| NSF Org: |
OIA OIA-Office of Integrative Activities |
| Recipient: |
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| Initial Amendment Date: | July 16, 2019 |
| Latest Amendment Date: | September 15, 2022 |
| Award Number: | 1849227 |
| Award Instrument: | Cooperative Agreement |
| Program Manager: |
Andrea Johnson
andjohns@nsf.gov (703)292-5164 OIA OIA-Office of Integrative Activities O/D Office Of The Director |
| Start Date: | July 1, 2019 |
| End Date: | December 31, 2024 (Estimated) |
| Total Intended Award Amount: | $20,000,000.00 |
| Total Awarded Amount to Date: | $20,000,000.00 |
| Funds Obligated to Date: |
FY 2020 = $4,471,539.00 FY 2021 = $4,372,317.00 FY 2022 = $8,278,290.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
5717 CORBETT HALL ORONO ME US 04469-5717 (207)581-1484 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
ME US 04469-5717 |
| 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): |
EPSCoR RII: Track-1, EPSCoR Research Infrastructure |
| Primary Program Source: |
01002223DB NSF RESEARCH & RELATED ACTIVIT 01001920DB NSF RESEARCH & RELATED ACTIVIT 01002223DB NSF RESEARCH & RELATED ACTIVIT 01002122DB NSF RESEARCH & RELATED ACTIVIT 01002021DB NSF RESEARCH & RELATED ACTIVIT |
| 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): | 47.083 |
ABSTRACT
This project, known as Maine-eDNA, aims to achieve transformational understanding of ecosystem dynamics and sustainability in coastal regions through the application of advanced genomic analysis techniques on environmental samples. This approach, termed environmental DNA (eDNA) analysis, potentially allows for all species present in an ecosystem to be detected in parallel. Coastal ecosystems exhibit complex spatial and temporal variability, and therefore it has typically been necessary to commit significant time and resources to characterize even small features of the overall system. The vision of Maine-eDNA is to show how the eDNA approach can transform how aquatic ecosystems are studied and managed. The project focuses its efforts across three watersheds along the Maine coast - Casco Bay, Damariscotta, and Penobscot River - and across the major habitat types (lake, river, estuary, coastal) within each watershed. Maine-eDNA's research will explore questions related to sustainable fisheries and harmful species, along with integrative studies that explore the transformational potential of big data and team science practices. The project's research activities will be integrated with an ambitious agenda to engage teachers, students, and environmental professionals across the state with targeted activities that will lead to a better-trained, more diverse STEM workforce.
Maine-eDNA brings together several of the state's public and private academic institutions and independent research laboratories to focus on a shared goal of applying eDNA approaches to understand coastal ecosystem dynamics across spatial and temporal scales. eDNA holds the promise of overcoming fundamental environmental sampling constraints by leveraging state-of-the-art molecular next-generation sequencing and bioinformatics technologies. The project's research will involve a multi-year sampling campaign across several habitat types in three major Maine watersheds, augmented by targeted sampling and analyses to support project objectives. eDNA approaches will be applied to coastal ecological problems of strong economic and societal relevance for the state, addressing research questions relating to sustainable fisheries (i.e., ecosystem-based restoration and early-life ecology) and harmful species (i.e., harmful algal and cyanobacterial blooms and invasive species). Additional Maine-eDNA research efforts will study how applying big data and team science approaches can lead to more rapid advances in understanding complex systems. To broaden the impact of its research agenda, Maine-eDNA's efforts will also include extensive education and outreach activities that will emphasize connections with the state's Native American and rural populations, as well as development opportunities for teachers and environmental professionals. The project will also build new partnerships and strengthen existing ties with Maine's resource managers and fishing industries. Maine-eDNA promises to have a strong beneficial impact on the research capacity of the participating institutions and on the state overall.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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.
