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CONCLUSION
The publication of this information introduces the availability of a detailed and comprehensive global dataset detailing 10 aspects of coastal ecological settings. This is a first-of-its-kind inventory of the properties of 4 million coastal segments at a management-appropriate spatial resolution (1 km). We classified those 4 million segments into 81,000 distinct coastal segment units (CSUs) using authoritative data and standards for describing the classes and their associated value ranges for each of the 10 variables. The data are freely available as an ArcGIS Online resource found at GISforScience.com. Our team plans to actively curate this datalayer as an authoritative geospatial resource in ArcGIS Living Atlas of the World. Tthe fully attributed, classified segment units data and the preliminary ECU data are available. The data will also be placed in the public domain after additional preparation and review, including making the data available in an open data format such as an OGC® (Open Geospatial Consortium) GeoPackage file or similar.
The CSU data permit spatial analysis and mapping of coastal ecological settings at any scale, anywhere on Earth. This comprehensive inventory of coastline environments should be useful for researchers, planners, managers, and policy makers. The community is invited to evaluate the data and provide feedback to improve the accuracy and utility of the data. Our team anticipates the development of a simple, web-based data visualization and query tool, the Global Coastline Explorer, which will allow anyone with an internet connection to access the data.
Ultimately, the utility of the classification will be judged by the end user who has assessed the CSU data and evaluated them for fitness of purpose. The classification
has three major advantages in that regard: 1) it is exhaustive (every coast is classified), 2) the classes are mutually exclusive (every coast fits into only one class, but that class can be described in rich taxonomic detail), and 3) standardized comparisons of coasts across any oceanic or continental geography are enabled.
This presentation also includes a scientific assessment of the global similarity of these coastline environments. A statistical clustering of the 4 million segments identified 16 ecological coastal units (ECUs) that differ from each other based on their aggregate ecological setting as established by the 10 variables. The ECU work is intended for the scientific community and other interested parties seeking to understand global patterns of variation in coastal ecological settings. The ECU data may be useful in understanding global patterns of biodiversity distribution, helping biogeographers answer that enduring question, “Why are species distributed where they are?”
The ECU data are considered preliminary, and we anticipate feedback from the community on their veracity and utility. The statistical analysis was rigorous and defensible, but the selection of variables in any clustering exercise is always the subject of debate. Did we omit an important variable or variables, such as, for example, elevation change at the coast, important for understanding uplift and subsidence effects on coastal landforms?
Regardless of the research value of the current clustering results, the newly created set of granular, management-appropriate, and globally comprehensive coastline segments represents an advance in coastal ecology. It is our hope that this resource will contribute to better understanding and wise stewardship of the planet’s many coastal environments.
ECU N (# % of pixels) total
N
Predominant Marine Physical Environment (% of total distribution of occurrences in cluster)
Average Chlorophyll Concentration (μ/l)
Average Tidal Range (m)
Average Significant Wave Height (m)
Average Turbidity (m-1)
Predominant Climate Region (% of total distribution of occurrences in cluster)
Predominant Erodibility Class (% of total distribution of occurrences in cluster)
Average Regional Sinuosity (unitless)
Average Slope (%)
Average Outflow Density (unitless)
1 234,549 6 Euhaline-Oxic-Warm to 1.8 2.1 0.77 0.22 Tropical Moist (100) Low (67) 2.57 97.87 0.0003 Very Warm (100)
2 308,444 8 Euhaline-Oxic-Warm to 2.99 2.37 0.88 0.22 Tropical Dry (33) High (59) 2.69 60.9 0.0006 Very Warm (97)
3 263,112 7 Euhaline-Oxic- 2.85 2.68 0.88 0.29 Warm Temperate Moist (37) Low (71) 2.26 79.7 0.0015 Moderate (45)
4 206,534 5 Euhaline-Oxic-Warm to 3.44 2.48 0.7 0.24 Tropical Moist (100) High (100) 2.64 53.48 0.0017 Very Warm (100)
5 248,600 6 Euhaline-Oxic- 6.14 2.41 0.58 0.29 Tropical Moist (65) High (100) 2.27 29.48 0.0115 Moderate (100)
6 206,328 5 Euhaline-Oxic-Moderate 3.54 1.98 1.02 0.36 Cool Temperate Moist (43) High (64) 2.53 49.95 0.0007 to Cool (49)
7 192,253 5 Polyhaline-Anoxic-Very 3.57 1.06 0.38 0.46 Polar Dry (47) Low (94) 2.89 20.87 0.0002 Cold (33)
8 199,849 5 Polyhaline-Highly Oxic- 1.8 0.93 0.3 0.33 Polar Dry (100) Low (81) 6.01 25.25 0 Superchilled (54)
9 179,728 4 Euhaline-Highly Oxic- 4.98 3.06 0.58 0.55 Boreal Moist (98) Low (48) 1.9 47.2 0.0008 Superchilled (51)
10 183,614 5 Euhaline-Highly Oxic- 3.46 1.22 0.58 0.44 Polar Moist (100) Medium (100) 1.87 47.35 0.0001 Superchilled (42)
11 215,600 5 Mesohaline-Severely 5.69 0.77 0.5 0.42 Polar Moist (64) High (83) 1.96 27.01 0.0005 Hypoxic-Very Cold (16)
12 401,296 1 Euhaline-Highly Oxic- 1.69 3.26 0.42 0.43 Polar Moist (100) Low (100) 2.58 49.28 0 Superchilled (100)
13 341,997 9 Euhaline-Oxic-Very 1.88 2.95 1.27 0.43 Cool Temperate Moist (53) Low (100) 2.63 110.51 0.0001 Cold (100)
14 271,424 7 Polyhaline-Highly Oxic- 2.28 1.46 0.74 0.36 Polar Moist (100) Low (100) 5.07 54.33 0.0001 Superchilled (29)
15 285,583 7 Mesohaline-Highly 3.15 1.54 0.88 0.58 Cool Temperate Moist (100) Low (100) 2.25 66.02 0.0004 Oxic-Very Cold (33)
16 266,931 7 Euhaline-Highly Oxic-S 2.66 3.53 1.29 0.43 Cool Temperate Moist (100) Medium (77) 1.97 84.27 0.0002 uperchilled (49)
Descriptive statistics on the distributions and average compositional characteristics of the ecological coastal units (ECUs).
Earth’s Coastlines 25
Appendix