# Sample Survey Strategies

Chapter
Part of the Springer Series on Environmental Management book series (SSEM)

The goal of wildlife ecology research is to learn about wildlife populations and their use of habitats. The objective of this chapter is to provide a description of the fundamentals of sampling for wildlife and other ecological studies. We discuss a majority of sampling issues from the perspective of design-based observational studies where empirical data are collected according to a specific study design. We end the chapter with a discussion of several common model-based sampling approaches that combine collection of new data with parameters from the literature or data from similar studies by way of a theoretical mathematical/statistical model. This chapter draws upon and summarizes topics from several books on applied statistical sampling and wildlife monitoring and we would encourage interested readers to see Thompson and Seber (1996), Thompson (2002b), Thompson et al. (1998), Cochran (1977), and Williams et al. (2002).

Typically, the availability of resources is limited in wildlife studies, so researchers are unable to carry out a census of a population of plants or animals. Even in the case of fixed organisms (e.g., plants), the amount of data may make it impossible to collect and process all relevant information within the available time. Other methods of data collection may be destructive, making measurements on all individuals in the population infeasible. Thus, in most cases wildlife ecologists must study a subset of the population and use information collected from that subset to make statements about the population as a whole. This subset under study is called a sample and is the focus of this section. We again note that there is a significant difference between a statistical population and a biological population (Chap. 1).

## Keywords

Simple Random Sample Line Transect Adaptive Sampling Resource Selection Aerial Survey

## References

1. Alldredge, J. R., D. L. Thomas, and L. McDonald. 1998. Survey and comparison of methods for study of resource selection. J. Agric. Biol. Environ. Stat. 3: 237–253.
2. Alpizar-Jara, R., and K. H. Pollock. 1996. A combination line transect and capture re-capture sampling model for multiple observers in aerial surveys. J. Environ. Stat. 3: 311–327.
3. Amstrup, S. C., T. L. McDonald, and B. F. J. Manly. 2005. Handbook of Capture–Recapture Analysis. Princeton University Press, Princeton.Google Scholar
4. Anderson, D. R. 2001. The need to get the basics right in wildlife field studies. Wildl. Soc. Bull. 29: 1294–1297.Google Scholar
5. Bart, J. and S. Earnst. 2002. Double sampling to estimate density and population trends in birds. Auk 119: 36–45.
6. Beavers, S. C., and F. L. Ramsey. 1998. Detectability analysis in transect surveys. J. Wildl. Manage. 62(3): 948–957.
7. Block, W. M., and L. A. Brennan. 1992. The habitat concept in ornithology: Theory and applications. Curr. Ornithol. 11: 35–91.Google Scholar
8. Borchers, D. L., S. T. Buckland, and W. Zucchini. 2002. Estimating Animal Abundance. Springer, Berlin Heidelberg New York.Google Scholar
9. Borgman, L. E., M. Taheri, and R. Hagan. 1984. Three-dimensional, frequency-domain simulations of geologic variables, in G. Verly, M. David, A. G. Journel, and A. Marechal, Eds. Geostatistics for Natural Resources Characterization, Part I. Reidel, Dordrecht.Google Scholar
10. Borgman, L. E., C. D. Miler, S. R. Signerini, and R. C. Faucette. 1994. Stochastic interpolation as a means to estimate oceanic fields. Atmos.-Ocean. 32(2): 395–419.Google Scholar
11. Bormann, F. H. 1953. The statistical efficiency of sample plot size and shape in forest ecology. Ecology 34: 474–487.
12. Brownie, C., J. E. Hines, J. D. Nichols, K. H. Pollock, and J. B. Hestbeck. 1993. Capture–recapture studies for multiple strata including non-Markovian transitions. Biometrics 49: 1173–1187.
