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This study determines the relationships between water flow and water quality in three types of channels in southern Florida, USA: Shark River Slough, Peace River, and Hillsboro Canal. Peace River most resembles a natural channel with floodplain connectivity, sinuosity, and uninhibited flow. Shark River Slough has a natural, shallow channel with sheet flow, while the Hillsboro Canal is the most modified channel due to dredging, straightening, and regulated flow. Hydrologic indices for each channel were estimated to characterize flow regimes and flow variability, while concentration–discharge (C–Q) relationships were determined to quantify the impact of flow regime on water quality. The greatest variability in flow occurred at the Hillsboro Canal, followed by Peace River and Shark River Slough. Connectivity to floodplains and long durations of low and high flow pulses at Peace River and Shark River Slough contributed to the dilution of water quality constituent concentrations at higher flows. Conversely, the channelized characteristics of the Hillsboro Canal resulted in an enrichment of constituents, especially during high flows. This study suggests that C–Q relationships can be used in canal discharge management to prevent water quality degradation of sensitive downstream wetland and aquatic ecosystems.

Northeast Shark River Slough (NESS), lying at the northeastern perimeter of Everglades National Park (ENP), Florida, USA, has been subjected to years of hydrologic modifications. Construction of the Tamiami Trail (US 41) in 1928 connected the east and west coasts of SE Florida and essentially created a hydrological barrier to southern sheet flow into ENP. Recently, a series of bridges were constructed to elevate a portion of Tamiami Trail, allow more water to flow under the bridges, and attempt to restore the ecological balance in the NESS and ENP. This project was conducted to determine aspects of soil physiochemistry and microbial dynamics in the NESS. We evaluated microbial respiration and enzyme assays as indicators of nutrient dynamics in NESS soils. Soil cores were collected from sites at certain distances from the inflow (near canal, NC (0–150 m); midway, M (150–600 m); and far from canal, FC (600–1200 m)). Soil slurries were incubated and assayed for CO2 emission and β-glucoside (MUFC) or phosphatase (MUFP) activity in concert with physicochemical analysis. Significantly higher TP contents at NC (2.45 times) and M (1.52 times) sites than FC sites indicated an uneven P distribution downstream from the source canal. The highest soil organic mattermore »content (84%) contents were observed at M sites, which was due to higher vegetation biomass observed at those sites. Consequently, CO2 efflux was greater at M sites (average 2.72 µmoles g dw−1 h−1) than the other two sites. We also found that amendments of glucose increased CO2 efflux from all soils, whereas the addition of phosphorus did not. The results indicate that microbial respiration downstream of inflows in the NESS is not limited by P, but more so by the availability of labile C.« less

Naturally formed forest patches known as tree islands are found within lower-statured wetland matrices throughout the world, where they contrast sharply with the surrounding vegetation. In some coastal wetlands they are embedded in former freshwater marshes that are currently exposed to saltwater intrusion and mangrove encroachment associated with accelerating sea-level rise. In this study we resurveyed tree composition and determined environmental conditions in tree islands of the coastal Florida Everglades that had been examined two decades earlier. We asked whether tree islands in this coastal transition zone were differentiated geomorphologically as well as compositionally, and whether favorable geomorphology enabled coastal forest type(s) to maintain their compositional integrity against rising seas. Patterns of variation in geomorphology and soils among forest types were evident, but were dwarfed by differences between forest and adjacent wetlands. Tree island surfaces were elevated by 12–44 cm, and 210Pb analyses indicated that their current rates of vertical accretion were more rapid than those of surrounding ecosystems. Tree island soils were deeper and more phosphorus-rich than in the adjoining matrix. Salinity decreased interiorward in both tree island and marsh, but porewater was fresher in forest than marsh in Mixed Swamp Forest, midway along the coastal gradient where tropicalmore »hardwoods were most abundant. Little decrease in the abundance of tropical hardwood species nor increase in halophytes was observed during the study period. Our data suggest that geomorphological differences between organic tree island and marl marsh, perhaps driven by groundwater upwelling through more transmissive tree island soils, contributed to the forests’ compositional stability, though this stasis may be short-lived despite management efforts.« less

The size and distribution of Phytoplankton populations are indicators of the ecological status of a water body. The chlorophyll-a (Chl-a) concentration is estimated as a proxy for the distribution of phytoplankton biomass. Remote sensing is the only practical method for the synoptic assessment of Chl-a at large spatial and temporal scales. Long-term records of ocean color data from the MODIS Aqua Sensor have proven inadequate to assess Chl-a due to the lack of a robust ocean color algorithm. Chl-a estimation in shallow and coastal water bodies has been a challenge and existing operational algorithms are only suitable for deeper water bodies. In this study, the Ocean Color 3M (OC3M) derived Chl-a concentrations were compared with observed data to assess the performance of the OC3M algorithm. Subsequently, a regression analysis between in situ Chl-a and remote sensing reflectance was performed to obtain a green-red band algorithm for coastal (case 2) water. The OC3M algorithm yielded an accurate estimate of Chl-a for deep ocean (case 1) water (RMSE = 0.007, r2 = 0.518, p < 0.001), but failed to perform well in the coastal (case 2) water of Chesapeake Bay (RMSE = 23.217, r2 = 0.009, p = 0.356). The algorithm developedmore »in this study predicted Chl-a more accurately in Chesapeake Bay (RMSE = 4.924, r2 = 0.444, p < 0.001) than the OC3M algorithm. The study indicates a maximum band ratio formulation using green and red bands could improve the satellite estimation of Chl-a in coastal waters.« less