This study was supported by the National Science Foundation (OIA-1655221, OCE-1655686) and Rhode Island Sea Grant (NA22-OAR4170123, RISG22-R/2223-95-5-U). We also would like to thank the Rhode Island School of Design for developing the Vis-A-Thon project and this visualization.

1. Applying the N-mass balance model
<ol>
	<li>Download the dissolved inorganic nitrogen (DIN) data from the US Environmental Protection Agency (USEPA) for 166 stations in Narragansett Bay from 1990 to 2015. 
	NOTE: In this study, the sum of ammonium (NH4+), nitrite (NO2-), and nitrate (NO3-) concentrations were considered as the DIN concentration.</li>
	<li>Split the Narragansett Bay into fifteen boxes along its axis modified from the previous study14 using Adobe Illustrator to divide the Bay in the map (Figure 1).</li>
	<li>Apply the N-mass balance model to calculate the mean concentration of DIN at each box. 
	NOTE: In this study, the N-mass balance model, consisting of DIN input and output terms, was modified from previous studies2,15 and applied to each box (1-15) of the Narragansett Bay as Equation 1. 
	<img alt="Equation 7" src="/files/ftp_upload/65728/65728eq07v2.jpg" style="margin: auto;" />&#160; Eq. (1) 
	Table 1 shows the definitions of each term and unit used in this model of Narragansett Bay. The model calculates the mean DIN concentration by determining the difference in each box of Narragansett Bay, representing the net DIN removal by biological production. Detailed information on the N-mass balance model is shown in the previous studies2,15. The detailed values used in the model of this study were derived from the previous studies14.</li>
	<li>Calculate the potential primary production (PPP) rate based on the N-mass balance model results by converting the net DIN removal to carbon units using the Redfield ratio (C: N = 106: 16, molar ratio) in a spreadsheet file.</li>
</ol>
2. Visualizing three zones in the map of Narragansett Bay
<ol>
	<li>Plot the identified three zones in the map of Narragansett Bay as a contour plot using the Ocean Data View software.
	<ol>
		<li>Save the PPP rate data of each box as a text file (.txt) from the spreadsheet file. 
		NOTE: The .txt file also includes the location of each box number as latitude and longitude. Put the longitude as a negative value. The PPP rate data is labeled as PPP [gC&#183;m-2&#183;day-1].</li>
		<li>Load the PPP rate data into the Ocean Data View software.
		<ol>
			<li>Go to open in the File menu.</li>
			<li>Click Associate Variables Box, Latitude, Longitude with Station, latitude [degrees_north], and Longitude [degrees_east], in the Metadata Variable Association window, then click the OK button.</li>
			<li>Click the OK button in the Import window.</li>
		</ol>
		</li>
		<li>Draw the contour plot to show the PPP ranges in the map of Narragansett Bay.
		<ol>
			<li>Right-click on the map, click Zoom, drag the red box to zoom into the data area of the map, and then click on Enter.</li>
			<li>Click the 1 SCATTER window of the Layout Templates in the View menu.</li>
			<li>Right-click in the Sample panel and select Derived Variables.</li>
			<li>Click the Add button after selecting Latitude under Metadata from the list of Choices panel. Do the same thing for Longitude and then click the OK button.</li>
			<li>Select drvd: Longitude [degrees_East] as X-Variable by right-clicking on the scatter window.</li>
			<li>Select drvd: Latitude [degrees_North] as Y-Variable by right-clicking on the scatter window.</li>
			<li>Select PPP [gC&#183;m-2&#183;day -1] as Z-Variable by right-clicking on the scatter window.</li>
			<li>Select Properties by right-clicking on the scatter window and go to the Display Style option.
			<ol>
				<li>Select the Gridded field.</li>
				<li>Go to the Contours option and click the &#60;&#60; button to make 0, 0.1, and 2 values only remain in the Already Defined Panes of the left.</li>
				<li>Click the OK button.</li>
			</ol>
			</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Based on the contour plot from the Ocean Data View Software, define the edge of the brown, green, and blue zones in Narraganset Bay, and visualize the zones using Adobe Illustrator to plot three zones in the map. 
	NOTE: Following the previous study15, the PPP rate of the brown zone was over 2 gC&#183;m-2&#183;day-1, the green zone was between 0.1-2 gC&#183;m-2&#183;day-1, and the blue zone was less than 0.1 gC&#183;m-2&#183;day-1, respectively.</li>
</ol>
3. Converting the contour plot of three zones into the three-dimensional (3D) frame with LED light
<ol>
	<li>Etch three acrylic panels as 5.5&#39;&#39; x 8&#39;&#39; with a laser cutter to show the boundary of each zone.</li>
	<li>Stack three acrylic panels in an illuminated frame.Overlap each acrylic panel showing the blue, green, and brown zones. Place a panel showing green zones on top of the blue zones panel and a brown zones panel on top of that.</li>
	<li>For the second physical model, etch four acrylic sheets as 5.5&#39;&#39; x 8&#39;&#39; with a laser cutter, with the UV printed three boundaries of zones and one panel to represent the entire Narragansett Bay (as per steps 3.1-3.2).</li>
	<li>Change the color of each zone into brown, green, and blue using the LEDs placed at the bottom of the frame.</li>
</ol>

