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Layer: Tourism & Recreation (1)

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• Recreational Fishing Catch Scores - Medium Res - 21 countries
• Recreational Fishing Catch Scores - High Res - 4 countries
• Modelled Total Dollar Value of Reef Tourism (per km2)
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Layer: Recreational Fishing Catch Scores - Low Res - 39 countries (160)

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Description: Mapped estimates of catch from recreational fishing on a scale from low to high. Values were derived from a study using big data from global datasets and user-generated content to map marine and coastal recreational fishing. Data from the recreational fishing app, Fishbrain, was enhanced with data from FishBase, the Sea Around Us Project, and literature searches. Low resolution (20m) grids are available for 39 countries/geographies. See the corresponding report and attribute overview for more details. Venturelli, P., Hrabowski, J., Muehler, A., Schaeffer, W., Willbanks, P., Boyd, R., Longley-Wood, K., & Spalding, M. (2024). Global assessment of the distribution and importance of coastal and marine recreational fishing. Ball State University and The Nature Conservancy.

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Description: Mapped estimates of catch from recreational fishing on a scale from low to high. Values were derived from a study using big data from global datasets and user-generated content to map marine and coastal recreational fishing. Data from the recreational fishing app, Fishbrain, was enhanced with data from FishBase, the Sea Around Us Project, and literature searches. Medium resolution (10m) grids are available for 21 countries/geographies. See the corresponding report and attribute overview for more details. Venturelli, P., Hrabowski, J., Muehler, A., Schaeffer, W., Willbanks, P., Boyd, R., Longley-Wood, K., & Spalding, M. (2024). Global assessment of the distribution and importance of coastal and marine recreational fishing. Ball State University and The Nature Conservancy.

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Layer: Recreational Fishing Catch Scores - High Res - 4 countries (159)

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Layer: Coastal Protection (5)

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Layer: Number of people avoiding damage from flooding per decade (7)

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Description: The maps show coastal points which summarise the number of persons (number per km of coast) in adjacent, hazard-exposed areas who are likely to be receiving protection from flooding. The hazard in the model is informed by wind and wave energy, which are indicative of threats arising both from flooding (including wave overtopping during storms) and erosion. Exposed areas include a 500m strip along all coasts, plus additional low-lying areas <5km from the shore. Population information in these hazard exposed areas is from WorldPop 2020, which provides population data over a 30′′ grid (approximately 1-km at the equator). For more details, see: Burke and Spalding (2022). Shoreline protection by the world’s coral reefs: Mapping the benefits topeople, assets, and infrastructure. Marine Policy.

Copyright Text: Burke and Spalding (2022); TNC, WRI

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Copyright Text: Burke and Spalding (2022); TNC, WRI

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Layer: Recreational Fishing Catch Scores - High Res - 4 countries (164)

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Layer: Modeled Mangrove Commercial Invertebrate Enhancement (28)

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Description: Commercial invertebrate enhancement values are based on a model, informed by field data, to estimate the invertebrate catch enhancement value of mangroves across the world. To calculate the number of individuals enhanced by mangroves, the team derived a model of fish density enhancement value from mangrove which incorporated biophysical and environmental inputs (e.g., salinity, sea surface temperature, productivity, mangrove edge length and area, and tidal amplitude). These values were then multiplied by an estimate of fishing pressure, derived from variables including population density, access to cities, proximity of key fishing habitats (coral reefs, mangroves, shallow shelfs), and storminess.The commercial invertebrates covered include representatives from all regions, however they do not include all commercial species enhanced by mangroves- only those strongly affiliated with mangroves and so estimates may be conservative. Further, there is a possible sampling bias between regions and so results are most useful for comparing enhancement within regions, and should be viewed with caution in making inter-regional comparisons.

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Description: The model provides a basic estimate of the relative size of coral reef fisheries catch. This catch is determined as a function of estimated reef productivity and fishing effort. A minor modifier to this basic model makes allowance for no-take fishing areas (where catches are zero) with a small buffer of potential enhanced fisheries in adjacent waters (spillover). We do not account for variability in the economic or social value of these fisheries. This global data set reflects the world's coral reefs as a 500m grid, classified by a relative estimate of the annual fish harvest. Values are represented in decile blocks. The estimation of coral-reef associated fisheries involves 4 steps: Estimate the pristine potential maximum sustainable yield on coral reefs – reflecting the potential sustainable production of fish on healthy reefs. This estimate was based on a review of numerous published estimates of fisheries yields or maximum sustainable yield per unit area world-wide. Estimate the realistic potential MSY on coral reefs, in light of current reef condition (degradation) reducing productivity. A proportional reduction based on the Reefs at Risk model of integrated threat, informed by other studies Estimate catch based on the potential MSY, adjusted by nearby population and available fishing area, using a model adapted from previous field-based studies (reefs are recorded as reaching maximum fishing effort at population levels greater than 600 persons within reach of each square kilometre of reef. This catch layer was modified for strictly protected no-take zones. Catch values were reduced to zero (no catch) in the no-take zones while changing the potential catch in a surrounding 1km buffer was raised to the maximum value.

