20190913 15065300 1.0 FGDC CSDGM Metadata FALSE file://\\MAGEOPROC\GIS_Data\abarnett\Resilient_Coastal_Sites_Archive\SAGOM\Data_Distribute_10April2020\South_Atlantic\Migration_Space\Migration_Space_units.gdb Local Area Network South_Atlantic_Additional_Migration_Space_SLR15 002 1277322.724100 1752882.724100 -1685953.505400 -229633.505400 1 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) NAD_1983_Albers <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.5'><WKT>PROJCS["NAD_1983_Albers",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Albers"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-96.0],PARAMETER["Standard_Parallel_1",20.0],PARAMETER["Standard_Parallel_2",60.0],PARAMETER["Latitude_Of_Origin",40.0],UNIT["Meter",1.0]]</WKT><XOrigin>-16688100</XOrigin><YOrigin>-9068200</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision></ProjectedCoordinateSystem> 20200410 10303900 20200410 10313000 150000000 5000 FGDC Version 6.2 (Build 9200) ; Esri ArcGIS 10.5.1.7333 South_Atlantic_Additional_Migration_Space_SLR15 2019-10-01T00:00:00 Eastern Conservation Science of The Nature Conservancy Eastern Conservation Science of The Nature Conservancy 99 Bedford ST, 5th floor Boston MA 02111 eScience@tnc.org 617-532-8300 Eastern Conservation Science of The Nature Conservancy Eastern Conservation Science of The Nature Conservancy False Eastern Conservation Science of The Nature Conservancy 1 -83.068677 -75.172099 37.172836 24.034516 Spatial: Dataset was developed for the South Atlantic US region which includes the following state coastlines: VA, NC, SC, GA, and FL. Temporal: Dataset was derived from NOAA SLR Viewer marsh migration data (January 2018) and 2010 NOAA Coastal-Change Analysis Program (C-CAP) regional land cover datasets. These datasets will be updated in the future by NOAA. 2018-12-03T00:00:00 Migration space is a central concept in the “Resilient Coastal Sites for Conservation in the South Atlantic" project, and a key factor in estimating site resilience. Migration space is defined as the area of adjacent low-lying land that is potentially suitable for supporting tidal habitats in the future as sea levels rise, and into which the current habitats could migrate. For example, as sea levels rose over the last century, Maryland’s Blackwater National Wildlife Refuge gained 2,949 acres of new salt marsh at the existing marsh’s upland edge (i.e., in the migration space, Lerner et al. 2013). The concept of migration space appears in many coastal resilience studies where it has been variously called “accommodation space,” “future marsh,” “marsh migration opportunity areas,” “migration pathways,” “potential marsh zone,” or “marsh migration opportunity areas” (Schuerch et al. 2018; C. Chaffee, pers. comm.; K. Lucey, pers. comm.; Maine Natural Areas Program, 2016). The transition process works like this: tidal marshes exist in a narrow zone between the mean high tide and the mean high water line. As the tide rises, existing marshes become increasingly inundated, creating unsuitable conditions for vegetation growth and converting the marsh to unconsolidated substrate or open water. Meanwhile, new land suitable for habitat development may become available in the immediately adjacent lowlands as they start receiving regular tidal inundation. If conditions are right, the marsh may be able to migrate onto this land. To delineate migration space for the full project area, we requested the latest SLR Viewer marsh migration data, with no accretion rate, for all the NOAA geographic units within the project area, from NOAA (N. Herold, pers. comm., 2018). The NOAA SLR Viewer data uses a modified bathtub approach that considers local and regional tidal variability for SLR scenarios from 0.5 to 10 feet in 0.5-foot increments. The NOAA model does not map migration space per se, but instead predicts the distribution of... <DIV STYLE="text-align:Left;"><DIV><DIV>To assess site resilience, we divided the coast into 1,232 individual sites centered around each tidal marsh or complex of tidal habitats. For each site, we estimated the amount of migration space available under four sea-level rise scenarios and we identified the amount of buffer area surrounding the whole tidal complex. We then examined the physical properties and condition characteristics of the site and its features using newly developed analyses as well as previously published and peer-reviewed datasets.Sites vary widely in the amount and suitability of migration space they provide. This is determined by the physical structure of the site and the intactness of processes that facilitate migration. A marsh hemmed in by rocky cliffs will eventually convert to open water, whereas a marsh bordered by low lying wetlands with ample migration space and a sufficient sediment supply will have the option of moving inland. As existing tidal marshes degrade or disappear, the amount of available high-quality migration space becomes an indicator of a site’s potential to support estuarine habitats in the future. The size and shape of a site’s migration space is dependent on the elevation, slope, and substrate of the adjacent land. The condition of the migration space also varies substantially among sites. For some tidal complexes, the migration space contains roads, houses, and other forms of hardened structures that resist conversion to tidal habitats, while the migration space of other complexes