Interdisciplinary Perspectives on Invasive Species Risk Modelling: Bridging Ecology, Climate Science, and Artificial Intelligence

Abstract

The escalating rate of the globalisation process of trade, transportation, and human mobility and the rise of climatic changes have resulted in the expansion of the severity of the invasion of alien species (IAS), the consequences of which are disastrous in terms of biodiversity, stability of the ecosystem, agriculture, and world sustainability. Even as useful as it is, however, the traditional ecological modelling approaches have been inclined to omit the fact of dynamic and nonlinear interaction of the biotic, climatical, and anthropogenic factors controlling the invasion of species. The review illustrates the integrative paradigm, which is a fusion of ecology, 
climatic science, and artificial intelligence (AI) in order to hasten the risk modelling and predictive analytics of invasive species. The most crucial part of this synthesis: the CLIMEX model that provides mechanistic insight into species-climate interactions and works as an analysis instrument. However, when combined with machine learning algorithms, such as the random forest, support vector magnificence and artificial neural networks, CLIMEX will be able to achieve higher predictive accuracy and, consequently, produce more accurate spatial and temporal predictions on potentially invasive areas. The integration of high-resolution climatic data with socio-economic variables and remote sensors can be used to produce adaptation and data-driven models, capable of providing ecological hotspots and introduction paths that could be provided with regard to future climatic scenarios. They are applied in agricultural pests management, in aquatic environment management, as well as in urban biodiversity management, and the right of the trans-linguistic approach of the existing ecological prediction. Moreover, the socio-economic and policy implementation also streamlines evidence-based decision-making to enhance the early warning systems and the accompanying mitigation of both local, national, and international risks. The article emphasises that the convergence of the ecology theory with the climate modelling and AI-based computing is capable of not only increasing the validity of the predictions that describe the whereabouts of species, but it also provides feasible solutions in terms of how to efficiently use resources, employ the climate, and avoid invasion of biological species. In this work, these disciplinary boundaries are dismantled and a holistic paradigm of predictive ecology is encouraged and is a component of the global initiatives in reaching the goals of resilience, sustainability, and preservation of ecological integrity in an environment more complex than any other.