AQUACULTURE SITE PROSPECTING: USING REMOTE SENSING AND ECOSYSTEM MODELS TO IDENTIFY FUTURE SUSTAINABLE AQUACULTURE GROWING AREAS

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: HATCH
• Reporting Frequency: Annual
• Accession No.: 1013134
• Project Start Date: Oct 1, 2017
• Project End Date: Sep 30, 2019
• Program Code: [(N/A)]- (N/A)

Recipient Organization
UNIVERSITY OF MAINE
(N/A)
ORONO,ME 04469

Performing Department
School of Marine Sciences

Non Technical Summary
Oyster aquaculture of the American oyster, Crassostrea virginica, is an expanding industry in coastal Maine, USA, with landings worth $4.8 million dollars in 2015, up from $0.6 million in 2003 and increasing by 250% between 2011 and 2015 (Maine DMR commercial landings 2016, www.maine.gov/dmr/aquaculture/harvestdata/documents/oyster2005-2015.pdf). Most of this growth is attributable to small oyster aquaculturists. The continued sustainable expansion of the industry will in part rely on proper site selection. Ultimately the success or failure of any aquaculture venture depends on vetting an initial location before the leasing process. The obvious site-dependent biophysical influences on parameters such as growth, survival, biofouling, and condition index are compounded in importance by the process needed to secure permission from a regulatory body: it takes a lot of work and time to acquire a lease. If an aquaculturist chooses an inappropriate site, there is a heavy penalty to be paid in lost time and money.Figure 1. Map of the upper Damariscotta shellfish leasesIn many cases, new sites are selected based on proximity to established successful sites. For example, many of the more recent shellfish leases in Maine have been adjacent to initial sites developed in the early 1970's in the Damariscotta River (Fig. 1). Figure 1 shows the current sites on the Damariscotta River estuary which are primarily up-river in sites that are relatively warmer and longer residence times. This gives confidence to a remote sensing approach that is spatially extensive even if it is not temporally intensive (large site to site variability tends to increase the import of site selection).There is an obvious spatial limit to the expansion potential based simply on existing successful sites. To prospect for new sites, aquaculturists have largely relied on trial and error, an inefficient and risky approach. We propose to develop and provide aquaculture site prospectors a new tool to vet and compare sites to existing successful sites based on remote sensing technology. Remote sensing has long been used to inform sustainable fishery harvest strategies (Klemas 2014, Glembocki et al., 2015) and water quality dynamics (Keith, et al., 2014; Le et al., 2013; Schaeffer et al., 2013) in coastal systems. However, as outlined by the International Ocean-Colour Coordinating Group (2009) chapter on 'Remote Sensing in Fisheries and Aquaculture', two issues remain outstanding in the application of satellite ocean color to aquaculture: (1) the spatial resolution of the satellite data optimized for accurate retrieval of aquatic ocean color information is not fine enough to resolve the types of embayments wherein most aquaculture occurs (i.e., less than 1 km wide) and (2) is the issue of adjacency (i.e., contamination of target pixels by radiation emanating from bright adjacent land pixels). Similarly, accurate sea surface temperature measurements from satellite remote sensing instruments are not available at sufficient spatial resolution for most aquaculture use. New capabilities associated with the new Landsat 8 satellite allow us to propose the use of Landsat imagery to work around these issues. The high resolution possible from this platform (30-120 m) and the latest updates to the products that can be derived from this platform (i.e., temperature, turbidity, chlorophyll, and colored dissolved organic material (CDOM), Franz et al., 2015) will provide new insights into the aquaculture site-selection process.

Animal Health Component

60%

Research Effort Categories

Basic

15%

Applied

60%

Developmental

25%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
307	3723	1060	100%

Knowledge Area
307 - Animal Management Systems;

Subject Of Investigation
3723 - Oysters;

Field Of Science
1060 - Biology (whole systems);

Keywords

aquaculture

oysters

mussels

scallops

site selection

remote sensing

Goals / Objectives
Therefore: our objectives are to (1) continue to collect in situ samples and use them to groundtruth remote sensing and model products for delivery to aquaculturists (e.g., our dock Chlorophyll dataset has been maintained at the Darling Marine Center for the past 14 years continuously and is the go-to dataset for aquaculturists when they need information on phytoplankton concentrations in the Damariscotta River Estuary), (2) compare in situ data with new satellite products (Sentinel 1 and 2), (3) work with the emerging ear hung scallop aquaculture industry to bring site selection tools (recognizing that all potential sites identified by these tools will represent new sites given the early state of development of the industry) developed for oysters to this new industry (we submitted a proposal to the National Sea Grant Integrated Aquaculture RFP in early May to support this effort), and (4) continue to serve data (http://perrylab.umeoce.maine.edu/docksampling.php) and satellite images with stakeholders (https://umaine.edu/coastalsat/).