13. Buckland, S. T. 1987. On the variable circular plot method of estimating animal density. Biometrics 43: 363–384.
14. Buckland, S. T., D. R. Anderson, K. P. Burnham, and J. L. Laake. 1993. Distance Sampling: Estimating Abundance of Biological Populations. Chapman and Hall, London.Google Scholar
15. Buckland, S. T., D. R. Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers, and L. Thomas. 2001. Introduction to Distance Sampling. Oxford University Press, Oxford.Google Scholar
16. Buckland, S. T., D. R. Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers, and L. Thomas. 2004. Advanced Distance Sampling. Oxford University Press, Oxford.Google Scholar
17. Burnham, K. P. 1993. A theory for combined analysis of ring recovery and recapture data, in J. D. Lebreton and P. M. North, Eds. Marked Individuals in the Study of Bird Population, pp. 199–214. Birkhäuser-Verlag, Basel, Switzerland.Google Scholar
18. Burnham, K. P., and W. S. Overton. 1978. Estimation of the size of a closed population when capture probabilities vary among animals. Bometrika 65: 625–633.
19. Burnham, K. P., D. R. Anderson, and J. L. Laake. 1980. Estimation of density from line transect sampling of biological populations. Wildl. Monogr. 72: 1–202.Google Scholar
20. Burnham, K. P., S. T. Buckland, J. L. Laake, D.L. Borchers, T. A. Marques, J. R. B. Bishop, and L. Thomas. 2004. In S. T. Buckland, D. R. Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers, and L. Thomas, Eds. Advanced Distance Sampling, pp. 307–392. Oxford University Press, Oxford.Google Scholar
21. Byth, K. 1982. On robust distance-based intensity estimators. Biometrics 38: 127–135.
22. Canfield, R. H. 1941. Application of the line intercept method in sampling range vegetation. J. Forest. 39: 388–394.Google Scholar
23. Caughley, G. 1977. Sampling in aerial survey. J. Wildl. Manage. 41: 605–615.
24. Caughley, G., and D. Grice. 1982. A correction factor for counting emus from the air and its application to counts in western Australia. Aust. Wildl. Res. 9: 253–259.
25. Chao, A. 1987. Estimating the population size for capture–recapture data with unequal catchability. Biometrics 43: 783–791.
26. Chao, A. 1988. Estimating animal abundance with capture frequency data. J. Wildl. Manage. 52: 295–300.
27. Chao, A. 1989. Estimating population size for sparse data in capture–recapture experiments. Biometrics 45: 427–438.
28. Christman, M. C. 2000. A review of quadrat-based sampling of rare, geographically clustered populations. J. Agric. Biol. Environ. Stat. 5: 168–201.
29. Cochran, W. G. 1977. Sampling Techniques, 3rd Edition. Wiley, New York.Google Scholar
30. Collier, B. A., S. S. Ditchkoff, J. B. Raglin, and J. M. Smith. 2007. Detection probability and sources of variation in white-tailed deer spotlight surveys. J. Wildl. Manage. 71: 277–281.
31. Conroy, M. J., J. R. Goldsberry, J. E. Hines, and D. B. Stotts. 1988. Evaluation of aerial transect surveys for wintering American black ducks. J. Wildl. Manage. 52: 694–703.
32. Cook, R. D., and J. O. Jacobson. 1979. A design for estimating visibility bias in aerial surveys. Biometrics 35: 735–742.
33. Cressie, N. A. C. 1991. Statistics for Spatial Data. Wiley, New York.Google Scholar
34. Darroch, J. N. 1958. The multiple recapture census: I. Estimation of a closed population. Biometrika 45: 343–359.Google Scholar
35. Dell, T. R., and J. L. Clutter. 1972. Ranked set sampling theory with order statistics background. Biometrics 28: 545–553.
36. Deutsch, C. V., and A. G. Journel. 1992. GSLIB Geostatistical Software Library and User’s Guide. Oxford University Press, New York.Google Scholar
37. Diggle, P. J. 1983. Statistical Analysis of Spatial Point Patterns. Academic, London.Google Scholar
38. Dinsmore, S. J., G. C. White, and F. L. Knopf. 2002. Advanced techniques for modeling avian nest survival. Ecology 83: 3476–3488.
39. Drummer, T. D. 1991. SIZETRAN: Analysis of size-biased line transect data. Wildl. Soc. Bull. 19(1): 117–118.Google Scholar
40. Drummer, T. D., and L. L. McDonald. 1987. Size bias in line transect sampling. Biometrics 43: 13–21.
41. Eberhardt, L. L. 1978. Transect methods for populations studies. J. Wildl. Manage. 42: 1–31.
42. Eberhardt, L. L., and M. A. Simmons. 1987. Calibrating population indices by double sampling. J. Wildl. Manage. 51: 665–675.
