Catalano, G.A.; Maci, F.; D’Urso, P.R.; Arcidiacono, C. GIS and SDM-Based Methodology for Resource Optimisation: Feasibility Study for Citrus in Mediterranean Area. Agronomy2023, 13, 549.
Catalano, G.A.; Maci, F.; D’Urso, P.R.; Arcidiacono, C. GIS and SDM-Based Methodology for Resource Optimisation: Feasibility Study for Citrus in Mediterranean Area. Agronomy 2023, 13, 549.
Catalano, G.A.; Maci, F.; D’Urso, P.R.; Arcidiacono, C. GIS and SDM-Based Methodology for Resource Optimisation: Feasibility Study for Citrus in Mediterranean Area. Agronomy2023, 13, 549.
Catalano, G.A.; Maci, F.; D’Urso, P.R.; Arcidiacono, C. GIS and SDM-Based Methodology for Resource Optimisation: Feasibility Study for Citrus in Mediterranean Area. Agronomy 2023, 13, 549.
Abstract
South Italy is characterised by a semi-arid climate with scarce rain and high evaporative demand, therefore the need to optimise water resources in this area is crucial, and climate change could worsen this condition. In citrus cultivation, which is one of the most important crops bred in Southern Italy, and more generally in Mediterranean regions, deficit irrigation strategies are im-plemented in order to cope with limited resource availability. On this basis, knowledge on how the territorial distribution of citrus would change in relation to these strategies constitutes valuable information for the stakeholders. Therefore, the objective of this study was to determine the prob-ability of presence of citrus in Sicily at changing of the percentage of water deficit application, in order to analyse change in the surface area and localisation of the crop. The methodology was based on the application of Species Distribution Models and Geographic Information Systems to the case study of the Province of Syracuse in Sicily. Different geostatistical and machine learning models were applied, based on 3-decades bioclimatic variables, DTM and irrigation; assessment of the outcomes was carried by using classification evaluation metrics. The analysis of the outcomes showed that uncorrelated predictor layers mainly included water input that affected most the probability of presence. Moreover, GIS analyses showed that deficit irrigation strategies would generate an overall reduction of cultivation surfaces in the territory and a decrease of citrus pres-ence in southern areas of the considered territory, where climate conditions are less favourable in terms of temperature and precipitations, thus providing useful information for decision support tools in agriculture and land use policy.
Keywords
Vistrails-SAHM software; citrus; spatial distribution; probability of presence; Mediterranean climate; predictor layers
Subject
Environmental and Earth Sciences, Sustainable Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
