The diversity of life and the complexity of ecosystems are rooted in cyclicity—an order that ensures the functioning of biological processes. In various industries that utilize natural resources, it is crucial to consider the characteristics of natural cyclicity and make corresponding forecasts. In our study, we approached this task by analyzing the cyclicity of long-term numerical series of insects. As a model species, we selected a widespread species of the ground beetle family, Pterostichus montanus. From 1988 to 2020, we conducted quantitative surveys from May to September at 14 stationary sites located along a 30-kilometer transect stretching from the shore of Lake Baikal to a mountain peak of the Barguzinsky ridge. Simultaneously, we recorded average the monthly air temperature and total monthly precipitation.
For the visualization and interpretation of the long-term series, we used spectral analysis and elements of fractal geometry, specifically Pareto histograms, which rank factor categories in descending order and allow us to identify the most significant factors influencing the entire process. These methods enabled us to detect cycles and determine the most important factors affecting the abundance of ground beetles.
In the long-term series of the model species, we identified eight cycles of varying strength. The most pronounced were the two-year cycles associated with the cyclicity of atmospheric precipitation (p = 0.001) and the three-year cycles determined by temperature regimes (p = 0.001). Longer cycles with a frequency of 8-11 years were of secondary importance (p = 0.1). We also found that the abundance of this species does not decrease with increasing altitude. Favorable conditions for the abundance of ground beetles include a pronounced litter layer, moderate light, and moisture. The studied species primarily coordinates its population dynamics with the cyclicity of meteorological parameters, highlighting the importance of studying cyclicity and its impact on natural ecosystems.