Библиографическое описание:An Autoregulatory Model of Forest Insect Population Dynamics and Forest Stand Damage Dynamics in Different Habitats: An Example of Lymantria dispar L. : научное издание / V. V. Soukhovolsky [et al.]. - Текст : непосредственный // Forests. - 2024. - Т. 15, № 7. - P. 1098. - ISSN 1999-4907, DOI 10.3390/f15071098.
Аннотация:<jats:p>This paper addresses the problem of constructing a mathematical model of population density dynamics and the dynamics of forest areas damaged by spongy moth (Lymantria dispar L.) outbreaks in the United States, Europe, Russia, and Japan. The key variable of the model is either the pest population density or the area of forests damaged by spongy moths during a season. This variable can be considered proportional to the total current pest abundance in the study area. For the purposes of modeling, data from a number of different authors was used (see bibliography), as well as data from surveys conducted at the egg or caterpillar stage. The complexity of modeling the dynamics of L. dispar abundance is largely due to the fact that, when studying the dynamics of spongy moth population density, the values of external factors such as parasites, predators, and the amount of available food are often unknown. A simple model was proposed using only two types of data: population density and monthly weather characteristics. Our analysis demonstrated that, even in the absence of knowledge regarding the characteristics of ecosystem components interacting with the spongy moth population (parasites, predators, and the state of forage trees), it is possible to introduce models that characterize the regulatory processes in the population in terms of (i) the presence of negative and positive feedbacks in the system and (ii) the influence of external weather factors. The system under investigation was described as an autoregressive system, whereby the current state of the population is dependent on its state in previous years. The order of autoregression in the system was estimated using the order of the maximum significant partial autocorrelation function. It was found that the regulation of spongy moth population density was characterized by the presence of two feedback loops: positive feedback between the current population density and the population density in the previous season and negative feedback between the current population density and the population density two years ago. To evaluate the model, its stability margin was calculated and found to be directly proportional to the positive feedback coefficient and inversely proportional to the negative feedback coefficient. The model was demonstrated to explain up to 90% of the observed variance of real data. Although the model coefficients for different local populations (North America, Europe, and Asia) differ, the general form of the equation describing both direct data on population densities and indirect data on pest dynamics characterized by areas of stand damage is consistent. Consequently, the form of the ADL model is general, irrespective of the location of the local population.</jats:p>
Держатель оригинала документа:Biological Institute, National Research Tomsk State University, Tomsk 634050, Russia, Department of Agriculture, Tokyo University of Agriculture and Technology, Tokyo 183-8509, Japan, Department of Ecology and Nature Management, Siberian Federal University, Krasnoyarsk 660041, Russia, Forest Health Department, French Ministry of Agriculture and Food, 75349 Paris, France, Institute Botanical Garden, Ural Branch of Russian Academy of Sciences, Yekaterinburg 620144, Russia, Institute of Systematics and Ecology of Animals, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630091, Russia, Institute of Water and Ecological Problems, Far East Branch of Russian Academy of Sciences, Khabarovsk 680000, Russia, Krasnoyarsk Scientific Center, Siberian Branch of Russian Academy of Sciences, Krasnoyarsk 660036, Russia, V.N. Sukachev Institute of Forest, Siberian Branch of Russian Academy of Sciences, Krasnoyarsk 660036, Russia
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