Skip directly to content

Minimize RSR Award Detail

Research Spending & Results

Award Detail

Doing Business As Name:University of Alaska Fairbanks Campus
  • Michael A Litzow
  • (907) 486-1503
Award Date:11/20/2017
Estimated Total Award Amount: $ 55,229
Funds Obligated to Date: $ 55,229
  • FY 2016=$55,229
Start Date:08/01/2017
End Date:07/31/2018
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.050
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:Collaborative Research: Effects of Changing Temperature on the Gulf of Alaska Ecosystem
Federal Award ID Number:1756081
DUNS ID:615245164
Parent DUNS ID:048679567
Program Officer:
  • Michael Sieracki
  • (703) 292-7585

Awardee Location

Street:West Ridge Research Bldg 008
Awardee Cong. District:00

Primary Place of Performance

Organization Name:University of Alaska Fairbanks Campus
Street:909 Koyukuk Dr.
Cong. District:00

Abstract at Time of Award

This research has the potential to transform our understanding of how climate affects marine ecosystems and improve efforts toward ecosystem-based fisheries management. Investigators will analyze existing data to determine how shifts in climate properties over time may have affected commercially important fishes in the Gulf of Alaska (GOA). For several decades, significant relationships between sea surface temperature (SST) and abundance of a broad group of marine organisms in the GOA offered some promise for incorporating environmental data into fisheries management strategies. However, many of these statistical connections deteriorated abruptly in the late 1980s, while at the same time interactions between GOA SST and other aspects of climate conditions changed as well. This study will test the hypothesis that a switch in large-scale climate variability in the 1980s led to reorganization of relationships among GOA atmospheric and oceanographic properties, which in turn, produced a change in connection between temperature and ocean biology. These types of "no-analogue climate states" are well recognized in paleoecology and have been anticipated as a potential outcome of climate change, but few studies of ecological response to such switches are available. The project will support a postdoctoral scientist, as well as graduate and undergraduate student researchers. It will facilitate cooperation among scientists at three public universities, a non-profit research lab, and a federal management agency in order to combine the range of expertise that will be required to carry out this research. This research has the potential to transform our understanding of how climate affects marine ecosystems. It is based on preliminary analyses showing that the statistical relationships between SST and community state in the Gulf of Alaska appear to be nonstationary, with driver-response relationships that differ markedly before and after 1988/89. Preliminary analyses also show that correlations between SST and a number of other GOA climate parameters are significantly different before and after 1988/89. Additionally, leading modes in North Pacific SST anomalies for 1950-present changed their relative importance before and after 1988/89, with the second mode (North Pacific Gyre Oscillation, or NPGO) explaining more variability than the first mode (Pacific Decadal Oscillation, or PDO) during the past three decades. This change is consistent with a switch to a no-analogue climate state, characterized by markedly different patterns of variability among basin-scale climate processes. The proposed hypothesis will be tested with a combination of statistical ecological models and numerical ocean models. The statistical approach (threshold generalized additive models) will provide formal tests for nonstationary relationships between SST variability and ecological characteristics at the community and population level using time series data (1965-present) for 17 salmon, groundfish and crustacean populations from the GOA. In addition, nonstationary relationships among atmospheric and hydrographic processes at basin and regional scales will be tested with time series generated by ocean data-assimilation and hindcast models. Finally, those nonstationary relationships identified will be used to parameterize statistical models of biological variability that account for non-analogous states in the system.

For specific questions or comments about this information including the NSF Project Outcomes Report, contact us.