Copyright Text: Data developed at the World Resources Institute (WRI), under a joint effort by WRI, TNC and Cambridge University under the project, "Attaining Aichi Target 11: How well are marine ecosystem services secured by protected areas?"

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Layer: Carbon Storage and Sequestration (30)

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Description: Coastal wetlands, including submerged seagrasses, mangrove forests, salt marshes and pelagic habitats offer a vital service to the global community in the face of global warming by sequestering large amounts of carbon in living matter and by storing carbon in layers of underground sediment.

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Description: The increasing value of mangrove above-ground biomass in decile blocks. Estimations of the relative amount of above ground biomass (agb) of the world’s mangroves based on a climate-based model that links global climate and mangrove distribution data with data collected from 95 field studies. <br> <br> Hutchison, J., Manica, A., Swetnam, R., Balmford, A. & Spalding, M. "Predicting global patterns in mangrove forest biomass." Conservation Letters 00 (2013) 1–8 C 2013 The Authors. Conservation Letters published by Wiley Periodicals, Inc.

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Description: Results of a project which used a machine learning data-driven model to predict the distribution of soil carbon under mangrove forests globally. Results are presented in decile blocks. Sanderman et al. (in review) A global map of mangrove forest soil carbon at 30 m spatial resolution. Environmental Research Letters.

Copyright Text: Woods Hole Research Center, TNC

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Copyright Text: Woods Hole Research Group, TNC

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Layer: Soil Organic Carbon2 (metric tons) (36)

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Description: Results of a project which used a machine learning data-driven model to predict the distribution of soil carbon under mangrove forests globally. Results are presented in decile blocks. Sanderman et al. (in review) A global map of mangrove forest soil carbon at 30 m spatial resolution. Environmental Research Letters.

Copyright Text: Woods Hole Research Group, TNC

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Layer: Soil Organic Carbon3 (metric tons) (37)

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Description: Results of a project which used a machine learning data-driven model to predict the distribution of soil carbon under mangrove forests globally. Results are presented in decile blocks. Sanderman et al. (in review) A global map of mangrove forest soil carbon at 30 m spatial resolution. Environmental Research Letters.

Copyright Text: Woolds Hole Research Group, TNC

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Layer: Regional Datasets (38)

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• Bahamas
• Gulf of California
• Indonesia (Lesser Sunda)
• Micronesia
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Layer: Australia (39)

Parent Layer: Regional Datasets

Sub Layers:
• Coastal Protection
• Blue Carbon
• Recreation
• Coastal Ecosystems
Name: Australia

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Layer: Coastal Protection (40)

Parent Layer: Australia

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• Coastal Exposure
• Habitat Roles
• Coastal Population
• Protected Value
• Protection Index - Mangroves
• Protection Index - Seagrass
• Protection Index - Saltmarsh
Name: Coastal Protection

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Layer: Coastal Exposure (41)

Parent Layer: Coastal Protection

Name: Coastal Exposure

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Description: Heatmap of the category of coastal exposure (red displays highest coastal exposure to lowest in blue) The coastal exposure is defined by the Hazard Index (HI) that was calculated as follows: HI=√(7&R_hab R_geo R_rel R_win R_wav R_slr R_sur ) where the relative ranking (R) indicates parameter that affects hazard index including, the ranking of habitats (R_hab; is calculated by the habitat risk exposure function embedded in Coastal Vulnerability toolbox of InVEST model, Eq. xx), the effects of geomorphology type (R_geo) and coastal relief (R_rel), and the exposures from wind (R_win), waves (R_wav), sea level rise (R_slr), and storm surge potential (R_sur). R_hab=max(1,4.8-0.5 √((1.5 〖max〗_h^N (5-R_h ))^2+(∑_h^N▒〖(5-R_h )^2-〖max〗_h^N (5-R_h )^2 〗) )) Eq.xx Where N is the number of habitat layers within the maximum protection distance of that habitat type and R_h is the risk rank of habitat type h. The relative ranking is defined independently for each parameter to assign the level of exposures from high (rank = 5) to low (rank = 1). For almost all the parameters, except for habitats and geomorphology, the rank is calculated by classifying the values using quartile sampling distribution, from first quartile or top 20% (rank = 5) to fifth quartile (rank = 1). Meanwhile, the habitat and geomorphology ranking systems are following the methods proposed by Gornitz (1990), and also see Arkema et al. (2013).