consists of intact and connected freshwater wetlands that could convert to tidal habitats.Our aim was to characterize each site’s migration space but not predict its future composition. Towards this end, we measured characteristics of the migration space related to its size, shape, volume, and condition, and we evaluated the options available to the tidal complex to rearrange and adjust to sea level rise. In the future, the area will likely support some combination of salt marsh, brackish marsh and tidal flat, but predictions concerning the abundance and spatial arrangement of the migration space’s future habitats are notoriously difficult to make because nature’s transitions are often non-linear and facilitated by pulses of disturbance and internal competition. For instance, in response to a 1.4 mm increase in the rate of SLR, the landward migration of low marsh cordgrass in some New York marshes appears to be displacing high marsh (Donnelly & Bertness 2001). Thus, our assumption was simply that a tidal complex with a large amount of high quality and heterogeneous migration space will have more options for adaptation, and will be more resilient, than a tidal complex with a small amount of degraded and homogenous migration space.To delineate migration space for the full project area, we requested the latest SLR Viewer (Marcy et al. 2011) marsh migration data, with no accretion rate, for all the NOAA geographic units within the project area, from NOAA (N. Herold, pers. comm., 2018). Specifically, we obtained data for the following states in the project area: Virginia, North Carolina, South Carolina, Georgia, and Florida. As accretion is very location-dependent, we chose not to use one of the three SLR Viewer accretion rates because they were flat rates applied across each geographic unit. For each geography, we combined four SLR scenarios (1.5’, 3’, 4’, and 6.5’) with the baseline scenario to identify pixels that changed from baseline. We only selected cells that transitioned to tidal habitats (unconsolidated shoreline, salt marsh, and transitional / brackish marsh) and not to open water or upland habitat. We combined the results from each of the geographies and projected to NAD83 Albers. The resultant migration space was then resampled to a 30-m grid and snapped to the NOAA 2010 C-CAP land cover grid (NOAA, 2017). The tidal complex grid and the migration space grid were combined to ensure that there were no overlapping pixels. While developed areas were not allowed to be future marsh in NOAA’s SLR Viewer marsh migration model, we still removed all roads and development, as represented in the original 30-m NOAA 2010 C-CAP land cover grid, from the migration space. We took this step as differences in spatial resolution between the underlying elevation and land cover datasets could occasionally result in small amounts of development in our resampled migration space. The remaining migration space was then spatially grouped into contiguous regions using an eight-neighbor rule that defined connected cells as those immediately to the right, left, above, or diagonal to each other. The region-grouped grid was converted to a polygon, and the SLR scenario represented by each migration space footprint was assigned to each polygon. Finally, the migration space scenario polygons that intersected any of the tidal complexes were selected. Because a single migration space polygon could be adjacent to and accessible to more than one tidal complex unit, each migration space polygon was linked to their respective tidal complex units with a unique ID by restructuring and aggregating the output from a one-to-many spatial join in ArcGIS. This linkage enabled the calculation of attributes for each tidal complex such as total migration space acreage, total number of migration space units, and the percent of the tidal complex perimeter that was immediately adjacent to migration space. Similar attributes were calculated for each migration space unit including total tidal complex acreage and number of tidal complex units.This dataset shows additional migration space units in the project area for the 1.5-foot sea level rise scenario. Additional migration space units are migration space units that did not spatially intersect current tidal marshes or were spatially disjunct from the migration space of current tidal marshes. Because additional migration space units were not directly associated with a tidal complex. these units were NOT used in the calculation of a tidal complex’s resilience score. The spatial separation could be due to roads, waterbodies, waterways, oil and gas fields, etc. Depending on local factors and context, the degree to which these features will prevent marshes from accessing the additional migration space areas in the future is unknown and likely varies by site.There were thousands of small and disconnected additional migration space areas, often individual pixels, typically found in urban settings, remote upstream riverine areas, or far from any migration space units or tidal marshes. We did not consider these isolated occurrences as additional migration space because they are unlikely to be important future marsh areas. We identified isolated migration space areas using the following approach. First, for unconfirmed additional migration space areas, an iterative analysis of the Euclidean distance from current tidal marshes and their migration