Brief review of previous lecture

1
Brief review of previous lecture

• Movement corridors
• Potential values
• Observational vs. experimental evaluations
• Alternatives to enhance habitat connectivity

• Conspecific attraction

• Habitat imprinting

2
Lecture Outline Population Viability Analysis
Conservation Genetics

• Extinctions rates, causes, species
  characteristics

• PVA
• Applications
• Types
• Criticisms
• General recommendations

• Conservation genetics
• Applications
• Genetic variation heterozygosity allelic
  diversity
• Hardy-Weinberg Principle
• Population bottlenecks
• Habitat fragmentation
• Inbreeding depression

3
Recent extinctions of animal species
4
Are current extinction rates elevated relative to
background rates?

• Most ecologists agree that current rates are
  relatively high and mainly due to human effects

• However, disagreement exists regarding the
  magnitude of the current extinction periodsome
  equate current period with historical mass
  extinctions others think predictions are
  overestimates.

5
Problems with evaluating current and future
extinction rates

• We dont know how many species there are on earth
• (perhaps 6-20 million but only 1.5 million
  described)

• Extinctions of certain groups are well documented
  (mammals, birds) but others are not (insects,
  plants).

• Background levels are estimated from fossil
  record and have great deal of uncertainty
  associated with them.

• Future predictions might overestimate species
  loss because the species most susceptible to
  human impacts might be lost first.

6
Causes of Endangerment for Vertebrates
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Species traits that might increase extinction risk

• Habitat specialist
• Habitat overlap with humans
• Sensitive to disturbance
• Limited dispersal ability
• Rarelow population density, restricted
  geographic range
• Low growth rate capacity (life-history
  constraints)
• Large space requirements (e.g., large carnivores)
• Harvestable

8
The demise of the passenger pigeon

• Probably the most abundant bird in North America.

• Continental population might have been 6 billion
  and represented 25-40 of
• all of the birds in North America.

• In 1866, a cloud of birds passed into southern
  Ontario that was a mile wide,
• 300 miles long, and took 14 hours to pass a
  single point.

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Population Viability Analysis (PVA)

• A quantitative assessment of a populations risk
  of extinction, quasi-extinction, or projected
  growth rate given current conditions or those
  expected due to proposed management.

• We already have conducted various sorts of PVA in
  lab with Ramas Ecolab
• Effect of TEDs on loggerhead sea turtles
• Habitat improvement for a spotted owl
  metapopulation
• Environmental stochasticity and helmeted
  honeyeater demography

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Potential Uses of PVA
from Morris and Doak. 2002. Quantitative
Conservation Biology.
11

• Initial focus of PVA was to determine Minimum
  Viable Population (MVP) size.
• For instance, what is the population size of
  grizzly bears needed to be 95 certain that the
  population should remain extant for 100 years?

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Main Types of PVA

• Deterministic Single Population Models
• e.g., age-structured matrix model using only
  mean vital values

13
IBM
Metapopulation (Detailed Multi-site)
Increasing Data Requirements
Stochastic Single Population
Deterministic Single Population
Increasing Realism
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Criticisms of PVA Are Models Reliable?
1. Poor data quality

• Data requirements for even deterministic model
  are not trivial
• Good estimates of means (and variances) of vital
  rates are difficult to obtain for endangered
  species
• Dispersal is especially tough to estimate with
  certainty

2. Form of density dependence unknown
5. Models not validated with field data
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Test of PVA1

• Extensive evaluation of PVA using data from 21
  long-term studies

• Surprisingly close match between model
  predictions and real outcomes.
• Actual population sizes fell within bounds
  predicted by stochastic simulations.

PVA is the best tool we have for estimating
extinction risk, and the alternatives are
subjective, less rigorous, and likely to provide
poorer predictions
1Brooks, BW et al. 2000. Predictive accuracy of
population viability analysis in conservation
biology. Nature 404385-387.
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Critique of Brook et al.1

• Argue that Brook et al.s conclusions were worded
  too strongly and a result of bias in studies
  included in the evaluation.

• Only used long-term studies with high-quality
  data and these conditions are the exception for
  populations of endangered species.

• Suggested that PVA will only be accurate for
  predicting extinction probability if data are
  extensive and reliable and if estimated vital
  rates are likely to apply into the future.

PVAs could be useful for comparing the
consequences of different management or
conservation strategiesHowever, we doubt the
general claim that they can be accurate in their
ability to predict the future status of wild
populations
Coulson et al. 2001. The use and abuse of
population viability analysis. TREE 16219-221.
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General Recommendations for using PVA
1. PVA should be treated as a model. Validity of
models should be tested with independent field
data and PVA adjusted accordingly.
2. Evaluate relative rather than absolute rates
of extinction or growth.
3. Do not focus on single value such as MVP
models are not accurate enough to make such
precise predictions.
4. Include uncertainty analysis in the broadest
sense (vital rate estimates, model structure and
assumptions).
5. Compare short-term and long-term projections.
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Conservation Genetics

• Integration of genetic and demographic approaches
  in wildlife ecology
• has become more common.

