Contributors | Affiliation | Role |
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Monismith, Stephen G. | Stanford University | Principal Investigator |
Woodson, Clifton Brock | University of Georgia (UGA) | Co-Principal Investigator |
Fong, Derek | Stanford University | Scientist |
Daly, Margaret | Stanford University | Student |
York, Amber D. | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Location: Isla Natividad, Baja California, Mexico (27º53.215 N, 115º11.325 W depth 15-30m)
From July - Aug of 2018, numerous instruments were deployed around Isla Natividad in Baja California Mexico. These included CTD’s which were attached to a steel cable thermistor chain. CTD’s were 1 meter above the bottom, vertically attached.
Folders and filenames included in this dataset contain transect and target depth identifiers.
Prefix letters represent a cross-shore transect line and the 2 numerals represent the approximate target depth of a mooring along that line. There were 4 transects (LG,PP, MP, BB) and moorings were targeted at 15, 20, and 25m on each transect. For example "BB15" indicates transect BB and target mooring depth of 15m. See the supplemental file "deploy_info.csv" for a list of transect-mooring deployments included in this dataset.
MATlab 2019 b is used for all QA/QC and processing. The following steps are taken for QA/QC
- NaN if salinity > 5* the standard deviation
- NaN if temperature > 5* the standard deviation
- NaN if DO > 5* the standard deviation
BCO-DMO Data Manager Processing Notes:
File |
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CTD data filename: CTD.zip (ZIP Archive (ZIP), 10.09 MB) MD5:6b5aa87c0042ac6d318f2f694169e4bb CTD data. Contains matlab .mat files and txt files containing exported vectors from the .mat file. This file bundle contains subfolders named by deployment ID (transectID+target_depth). Each folder contains a file ending with _Info.txt which contains deployment information such as start and end time, lat,lon, depth, units. Within each folder is the .mat file for the deployment containing a structure "DATA" % example DATA struct % DATA 1x1 5247936 struct % % Temp: [1×163977 double] % Sal: [1×163977 double] % Depth: [1×163977 double] % Time: [1×163977 double] Units: temperature (Celcius), Salinity (psu), depth (m), DO (mg/L) Time is a matlab datenum type in time zone Mountain Time (MT). |
File |
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Deployment Information filename: deploy_info.csv (Comma Separated Values (.csv), 5.04 KB) MD5:85b804862d2c8f74418595fe27222216 Deployment Information for transects and moorings. Columns (parameter) info: Data_Type, Data type collected (e.g. MiniDOT,CTD) Deployment_ID, Deployment identifier. Prefix letters represent a cross-shore transect line and the 2 numerals represent the approximate target depth of a mooring along that line. Transect_ID, There were 4 transects (LG,PP, MP, BB). Target_Depth, Moorings targed deployment depth along transect. Targeted at 15, 20, and 25m on each transect. Start_Date,Start Date local time zone (MT) in format "%d-%b-%Y %H:%M:%S" End_Date, End Date local time zone (MT) in format "%d-%b-%Y %H:%M:%S" Time_Zone, Timezone (MT, mountain time) used for Start_Date and End_Date ISO_DateTime_UTC_Start, Start Date time zone UTC in ISO 8601 format "%Y-%m-%dT%H:%M:%SZ" Latitude, latitude in decimal degrees Longitude, longitude in decimal degrees Units,units used for the data type Depth, notes "Bottom(seafloor) or no value" |
Dataset-specific Instrument Name | |
Generic Instrument Name | CTD Sea-Bird MicroCAT 37 |
Generic Instrument Description | The Sea-Bird MicroCAT CTD unit is a high-accuracy conductivity and temperature recorder based on the Sea-Bird SBE 37 MicroCAT series of products. It can be configured with optional pressure sensor, internal batteries, memory, built-in Inductive Modem, integral Pump, and/or SBE-43 Integrated Dissolved Oxygen sensor. Constructed of titanium and other non-corroding materials for long life with minimal maintenance, the MicroCAT is designed for long duration on moorings.
In a typical mooring, a modem module housed in the buoy communicates with underwater instruments and is interfaced to a computer or data logger via serial port. The computer or data logger is programmed to poll each instrument on the mooring for its data, and send the data to a telemetry transmitter (satellite link, cell phone, RF modem, etc.). The MicroCAT saves data in memory for upload after recovery, providing a data backup if real-time telemetry is interrupted. |
NSF Award Abstract:
Oceanographic variability is increasingly recognized as a driver of change in marine ecosystems. Understanding the effects of this oceanographic variability and its extremes on organisms, populations, ecosystems and the critical services they deliver is of great scientific interest and pivotal for resource management and policy. The overarching goal of this project is to determine how small-scale heterogeneity in habitat quality and site-specific vulnerability to extreme oceanographic conditions might help identify safe spaces and protect coastal populations and fisheries from the detrimental effects of increasing frequency, intensity and durations of extreme oceanographic conditions. This project will combine detailed nearshore oceanographic studies with ecological experiments and coupled biophysical modeling to advance understanding of the drivers of local oceanographic variability and consequent effects on coastal marine animals. The research will determine how multiple, potentially stressful, environmental drivers co-vary in the field and how such variation affects the population dynamics of coastal species. Specifically, this project will provide key insights regarding how changes in ocean acidification, dissolved oxygen and temperature will affect green and pink abalone, an ecologically and economically important resource in the southern California Current. Team members will work with partner non-governmental organizations, resource agencies, and fishing cooperative federations to disseminate results and incorporate data and insights into fisheries management and adaptation initiatives in Baja California, Mexico and in California, USA. This project will also support the training and professional development of underrepresented groups at the high school, undergraduate, graduate and postdoctoral levels through direct involvement in research, intensive courses and international workshops.
Despite large-scale drivers and regional perturbations, local variability in ocean conditions may be a major driver of the overall performance and vulnerability of coastal marine species. Research performed as part of this project will test two specific hypotheses: (1) The relative influences of upwelling versus tides, as mediated by coastal geometry and structural complexity associated with rocky reefs and kelp forests act to create high local variability in physical conditions, at scales of 10s-1000s meters; and (2) Local variability in oceanographic conditions results in high local patchiness in the performance of sedentary marine organisms, providing for safe spaces in the face of escalating heat waves, hypoxia, and acidification, that have caused recent mass mortalities in multiple species across the California Current region. Integrated oceanographic-ecological field studies will be conducted along the coast of Baja California, Mexico, using green and pink abalone (Haliotis fulgens, H. corrugata) as model species. Complementary laboratory experiments will evaluate how different exposure regimes (frequency, intensity and duration of high temperature, and/or low dissolved oxygen and acidity events) may affect the demography and persistence of abalone populations under current and future environments. Coupled biophysical and population models will integrate results from the field and laboratory experiments to understand how local variability in ocean conditions affects population dynamics over longer periods. The research will advance the understanding of factors affecting the resilience coastal species by (1) ascertaining how large-scale oceanographic phenomena manifest in ocean conditions (dissolved oxygen, acidity, temperature) at local scales that are most relevant to coastal marine ecosystems and (2) determining the effects of current, and expected future, ocean conditions and variability on important marine species.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |