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Marine Ecology Progress Series

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MEPS 612:127-140 (2019)  -  DOI:

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

Nicolás Battini1,2,3,*, Nahuel Farías4,5, Clara Belen Giachetti1,2,3, Evangelina Schwindt1,2, Alejandro Bortolus1,6

1Grupo de Ecología en Ambientes Costeros (GEAC), Puerto Madryn 9120, Argentina
2Instituto de Biología de Organismos Marinos (IBIOMAR-CONICET), Puerto Madryn 9120, Argentina
3Facultad de Ciencias Exactas y Naturales (UBA), Buenos Aires 1428, Argentina
4Laboratorio de Invertebrados, FCEyN-UNMDP, Mar del Plata 7602, Argentina
5Instituto de Investigaciones Marinas y Costeras (IIMyC-CONICET), Mar del Plata 7602, Argentina
6Instituto Patagónico para el Estudio de los Ecosistemas Continentales (IPEEC), CONICET, Puerto Madryn 9120, Argentina
*Corresponding author:

ABSTRACT: 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.

KEY WORDS: Pleurobranchaea maculata · Invasive species · Species distribution · SDM · Ecological niche · Niche shift · Neurotoxins

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Cite this article as: Battini N, Farías N, Giachetti CB, Schwindt E, Bortolus A (2019) Staying ahead of invaders: using species distribution modeling to predict alien species’ potential niche shifts. Mar Ecol Prog Ser 612:127-140.

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