Project Methods
Apply new atmospheric correction and ocean color processing algorithms to Landsat 8 data from the coast of Maine to create maps of satellite-defined temperature, turbidity, chlorophyll and colored dissolved organic matter (CDOM) for both currently successful sites and future sites.Validate Landsat remote-sensed estimates of temperature, turbidity, chlorophyll and CDOM to obtain uncertainties in the space-based estimates of these parameter at several sites on the coast ME.Create time series, climatologies, and frequency diagrams of these water quality properties at the study sites from 2013 to the present.Compare the statistics of water quality parameters at existing successful aquaculture sites with coastal locations at other Maine sites to create GIS layers characterizing regions of the coast and highlighting potential sites for aquaculture.At each stage: consult with both prospective growers (co-PI Morse's Aquaculture Training Program) and existing growers (co-PI Newell's involvement with Maine Aquaculture Association, Pemaquid Oyster Company, Maine Aquaculture Innovation Center, local grower communities) about what information is useful. This information will include potential new sites for both oyster and ear-hung scallop aquaculture.More information and detail can be found in the recently accepted Snyder, Brady, Boss, Newell 2017 in Frontiers in Marine Science: OYSTER AQUACULTURE SITE SELECTION USING LANDSAT 8 - DERIVED SEA SURFACE TEMPERATURE, TURBIDITY, AND CHLOROPHYLL A.The coast of Maine includes a series of fjards (shallower and broader fjords, small fjords) and jagged embayments carved by receding glaciers during the Pleistocene epoch. In situ samples will be collected and ocean monitoring buoy systems that are maintained as part of the Sustainable Ecological Aquaculture Network will be used to validate Landsat-8 derived products on the Maine coast.All applicable raw data from Landsat 8 will be downloaded from the USGS Earth Explorer website from the period 2013 to present (USGS, 2016). To calculate SST, we use brightness temperature values from Landsat 8's Thermal Infrared Sensor (TIRS) Band 10. There are stray light issues associated with the two TIRS bands (Band 10 and Band 11) due to the curvature of the optical lens. Of these two bands we have chosen to use thermal Band 10 because it has lesser issues of the two. Each image is processed in the NASA SeaDAS platform up to level 2 to retrieve latitude and longitude arrays, a geo-registered image, and the associated land/cloud mask.Turbidity, T, (note that 1 g L-1 of SPM is equivalent, within our range of values found in our study area, to a turbidity of 1 NTU (Pfannkuche and Schmidt, 2003)) was calculated over the entire satellite scene using atmospherically corrected R_rs (655). Our algorithm was validated using water samples with a Hach turbidity sensor (an instrument that uses a tungsten filament lamp and measures side-scattering and transmission), and sensors on buoys (that measure light scattered in the back direction at a 20 nm bandwidth around 700 nm) to estimate turbidity. To cross-calibrate the two sensors, we compared their measurements using a dilution series of Arizona Dust standard. In the dilution experiment, the buoy sensor measured lower values than the Hach sensor by nearly 60%. We used the intercomparison data to correct the buoy-based turbidity against the Hach turbidity (which is the state-of-the-art standard) and to validate the satellite based turbidity.Chl a is calculated using the standard OC3 algorithm (O'Reilly et al., 1998) from the NASA Ocean Biology Processing Group, using the above-calculated R_rs. Because this algorithm is designed for oceanic waters, validation is necessary for the coastal waters of interest. In situ Chl a was measured using the fluorometeric technique (Cullen, 1982) in 2016 at the buoy sites in the Damariscotta River. Water samples were collected in triplicate, within 30 minutes of each overpass and filtered for extraction on a Turner 10 AU fluorometer per standard protocol. We propose to continue this validation and extend this sampling to more Maine estuaries in the future using citizen monitoring programs (we have organized 13 NGO's along the coast to help with this distributed monitoring).Validation has been carried out for physical and biogeochemical parameters (SST, SPM, and Chl a) using data from water samples and three oceanographic buoy observing systems. The desired accuracy for matchup data of these products was 1oC for SST, 1NTU for SPM, and within 50% relative difference for Chl a. Historical data has been downloaded from the NERACOOS (Northeastern Regional Association of Coastal Ocean Observing Systems) buoys E01 and I01, a Land/Ocean Biogeochemical Observatory (LOBO) buoy at Bowdoin College in Harpswell Sound, and two LOBO buoys at the University of Maine's Darling Marine Center. Being able to extrapolate the data from these buoys to inform aquaculture site selection and water quality issues across the coast is a significant new leveraging of University assets.Temperature data were collected from all three observing systems and compared to Landsat 8 SST. So far, a total of 52 matchups were identified originating from 31 clear overpasses from 2013 to 2016. In situ SPM was used to validate satellite-derived SPM during eight overpasses in 2015 and 2016. Data were collected from the UMaine LOBO buoys in the Damariscotta River, and were measured by a WET Labs WQM fluorescent sensor capable of measuring turbidity from 0 - 25 NTU at 700 nm vicariously calibrated against a Hach turbidity sensor. The corrected in-situ turbidity and chlorophyll data were used to validate the SPM and Chl a products derived from OLI.An Oyster Growth Suitability Index has been designed using the satellite-derived SST, SPM, and Chl a. A weighting and indexing procedure of these three physical parameters described ideal, moderate, and poor conditions for growing market sized oysters in surface culture. The criteria for the index was chosen based on stakeholder knowledge. Temperature is the most important variable in oyster growth, especially in the relatively cold waters of coastal Maine (Ehrich and Harris, 2015), and therefore was given an importance weight factor of 80% as a subjective percentage based on expert opinion and local stakeholder input. Chl a and SPM were given subjective weights of 15% and 5%, respectively. These relative weights were chosen as a starting point for the index , and can easily be refined in future iterations to optimize the index (Gong et al., 2012).We combined images from the same month across all study years to create a climatological monthly index (four in July, two in August, and three in September). The index therefore does not include information about the possible factors impacting site selection, such as bottom depth, or residential restrictions. Future work as part of this MAFES project will include this information for a more comprehensive index. We also intend to extend this analysis to other emerging bivalve aquaculture species such as ear-hung scallops and rope-grown mussels.

