Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

Hydrographic, nutrient and oxygen data from CTD bottles and beam transmission and fluorescence data from CTD profiles during R/V Point Sur PS1809 (HRR legs 1, 2, 3) at the Gulf Mexico, Louisiana and Texas coast, Sept-Oct 2017.

Nutrient Analysis Equipment and Techniques:

Nutrient samples were collected, filtered (0.2 µm Acropak-200 polyethersulfone filters, Pall) and frozen on board until analysis on shore up to 3 months later. Nutrient analyses (phosphate, silicate, nitrate+nitrite, nitrite, ammonium, and urea) were performed on a 6-channel Astoria-Pacific autoanalyzer using standard methods (WHPO 1994). Ammonia analyses were based on Solorzano (1969), using phenol/hypochlorite in alkaline medium with a sodium nitroprusside catalyst. Urea analyses were based on Aminot and Kerouel (1982) using diacetyl monoxime in acid solution.

Dissolved Oxygen Analysis Equipment and Techniques:

Samples were collected for dissolved oxygen analyses soon after the rosette was brought on board. Using a Tygon or silicone drawing tube, nominal 125 ml volume-calibrated iodine flasks were rinsed 3 times with minimal agitation, then filled and allowed to overflow for at least 3 flask volumes. Reagents (MnCl2 then NaI/NaOH) were added to fix the oxygen before stoppering. The flasks were shaken twice (> 1-minute inversions) to assure thorough dispersion of the precipitate. The lip of the flask stopper was filled with ultrapure water to prevent access to atmospheric oxygen during the up to 3 hours between sample collection and analysis.

Oxygen flask volumes were determined gravimetrically to determine flask volumes at TAMU Geochemical and Environmental Research Group (GERG). This is done once before using flasks for the first time and periodically thereafter when a suspect volume is detected.

Dissolved oxygen analyses were performed with an automated Winkler oxygen titrator (Langdon Enterprises, Miami) using amperometric end-point detection. Thiosulfate (nominally 0.01 N) was standardized against 0.01 N potassium iodate prior to sample analysis.

Salinity Analysis Equipment and Techniques:

Salinity samples were drawn into 200 mL Kimax high-alumina borosilicate bottles, which were rinsed three times with sample prior to filling to the shoulder. The bottles were sealed with plastic insert thimbles to reduce evaporation. PSS78 salinity (UNESCO 1981) was calculated for each sample from the measured conductivity ratios.

A Guildline Autosal 8400B salinometer (S/N 65715) was used for salinity/conductivity measurements. The salinity analyses were performed after samples had equilibrated to laboratory temperature, usually within 6 weeks after collection. The salinometer was standardized for each group of analyses using OSIL standard seawater, with frequent use of a secondary deep water standard to check for drift during runs.

SBE Data Processing Version 7.26.6.28 was used to process the raw Sea-Bird CTD data (.hex) into a human-readable format (.cnv). The order of functions ran via SBE Data Processing was: Data Conversion, Filter, Align CTD, Cell Thermal Mass, Loop Edit, Derive, and Bin Average.

BCO-DMO Processing Notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions (e.g., replaced spaces and hyphens with underscores)
- added columns for cruise_id, cruise_name, and chf_sci
- commented out units row

NSF Award Abstract:
Hurricane Harvey is the strongest hurricane to hit the Texas coast in decades and the resulting tidal surges, flooding and terrestrial runoff have had a severe impact on the coastal ocean. The effects on the phytoplankton, the first link in the food chain, may be unprecedented. To determine how the phytoplankton community will respond to such drastic changes in salinity, nutrient inputs, and potential toxins, immediate and continuous sampling is the only way to fully capture the effects and to identify when conditions return to "normal". An automated, continuous phytoplankton imaging instrument that is deployed on the Texas coast records images of the phytoplankton and permits calculation of the abundance of different species. Together with molecular information on the genes that have been "turned on", or expressed, outcomes of this project will help determine the responses of individual types of phytoplankton. Extreme storms are expected to increase in frequency with future climate change, so the responses identified now will be valuable in predicting how such events will affect these primary producers, which in turn support most of the food webs in marine ecosystems, in the future.

High temporal resolution observations from the Imaging FlowCytobot (IFCB) have revealed that hurricanes in the Gulf of Mexico cause drastic changes in the phytoplankton community structure. The objectives of this RAPID project are: 1) to characterize the dynamics of the phytoplankton species in relation to the environmental variables along the Texas coast; 2) to assess the short and long-term changes in the phytoplankton community; and 3) to identify the strategies of the phytoplankton community for resource acquisition. To accomplish these objectives, this project will utilize IFCB time series to follow phytoplankton community structure during the recovery period from Hurricane Harvey. In addition, two RAPID response cruises (in late September and early October) to sample at 5 sites along a transect from Galveston to Port Aransas, TX. At each station, CTD profiles and water samples from surface and the chlorophyll maximum will be collected for nutrients, carbonate chemistry, and RNA sequencing for metatranscriptomic analysis. Metatranscriptomics can provide an indication of the metabolic strategies employed and functional relationships within the plankton community in response to changes in the environment. The advantage of a metatranscriptomic approach is that the entire molecular response to the environment is captured. So, while the response of phytoplankton to increased nutrient inputs from floodwater runoff is targeted, the responses to other environmental stresses (toxics, hypoxia, acidification) are also captured. Analyses of this time series using multivariate statistical techniques, such as principal component analysis (PCA), and network analysis, a powerful technique for identifying potential interactions among taxa, will provide insights on the environmental factors and metabolic responses structuring the community during the aftermath of the hurricane.

Related data from the The Texas Observatory for Algal Succession Time-Series (TOAST) can be found at the following: https://toast.tamu.edu/timeline?dataset=HRR_Cruise