Dataset: Thalassinid hydraulics and oxygen dynamics

Name: Images, porewater pressure, O2 data from lab experiments of Thalassinids in different sediment types; conducted at the Pacific Coastal Ecology Branch in Newport, OR in 2009 (Infaunal Hydraulics project)
Published: 2013-05-28
License: https://creativecommons.org/licenses/by/4.0/
Keywords: oceans

Cite This Dataset

Project:

Linking infaunal hydraulic activities, porewater flow and biogeochemical processes in marine sediments (Infaunal Hydraulics)

Co-Principal Investigator:

Dr David S Wethey (University of South Carolina)

Dr Sarah A Woodin (University of South Carolina)

Contact:

Dr Nils Volkenborn (University of South Carolina)

BCO-DMO Data Manager:

Shannon Rauch (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Version Date:

2013-05-28

Validated:

Yes

Current State:

Final with updates expected

Data URL:

https://www.bco-dmo.org/dataset/3942/data

Images, porewater pressure, O2 data from lab experiments of Thalassinids in different sediment types; conducted at the Pacific Coastal Ecology Branch in Newport, OR in 2009 (Infaunal Hydraulics project)

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Description

This dataset includes results from experiments investigating the hydraulic activities of the thalassinidean ghost shrimp, Neotrypaea californiensis. Porewater pressure sensing, time-lapse photography, and planar optode imaging methods were used. Data are from three sediment types (mud, muddy sand, sand), with two shrimp per sediment type. MP4 movies and NetCDF files are avialable for download.

Quick-look files are MP4 movies with H264 codec incorporating simulateneous optode, visible light imagery and pressure records. The movie files provide a "quick look" of what exactly can be found in the NetCDF files. They contain time-lapse photography (side view or sometimes top-down view), oxygen images (in case of side view photography the oxygen images were flipped horizontally, because they were taken from the opposite side of the tanks) and porewater pressure data. The vertical red line marks the time point in the 20 min pressure record that corresponds to the images.

NetCDF optode files include optode imagery as time-resolved matrices, and a time series of pressure records. Oxygen images are matrices of percent air saturation values. 10 hour time series were split in four 2.5 hour blocks. All times are in unix format (seconds since 1970-01-01).

NetCDF Nikon files include visible light imagery as time-resolved matrices and a time series of pressure records. Nikon images are matrices of 24 bit RGB values. 10 hour time series were split in four 2.5 h blocks. Nikon images are matrices of 24 bit RGB values. All times are in unix format (seconds since 1970-01-01).

For details see:
Volkenborn N., Polerecky L., Wethey D.S., DeWitt T.H., Woodin S.A (2012) Hydraulic activities by ghost shrimp Neotrypaea californiensis induce oxic-anoxic oscillations in sediments. Marine Ecology Progress Series 455: 141-156. DOI: 10.3354/meps09645

Acquisition Description

Measurements were conducted in a tank (50 cm wide, 57 cm high, 3.1 cm deep) containing approx. 47 cm sediment with 10 cm of overlying water (overlying water flow rate = 20 to 60 mL per minute). The pressure sensor was located 25 cm deep in the sediment on the right side of the tank. Images were taken at 30 second intervals.

Experiments were conducted at the Pacific Coastal Ecology Branch, Western Ecology Division, US Environmental Protection Agency, Newport, Oregon 97365, USA.

