
Different definitions depending on which aspect of the
polymorphism fluctuation we are interested in:
Inbreeding effective size  Change in inbreeding level
Variance effective size  Change in gene frequencies
Eigenvalue effective size  Change in heterozygosity level
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Effective population size: definitions
The size of an ideal population for which we would have a
fluctuation of polymorphism (rate of genetic diversity loss or
rate of genetic drift) equivalent to that of a natural
population:
Why does a census population differ normally
from an effective population size?
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Effective population size: definitions
The size of an ideal population for which we would have a
fluctuation of polymorphism (rate of genetic diversity loss or
rate of genetic drift) equivalent to that of a natural
population:
not equal to the census number N
influenced by the number of breeding individuals in a population
time fluctuations of the population size (seasonal, climatic change)
and sex ratio
variance of the number of offspring (polygyny, polyandry, sexual
selection)
inbreeding
overlapping generations
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Effective population size: unequal sex ratio
 Inbreeding effective size
4 Nm Nf
Ne =
Compare census and
effective population size of
this Training Workshop!
Training Workshop on Forest Biodiversity, June 2006, Kuala Lumpur, Malaysia
Nm + Nf
Effective population size: unequal sex ratio
 Inbreeding effective size
4 Nm Nf
Ne =
Malaysian example:
Nm + Nf
Garcinia scortechinii tended towards femalenees in a censused 25
ha area in the Pasoh Forest Reserve (West Malaysia). No males
recorded, however 68 % of the adult trees fruited (Thomas 1997).
Sexual function S = 1.0
 Ne = 0 !
Training Workshop on Forest Biodiversity, June 2006, Kuala Lumpur, Malaysia
Effective population size: unequal sex ratio
 Inbreeding effective size
Effective sizes of a dioecious
population for different sex-ratios
Effective size of a dioecious population of
census size 100 as a function of the
number of males in the population
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Effective population size: size fluctuations
 variance effective size
Var(k)=0
all breeding
individuals produce an
identical number of
offspring
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Effective population size: size fluctuations
 eigenvalue effective size
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Effective neighborhood size
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Effective neighborhood size
General definition extended to the case of monoecious dispersing plants
by pollen and seeds:
A = 4 π (δ /2 + δ )
2
p
2
s
Levin & Kester (1968)
Quercus petraea
Querucs robur
(isozymes)
(SSR)
(SSR)
A = 15.2 ha
A = 19.3 ha
A = 12.0 ha
Le Corre et al. (1998)
Streiff (1998)
Streiff et al.(1999)
Genetic neigbhourhood sizes approx. 1200 - 4000 trees
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Minimum viable population (MVP): definition
Thomas Geburek, Department of Genetics, Austria
How large?
Three major components must be considered in answering this
question:
(1) Is the population large enough to avoid inbreeding depression?
(2) Is there sufficient genetic diversity to retain evolutionary
potential ( Allee effect)
(3) Is the population large enough to avoid accumulating new
deleterious mutations?
How would you define MVP ?
Minimum viable population: definition
one that meets ‘the minimum conditions for the long-term
persistence and adaptation of a species or population in
a given place’ .
theoretically sufficiently large to protect against
extinctions caused by harmful and unpredictable genetic,
demographic or environmental factors over a given
period of time (generally expressed in hundreds of
years).
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Soulé (1987)
Minimum viable population: checklist
The environment including 'worst-case' eventualities that affect the
viability of the population:
(1) Habitat quality including herbivore pressure (game browsing
etc.), insect gradations and fungal epidemics.
(2) Habitat quantity available for the target species.
(3) Disturbance regime (fire, avalanches, torrents, etc)
(4) Population size, structure and fitness are the field of dynamic
interactions between a population and its environment.
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Minimum viable population: checklist
The physical, chemical amd general biological properties of a
population:
(1) Physiology, morphology and disease resistance.
(2) Mode of reproduction.
(3) Adaptedness to the given environment (ability to survive and
reproduce)
(4) Microspatial distribution of trees pollen dispersal, mating
(5) Macrospatial distribution
(6) Ability to occupy the given habitat and to migrate into others
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Minimum viable population: checklist
The environment including 'worst-case' eventualities that affect the
viability of the population (continued):
c
(5) The age structure of the individual population determines the
fluctuations of population size. In addition, the totality of genetic resources
of a species should have an age structure in order to have reproductive material
continuously available for use, and for safety considerations.
(5) Intrinsic rate of increase and its spatial variation.
(6) Sex ratio. In dioecious species the sex ratio is among the determinants of the
completeness of pollination and the evenness of seed distribution. It varies also within
species.
(5) Dynamics of spatial distribution (size and distribution of
patches).
(5) Genetic variation (proportion and number of polymorphic
gene loci and the numbers of their alleles). Pertinent information
exists mainly about neutral marker loci.