Progress 10/01/17 to 09/30/19

Outputs
Target Audience:The primary audience are aquaculturists (prospective and existing growers reached through workshops, and online products such as maine.loboviz.com and umaine.edu/coastalsat). Secondary audience includes regulatory agencies, cooperative extension, and citizen science groups: Maine Department of Marine Resources, Maine Department of Environmental Protection, Maine Aquaculture Innovation Center, Maine Sea Grant, and the Maine Aquaculture Association, and the Maine Coastal Observing Alliance. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Several graduate students have participated in the project: Kate Liberti (PhD UMaine School of Marine Sciences (SMS)) Jordan Snyder, and Thomas Kiffney (Master's, UMaine School of Marine Sciences) in particular collected validation data for satellite imagery and used the results in their theses. Many undergraduate studentsreceived training on satellite image analysis and lab analysis of validation samples. Importantly, analysis was incorporated into SMS 484 Estuarine Oceanography, a required course for UMaine Marine Science majors (one of the largest such programs in the US). Inaddition, the project developed a module in the Aquaculture in Shared Waters (ASW) course, one of the largest training programs for aquaculture in the US. ASW specifically trains fishermen in aquaculture techniques to diversify Maine's working waterfront. Results from this project have been incorporated into the Site Selection module. Finally, we have conducted a number of workshops at the Fishermen's Forum, the Northeast Aquaculture Convention and Expo, and the Maine Aquaculture Research and development Forum to train prospective growers on how to choose a site. How have the results been disseminated to communities of interest?We used multiple strategies to disseminate information to new growers: (1) we developed a site selection module in the Aquaculture in Shared Waters program (https://seagrant.umaine.edu/extension/aquaculture-in-shared-waters/), (2) we presented multiple workshops (i.e., Fishermen's Forum (largest annual meeting of Northeast fishermen and aquaculturists), Northeast Aquaculture Convention and Expo (largest regional meeting of aquaculturists), and the Maine Aquaculture Research and Development Forum), and (3) we developed a suite of web applications and databases for growers to access (i.e., maine.loboviz.com, umaine.edu/coastalsat, andhttp://www.shellgis.com/examples/TFWMidMaine.html). In combination, we have reached a new generation of growers interested in fine scale resolution siting tools specific to Maine serpentine coastline. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? We made progress and transitionedall four objectives to the next phase of the project. Specifically, we have leveraged the results of this fast track ME021834,Aquaculture Site Prospecting: Using Remote Sensing and Ecosystem Models to Identify Future Sustainable Aquaculture Growing Areas project, to a new full scale: ME022014,Remote Sensing and Aquaculture: Identifying Sustainable Aquaculture Growing Areas Via Satellite Imageryand a National Sea Grant funded effort. Now, for the first time, growers in Maine have access to nearshore remote sensing data on a spatial resolution that matches their farms (20-50 meters; umaine.edu/coastalsat). However, the temporal resolution is relatively sparse (16 days). Consequently, our new leveraged funding will extend this technology to include other remote sensing products that have a spatial resolution on the order of 5 days which would significantly increase the information available to growers. In addition to temperature, chlorophyll, and turbidity, we are optimistic that chromophoric dissolved organic matter (CDOM), a proxy for salinity, can be measured remotely. If successful, this would be the first remotely sensed salinity product available for growers in the world (low salinity generally increases bacterial exposure, low pH exposure, nutrient loading, and poor growth rates). In the mean time, this project has created the first database of remote sensing imagery available to aquaculturists and validated with in situ nearshore observations. This information has also been leveraged to characterize nearshore conditions to fisheries. The result has been fine-scale mapping on nearshore dynamic variable such as temperature, turbidity, and chlorophyll.