43. Erickson, W. P., T. L. McDonald, and R. Skinner. 1998. Habitat selection using GIS data: A case study. J. Agric. Biol. Environ. Stat. 3: 296–310.
44. Flowy, T. J., L. D. Mech, and M. E. Nelson. 1979. An improved method of censusing deer in deciduous–coniferous forests. J. Wildl. Manage. 43: 258–261.
45. Foreman. K. 1991. Survey Sampling Principles. Marcel Dekker, New York.Google Scholar
46. Fretwell, S. D., and H. L. Lucas. 1970. On territorial behavior and other factors influencing habitat distribution in birds. I. Acta Biotheoret. 19: 16–36.
47. Gaillard, J. M. 1988. Contribution a la Dynamique des Populations de Grands Mammiferes: l’Exemple du Chevreuil (Capreolus capreolus). Dissertation. Universite Lyon I, Villeurbanne, France.Google Scholar
48. Gasaway, W. C., S. D. DuBois, D. J. Reed, and S. J. Harbo. 1986. Estimating Moose Population Parameters from Aerial Surveys. Institute of Arctic Biology, Biological Papers of the University of Alaska, Fairbanks, AK 99775, No. 22.Google Scholar
49. Gilbert, R. O. 1987. Statistical Methods for Environmental Pollution Monitoring. Van Nostrand Reinhold, New York.Google Scholar
50. Gilbert, R. O., and J. C. Simpson. 1992. Statistical methods for evaluating the attainment of cleanup standards. Vol. 3, Based Standards for Soils and Solid Media. Prepared by Pacific Northwest Laboratory, Battelle Memorial Institute, Richland, WA, for U.S. Environmental Protection Agency under a Related Services Agreement with U.S. Department of Energy, Washington, DC. PNL-7409 Vol. 3, Rev. 1/UC-600.Google Scholar
51. Graham, A., and R. Bell. 1969. Factors influencing the countability of animals. East Afr. Agric. For. J. 34: 38–43.Google Scholar
52. Grosenbaugh, L. R. 1952. Plotless timber estimates–new, fast, easy. J. For. 50: 532–537.Google Scholar
53. Guenzel, R. J. 1997. Estimating Pronghorn Abundance Using Aerial Line Transect Sampling. Wyoming Game and Fish Department, Cheyenne, WY.Google Scholar
54. Hasel, A. A. 1938. Sampling error in timber surveys. J. Agric. Res. 57: 713–736.Google Scholar
55. Hendricks, W. A. 1956. The Mathematical Theory of Sampling. The Scarecrow Press, New Brunswick.Google Scholar
56. Hornocker, M. G. 1970. An analysis of mountain lion predation upon mule deor and elk in the Idaho Primitive Area. Wildl. Monogr. 21.Google Scholar
57. Horvitz, D. G., and D. J. Thompson. 1952. A generalization of sampling without replacement from a finite universe. J. Am. Stat. Assoc. 47: 663–685.
58. Hosmer Jr., D. W., and S. Lemeshow. 1999. Applied Survival Analysis. Wiley, New York.Google Scholar
59. Huggins, R. M. 1989. On the statistical analysis of capture experiments. Biometrika 76: 133–140.
60. Huggins, R. M. 1991. Some practical aspects of a conditional likelihood approach to capture experiments. Biometrics 47: 725–732.
61. Hurlbert, S. H. 1984. Pseudoreplication and the design of ecological field experiments. Ecol. Monogr. 54: 187–211.
62. Isaaks, E. H., and R. M. Srivastava. 1989. An Introduction to Applied Geostatistics, Oxford University Press, New York.Google Scholar
63. Johnson, D. H. 1980. The comparison of usage and availability measurements for evaluating resource preference. Ecology 61: 65–71.