Integrated Visualization of Biogeochemical Data for Nutrient Management

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	<li>Nixon, S. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coastal+marine+eutrophication:+A+definition,+social+causes,+and+future+concerns.">Coastal marine eutrophication: A definition, social causes, and future concerns.</a> Ophelia. 41, 199-219 (1995).</li><li>Kim, J. S., Brush, M. J., Song, B., Anderson, I. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reconstructing+primary+production+in+a+changing+estuary:+A+mass+balance+modeling+approach.">Reconstructing primary production in a changing estuary: A mass balance modeling approach.</a> Limnology and Oceanography. 66 (6), 2535-2546 (2021).</li><li>Kemp, W. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Eutrophication+of+Chesapeake+Bay:+historical+trends+and+ecological+interactions.">Eutrophication of Chesapeake Bay: historical trends and ecological interactions.</a> Marine Ecology Progress Series. 303, 1-29 (2005).</li><li>Brush, M. J., Malone, T. C., Malej, A., Faganeli, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Coastal Ecosystems in Transition: A Comparative Analysis of the Northern Adriatic and Chesapeake Bay. Chapter 5, (2021).</li><li>Howarth, R. W., Marino, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nitrogen+as+the+limiting+nutrient+for+eutrophication+in+coastal+marine+ecosystems:+Evolving+views+over+three+decades.">Nitrogen as the limiting nutrient for eutrophication in coastal marine ecosystems: Evolving views over three decades.</a> Limnology and Oceanography. 51 (1 part 2), 364-376 (2006).</li><li>Paerl, H. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Controlling+eutrophication+along+the+freshwater-marine+continuum:+Dual+nutrient+(N+and+P)+reductions+are+essential.">Controlling eutrophication along the freshwater-marine continuum: Dual nutrient (N and P) reductions are essential.</a> Estuaries and Coasts. 32, 593-601 (2009).</li><li>Kim, J. S., Chapman, P., Rowe, G., DiMarco, S. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Categorizing+zonal+productivity+on+the+continental+shelf+with+nutrient-salinity+ratios.">Categorizing zonal productivity on the continental shelf with nutrient-salinity ratios.</a> Journal of Marine Systems. 206, 103336 (2020).</li><li>Rowe, G. T., Chapman, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Continental+shelf+hypoxia:+Some+nagging+questions.">Continental shelf hypoxia: Some nagging questions.</a> Gulf of Mexico Science. 20 (2), 153-160 (2002).</li><li>Nixon, S. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Eutrophication+and+the+macroscope.">Eutrophication and the macroscope.</a> Hydrobiologia. 629, 5-19 (2009).</li><li>Barbier, E. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+value+of+estuarine+and+coastal+ecosystem+services.">The value of estuarine and coastal ecosystem services.</a> Ecological Monographs. 81 (2), 169-193 (2011).</li><li>Cloern, J. E., Foster, S. Q., Kleckner, A. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phytoplankton+primary+production+in+the+world's+estuarinecoastal+ecosystem.">Phytoplankton primary production in the world's estuarinecoastal ecosystem.</a> Biogeosciences. 11 (9), 2477-2501 (2014).</li><li>Codiga, D. L., Stoffel, H. E., Oviatt, C. A., Schmidt, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Managed+nitrogen+load+decrease+reduces+chlorophyll+and+hypoxia+in+warming+temperate+urban+estuary.">Managed nitrogen load decrease reduces chlorophyll and hypoxia in warming temperate urban estuary.</a> Frontiers in Marine Science. 9, 930347 (2022).</li><li>Sigman, D. M., Hain, M. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+biological+productivity+of+the+ocean.">The biological productivity of the ocean.</a> Nature Education Knowledge. 3 (10), 21 (2012).</li><li>Kremer, J. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simulating+property+exchange+in+estuarine+ecosystem+models+at+ecologically+appropriate+scales.">Simulating property exchange in estuarine ecosystem models at ecologically appropriate scales.</a> Ecological Modelling. 221 (7), 1080-1088 (2010).</li><li>Kim, J. S., Chapman, P., Rowe, G., DiMarco, S. F., Thornton, D. C. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Implications+of+different+nitrogen+input+sources+for+potential+production+and+carbon+flux+estimates+in+the+coastal+Gulf+of+Mexico+(GOM)+and+Korean+Peninsula+coastal+waters.">Implications of different nitrogen input sources for potential production and carbon flux estimates in the coastal Gulf of Mexico (GOM) and Korean Peninsula coastal waters.</a> Ocean Science. 16, 45-63 (2020).</li><li>Lake, S. J., Brush, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+contribution+of+microphytobenthos+to+total+productivity+in+upper+Narragansett+Bay,+Rhode+Island.">The contribution of microphytobenthos to total productivity in upper Narragansett Bay, Rhode Island.</a> Estuarine, Coastal and Shelf Science. 95 (2-3), 289-297 (2011).</li><li>Brush, M. J., Nixon, S. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+the+role+of+macroalgae+in+a+shallow+sub-estuary+of+Narragansett+Bay,+RI+(USA).">Modeling the role of macroalgae in a shallow sub-estuary of Narragansett Bay, RI (USA).</a> Ecological Modelling. 221 (7), 1065-1079 (2010).</li><li>Deacutis, C. F., Murray, D., Prell, W., Saarman, E., Korhun, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hypoxia+in+the+upper+half+of+Narragansett+Bay,+RI,+during+August+2001+and+2002.">Hypoxia in the upper half of Narragansett Bay, RI, during August 2001 and 2002.</a> Northeastern Naturalist. 13 (Special Issue 4), 173-198 (2006).</li><li>Oviatt, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Managed+nutrient+reduction+impacts+on+nutrient+concentrations,+water+clarity,+primary+production,+and+hypoxia+in+a+north+temperate+estuary.">Managed nutrient reduction impacts on nutrient concentrations, water clarity, primary production, and hypoxia in a north temperate estuary.</a> Estuarine, Coastal and Shelf Science. 199, 25-34 (2017).</li><li>Boesch, D. 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The authors have no conflicts of interest to declare.