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Layer: Habitat Roles (42)

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Description: Heatmap of the category of total habitat role in coastal protection (red displays highest habitat role grading to lowest in blue ). The value is calculated by, at first, subtracting the Hazard Index in “with” Habitat scenario from another Hazard Index in “without” Habitat scenario. Then, the value divided by the maximum Hazard Index (“without” Habitat scenario) is considered as Habitat Roles.

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Layer: Coastal Population (43)

Parent Layer: Coastal Protection

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Description: Heatmap of the density of human population benefitted by coastal protection service provided by coastal wetlands (saltmarsh, mangroves and seagrass). Red displays >10,000 grading to < 500 people per 1 km2 in blue . The protected value is estimated by calculating the difference in the number of people exposed to coastal hazards “with” and “without” habitats included in the hazard index (see Coastal Exposure). There is a maximum distance limit by 1 km from the coastline to match the model resolution. (Data source: embedded in InVEST. The original source is Center for International Earth Science Information Network (CIESIN), Columbia University; and Centro Internacional de Agricultura Tropical (CIAT)). The data is at 100 m resolution and obtained from the InVEST 3.5.0 data package (Sharp et al., 2018) and Gridded Population of the World Version 3 (GPWv3): courtesy of CIESIN, Columbia University; and CIAT (2005).

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Layer: Protected Value (44)

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Description: Heatmap of total protected value (in Australian Dollar) due to coastal protection service provided by coastal wetlands (saltmarsh, mangroves and seagrass) for coastal counties in Australia (red displays >100 grading to <1 million AUD per coastal county in blue). The protected value is estimated by calculating the difference in the total value of property exposed to coastal hazards “with” and “without” habitats included in the hazard index (see Coastal Exposure). Finally, the total protected value is summed by county and by limiting maximum distance 1 km from the coastline to match the model resolution. (Data source: global exposure datasets from Global Assessment Report (2015) provided by United Nations Office for Disaster Risk Reduction (UNISDR)). It contains total economic capital stock values in 4 km resolution, then resampled into 1 km resolution. This is derived from the value of property within 1 km2 of the coastline where the presence of coastal wetlands reduces the impacts of inundation from storms.

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Layer: Protection Index - Mangroves (45)

Parent Layer: Coastal Protection

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Description: Heatmap of the percentage that mangrove ecosystems contribute to reduce coastal hazard index (see Coastal Exposure). Red displays >10 grading to 1 – 2 % in blue.

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Layer: Protection Index - Seagrass (46)

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Description: Heatmap of the percentage that seagrass ecosystems contribute to reduce coastal hazard index (see Coastal Exposure). Red displays >10 grading to 1 – 2 % in blue.

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Layer: Protection Index - Saltmarsh (47)

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Description: Heatmap of the percentage that saltmarsh ecosystems contribute to reduce coastal hazard index (see Coastal Exposure). Red displays >10 grading to 1 – 2 % in blue.

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Layer: Blue Carbon (48)

Parent Layer: Australia

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• Mangrove and Tidal Marsh Soil Carbon Stock - Tonnes Soil C per ha
• Potential Coastal Wetland Carbon Sequestration by 2050 (Levee Removal + SLR scenario) Tonnes C per ha
• Potential Coastal Wetland Carbon Sequestration by 2100 (Levee Removal + SLR scenario) Tonnes C per ha
• Potential Coastal Wetland Carbon Sequestration by 2050 (SLR Scenario) Tonnes C per ha
• Potential Coastal Wetland Carbon Sequestration by 2100 (SLR Scenario) Tonnes C per ha
• Potential Coastal Wetland Carbon Sequestration by 2050 (Top 20th %ile Risk Scenario) Tonnes C per ha
• Potential Coastal Wetland Carbon Sequestration by 2100 (Top 20th %ile Risk Scenario) Tonnes C per ha
• Potential Coastal Wetland Carbon Sequestration by 2050 (Top 50th %ile Risk Scenario) Tonnes C per ha
• Potential Coastal Wetland Carbon Sequestration by 2100 (Top 50th %ile Risk Scenario) Tonnes C per ha
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Layer: Seagrass Soil Carbon Stock - Tonnes Soil C per ha (49)

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Description: Soil carbon stock for Australian seagrass ecosystems were associated with multiple environmental and anthropogenic variables across Australia in a boosted regression tree (BRT). The resulting associations from the BRT were used to extrapolate carbon stock values across the coverage of seagrass ecosystems in Australia.