space areas, including confirmed additional migration space, was performed. Next, pixels that did not meet the distance thresholds in the first step but were within 60 meters of a NHDPlus v2 (USEPA & USGS, 2012) streamline were retained as additional migration space. Any remaining pixels less than or equal to two acres in size were then removed from the additional migration space. Finally, visual inspection was used to remove isolated migration space areas that were not identified through the previous steps. We assigned resilience scores to the additional migration space areas using several approaches. First, we spatially allocated resilience scores based on Euclidean distance from tidal marshes or migration space units. While this approach was a good starting point, there were migration space areas whose score assignments had to be done manually or by taking the highest of two equidistant nearby scores. The manual assignment included straightforward cases, but often it was unclear how marshes might move into a migration space area (e.g., will marsh travel through waterways to nearby migration space areas; will marsh use all migration space areas along a waterway or waterbody or only on the same side as the current marsh?). For sites with unclear relationships to current marshes and their migration space, the highest resilience score in the general geographic area of the additional migration space was assigned. Consequently, please interpret the scores of the additional migration space with caution and use local expertise and knowledge as you see fit. REFERENCESChaffee, C, Coastal policy analyst for the R.I. Coastal Resources Management Council. personal communication. April 4, 2017.Donnelly, J.P, & Bertness, M.D. 2001. Rapid shoreward encroachment of salt marsh cordgrass in response to accelerated sea-level rise. PNAS 98(25) www.pnas.org/cgi/doi/10.1073/pnas.251209298Herold, N. 2018. NOAA Sea Level Rise (SLR) Viewer marsh migration data (10-m), with no accretion rate, for all SLR scenarios from 0.5-ft. to 10.0-ft. for VA, NC, SC, GA, and FL. Personal communication Jan. 24, 2018. Lerner, J.A., Curson, D.R., Whitbeck, M., & Meyers, E.J., Blackwater 2100: A strategy for salt marsh persistence in an era of climate change. 2013. The Conservation Fund (Arlington, VA) and Audubon MD-DC (Baltimore, MD).Lucey, K. NH Coastal Program. Personal Communication. April 4, 2017.Maine Natural Areas Program. 2016. Coastal Resiliency Datasets, Schlawin, J and Puryear, K., project leads. http://www.maine.gov/dacf/mnap/assistance/coastal_resiliency.htmlMarcy, D., Herold, N., Waters, K., Brooks, W., Hadley, B., Pendleton, M., Schmid, K., Sutherland, M., Dragonov, K., McCombs, J., Ryan, S. 2011. New Mapping Tool and Techniques For Visualizing Sea Level Rise And Coastal Flooding Impacts. National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center. Originally published in the Proceedings of the 2011 Solutions to Coastal Disasters Conference, American Society of Civil Engineers (ASCE), and reprinted with permission of ASCE(<A href="https://coast.noaa.gov/slr/">https://coast.noaa.gov/slr/</A>).National Oceanic and Atmospheric Administration (NOAA), Office for Coastal Management. “VA_2010_CCAP_LAND_COVER,” “NC_2010_CCAP_LAND_COVER,” “SC_2010_CCAP_LAND_COVER,” “GA_2010_CCAP_LAND_COVER,” “FL_2010_CCAP_LAND_COVER”. Coastal Change Analysis Program (C-CAP) Regional Land Cover. Charleston, SC: NOAA Office for Coastal Management. Accessed September 2017 at <A href="http://www.coast.noaa.gov/ccapftp">www.coast.noaa.gov/ccapftp</A>.Schuerch, M.; Spencer, T.; Temmerman, S.; Kirwan, M L.; Wolff, C.; Linck, D.; McOwen, C.J.; Pickering, M.D.; Reef, R.; Vafeidis, A.T.; Hinkel J.; Nicholls, R.J.; and Sally Brown. 2018. Future response of global coastal wetlands to sea-level rise. Nature 561: 231-234. U.S. Environmental Protection Agency (USEPA) and the U.S. Geological Survey (USGS). 2012. National Hydrography Dataset Plus – NHDPlus. Version 2.01.</DIV></DIV></DIV> The Nature Conservancy reserves all rights in data provided. All data are provided as is. This is not a survey quality dataset. The Nature Conservancy makes no warranty as to the currency, completeness, accuracy or utility of any specific data. This disclaimer applies both to individual use of the data and aggregate use with other data. It is strongly recommended that careful attention be paid to the contents of the metadata file associated with these data. resilient coastal sites migration space migration space unit tidal complex resilience sea level rise marsh migration climate resilience South Atlantic US <DIV STYLE="text-align:Left;"><DIV><DIV>The Nature Conservancy compiled this data set from publicly available data sources and this data is freely distributable without permission from Eastern Division Conservation Science. This data set must be cited on all electronic and hard copy products using the language of the Data Set Credit. The Nature Conservancy shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any sale, distribution, loan, or offering for use of these digital data, in whole or in part, is prohibited without the approval of The Nature Conservancy. The use of these data to produce other GIS products and services with the intent to sell for a profit is prohibited without the written consent of The Nature Conservancy. All parties receiving these data must be informed of these restrictions. The Nature Conservancy shall be acknowledged as data contributors to any reports or other products derived from these data.