An Individual-based Model of the Population Dynamics of the Saiga Antelope (Saiga tatarica tatarica) in the North-West Pre-Caspian Region (Russia)тезисы докладаТезисы
Аннотация:For study of the population dynamics of the Saiga Antelope an individual-based model was developed. The model is based on the published data collected in 20th century by different researchers during field studies of the Saiga population inhabiting in the North-West Pre-Caspian region in Russia. Parameters for the model have been calculated from the data collected until 1998, i.e. before the current depression period had started.
To prepare modeling scheme three main ‘stages’ during annual population cycle have been identified: calving stage (May), aggregation stage (August), mating stage (November-December). Exactly for these important stages, the main part of the parameters were collected, measured and calculated previously and it was a reason for their use in the proposed model.
The numerous field data, allowed us to determine such life-history parameters as mortality rates for males and females of different age classes between main stages in annual population cycle; probabilities of breeding depending on proportion of mature males in population; age-specific fertility as a calf number for females of different age classes; sex ratio for newborns and etc.
An important part of the model is addition of unfavorable conditions (according to unfavorable years) such as drought in summer, autumn and spring; an effect of melting-freezing in winter and heavy rains during the calving stage. The corresponding coefficients for mortality rates have been added for different unfavorable conditions, which can be applied using various schemes. An effect from autumn shooting, which was existed in the previous century and connected to the summer population size, has been added as well.
First results received during modeling show a strong growth of population size when the life-history parameters have been used only for favorable years and the effects at population dynamics of adverse weather conditions with excess mortality and autumn shooting can be estimated.