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Minimum viable population: checklist
The environment including 'worst-case' eventualities that affect the
viability of the population (continued):
(11)Heterozygosity. The previous and this term are often used as synonyms. It is
true that without genetic variation there is no heterozygosity. However, heterozygosity is
a parameter of the genotypic structure and does not directly measure genic variation.
(12)Adaptability. Genetic variation is considered to be the sole basis of adaptability.
Environmental degradation challenges adaptational processes in tree populations.
(11)Spatial genetic structure. Restrictions on the transport distances of effective
pollen and viable seed imply the development of spatial genetic structures. This is
eventually enhanced or blurred by viability selection.
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Discussion of the 50/500 rule of thumb
No finite population is immune from
eventual inbreeding depression
Generally we do not know precisely how large
population must be to avoid meaningful
inbreeding depression.
Pragmatically the IUCN scheme for categorization
extinction risk is set as
50 adults critically endandered
250 adults endangered
1000 adults  vulnerable
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Effective population sizes of approx. 500 - 5000 have been
suggested as necessary to maintain short-term evolutionary
potential.
Populations with Ne less than 500 are not doomed to immediate
extinction, but will became increasingly vulnerable with time.
Wild populations often require a census size about 10
times larger than Ne .
Effective population sizes of 10,000 to 100,000 are required to
retain single-locus diversity due to the balance between mutation
and drift.
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
How to prioritize objectively conservation units?
Towards a unified concept for defining conservation
units:
„Selective Environmental Neighborhoods“ (SEN)
(sensu Brandon)
„Evolutionary Signifcant Units“ (ESU)
(sensu Ryder, Waples, Crandall et al. among others)
•
first concept appeared in the eighties
•
developed to provide an objective approach to prioritizing
units for protection below the species level
•
concept has been frequently moulded
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Evolutionary Signifcant Unit (ESU)
(sensu Crandall et al.)
(1) Ecological exchangeability
Individuals can be moved between populations and can
occupy the same ecological niche
(2) Genetic exchangeability
Individuals are genetically exchangeable if there is ample
gene flow among populations.
Unique alleles or low gene flow estimates (effective number of migrants per
generation (Nm) <1) are indicative fo non exchangeability.
Crandall et al. (2000)
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Extinction: definition
Reproductive failure or death of the last individuals of a population or
species.
What is causing extinctions?
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Extinction: definition
Reproductive failure or death of the last individuals of a population or
species. Caused by
(1) Demographic stochasticity
(2) Environmental stochasticity including catastrophes
(3) Genetic stochasticity
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Extinction:
demographic, environmental and genetical stochasticity
(1) Demographic stochasticity
Random fluctuation of population parameters such as
distribution of age classes or sex ratios
Individual of any age have specific rates of survival and
reproduction
 Chance variation in individual birth and death
(2) Environmental stochasticity
Induced by temporal changes of rates of survival and reproduction
Fires, damages by wind and snow, drought periods, large-scale cuttings of
forests, insects graduation, outbreaks of parasites
 Random series of environmental changes
(3) Genetic stochasticity
Main source is finite population size
Drift effects including bottleneck and founder effects
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Population Viability Analysis (PVA): definition
Assessing the likelihood that a population will persist over time,
estimation of extinction probabilities by analyses that
incorporate identifiable threats to population survival in to
models of the extinction process.
Will a population fail or prosper in response to specific
circumstances?
What is the risk of extinction for a population over a specific
time, under a given set of circumstances?
Based on a model that relates a dependent variable (i.e. N) to
the independent variables that influence it (weather, mortality,
etc.), this relationship is mediated through parameters (i.e.
survival rates, reproductive rates)
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Population Viability Analysis (PVA)
How do we do a PVA?
(1) Construct a mathematical model using the following data:
Average mortality rates
Average recruitment rates
Current age distribution
Current size
(2) Add stochasticity to the model
Allow model elements to vary at random between their observed
range of annual values
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Population Viability Analysis (PVA): Benefits
• Simulations of individual populations can be run using this random
variation to determine the probability of population extinction within a
certain period of time or the mean time to extinction.
• Can determine which parameter or combination of parameters most
influences extinction probabilities
• Management regimes that affect population parameters can then be
developed and analyzed
• Simulations of the impact of this management regime could be
compared with the original population model to determine how it
affects the probability that the population will persist in the future –
can evaluate the effectiveness of management efforts
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
Population Viability Analysis (PVA): Problems
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Different definitions – not restricted to a mathematical model, but
should be
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Estimating parameters – totally dependent upon field data which is
not always available (the more data, the better the analysis)
•
Can’t diagnose the cause of decline, or prescribe a remedy for it
•
Level of uncertainty may be large
Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia
By now you know
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Training Workshop on Forest Biodiversity, Kuala Lumpur, Malaysia