64. Johnson, D. H., Ed. 1998. J. Agric. Biol. Environ. Stat. 3(3) Special Issue: Resource Selection Using Data from Geographical Information Systems (GIS).Google Scholar
65. Johnson, D. H. 2002. The importance of replication in wildlife research. J. Wildl. Manage. 66: 919–932.
66. Journel, A. G., and C. J. Huijbregts. 1978. Mining Geostatistics. Academic, London.Google Scholar
67. Kaiser, L. 1983. Unbiased estimation in line-intercept sampling. Biometrics 39: 965–976.
68. Kalamkar, R. J. 1932. Experimental error and the field plot technique with potatoes. J. Agric. Sci. 22: 373–383.
69. Kaplan, E. L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. J. Am. Stat. Assoc. 53: 457–481.
70. Kendall, W. L. 1999. Robustness of closed capture–recapture methods to violations of the closure assumption. Ecology 80: 2517–2525.Google Scholar
71. Kendall, W. L., and K. H. Pollock. 1992. The robust design in capture–recapture studies: A review and evaluation by Monte Carlo simulation, in D. R. McCullough, and R. H. Barrett, Eds. Wildlife 2001: Populations, pp. 31–43. Elsevier, London.Google Scholar
72. Kendall, W. L., J. D. Nichols, and J. E. Hines, 1997. Estimating temporary emigration using capture–recapture data with Pollock’s robust design. Ecology 78: 563–578.Google Scholar
73. Kern, J. W. 1997. Data analysis techniques for point prediction and estimation of spatial means. Technical Research Work Order Dan Goodman, Department of Biology, Montana State University, Bozeman, MT. Contract 290801.Google Scholar
74. Kery, M., J. A. Royle, and H. Schmid. 2005. Modeling avian abundance from replicated counts using binomial mixture models. Ecol. Appl. 15: 1450–1461.
75. Kleinbaum, D. G. 1996. Survival Analysis: A self-learning text. Springer, New York.Google Scholar
76. Krebs, C. J. 1989. Ecological Methodology. Harper Collins, New York.Google Scholar
77. Krebs, C. J. 1999. Ecological Methodology, 2nd Edition. Addison-Welsey, Menlo Park.Google Scholar
78. Krige, D. G. 1951. A Statistical Approach to Some Mine Valuation and Allied Problems at the Witwaterstrand. Unpublished Masters Thesis, University of Witwaterstrand.Google Scholar
79. Kuehl, R. O. 2000. Design of Experiments: Statistical Principles of Research Design and Analysis, 2nd Edition. Brooks/Cole, Pacific Grove.Google Scholar
80. Laake, J. L., K. P. Burnham, and D. R. Anderson. 1979. User’s Manual for Program TRANSECT, 26 pp. Utah State University Press, Logan, Utah.Google Scholar
81. Laake, J. L., S. T. Buckland, D. R. Anderson, and K. P. Burnham. 1993. DISTANCE User’s Guide. Version 2.0. Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University, Fort Collins, CO.Google Scholar
82. Lancia, R. A., W. L. Kendall, K. H. Pollock, and J. D. Nichols. 2005. Estimating the number of animals in wildlife populations, in C. E. Braun, Ed. Research and Management Techniques for Wildlife and Habitats, pp. 106–153. Wildlife Society, Bethesda, MD.Google Scholar
83. Lebreton, J. -D., K. P. Burnham, J. Clobert, and D. R. Anderson. 1992. Modeling survival and testing biological hypotheses using marked animals: A unified approach with case studies. Ecol. Monogr. 62: 67–118.
84. Lee, S. -M., and A. Chao. 1994. Estimating population size via sample coverage for closed capture–recapture models. Biometrics 50: 88–97.
85. Lincoln, F. C. 1930. Calculating waterfowl abundance on the basis of banding returns. US Dept. Agric. Circ. No. 118: 1–4.Google Scholar
86. Link, W. A., and R. J. Barker. 2005. Modeling association among demographic parameters in analysis of open population capture–recapture data. Biometrics 61: 46–54.
87. Lucas, H. A., and G. A. F. Seber. 1977. Estimating coverage and particle density using the line intercept method. Biometrika 64: 618–622.
88. Ludwig, J. A., and J. F. Reynolds. 1988. Statistical Ecology. Wiley, New York.Google Scholar
89. Lukacs, P. M. 2002. WebSim: Simulation software to assist in trapping web design. Wildl. Soc. Bull. 30: 1259–1261.Google Scholar
90. Lukacs, P. M., A. B. Franklin, D. R. Anderson. 2004. In S. T. Buckland, D. R. Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers, and L. Thomas, Eds. Advanced Distance Sampling, pp. 260–278. Oxford University Press, Oxford.Google Scholar
91. Lukacs, P. M., D. R. Anderson, and K. P. Burnham. 2005. Evaluation of trapping-web design. Wildl. Res. 32: 103–110.
92. MacKenzie, D. I. 2005. What are the issues with presence–absence data for wildlife managers? J. Wildl. Manage. 69: 849–860.