This study estimated the extent of nutrient impacts from riverine inputs in Narraganset Bay (NB) based on the N-mass balance model by defining the three theoretical zones. Historically, hypoxic zones appeared near the Providence River, the western side of Greenwich Bay, and Mount Hope Bay during the summer period18, which were defined as brown zones in this study. Moreover, the zonation of NB is comparable to the results of a previous study19, which examined nutrient concen...

Primary productivity, the production of organic compounds by phytoplankton, fuels ecosystem food webs, and is important for understanding the system&#39;s function in response to environmental changes1,2. Estuarine primary productivity is also closely linked to eutrophication which is defined as excessive nutrients in the ecosystem1, causing several harmful consequences in the coastal regions, such as an overgrowth of phytoplankton leading to large algal blooms and subsequent hypoxia3,4. Importantly, primary productivity in estuaries is highly dependent on the riverine nutrient loading, particularly nitrogen concentrations, which are the typical limiting nutrient in most temperate ocean ecosystems5,6. However, an estimation of the extent of riverine nitrogen impacts in coastal areas remains challenging.
To estimate the estuarine primary productivity, a nitrogen (N) mass balance model is a useful tool to calculate nitrogen fluxes2. The N-mass balance model also provides an understanding of biological mechanisms beyond data observations, revealing information at the edges of different primary productivity zones7. Three different zones8, defined as brown, green, and blue zones, are particularly useful for predicting the impact of nutrient loading in hypoxic regions. The brown zone, defined as the nearest region of a river mouth, represents a high physical process, the green zone has high biological productivity, and the blue zone represents low biological process. The boundary of each zone depends on river flow, nutrient concentrations, and mixing rates8.
Narragansett Bay (NB) is a coastal, temperate estuary in Rhode Island, USA, supporting economic and ecological services and goods9,10,11, in which hypoxia has been consistently occurring. These hypoxic events, defined as the period of low dissolved oxygen (i.e., less than 2-3 mg of oxygen per liter), are particularly prevalent in July and August and are heavily impacted by riverine nitrogen loading during these months12. With an increase in primary production and hypoxia due to anthropogenic emissions of nutrients13, understanding the nitrogen inputs into NB is critical to managing and addressing coastal issues such as eutrophication and hypoxia. Thus, in this study, the rate of primary production in NB is calculated from the N-mass balance model using historically observed nutrient data, especially dissolved inorganic nitrogen (DIN). Based on the results of the N-mass balance model by converting to carbon units using the Redfield ratio, three different primary productivity zones were identified to visualize the extent of nitrogen influence from the river in NB. The model was then recreated into a 3D representation to better visualize the different zones. The products produced from this study can better inform nutrient management in NB in response to hypoxia and eutrophication. Further, results from this study are applicable to other coastal regions to visualize the effects of riverine transport on nutrients and primary productivity.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Adobe Illustrator&#160;</td>
			<td>Adobe</td>
			<td>version 27.6.1</td>
			<td>https://www.adobe.com/products/illustrator.html</td>
		</tr>
		<tr>