Planar Optode Imaging:
The lifetime imaging system is modified after Holst and Grunwald (2001). It comprises a cooled CCD camera (pco.1600MOD, PCO AG, Donaupark 11, 93309 Kelheim, Germany), a pulse delay generator (T560, Highland Technology, 18 Otis St, San Francisco CA), an array of blue-light emitting diodes (LEDs; lambda max = 455 nm, LXHL-LR5C, Philips Lumileds, 370 W Trimble Rd, San Jose, CA) attached to a heat sink (~5×5×2.5 cm), and a custom-made power supply. The camera accumulates multiple exposures with a programmable modulation time. By using the output of the exposure synchronization of the camera as a trigger for the pulse delay generator and subsequently the LED light pulse, any jitter between the camera exposure time and the preceding light flash can be avoided. The timing parameters is chosen as follows. After the LED pulse of 20 µs duration and a given delay, delta, the electronic shutter for camera exposure opens for D = 10 µs. The delays of delta_1 = 1 µs and delta_2 = 11 µs are applied for the accumulation of the first (I1) and second (I2) intensity window images (gates), respectively, which are acquired sequentially. Summing up all times to 41 µs for the longest delay reveals the minimum time interval for the accumulations of single exposures. Typically an interval of 44 µs is chosen, corresponding to a repetition rate of almost 23 kHz. Using the first and second intensity window images, the luminescence lifetime image is calculated as t = D/ln(I1/I2) (Holst and Grunwald 2001). The peak current through the LEDs (typically 200–300 mA) and the integration time during which both intensity windows are accumulated (typically 250–1000 ms) are adjusted to optimize image quality. The control of the camera and image acquisition through the IEEE 1394 (firewire) interface, and of the delay pulse generator through the RS232 (serial) interface, are done by a laptop computer using software developed by Lubos Polercky (Microsensors Group, Max Planck Institute for Marine Microbiology, Bremen, 28359, Germany) and Uli Henne (German Aerospace Center, Institute of Aerodynamics and Flow Technology, Göttingen, 37073, Germany) in Borland Delphi and C++. Optodes were calibrated using the lifetime values measured in the anoxic sediment and in the air-saturated overlying water. For details see Matsui, GY et al. 2011.

Porewater Pressure Sensing:
The differential pressure sensors (Honeywell 27PC) are piezoresistive bridges that provide a differential voltage proportional to the pressure difference between the 2 sides of the sensor. While one side of the sensor is indirect contact with the sediment porewater (gage pressure), the ambient (hydrostatic) pressure isdetected within a water-filled space within the PVC channels (plenum) that is in direct contact with the overlying water and isolated from the porewater. Data are typically collected at 200 Hz using autonomous 8-channel 16-bit data loggers (CF2, Persistor Instruments, 153-A Lovells Lane, Marston Mills MA). Amplifiers on the boards allow adjustment of the dynamic range of the sensors. Sensors are calibrated by varying the water heights on both sides of the sensors, i.e. the plenum and sediment side. Twelve positive and negative pressures are typically applied to each sensor, and the linear calibration between the gauge pressure and measured voltage has typically R2 > 0.95. The 200 Hz raw data are downscaled to 1Hz by taking the median of all values in each 1-second interval. The median of each 60 minute block was calculated, and linearly interpolated values of this median time series was subtracted from each 1Hz data value to remove long term drift from the signals.

Time-lapse photography:
Images of the shrimp tanks are taken with digital SLR cameras (Nikon D200 and D300) using flash, triggered by time-lapse controllers (Digi-Snap, Harbortronics) or by a digital delay generator (T560 Highland Technology). Images are typically taken at 15 to 30 s intervals.

Related files and references:
Optode system:
Matsui, GY, N Volkenborn, L Polerecky, U Henne, DS Wethey, CR Lovell, SA Woodin. 2011. Mechanical imitation of bidirectional bioadvection in aquatic sediments. Limnology and Oceanography: Methods 9: 84-96. DOI: 10.4319/lom.2011.9.84

These data are related to Figures 4, 5, and 6 in the following paper:
Volkenborn, N, L Polerecky, DS Wethey, TH DeWitt, SA Woodin. 2012. Hydraulic activities by the ghost shrimp Neotrypaea californiensis induce oxic-anoxic oscillations in sediments. Marine Ecology Progress Series 455: 141-156. DOI: 10.3354/meps09645

