| Contributors | Affiliation | Role |
|---|---|---|
| Heil, Cynthia | Mote Marine Laboratory (Mote) | Principal Investigator |
| Glibert, Patricia A. | University of Maryland Center for Environmental Science (UMCES/HPL) | Co-Principal Investigator |
| Hall, Emily | Mote Marine Laboratory (Mote) | Co-Principal Investigator |
| Li, Ming | University of Maryland Center for Environmental Science (UMCES/HPL) | Co-Principal Investigator |
| Rauch, Shannon | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Sampling Plan: Four sampling efforts were conducted (May 2023, August 2023, September 2023, October 2024), focusing on five stations located from Charlotte Harbor to the adjacent inner West Florida Shelf (WFS) system directly impacted by Hurricane Ian and the resulting plumes using Mote's R/V Mote (42 ft). At each station, water column CTD profiles of temperature, salinity, dissolved oxygen, and pH were made, and discrete surface and bottom water samples were collected by rosette-mounted Niskin bottles and analyzed for the parameters and rates listed in Table 1. Sample processing occurred on board or immediately after return to the laboratory. Net community production and oxygen utilization rates were calculated using observed O2 differences at hour intervals after air-sea O2 corrections (e.g., Wang et al. 2017). The balance between ecosystem respiration and production, the net community production, yielded a measure of the net autotrophic or heterotrophic ecosystem state (Hopkinson and Smith 2005). The carbonate and nutrient suite and rate process measurements (including uptake and regeneration rates) and direct measurements of organic matter respiration allowed an assessment of how nutrient availability and forms influence hypoxia and how hurricane inputs influence carbonate chemistry in this system, specifically the connection between acidification and hypoxia (e.g. O2 vs. pH relationships).
Analytical Methods: See Table 1 (supplemental file).
- Imported the original CSV file "Heil & Hall RAPID Chemical and BIological Data -FINAL as CSV.csv" into the BCO-DMO processing system.
- Renamed columns via a series of regex substitutions to remove/replace special characters: spaces to underscores, commas removed, closing parentheses removed, opening parentheses removed, "@" replaced with "at", periods removed, "/" replaced with underscore, hyphens replaced with underscore, ">" replaced with "gt", "+" replaced with "plus". These are requirements of BCO-DMO's naming conventions.
- Split column "Date_Collected_Time_Zone" into new columns "Date_Collected" and "Time_Zone", deleting the original input column.
- Converted column "Date_Collected" from string format "%m/%d/%Y" to date type with output format "%Y-%m-%d".
- Applied find/replace to column "Total_Karenia_species" to remove commas from numeric values.
- Set data types for all columns.
- Renamed column "Tital_Dinoflagellates" to "Total_Dinoflagellates".
- Saved the final file in CSV format as "1003828_v1_chem_bio_post-ian.csv".
| Parameter | Description | Units |
| Sample_depth_surface_bottom | S=surface (Niskin bottle at surface), B=bottom (Niskin bottle 0.5 m above bottom), specific S and B depth for each station are in CTD DEPTH column | unitless |
| Client_ID | Funding agency | unitless |
| SampID | Station Identification | unitless |
| Latitude_1 | Latitude | decimal degrees |
| Longitude_1 | Longitude | decimal degrees |
| Date_Collected | Date (EDT) | unitless |
| Time_Zone | Time Zone | unitless |
| Tag_Number | Mote internal ID number | unitless |
| Nitrogen_Ammonia_as_N_Diss_mg_L | Ammonium | mg L-1 |
| Nitrogen_Ammonia_as_N_Diss_uM | Ammonium | uM |
| Nitrogen_Nitrate_Nitrite_as_N_Diss_mg_L | Nitrate + Nitrite | mg L-1 |
| Nitrogen_Nitrate_Nitrite_as_N_Diss_uM | Nitrate + Nitrite | uM |
| Nitrogen_Particulate_ug_L | Particulate Nitrogen | ug L-1 |
| Nitrogen_Particulate_uM | Particulate Nitrogen | uM |
| Nitrogen_Total_Diss_mg_L | Total Dissolved Nitrogen | mg L-1 |
| Nitrogen_Total_Diss_uM | Total Dissolved Nitrogen | uM |
| Phosphorus_Orthophosphate_as_P_Diss_mg_L | Orthophosphate | mg L-1 |
| Phosphorus_Orthophosphate_as_P_Diss_uM | Orthophosphate | uM |
| Phosphorus_Particulate_ug_L | Particulate Phosphorus | ug L-1 |
| Phosphorus_Particulate_uM | Particulate Phosphorus | uM |
| Phosphorus_Total_Diss_mg_L | Total Dissolved Phosphorus | mg L-1 |
| Phosphorus_Total_Diss_uM | Total Dissolved Phosphorus | uM |
| Silica_as_SiO2_Diss_mg_L | Silica (as SiO2, dissolved) | mg L-1 |
| Silica_as_SiO2_Diss_uM | Silica (as SiO2, dissolved) | uM |
| Silica_particulate_as_SiO2_ug_L | Particulate Silica | ug L-1 |
| Silica_particulate_as_SiO2_uM | Particulate Silica | uM |
| Organic_Carbon_Dissolved_mg_L | dissolved organic carbon | mg L-1 |
| Organic_Carbon_Dissolved_uM | dissolved organic carbon | uM |
| Carbon_Particulate_ug_L | Particulate Carbon | ug L-1 |
| Carbon_Particulate_uM | Particulate Carbon | uM |
| CDOM_Abs_at_280_nm | Colored Dissolved Organic Material Absorption at 280 nm | unitless |
| CDOM_Abs_at_312_nm | Colored Dissolved Organic Material Absorption at 312 nm | unitless |
| CDOM_Abs_at_350_nm | Colored Dissolved Organic Material Absorption at 350 nm | unitless |
| CDOM_Abs_at_374_nm | Colored Dissolved Organic Material Absorption at 374 nm | unitless |
| CDOM_Abs_at_376_nm | Colored Dissolved Organic Material Absorption at 376 nm | unitless |
| CDOM_Abs_at_400_nm | Colored Dissolved Organic Material Absorption at 400 nm | unitless |
| CDOM_Abs_at_412_nm | Colored Dissolved Organic Material Absorption at 412 nm | unitless |
| CDOM_Abs_at_430_nm | Colored Dissolved Organic Material Absorption at 430 nm | unitless |
| CDOM_Abs_at_440_nm | Colored Dissolved Organic Material Absorption at 440 nm | unitless |
| Chlorophyll_a_free_of_pheophytin | Chlorophyll a (without phaeopigments) | ug/L |
| CTD_DEPTH | sample depth measured by CTD | meters (m) |
| CTD_DO | dissolved oxygen concentration from CTD | mg L-1 |
| CTD_FLUOR | Fluorescence from CTD | unitless |
| CTD_PAR | Photosynthetically active radiation | µmol photons m-2 s-1 |
| CTD_SAL | Salinity from CTD | PSU |
| CTD_TEMP | Temperature from CTD | degrees Celsius |
| CTD_TURB | Turbidity from CTD | NTU |
| Total_Karenia_species | Concentration of all Karenia species | cells L-1 |
| Total_Phytoplankton | Concentration of all phytoplankton | cells L-1 |
| Total_Dinoflagellates | Concentration of all dinoflagellates | cells L-1 |
| Total_Diatoms | Concentration of all diatoms | cells L-1 |
| Total_Other_Plankton | Concentration of all flagellates (excluding dinoflagellates) | cells L-1 |
| Total_Cyanobacteria | Concentration of all cyanobacteria | cells L-1 |
| Latitude_2 | geographic coordinate specifying the north-south position of a point on Earth's surface | degrees |
| Longitude_2 | angular distance of a point east or west of the Prime Meridian (0°), | degrees |
| Sigma_t | seawater density | kg/m3 |
| Aragonite_saturation_state | Aragonite saturation state | unitless |
| Bicarbonate | Bicarbonate | µM Kg SW-1 |
| Borate_Alkalinity | Borate Alkalinity | µM Kg SW-1 |
| Calcite_saturation_state | Calcite saturation state | unitless |
| Carbon_dioxide_fugacity | effective partial pressure of CO2 | µAtm |
| Carbonate | Carbonate | µM Kg SW-1 |
| Dissolved_carbon_dioxide | Dissolved carbon dioxide | µM Kg SW-1 |
| Hplus_in | Hydrogen ion concentration | unitless |
| Hydroxide_alkalinity | Hydroxide alkalinity | µM Kg-1 |
| Organic_Alkalinity_calculated | Organic Alkalinity, calculated | µM Kg SW-1 |