</DIV></DIV></DIV>, <DIV STYLE="text-align:Left;"><DIV><DIV>Neither The Nature Conservancy nor any of its partners makes any warranty, expressed or implied as to the use or appropriateness of use of the enclosed data, nor are there warranties of merchantability or fitness for a particular purpose or use. No representation is made as to the currency, accuracy or completeness of the information in this dataset or of the data sources on which it is based. Neither The Nature Conservancy nor any partners shall be liable for any lost profits or consequential damages, or claims against the user by third parties.</DIV></DIV></DIV> <DIV STYLE="text-align:Left;"><DIV><DIV>The Nature Conservancy compiled this data set from publicly available data sources and this data is freely distributable without permission from Eastern Division Conservation Science. This data set must be cited on all electronic and hard copy products using the language of the Data Set Credit. The Nature Conservancy shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any sale, distribution, loan, or offering for use of these digital data, in whole or in part, is prohibited without the approval of The Nature Conservancy. The use of these data to produce other GIS products and services with the intent to sell for a profit is prohibited without the written consent of The Nature Conservancy. All parties receiving these data must be informed of these restrictions. The Nature Conservancy shall be acknowledged as data contributors to any reports or other products derived from these data.</DIV></DIV></DIV>, <DIV STYLE="text-align:Left;"><DIV><DIV>Neither The Nature Conservancy nor any of its partners makes any warranty, expressed or implied as to the use or appropriateness of use of the enclosed data, nor are there warranties of merchantability or fitness for a particular purpose or use. No representation is made as to the currency, accuracy or completeness of the information in this dataset or of the data sources on which it is based. Neither The Nature Conservancy nor any partners shall be liable for any lost profits or consequential damages, or claims against the user by third parties.</DIV></DIV></DIV> Eastern Conservation Science of The Nature Conservancy Eastern Conservation Science of The Nature Conservancy 99 Bedford ST, 5th floor Boston MA 02111 eScience@tnc.org 617-532-8300 Eastern Conservation Science of The Nature Conservancy Eastern Conservation Science of The Nature Conservancy File Geodatabase Feature Class dataset 6539 Simple FALSE 6539 TRUE FALSE South_Atlantic_Additional_Migration_Space_SLR15 Feature Class 6539 Additional migration space units for the 1.5-foot sea level rise scenario Eastern Conservation Science of The Nature Conservancy OBJECTID FID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. MS_ID Additional Migration Space ID Integer 4 0 0 Unique identification number for each discrete additional migration space unit. Eastern Conservation Science of The Nature Conservancy Unique ID's for the migration space units were initially automatically generated but not all migration space units were associated with tidal complexes so these units were excluded from the analysis, hence unsequential numeric IDs for the migration space units. MS_Acres Additional Migration Space Acres Single 4 0 0 Area of the additional migration space unit in acres. Eastern Conservation Science of The Nature Conservancy Acreage of each migration space unit was calculated in ArcGIS. MS_Perim Additional Migration Space Perimeter Single 4 0 0 Length of the boundary (km) of the additional migration space unit. Eastern Conservation Science of The Nature Conservancy Perimeter of each migration space unit was calculated in km in ArcGIS. SLR Sea Level Rise Scenario Integer 4 0 0 Sea level rise (SLR) scenario in feet, for which the additional migration space area units were derived. Eastern Conservation Science of The Nature Conservancy SLR scenario information was added to the dataset in ArcGIS CSR Coastal Shoreline Region String 50 0 0 To facilitate comparisons between similar types of ecosystems and estuaries, we divided the study area into four coastal shoreline regions associated with discrete geographic stretches of shoreline that share similar processes and dominant estuary types. Stratifying the results within the shoreline regions allowed us to account for systematic variation in processes, geomorphology, habitat types, and species use, and thus make fair comparisons of resilience characteristics within regions of similar estuary types as opposed to comparing across types. Eastern Conservation Science of The Nature Conservancy CSR names were assigned to the polygons in ArcGIS RESILB1st Estimated Resilience + Migration Space Trend Stratified Z-score Potentially Associated with the Additional Migration Space Unit Double 8 0 0 Z-value for resilience score with migration space trend boost. Tidal complex units whose migration space showed a significant increase (p < .05) from the 1.5 to 6.5-ft. SLR scenario received an additional 0.50 standard deviation units to their score. Because additional migration space units were not directly associated with a tidal complex, these units were NOT used in the calculation of a tidal complex’s resilience score. We assigned resilience scores