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Climate-Based Modeling of Invasive Species Impact on Urban Green Infrastructure Using CLIMEX and Remote Sensing Data

Year: 2026
Type: article
Abstract: The pace at which invasive alien species are established and spread is becoming a threat, especially to urban ecosystems, due, in part, to the variability of climates, urban growth, and fragmentation of habitats. These biological invasions are highly dangerous to urban green infrastructure (UGI), which sabotages biodiversity, ecological services, and ecological resilience in the long term. A unravelled modelling approach to employ the CLIMEX model of species distribution as well as the spatial analysis of ecosystems via remote sensing to observe invasion risk zones and map them in the fast urbanising landscapes was created in this work. The climatic suitability of chosen invasive species in the current and future climate conditions under parameters serving as temperature, precipitation, and humidity was simulated with the help of the CLIMEX model, and the land cover dynamics and vegetation indices (as well as the urban heat islands) were measured with the assistance of remote sensing data (Sentinel-2 and ModiS) measurements. It was possible to integrate these datasets using a GIS based multi-criteria methodology to create an Invasion Risk Index (IRI) to predict ecologically sensitive regions. The findings indicated that areas with an average rainfall, increasing temperatures, and discontinuous vegetation shows high ecological suitability of the invasive species, and this would be more so at the urban fringes, transport corridors, and industrial areas. These findings underscore the synergistic role of climatic and anthropogenic factors in shaping invasion dynamics and highlight the necessity for adaptive urban planning that incorporates ecological modeling outputs. The proposed framework offers a robust, scalable approach for predicting biological invasions, guiding urban biodiversity conservation strategies, and supporting policymakers in developing climate-resilient, biodiversity-secure urban ecosystems.
Language: English
Open Access status: diamond
OpenAlex ID: W7220239168
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