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Ecological Marine Units: A 3-D Mapping of the Ocean Based on NOAA’s World Ocean Atlas EBM Tools Network/OpenChannels Webinar May 17, 2017 Dawn Wright, Chief Scientist, Environmental Systems Research Institute (aka Esri) Affiliated Professor, Oregon State University Roger Sayre, USGS Senior Scientist for Ecosystems, Climate and Land Use Change Sean Breyer, Esri ArcGIS Content Program Manager

Ecological Marine Units · 2017-07-13 · Ecological Marine Units: A 3-D Mapping of the Ocean Based on NOAA’s World Ocean Atlas EBM Tools Network/OpenChannels Webinar May 17, 2017

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Ecological Marine Units:A 3-D Mapping of the Ocean Based on NOAA’s World Ocean Atlas

EBM Tools Network/OpenChannels WebinarMay 17, 2017

Dawn Wright, Chief Scientist, Environmental Systems Research Institute (aka Esri)Affiliated Professor, Oregon State University

Roger Sayre, USGS Senior Scientist for Ecosystems, Climate and Land Use ChangeSean Breyer, Esri ArcGIS Content Program Manager

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HORIZONTALLY on the LEFT VERTICALLY on the RIGHT

ON THE LEFT: 37 mutually exclusive EMU clusters (shown with ELUs) representing the maximum global horizontal dimensions of the clusters AT SELECTED DEPTHS AND in different colors

ON THE RIGHT: Vertical profile area graph with depth on Y-axis and cell count for each Cluster/area it covers on X-axis. This graph shows the cluster variety at the top of the water column and through the water column we can see how each Cluster either slowly disappears with depth or in some cases deep water clusters become more dominant. It also help illustrate how in some cases the cluster is spread across the CMECS depth terms and we may need a better data-driven depth name for the clusters. Interesting too that there are apparent depths where groups of clusters end -100 to -200m and -500 to -700m and -1400 to -1600m.Our diagram illustrates that there is no simple clear-cutHORIZONTAL boundary for water attributes – an overlayof depth distribution on it will also be informative

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How do we best visualize something that is really continuous and in 3D? One way is to conceptualize the data as columnar stacks of cells whose centroids define the point mesh

As we zoom in, cylinders will pop up, representing data points from NOAA’s World Ocean Atlas, 52 million observations over a span of 50 years about the primary physical and chemical characteristics of the oceans at 105 depth levels: in other words, the key variables that enable life throughout the ocean such as salinity, temperature, dissolved oxygen, phosphate, nitrate, silicate.

This is actually a continuous grid of data at the surface and continuous volumes at depth but we are representing the units as columns so that you can see sideways better into the layers at depth. One major point is that nutrient and oxygen distributions in particular not only shape but ARE SHAPED by biological processes (physicochemical).

Red discs represent a layer of the water that is hypoxic, i.e., depleted in oxygen.

This information will be hugely significant biologically, to be able to see that over a global expanse, where it thins out, where it mixes with other water masses. This is a global framework.

Will soon start time slicing into monthly averages, OBIS has not been added to this yet, but that is in progress.

It will be exciting to be able to continually populate and improve this with data from any cruise or expedition as we go forward in time. NOAA administrator Kathryn Sullivan likens this to a christmas tree that we ALL can hang ornaments on now, and over time really come to a richer understanding of our ocean, while also helping us to understand what’s the next science data or target we should go after to make this more useful, especially for MPA designation or evaluation and CMSP.

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POC may be useful more as a validation of the clustering rather than as input (POC data are scattered, hard to obtain from Lutz or to compile from NASA, hard to recalculate for entire global water column)

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AF

EMU logo by Esri’s Sean Breyer

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