to the additional migration space areas using several approaches. First, we spatially allocated resilience scores based on Euclidean distance from tidal marshes or migration space units. While this approach was a good starting point, there were migration space areas whose score assignments had to be done manually or by taking the highest of two equidistant nearby scores. The manual assignment included straightforward cases, but often it was unclear how marshes might move into a migration space area (e.g., will marsh travel through waterways to nearby migration space areas; will marsh use all migration space areas along a waterway or waterbody or only on the same side as the current marsh?). For sites with unclear relationships to current marshes and their migration space, the highest resilience score in the general geographic area of the additional migration space was assigned. Consequently, please interpret the scores of the additional migration space with caution and use local expertise and knowledge as you see fit. Eastern Conservation Science of The Nature Conservancy RESILB1stC Estimated Resilience + Migration Space Trend Stratified Z-score Class Potentially Associated with the Additional Migration Space Unit String 50 0 0 The z-score for a tidal complex’s resilience score with migration space trend was assigned to one of seven classes: far below average, below average, slightly below average, average, slightly above average, average, and far above average. This class indicates how far above or below the mean the resilience score is for the coastal shoreline region. Because additional migration space units were not directly associated with a tidal complex, these units were NOT used in the calculation of a tidal complex’s resilience score. We assigned resilience scores to the additional migration space areas using several approaches. First, we spatially allocated resilience scores based on Euclidean distance from tidal marshes or migration space units. While this approach was a good starting point, there were migration space areas whose score assignments had to be done manually or by taking the highest of two equidistant nearby scores. The manual assignment included straightforward cases, but often it was unclear how marshes might move into a migration space area (e.g., will marsh travel through waterways to nearby migration space areas; will marsh use all migration space areas along a waterway or waterbody or only on the same side as the current marsh?). For sites with unclear relationships to current marshes and their migration space, the highest resilience score in the general geographic area of the additional migration space was assigned. Consequently, please interpret the scores of the additional migration space with caution and use local expertise and knowledge as you see fit. Eastern Conservation Science of The Nature Conservancy Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. SA_PER Percent of Additional Migration Space Permanently Protected Single 4 0 0 Percent of the additional migration space unit that is permanently protected from development (i.e., has a GAP status of 1, 2, or 3). Eastern Conservation Science of The Nature Conservancy FD_PER Additional Migration Space Future Development Percent Single 4 0 0 Percent of the additional migration space unit expected to be developed by 2100. Predicted future development is from the National Land Transformation Model (http://ltm.agriculture.purdue.edu/usgs.htm), an urban expansion model with projections to 2100 for the US. 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BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB//2Q== Eastern Conservation Science of The Nature Conservancy Eastern Conservation Science of The Nature Conservancy 99 Bedford ST, 5th floor Boston MA 02111 eScience@tnc.org 617-532-8300 Eastern Conservation Science of The Nature Conservancy To delineate marsh migration space, the latest NOAA Sea Level Rise (SLR) Viewer marsh migration data (ftp://coast.noaa.gov/pub/crs/SLR/) was downloaded for the project area. The NOAA SLR Viewer data uses a modified bathtub approach that considers local and regional tidal variability for SLR scenarios from 1 to 10 feet in .5-foot increments. The NOAA model does not map migrations per se, but instead predicts the distribution of future habitat types based on the SLR scenario and tidal class thresholds. To convert the results to migration space, we combined the area of four predicted habitat classes: brackish marsh, tidal marsh, tidal flat and open water into a single spatial extent. This eliminated error in habitat class predictions and focused only on the spatial extent of the migration space. To delineate migration space for the full project area, we downloaded the latest SLR Viewer marsh migration data, with no accretion rate, for the following states in the project area: Virginia, North Carolina, South Carolina, Georgia, and Florida. As accretion is very location-dependent, we chose not to use one of the three SLR Viewer accretion rates because they were flat rates applied across each geographic unit. For each geography, we combined four SLR scenarios (1.5’, 1.5’, 3’, 4’, and 6.5’) with the baseline scenario to identify pixels that changed from baseline. We only selected cells that transitioned to tidal habitats (unconsolidated shoreline, salt marsh, and transitional / brackish marsh) and not to open water