Table of Contents

• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

Physical data collected by at towed plankton imaging system in a subtropical, pelagic environment; collected on R/V Walton Smith cruises, WS1406 and WS15161.

Status note: These data are restricted from public access until the related manuscript has been published.

The In Situ Ichthyoplankton Imaging System (ISIIS) is a high resolution imaging system designed to image sufficient volumes of water to accurately quantify rare meso- and macroplankton such as fish and crab larvae, and also associated plankters (e.g., ctenophores, larvaceans, euphausiids, chaetognaths, hydrozoans, scyphozoans, pteropods, copepods) in situ (Cowen & Guigand 2008). An additional, finer scale imaging system has been added to the current system (ISIIS-2) and is capable of imaging up to 140 L per second, with pixel resolution of 45-68 um. This yields particle resolution down to ~ 450 um, adding considerable breadth to the full size range of organisms that can be detected and enumerated. The ISIIS is also instrumented with a set of environmental sensors including: Seabird CTD (SBE 49), Biospherical PAR (QCP2300), Seabird dissolved O2 (SBE 43), and Wet Labs Fluorometer (ECO). All data are passed via fiber optic cable to an onboard computer, time-stamped for cross-referencing, and saved on a high-speed disk array. Oxygen data from 2014 were excluded as they were found to be outside the calibrated range of the sensor.

Related references:
Cowen RK, Guigand CM. 2008. In situ Ichthyoplankton Imaging System (ISIIS): system design and preliminary results. Limnol Oceanogr Methods. 6: 126-132. doi:10.4319/lom.2008.6.126

Temperature, salinity, pressure, depth, oxygen, fluorescence, and irradiance data are collected at a higher temporal frequency than latitude and longitude observations that come from the ship’s NEMA system. Latitude and longitude values have been linearly interpolated between observations using time.

In 2014, latitude and longitude data from the NEMA system were not automatically logged with the physical data during ISIIS tows. To address this, temperature, salinity, pressure, depth, oxygen, fluorescence, and irradiance data were binned to the nearest second (mean for each second bin) in order to merge them with the ship’s GPS data.

Seawater density (kg per cubic meter) was calculated from pressure, temperature, and salinity using the UNESCO equation of state from the ‘R’ Library ‘OCE’ package.

Temperature, salinity, oxygen, fluorescence, irradiance values less than zero were excluded as they are erroneous

Density values less than 1000 kg per cubic meter were excluded as they are erroneous

Oxygen (2015 only) was corrected for post-calibration sensor drift using the equation:
Final oxygen (ml L-1) = Initial oxygen (ml L-1)*1.0649702 – 0.0029434

Fluorescence (volts) data from the Wet Labs Eco Fluorometer was converted to chlorophyll (ug/L) using the following equation:
chlorophyll (µg L-1) = scale factor*(volts – dark counts)
2014: Scale factor = 25; Dark counts = 0.028. 2015: Scale factor = 24; Dark counts = 0.026.

Large camera parameters used in volume imaged calculations:
2014:
Image width: 2048 pixels
Scan rate: 35,000 lines s-1
Depth of field: 50 cm
Field of view: 11.2 cm

2015:
Image width: 2048 pixels
Scan rate: 35,000 lines s-1
Depth of field: 50 cm
Field of view: 11 cm

Small camera parameters used in volume imaged calculations:
2014:
Image width: 1024 pixels
Scan rate: 62,000 lines s-1
Depth of field: 10 cm
Field of view: 6 cm

2015:
Image width: 1024 pixels
Scan rate: 55,000 lines s-1
Depth of field: 10 cm
Field of view: 4.6 cm

Derived camera data calculated using equations below:
lg.hz.line =  horizontal.velocity (cm s-1) / lg.scan.rate
lg.eff.image.length (cm) = lg.image.width *lg.hz.line
lg.vol.image (cm3) = lg.dof*lg.fov*lg.eff.image.length
lg.image.sec (images s-1) = horizontal.velocity (cm s-1)/lg.eff.image.length
lg.vol.rate (m3 s-1) = (lg.image.sec*lg.vol.image)*1E-06
sm.hz.line =  horizontal.velocity (cm s-1) / sm.scan.rate
sm.eff.image.length (cm) = sm.image.width *sm.hz.line
sm.vol.image (cm3) = sm.dof*sm.fov*sm.eff.image.length
sm.image.sec (images s-1) = horizontal.velocity (cm s-1)/sm.eff.image.length
sm.vol.rate (m3 s-1) = (sm.image.sec*sm.vol.image)*1E-06

Description from NSF award abstract:
The spatial pattern of organisms within pelagic marine environments is of significant ecological importance, and this is particularly true for larval fishes. Patchy prey and predator environments should lead to variation in predator-prey interactions, and thus to variations in larval fish growth and survival. These have proven very difficult to resolve in nature, due in large part to the broad range of spatial scales involved and technological challenges with adequately sampling the various processes simultaneously. This study will use new technology (In Situ Ichthyoplankton Imaging System - ISIIS) to simultaneously measure the fine-scale distribution of larval fishes in relation to their prey, their planktonic predators, and the physical environment of the Straits of Florida. This will be combined with targeted fine-scale net sampling and analyses of individual recent daily larval growth. By sampling a series of water masses at very high resolution, this study will address specific hypotheses concerning: i) the drivers of aggregations and patchiness, and ii) the biological consequences of predator-prey interactions at fine scales.

The primary intellectual merit of the study is the unprecedented examination of plankton processes at scales of relevance to biological interactions among larval fishes, their prey, and their predators. This field study will further our understanding of the predator-prey interactions contributing to spatially explicit larval growth and mortality patterns. The focus on subtropical planktonic food webs will enhance scientific knowledge of these understudied pelagic ecosystems and provide valuable data for comparative analyses with pelagic food web dynamics at higher latitudes. A deeper understanding of pelagic planktonic ecosystems over a range of spatial and temporal scales is increasingly important as the oceans undergo major environmental changes. Substantial increases in the relative dominance of gelatinous organisms, for example, have the potential to cause major shifts in pelagic food webs. A better understanding of the fine-scale interactions of such food webs will help society anticipate and respond to the consequences of such changes.

Note (07 Oct 2014): Funding for this project transferred from award OCE-1333800 to OCE-1419987, coincident with the Principal Investigator's affiliation change from University of Miami to Oregon State University.