| Partial_pressure_of_carbon_dioxide | Partial pressure of carbon dioxide | µAtm |
| Revelle | ratio of instantaneous change in carbon dioxide (CO 2 ) to the change in total dissolved inorganic carbon | unitless |
| Total_Alkalinity | Total Alkalinity | µM Kg-1 |
| Total_Alkalinity_calculated | Total Alkalinity, calculated | µM Kg-1 |
| Total_Dissolved_Inorganic_Carbon | Total Dissolved Inorganic Carbon | µM Kg-1 |
| Total_pH_calculated | Total pH, calculated | Calculated (Units) |
| Total_pH_measured | Total pH, measured | Calculated (Units) |
| BLANK_CORR_Photosynthetic_rate | blank corrected, O2 based photosynthetic rate | µmol O2 L-1 hr-1 |
| BLANK_CORR_Respiration_rate | blank corrected, O2 based respiration rate | µmol O2 L-1 hr-1 |
| Phosphorus_Uptake | 33PO4 uptake rate of >0.7 um fraction | uM L-1 hr-1 |
| Phosphorus_Regeneration_Bulk_whole_water | 33Phosphorus Regeneration rate of whole water | uM L-1 hr-1 |
| Phosphorus_Regeneration_gt07_um | 33Phosphorus Regeneration rate of >0.7 um fraction | uM L-1 hr-1 |
| TChl_a | HPLC Pigment -Total Chlorphyll a | ug L-1 |
| TChl_b | HPLC Pigment -Total Chlorphyll b | ug L-1 |
| TChl_c | HPLC Pigment -Total Chlorphyll c | ug L-1 |
| Caro | HPLC Pigment -alphas + beta carotene | ug L-1 |
| But_fuco | HPLC Pigment - 19′-butanoyloxyfucoxanthin | ug L-1 |
| Hex_fuco | HPLC Pigment - 19′-hexanoyloxyfucoxanthin | ug L-1 |
| Allo | HPLC Pigment -Alloxanthin | ug L-1 |
| Diad | HPLC Pigment -diadinoxanthin | ug L-1 |
| Diato | HPLC Pigment - diatoxanthin | ug L-1 |
| Fuco | HPLC Pigment - fucoxanthin | ug L-1 |
| Perid | HPLC Pigment -peridinin | ug L-1 |
| Zea | HPLC Pigment - zeaxanthin | ug L-1 |
| Chl_a | HPLC Pigment - Chlorophyll a | ug L-1 |
| DVVChl_a | HPLC Pigment - Divinyl Chlorophyll a | ug L-1 |
| Chlide_a | HPLC Pigment - chlorophyllide a | ug L-1 |
| Chl_b | HPLC Pigment - Chlorophyll b | ug L-1 |
| DVChl_b | HPLC Pigment - divinyl chlorophyll b | ug L-1 |
| Chl_c12 | HPLC Pigment - Chlorophyll c1, 2 | ug L-1 |
| Chl_c3 | HPLC Pigment - Chlorophyll c3 | ug L-1 |
| Lut | HPLC Pigment - lutein | ug L-1 |
| Neo | HPLC Pigment - neoxanthin | ug L-1 |
| Viola | HPLC Pigment - violaxanthin | ug L-1 |
| Phytin_a | HPLC Pigment - Phaeophytin a | ug L-1 |
| Phide_a | HPLC Pigment - Chlorophyllide a | ug L-1 |
| Pras | HPLC Pigment - prasinoxanthin | ug L-1 |
| Gyr_diester | HPLC Pigment - Gyroxanthin diester | ug L-1 |
| Dataset-specific Instrument Name | Bran+Luebbe/Seal AA3 |
| Generic Instrument Name | Bran+Luebbe / SEAL Analytical AutoAnalyzer 3 (AA3) continuous-flow analyzer |
| Generic Instrument Description | The AutoAnalyzer 3 (AA3) is a segmented continuous-flow analyzer (continuous flow analyzer, CFA) used for automated colorimetric analysis of dissolved nutrients and other analytes in environmental, seawater, freshwater, wastewater, soil, and agricultural samples. The AA3 was originally manufactured by Bran+Luebbe and, following acquisition of the product line in 2006, has continued to be manufactured and supported by SEAL Analytical. The AA3 is the third-generation instrument in the Technicon AutoAnalyzer family and is widely used for determination of nitrate, nitrite, ammonium, phosphate, silicate, and other dissolved nutrients. See the description from the manufacturer. |
| Dataset-specific Instrument Name | Apollo SciTech DIC Analyzer |
| Generic Instrument Name | Inorganic Carbon Analyzer |
| Generic Instrument Description | Instruments measuring carbonate in sediments and inorganic carbon (including DIC) in the water column. |
| Dataset-specific Instrument Name | Niskin bottle |
| Generic Instrument Name | Niskin bottle |
| Dataset-specific Description | At each station, water column CTD profiles of temperature, salinity, dissolved oxygen, and pH were made, and discrete surface and bottom water samples were collected by rosette-mounted Niskin bottles. |
