OOS 24-6 - Assessing environmental drivers of DOC fluxes in the Shark River estuary: Modeling the effects of climate, water management, and salinity

Wednesday, August 10, 2016: 3:20 PM
Grand Floridian Blrm G, Ft Lauderdale Convention Center
Peter Regier1,2, Henry Briceno2 and Rudolf Jaffé1,2, (1)Chemistry and Biochemistry, Florida International University, Miami, FL, (2)Southeast Environmental Research Center, Florida International University, Miami, FL

The Florida Everglades, comprised of freshwater marshes and mangrove estuaries has undergone over a century of drainage and development.  Current restoration efforts aim to re-establish natural hydraulic connectivity and pre-drainage ecosystem function through increased freshwater delivery, improved water quality and seasonal timing. However, it is uncertain how restoration efforts will impact downstream areas, including Everglades National Park (ENP), especially with increasing pressure from sea level rise (SLR).  As the aquatic transport of carbon, primarily as dissolved organic carbon (DOC), plays a critical role in biogeochemical cycling and food-web dynamics, a long-term understanding of the drivers of this export are critical for predicting ecosystem response to large-scale changes like climate and management.   Monthly DOC fluxes were calculated for the Shark River (ENP) and interpreted in the context of potential environmental drivers using multi-variate methods to untangle the interconnected controls of DOC export.  This was followed with simple predictive modelling of fluxes in the context of climate change scenarios.  The approach was designed to answer two key knowledge gaps for ENP: (1) what are the patterns and drivers of long-term DOC fluxes and (2) how do climate change (SLR) and water management impact DOC export?


Principle component analysis (PCA) of monthly (intra-annual) and yearly (inter-annual) data indicated that freshwater hydrology was the primary driver associated with DOC fluxes across monthly to yearly temporal scales.  Additional controls of DOC export included seasonal cycles, long-term climatic variations and extreme weather events, including hurricanes and droughts.  Stepwise linear regression selected 4 predictors of DOC flux: salinity, rainfall, inflows and the Atlantic Multidecadal Oscillation (AMO) which explained 60.4%, 20.8%, 11.1% and 7.7% of model power, respectively for a final model predicting 84.1% of DOC flux variability (p<0.0001).  Scenarios based on climate change forecasts generally predicted decreased DOC flux, largely due to reduced freshwater availability to the estuary.