Ecological sustainability has recently risen to prominence in scientific research and management applications. Approaches to measuring ecological connectivity and their application to optimize ecological network (EN) design are powerful tools against landscape fragmentation and biodiversity loss.We focused on building an EN by identifying the most sensitive areas for ecological connectivity within the Reggio Calabria (Italy) metropolitan area. We also proposed a defragmentation scenario to improve the obtained EN.The CORINE Land Cover and the Urban Atlas 2018 were used to obtain a fine-scale representation of the study area. Ten terrestrial mammal species were used to model connectivity following a multi-species approach. Dispersal distance, patch size, and resistance to species movement were used to identify patches and corridors. Vegetational fractional coverage based on three years time series of Sentinel-2 red-edge normalized difference vegetation index was used to discriminate areas with higher naturalness. We used graph theory and connectivity metrics to test the EN's robustness and identify locations for restoration in a defragmentation scenario.The obtained EN, formed by three separate components, was composed of 724 arcs and 300 nodes with an average patch area of 27.04 ha. After the defragmentation hypothesis, the EN, formed by only one component, was composed of 771 arcs and 328 nodes with an average patch area of 26.82 ha.It was possible to analyze an EN's connectivity and evaluate the impact of a scenario intended to enhance multi-species connectivity. By comparing several connectivity metrics, we highlighted the potential of land in-terventions as a planning tool to enhance future ecological sustainability and biodiversity conservation.

Combined use of urban Atlas and Corine land cover datasets for the implementation of an ecological network using graph theory within a multi-species approach / Lumia, G; Pratico', S; Di Fazio, S; Cushman, S; Modica, G. - In: ECOLOGICAL INDICATORS. - ISSN 1470-160X. - 148:(2023), p. 110150. [10.1016/j.ecolind.2023.110150]

Combined use of urban Atlas and Corine land cover datasets for the implementation of an ecological network using graph theory within a multi-species approach

Lumia, G;Pratico', S
;
Di Fazio, S;Modica, G
2023-01-01

Abstract

Ecological sustainability has recently risen to prominence in scientific research and management applications. Approaches to measuring ecological connectivity and their application to optimize ecological network (EN) design are powerful tools against landscape fragmentation and biodiversity loss.We focused on building an EN by identifying the most sensitive areas for ecological connectivity within the Reggio Calabria (Italy) metropolitan area. We also proposed a defragmentation scenario to improve the obtained EN.The CORINE Land Cover and the Urban Atlas 2018 were used to obtain a fine-scale representation of the study area. Ten terrestrial mammal species were used to model connectivity following a multi-species approach. Dispersal distance, patch size, and resistance to species movement were used to identify patches and corridors. Vegetational fractional coverage based on three years time series of Sentinel-2 red-edge normalized difference vegetation index was used to discriminate areas with higher naturalness. We used graph theory and connectivity metrics to test the EN's robustness and identify locations for restoration in a defragmentation scenario.The obtained EN, formed by three separate components, was composed of 724 arcs and 300 nodes with an average patch area of 27.04 ha. After the defragmentation hypothesis, the EN, formed by only one component, was composed of 771 arcs and 328 nodes with an average patch area of 26.82 ha.It was possible to analyze an EN's connectivity and evaluate the impact of a scenario intended to enhance multi-species connectivity. By comparing several connectivity metrics, we highlighted the potential of land in-terventions as a planning tool to enhance future ecological sustainability and biodiversity conservation.
2023
Remote sensing (RS)
Vegetation Fractional Coverage (VFC)
Sentinel-2
Google Earth Engine (GEE)
Graphab
Landscape connectivity
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/135586
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