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Project Work Plan

Department of Interior USGS GE PES
Fiscal Year 2014 Study Work Plan

TITLE: Estimating abundance of the Cape Sable Seaside Sparrow and other species of concern in south Florida
Principle Investigator CONTACT INFORMATION: USGS Southeast Ecological Science Center, 7920 NW 71st Street, Gainesville, Florida 32653, USA; Email: bob_dorazio@usgs.gov; ph: 352-264-3476; FAX: 352-378-4956

STATEMENT OF PROBLEM: The Cape Sable Seaside Sparrow (CSSS) is an endangered bird whose reproductive success depends in large part on how water in the Everglades is managed. Water levels during the CSSS breeding season must be maintained at low level to avoid flooding the nests. At other times, water levels must be maintained to promote growth of the plant communities these birds prefer. Everglades restoration planners require robust and quantitative information on the changing abundance of various subpopulations of the CSSS, and how these changes have been influenced as a result of variable hydrologic conditions. Annual surveys of the CSSS have taken place since the early 1990s. During this time, significant decreases in the bird counts of a few of the subpopulations have been recorded, suggesting a decline in CSSS abundance. However, past attempts to quantify detection probability during these surveys were extremely limited. Moreover, there have been no attempts to determine how bird detection probability during these surveys changed with environmental covariates such as habitat type or water levels. As such, estimates of CSSS abundance based on the annual record of bird counts may be subject to considerable error or bias. This lack of confidence in CSSS population estimates is hindering progress on Everglades restoration planning.


Data analyses will be conducted by developing probability-based models of latent ecological state variables and conditional models of observable quantities that depend on those state variables. Either classical or Bayesian modes of inference will be used, as needed. All models will be implemented using the R programming language.

WORK PLAN: Oct. 2013-Sept. 2014

Task 1: Review CSSS bird count data provided by NPS and methods for estimating abundance.

Task 2: Using model simulations compare historic abundance estimates based on protocols employed by CSSS field biologists with abundance estimates that would have been provided utilizing protocols designed to quantify detection probability and influence of environmental covariates.

Task 3: In interagency meetings and at professional conferences, promote and describe results of novel applications of abundance and occupancy models that incorporate information on effects of environmental covariates on detection probability towards other Everglades restoration wildlife indicators, endangered species, or species of management concern.

Task 4: In consultation with NPS and FWS, assist in the formulation of new survey designs, survey protocols, and population models for the CSSS subpopulations in the Everglades. Provide recommendations for utilizing survey data and model results in assessments of past changes in hydrology and in the evaluation of proposed restoration plans.


  1. CSSS data analysis and modeling results
    1. Preliminary Work Completed:
      Reviewed CSSS literature and analyzed duplicated point counts from surveys in 2000. Analysis revealed effect of water level on abundance of sparrows (higher water levels corresponded to lower abundances) and effect of vegetation on detectability of sparrows.
  2. Presentation(s) in interagency forums responsible for Everglades management and restoration
    1. Preliminary Work Completed:
      Presented "New approaches for estimating the spatial distribution and abundance of a species" to Joint Meeting of Working Group and Science Coordination Group in April 2014. Presentation included a historical summary of CSSS data, a statistical analysis of double-observer counts from a simulated population of CSSS, recommendations for improving the existing CSSS monitoring program, and list of ways that USGS can assist and improve assessments of Everglades restoration efforts.
  3. Development and review of new survey designs, protocols, and population modeling efforts in consultation with FWS, NPS and other south Florida natural resource agencies
  4. Peer-reviewed articles and/or conference proceedings

RELEVANCE AND BENEFITS: The project addresses important concerns identified by the USGS's Priority Ecosystems Science (PES) Greater Everglades study unit by providing sound, relevant and timely information pertinent for the restoration, preservation, and protection of the South Florida ecosystem (see: http://access.usgs.gov/about.html), including threatened and endangered species such as the CSSS. The provided information is expected to address the science needs of Department of the Interior agencies active in Everglades restoration.

COMMUNICATION PLAN, TECHNOLOGY AND INFORMATION TRANSFER: The information and results of this project will be openly available in the form of peer reviewed publications and presentation material.

COOPERATORS AND PARTNERS: The USGS's Greater Everglades Priority Ecosystems Science program is funding this project.

Robert Dorazio is a Research Statistician at the U.S. Geological Survey's Southeast Ecological Science Center. He also holds a Courtesy Associate Professorship in the Department of Statistics at the University of Florida. His research is motivated primarily by statistical inference problems that arise in the general areas of population dynamics, community ecology, and conservation biology. In solving these problems he develops and applies novel sampling designs and novel statistical models in quantitative investigations of natural populations or communities of animals (including imperiled or declining species). He is also interested in developing the theory and practice of adaptive decision making in problems of natural resource management.

FACILITIES, EQUIPMENT, AND STUDY AREAS: Office will be provided by the Southeast Ecological Science Center.


JOB HAZARD ANALYSES (JHA): Office Work, Travel

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