Staying ahead of invaders: Using species distribution modeling to predict alien species’ potential niche shifts

Early detection and rapid response are essential to prevent invasive species from thriving in marine environments following their introduction. Species distribution models (SDMs) are widely used to predict the potential distribution of invasive species, providing excellent tools for the design of st...

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Detalles Bibliográficos
Autores principales:	Battini, N., Farías, N., Giachetti, C.B., Schwindt, E., Bortolus, A.
Formato:	JOUR
Materias:	Ecological niche Invasive species Neurotoxins Niche shift Pleurobranchaea maculata SDM Species distribution Opisthobranchia Pleurobranchaea
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_01718630_v_n_p127_Battini
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_01718630_v_n_p127_Battini
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spelling	todo:paper_01718630_v_n_p127_Battini2023-10-03T15:07:36Z Staying ahead of invaders: Using species distribution modeling to predict alien species’ potential niche shifts Battini, N. Farías, N. Giachetti, C.B. Schwindt, E. Bortolus, A. Ecological niche Invasive species Neurotoxins Niche shift Pleurobranchaea maculata SDM Species distribution Opisthobranchia Pleurobranchaea Early detection and rapid response are essential to prevent invasive species from thriving in marine environments following their introduction. Species distribution models (SDMs) are widely used to predict the potential distribution of invasive species, providing excellent tools for the design of strategies to prevent or mitigate impacts of non-native species. Niche shifts are among the major drawbacks in the use of SDMs, leading scientists to formulate inaccurate predictions. In this work, we tested the performance of 3 different SDMs (Bioclim, Mahalanobis distance and Maxent) to predict the distribution of a niche-shifting invasive species using native data only. As a model organism, we used the neurotoxic sea-slug Pleurobranchaea maculata, which was recently introduced into the southwestern Atlantic, where it has undergone a niche shift. Our results show that Maxent outperforms the other modeling techniques in predicting the invasive distribution, but that Bioclim provides the most accurate outputs, minimizing over- and underpredictions. Our study strongly suggests that niche decomposition can provide important evidence for the underlying causes of niche shifts, aiding our understanding of why they occur and how they can be addressed by SDMs. This approach will improve the interpretation of SDMs in order to predict the potential spread of invasive species worldwide. © Inter-Research 2019 JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_01718630_v_n_p127_Battini
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Ecological niche Invasive species Neurotoxins Niche shift Pleurobranchaea maculata SDM Species distribution Opisthobranchia Pleurobranchaea
spellingShingle	Ecological niche Invasive species Neurotoxins Niche shift Pleurobranchaea maculata SDM Species distribution Opisthobranchia Pleurobranchaea Battini, N. Farías, N. Giachetti, C.B. Schwindt, E. Bortolus, A. Staying ahead of invaders: Using species distribution modeling to predict alien species’ potential niche shifts
topic_facet	Ecological niche Invasive species Neurotoxins Niche shift Pleurobranchaea maculata SDM Species distribution Opisthobranchia Pleurobranchaea
description	Early detection and rapid response are essential to prevent invasive species from thriving in marine environments following their introduction. Species distribution models (SDMs) are widely used to predict the potential distribution of invasive species, providing excellent tools for the design of strategies to prevent or mitigate impacts of non-native species. Niche shifts are among the major drawbacks in the use of SDMs, leading scientists to formulate inaccurate predictions. In this work, we tested the performance of 3 different SDMs (Bioclim, Mahalanobis distance and Maxent) to predict the distribution of a niche-shifting invasive species using native data only. As a model organism, we used the neurotoxic sea-slug Pleurobranchaea maculata, which was recently introduced into the southwestern Atlantic, where it has undergone a niche shift. Our results show that Maxent outperforms the other modeling techniques in predicting the invasive distribution, but that Bioclim provides the most accurate outputs, minimizing over- and underpredictions. Our study strongly suggests that niche decomposition can provide important evidence for the underlying causes of niche shifts, aiding our understanding of why they occur and how they can be addressed by SDMs. This approach will improve the interpretation of SDMs in order to predict the potential spread of invasive species worldwide. © Inter-Research 2019
format	JOUR
author	Battini, N. Farías, N. Giachetti, C.B. Schwindt, E. Bortolus, A.
author_facet	Battini, N. Farías, N. Giachetti, C.B. Schwindt, E. Bortolus, A.
author_sort	Battini, N.
title	Staying ahead of invaders: Using species distribution modeling to predict alien species’ potential niche shifts
title_short	Staying ahead of invaders: Using species distribution modeling to predict alien species’ potential niche shifts
title_full	Staying ahead of invaders: Using species distribution modeling to predict alien species’ potential niche shifts
title_fullStr	Staying ahead of invaders: Using species distribution modeling to predict alien species’ potential niche shifts
title_full_unstemmed	Staying ahead of invaders: Using species distribution modeling to predict alien species’ potential niche shifts
title_sort	staying ahead of invaders: using species distribution modeling to predict alien species’ potential niche shifts
url	http://hdl.handle.net/20.500.12110/paper_01718630_v_n_p127_Battini
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Staying ahead of invaders: Using species distribution modeling to predict alien species’ potential niche shifts

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