RI C-AIM: A Coastal Collaboration

RI C-AIM: A Coastal Collaboration


Through RI C-AIM, scientists and students are working together to position Rhode Island as a ‘state of excellence’ for assessing, predicting and responding to the effects of climate variability on coastal ecosystems.

Real-time data

Initiatives such as the Narragansett Bay Observatory and the RI Data Discovery Center will establish a data collection network to gather real-time chemical and biological information about the bay. Such a system will help not only researchers, but local communities understand the ecological changes along the coastal areas of Narragansett Bay and inform future decisions. 


The RI C-AIM effort is not just a lab project, but an activation of many engineering and scientific resources throughout Rhode Island. Researchers will transmit and help disseminate data to businesses and residents reliant on a thriving coastal ecosystem. Students from eight higher education institutions across the state will work hand-in-hand with scientists to develop new instruments and computer systems which corral and interpret data. Moreover, Rhode Islanders will have opportunity to become ‘citizen scientists’ and take ownership of the RI C-AIM process, participating in various stakeholder events.

Thrust 1: Assessing Biological and Ecosystem Impacts

  • Goal 1.1: Create an integrated Bay Observatory and disseminate continuous, real-time in-situ ecological and environmental data for Narragansett Bay and key riverine watersheds that empty into the bay, providing high-resolution assessments of when and where different functional groups are present as a function of environmental conditions.

    Objective 1.1.1. Meet with community to gather input to optimize observatory design and sampling program.

    Objective 1.1.2. Purchase, test, calibrate, install, and connect/integrate instrumentation for data collection.

    Objective 1.1.3. Link instruments to the data portal (RIDDC) for real-time wireless data transmission.

    Objective 1.1.4. Maintain the Narragansett Bay Observatory.

    Goal 1.2: Identify linkages between physical and biogeochemical factors, anthropogenic stressors, and the presence and co-occurrence of species and metabolisms, including the land-activity that impacts the Narragansett Bay ecosystem.

    Objective 1.2.1. Measure rates of biogeochemical and biological transformations.

    Objective 1.2.2. Determine the physiological capacity of biogeochemically- and economically- relevant species and communities in NB.

    Objective 1.2.3. Identify associations between organismal responses and physical (meteorological, oceanographic) or chemical trigger events.

    • Create a networked observatory in Narragansett Bay with live-stream data which is publicly available for real-time data analysis, as well as for hind- and forecasting

    • Develop a much better understanding of the relationship of the planktonic species in Narragansett Bay with environmental dynamics to resolve unanswered questions, such as:

      • What changes in the ecosystem result in toxic algal blooms

      • What prevents bivalve recruitment into upper Narragansett Bay?

      • What are the ecosystem impacts of extended hypoxia?

    • Provide ecosystem modelers with high-resolution data, needed for better understanding monitoring and management of the bay
  • URI: Beinart, Bertin, Gold, Gomez-Chiarri, Granger, Jenkins, KincaidKing, LaneMaranda, Menden-Deuer, Mouw, Omand, Oviatt, PradhanangRobinson, Rothstein, Rynearson, Thornber, Ullman,    Vincent, Zhang

    RIC: Govenar, Knowlton

    Salve Regina: A. Reid, Axen

    Brown: Morgan

    Bryant: C. Reid

    Other: Grear, Hyde, Keith (EPA), Donohue (The Collaborative), Beauman (leadership team)

Thrust 3: Enabling Technologies for Improved Detection

  • Goal 3.1: Create reliable, stand-alone sensor platforms capable of detecting nitrogen and phosphorus in real time, at low cost, and in challenging settings.

    Objective 3.1.1. Create micro-fluidic sensors with integrated nanoscale architectures for rapid detection of seawater nutrients.

    Objective 3.1.2. Evaluate fouling behavior of SERS sensors.

    Goal 3.2: Investigate the use of paper-based devices for low-cost, wide-scale community-driven sensing of nitrogen and phosphorus.

    Objective 3.2.1. Test existing chemical assays for nitrate and phosphate detection in a paper- based format.

