PIFSC Young Scientist Opportunity (PYSO) Project Listing for Summer 2018

Applicants please refer to these projects and the corresponding project letter on your application coversheet (PDF). You may select more than one project on your coversheet.

Project A: Using artificial light to enhance fish surveys underwater

Advisors: Dianna Miller (dianna.miller@noaa.gov), Jeremy Taylor (jeremy.taylor@noaa.gov ), Dr. Ruhul Amin (ruhul.amin@noaa.gov)

Background: In an effort to monitor fishery resources in Hawaii and the Pacific Islands region and help improve population estimates of commercially-important Deep-7 bottomfish, scientists have recently integrated new camera methodologies into fisheries stock assessments. The Modular Optical Underwater Survey System (MOUSS) is used to provide species-specific, size-structured abundance data for Hawaiian bottomfish. The MOUSS has reliably produced high-quality videos to approximately 220 meters, but beyond those depths, the MOUSS cameras often receive insufficient ambient light to produce useful videos. For these deep camera deployments, resulting videos are frequently deemed too dark to annotate, although bottomfish commonly occur to depths of 400 meters. In order to obtain accurate fish population estimates over the full range of bottomfish habitat, we have devised new artificial LED light technology to increase the depth of successful video surveys.

Studies of fish in deep water habitats often rely on an artificial light source for visual assessments. However, addition of artificial light may create unnatural avoidance or attraction behaviors, so it may be useful to compare light of different wavelengths to ensure light color does not bias fish surveys. It is widely believed that deep water marine fish are less sensitive to red light (620-700 nm) versus other wavelengths due to poor visual sensitivity in the red part of the color spectrum. Thus, less-intrusive red lights may be useful to help minimize changes in fish behavior during camera surveys. To increase the depth limit of successful MOUSS surveys, we will test the addition of an LED light prototype, and compare white light versus colored light using red (620 nm), green (500-600 nm) and blue (430-460 nm) colored filters.

Objectives: The overall goal of this study is to determine whether the addition of an artificial LED light will enhance the ability of underwater cameras to observe bottomfish in situ. Specifically, we will:

  1. Assess the addition of an artificial LED light on the Modular Optical Underwater Survey System (MOUSS) stereo-camera system in Hawaiian waters.
  2. Assess whether the specific color (wavelength in nanometers) of light affects either camera avoidance or attraction behavior in Hawaiian bottomfish.

Duties and Responsibilities: With guidance from mentors, the selected student intern will compare preliminary survey data from PIFSC’s LED lighting study, and learn to process, analyze, and display quantitative fisheries data. Additionally, there may be opportunity for the student to assist with field operations if data collection is ongoing. Intern will be responsible for comparing fish abundance estimates from camera surveys utilizing artificial lighting of varying color (i.e. white, red, blue, green). The student will interpret this data to recommend a best lighting option which will help avoid survey bias. The student will prepare a final report and presentation addressing how they accomplished the study objectives with preliminary results displayed graphically.

The student will learn:

  • Valuable hands-on experience working with specialized scientific gear including underwater cameras, artificial lighting prototypes, and waterproof housings.
  • Basic research and data interpretation skills, with a focus on fisheries-independent survey techniques using artificial light.
  • Experience processing fisheries data using statistical analysis software and graphing techniques.
  • Potential for student to gain valuable field experience assisting with camera deployment operations or other data collection from a NOAA small boat.

Qualifications: Some familiarity with statistical analyses, computer programing such as python, image processing, and camera and artificial lighting technologies.

Project B: Assessing occurrence of cetaceans using passive acoustics

Advisors: Ann Allen (ann.allen@noaa.gov), Ali Bayless (ali.bayless@noaa.gov)

Background: Passive acoustics are useful for augmenting visual surveys and assessing temporal and spatial changes in the density and behavior of some marine animals. They can also provide important details about the acoustic environments of cetaceans. The Pacific Islands Fisheries Science Center’s Cetacean Research Program, uses a variety of acoustic recording instruments to study cetaceans in the Pacific Islands Region (PIR), including towed hydrophone arrays, bottom-mounted long-term acoustic recording devices, acoustic recording underwater gliders, miniature recorders for use on mobile or dynamic platforms, and acoustic recording tags that temporarily attach to dolphins and whales using suction cups.

Over the years, passive acoustic datasets have been collected with the Pacific Islands Passive Acoustic Network (PIPAN). Many species of cetacean produce characteristic sounds and their seasonality and movements can be evaluated based on the detection of those sounds. The PIPAN includes several monitoring stations within the U.S. territories of the Pacific Islands Region, including Hawaii, Wake, Palmyra, and the Commonwealth of the Northern Mariana Islands.

Objectives: The intern will evaluate the occurrence and characteristics of sounds produced by cetaceans from archived passive acoustic datasets. The specific species of focus will be discussed between the prospective intern and mentor based on intern interest and skill prior to finalizing the project objectives.