Processing Description

Data Processing:
Programs in R statistics language that were used to make the netcdf files:
parms_090608_EPA_lab_h1_Molli_1_Neo_sand1_500_1700.r
parms_090608_EPA_lab_h2_Molli_1_Neo_mud1_2520_3720.r
parms_090620_EPA_lab_h1_Molli_3_Neo_mud_3900_5100.R
parms_090620_EPA_lab_h1_Molli_3_Neo_sand_2690_3890.R
parms_090626_EPA_lab_h1_Molli_4_Neo_sand2_30_630.r
parms_090627_EPA_lab_h1_Molli_4_Neo_sand2_100_700.r
parms_090627_EPA_lab_h1_Molli_4_Neo_sand_0_1200.R
plot_optode_nikon_pressure_2_ncdf_avi_readparms_090608_500_1700_sand.r
plot_optode_nikon_pressure_2_ncdf_avi_readparms_090608_2520_3720_mud.r
plot_optode_nikon_pressure_2_ncdf_avi_readparms_090620_2690_3890.R
plot_optode_nikon_pressure_2_ncdf_avi_readparms_090620_3900_5100_mud.R
plot_optode_nikon_pressure_2_ncdf_avi_readparms_090626_sand_right.r
plot_optode_nikon_pressure_2_ncdf_avi_readparms_090627_sand_right.r

More Information about this dataset

Funding Sources

Funding Source	Award Number
NSF Division of Ocean Sciences	OCE-0928002

Deployments

Deployment	Synonyms	Start Date	Platform	Investigator
lab_EPA_WED_2009		2009-06-03	Pacific Coastal Ecology Branch	Dr David S Wethey (Co-Principal Investigator) Dr Sarah A Woodin (Co-Principal Investigator)	data info

Instruments

Camera

(more info)

Short Name: camera

Community Standard Description

Generic Description

All types of photographic equipment including stills, video, film and digital systems.

PI supplied instrument name: Camera

Dataset-specific description

Images of the tanks are taken with digital SLR cameras (Nikon D200 and D300) using flash, triggered by time-lapse controllers (Digi-Snap, Harbortronics) or by a digital delay generator (T560 Highland Technology).

Parameters

Supplied Name	Supplied description	Supplied Units	Standard Name
species	Name of the species.	text	species
date_exp	Date of the experiment.	mmddYYYY	date
time_start	Time when the experiment began, in hours and minutes (24-hour clock).	HHMM	time_begin
time_end	Time when the experiment ended, in hours and minutes (24-hour clock).	HHMM	time
duration	Duration of the experiment.	dimensionless	unknown
date_shrimp_added	Date when the shrimp was added to the experimental tank.	mmddYYYY	date
time_shrimp_added	Time when the shrimp was added to the experimental tank, in hours and minutes (24-hour clock).	HHMM	time
len_shrimp	Carapace length of the shrimp.	centimeters	length
press_sensor	Identification of the pressure sensor.	text	instrument
press_sensor_location	Description of where the pressure sensor was located within the experimental tank.	text	unknown
sediment_type	Type of sediment in the experimental tank: mud, muddy sand, or sand.	text	unknown
sediment_permeability	Permeability of the sediment in the experimental tank (10^-12 m^2).	10^-12 square meters	unknown
sediment_pot_O2	Sedimentary potential volumeteric O2 consumption (in umol cm-3 h-1).	umol per cubic centimeter per hour	unknown
sediment_porosity	Sediment porosity.	vol fraction	porosity
tot_org_matter	% weight total organic matter.	% weight	unknown
movie	Link to the movie (mp4) file. Movies provide a "quick look" of what is in the NetCDF files, incorporating simultaneous visible light and optode imagery and pressure records. The vertical red line marks the time point in the 20 min pressure record that corresponds to the images.	dimensionless	unknown
nikon_NetCDF_files	Link to the Nikon NetCDF files (.zip). Nikon NetCDF files include visible light imagery as time-resolved matrices, and a time series of pressure records. 10 hour time series were split in four 2.5 h blocks. Nikon images are matrices of 24 bit RGB values. All times are in unix format (seconds since 1970-01-01).	dimensionless	unknown
O2_NetCDF_files	Link to the NetCDF optode files, which include optode imagery as time-resolved matrices, and a time series of pressure records. Oxygen images are matrices of percent air saturation values. 10 hour time series were split in four 2.5 hour blocks. All times are in unix format (seconds since 1970-01-01).	dimensionless	unknown
R_files	Link to R files, which show how the NetCDF files were created.	dimensionless	unknown

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Dataset: Thalassinid hydraulics and oxygen dynamics