О. V. Matsyura, М. V. Matsyura, А. А. Zimaroyeva


For the analysis of long-term observations data on dynamics of bird populations the most suitable methods could be the stochastic processes. Abundance (density) of birds is calculated on the integrated area of studied habitats. Using the method of autocorrelation the correlogram of changes in number of birds drawn during the study period in all the area. After that, the calculation of the autocorrelation coefficients and partial autocorrelation are performed. The most appropriate model is the mixed autoregressive moving average (ARIMA). Ecological significance of autoregressive parameters is to display the frequency of changes in the number of birds in the seasonal and long-term aspects. The sliding average is one of the simplest methods, which allows reject the random fluctuations of the empirical regression line. Validation of the model could be conducted on truncated data series (10 years). The forecast is calculated for the next two years and compared with empirical data. Calculation of correlation coefficients between the real data and the forecast is performed using non-parametric Spearman correlation coefficient. The residual rows of selected models are estimated by residual correlogram. The constructed model can be used to analyze and forecast the number of birds in breeding biotopes.

Keywords: analysis, density, indirect methods, birds, Simply Tagging.


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

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.

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

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

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

Darroch, J.N. (1959). The multiple-capture census II. Estimation when there is immigration or death. Biometrika, 46, 336-351.

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

Leslie, P.H., Chitty, D. (1951). The estimation of population parameters from data obtained by means of the capture-recapture method. I. 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.

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

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

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

Seber, G.A.F. (1986). A review of estimating animal abundance. Biometrics, 42, 267-292.

Schnabel, Z.E. (1938). The estimation of the total fish population of a lake. Amer. Math. Mon., 45, 348-352.

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


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