Funded PhD project: population assessments for insular cetaceans in Hawaii
Call for applicants for a funded PhD project: population assessments for insular cetaceans in
the Main Hawaiian Islands
The Marine Mammal Research Program (MMRP) at the Hawaiʻi Institute of Marine Biology
(HIMB), NOAA Fisheries’ Pacific Island Fisheries Science Center (PIFSC) and Cascadia Research
Collective (CRC) are seeking applicants for a PhD project that aims to improve population
assessments for insular cetaceans in the Main Hawaiian Islands (MHI).
Applicants must have strong analytical skillsets and, ideally, strong coding experience in areas
pertaining to machine-learning and artificial intelligence. The successful candidate will be
provided with full tuition costs and a PhD stipend for four years at the University of Hawaiʻi,
funded by the NOAA Fisheries QUEST program (see below). As the fellowship is intended to
create a pipeline into NOAA Fisheries, the supported student must be a U.S. citizen.
Hawaiʻi’s unique ecosystems support insular (island-associated) populations of several cetacean
species that are otherwise considered to have pelagic distributions. To date, five species with
island-associated stocks in the Main Hawaiian Islands are recognized within the NMFS Stock
Assessment Reports, including spinner, pantropical spotted, and bottlenose dolphins, false
killer whales and melon-headed whales, and others are likely to be recognized in the coming
years as additional genetic, movement, abundance, and demographic data become available.
Assessments of insular cetaceans are challenged by the distribution of these stocks, as typical
large-scale line-transect surveys used for surveying cetaceans over large areas are
inappropriate and yield insufficient sightings to conduct robust abundance analyses. Further,
many of these island-associated stocks overlap with pelagic populations.
PIFSC and CRC have been conducting surveys near each of the MHI for over a decade and have
amassed a large sighting, individual photo-ID, and telemetry dataset for over a dozen species.
To date, these data have been essential for evaluating population structure and range and have
provided the data needed to conduct mark-recapture abundance estimates for some insular
stocks, including MHI insular false killer whales (Bradford et al. 2017) and bottlenose dolphins
(Van Cise et al. in review, Baird et al. 2009). However, nonsystematic data collection and the
significant time investment to maintain photo-ID catalogs for some species have meant that the
data do not readily fit within NOAA’s other assessment frameworks. This PhD project will aim to
adapt existing or develop new analytical tools to allow for greater use of this type of non-
systematic data commonly collected by CRC, PIFSC, and other research partners in order to help
the PIFSC fill assessment gaps for several insular populations. The specific approach and
species chosen will be determined based on the qualifications and interests of the selected
graduate student and in collaboration with the MMRP, PIFSC and CRC partners, though will
generally include the elements described below.
This project will aim to use a rich sighting, photo, and telemetry dataset from one or more
species to develop and validate new analytical approaches that do not require such a rich
dataset for use on the other species. Projects may include:
- Development and application of artificial intelligence and machine learning approaches
for photo-ID matching or other analyses.
- Development of advanced statistical approaches to modeling species abundance and
range using survey datasets with non-systematic effort, possibly including use of
encounter-only models to assess population abundance, with validation of those models
using the photo-ID and telemetry data available for those species.
- Examining the sensitivity of resulting abundance and other demographic parameter
estimates to various data types, data distribution through time, and other factors that
may influence population demographics.
We encourage applicants with strong coding and statistical skills to apply. The successful
graduate student will most likely use large datasets collected from false killer whales, rough-
toothed or spotted dolphins, though data from a number of other species are also available for
development, testing, and validation of approaches.
The project is well-suited to a PhD project given the need to explore a variety of analytical
frameworks, understand the nature of large and complex datasets, and develop and validate
approaches that can be used in an assessment context. The student will be well-supported by a
highly quantitative team at the University of Hawaiʻi and PIFSC and the successful student will
contribute directly to NOAA Fisheries assessment needs.
The Quantitative Ecology and Socioeconomics Training (QUEST) program is designed to prepare
the next generation of assessment scientists for careers in fisheries or protected species
population assessment, ecosystem assessment, and marine resource economics. The PIFSC
QUEST program supports graduate fellowships for students working toward such quantitative
fields, with the goal of building capacity for the PIFSC workforce to meet its science
requirements under the Magnuson-Stevens Fishery Conservation and Management Act, Marine
Mammal Protection Act, and Endangered Species Act. QUEST students collaborate with PIFSC
researchers to develop student capabilities and skills directly related to mission needs. The
QUEST student will work closely with a PIFSC work-group (in this case the Cetacean Research
Program within the Protected Species Division) and will be expected to spend a portion of each
year (generally summer, though this is flexible) working at PIFSC. As the fellowship is intended
to create a pipeline into NOAA Fisheries, the supported student must be a U.S. citizen.
Candidates should submit the following materials via email to email@example.com in a single
PDF document, with the file name “YourLastName_QUEST_PhD.pdf” and the subject heading
“QUEST PhD application” by 1 October, 2020:
1) Brief introductory cover letter (maximum of 1 page)
2) Two statements covering (maximum 1 page each):
a) Provide an overview of your quantitative skillsets, analytical skillsets
and/or coding experience in areas pertaining to machine-learning and artificial
b) What you hope to gain through a graduate school experience
3) Your CV
The chosen candidate would then apply (in December 2020) for entrance into a PhD program
with the Marine Mammal Research Program the Hawaii Institute of Marine Biology at the
University of Hawaii – with a start date in August 2021.