93. MacKenzie, D. I., and J. A. Royle. 2005. Designing occupancy studies: General advice and allocating survey effort. J. Appl. Ecol. 42: 1105–1114.
94. MacKenzie, D. I., J. D. Nichols, G. B. Lachman, S. Droege, J. A. Royle, and C. A. Langtimm. 2002. Estimating site occupancy rates when detection probabilities are less than one. Ecology 83: 2248–2255.
95. MacKenzie, D. I., J. A. Royle, J. A. Brown, and J. D. Nichols. 2004. Occupancy estimation and modeling for rare and elusive species. In W. L. Thompson, Ed. Sampling Rare or Elusive Species, pp. 149–172. Island Press, Washington.Google Scholar
96. MacKenzie, D. I., J. D. Nichols, J. Andrew Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy Estimation and Modeling. Academic Press, London.Google Scholar
97. Manly, B. F. J. 1991. Randomization and Monte Carlo Methods in Biology. Chapman and Hall, London.Google Scholar
98. Manly, B. F. J., L. McDonald, and D. Thomas. 1993. Resource Selection by Animals: Statistical Design and Analysis for Field Studies. Chapman and Hall, London.Google Scholar
99. Manly, B. F. J., L. McDonald, and G. W. Garner. 1996. Maximum likelihood estimation for the double-count method with independent observers. J. Agric. Biol. Environ. Stat. 1(2): 170–189.
100. Marques, F. C. C., and S. T. Buckland. 2004. In S. T. Buckland, D. R. Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers, and L. Thomas, Eds. Advanced Distance Sampling, pp. 31–47. Oxford University Press, Oxford.Google Scholar
101. Matheron, G. 1962. Traite de Geostatistique Appliquee, Tome I. Memoires du Bureau de Recherches Geologiques et Minieres, No. 14. Editions Technip, Paris.Google Scholar
102. Matheron, G. 1971. The theory of regionized variables and its applications. Cahiers du Centre de Morphologie Mathematique, No. 5. Fontaine-bleau, France.Google Scholar
103. McCullagh, P., and J. A. Nelder. 1983. Generalized Linear Models. Chapman and Hall, London.Google Scholar
104. McDonald, L. L. 1980. Line-intercept sampling for attributes other than cover and density. J. Wildl. Manage. 44: 530–533.
105. McDonald, L. L. 1991. Workshop Notes on Statistics for Field Ecology. Western Ecosystems Technology, Inc. Cheyenne, WY.Google Scholar
106. McDonald, L. L. 2004. Sampling rare populations, in W. L. Thompson, Ed. Sampling Rare or Elusive Species, pp. 11–42. Island Press, Washington.Google Scholar
107. McDonald, L. L., H. B. Harvey, F. J. Mauer, and A. W. Brackney. 1990. Design of aerial surveys for Dall sheep in the Arctic National Wildlife Refuge, Alaska. Seventh Biennial Northern Wild Sheep and Goat Symposium. May 14–17, 1990, Clarkston, Washington.Google Scholar
108. McDonald, L. L., W. P. Erickson, and M. D. Strickland. 1995. Survey design, statistical analysis, and basis for statistical inferences in Coastal Habitat Injury Assessment: Exxon Valdez Oil Spill, in P. G. Wells, J. N. Buther, and J. S. Hughes, Eds. Exxon Valdez Oil Spill: Fate and Effects in Alaskan Waters. ASTM STP 1219. American Society for Testing and Materials, Philadelphia, PA.Google Scholar
109. Menkins Jr., G. E., and S. H. Anderson. 1988. Estimation of small-mammal population size. Ecology 69: 1952–1959.
110. Miller, S. D., G. C. White, R. A. Sellers, H. V. Reynolds, J. W. Schoen, K. Titus, V. G. Barnes, R. B. Smith, R. R. Nelson, W. B. Ballard, and C. C. Schwartz. 1997. Brown and black bear density estimation in Alsaka using radiotelemetry and replicated mark-resight techniques. Wildl. Monogr. 133.Google Scholar
111. Mode, N. A., L. L. Conquest, and D. A. Marker. 2002. Incorporating prior knowledge in environmental sampling: ranked set sampling and other double sampling procedures. Environmetrics 13: 513–521.
