Reading Assignments

(to be read before lecture)

Lecture 2:

• Pages 6-25 in Burnham, K. P., D. R. Anderson, G. C. White, C. Brownie, and K. H. Pollock. 1987. Design and analysis methods for fish survival experiments based on release-recapture. Am. Fish. Soc. Monogr. 5:1-437.
• Chapters 1 and 2 and the Glossary in White, G. C., D. R. Anderson, K. P. Burnham, and D. L. Otis. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos Nat. Lab. Report LA-8787-NERP, Los Alamos, NM. 235pp.

Lecture 3:

• Chapter 1 of Brownie, C., D. R. Anderson, K. P. Burnham, and D. S. Robson. 1985. Statistical inference from band recovery data — a handbook, 2nd ed. U. S. Fish and Wildl. Serv. Res. Publ. 156, Washington, D. C. 305pp.
• Study a book on Sampling to augment the class material
• Find your linear algebra book and review material on multiplication of vectors and matrices

Lecture 4:

• Scan Chapter 9 of Brownie, C., D. R. Anderson, K. P. Burnham, and D. S. Robson. 1985. Statistical inference from band recovery data — a handbook, 2nd ed. U. S. Fish and Wildl. Serv. Res. Publ. 156, Washington, D. C. 305pp.
• Snoop around Appendix C of Brownie, C., D. R. Anderson, K. P. Burnham, and D. S. Robson. 1985. Statistical inference from band recovery data — a handbook, 2nd ed. U. S. Fish and Wildl. Serv. Res. Publ. 156, Washington, D. C. 305pp.
• Scan a book on applied probability to gain familiarity with the binomial and multinomial distributions
• Study Chapter 1 of Burnham, K. P., D. R. Anderson, G. C. White, C. Brownie, and K. H. Pollock. 1987. Design and analysis methods for fish survival experiments based on release-recapture. Am. Fish. Soc. Monogr. 5:1-437.
• Find your calculus book and review derivatives for log and exponential functions
• Come to class with some questions!

Lecture 5:

• Continue scanning Brownie, C., D. R. Anderson, K. P. Burnham, and D. S. Robson. 1985. Statistical inference from band recovery data — a handbook, 2nd ed. U. S. Fish and Wildl. Serv. Res. Publ. 156, Washington, D. C. 305pp.
• Goodness-of-fit of Product Multinomial Models
• Be certain you understand the binomial and multinomial probability functions, likelihoods and log-likelihoods

Lecture 6:

• Program MARK: Survival Estimation from Populations of Marked Animals — Gary C. White and Kenneth P. Burnham
• First Steps with Program MARK: Linear Models — Evan Cooch
• Be aware of “Program MARK: First Steps” by Evan Cooch and Gary C. White.

Lecture 7:

• Section on design matrices and computing the mean of a set of parameters from Advanced Features of Program MARK — Gary C. White, Kenneth P. Burnham, and David R. Anderson
• First Steps with Program MARK: Linear Models — Evan Cooch
• Two good references on likelihood methods:
  Azzalini, A. 1996. Statistical inference based on the likelihood. Chapman and Hall.
  Royall, R. M. 1997. Statistical evidence: a likelihood paradigm. Chapman and Hall.

Lecture 8:

• Lebreton, J.-D., K.P. Burnham, J. Clobert, and D.R. Anderson. 1992. Modeling survival and testing biological hypotheses using marked animals: case studies and recent advances. Ecol. Monogr. 62:67-118.
• Models Versus Full Reality (in the “Additional Reading” section)
• Keep working to understand the concept of a design matrix
• Study the figures and model naming conventions of various models in lecture6; this will help understand what the (sub)model is achieving (a picture is worth a 1000 words-type of thing).
• Start to review old mid-term exams to understand the type of questions to expect
• Keep reading and re-reading materials; as your understanding of the subjects
  increases, you can better understand points that were unclear on first reading.

Lecture 9:

• Lebreton, J.-D., K.P. Burnham, J. Clobert, and D.R. Anderson. 1992. Modeling survival and testing biological hypotheses using marked animals: case studies and recent advances. Ecol. Monogr. 62:67-118.
• The Set of Candidate Models (in the “Additional Reading” section)
• Goodness-of-fit of Product Multinomial Models (in the “Additional Reading” section)
• Advanced Features of Program MARK — Gary C. White, Kenneth P. Burnham, and David R. Anderson
• White, G. C.  2002.  Discussant: The Use of Auxiliary Variables in Capture-Recapture Modeling: An Overview.  Journal of Applied Statistics 29(1-4):103-106.
• Anderson, D. R., K. P. Burnham, and G. C. White. 1994. AIC model selection in overdispersed capture-recapture data. Ecology 75:1780-1793.

Lecture 10:

• Jointly Analyzing Live and Dead Encounters using MARK — Richard J. Barker and Gary C. White
• Szymczak, M.R. and Rexstad, E.A. 1991.   Harvest distribution and survival of a gadwall population.  Journal of Wildlife Management: 55:592-600.
• Pradel, R. 1996. Utilization of capture-mark-recapture for the study of recruitment and population growth rate.  Biometrics 52:703-709.
• Nichols, J. D., and J. E. Hines. 2002. Approaches for the direct estimation of lambda, and demographic contributions to lambda, using capture-recapture data. Journal of Applied Statistics 29(1-4):539-568.
• Hines, J. E., and J. D. Nichols. 2002. Investigations of potential bias in the estimation of lambda using Pradel’s (1996) model for capture-recapture data. Journal of Applied Statistics 29(1-4):573-587.

