
NSF Org: |
OPP Office of Polar Programs (OPP) |
Recipient: |
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Initial Amendment Date: | July 9, 2014 |
Latest Amendment Date: | August 28, 2015 |
Award Number: | 1341440 |
Award Instrument: | Continuing Grant |
Program Manager: |
Jennifer Burns
OPP Office of Polar Programs (OPP) GEO Directorate for Geosciences |
Start Date: | August 1, 2014 |
End Date: | July 31, 2018 (Estimated) |
Total Intended Award Amount: | $169,203.00 |
Total Awarded Amount to Date: | $169,203.00 |
Funds Obligated to Date: |
FY 2015 = $114,771.00 |
History of Investigator: |
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Recipient Sponsored Research Office: |
2145 N TANANA LOOP FAIRBANKS AK US 99775-0001 (907)474-7301 |
Sponsor Congressional District: |
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Primary Place of Performance: |
930 Koyukuk Drive Fairbanks AK US 99775-7340 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | ANT Organisms & Ecosystems |
Primary Program Source: |
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Program Reference Code(s): | |
Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.078 |
ABSTRACT
The aim of study is to understand how climate-related changes in snow and ice affect predator populations in the Antarctic, using the Adélie penguin as a focal species due to its long history as a Southern Ocean 'sentinel' species and the number of long-term research programs monitoring its abundance, distribution, and breeding biology. Understanding the environmental factors that control predator population dynamics is critically important for projecting the state of populations under future climate change scenarios, and for designing better conservation strategies for the Antarctic ecosystem. For the first time, datasets from a network of observational sites for the Adélie penguin across the entire Antarctic will be combined and analyzed, with a focus on linkages among the ice environment, primary production, and the population responses of Adélie penguins. The project will also further the NSF goals of making scientific discoveries available to the general public and of training new generations of scientists. The results of this project can be used to illustrate intuitively to the general public the complex interactions between ice, ocean, pelagic food web and top predators. This project also offers an excellent platform to demonstrate the process of climate-change science - how scientists simulate climate change scenarios and interpret model results. This project supports the training of undergraduate and graduate students in the fields of polar oceanography, plankton and seabird ecology, coupled physical-biological modeling and mathematical ecology. The results will be broadly disseminated to the general oceanographic research community through scientific workshops, conferences and peer-reviewed journal articles, and to undergraduate and graduate education communities, K-12 schools and organizations, and the interested public through web-based servers using existing infrastructure at the investigators' institutions.
The key question to be addressed in this project is how climate impacts the timing of periodic biological events (phenology) and how interannual variation in this periodic forcing influences the abundance of penguins in the Antarctic. The focus will be on the timing of ice algae and phytoplankton blooms because the high seasonality of sea ice and associated pulsed primary productivity are major drivers of the Antarctic food web. This study will also examine the responses of Adélie penguins to changes in sea ice dynamics and ice algae-phytoplankton phenology. Adélie penguins, like many other Antarctic seabirds, are long-lived, upper trophic-level predators that integrate the effects of sea ice on the food web at regional scales, and thus serve as a reliable biological indicator of environmental changes. The proposed approach is designed to accommodate the limits of measuring and modeling the intermediate trophic levels between phytoplankton and penguins (e.g., zooplankton and fish) at the pan-Antarctic scale, which are important but latent variables in the Southern Ocean food web. Through the use of remotely sensed and in situ data, along with state of the art statistical approaches (e.g. wavelet analysis) and numerical modeling, this highly interdisciplinary study will advance our understanding of polar ecosystems and improve the projection of future climate change scenarios.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project has the following three specific objectives. 1) examine environmental drivers and spatio-temporal patterns of phytoplankton phenology.2) assess the consequences of phenological mismatch between phytoplankton and Adélie penguins.3) develop a pan-Antarctic analysis of Southern Ocean food web dynamics, and to model the impacts of projected climate change scenarios on phytoplankton and Adélie penguins. Our outcome includes the following: 1) conducted series of global ice-ocean ecosystem model runs and validated the model with in-situ data and satellite remote sensing ocean temperature, chlorophyll and sea ice concentration data. The model reproduced the long term trend of increasing Antarctic sea ice extent in the last several decades and the seasonal patterns of sea ice retreat and phytoplankton bloom; 2) Using 18-year satellite measurements (1997–2015) of sea ice and chlorophyll concentrations, we assessed the synchronicity between the spring phytoplankton bloom and light availability, taking into account the ice cover and the incident solar irradiance, for 50 circum-Antarctic coastal polynyas. The synchronicity was strong (i.e., earlier ice-adjusted light onset leads to earlier bloom and vice versa) in most of the western Antarctic polynyas but weak in a majority of the eastern Antarctic polynyas (Figure 1). The west-east asymmetry is related to sea ice production rate: the formation of many eastern Antarctic polynyas is associated with strong katabatic wind and high sea ice production rate, leading to stronger water column mixing that could damp phytoplankton blooms and weaken the synchronicity. 3) We worked on the analysis of the phenological coupling between sea ice, stratification and phytoplankton bloom in the seasonal ice zones (SIZs). We expanded our analyses on the role of large scale atmospheric forcing, represented by Southern Annular Mode (SAM), in controlling ice and stratification dynamics. The model well simulated the seasonal variation of the mixed layer depth (MLD) in winter and summer as compared with observed climatology based on available ARGO data. We examined the responses of multiple model variables (in addition to MLDs) to SAM, including ice thickness, surface temperature and salinity, nutrients (iron and nitrate), as well as Chl-a and primary production. We found that the variations of sea surface temperature, MLD, and surface nitrate concentration correspond to SAM in the same spatial and seasonal patterns, but the surface iron concentration does not show similar spatial and seasonal patterns. Since the phytoplankton bloom in the Antarctic Ocean is mainly iron-limited, the phytoplankton and primary production do not have clear temporal and spatial patterns in response to SAM variations.4) We made effort in producing input covariates of seabird models for the groups of co-PIs Jenouvrier and Lynch, which has directly contributed to three publications on the Antarctic seabird dynamics. The MATLAB codes used for data processing and analysis have been archived and made available to any users who wish to employ the same method in their research.
Last Modified: 08/22/2018
Modified by: Meibing Jin
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