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Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling

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Abstract

Invasive species may exhibit higher levels of growth and reproduction when environmental conditions are most suitable, and thus their effects on native fauna may be intensified. Understanding potential impacts of these species, especially in the nascent stages of a biological invasion, requires critical information concerning spatial and temporal distributions of habitat suitability. Using empirically supported environmental variables (e.g., temperature, salinity, dissolved oxygen, rugosity, and benthic substrate), our models predicted habitat suitability for the invasive lionfish (Pterois volitans) in Biscayne Bay, Florida. The use of Geographic Information Systems (GIS) as a platform for the modeling process allowed us to quantify correlations between temporal (seasonal) fluctuations in the above variables and the spatial distribution of five discrete habitat quality classes, whose ranges are supported by statistical deviations from the apparent best conditions described in prior studies. Analysis of the resulting models revealed little fluctuation in spatial extent of the five habitat classes on a monthly basis. Class 5, which represented the area with environmental variables closest to the best conditions for lionfish, occupied approximately one-third of Biscayne Bay, with subsequent habitats declining in area. A key finding from this study was that habitat suitability increased eastward from the coastline, where higher quality habitats were adjacent to the Atlantic Ocean and displayed marine levels of ambient water quality. Corroboration of the models with sightings from the USGS-NAS database appeared to support our findings by nesting 79 % of values within habitat class 5; however, field testing (i.e., lionfish surveys) is necessary to confirm the relationship between habitat classes and lionfish distribution.

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Acknowledgments

The authors thank Dr. Vanessa McDonough (Biscayne National Park), Judd Patterson (National Park Service), and Omar Abdelrahman (DERM) for generously providing raw data used as model inputs. A special thanks to Dr. Shouraseni Sen Roy (University of Miami) and Chris Hanson (University of Miami) for all of their help in constructing, formatting, and troubleshooting our GIS models. We appreciate comments of Dr. Craig Layman (North Carolina State University) and an anonymous USGS reviewer. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DG1E-0951782. Don DeAngelis was supported by the USGS’s Greater Everglades Priority Ecosystem Science program. Pam Schofield was supported by the USGS Invasives Program. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the US Government.

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Authors and Affiliations

  1. Department of Biology, University of Miami, P.O. Box 249118, Coral Gables, FL, 33124-0421, USA

    Nicholas A. Bernal, Donald L. DeAngelis & Kathleen Sullivan Sealey

  2. US Geological Survey, Department of Biology, University of Miami, P.O. Box 249118, Coral Gables, FL, 33124-0421, USA

    Donald L. DeAngelis

  3. US Geological Survey, Gainesville, FL, 32653, USA

    Pamela J. Schofield

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  1. Nicholas A. Bernal
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  2. Donald L. DeAngelis
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  3. Pamela J. Schofield
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  4. Kathleen Sullivan Sealey
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Correspondence to Nicholas A. Bernal.

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Bernal, N.A., DeAngelis, D.L., Schofield, P.J. et al. Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling. Biol Invasions 17, 1603–1614 (2015). https://doi.org/10.1007/s10530-014-0819-6

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  • DOI: https://doi.org/10.1007/s10530-014-0819-6

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