Lecture 11:

• Scan Parts 1,2,4,6,7, and 9 (software) of  Burnham, K. P., D. R. Anderson, G. C. White, C. Brownie, and K. H. Pollock. 1987. Design and analysis methods for fish survival experiments based on release-recapture. Am. Fish. Soc. Monogr. 5:1-437.

Lecture 12:

• Data Dredging — Two Examples (in the “Additional Reading” section)
• Review

Lecture 13:

• Midterm I

Lecture 14:

• Exploring Ecological Relationships in Survival and Estimating Rates of Population Change Using Program MARK — Alan B. Franklin
• Pollock, K. H. 2002. The use of auxiliary variables in capture-recapture modelling: an overview. Journal of Applied Statistics 29(1-4):85-102.

Lecture 15:

•  White, G. C., D. R. Anderson, K. P. Burnham, and D. L. Otis. 1982.  Capture-recapture and removal methods for sampling closed populations. Los Alamos Nat. Lab. Report LA-8787-NERP, Los Alamos, NM. 235pp.

Optional, concerning DNA mark-recapture

• Lukacs, P. M., and K. P. Burnham. 2005. Estimating population size from DNA-based closed capture-recapture data incorporating genotyping error. Journal of Wildlife Management 69:396-403.
• Lukacs, P. M., and K. P. Burnham. 2005. Review of capture-recapture methods applicable to noninvasive genetic sampling. Molecular Ecology 14:3909-3919.

Lecture 16:

• White, G. C., D. R. Anderson, K. P. Burnham, and D. L. Otis. 1982.  Capture-recapture and removal methods for sampling closed populations. Los Alamos Nat. Lab. Report LA-8787-NERP, Los Alamos, NM. 235pp.
• White, G. C.  2002.  Discussant: The Use of Auxiliary Variables in Capture-Recapture Modeling: An Overview.  Journal of Applied Statistics 29(1-4):103-106.

Optional, concerning a more detailed discussion of multimodel inference

• Burnham, K. P., and D. R. Anderson. 2004. Multimodel inference – understanding AIC and BIC in model selection. Sociological Methods & Research 33:261-304.

Lecture 17:

• The Robust Design for Capture-Recapture Studies: Analysis using Program MARK — William L. Kendall
• Lebreton, J.-D., and R. Pradel.  2002.  Multistate recapture models: modelling incomplete individual histories.  Journal of Applied Statistics 29(1-4):353-369.

Lecture 18:

• Burnham, K. P. and G. C. White.  2002.  Evaluation of some random effects methodology applicable to bird ringing data.  Journal of Applied Statistics 29(1-4):245-264.
• Franklin, A. B., D. R. Anderson, and K. P. Burnham.  2002.  Estimation of long-term trends and variation in avian survival probabilities using random effects models.  Journal of Applied Statistics 29(1-4):267-287.

Lecture 19:

 

• Review

 

Lecture 20:

• Midterm II

Lecture 21:

Lecture 22:

Lecture 23:

• Chapters 1, 2, 4, and 7 in Buckland, S.T., D.R. Anderson, K.P. Burnham, and J.L. Laake. 1993. Distance sampling: estimating abundance of biological populations. Chapman and Hall, New York, N.Y. 446 pp.

Lecture 24:

• Chapters 1, 2, 4, and 7 in Buckland, S.T., D.R. Anderson, K.P. Burnham, and J.L. Laake. 1993. Distance sampling: estimating abundance of biological populations. Chapman and Hall, New York, N.Y. 446 pp.

Lecture 25:

• Scan Chapters 3 and 8 in Buckland, S.T., D.R. Anderson, K.P. Burnham, and J.L. Laake. 1993. Distance sampling: estimating abundance of biological populations. Chapman and Hall, New York, N.Y. 446 pp.

Lecture 26:

• Point Transects, Chapters 1-3, 5, some in 7 from Buckland, S.T., D.R. Anderson, K.P. Burnham, and J.L. Laake. 1993. Distance sampling: estimating abundance of biological populations. Chapman and Hall, New York, N.Y. 446 pp.
• Anderson, D. R., K. P. Burnham, G. C. White, and D. L. Otis.  1983.  Density estimation of small mammal populations using a trapping web and distance sampling methods.  Ecology 64:674-680.

Lecture 27:

• Bootstrap, Review pages 94-96 in Chapter 3, pages 119-120 in Chapter 4, and pages 155-158 in Chapter 5 from Buckland, S.T., D.R. Anderson, K.P. Burnham, and J.L. Laake. 1993. Distance sampling: estimating abundance of biological populations. Chapman and Hall, New York, N.Y. 446 pp.

Lecture 28:

• Review

Lecture 29:

• Final Exam

Other Interesting and Relevant Papers and Books

• Lukacs, P. M., V. J. Dreitz, F. L. Knopf, and K. P. Burnham. 2004. Estimating survival probabilities of unmarked dependent young when detection is imperfect. Condor 106:926–931.
• Thompson, W. L. (ed.).  2004.  Sampling Rare or Elusive Species.  Island Press, Washington, D.C., USA.  429pp.
• Euring 2003.  2004.  Entire volume of Animal Biodiversity and Conservation 27.1:1-572.