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Let‘s talk about

........

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

Extinction

Adaptive Genetic Variance

Effective Population Sizes

Heterozygosity

Transfer of FGR

MVP

SLOSS

Population Size

ESU

Fragmentation

Genetic Richness

Inbreeding

Sampling

ex situ

Bottleneck

in situ

Population and Metapopulation: some definitions

What is a population ?

What is a local population ?

What is a metapopulation ?

Population

Population a community of potentially interbreeding individuals at a given locality sharing a common gene pool.

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.

Johannsen (1903)

Hanski and Simberloff (1997)

Metapopulation

“any assemblage of discrete local populations with migration among them”

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

What is the difference to panmitic populations?

Hanski & Gilpin (1997)

Hanski & Simberloff (1997)

Metapopulation

“any assemblage of discrete local populations with migration among them”

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

What is the difference to panmitic populations?

Contrast with panmictic population where every individual has equal likelihood of interacting with every other one !

Hanski & Gilpin (1997)

Hanski & Simberloff (1997)

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)

Metapopulation: types

Harrison & Taylor (1997)

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

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?

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

Effective population size: unequal sex ratio

 Inbreeding effective size

4 Nm Nf

Ne=

Nm + Nf

Compare census and effective population size of this Training Workshop!

Training Workshop on Forest Biodiversity, June 2006, Kuala Lumpur, Malaysia

4 Nm Nf

Ne=

Nm + Nf

Malaysian example:

Garciniascortechinii 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 size of a dioecious population of

census size 100 as a function of the number of males in the population

Effective sizes of a dioecious population for different sex-ratios

Effective population size: size fluctuations

 variance effective size

Var(k)=0

all breeding individuals produce an identical number of offspring

Effective population size: size fluctuations

 eigenvalue effective size

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

s

Levin & Kester (1968)

Quercus petraea (isozymes) A = 15.2 ha

(SSR) A = 19.3 ha

Querucs robur (SSR) A = 12.0 ha

Le Corre et al. (1998)

Streiff (1998)

Streiff et al.(1999)

Genetic neigbhourhood sizes approx. 1200 - 4000 trees

Minimum viable population (MVP): definition

Thomas Geburek, Department of Genetics, Austria

How large?

Three major components must be considered in answering this question:
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).

Soulé (1987)

Minimum viable population: checklist

The environment including 'worst-case' eventualities that affect the viability of the population:

Habitat quality including herbivore pressure (game browsing etc.), insect gradations and fungal epidemics.
Habitat quantity available for the target species.
Disturbance regime (fire, avalanches, torrents, etc)
Population size, structure and fitness are the field of dynamic interactions between a population and its environment.

The physical, chemical amd general biological properties of a population:

Physiology, morphology and disease resistance.
Mode of reproduction.
Adaptedness to the given environment (ability to survive and reproduce)
Microspatial distribution of trees pollen dispersal, mating
Macrospatial distribution
Ability to occupy the given habitat and to migrate into others

The environment including 'worst-case' eventualities that affect the viability of the population (continued):

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.
Intrinsic rate of increaseand its spatial variation.
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.
Dynamics of spatial distribution (size and distribution of patches).
Genetic variation (proportion and number of polymorphic gene loci and the numbers of their alleles).Pertinent information exists mainly about neutral marker loci.

The environment including 'worst-case' eventualities that affect the viability of the population (continued):

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.
Adaptability.Genetic variation is considered to be the sole basis of adaptability. Environmental degradation challenges adaptational processes in tree populations.
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.

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

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.

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

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)

Extinction: definition

Reproductive failure or death of the last individuals of a population or species.

What is causing extinctions?

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

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

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)

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

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

Population Viability Analysis (PVA): Problems

Different definitions – not restricted to a mathematical model, but should be
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

By now you know

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