Duties and Responsibilities: Depending on the specific species of interest, the intern will scan archived passive acoustic datasets using custom software. The intern will identify individual calls or periods of calling (depending on the species and analysis question) within the dataset through manual scanning or use automated detectors. Depending on the species of interest, the intern may scan data from multiple locations within the network to examine population movements or may scan multiple years at a single site to examine inter-annual variability. The eventual log of call occurrence will be summarized at various temporal scales and statistical analyses can be carried out to examine relationships with environmental or other features.

The student will learn:

  • Valuable and direct experience using passive acoustics to study marine organisms and their ecology. Passive acoustic techniques for assessing animal population structure, occurrence, and abundance are becoming more widely used as an alternative to visual-based surveys.
  • Become familiar with underwater acoustic data and signal processing paradigms and how these data are commonly analyzed.

Qualifications: Familiarity and comfort with computers. Programming experience is not required, but would be a benefit for developing automated algorithms to detect animal calls using MATLAB or to conduct statistical analyses using MATLAB or R. However, internship will be tailored to the skill level of the intern. Familiarity with general principles of signal processing techniques and underwater sound propagation are desired, but not required.

Project C: Identifying oceanographic features as critical nursery habitat for early stages of commercially important Hawaiian shore fish and coastal fish

Advisors: Jamison Gove (Jamison.gove@noaa.gov), Jonathan Whitney (jonathan.whitney@noaa.gov), Donald Kobayashi (donald.kobayashi@noaa.gov)

Background: Understanding the habitat requirements of fish species throughout their life history provides insight into the environmental drivers that regulate their distribution and abundance. For reef-associated fish, identifying nursery habitats is particularly important because survival of early life stages is intricately linked to habitat quality and availability, which in turn have been linked to abundance of adult populations. In the Hawaiian Islands, the overwhelming majority of reef-associated and coastal pelagic fish stocks have been designated data-poor. For most taxa, there is a complete lack of stock-recruitment relationships and either no or inadequate data on early life history, which has limited assessments to assuming constant recruitment. The lack of studies on fish larval ecology renders it difficult to predict how environmental change will impact fisheries. Addressing these knowledge gaps will be critical to improving our understanding of how environmental changes will affect larval growth, survival, recruitment and ultimately replenishment of stock biomass.

Surface slicks–narrow, meandering lines on the ocean’s surface–are a conspicuous oceanic feature in the main Hawaiian Islands and may contribute to the recruitment and retention of early life history stages of marine organisms. Preliminary results from a recent Pacific Island Fisheries Science Center research expedition indicate a strong correlation between surface slicks and larval abundance. Larval fish densities were on average seven times greater in slicks than in adjacent waters, presumably due to the enhanced primary productivity (higher chlorophyll-a measurements) and planktonic prey (greater zooplankton density). This work is helping to improve our understanding of the ecology of larvae and early juveniles of ecologically and commercially important fish species in the Hawaiian Islands.

Objectives: The overarching goals of this project are to examine the spatial and temporal variability in larval distribution and abundance in relation to specific oceanographic features (slicks) in order to identify the environmental conditions that drive that variability and ultimately use that knowledge to develop indicators to improve stock and ecosystem assessments. Our approach is to first complete the processing and assembly of a 20-year (1998–2017) PIFSC time series of neustonic ichthyoplankton collections from the west coast of Hawaii Island (West Hawaii) in order to assess inter-annual variation in larval abundance and distribution. Next, we will assemble data from historical collections with ichthyoplankton and zooplankton surveys from three recent PIFSC field experiments that provide high-resolution biophysical coupled sampling of more than 100 slicks–sampled across three seasons to assess intra-annual variation in larval dynamics. We will then analyze both ichthyoplankton data sets individually and comparatively to assess patterns of change in abundance, distribution, and assemblages of key species. This work has direct application to current issues in marine fish ecology and the management of living marine species, such as understanding sources of variation in year class strength, and evaluating potentially important fish nursery areas (essential fish habitat).

Duties and Responsibilities: The student will be expected to assist with processing of data and collections with a particular emphasis on processing zooplankton collections to determine the composition and abundance of larval fish, invertebrates, and microplastics in nearshore Hawaiian waters. This will include:

  1. sorting, identification and enumeration of zooplankton samples using dissecting microscopes,
  2. characterize the distribution and concentrations of microplastics in slicks and surrounding surface waters [also biological interactions],
  3. assist with data analysis including integrating diverse datasets (biological, acoustic, hydrographic) to characterize bio-physical interactions,
  4. assist with preparing genetic samples for metabarcoding to aid specimen identification

The student will learn:

  • Identification and taxonomy of zooplankton, with a particular emphasis on larval fishes.
  • Methods for collecting, preserving, and processing zooplankton samples.
  • Methods for the analysis of microplastics in water samples.
  • Methods for preparing, processing, and analysis of metabarcoding genetic data.
  • Data analysis including multivariate statistical approaches.

