AVIAN MONITORING SOFTWARE – A REVIEW
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Keywords

computer programs
environmental monitoring
ornithology
species diversity
population dynamics.

How to Cite

Matsyura, A. V., & Jankowski, K. (2016). AVIAN MONITORING SOFTWARE – A REVIEW. Acta Biologica Sibirica, 2(2), 5-24. https://doi.org/10.14258/abs.v2i2.1310

Abstract

A review of the most common computer programs for processing data ornithological monitoring. The possibilities and limitations of programs, examples of their use. The technique of field data processing with the help of environmental applications of computer programs.

https://doi.org/10.14258/abs.v2i2.1310
PDF (Русский)

References

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Pennycuick C.J. Wingbeat frequency of birds in steady cruising flight: new data and improved predictions / C.J. Pennycuick // J. Exp. Biology. – 1996. – Vol. 199. – P. 1613–1618.

Pennycuick C.J. Field observations of thermals and thermal streets, and the theory of cross–country soaring flight / C.J. Pennycuick // Journal of Avian Biology. – 1998. – Vol. 29. – P. 33–43.

Pollock K.H. Statistical inference for capture–recapture experiments / K.H. Pollock, J.D. Nichols, C. Brownie // Wildlife Monographs. – 1990. – Vol. 107. – P. 1–98.

Prairie Y.T. Evaluating the predictive power of regression models / Y.T. Prairie // Can. J. Fish and Aquat. Sci. – 1996. – Vol. 3. – P. 490–492.

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Ter Braak C.J.F. Analysis of monitoring data with many missing values: which method? // The European Union and Biodiversity [W. Hagemeijer] / C.J.F. Ter Braak, A.J. van Strien, R. Meijer. – Brussels: Friends of the Earth & EEB, 1998. – 76 p.

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Underhill L.G. Indices for waterbird populations // BTO Research Report / L.G. Underhill. – London: Brit. Press, 1989. – P. 33–51.

Van den Bossche W. Satellite tracking of white storks Ciconia ciconia / W. Van den Bossche, M. Katz, U. Querner // Proceedings of the 22nd International Ornithological Congress, Durban, 1999. – P. 22–23.

Verstrael T. Bird Numbers. Distribution, Monitoring and Ecological Aspects / T. Verstrael // Proceeding 12th International Conference of IBCC and EOAC. – Statistics Netherlands, Voorburg & SOVON, Beek–Ubbergen, 1997. – P. 33–38.

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Welkinson D.M. Relationship between species richness and rarity in Welsh aquatic flora / D.M. Welkinson // Watsonia. – 1998. – Vol. 22. – P. 29–32.

White G.C. Capture–recapture and removal methods for sampling closed populations / White G.C., Anderson D.R., Burnham K.P. – Los Alamos National Laboratory, Los Alamos, New Mexico, 1982. – P. 43–78.

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Batschelet, E. (1965). Statistical methods for the analysis of problems in animal orientation and certain biological rhythms. Washington: Am. Inst. Sci.

Batschelet, E. (1972). Recent statistical methods for orientation data. In: Animal Orientation and Navigation (Ed. S. R. Galler et al) (pp. 61–91). Washington, DC: NASA

Batschelet, E. (1981). Circular statistics in biology. London: Academic Press.

Begon, M. (1983). Abuses of mathematical techniques in Ecology: applications of Jolly's capture–recapture method. Oikos, 40, 155–158.

Birdlife International. (2000). European Bird Census Council: European bird populations: estimates and trends. Cambridge, UK: BirdLife International (BirdLife Conservation Series No. 10).

Buckland, S.T. (1987). On the variable circular plot method of estimating animal density. Biometrics, 43, 363–384.

Burnham, K.P., Anderson, D.R., Laake, J.L. (1980). Estimation of density from line transect data. Wildlife Monograph, 72, 94–99.

Chao, A. (1989). Estimating population size for sparse data in capture–recapture experiments. London: Willey & Sons.

Chao, A. (1987). Estimating the population size for capture–recapture data with unequal catchability. Biometrics, 43(4), 783–792.

Chapman, D.G. (1951). Some properties of the hypergeometric distribution with applications to zoological sample censuses. Univ. of California Publ. Stat., 1(7), 131–160.

Cormack, R.M. (1989). Log–linear models for capture–recapture. Biometrics, 45(2), 395–414.

Crain, B.R., Burnham, K.P., Anderson, D.R. (1989). Nonparametric estimation of population density for line transect sampling using Fourier series. Biometrical Journal, 21, 731–748.

Engeman, R.M., Sugihara, R.T., Pank, L.F. (1994). A comparison of plotless density estimators using Monte Carlo simulation. Ecology, 75(6), 1769–1779.

Ensign, W.E., Angermeier, P.L., Dolloff, C.A. (1995). Use of line transect methods of estimate abundance of benthic stream fishes. Can. J. Fish. Aq. Sci., 52(1), 213–222.

Erni, B., Liechti, F., Underhill, L.G. (2002). Wind and rain govern the intensity of nocturnal bird migration in central Europe – a log–linear regression analysis. Ardea, 90, 155–166.

European bird populations: estimates and trends. (2004). BirdLife Conservation Series No. 10. Cambridge: BirdLife International.

Gadagkar, R. (2005). An undesirable property of Hill's index N2. Oecologia, 80, 140–141.

Geisser, P.H., Sauer, J.R., (1990). Topics in route–regression analysis. In: Survey designs and statistical methods for the estimation of avian populations trends (pp. 85–97). Washington: U.S. Fish and Wildlife service.

Guisan, A., Zimmermann, N.E. (2000). Predictive habitat distribution models in ecology. Ecological Modelling, 135, 147–186.

