Methods to Collect

Required Data to

Develop Rigorous

Population

Viability Analysis

(PVA) Models

By: Gary C. White

Department of Fishery and

Wildlife Biology 

Colorado State University

The ninth in a series of 13,

Session 3

Background

Population viability analysis

(PVA) examines the question

of whether a biological population of a given size will

persist (remain viable) for

some specified time period.

To develop useful estimates

of population viability, stochastic population models

must be developed that

incorporate demographic,

temporal, and individual variation. The lack of individual

heterogeneity in previous

population viability analyses

has resulted in underestimates of persistence, making

the conclusions overly pessimistic. Additionally, spatial

and genetic variation may be

required, depending on the

population being modeled

and the time frame of the

analysis. Estimates of these

variance components must

be constructed by removing

the sampling variation inherent in estimates of population

parameters. Most previous

population viability analyses

have not separated sampling

variation from process variation in the parameter

estimates, so they underestimate population persistence.

Further, the uncertainty

(sampling variance) of parameter estimates must be

incorporated into estimates

and confidence intervals of

persistence if valid inferences are to be made back

to the population under

consideration.

Discussion

Marked animals have been

widely used to estimate population size, survival rate, and

recruitment in biological

populations. Wild horse populations seem particularly

suited to methods of analysis

based on marked animals

because of the individual

heterogeneity in appearance

makes many individuals

uniquely identifiable, so

that capture to apply marks

is not required. In addition,

DNA techniques provide

alternative methods to

obtain data on identifiable

individuals. Estimation

methods based on the

Cormack-Jolly-Seber model

available in Program MARK

(White and Burnham,

1999, in press) seem wellsuited to estimation of wild

horse survival rates from

inferences on identifiable

individuals. Procedures to

separate sampling variation

from process variation are

already available in the 

program. Recruitment to

reproductive age can be

estimated from age ratios

estimated by population surveys. Population size can be

estimated from ratios of

uniquely identifiable individuals to unidentifiable

animals during the same

surveys with estimators

provided in Program

NOREMARK (White 1996).

Thus the techniques required

to obtain the data to develop

rigorous PVA models for wild

horse populations are available

and manageable. However, the

cost of information is always

high, so the real question is

whether this information is

considered worth the expense

by policy makers, and ultimately, the voting public.

Conclusion

Rigorous statistical methods

and associated field data collection procedures are available

to estimate the necessary parameters to model defensibly

wild horse populations. To

obtain defensible models, a

RESOURCE NOTES

NO. 31 DATE 07/27/00

Range

Wild Horse andBurro Program
commitment to consistent

and long-term data collection and analysis must be

made by the agency.

Contact

Gary C. White, PhD.

Department of Fishery and

Wildlife Biology

211B J.V.K. Wager

Colorado State University

Fort Collins, CO 80523

phone 970-491-6678

fax: 970-491-5091

email:

gwhite@cnr.colostate.edu

For further reading:

White, G. C. 1996.

NOREMARK: population

estimation from mark

resighting surveys. Wildlife

Society Bulletin 24:50-52.

White, G.C. 1999. 

(a) Modeling Population

Dynamics. pp. 84-107 in S.

Demarais and P. Krausman,

eds. Ecology and

Management of Large

Mammals in North America.

White, G.C. 1999. 

(b) Population viability

analysis: data requirements

and essential analysis. pp.

288-327. in L. Boitani and T.

K. Fuller, editors. Research

techniques in animal ecology.

Columbia University Press,

New York, New York, USA. 

White, G. C., and K. P.

Burnham. 1999. Program

MARK: survival estimation

from populations of marked

animals. Bird Study. In Press.

Software and more information are available via

WWW at:

http://www.cnr.colostate.edu/

~gwhite

Range

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