    Objective 3.2.2. Determine and respond to paper-based sensing challenges introduced by complex aquatic samples.

    Objective 3.2.3 Test paper devices on-site in environmentally relevant locations.

    Goal 3.3. Create a new and versatile class of sensors that are more specific or more sensitive than existing sensors.

    Objective 3.2.1. Create living biosensors in micro-fluidic devices to detect low levels of bioavailablephosphorus  and nitrogen.

    • Improved understanding of the molecular-level challenges of sensing in complex aquatic environments
    • Improved understanding of the performance capabilities of SERS in complex media
    • Improved understanding of surface fouling phenomena and countermeasures
    • New understanding of the potential of micro-fluidic biosensors for analyte detection.
  • URI: Bothun, Craver, Dwyer, Faghri, Jenkins, Levine, Vincent

    Brown: Boekelheide, Kane, Morgan, Tripathi

    Roger Williams: Lemire, Murphy

    Salve Regina: Munge

Thrust 2: Predicting Ecosystem Response Through Integration

  • Goal 2.1. Model and predict the distribution and source of nutrients, pollutants, low oxygen concentrations, chlorophyll and zooplankton in Narragansett Bay using lower-trophic level predictive models informed by species-specific microbial metabolic pathway models and the integrated Bay Observatory.

    Objective 2.1.1 Construct predictive bio-geochemical, ecological (B/E) model variants.

    Objective 2.1.2 Develop microbial, metabolic pathway models.

    Goal 2.2. Apply mature existing nested-grid models, and develop new high-resolution circulation models to understand and predict the distribution and source of nutrients, pollutants, and low oxygen concentrations in Narragansett Bay.

    Objective 2.2.1. Couple nested grid circulation models with B/E models.

    Objective 2.2.2. Resolve small-scale, bio-geochemical/ecological/circulation (B/E/C) processes with limited domain, high-resolution models.

    Goal 2.3. Develop higher trophic level models for aquaculture and fisheries species of interest and integrate these with the B/E/C models of Narragansett.

    Objective 2.3.1. Build integrated ecosystem models.

    Goal 2.4. Understand how human communities will interact and respond to changes in coastal environment under policy and market incentives for sustainable coastal economy.

    Objective 2.4.1. Understand potential mitigation and adaptation strategies for increasing sustainability of coastal economy.

    Objective 2.4.2. Understand how human, heterogeneous activity and coastal resource management is influenced by structure and function of coastal resources.

    Objective 2.4.3. Identify social-environmental feedbacks and develop adaptive strategies for communities to cope, manage, and adjust to change.


    • A set of natural and social sciences models, and simulation output, suitable for better understanding, management, and monitoring of Narragansett Bay and related waterways. These tools will provide context for observations being collected in the region now and in the future, and will be capable of aiding in the assessment of hazards, risks, mitigation and/or adaptation strategies, and uncertainties about these estuarine ecosystems and the surrounding human environment. Hypoxia, sea level rise, storm surge, pollutant tracking, beach closures, and wastewater management are primary applications of these tools.
    • New modeling approaches, such as the high-resolution embedded biogeochemical–ecological- circulation modeling system, new species-specific Omics models, the coupling of those natural models with social science models, and the formal use of both new and existing natural observations (Narragansett Bay Observatory) and societal data collected during the project to improve these models.


  • Goals

    Goal 1.1. Foster collaborations between artists, designers, engineers, and scientists toward the development of novels approaches to data visualization and the imaging and photographic documentation of scientific observations, to comprehend interactions in complex ecosystems, and to facilitate a broader understanding of our scientific observations with business leaders, policy makers, and the general public.

