Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Influence of Parameters in SDMs Application to Citrus Presence in Mediterranean Area

Version 1 : Received: 21 February 2023 / Approved: 22 February 2023 / Online: 22 February 2023 (07:32:03 CET)

How to cite: Catalano, G.A.; D'Urso, P.R.; Maci, F.; Arcidiacono, C. Influence of Parameters in SDMs Application to Citrus Presence in Mediterranean Area. Preprints 2023, 2023020379. https://doi.org/10.20944/preprints202302.0379.v1 Catalano, G.A.; D'Urso, P.R.; Maci, F.; Arcidiacono, C. Influence of Parameters in SDMs Application to Citrus Presence in Mediterranean Area. Preprints 2023, 2023020379. https://doi.org/10.20944/preprints202302.0379.v1

Abstract

In this study, the application of the main algorithms used for SDM, namely Boosted Regression Tree (BRT), Generalized Linear Model (GLM), Multivariate Adaptive Regression Splines (MARS), Maximum Entropy (MAXENT) and Random Forest (RF), were considered in order to simulate the citrus probability of distribution in a Mediterranean area, based on presence data and a random background sample, and in relation to several predictors. The predictors were grouped under 19 bioclimatic variables, elevation described through a Digital terrain model, soil physical properties, and irrigation. Sensitivity analysis was carried out by: modifying the values of the main models’ parameters; and reducing the input presence points.

Keywords

Vistrails-SAHM software; citrus; spatial distribution; probability of presence; Mediterranean climate; predictor layers

Subject

Computer Science and Mathematics, Information Systems

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