			<td>Ampersand Gessobord Uncradled 1/8&#34; Profile 8&#34; x 8&#34;</td>
			<td>Risdstore</td>
			<td>70731053088</td>
			<td>https://www.risdstore.com/ampersand-gessobord-8x8-flat-1-8-profile.html</td>
		</tr>
		<tr>
			<td>Ocean Data View software</td>
			<td></td>
			<td></td>
			<td>https://odv.awi.de/en/software/download/</td>
		</tr>
		<tr>
			<td>W-Series (Wide) Flexible LED Strip Light - Ultra Bright (18 LEDs/foot)</td>
			<td>aspectLED</td>
			<td>SKU AL-SL-W-U</td>
			<td>https://www.aspectled.com/products/w-wide-5050-ultra-bright?gclid=CjwKCAjwm4ukBhAuEiwA0z 
			QxkyqisRPqBcHvXEW8KcJE-bK0d2cvGtqlOxXWJI_ 
			E2rd6DzttPR0FLRoCgfkQAvD_BwE</td>
		</tr>
	</tbody>
</table>

visualization of productivity zones based on nitrogen mass balance model in narragansett bay, rhode island

Primary productivity in the coastal regions, linked to eutrophication and hypoxia, provides a critical understanding of ecosystem function. Although primary productivity largely depends on riverine nutrient inputs, estimation of the extent of riverine nutrient influences in the coastal regions is challenging. A nitrogen mass balance model is a practical tool to evaluate coastal ocean productivity to understand biological mechanisms beyond data observations. This study visualizes the biological production zones in Narragansett Bay, Rhode Island, USA, where hypoxia frequently occurs, by applying a nitrogen mass balance model. The Bay is divided into three zones - brown, green, and blue zones - based on primary productivity, which are defined by the mass balance model results. Brown, green, and blue zones represent a high physical process, a high biological process, and a low biological process zone, depending on river flow, nutrient concentrations, and mixing rates. The results of this study can better inform nutrient management in the coastal ocean in response to hypoxia and eutrophication.

Author Spotlight: Understanding Riverine Nitrogen Impacts and Primary Productivity for Effective Nutrient Management

Visualization of Productivity Zones Based on Nitrogen Mass Balance Model in Narragansett Bay, Rhode Island

Three theoretical zones of Narragansett Bay based on the N-mass balance model 
The three theoretical zones in Narragansett Bay (NB) were defined based on the N-mass balance model results, in which the DIN data were applied to fifteen boxes of NB, and then the mean DIN in each box was converted to the PPP rates for the summer period. As shown in Figure 2, based on the mean summer (June to September) PPP rates of each box, three (brown, green, and blue) zones in NB were i...

Watch this Scientific Journal Video about Visualization of Productivity Zones Based on Nitrogen Mass Balance Model in Narragansett Bay, Rhode Island at JoVE.com

Here, we aim to visualize the zonation of biological productivity in Narragansett Bay, Rhode Island, based on the nitrogen mass balance model. The results will inform nutrient management in the coastal regions to reduce hypoxia and eutrophication.

Primary productivity in the coastal regions, linked to eutrophication and hypoxia, provides a critical understanding of ecosystem function. Although ...

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Applying the N-Mass Balance Model for Visualizing Biological Productivity Zones in Narragansett Bay, Rhode Island

262 Views.  University of Texas - Rio Grande Valley.  Here, we aim to visualize the zonation of biological productivity in Narragansett Bay, Rhode Island, based on the nitrogen mass balance model. The results will inform nutrient management in the coastal regions to reduce hypoxia and eutrophication.

Integrated Visualization of Biogeochemical Data for Nutrient Management

Summary