112. Mood, A. M., F. A. Graybill, and D. C. Boes. 1974. Introduction to the Theory of Statistics, 3rd Edition. McGraw-Hill, Boston.Google Scholar
113. Morrison, M. L., W. M. Block, M. D. Strickland, and W. L. Kendall. 2001. Wildlife Study Design. Springer.Google Scholar
114. Munholland, P. L., and J. J. Borkowski. 1996. Simple latin square sampling +1: A spatial design using quadrats. Biometrics 52: 125–136.
115. Muttlak, H. A., and L. L.McDonald. 1992. Ranked set sampling and the line intercept method: a more efficient procedure Biometrical J. 34: 329–346.
116. Nichols, J. D., and K. H. Pollock. 1983. Estimation methodology in contemporary small mammal capture–recapture studies. J. Mammal. 64: 253–260.
117. Nichols, J. D., and K. H. Pollock. 1990. Estimation of recruitment from immigration versus in situ reproduction using Pollocks robust design. Ecology 71: 21–26.
118. Noon, B. R., N. M. Ishwar, and K. Vasudevan. 2006. Efficiency of adaptive cluster sampling and random sampling in detecting terrestrial herptofauna in a tropical rainforest. J. Wildl. Manage. 34: 59–68.Google Scholar
119. Otis, D. L., K. P. Burnham, G. C. White, and D. R. Anderson. 1978. Statistical inference from capture data on closed animal populations. Wildl. Monogr. 62.Google Scholar
120. Otis, D. L., L. L. McDonald, and M. Evans. 1993. Parameter estimation in encounter sampling surveys. J. Wildl. Manage. 57: 543–548.
121. Overton, W. S., D. White, and D. L. Stevens. 1991. Design Report for EMAP: Environmental Monitoring and Assessment Program. Environmental Research Laboratory, U.S. Environmental Protection Agency, Corvallis, OR. EPA/600/3–91/053.Google Scholar
122. Packard, J. M., R. C. Summers, and L. B. Barnes. 1985. Variation of visibility bias during aerial surveys of manatees. J. Wildl. Manage. 49: 347–351.
123. Patil, G. P., A. K. Sinha, and C. Taillie. 1994. Ranked set sampling, in G. P. Patil and C. R. Rao, Eds. Handbook of Statistics, Environmental Statistics, Vol. 12. North-Holland, Amsterdam.Google Scholar
124. Pechanec, J. F., and G. Stewart. 1940. Sage brush-grass range sampling studies: size and structure of sampling unit. Am. Soc. Agron. J. 32: 669–682.Google Scholar
125. Peterjohn, B. G., J. R. Sauer, and W. A. Link. 1996. The 1994 and 1995 summary of the North American Breeding Bird Survey. Bird Popul. 3: 48–66.Google Scholar
126. Pollock, K. H. 1974. The Assumption of Equal Catchability of Animals in Tag-Recapture Experiments. Ph.D. Thesis, Cornell University, Ithaca, NY.Google Scholar
127. Pollock, K. H. 1982. A capture–recapture design robust to unequal probability of capture. J. Wildl. Manage. 46: 752–757.
128. Pollock, K. H. 1991. Modeling capture, recapture, and removal statistics for estimation of demographic parameters for fish and wildlife populations: past, present, and future. J. Am. Stat. Assoc. 86: 225–238.
129. Pollock, K. H., and M. C. Otto. 1983. Robust estimation of population size in closed animal populations from capture–recapture experiments. Biometrics 39: 1035–1049.
130. Pollock, K. H., and W. L. Kendall. 1987. Visibility bias in aerial surveys: A review of estimation procedures. J. Wildl. Manage. 51: 502–520.
131. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: The staggered entry design. J. Wildl. Manage. 53: 7–15.
132. Pollock, K. H., J. D. Nichols, C. Brownie, and J. E. Hines. 1990. Statistical inferences for capture–recapture experiments. Wildl. Monogr. 107.Google Scholar
133. Pradel, R. 1996. Utilization of capture–mark–recapture for the study of recruitment and population growth rate. Biometrics 52: 703–709.
