
NSF Org: |
OCE Division Of Ocean Sciences |
Recipient: |
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Initial Amendment Date: | July 11, 2013 |
Latest Amendment Date: | July 11, 2013 |
Award Number: | 1333755 |
Award Instrument: | Standard Grant |
Program Manager: |
Michael Sieracki
OCE Division Of Ocean Sciences GEO Directorate for Geosciences |
Start Date: | September 1, 2013 |
End Date: | August 31, 2018 (Estimated) |
Total Intended Award Amount: | $394,730.00 |
Total Awarded Amount to Date: | $394,730.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
39 WILDFLOWER LANE BEALS ME US 04611-3201 (207)497-5769 |
Sponsor Congressional District: |
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Primary Place of Performance: |
39 Wildflower Lane Beals ME US 04611-0083 |
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): | BIOLOGICAL OCEANOGRAPHY |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.050 |
ABSTRACT
Existing larval transport models focus mainly on along-shelf transport and have done little to explicitly incorporate the effects of cross-shelf mixing and transport processes. Yet cross-shelf transits (both outgoing and incoming legs) are critical components of the dispersal paths of coastal invertebrates. This project will explore the role of cross-shelf mixing in the connectivity of blue mussel populations in eastern Maine. Previous work has shown that the Eastern Maine Coastal Current (EMCC) begins to diverge from shore southwest of the Grand Manan Channel and creates a gradient in cross-shelf mixing and larval transport, with cross-shelf mixing being more common on the northeastern end, episodic in the transitional middle area, and then becoming rare in the southwestern half of the region of the Gulf of Maine. As a result, the investigators predict that northeastern populations of mussels are seeded mostly from up-stream sources, while a significant component of self-seeding (local retention) exists in southwestern populations. Larvae settling in the intervening bays are expected to be derived from a mixture of local and up-stream sources. Using a combined empirical and theoretical approach hydrographic, current profile, and larval vertical migration data will be collected and used to develop and validate a high-resolution coastal circulation model coupled to a model of larval behavior. The investigators will model simulations in different years using the empirical data from mussel reproductive output and spawning times. Connectivity predicted from this model will be then tested against independent empirical estimates of connectivity based on trace element fingerprinting for larvae which can be connected to specific natal habitats. Regions of agreement and discrepancy in the model will be identified to guide additional data collection and model refinement. This iterative process will ensure an understanding of both larval transport patterns and processes, and provide estimates of inter-annual variability in connectivity for blue mussel populations in the Gulf of Maine.
The project will provide interdisciplinary training for a number of undergraduate and graduate students. All three investigators have established track records of training students at either the undergraduate or graduate level, or both. Inter-institutional and interdisciplinary exchange will be fostered by a twice per year mini-symposium/retreat at which all project participants from the three laboratories will present and discuss results from their portions of the project. This project also has important implications for the commercial mussel aquaculture industry in Maine, which relies heavily on natural settlement and desires a better understanding of larval supply patterns to facilitate site selection for collecting newly settled spat.
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.
Most sessile marine animals have a larval stage that can potentially disperse long distances. Consequently, animals harvested in one spot may have been born in a completely different location, and understanding how and where they moved is critical for managing harvested species and deciding how to position marine reserves. Our project evaluated larval dispersal in commercially-harvested blue mussels in eastern Maine, where a strong coastal current is located offshore of a very complex coastline, with deep bays separated by rocky headlands and islands. Because mussels live up in the bays, the dispersal of mussel larvae up and down the bays and in and out of the coastal current plays an important role in determining dispersal patterns. We used a coupled biological/physical model to predict mussel dispersal patterns. This model was based on a very high-resolution coastal circulation model (the physical component) which we tested with field-collected current data. The model was very accurate at predicting observed currents. This physical model was then coupled with a biological model of larval mussel growth, mortality, and behavior. The growth and mortality parts of the model were based on laboratory experiments in which we reared larvae at different temperatures, while the behavior component was based on field observation of the vertical movement of mussel larvae. Contrary to some past reports, we discovered that mussel larvae migrate vertically on a day/night cycle, but do not migrate vertically on the flood/ebb tidal cycle. They do move vertically on the tide cycle, but this movement is passive and driven by currents, and thus does not represent a behavior that needs to be modeled. The coupled biophysical model predicted that most larval dispersal occurs among mussel beds within a bay, or between neighboring bays. Successful dispersal over longer distances did occur, but much more rarely. Dispersal was mostly from northeast to southwest (in the direction of the coastal current), but localized northeastward dispersal against the prevailing current was possible because flooding tides can move the larvae between bays within one tidal cycle. Tides were the main process moving larvae between the bays and the coastal current, while the physical structure of the bottom largely dictated where these across-shelf movements occurred. Wind appeared to play surprisingly little role in moving larvae up and down bays, but that result is partly because wind direction did not vary much. This region is known as "downeast" Maine because the wind blows very consistently from the southwest. We engaged with mussel harvesters and managers (the Maine state Dept. of Marine Resources) to share data and results. Mussel harvesting has traditionally been largely unregulated in Maine, but market pressures driven by the need to document that the harvest is sustainable are pushing the industry toward greater regulation. The state has only recently begun monitoring this resource, and their efforts to date have been limited to one bed. We were able to supply preliminary data on 14 other beds over a 4 year time span. Those data had originally been collected to support our modeling efforts (we needed to know how many larvae each bed produced, which is determined by the number of mussels and how large they are), but served as a preliminary stock assessment. We also trained two post-docs and eight undergraduate research assistants. One of the undergraduates worked on the project two summers and developed an independent project that was recently published in a major journal; she is currently applying to PhD program. One post-doc now has a permanent job in industry, and the other has a Knauss fellowship from NOAA to work with the federal legislature for a year. |
Last Modified: 12/11/2018
Modified by: Philip O Yund
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