Data Release: Modeling coastal salinity regime for biological application
Dates
Publication Date
2023-02-22
Start Date
1981-01-13
End Date
2017-12-27
Citation
Yurek, S., Reaver, N., Eaton, M., Allen, M., Chagaris, D., Martin, J., Frederick, P., and Dehaven, M., 2023, Data Release: Modeling coastal salinity regime for biological application: U.S. Geological Survey data release, https://doi.org/10.5066/P934VZ8K.
Summary
Salinity regimes in coastal ecosystems are highly dynamic and driven by complex geomorphic and hydrological processes. Estuarine biota are generally adapted to salinity fluctuation, but are vulnerable to salinity extremes. Characterizing coastal salinity regime for ecological studies therefore requires representing extremes of salinity ranges at various time scales relevant to ecology (e.g., daily, monthly, seasonally). This data release provides supporting data for the journal article titled, "Quantifying uncertainty in coastal salinity regime for biological application using quantile regression," by Yurek et al. (2022). A spatially-resolved model was developed that derives quantile distributions of salinity related to various landscape [...]
Summary
Salinity regimes in coastal ecosystems are highly dynamic and driven by complex geomorphic and hydrological processes. Estuarine biota are generally adapted to salinity fluctuation, but are vulnerable to salinity extremes. Characterizing coastal salinity regime for ecological studies therefore requires representing extremes of salinity ranges at various time scales relevant to ecology (e.g., daily, monthly, seasonally). This data release provides supporting data for the journal article titled, "Quantifying uncertainty in coastal salinity regime for biological application using quantile regression," by Yurek et al. (2022). A spatially-resolved model was developed that derives quantile distributions of salinity related to various landscape variables, such as tidal forcing, wind velocity and direction, and freshwater discharge into the Suwannee Sound estuary. The model also considers various time scales of freshwater streamflow, from daily to bi-weekly scales, which represent terrestrial watershed dynamics such as time-of-travel of overland flow from headwaters to the coast. This data release provides programming routines and supporting data for the model, including: (1) scripts used to run the model written in R programming language, (2) input data used to fit the model, and (3) model output predictions across the spatial extent of the Suwannee Sound estuary. The predictions of the model represent a method of quantifying uncertainty in predictions, and represent approximate ranges of salinity conditions. These predictions are intended for use in future ecological modeling studies and analyses of impacts of salinity uncertainty on estuarine biota. They are limited by the data set used here and are not intended to indicate exact levels for any given location or time.
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Related External Resources
Type: Related Primary Publication
Yurek, S., Allen, M., Eaton, M.J., Chagaris, D., Reaver, N., Martin, J., Frederick, P., and Dehaven, M., 2023, Quantifying uncertainty in coastal salinity regime for biological application using quantile regression: Ecosphere, v. 14, no. 4, art. e4488, https://doi.org/10.1002/ecs2.4488.
This data release provides programming routines and supporting data for quantile regression analyses of salinity regime dynamics in Suwannee Sound, FL. The data release contains (1) scripts used to run the model written in R programming language, (2) input data used to fit the model, and (3) model output predictions across the spatial extent of the Suwannee Sound estuary.