    Expected Outcomes

    • New visualizations will be created that illuminate research, education, training and communication.
    • Novel approaches to data visualization and new methods of imaging will be fostered.
    • Imaging infrastructure and access/training on high-end imaging equipment will be enhanced.
    • New method for batch processing of confocal images
    • New method for quantitative analysis of confocal images
    • Heightened awareness of value of high throughput biology and 3D images

    Associated Researchers

    RISD: Overstrom, Bissonnette

    Brown: Creton, Morgan

    URI: Gomez-Chiarri, Rothstein, E. Uchida

    PC: DeGiorgis

    RWU: Lemire

  • Goals

    Goal 2.1: To increase visibility and access to RI C-AIM research, a subset of samples, data, and/or techniques from each research thrust will be integrated into high school and/or undergraduate curricula, first piloted at one institution and then shared among RI institutions as a module or course plan.

    Goal 2.2: Recruit and retain a diverse, inclusive, and productive research community through training and career development.

    Goal 2.3: Increase the number of URM participants in RI C-AIM to help build a diverse RI workforce.

    Expected Outcomes

    • Increased visibility and access to RI C-AIM research
    • Annual Science Communication Workshops will build ability and confidence in a variety of communication skills and tools, including delivering presentations, writing for a variety of non- expert audiences, interacting with journalists, and creating short videos.
    • SciComm Exchange sessions will introduce a wide range of science communication and public engagement topics and offer opportunities for discussion and networking for C-AIM participants from all participating RI institutions.
    • Develop a series of up to 4 modules for Career Development program in collaboration with C-AIM partners. A cohort of 3-5 post-docs and junior faculty will be selected in years 1-4 of the project to participate in the Career Development program in years 2-5.
    • Career Development participants will take on mentorship roles for successive cohorts in the program, participating in module development.
    • Career Development participants will report greater confidence in leadership and communication skills than their C-AIM counterparts who did not participate in the program.
    • Career Development participants will demonstrate higher rates of success in proposal submissions, funded proposals, and accepted publications than colleagues at similar career stages
    • The Career Development program will promote faculty retention, based on self-reporting by program participants.
    • SURF will provide authentic research experiences for undergraduates under the mentorship of researchers engaged in each of the research thrusts
    • SURF+ will extend summer research experiences and student mentoring throughout the academic year, thereby strengthening pathways to graduate school and employment in Rhode Island

    Associated Researchers

    URI: Beauman, Bose, Bothun, Craver, Dwyer, Flynn, Jenkins, Menezes, Rothstein, Watson, Zheng 

    RIC: Govenar, Giuriceo, Stilwell

    Brown: Fox-Kemper, Morgan

    RWU: Lemire


  • Goals

    Goal 3.1: Engaging stakeholders through establishment of Academic-Industry-Community partnership, hosting annual RI C-AIM symposium, and enabling effective internal and external communication. 

    Goal 3.2: Program sustainability by identifying and supporting emerging areas, and sustaining research at core facilities. 

    Expected Outcomes

    • Familiarity with programs (e.g. Innovation Vouchers program) & e.g. intellectual property law, startup business ecosystem;
    • Ongoing engagement through joint industry-academic retreats and e.g. Capstone projects.
    • Campus best-practices for how to encourage research translation (e.g. cost centers for instruments, certificate programs for industry training)
    • Matchmaking efforts between industry and academia, e.g. a channel for unfunded STAC proposals to be matched to suitable RI industries either for the content or the expertise.
    • Increased collaboration and awareness of activities/opportunities across institutions
    • Continued public understanding of and appreciation for RI C-AIM research and WFD.

    Associated Researchers

    URI: Beauman, Bothun, Dwyer, Flynn, Rothstein, Watson

    RWU: Lemire

  • Goals

    Goal 1.1: (applicable to RT 1: Integrated Bay Observatory, RT 2: Predicting Ecosystem Response, IT1: Visualization & Imaging) Become the go-to-source for data storage, internal data sharing and external data sharing on Narragansett Bay.

    Expected Outcomes

    • RI C-AIM investigators and their institutions become internationally recognized for their research and the data on Narragansett Bay raises the public’s awareness.

    Associated Researchers

    Brown: Creton, Morgan, Huffman

    RISD: Overstrom


Through a $19 million grant from the National Science Foundation, RI C-AIM is also drawing on the expertise and guidance from a number of organizations throughout the state:

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