Neural network modeling of monthly salinity variations in oyster reef in Apalachicola Bay in response to freshwater inflow and winds
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Estuarine organisms have varying tolerances and respond differently to salinity. Bottom-dwelling species such as oysters tolerate some change in salinity, but salinity outside an acceptable range will negatively affect their abundance as well as their survival within this sensitive ecosystem. Salinity in the Apalachicola Bay is heavily influenced by freshwater inflow discharged from the Apalachicola River. In this study, artificial neural network (ANN) was applied to correlate the monthly salinity variations at an oyster reef in Apalachicola Bay to the river inflow and wind. Parameters in the ANN were trained until the simulated salinity data correlated well with the observations from 2005 to 2007. Once the model is trained and optimized, the ANN structure is verified comparing the simulated data to the second dataset from 2008–2010. Four neural network training algorithms, including gradient decent, scaled conjugate gradient, quasi-Newton, and Levenberg–Marquardt, have been evaluated. The scaled conjugate gradient algorithm was selected for this study because it provides the best correlation with the value of 0.85. The verified ANN model was applied to investigate the potential impacts of freshwater reductions from upstream river on the salinity in the oyster reef. By comparing the resulting salinity from ANN model simulations to the optimal salinity range for oyster growth, the impacts of freshwater reduction scenarios on oyster growth can be examined.
KeywordsNeural network Salinity Freshwater inflow Oyster Apalachicola Bay
This research was funded in part under Award No. NA11SEC4810001 from the National Oceanic and Atmospheric Administration (NOAA) of Environmental Cooperative Sciences Center (ECSC) at Florida Agricultural & Mechanical University (FAMU). The statements and conclusions are those of the authors and do not necessarily reflect the views of NOAA-ECSC or their affiliates.
Compliance with ethical standards
Conflict of interest
The authors declare no conflict of interest.
- 1.Altunkaynak and Wang (2011) Estimation of significant height in shallow lakes using the expert system techniques. Expert Syst Appl 39(2012):2549–2559Google Scholar
- 2.Berrigan ME (1990) Biological and economical assessment of an oyster resource development project in Apalachicola Bay, FL. J Shellfish Res 9:149–158Google Scholar
- 7.Demuth H, Beale M (2009) Matlab neural network toolbox user’s guide version 6. The MathWorks Inc., NatickGoogle Scholar
- 10.Harned DA, Newcomb DJ, Hudson ET, Levine JF (1996) Salinity variation in an estuary used for oyster cultivation in Southeastern North Carolina during the passover of the eye of Hurricane Bertha [abs.]. Transactions of the American Geophysical Union 1996 Fall Meeting, December 1996, San Francisco, California, EOS, vol 77, no 46. https://nc.water.usgs.gov/albe/pubs/AGUoys.html
- 11.Haykin S (2009) Neural networks and learning machines: a comprehensive foundation. Prentice Hall, Englewood CliffsGoogle Scholar
- 20.Lenihan HS, Peterson CH (1998) How habitat degradation through fishery disturbance enhances impacts of hypoxia on oyster reefs. Ecol Appl 8:128–140. https://doi.org/10.1890/1051-0761(1998)008[0128:HHDTFD]2.0.CO;2 CrossRefGoogle Scholar
- 24.Lopez R (2017) OpenNN: Open Neural Networks Library. www.opennn.net
- 26.Mackenzie CL Jr (1970) Causes of oyster spat mortality, conditions of oyster setting beds, and recommendations for oyster bed management. Proc Natl Shellfish Assoc 60:59–67Google Scholar
- 29.NOAA National Ocean Service. Apalachicola Bay Station (2005–2010). http://tidesandcurrents.noaa.gov/station_info.shtml?stn=8728690%20Apalachicola,%20FL. Last accessed Mar 2016
- 30.National Estuarine Research Reserve System (NERRS) (2012) System-wide monitoring program. Data accessed from the NOAA NERRS Centralized Data Management Office website:www.nerrsdata.org. Accessed 01 Oct 2016
- 35.Sumich JL (1996) An introduction to the biology of marine life, 6th edn. Wm. C. Brown, Dubuque, IA, pp 255–269Google Scholar
- 37.Twichell DC, Andrews BD, Edminston HL, Stevenson WR (2007) Geophysical mapping of oyster habitats in a shallow estuary, Apalachicola Bay, FL. United States Geological Survey Open-File Report 2016-1381. http://pubs.usgs.gov/of/2006/1381/
- 39.USACE (1998) Water allocation for the Apalachicola–Chattahoochee–Flint (ACF) River Basin, main report of the draft environmental impact statement. Fed Regist 63:53023–53024Google Scholar