• Many insights are possible from genetic tools
• Dispersal and connectivity
• Estimating abundances with mark-recapture
  approaches
• Species ID
• Parentage
• Wildlife forensics
• Levels of genetic variation and historical
  population sizes
• Taxonomic relationships and hybridization

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Genetic variation (nuclear)

• Homozygous two alleles (different form of gene)
  at a locus are the same.
• Heterozygous two alleles at a locus are
  different.

Hardy-Weinberg Principle and Heterozygosity
If two alleles (A1 and A2) at a locus have
frequency of p and q, then after one generation
of random mating, the genotype frequencies
are A1 A1 p2 A1 A2 2pq A2 A2 q2 and
p2 2pq q2 1
If we extend concept to multiple alleles in which
homozygote frequency for any allele i with
frequency p is pi2, the expected Hardy-Weinberg
frequency of heterozygotes, given k alleles at a
locus, is
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Expected heterozygosity for single locus

• Example for endangered Hawaiian Laysan finch.
• One locus with three alleles

p1 0.364 p2 0.352 p3 0.284
1 (0.3642 0.3522 0.2842) 0.663
Expected heterozygosity based on Hardy-Weinberg
Principle
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Hardy-Weinberg Equilibrium

• Allele and genotype frequencies will remain
  constant over time if they are at equilibrium.
• Equilibrium means that they are not affected by
  evolutionary forces.

Natural selection
Mutation
Genetic drift
Gene flow

• Hardy-Weinberg equilibrium is unlikely for real
  populations, but expected
• heterozygosity can serve as benchmark. That is,
  we can ask why population deviates from expected.

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Number of alleles at a locus

• Polymorphic gt1 allele detected at a locus across
  all individuals (vs. monomorphic)

• Allelic diversity or richness average number of
  alleles per locus

Allelic diversity is lost more quickly during a
severe population bottleneck than is
heterozygosity, because heterozygosity not
affected as much by changes in frequencies of
rare alleles.
mean heterozygosity
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Population bottlenecks and loss of genetic
diversity

• Two separate studies compared genetic diversity
  before and after a severe population reduction
  for northern elephant seals and Guadalupe fur
  seals.
• Both species hunted to near extinction during
  18th and 19th centuries.
• For instance, northern elephant seals might have
  been reduced to 10-30 individuals. The
  population has recovered to 100,000 seals.

• Compared variation from bones of pre-bottleneck
  seals to extant populations.
• Both species showed loss of genetic diversity.
• For Guadalupe fur seal, pre-bottleneck sample
  included 25 mtDNA genotypes,
• whereas only 7 genotypes found for extant seals.

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Determinants of genetic variation in populations
Natural selection
Mutation
Genetic drift
Gene flow

• Genetic drift is only one of BIG FOUR that always
  acts to decrease variation in populations over
  the long haul.
• With drift, allelic frequencies change randomly
  across generations.
• Drift leads to loss of alleles as they are FIXED
  (frequency 1.0) and to a decrease in
  heterozygosity.
• Genetic drift most important for small
  populations (very much like demographic
  stochasticity).

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Habitat fragmentation and genetic variation

• Small, isolated populations can be dominated by
  genetic drift leading to reduced heterozygosity
  and allelic diversity.
• Genetic diversity can still be maintained across
  populations.

(from Mills)
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Why might fragmentation not lead to loss of
genetic variation?

• Fragmentation might not lead to genetic
  isolation. Only a small level of gene flow is
  needed to maintain variation.

One-migrant-per-generation rule
2. Fragmentation event might have been too
recent for genetic effects to be expressed.
3. Populations might be historically fragmented
due to natural dispersal barriers, which can add
noise and make it difficult to detect
fragmentation effects.
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Inbreeding loss of heterozygosity due to mating
of individuals of related ancestry.
That any evil directly follows from the closest
inbreeding has been denied by many persons but
rarely any practical breeder and never, as far
as I know, by one who has largely bred animals
which propagate their kind quickly.
Charles Darwin (from Mills)
Total Inbreeding Coefficient (Fit) includes
components due to non-random mating and due to
genetic drift.
Inbreeding depression decrease in demographic
vital rates due to inbreeding.
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Inbreeding depression in red-cockaded woodpeckers

• All vital rates are not create equal.

• Is inbreeding affecting vital rate with strong
  influence on population growth rate?

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Some genetic markers used in wildlife biology1

• Protein electrophoresis
• Restriction fragment length polymorhphism (RFLP)
• DNA fingerprints
• Microsatellite markers
• DNA sequencing

Modern techniques greatly aided by polymerase
chain reaction (PCR) process for amplifying small
samples of DNA.
1See Mills Text (Chapter 3) for descriptions