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Sea Nettles Habitat

The habitat of a species is defined by multiple physical and biotic parameters. Though salinity and temperature were known to be important physical factors influencing the presence of sea nettles, a quantitative relationship between these variables has not been previously formulated for the entire Chesapeake Bay. We developed a bay-wide model to predict the probability of encountering sea nettles and their density in surface waters of the Chesapeake Bay by analyzing coincident data of nettle density, salinity and sea-surface temperature collected during the spring, summer and fall of 1987-2000 in surface waters of the bay and selected tributaries.

Concentrations of Chrysaora were found within a relatively narrow, well-defined range of temperature and salinity (26-30 °C and 10-16 PSU, Fig. 1).

Nettle Density

Figure 1. Plot illustrating the salinity and sea-surface temperatures encompassing 95% of the sea nettle densities in surface waters of the Chesapeake Bay.

The in-situ data were used to derive an empirical model that estimates the likelihood of sea nettle encounter, pnettles, as a function of salinity and temperature (Fig. 2):

pnettles = elogit / [elogit + 1],

where logit = -6.995 + (0.30 * temperature) - (0.469 *salinityopt).

Temperature is in degrees celsius and salinityopt is the difference between ambient salinity and optimal salinity for nettles (= 13.5 psu) as determined from in-situ observations.

A graphical representation of this model is presented below in Figure 2.

Nettle Density

Figure 2. Graphical representation of the model describing the likelihood of encountering sea nettles in surface waters of Chesapeake Bay.

 

Please send your comments to Christopher Brown.

 

This project represents collaboration between scientists of the National Oceanic and Atmospheric Administration , Yale University, Shannon Point Marine Center and the University of Maryland Center for Environmental Science. Funding for this project was provided by the NOAA Ocean Remote Sensing Program, the NOAA Center for Sponsored Coastal Ocean Research EcoForecasting Program and Maryland SeaGrant.

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