Title

Predicting risks of invasion of macroalgae in the genus Caulerpa in Florida

Authors

Authors

C. G. Glardon; L. J. Walters; P. F. Quintana-Ascencio; L. A. McCauley; W. T. Stam;J. L. Olsen

Comments

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Abbreviated Journal Title

Biol. Invasions

Keywords

Algae; Caulerpa taxifolia; chlorophyta; coastal; invasive species; prediction models; MEDITERRANEAN SEA; RACEMOSA CAULERPALES; BIOLOGICAL INVASIONS; LIGURIAN; SEA; E-COMMERCE; TAXIFOLIA; ALGA; CHLOROPHYTA; SEAGRASS; AQUARIUM; Biodiversity Conservation; Ecology

Abstract

There is worldwide concern about the aquarium strain of the green alga Caulerpa taxifolia (Vahl) C. Agardh that was introduced to the Mediterranean Sea in 1984. Since that time, it has flourished and now covers thousands of hectares of near-shore waters. More recently, aquarium strains of C. taxifolia invaded southern California and Australian waters. Our goal was to evaluate potential invasion of C. taxifolia to Florida's coastal waters. We looked for evidence of C. taxifolia-aquarium strain, as well as the present distribution of all species of Caulerpa, in Florida's near-shore waters. We surveyed 24 areas in six zones along the Floridian coastline, and evaluated the association of potential indicators for the presence of Caulerpa. Latitude, presence of seagrass beds, human population density, and proximity to marinas were the four variables simultaneously considered. Caulerpa taxifolia-aquarium strain was not found at any of our survey locations. However, 14 species of Caulerpa were found at 31 of the 132 sites visited. Percent correct for our model was 61.5% for presence and 98.1% for absence. There was a positive correlation between Caulerpa spp. and seagrass beds and proximity to marinas. There was a negative correlation with latitude and human population density. The parameters in the logistic regression model assessing the association of Caulerpa occurrence with the measured variables were then used to predict current and future probabilities of Caulerpa spp. presence throughout the state. This prediction model will allow resource managers to focus their efforts in future surveys.

Journal Title

Biological Invasions

Volume

10

Issue/Number

7

Publication Date

1-1-2008

Document Type

Article

Language

English

First Page

1147

Last Page

1157

WOS Identifier

WOS:000258704400020

ISSN

1387-3547

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