| Generic Instrument Description | A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24, or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc. |
NSF Award Abstract:
Many coastal systems are facing the threats of continuing development and climate change, including an increased intensity of extreme weather events such as hurricanes. Such storms are now wetter than in prior years because warmer atmospheres hold more moisture. Thus, they release more rainfall and deliver more nutrients and organic matter to coastal areas. This, in turn, leads to phytoplankton blooms with potential for regional “dead zones” or areas with little or no dissolved oxygen. Hurricane Ian, a category 4 hurricane which hit southwest Florida in late September 2022, resulted in immense nutrient and organic carbon inputs to the coastal estuaries and southwest Florida shelf waters and presents an opportunity to examine the effects of a major storm disturbance on a coastal system that is under increasing coastal nutrient stress. The objective of this RAPID project is to examine carbon and nutrient cycling along a gradient of stations from the estuary to low-nutrient shelf waters to determine the rate of change and recovery in this system and the relationship of large hurricane inputs to hypoxia, anoxia, and ocean acidification. These data are being used to develop a regional model to predict the impact of future hurricanes on ocean acidification, phytoplankton blooms, and local hypoxia and anoxia. This study leverages ongoing monitoring programs funded by state and federal management agencies, as well as NSF-supported programs for undergraduate students. It provides partial support for training of postdoctoral investigators and a graduate student. Outreach will include presentations to elementary and high school students.
In September 2022, southwest Florida experienced a direct hit from category-4 Hurricane Ian, resulting in extensive watershed flooding and nutrient- and dissolved-organic-matter-laden estuarine plumes extending more than 50 miles onto the shallow oligotrophic west Florida shelf (WFS). The massive terrestrial organic carbon and nutrient inputs to the southwest Florida coastal and shelf region may be priming this oligotrophic system for extensive phytoplankton blooms, as well as significant changes in carbon chemistry and nutrient cycling that could lead to longer-term regional hypoxia and anoxia. In this RAPID project, the investigators are measuring a suite of carbon and nutrient parameters, as well as carbon and nutrient cycling, at stations in Charlotte Harbor and the adjacent inner WFS system in December 2022, February 2023, and September 2023. The objectives are to assess: 1) a timescale of system responses from shorter (weeks to months) to 1-year impacts post-hurricane; 2) how nutrient availability and forms influence hypoxia; and 3) how hurricane-driven inputs influence carbonate chemistry in this system, specifically the connection between acidification and hypoxia. The investigators are using new data collected in this study and monitoring data from regional state and federal programs in a coupled hydrodynamic-biogeochemical model to understand conditions on the WFS. Hindcast simulations and modeling experiments are assessing how large inputs of nutrients and organic matter affect phytoplankton, oxygen conditions, and carbon chemistry. Modeling experiments are exploring how storms of varying wind and precipitation intensity affect the WFS and estuaries, identifying the tipping point at which the WFS switches from episodic to persistent hypoxia.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
| Funding Source | Award |
|---|---|
| NSF Division of Ocean Sciences (NSF OCE) |