Spatiotemporal modeling of invasive arthropod spread in urban ecosystems with recreational areas

Abstract

This article examines contemporary approaches to modeling the spread of invasive species in urban ecosystems, considering their spatiotemporal dynamics and the functional heterogeneity of the environment. The relevance of this study stems from the need to enhance the accuracy of predicting invasion processes in urban ecosystems, where conventional bioclimatic models often fail to capture the complex mosaic structure of the environment. The study aims to develop and formalize a spatiotemporal model of invasive arthropod spread in urban ecosystems with recreational areas, considering their role as attractors, repellents, and ecological traps. The objectives included analyzing the spatial structure of urban ecosystems, identifying patterns of population distribution, and assessing the influence of environmental connectivity on invasion processes. The methodology was based on a spatially explicit discrete matrix approach, in which the urban ecosystem was modeled as a 10×10 grid. Contagion (Kc) and structural connectivity (Ksh) coefficients were applied to evaluate spatial patterns and simulate population spread scenarios. The results demonstrate that the degree of saturation of urban ecosystems with recreational areas, as well as their spatial connectivity, determines the nature of invasion processes. It was found that at a Schroeder coefficient of
Ksh ≥ 0.6, a network of ecologically connected localities is formed, enabling active biotic exchange and facilitating the spread of invasive species. In contrast, at Ksh < 0.6, the system becomes fragmented, and the infiltration process follows a probabilistic pattern based on Markov transitions. It was also established that the type of spatial distribution (uniform, random, or aggregated) significantly influences the formation of population clusters and their rate of spread. Recreational areas were shown to have a dual function, acting either as centers of population accumulation or as barriers, thereby creating an ecological trap effect. An analytical relationship describing the rate of population infiltration as a function of trophic specialization, resource availability, and spatial structure of the environment is proposed. The findings highlight that incorporating the spatiotemporal organization of urban ecosystems significantly improves the accuracy of invasion predictions. The practical significance of the study lies in the application of the model for identifying high-risk zones and optimizing the management of urban green spaces.