Publications

• Type: Journal Articles Status: Published Year Published: 2019 Citation: Adams, C.M., Mayer, L., Rawson, P., Brady, D.C., & Newell, C. (2019) Detrital protein contribution to oyster nutrition and growth in the Damariscotta estuary, Maine, USA. Aquaculture Environmental Interactions doi:10.3354/aei00330
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Oppenheim, N., Wahle, R., Brady, D.C., Goode, A. & Pershing, A. (2019) Forecasting fishery trends in a warming ocean: A modeling framework using early life stages of the American lobster. Ecological Applications. 29(8), e02006 1-10 doi:10.1002/eap.2006
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Gray, M. W., Chaparro, O., Huebert, K. B., O'Neill, S. P., Couture, T., Moreira, A., & Brady, D. C. (2019). Life History Traits Conferring Larval Resistance against Ocean Acidification: The Case of Brooding Oysters of the Genus Ostrea. Journal of Shellfish Research, 38(3), 751-761
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Goode, A., Brady, D.C., Steneck, R., & Wahle, R. (2019) The brighter side of climate change: Ocean warming crosses a biological threshold to amplify an iconic fishery. Global Change Biology doi:10.1111/gcb.14778
• Type: Journal Articles Status: Published Year Published: 2017 Citation: Snyder, J., Boss, E., Weatherbee, R., Thomas, A., Brady, D.C., and Newell, C. (2017) Oyster aquaculture site selection using Landsat 8-derived sea surface temperature, turbidity, and chlorophyll a. Frontiers in Marine Science 4(190), 1-11 doi:10.3389/fmars.2017.00190.
• Type: Book Chapters Status: Published Year Published: 2018 Citation: Newell, C.R., Brady, D.C., & Richardson, J. (2018) Chapter 24 Farm-scale production models. Chapter in The G+S Book: Goods and Services of Marine Bivalves. Springer.
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Johnson, T.R., Beard, K., Brady, D.C., Byron, C.J., Cleaver, C., Duffy, K., Keeney, N., Kimble, M., Miller, M., Moeykens, S., Teisl, M., van Walsum, G.P., Yuan, J. (2019) A social-ecological systems framework to guide marine aquaculture research. Sustainability 2019, 11, 2522; doi:10.3390/su11092522

