Climate changes are responsible for considerable effects on agriculture due to the variation of temperatures and weather patterns. Governments are implementing different actions for a transition towards sustainable food and agriculture reducing the impacts on the environment. Environmental monitoring is of utmost importance in the identification of these actions as it allows resources protection, impacts mitigation, by ensuring a sustainable use of natural resources. Advanced technologies such as remote sensing and geographical information system, coupled with statistical tools, are helpful in determining the variation in the land cover due to climate changes. Based on the literature, the geostatistical tool Software for Assisted Habitat Modeling Package (SAHM) is a promising tool for environmental monitoring. On this basis, this study aimed at assessing SAHM for monitoring suitability and potential distribution of a specific vegetation in a territory. In the case study, the main objective was to predict the potential citrus coverage distribution in Eastern Sicily by the application of different geospatial models available in the SAHM environment. Based on the bioclimatic data acquired from open-source databases, species probabilities of occurrence were investigated in the territorial area belonging to the province of Syracuse by using different models (e.g., MaxEnt, BRT, MARS, GLM, and Random Forest). Comparisons between the results obtained by using these models were carried out, sensitivity to the dataset width and covariates’ selection was investigated, and accuracy measures were analysed. The results were provided by thematic maps showing the suitability of the plants’ presence at different bioclimatic conditions. The outcomes of this study are relevant for decision support of companies and territorial administrations in land use planning.

Assessing Application Potential of Species Distribution Models to the Case Study of Citrus in Eastern Sicily

Catalano Giuseppe Antonio
Primo
;
Valenti Francesca;D’Urso Provvidenza Rita
Penultimo
;
Arcidiacono Claudia
Ultimo
2023-01-01

Abstract

Climate changes are responsible for considerable effects on agriculture due to the variation of temperatures and weather patterns. Governments are implementing different actions for a transition towards sustainable food and agriculture reducing the impacts on the environment. Environmental monitoring is of utmost importance in the identification of these actions as it allows resources protection, impacts mitigation, by ensuring a sustainable use of natural resources. Advanced technologies such as remote sensing and geographical information system, coupled with statistical tools, are helpful in determining the variation in the land cover due to climate changes. Based on the literature, the geostatistical tool Software for Assisted Habitat Modeling Package (SAHM) is a promising tool for environmental monitoring. On this basis, this study aimed at assessing SAHM for monitoring suitability and potential distribution of a specific vegetation in a territory. In the case study, the main objective was to predict the potential citrus coverage distribution in Eastern Sicily by the application of different geospatial models available in the SAHM environment. Based on the bioclimatic data acquired from open-source databases, species probabilities of occurrence were investigated in the territorial area belonging to the province of Syracuse by using different models (e.g., MaxEnt, BRT, MARS, GLM, and Random Forest). Comparisons between the results obtained by using these models were carried out, sensitivity to the dataset width and covariates’ selection was investigated, and accuracy measures were analysed. The results were provided by thematic maps showing the suitability of the plants’ presence at different bioclimatic conditions. The outcomes of this study are relevant for decision support of companies and territorial administrations in land use planning.
2023
978-3-031-30328-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/558704
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