Qualifications: Applicants should have a strong academic interest in marine science, coursework in biology and relevant lab experience, as well as a strong work ethic, willingness to learn, and ability to work both independently and as part of a team. The ideal candidate would have one or more of the following:

  1. Demonstrated interest or experience related to plankton ecology including familiarity with processing and identifying zooplankton;
  2. Coursework in ichthyology, invertebrate zoology, and marine science;
  3. Laboratory experience working under dissecting microscopes.

Project D: Assessing juvenile coral density and size distribution using advanced technology imaging capabilities that detects fluorescence in corals

Advisors: Rhonda Suka (Rhonda.Suka@noaa.gov), Annette DesRochers (Annette.Desrochers@noaa.gov), Ivor Williams (Ivor.Williams@noaa.gov)

Background and Description: Our mission within the NOAA Ecosystem Sciences Division (ESD) is to provide scientifically sound data on the status and trends of coral reef ecosystems to resource managers and stakeholders as well as the public. Our teams conduct long-term monitoring of coral reefs throughout the U.S. Pacific to better understand the population dynamics, diversity, health and resiliency, as well as threats to these ecosystems including ocean warming and acidification.

In 2014, Hawaii’s coral experienced record levels of bleaching, this followed by continued thermal stress in 2015 and 2016 creating back-to-back bleaching events. In areas already under stress, the added impact of thermal stress can make recovery even more difficult for coral. In an effort to promote conditions favorable to corals in West Maui, the Kahekili Herbivore Fisheries Management Area (KHFMA) was developed to protect herbivorous fishes and sea urchins in 2009. Continued monitoring of this area has shown an increase in herbivorous fish biomass and crustose coralline algae cover since the KHFMA was established. With slow growing coral, changes are more subtle and can take more time. By 2012, coral cover within the KHFMA was on the rise, until the bleaching event in 2015, which caused some coral mortality. This raises some pressing questions as to how these coral reef ecosystems will recover and how long that recovery might take. By monitoring juvenile and young coral growth and survivorship, we can gain a better understanding about the resilience of the coral population and the timescale for recovery.

Detecting juvenile and young coral (less than 10 cm maximum diameter) is difficult in the field and even more difficult from photographs. In an effort to improve our ability to quantify juvenile coral cover and recruitment, as well as changes of colonies over time, we are employing an emerging technology – Fluorescence Imagery. This technology is used to detect the chlorophyll-a fluorescence of coral, which makes coral appear to glow in a photograph. This method has the potential to greatly improve the ability to detect very small coral in photographs and make automated delineation and sizing in ArcGIS much more effective. In addition, the use of Structure from Motion (SfM) techniques provides a highly accurate, scaled image, which allows colony size to be recorded along with coral species and substrate type over a large area. Structure from Motion is a photogrammetric method used to create two-dimensional mosaic images and three-dimensional surfaces from a series of photographs. The resulting photomosaic is analyzed to compare changes in coral colonies and seafloor structure over time.


  1. Assess the capability of automated detection and delineation of juvenile coral using fluorescence imagery in ArcGIS.
  2. Classification and sizing of juvenile coral using photomosaics created through SfM techniques.

Duties and Responsibilities: Through this project a series of 3D models and 2D photomosaics of seafloor characteristics will be produced. For each model, an analysis of juvenile coral will be completed to produce a spatial model and statistical data for size distribution and density of colonies. This project also seeks to demonstrate an increase in accuracy and efficiency for identifying juvenile coral using fluorescence imagery and to create an index for Hawaii coral species fluorescence spectral values. As such, work includes post-processing of seafloor imagery, classification of sessile organisms and benthic habitats, creating 3D surface models from image series, spatial analysis and map production using ArcGIS, creating product documentation (metadata), creating imagery and maps for presentations and outreach, and more. Activities will be varied and student’s ability to follow precise instructions, work independently as well as with a team while producing high quality work are crucial.

The student would learn:

  • Structure from Motion techniques to produce 2D and 3D models using PhotoScan software.
  • Spatial analysis within the ArcGIS environment.
  • Fluorescence imagery analysis using image processing software (Adobe Photoshop or ENVI).
  • Identification of Hawaii sessile biota and seafloor characteristics.
  • Data organizational skills.
  • Student will also have opportunities to attend scientific talks and presentations, participate in field trips, present their work to the NOAA community and connect and work directly with NOAA scientists.

Qualifications: Interns are not required to have previous experience with Fluorescence Imaging or Structure from Motion techniques. A working knowledge of ArcGIS Desktop and experience with Microsoft Excel is needed. Experience working with digital imagery and knowledge of Hawaiian benthic flora and fauna are not required but preferred. Interns must pay close attention to detail, have strong organizational skills, the ability to focus on repetitive tasks, work with a variety of data and work well independently under the guidance and supervision of a mentor within the ESD team.