Project Outcomes Report – NSF Award# 1849227
Project Title: RII Track-1: Molecule to Ecosystem: Environmental DNA as a Nexus of Coastal Ecosystem Sustainability for Maine (Maine-eDNA)
Recipient Organization: University of Maine
Project/Grant Period: 07/01/2019 – 12/31/24
PI: Dr. Kody Varahramyan
The Maine-eDNA project, formally titled Molecule to Ecosystem: Environmental DNA as a Nexus of Coastal Ecosystem Sustainability for Maine, was a transformative five-year initiative funded by NSF EPSCoR. The project aimed to position Maine as “The DNA Coast,” establishing it as a global leader in environmental DNA (eDNA) research and education focused on sustaining coastal marine and freshwater ecosystems. Through a statewide, multi-institutional collaboration, Maine-eDNA integrated scientific discovery, education, and community partnerships to achieve this ambitious vision.
Over the course of the project, Maine-eDNA developed one of the world’s largest coastal eDNA datasets, banking over 5,500 samples across four genetic markers (12S, 16S, 18S, and COI). This unprecedented resource captured biodiversity from microbes to whales, revealing critical spatial and temporal biodiversity patterns across Maine’s interconnected aquatic systems. Thematic research advanced major scientific frontiers. In Sustainable Fisheries, researchers applied eDNA tools to monitor river herring restoration, larval recruitment in shellfish and seaweed, and ecosystem-based fisheries management. In the study of Harmful and Shifting Species, the project developed new detection methods for harmful algal blooms and tracked climate-driven range shifts in coastal species, especially kelp forests. Macrosystem Integration work revealed broad-scale ecological dynamics and improved understanding of eDNA behavior over time and space. Maine-eDNA thus demonstrated the power of eDNA for large-scale, real-world coastal ecosystem monitoring.
Education and workforce development were at the core of the project. Maine-eDNA supported 31 faculty and research scientists, 47 graduate students and 174 undergraduates, producing 69 publications and 241 presentations. Its K-12 initiatives engaged over 13,00 students across Maine, connecting classrooms with authentic, locally relevant environmental research. Graduate students led research initiatives, publications, and grant proposals, with many transitioning into academic, research, and professional roles.
The project was a leader in ethical data management, building a comprehensive metadata system aligned with FAIR (Findable, Accessible, Interoperable, Reusable) principles. Going further, Maine-eDNA also incorporated CARE (Collective Benefit, Authority to Control, Responsibility, Ethics) principles to acknowledge Indigenous data rights, including Biocultural Notices and Labels to mark samples from traditional Wabanaki territories. During its no-cost extension, the project secured follow-on funding to build a public, open-source database, ensuring that the vast trove of biodiversity data collected will be accessible to communities for years to come.
Maine-eDNA built a network of over 120 partnerships across academic institutions, NGOs, industry, and government. The project’s methods and tools are now being used by the Maine Department of Marine Resources, Maine Department of Transportation, regional Indigenous tribes, conservation groups, and aquaculture industries. The project leveraged its investment substantially, submitting 347 grant proposals and winning 176 awards totaling nearly $63 million. Its influence extended beyond Maine to help shape national strategies for eDNA use.
The project’s scientific contributions were wide-ranging. Maine-eDNA helped move environmental DNA from an emerging scientific technique to a core method for ecosystem monitoring, sustainable fisheries management, blue carbon research, and invasive species detection. New methodologies developed, including eRNA and methylated eDNA tools, promise to have long-term impacts on conservation, fisheries, and aquaculture management. Beyond these scientific advances, Maine-eDNA created pathways for broader public engagement with environmental science, strengthening Maine’s STEM pipeline and equipping coastal communities to face accelerating environmental changes. Its ethical leadership around Indigenous data sovereignty has been recognized nationally and internationally as a model for future projects.
Through its integrated achievements in research, education, ethics, and partnership-building, Maine-eDNA successfully transformed Maine into a leader in environmental DNA science. It has left a legacy of major scientific discoveries, robust educational infrastructure, deep community collaborations, and a comprehensive biodiversity dataset that will support future research and coastal management. As environmental DNA becomes a key tool in global ecological monitoring, Maine’s leadership as “The DNA Coast” will continue to shape the future of sustainable coastal stewardship for decades to come.
Last Modified: 04/30/2025
Modified by: Khodadad Varahramyan
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