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Evaluation and Improvement in Desert Bighorn Sheep Population Estimates

Post Date

February 4th 2010

Application Due Date

March 4th 2010

Funding Opportunity Number


CFDA Number(s)


Funding Instrument Type(s)

Cooperative Agreement

Funding Activity Categories

Natural Resources

Number of Awards


Eligibility Categories

State Governments
Special District Governments
Public and State Controlled Institutions of Higher Education
Federally Recognized Native American Tribal Governments
Non-Federally Recognized Native American Tribal Organizations
Non-Profits With 501 (c) (3) Status With The IRS (Except Higher Education Institutions)
Non-Profits Without 501 (c) (3) Status With The IRS (Except Higher Education Institutions)
Private Institutions of Higher Education
For-Profit Organizations (Except Small Businesses)
Small Businesses

Eligible applicants include nonprofit organizations, public and private educational organizations, federal, state, local and tribal governments and organizations, foreign governments, consulting firms, research firms and individual companies.


  • Estimated Total Funding:


  • Award Range:

    $10000 - $15000

Grant Description

The United States Fish and Wildlife Service (USFWS) and the Arizona Game and Fish Department (AZGFD) count and estimate desert bighorn sheep (DBS) populations on Federal and State owned lands. A variety of methods have been used since 1981, founded on a two-helicopter double-count, simultaneous double-count, and mark-resight methodology (Seber 1973, Furlow et al. 1981, Miller et al. 1985, Samuel et al. 1987, Lee et al. 1992). Presently, a "group-size-density-estimator" method is in use and has been consistently conducted since 1997. The areas surveyed and the amount of effort in each survey is standardized. Radio-collared sheep were used to evaluate sighting rates for these surveys (Hervert et al. 1998). Over recent years, both agencies have dedicated much effort to address the level of variation associated with such survey data. One problematic issue is that the average group size of the marked animals seen on surveys can be significantly larger than the average group size of marked animals missed on surveys. This difference can be explained by the observed probabilities for discrete group sizes. For example, observers miss more small groups than large groups. This group size bias can greatly influence the accuracy of the population estimate. This bias can generate estimates with wide confidence intervals. This in turn challenges managers’ abilities to accurately determine population declines or increases in a statistically defensible framework. Presently, survey data are used for (but not limited to) evaluating population trends, regional meta-analyses, setting harvest objectives, quantifying lamb/ewe ratios, and lambda. The successful applicant will need to understand the connection between survey methods and the management decisions made from the survey data now, and the population based information we hope to gain from survey data. Certainly, the biometrician must know what the survey results are used for in order to help tune the technique. Such discussions will be led by AZGFD. Deliverables 1) Ensure that statistical calculations in present methods are correct. 2) Irrespective of the outcome of #1, we seek an evaluation to improve survey methodology and data analysis to increase survey accuracy. This requires: A) An investigation that quantifies and reports the relationship between count accuracy and effort, and presents a range of options informing agencies the tradeoffs between count accuracy and effort. B) Provide information describing changes we can easily make, versus changes that would require significant retooling and investment, (i.e. 'easy', low-hanging fruit changes vs. expensive time consuming changes) and expected accuracy from given methods. C) For example, what improvements could be conducted to get population estimates within 25%, 15% and 5% of the true population size? What increases in effort or costs would this or would this not incur? 3) These agencies seek a robust method applicable to estimating desert bighorn sheep numbers range-wide. Consistency in methods among disparate populations when aggregated makes range-wide predictions more robust. Achieving this objective entails knowing tradeoffs between the available options to increase survey accuracy, effort and costs. Granted, some areas may warrant different survey efforts than others. That in itself is fine, as long as estimates gained from disparate methods correspond and scale 4) Examine historic count data and methods to determine if back calculations can be conducted to provide more accurate population estimates and more accurately reflect counts gained from present methods. If such analyses are appropriate, then perform those calculations. 5) Can biometric modeling allow us to project populations for the next year? If we could generate a robust method to forecast populations, it could mean scaling back surveys to every other year or every three years at a substantial cost savings. It would also allow us to set hunt permits more accurately. Scaling back surveys would cause a decrease in our abilities to quantify certain population parameters. We would need to know these tradeoffs. Results of this project are highly relevant to enumerating sheep across Federal and State lands, plus other desert bighorn sheep populations range-wide. Indeed, counts generated from consistent methods in disparate locations enables us to better compare and contrast populations, and evaluate range-wide trends. Overall, this is an exploration seeking to improve how we enumerate animals notoriously difficult to census. Results of this work enable us to evaluate what we do and determine which adjustments to current protocols may make most sense considering the nature of their improvements and costs to get them. Herein we are not proposing any changes in survey methodology. Rather, we’re seeking an objective evaluation of the method to help improve it. Project results will better empower both agencies to balance needs with improvements and costs, while also providing more information to appropriately articulate the challenges and limitations inherent in these important surveys.

Contact Information

  • Agency


  • Office:


  • Agency Contact:

    Dr. Grant Harris
    fax 505-248-6874

  • Agency Mailing Address:

  • Agency Email Address:

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