Progress 10/01/17 to 09/30/18

Outputs
Target Audience:Aquaculturists (prospective and existing growers reached through workshops, and online products such as maine.loboviz.com and umaine.edu/coastalsat), Maine Department of Marine Resources, Maine Department of Environmental Protection Changes/Problems:Project Objectives That Were Met: Our goals were: (1) continue to collect in situ samples and use them to groundtruth remote sensing and model products for delivery to aquaculturists (e.g., our dock Chlorophyll dataset has been maintained at the Darling Marine Center for the past 14 years continuously and is the go to dataset for aquaculturists when they need information on phytoplankton concentrations in the Damariscotta River Estuary), (2) compare in situ data with new satellite products (Sentinel 1 and 2), (3) work with the emerging ear hung scallop aquaculture industry to bring site selection tools (recognizing that all potential sites identified by these tools will represent new sites given the early state of development of the industry) developed for oysters to this new industry (we submitted a proposal to the National Sea Grant Integrated Aquaculture RFP in early May to support this effort), and (4) continue to serve data (http://perrylab.umeoce.maine.edu/docksampling.php) and satellite images with stakeholders (https://umaine.edu/coastalsat/). To varying degrees, we have met all of these objectives (see Objective Not Met to see a discussion of Objective (2)). Project Objectives Not Met: Arguably, objective (2) compare in situ data with new satellite products (Sentinel 1 and 2) is the only goal we are still working on. It was the most cutting-edge objective in the original proposal and our new National Sea Grant Integrated Aquaculture grant referenced in the original proposal was funded. We intend to complete Objective 2 this year with this funding. Sentinel 2-A and B imagery from the European Space Agency was only recently available and we are in the process of recruiting a student to further this work. What opportunities for training and professional development has the project provided?The primary training and development opportunities produced by this project were targeted to two specific audiences: (1) prospective growers and (2) students. The former category was reached through Maine Sea Grant Aquaculture in Shared Waters classes where Dr. Brady walked growers through the sources of information that exist for site selection including data generated by this project and a workshop developed by Dana Morse (Maine Sea Grant), Carter Newell (Pemaquid Oyster and Mussel Company), and Dr. Brady that will be delivered at the Fisherman's Forum and Northeast Aquaculture Convention and Expo. The latter audience (students) has focused on graduate students: Jordan Snyder used remote sensing data to inform potential aquaculture siting in her master's thesis and now works for UC Davis on a macroalgal biofuels project funded by DOE, Kate Coupland is a PhD student with a prospective graduation date in 2020 who is collecting the dock chlorophyll samples for this project, and Nicholas Keeney, a PhD student, who is using the data to generate new cyberinfrastructure for growers. How have the results been disseminated to communities of interest?The aforementioned workshops (listed under opportunities for professional development) will be our primary vehicle for disseminating results in the near future. In the meantime, all imagery is available to growers at umaine.edu/coastalsat and all buoy information is available at maine.loboviz.com. We have augmented this dissemination with public talks at the Royal River, Damariscotta, West Bath, and Bagaduce River estuaries. What do you plan to do during the next reporting period to accomplish the goals?A number of exciting developments have allowed this project to grow rapidly since the MAFES Hatch Funding. Over the next reporting period, we plan on pursuing a number of follow on grant opportunities to develop business prospecting tools and cyberinfrastructure to reduce new aquaculture company risk: Brady, D.C., Morse, D., Gray, M., Testa, J.M., & Cornwell, J. Is the biogeochemical footprint of shellfish aquaculture the key to nutrient valuation?: a field and modeling assessment. Letter of Intent Submitted to the Northeast Regional Aquaculture Council. $200,000, Brady, D.C., Mills, K., Belle, S., Vonderweidt, C. Incorporating Environmental Change into Aquaculture Business Planning and Risk Assessment. Letter of Intent Accepted and Submission to follow in November 2018 to the NOAA Saltonstall Kennedy. $300,000, Byron, C., Brady, D.C., Keeney, N.R., Gelais, A., Costa-Pierce, B., Gower, T., Arciero, M., Quinlan, J. Ginot, T, Bouchard, D., Dwyer M. North Atlantic coastal data infrastructure and food systems forecasting. Letter of Intent to USDA NIFA Food and Agriculture Cyberinformatics Tools (FACT) was encouraged for full proposal submission. Budget is $1M between public and private partners (UNE/UMaine/Oceanicsdotio/Instrospective Systems) to develop and transfer tools for data-driven decision-making to ocean food industries. Additionally, we have already received two follow on opportunities: New high-resolution satellite-derived water-quality data informs sustainable aquaculture development. Brady, D., Boss, E., Morse, D., Thomas, A. Funded by the National Sea Grant Aquaculture Initiative funded for $692,200 from September 1st, 2018-August 31st, 2021; Optimizing production and products for scallop aquaculture. Brady, D.C. (UMaine) and Morse, D. (Maine Sea Grant). NOAA Saltonstall-Kennedy Grant funded for $295,380 for project period 9/1/2018-8/31/2020. The goal in the next project period is to continue taking dock chlorophyll samples (continuing a 16 year dataset that is unique along the coast of Maine and now we are adding a New Hampshire firm interested in developing low cost senor technology and comparing their results to our time series funded by NOAA SBIR: OpenWater - A Citizen Science Monitoring System. Kynor, D. (Creare), Boss, E., & Brady, D.C. NOAA Small Business Innovation Research (SBIR) Phase 2 funded at $400,000 for 5/1/2018-4/30/2020. The new high resolution satellite project will be the focus of new student recruiting and data analysis of new imagery too. We are adding the ability to analyze chromophoric dissolved organic matter which can be related to estuarine salinity. Knowing the salinity of your site is key to growers operating under the constraints of environmental variability.

