James Hines
Jim Hines is a computer scientist, working with USGS and non-agency biologists developing methods and computer software for estimation of ecological parameters. He also maintains a web-server used to communicate results of the North American Breeding Bird Survey as well as software written by current and former EESC scientists.
Jim Hines started with the USFWS in 1977 as a part-time computer clerk. After obtaining a BS in Math, he became a full-time computer programmer, then computer specialist and computer scientist. He is co-author on 2 books,
Professional Experience
1977-present USFWS, NBS, USGS - Computer clerk, programmer, specialist, scientist.
Education and Certifications
Hon Dsc. University of Florda, 2023
B.S. University of Maryland, Mathematics, 1979.
Honors and Awards
2016 - Biometrics Working Group Special Recognition Award
2015 - U.S. Geological Survey Distinguished Service Award
2012 - U.S. Geological Survey Meritorious Service Award
2012 - The Wildlife Society's Wildlife Publication Award for Book
1991 - The Wildlife Society's Wildlife Publication Award for Monograph
Science and Products
Additional comments on the assumption of homogenous survival rates in modern bird banding estimation models
Breeding-ground habitat conditions and the survival of mallards
Of mice and mallards: tests of the compensatory mortality hypothesis in vertebrate populations
The relationship between harvest rates and survival rates of mallards: a straightforward approach with randomly-partitioned data sets
Remarks on the use of mark-recapture methodology in estimating avian population size
Estimating nesting success: A model, estimators, and a field example
Fifty-sixth Christmas Bird Count. 147. Southern Dorchester County, Md
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Additional comments on the assumption of homogenous survival rates in modern bird banding estimation models
We examined the problem of heterogeneous survival and recovery rates in bird banding estimation models. We suggest that positively correlated subgroup survival and recovery probabilities may result from winter banding operations and that this situation will produce positively biased survival rate estimates. The magnitude of the survival estimate bias depends on the proportion of the population inAuthorsJ. D. Nichols, S.L. Stokes, J. E. Hines, M.J. ConroyBreeding-ground habitat conditions and the survival of mallards
The relationship between habitat conditions in prairie breeding areas of North America and mallard (Anas platyrhynchos) survival rates was investigated. Annual survival-rate estimates for mallards generally were higher during years of high May pond numbers and low mallards-per-pond ratios than during years of low pond numbers and high ratios. This tendency was most pronounced among males. TheseAuthorsJ. D. Nichols, R.S. Pospahala, J. E. HinesOf mice and mallards: tests of the compensatory mortality hypothesis in vertebrate populations
No abstract available.AuthorsJ. D. Nichols, J. E. HinesThe relationship between harvest rates and survival rates of mallards: a straightforward approach with randomly-partitioned data sets
No abstract available.AuthorsJ. E. Hines, J. D. NicholsRemarks on the use of mark-recapture methodology in estimating avian population size
No abstract available.AuthorsJ. D. Nichols, B.R. Noon, S.L. Stokes, J. E. HinesEstimating nesting success: A model, estimators, and a field example
No abstract available.AuthorsGary L. Hensler, J. D. Nichols, R.A. Coon, H.F. Percival, J. E. HinesFifty-sixth Christmas Bird Count. 147. Southern Dorchester County, Md
Summary and Recommendations: We suggest that managers are approaching the limits of their ability to improve waterfowl harvest management, primarily because the information needed to make better decisions is being sacrificed by the current approach to setting regulations. We propose an actively adaptive management strategy in which regulatory decisions play a dominant role in reducing uncertaintAuthorsF.A. Johnson, B.K. Williams, J. D. Nichols, J. E. Hines, W. L. Kendall, G.W. Smith, David F. Caithamer - Web Tools
- Software
Filter Total Items: 35
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