ECOLOGY AND MANAGEMENT
OF SMALL POPULATIONS
L. Scott Mills1, J. Michael Scott2, Katherine M.
Strickler2, and Stanley A. Temple3
1Wildlife
Biology Program, University of Montana
2Department of Fisheries and Wildlife, University of Idaho
3Department of Forest and Wildlife Ecology,
University of Wisconsin
What is a Small Population?
► Small
population size is a relative concept
 Based on comparisons with historical population sizes,
conspecifics, management standards
► Real
issue is not absolute size of the population, but
its vulnerability to dropping below some threshold:
 Extinction risk for imperiled species
 Minimum harvestable levels for exploited species
Categorization of Small Populations
International Union for Conservation of Nature (IUCN) Red List
criteria for defining small populations
Red list category
Very small population
Small population and declining
Critically endangered
<50 mature individuals
<250 mature individuals,
population declining
Endangered
<250 mature individuals
<2,500 mature individuals,
population declining
Vulnerable
<1,000 mature individuals
<10,000 mature individuals,
population declining
Categorization of Small Populations
Natural Heritage Program conservation status rank definitions
Rank
Definition
1
Critically imperiled. Typically 5 or fewer occurrences or 1,000 or fewer
individuals
2
Imperiled. Typically 6 to 20 occurrences or 1,000 to 3,000 individuals
3
Vulnerable. Rare; typically 21 to 100 occurrences or 3,000 to 10,000
individuals
4
Apparently secure. Uncommon, but not rare; some cause for long-term
concern; usually more than 100 occurrences and 10,000 individuals
5
Secure. Common; widespread and abundant
Naturally Small vs. Declining
Populations
►
Naturally small populations
 Geographically constrained (islands, naturally isolated
patches)
 Life-history characteristics associated with small
populations (trophic level, body size, home range size)
 Naturally stable at small sizes in absence of threats
►
Declining populations
 Restricted to small, isolated populations following a
reduction in population size
 Increased risk of extinction
 Management may be needed to reduce threats
Legal Mandates for Managing Small
Populations
►
Endangered Species Act (United States)
 Provides for protection and recovery of species
 USFWS and NOAA Fisheries responsible for listing or delisting
recommendations
►
Species at Risk Act (Canada)
 Listing recommendations by Committee on the Status of Endangered
Wildlife in Canada (COSEWIC)
►
CITES (Convention on International Trade in Endangered Species)
 Restricts international transportation and trade of listed species
►
53 federal statutes in the United States
 Provide for conservation of species and habitats
Ecological Characters Predicting
Risk:
► Smaller
populations
► Restricted
range / narrow endemics
► High
variance in population growth rate (high
environmental stochasticity, var(r) > 2r)
► Large
body size
The Extinction Vortex:
Stochastic and
Deterministic Drivers
In Chapter
From Mills (2007) after
Soule and Mills (1998)
Demographic Stochasticity
(caribou example: true survival is 0.74)
(from Mills 2007)
Genetic
Stochasticity
(As populations become
small & isolated genetic
drift causes random loss
of alleles and increase in
homozygosity)
From:
Mills and Tallmon 2009
Wildlife Population Risk Assessment
-We are often concerned with populations that are small
or declining (or both)
-We’ve gone over various ways to measure abundance,
population dynamics, survival, reproduction, etc.
-But what do we do with this information?
-How do we quantify:
a) a population’s viability
b) What to do! (the impact of different
management options)
Population Viability Analysis
Components of a PVA
1. Viability: Not extinct , not below quasi-extinction threshold
2. Time: Predictions are less reliable farther into the future (like the
weather!) So we aim to make short-term predictions couched within
long-term goals.
Probability of quasi-extinction
3. Likelihood: Embrace uncertainty! Persistence is measured as a
probability, often displayed as a cumulative distribution function.
Johnson Creek:
1.0
Lacy Creek (LS):
0.8
Squaw Creek (LS):
0.6
Rape Creek:
0.4
0.2
Stone Creek:
0
0
10
20
30
40
50
60
Year
70
80
90
100
PVA
► Allows
comparison of a range of options
► Strong
biological basis (all that stuff on pop.
growth, survival, fecundity, environmental
stochasticity, genetics, etc.)
► Social
components (how secure do we want the
population to be? What are management goals?)
Types of PVAs
1. Count-based (unstructured population): uses timeseries of abundance or density
2. Demographically explicit PVA (structured population):
uses matrix models, individual-based simulations,
sensitivity analysis, etc.
-Metapopulation (structured, unstructured, or presence/absence)
-Spatially-explicit (powerful but incredibly data hungry)
Time-series PVA
Time-series PVA based on gray whales
off the coast of California. (a)
Abundance estimates over time, with SE
bars representing sample variance (data
from Rugh et al. 2005; see also Wade
2002a). (b) The cumulative distribution
function (and its 90% confidence
interval) of the density-independent
quasi-extinction probability of decline
from the 2001 abundance of 18,178 to a
quasi-extinction threshold of 10,000 or
fewer whales. © Quasi-extinction
probability, as a (b) except that a logistic
growth model of negative density
dependence is assumed.
From Mills 2007
Demographically Explicit PVA
Incorporates
Age structure
Age-specific vital rates
Can also include:
Sex-specific vital rates
Variance and covariance in vital rates
Density dependence
Inbreeding depression
Environmental stochasticity
Demographic stochasticity
Animal behavior
Multiple populations
Demographically Explicit PVA
Can investigate specific mechanisms potentially
affecting viability.
Can compare the effects of alternative management
options.
But data hungry!
Other Approaches to Assess Viability
► Expert opinion
► Rules-of-thumb
 E.g., IUCN Red List
 25,000 species
worldwide assessed
for conservation status!
The IUCN population assessment procedures
(Gärdenfors et al. 2001, IUCN 2001).
Closing Thoughts About PVA
Using PVA, we can be explicit about threats to populations, can
get non-intuitive results, and can identify gaps in our
knowledge
1. Remain aware of data quantity and quality (“garbage in,
garbage out”)
2. View viability metrics as relative, not absolute estimates of
when a population will go extinct
3. Consider a range of possibilities whenever there is doubt
about a process, functional relationship, or measured
parameter (embrace uncertainty)
Closing Thoughts About PVA
4. Don’t try to project too far into the future—
relatively short predictions are more likely to fall
into the realm of reality and work within political
and economic constraints
5. Keep it simple, but keep in mind the things you left
out
6. Consider PVAs a work in progress, not the final
work
Management of Small Populations
► Must
address proximate and ultimate causes of
population declines
 Improvement of birth and death rates
 Population augmentation
 Habitat protection
 Reduction or removal of other threat factors
(e.g., harvest, invasive species, contaminants)
► Monitoring
Conservation-Reliant Species
►
►
For many endangered species, full recovery is not attainable
Recovery should be viewed as a continuum
Conservation-Reliant Species
►
“Conservation-reliant species” can maintain self-sustaining
populations with ongoing management
►
Ongoing management ensures that necessary conservation actions
will continue following delisting
►
Cooperative relationships between state governments, federal
agencies, and private landowners will be required
Special Considerations for Managing
Listed Species
► Permits
are required for any hands-on management or
research
► Take
permits, listing or delisting decisions, and critical
habitat designation are subject to public review
► Management
programs for listed species tend to receive
intense public scrutiny
SUMMARY
Most effective recovery programs incorporate field data
and and quantitative tools.
Each species and situation presents unique challenges.
No one-size-fits-all approach.
Modeling framework (PVA) can help assess management
scenarios and account for uncertainty.
Management of small populations needs to begin early.