134. Quang, P. X. 1989. A nonparametric approach to size-biased line transect sampling. Draft Report. Department of Mathematical Sciences, University of Alaska, Fairbanks, AK 99775. Biometrics 47(1): 269–279.
135. Quang, P. X., and E. F. Becker. 1996. Line transect sampling under varying conditions with application to aerial surveys. Ecology 77: 1297–1302.
136. Quang, P. X., and E. F. Becker. 1997. Combining line transect and double count sampling techniques for aerial surveys. J. Agric. Biol. Environ. Stat. 2: 230–242.
137. Ramsey, F. L., and J. M. Scott. 1979. Estimating population densities from variable circular plot surveys, in R. M. Cormack, G. P. Patil and D. S. Robson, Eds. Sampling Biological Populations, pp. 155–181. International Co-operative Publishing House, Fairland, MD.Google Scholar
138. Reed, D. J., L. L. McDonald, and J. R. Gilbert. 1989. Variance of the product of estimates. Draft report. Alaska Department of Fish and Game, 1300 College Road, Fairbanks, AK 99701.Google Scholar
139. Rexstad, E., and K. Burnham. 1991. Users Guide for Interactive Program CAPTURE, Abundance Estimation for Closed Populations. Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO.Google Scholar
140. Reynolds, R. T., J. M. Scott, and R. A. Nussbaum. 1980. A variable circular-plot method for estimating bird numbers. Condor 82(3): 309–313.
141. Rotella, J. J., S. J. Dinsmore, and T. L. Shaffer. 2004. Modeling nest-survival data: A comparison of recently developed methods that can be implemented in MARK and SAS. Anim. Biodivers. Conserv. 27: 187–205.Google Scholar
142. Royle, J. A. 2004a. Generalized estimators of avian abundance from count survey data. Anim. Biodivers. Conserv. 27: 375–386.Google Scholar
143. Royle, J. A. 2004b. Modeling abundance index data from anuran calling surveys. Conserv. Biol. 18: 1378–1385.
144. Royle, J. A., and W. A. Link. 2005. A general class of multinomial mixture models for anuran calling survey data. Ecology 86: 2505–2512.
145. Royle, J. A., and J. D. Nichols. 2003. Estimating abundance from repeated presence–absence data or point counts. Ecology 84: 777–790.
146. Royle, J. A., J. D. Nichols, and M. Kery. 2005. Modelling occurrence and abundance of species when detection is imperfect. Oikos 110: 353–359.
147. Samuel, M. D., E. O. Garton, M. W. Schlegel, and R. G. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. J. Wildl. Manage. 51: 622–630.
148. Scheaffer, R. L., W. Mendenhall, and L. Ott. 1990. Elementary Survey Sampling. PWS-Kent, Boston, MA.Google Scholar
149. Schoenly, K. G., I. T. Domingo, and A. T. Barrion. 2003. Determining optimal quadrat sizes for invertebrate communities in agrobiodiversity studies: A case study from tropical irrigated rice. Environ. Entomol. 32: 929–938.
150. Schwarz, C. J., and A. N. Arnason. 1996. A general methodology for the analysis of capture–recapture experiments in open populations. Biometrics 52: 860–873.
151. Schwarz, C. J., and W. T. Stobo. 1997. Estimating temporary migration using the robust design. Biometrics 53: 178–194.
152. Seber, G. A. F. 1982. The Estimation of Animal Abundance and Related Parameters, 2nd Edition. Griffin, London.Google Scholar
153. Shaffer, T. L. 2004. A unified approach to analyzing nest success. Auk 121: 526–540.
154. Skinner, R., W. Erickson, G. Minick, and L. L. McDonald. 1997. Estimating Moose Populations and Trends Using Line Transect Sampling. Technical Report Prepared for the USFWS, Innoko National Wildlife Refuge, McGrath, AK.Google Scholar
155. Smith, W. 1979. An oil spill sampling strategy, in R. M. Cormack, G. P. Patil, and D. S. Robson, Eds. Sampling Biological Populations, pp. 355–363. International Co-operative Publishing House, Fairland, MD.Google Scholar
156. Smith, D. R., M. J. Conroy, and D. H. Brakhage. 1995. Efficiency of adaptive cluster sampling for estimating density of wintering waterfowl. Biometrics 51: 777–788.
