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Award Detail

Doing Business As Name:University of Massachusetts Boston
  • Ron J Etter
  • (617) 287-6613
  • Robyn E Hannigan
Award Date:07/11/2013
Estimated Total Award Amount: $ 353,436
Funds Obligated to Date: $ 353,436
  • FY 2013=$353,436
Start Date:09/01/2013
End Date:08/31/2018
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: An integrated theoretical and empirical approach to across-shelf mixing and connectivity of mussel populations
Federal Award ID Number:1334022
DUNS ID:808008122
Parent DUNS ID:079520631
Program Officer:
  • Daniel J. Thornhill
  • (703) 292-8143

Awardee Location

Street:100 Morrissey Boulevard
Awardee Cong. District:08

Primary Place of Performance

Organization Name:University of Massachusetts Boston
Cong. District:08

Abstract at Time of Award

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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Morello, SL and RJ Etter. "Estimating the impact of consumers in ecological communities: manual removals identify the complex role of individual consumers in the Gulf of Maine." Journal of Experimental Marine Biology and Ecology, v.495, 2017, p.89.

Morello, SL and RJ Etter. "Estimating the impact of consumers in ecological communities: manual removals identify the complex role of individual consumers in the Gulf of Maine." Journal of Experimental Marine Biology and Ecology, v.495, 2017, p.89.

Morello, SL and RJ Etter "The relative importance of spatial and temporal variation in predicting community structure at different scales as estimated from Markov Chain Models." Marine Ecology Progress Series, v.583, 2017, p.15.

Morello, SL and RJ Etter. "Transition probabilities help identify putative drivers of community change in complex systems" Ecology, v.99, 2018, p.1357.

Sorte, C.J.B., V.E. Davidson, M.C. Franklin, K.M. Benes, M.M. Doellman, R.J. Etter, R.E. Hannigan, J. Lubchenco, B.A. Menge. "Long-term declines in an intertidal foundation species parallel shifts in community composition" Global Change Biology, v.23, 2017, p.341-. doi:10.1111/gcb.13425 

Sorte**, C.J.B., V.E. Davidson, M.C. Franklin, K.M. Benes, M.M. Doellman, R.J. Etter, R.E. Hannigan, J. Lubchenco, B.A. Menge "Long-term declines in an intertidal foundation species parallel shifts in community composition." Global Change Biology, v.23, 2017, p.341.

Project Outcomes Report


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.

Understanding how populations are connected through dispersal is critical for ecology, evolution, conservation and management, and will play a crucial role in predicting how organisms might respond to contemporary anthropogenic stresses.  Many marine organisms disperse in the water column as small larvae.  Tracking minute pelagic larvae that drift with the ocean currents and potentially travel tens to hundreds of kilometers during several weeks of development is extremely difficult.   We used trace element fingerprints (TEF) derived from the chemical signatures found in calcified structures, such as shells, to quantify dispersal and population connectivity in the blue mussel (Mytilus edulis) in the Gulf of Maine over three years (2015-2017).   TEFs vary geographically, characterize different water masses, and can be used to identify the location where shell material was deposited.

Our results indicate that 1) larvae and juveniles have distinct TEFs even when reared under identical conditions, 2) TEFs differ strongly among bays within eastern Maine which has allowed us to assign settlers to natal sites, 3) Inter-annual differences in TEFs, dispersal and connectivity are apparent, 4) our unfolding estimates of larval dispersal and population connectivity indicate that connectivity among populations is typically downstream (NE – SW) of the major coastal currents, although there is some dispersal against the mean flow of the coastal currents. While upstream dispersal may seem odd, it is consistent with what has emerged from preliminary runs of our bio-physical model. Some simulated particles get caught in local eddies or entrained into bays northeast of their spawning sites due to tidal oscillations.  All of these findings suggest we should be able to successfully validate predictions from our biophysical model with elemental fingerprints.

Broader Impacts

The empirical and population connectivity data provide important insights into which populations are most important to maintain mussels in the Gulf of Maine and should aid in developing more efficient conservation and management strategies.

Five graduate students and eight undergradute students were trained on a variety of techniques including estimating connectivity, trace elemental fingerprints, population genetics and the physical oceanography in the Gulf of Maine. They were also trained more generally on how to design experiments, test hypotheses and present their findings. Our students included those from various programs at UMB to maximize involvement of underrepresented groups (e.g. REU, Bridges to Baccalaureate Program, Initiative for Maximizing Student Diversity, McNair program).

A postdoc was also trained in estimating population connectivity and he developed the software to use a Bayesian infinite mixture model for more accurately assigning mussels to natal sites based on TEFs.

Last Modified: 11/30/2018
Modified by: Ron J Etter

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