Hurvich, C.M., Tsai, C.L. (1989). Regression and time series model selection in small samples. Biometrika, 76, 297–307.

Hutchinson, G.E., MacArthur, R.H. (1959). A Theoretical Ecological Model of Size Distribution among Species of Animal. American Nature, 93, 117–125.

Jackson, D.A., Somers, K.M., Harvey, H.H. (1989). Similarity coefficients: measures of co–occurence and association or simply measures of occurrence? Amer. Nat., 133, 436–453.

Kelley, J.R. (2000). Line–transect sampling for estimating breeding wood duck density in forested wetlands. Wildlife Soc. Bull., 24(1), 32–36.

Kendall, M.G., Moran, P.A.P. (1963). Geometrical probability. London: Griffin.

Kendall, M.G., Ord, J.K. (1990). Time series (3rd Ed.). London: Griffin.

Keuls, M., Over, H.I., de Wit, C.T. (1998). The distance method for estimating densities. Statistica Neerlandica, 17, 71–91.

Lebreton, J.D. Modeling survival and testing biological hypotheses using marked animals: A unified approach with case studies / J.D. Lebreton, K.P. Burnham, J. Clobert // Ecological Monographs. – 1992. – Vol. 62(1). – P. 67–118.

Leslie, P.H., Chitty, D. (1951). The estimation of population parameters from data obtained by means of the capture–recapture method. 1. The maximum likelihood equations for estimating the death–rate. Biometrika, 38, 269–292.

Leslie, P.H. (1952).The estimation of population parameters from data obtained by means of the capture–recapture method II. The estimation of total numbers. Biometrika, 39, 363–388.

Liechti, F., Klaassen, M., Bruderer, B. (2000). Predicting migratory flight altitudes by physiological migration models. Auk, 117, 205–214.

Lincoln, F.C. (1971). Calculating waterfowl abundance on the basis of banding returns. U.S.D.A. Circ., 118, 1–4.

Montgomery, D.C., Johnson, L.A., Gardiner, J.S. (1990). Forecasting and time series analysis (2nd Ed.). New York: McGraw–Hill.

Morisita, M. (1957). A new method for the estimation of density by spacing method applicable to nonrandomly distributed populations. Physiology and Ecology, 7, 134–144.

Mouritsen, H. (2003). Spatiotemporal orientation strategies of long–distance migrants. In: Avian Migration (P. Berthold, E. Gwinner, E. Sonnenschein, Eds.) (pp. 4930513). Berlin, Heidelberg: Springer–Verlag.

Pennycuick, C.J. (1975). Mechanics of flight. Avian Biology, 5, 1–75.

Pennycuick, C.J. (1989). Bird flight performance: a practical calculation manual. Oxford: Oxford University Press.

Pennycuick, C.J. (1996). Wingbeat frequency of birds in steady cruising flight: new data and improved predictions. J. Exp. Biology, 199, 1613–1618.

Pennycuick, C.J. (1998). Field observations of thermals and thermal streets, and the theory of cross–country soaring flight. Journal of Avian Biology, 29, 33–43.

Pollock, K.H., Nichols, J.D., Brownie, C. (1990). Statistical inference for capture–recapture experiments. Wildlife Monographs, 107, 1–98.

Prairie, Y.T. (1996). Evaluating the predictive power of regression models. Can. J. Fish and Aquat. Sci., 3, 490–492.

Safriel, U.N., Lavee, D. (1998). Weight changes of cross–desert migrants at an oasis – do energetic considerations alone determine the length of stopover? Oecologia, 76, 611–619.

Schmidt–Koenig, K. (1979). Avian Orientation and Navigation. New York: Academic Press.

Seber, G.A.F. (1968). A review of estimating animal abundance. Biometrics, 1986, 267–292.

Seber, G.A.F. (1982). The estimation of animal abundance and related parameters. London: Griffin.

Southwell, C., Weaver, K. (1999). Evaluation of analytical procedures for density estimation from line–transect data: Data grouping, data truncation and the unit of analysis. Wildlife Research, 20(4), 433–444.

STATISTICA. (2002). Electronic manual. Bedford: StatSoft, Inc.

SYSTAT. (1989). Evanston: SYSTAT, Inc.

Ter Braak, C.J.F., van Strien, A.J., Meijer, R. (1998). Analysis of monitoring data with many missing values: which method? In: The European Union and Biodiversity (W. Hagemeijer, Ed.). Brussels: Friends of the Earth & EEB.

Tonhasca, А. (1994). Diversity indices in the analysis of biological communities. Cienc. et cult., 3, 138–140.

Underhill L.G. Indices for waterbird populations // BTO Research Report / L.G. Underhill. – London: Brit. Press, 1989. – P. 33–51.

Van den Bossche, W., Katz, M., Querner, U. (1999). Satellite tracking of white storks Ciconia ciconia. Proceedings of the 22nd International Ornithological Congress, Durban.

Verstrael, T. (1997). Bird Numbers. Distribution, Monitoring and Ecological Aspects. Proceeding 12th International Conference of IBCC and EOAC. Statistics Netherlands, Voorburg & SOVON, Beek–Ubbergen.

Welham, C.V.J. (1994). Flight speeds of migrating birds: a test of the maximum range speed predictions from three aerodynamic equations. Behavioral Ecology, 5, 1–8.

Welkinson, D.M. (1998). Relationship between species richness and rarity in Welsh aquatic flora. Watsonia, 22, 29–32.

White, G.C., Anderson, D.R., Burnham, K.P. (1982). Capture–recapture and removal methods for sampling closed populations. Los Alamos, New Mexico: Los Alamos National Laboratory.

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