Are Data on Predators Necessary When Modeling Prey Population Dynamics?

Описание

Тип публикации: статья из журнала

Год издания: 2023

Идентификатор DOI: 10.1134/s207908642303009x

Ключевые слова: life sciences, general, cell biology, biochemistry, zoology, ecology

Аннотация: A new approach is proposed for building a model of the prey population in the “predator–prey” system without using data on the dynamics of the predator numbers. To replace these data, autoregressive models with a set of linear positive and negative feedbacks are considered, which replace data on the influence of predator populations. The proposed approach can be used to model local populations of animals, for which there are no complete data on their interactions with other species in the ecosystem. We used conjugate series of dynamics of prey and predator populations: “classical” data on the number of lynx and hare skins purchased by the Hudson’s Bay Company, as well as annual data on the number of moose and wolves on the Isle Royale on Lake Superior in North America. The studied populations were considered as auto-regulated (AR) systems with feedback. The regulation of the number of the prey populations (hares and moose) is characterized by the presence of two feedback loops: a positive feedback between the current population density and the population density in the previous season, and a negative feedback between the current population density and the population density 2 years before this. It is shown that in order to build a model of prey populations, there is no need to know how many species of predators (including humans) affect this population. Based on the data on the temporal dynamics of the studied populations, an assessment of the feedback coefficients of AR equations, their stability and stability margin is given. The coefficient of determination <i>R</i>2 for the considered models reaches the value <i>R</i>2 = 0.978.

Ссылки на полный текст

Издание

Журнал: Biology Bulletin Reviews

Выпуск журнала: Т. 13, 3

Номера страниц: 216-227

ISSN журнала: 20790864

Место издания: Moscow

Издатель: Pleiades Publishing, Ltd.

Персоны

  • Soukhovolsky V.G. (Sukachev Institute of Forests, Siberian Branch, Russian Academy of Sciences)
  • Ivanova Y.D. (Institute of Biophysics, Siberian Branch, Russian Academy of Sciences)
  • Kovalev A.V. (Federal Research Center KSC Siberian Branch, Russian Academy of Sciences)

Вхождение в базы данных