Perspectives on in situ Sensors for Ocean Acidification Research

As ocean acidification (OA) sensor technology develops and improves, in situ deployment of such sensors is becoming more widespread. However, the scientific value of these data depends on the development and application of best practices for calibration, validation, and quality assurance as well as on further development and optimization of the measurement technologies themselves. Here, we summarize the results of a 2-day workshop on OA sensor best practices held in February 2018, in Victoria, British Columbia, Canada, drawing on the collective experience and perspectives of the participants. The workshop on in situ Sensors for OA Research was organized around three basic questions: 1) What are the factors limiting the precision, accuracy and reliability of sensor data? 2) What can we do to facilitate the quality assurance/quality control (QA/QC) process and optimize the utility of these data? and 3) What sort of data or metadata are needed for these data to be most useful to future users? A synthesis of the discussion of these questions among workshop participants and conclusions drawn is presented in this paper

Modified FlowCAM procedure for quantifying size distribution of zooplankton with sample recycling capacity

<div><p>We have developed a modified FlowCAM procedure for efficiently quantifying the size distribution of zooplankton. The modified method offers the following new features: 1) prevents animals from settling and clogging with constant bubbling in the sample container; 2) prevents damage to sample animals and facilitates recycling by replacing the built-in peristaltic pump with an external syringe pump, in order to generate negative pressure, creates a steady flow by drawing air from the receiving conical flask (i.e. vacuum pump), and transfers plankton from the sample container toward the main flowcell of the imaging system and finally into the receiving flask; 3) aligns samples in advance of imaging and prevents clogging with an additional flowcell placed ahead of the main flowcell. These modifications were designed to overcome the difficulties applying the standard FlowCAM procedure to studies where the number of individuals per sample is small, and since the FlowCAM can only image a subset of a sample. Our effective recycling procedure allows users to pass the same sample through the FlowCAM many times (i.e. bootstrapping the sample) in order to generate a good size distribution. Although more advanced FlowCAM models are equipped with syringe pump and Field of View (FOV) flowcells which can image all particles passing through the flow field; we note that these advanced setups are very expensive, offer limited syringe and flowcell sizes, and do not guarantee recycling. In contrast, our modifications are inexpensive and flexible. Finally, we compared the biovolumes estimated by automated FlowCAM image analysis versus conventional manual measurements, and found that the size of an individual zooplankter can be estimated by the FlowCAM image system after ground truthing.</p></div

Schematic illustration of the modified FlowCAM procedure for optimizing FlowCAM capacity for zooplankton analysis.

<p>Modifications were made upon the standard FlowCAM setup: constant air bubbling (to prevent particles from settling and aggregating), a secondary flowcell (to force particles to align and to provide a window to monitor the occurrence of clogging), an external syringe pump, and a receiving conical flask (to archive sample recycling).</p

Examples of FlowCAM images of the 7 dominant copepod morphotypes.

<p>Examples from FlowCAM image libraries that were built prior to the semi-automatic classification for the 7 dominant copepod morphotypes: (a) calanoid copepodite, (b) oithonid (cyclopoid) copepodite, (c) corycaeid (poecilostomatoid) copepodite, (d) oncaeid (poecilostomatoid) copepodite, (e) calanoid nauplius, (f) cyclopoid nauplius, and (g) harpacticoid nauplius.</p

Scatter plots illustrating the relationships between the biovolumes estimated with Area-Based-Diameter (V_ABD) from the FlowCAM versus the manual image measurements using ruler tools for the 7 dominant copepod morphotypes.

<p>A hundred individuals from each morphotype assemblage are randomly chosen. The biovolume of each individual was estimated by both V_ABD using the FlowCAM image analysis and “microscopic measurement” for each morphotype: (a) calanoid copepodite, (b) oithonid copepodite, (c) corycaeid copepodite, (d) oncaeid copepodite, (e) calanoid nauplius, (f) cyclopoid nauplius, and (g) harpacticoid nauplius. Linear regression analysis reveals significant correlations (p < 0.0001) between the biovolumes estimated with Area-Based-Diameter (V_ABD) versus microscopic measurement for all morphotypes.</p

Map showing the three sampling stations in the East China Sea.

<p>Copepod nauplii and copepodites samples were respectively collected with 50 and 100 μm zooplankton net at 10 m depth at station 1, 5 and 9 in May, 2013.</p

Example illustrating the inconsistency between the target length and width versus the FlowCAM image-based length and width.

<p>The target length and width of the copepod in this image are 400.1 and 102.9 μm respectively. However, the actual length and width FlowCAM measured are 690.6 and 477.8 μm respectively, which are affected by the extended copepod antenna.</p

Regression coefficients for biovolume data transformation (from FlowCAM data to Microscopy data at log scale) for 7 dominant copepod morphotypes using a linear regression model.

<p>Regression coefficients for biovolume data transformation (from FlowCAM data to Microscopy data at log scale) for 7 dominant copepod morphotypes using a linear regression model.</p

Comparison of FlowCAM image analysis versus microscope measurements.

<p>Comparison of FlowCAM image analysis versus microscope measurements.</p