or upland habitat. We combined the results from each of the geographies and projected to NAD83 Albers. The resultant migration space was then resampled to a 30-m grid and snapped to the 2010 NOAA C-CAP land cover grid. The tidal complex grid and the migration space grid were combined to ensure that there were no overlapping pixels. While developed areas were not allowed to be future marsh in NOAA’s SLR Viewer marsh migration model, we still removed all roads and development, as represented in the original 30-m NOAA 2010 C-CAP land cover grid, from the migration space. We took this step as differences in spatial resolution between the underlying elevation and land cover datasets could occasionally result in small amounts of development in our resampled migration space. The remaining migration space was then spatially grouped into contiguous regions using an eight-neighbor rule that defined connected cells as those immediately to the right, left, above, or diagonal to each other. The region-grouped grid was converted to a polygon, and the SLR scenario represented by each migration space footprint was assigned to each polygon. Finally, the migration space scenario polygons that intersected any of the tidal complexes were selected. Because a single migration space polygon could be adjacent to and accessible to more than one tidal complex unit, each migration space polygon was linked to their respective tidal complex units with a unique ID by restructuring and aggregating the output from a one-to-many spatial join in ArcGIS. This linkage enabled the calculation of attributes for each tidal complex such as total migration space acreage, total number of migration space units, and the percent of the tidal complex perimeter that was immediately adjacent to migration space. Similar attributes were calculated for each migration space unit including total tidal complex acreage and number of tidal complex units. Additional migration space units are migration space units that did not spatially intersect current tidal marshes or were spatially disjunct from the migration space of current tidal marshes. Because additional migration space units were not directly associated with a tidal complex, these units were NOT used in the calculation of a tidal complex’s resilience score. The spatial separation could be due to roads, waterbodies, waterways, oil and gas fields, etc. Depending on local factors and context, the degree to which these features will prevent marshes from accessing the additional migration space areas in the future is unknown and likely varies by site. There were thousands of small and disconnected additional migration space areas, often individual pixels, typically found in urban settings, remote upstream riverine areas, or far from any migration space units or tidal marshes. We did not consider these isolated occurrences as additional migration space because they are unlikely to be important future marsh areas. We identified isolated migration space areas using the following approach. First, for unconfirmed additional migration space areas, an iterative analysis of the Euclidean distance from current tidal marshes and their migration space areas, including confirmed additional migration space, was performed. Next, pixels that did not meet the distance thresholds in the first step but were within 60 meters of a NHDPlus v2 (USEPA & USGS, 2012) streamline were retained as additional migration space. Any remaining pixels less than or equal to two acres in size were then removed from the additional migration space. Finally, visual inspection was used to remove isolated migration space areas that were not identified through the previous steps. REFERENCES U.S. Environmental Protection Agency (USEPA) and the U.S. Geological Survey (USGS). 2012. National Hydrography Dataset Plus – NHDPlus. Version 2.01. <DIV STYLE="text-align:Left;"><DIV><DIV>The Nature Conservancy compiled this data set from publicly available data sources and this data is freely distributable without permission from Eastern Division Conservation Science. This data set must be cited on all electronic and hard copy products using the language of the Data Set Credit. The Nature Conservancy shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any sale, distribution, loan, or offering for use of these digital data, in whole or in part, is prohibited without the approval of The Nature Conservancy. The use of these data to produce other GIS products and services with the intent to sell for a profit is prohibited without the written consent of The Nature Conservancy. All parties receiving these data must be informed of these restrictions. The Nature Conservancy shall be acknowledged as data contributors to any reports or other products derived from these data.</DIV></DIV><DIV><DIV></DIV></DIV></DIV> <DIV STYLE="text-align:Left;"><DIV>Neither The Nature Conservancy nor any of its partners makes any warranty, expressed or implied as to the use or appropriateness of use of the enclosed data, nor are there warranties of merchantability or fitness for a particular purpose or use. No representation is made as to the currency, accuracy or completeness of the information in this dataset or of the data sources on which it is based. Neither The Nature Conservancy nor any partners shall be liable for any lost profits or consequential damages, or claims against the user by third parties.</DIV></DIV>