Impacts
What was accomplished under these goals? We have made progress on all four major objectives. For the first time, growers in Maine have access to nearshore remote sensing data on a spatial resolution that matches their farms (20-50 meters). However, the temporal resolution is relatively sparse (16 days). Consequently, our future objectives and preproposal under development to MAFES is to extend this technology to include other remote sensing products that have a spatial resolution on the order of 5 days which would significantly increase the information available to growers. In addition to temperature, chlorophyll, and turbidity, we are optimistic that chromophoric dissolved organic matter (CDOM), a proxy for salinity, can be measured remotely. If successful, this would be the first remotely sensed salinity product available for growers in the world (low salinity generally increases bacterial exposure, low pH exposure, nutrient loading, and poor growth rates).

Publications

• Type: Journal Articles Status: Under Review Year Published: 2019 Citation: Adams, C.M., Mayer, L., Rawson, P., Brady, D.C., & Newell, C. (in review) Detrital protein contribution to oyster nutrition and growth in the Damariscotta estuary, Maine, USA. Marine Ecology Progress Series
• Type: Journal Articles Status: Accepted Year Published: 2019 Citation: Gray, M.W., Chapparo, O., O⿿Neill, S.P., Couture, T., Moreira, A., & Brady, D.C. (in press) Does brooding prepare young for tomorrow⿿s acidic oceans and estuaries? Special Issue of Journal of Shellfish Research
• Type: Journal Articles Status: Accepted Year Published: 2018 Citation: Bayer, S.R., Wahle, R.A., Brady, D.C., Jumars, P.A., Stokesbury, K.D.E., & Carey, J.D. (2018) Fertilization dynamics in scallop aggregations: reconciling model predictions with field measurements. Ecosphere. 9(8), e02359.
• Type: Journal Articles Status: Accepted Year Published: 2018 Citation: Testa, J.M., Brady, D.C., Murphy, R., & Kemp, W.M. (2018) Nutrient- and climate-induced shifts in the phenology of linked biogeochemical cycles in a temperate estuary. Frontiers in Marine Science. 5(114), 1-15 doi: 10.3389/fmars.2018.0011
• Type: Journal Articles Status: Accepted Year Published: 2018 Citation: Friedland, K.D., Mouw, C.B., Asch, R.G., Ferreira, A.S.A., Henson, S., Hyde, K.J., Morse, R.E., Thomas, A.C., & Brady, D.C. (2018) Phenology and time series trends of the dominant seasonal phytoplankton bloom across global scales. Global Ecology and Biogeography 27(5), 551-569 doi: 10.1111/geb.12717.
• Type: Journal Articles Status: Accepted Year Published: 2017 Citation: Snyder, J., Boss, E., Weatherbee, R., Thomas, A., Brady, D.C., and Newell, C. (2017) Oyster aquaculture site selection using Landsat 8-derived sea surface temperature, turbidity, and chlorophyll a. Frontiers in Marine Science 4(190), 1-11 doi: 10.3389/fmars.2017.00190
• Type: Journal Articles Status: Accepted Year Published: 2017 Citation: Du Clos, K.T., Jones, I.T., Carrier, T.J., Brady, D.C., and Jumars, P.A. (2017) Model-assisted measurements of suspension-feeding flow velocities. Journal of Experimental Biology 220: 2096-2107
• Type: Journal Articles Status: Accepted Year Published: 2017 Citation: Frederick, C., Brady, D.C., & Bricknell, I. (2017) Landing strips: Model development for estimating body surface area of farmed Atlantic salmon (Salmo salar). Aquaculture 473: 299-302
• Type: Journal Articles Status: Accepted Year Published: 2017 Citation: Li, B., Tanaka, K.R., Chen, Y., Brady, D.C., & Thomas, A.C. (2017) Assessing the quality of modeled bottom water temperatures from the Finite-Volume Community Ocean Model (FVCOM) in the Northwest Atlantic Region. Journal of Marine Systems. 173: 21-30