AbstractAlthough many hypotheses explaining invasion success have been formulated, invasion drivers are usually tested in isolation. This work aims to analyze the combined influence of propagule pressure (P), abiotic (A) and biotic (B) factors (PAB) on determining the invasion process of an exotic plant taxon (Carpobrotus sp.) in Mediterranean coastal landscapes. Specifically, we used a binomial Generalized Additive Model for exploring the relation between the occurrence of the invasive species and a set of PAB proxy variables derived from high-resolution remote sensed imagery (LiDAR - Light Detection and Ranging - and orthophotos). We evaluated the predictive power of the model by computing the mean of the AUC scores obtained through a 5-fold cross-validation and visual inspection of the Hosmer-Lemeshow plot. The integrated PAB approach efficiently captured the different roles played by the drivers of invasion in affecting the presence of the species. Invasion does not proceed homogeneously across the coastal landscape, but is promoted wherever the combined action of the PAB factors is favorable for establishment of the invader. Moreover, the use of remotely sensed data allowed us to model the invader-landscape relationship on a large geographic extent and to highlight the coastal sectors that are most likely to be invaded in the future.

Modeling plant invasion on Mediterranean coastal landscapes: An integrative approach using remotely sensed data

Carranza, Maria Laura
Writing – Review & Editing
2018-01-01

Abstract

AbstractAlthough many hypotheses explaining invasion success have been formulated, invasion drivers are usually tested in isolation. This work aims to analyze the combined influence of propagule pressure (P), abiotic (A) and biotic (B) factors (PAB) on determining the invasion process of an exotic plant taxon (Carpobrotus sp.) in Mediterranean coastal landscapes. Specifically, we used a binomial Generalized Additive Model for exploring the relation between the occurrence of the invasive species and a set of PAB proxy variables derived from high-resolution remote sensed imagery (LiDAR - Light Detection and Ranging - and orthophotos). We evaluated the predictive power of the model by computing the mean of the AUC scores obtained through a 5-fold cross-validation and visual inspection of the Hosmer-Lemeshow plot. The integrated PAB approach efficiently captured the different roles played by the drivers of invasion in affecting the presence of the species. Invasion does not proceed homogeneously across the coastal landscape, but is promoted wherever the combined action of the PAB factors is favorable for establishment of the invader. Moreover, the use of remotely sensed data allowed us to model the invader-landscape relationship on a large geographic extent and to highlight the coastal sectors that are most likely to be invaded in the future.
http://www.sciencedirect.com/science/article/pii/S0169204617302967
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/72748
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