157. Smith, D. R., J. A. Brown, and N. C. H. Lo. 2004. Application of adaptive sampling to biological populations, in W. L. Thompson, Ed. Sampling Rare or Elusive Species, pp. 77–122. Island Press, Washington.Google Scholar
158. Southwell, C. 1994. Evaluation of walked line transect counts for estimating macropod density. J. Wildl. Manage. 58: 348–356.
159. Stanley, T. R. 2000. Modeling and estimation of stage-specific daily survival probabilities of nests. Ecology 81: 2048–2053.
160. Steinhorst, R. K., and M. D. Samuel. 1989. Sightability adjustment methods for aerial surveys of wildlife populations. Biometrics 45: 415–425.
161. Stevens, D. L., and A. R. Olsen. 1999. Spatially restricted surveys over time for aquatic resources. J. Agric. Biol. Environ. Stat. 4: 415–428.
162. Stevens, D. L., and A. R. Olsen. 2004. Spatially balanced sampling of natural resources. J. Am. Stat. Assoc. 99: 262–278.
163. Strickland, M. D., L. McDonald, J. W. Kern, T. Spraker, and A. Loranger. 1994. Analysis of 1992 Dall’s sheep and mountain goal survey data, Kenai National Wildlife Refuge. Bienn. Symp. Northern Wild Sheep and Mountain Goat Council.Google Scholar
164. Strickland, M. D., W. P. Erickson, and L. L. McDonald. 1996. Avian Monitoring Studies: Buffalo Ridge Wind Resource Area, Minnesota. Prepared for Northern States Power, Minneapolis, MN.Google Scholar
165. Thomas, J. W. Ed. 1979. Wildlife Habitats in Managed Forests: The Blue Mountains of Oregon and Washington. US Forest Service, Agriculture Handbook 553.Google Scholar
166. Thompson, S. K. 1990. Adaptive cluster sampling. J. Am Stat. Assoc. 85: 1050–1059.
167. Thompson, S. K. 1991a. Adaptive cluster sampling: designs with primary and secondary units. Biometrics 47: 1103–1115.
168. Thompson, S. K. 1991b. Stratified adaptive cluster sampling. Biometrika 78: 389–397.
169. Thompson, S. K. 1992. Sampling. Wiley, New York.Google Scholar
170. Thompson, W. L. 2002a. Towards reliable bird surveys: Accounting for individuals present but not detected. Auk 119: 18–25.
171. Thompson, S. K. 2002b. Sampling, 2nd Edition. Wiley, New York.Google Scholar
172. Thompson, S. K., and G. A. F. Seber. 1996. Adaptive Sampling. Wiley, New York.Google Scholar
173. Thomas, D., and E. Taylor. 1990. Study designs and tests for comparing resource use and availability. J. Wildl. Manage. 54: 322–330.
174. Thompson, W. L., G. C. White, and C. Gowan. 1998. Monitoring vertebrate populations. Academic, London.Google Scholar
175. Trenkel, V. M., S. T. Buckland, C. McLean, and D. A. Elston. 1997. Evaluation of aerial line transect methodology for estimating red deer (Cervus elaphus) abundance in Scotland. J. Environ. Manage. 50: 39–50.
176. Venables, W. N., and B. D. Ripley. 2002. Modern Applied Statistics with S. Springer, New York.Google Scholar
177. Vojta, C. D. 2005. Old dog, new tricks: Innovations with presence–absence information. J. Wildl. Manage. 69: 845–848.
178. White, G. C., D. R. Anderson, K. P. Burnham, and D. L. Otis, 1982. Capture–Recapture and Removal Methods for Sampling, Closed Populations. Rpt. LA-8787-NERP. Los Alamos National Laboratory, Los Alamos, NM.Google Scholar
179. Wiegert, R. G. 1962. The selection of an optimum quadrat size for sampling the standing crop of grasses and forbs. Ecology 43: 125–129.
180. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2002. Analysis and Management of Animal Population. Academic, London.Google Scholar
181. Wolter, K. M. 1984. Investigation of some estimators of variance for systematic sampling. J. Am. Stat. Assoc. 79: 781–790.
182. Zippen, C. 1958. The removal method of population estimation. J. Wildl. Manage. 22: 82–90.