Bailey, Helen: University of Maryland (Project Lead)
Bograd, Steven: NOAA NMFS Pacific Fisheries Environmental Laboratory (Institution Lead)
Howell, Evan: NOAA Pacific Islands Fisheries Science Center (Institution Lead)
Mate, Bruce: Oregon State University (Institution Lead)
Project Funding:
2011 - 2015
NRA: 2010 NASA: Climate and Biological Response: Research and Applications
Funded by NASA
Abstract:
Many whale populations have been slow to increase in numbers following cessation of commercial whaling, and one of the reasons for this is human-induced mortality. There were 21 blue whale (Balaenoptera musculus) strandings along the California coast during 1988 to 2007, of which 8 were confirmed as ship strikes. Eleven other whale species have been hit by ships, including fin whales (Balaenoptera physalus), humpback whales (Megaptera novaeangliae), and gray whales (Eschrichtius robustus). Entanglement in fishing nets and lines can also lead to drowning, which has resulted in the death of thousands of cetaceans. There is great concern that underwater noise from human sources, such as seismic activity, Navy sonar, vessel noise, and offshore energy can cause stranding, impair hearing, mask calls, or result in area avoidance. These anthropogenic impacts are a major source of mortality to large whales. There is an urgent need for a comprehensive conservation strategy and we propose near real-time predictions of the probability of whale occurrence to help limit anthropogenic activities to times and areas of lower risk to whales. Our team has access to the largest satellite tracking dataset for whales in the world. The advantage of telemetry data is that it provides an animal’s eye-view of its movements and habitat preferences, and is not limited to the spatial scale and resolution of standard survey designs. This telemetry data will be combined with satellite-derived oceanographic data to create predictive habitat models. These products will allow large multi-species whale hotspots to be identified, and provide a near real-time tool for determining risk to whales. Managers and users of ecosystem services could
identify the time or location at which there would be the lowest probability of whale
occurrence, and ultimately the lowest risk to whales. This creates a building block
towards developing a decision support system for distribution to marine users,
developers, and planners.
The development of our near real-time tool will involve analyzing multi-year satellitederived
tracks of blue, fin, humpback and gray whales in the California Current System.
A switching state-space model will be applied to the raw Argos satellite tracks of these
whales to provide temporally regularized position estimates and to infer their behaviors.
We have already applied this to the blue whale data set, and will apply the same
procedure to the fin, humpback and gray whale tracks so that position and behavioral
estimates will be comparable for all four species. Satellite-derived environmental data
will then be extracted for the time and location of each whale position. This will include
sea surface temperature, chlorophyll-a concentration, and sea surface height. Additional
variables derived from satellite products will also be used, such as primary productivity,
temperature fronts, Ekman upwelling, geostrophic currents, and eddy kinetic energy. We
will then use an ensemble of habitat modeling techniques including generalized additive
and generalized linear mixed models, and resource selection functions to quantify and
predict the probability of whale occurrence based on environmental parameters. The
habitat models for each whale species will be calculated from daily to weekly satellite
products to generate a near real-time product that predicts large whale occurrence in the
California Current System. This tool will be hosted by NOAA/SWFSC and will be
transferred to the NOAA Southwest Regional Office. It can then be merged with products
describing anthropogenic activities, and developed in the future as a decision support
system for managers, the Navy, offshore energy industry, and other marine users to
reduce the risk of impact to Federally protected resources such as whales. Our project
will support NASA’s objectives by assisting management of marine protected species
under a changing climate and facilitating compliance with legal mandates.
Publications:
Abrahms, B., Hazen, E. L., Aikens, E. O., Savoca, M. S., Goldbogen, J. A., Bograd, S. J., Jacox, M. G., Irvine, L. M., Palacios, D. M., Mate, B. R. 2019. Memory and resource tracking drive blue whale migrations. Proceedings of the National Academy of Sciences. 116(12), 5582-5587. DOI: 10.1073/pnas.1819031116
Bailey, H., E. Hazen, B. Mate, S.J. Bograd, L. Irvine, D.M. Palacios, K.A. Forney, E. Howell, A. Hoover, L. DeWitt and J. Wingfield. Lessons learned from WhaleWatch. Satellite Remote Sensing for Conservation Action: Case Studies from Aquatic and Terrestrial Ecosystems (2018): 229. ISBN: 9781108456708
Hazen, E. L., Palacios, D. M., Forney, K. A., Howell, E. A., Becker, E., Hoover, A. L., Irvine, L., DeAngelis, M., Bograd, S. J., Mate, B. R., Bailey, H. 2016. WhaleWatch: a dynamic management tool for predicting blue whale density in the California Current. Journal of Applied Ecology. 54(5), 1415-1428. DOI: 10.1111/1365-2664.12820
Irvine, L. M., Mate, B. R., Winsor, M. H., Palacios, D. M., Bograd, S. J., Costa, D. P., Bailey, H. 2014. Spatial and Temporal Occurrence of Blue Whales off the U.S. West Coast, with Implications for Management. PLoS ONE. 9(7), e102959. DOI: 10.1371/journal.pone.0102959
Pardo, M. A., Gerrodette, T., Beier, E., Gendron, D., Forney, K. A., Chivers, S. J., Barlow, J., Palacios, D. M. 2015. Inferring Cetacean Population Densities from the Absolute Dynamic Topography of the Ocean in a Hierarchical Bayesian Framework. PLOS ONE. 10(3), e0120727. DOI: 10.1371/journal.pone.0120727
More details may be found in the following project profile(s):