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Layer: Mangrove and Tidal Marsh Soil Carbon Stock - Tonnes Soil C per ha (50)

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Description: Soil carbon stock for Australian tidal marsh and mangrove ecosystems were associated with multiple environmental and anthropogenic variables across Australia in a boosted regression tree (BRT). The resulting associations from the BRT were used to extrapolate carbon stock values across the coverage of tidal marsh and mangrove ecosystems in Australia.

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Layer: Potential Coastal Wetland Carbon Sequestration by 2050 (Levee Removal + SLR scenario) Tonnes C per ha (51)

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Name: Potential Coastal Wetland Carbon Sequestration by 2050 (Levee Removal + SLR scenario) Tonnes C per ha

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Description: Potential soil carbon sequestration (tonnes C) per hectare for Australian coastal wetland ecosystems (saltmarsh, mangrove, and seagrass) in Victoria was calculated from 2020 to 2050 and 2020 to 2100 using the InVEST Coastal Blue Carbon Model v3.7 (Natural Capital Project). Annual carbon sequestration rates for each ecosystem were extrapolated over time to estimate net carbon sequestration. Restored ecosystems had sequestration rates that were initially lower than undisturbed ecosystems but caught up over time. This layer represents potential carbon sequestration (tonnes C) per hectare by 2050 under the Levee Removal Plus Sea Level Rise Scenario, in which current coastal ecosystems remain in place for the entire modelling period and coastal levees are breeched, returning tidal inundation to low-lying area in the vicinity of breeched structures. Sea level rise would augment inundation over time. It is assumed that newly inundated areas would be restored to tidal marsh or mangrove.

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Layer: Potential Coastal Wetland Carbon Sequestration by 2100 (Levee Removal + SLR scenario) Tonnes C per ha (52)

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Description: Potential soil carbon sequestration (tonnes C) per hectare for Australian wetland ecosystems (saltmarsh, mangrove, and seagrass) in Victoria was calculated from 2020 to 2050 and 2020 to 2100 using the InVEST Coastal Blue Carbon Model v3.7 (Natural Capital Project). Annual carbon sequestration rates for each ecosystem were extrapolated over time to estimate net carbon sequestration. Restored ecosystems had sequestration rates that were initially lower than undisturbed ecosystems but caught up over time. This layer represents potential carbon sequestration (tonnes C) per hectare by 2100 under the Levee Removal Plus Sea Level Rise Scenario, in which current coastal ecosystems remain in place for the entire modelling period and coastal levees are breeched, returning tidal inundation to low-lying area in the vicinity of breeched structures. Sea level rise would augment inundation over time. It is assumed that newly inundated areas would be restored to tidal marsh or mangrove.

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Layer: Potential Coastal Wetland Carbon Sequestration by 2050 (SLR Scenario) Tonnes C per ha (53)

Parent Layer: Blue Carbon

Name: Potential Coastal Wetland Carbon Sequestration by 2050 (SLR Scenario) Tonnes C per ha

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Description: Potential soil carbon sequestration for Australian coastal wetland ecosystems (saltmarsh, mangrove, and seagrass) in Victoria was calculated from 2020 to 2050 and 2020 to 2100 using the InVEST Coastal Blue Carbon Model v3.7 (Natural Capital Project). Annual carbon sequestration rates for each ecosystem were extrapolated over time to estimate net carbon sequestration. Restored ecosystems had sequestration rates that were initially lower than undisturbed ecosystems but caught up over time. This layer represents potential carbon sequestration (tonnes C) per hectare by 2050 under the Sea Level Rise Scenario, in which current coastal ecosystems remain in place for the entire modelling period and sea level rise returns tidal inundation to low-lying areas. It is assumed that newly inundated areas would be restored to tidal marsh or mangrove.

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Layer: Potential Coastal Wetland Carbon Sequestration by 2100 (SLR Scenario) Tonnes C per ha (54)

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Description: Potential soil carbon sequestration for Australian coastal wetland ecosystems (saltmarsh, mangrove, and seagrass) in Victoria was calculated from 2020 to 2050 and 2020 to 2100 using the InVEST Coastal Blue Carbon Model v3.7 (Natural Capital Project). Annual carbon sequestration rates for each ecosystem were extrapolated over time to estimate net carbon sequestration. Restored ecosystems had sequestration rates that were initially lower than undisturbed ecosystems but caught up over time. This layer represents potential carbon sequestration (tonnes C) per hectare by 2100 under the Sea Level Rise Scenario, in which current coastal ecosystems remain in place for the entire modelling period and sea level rise returns tidal inundation to low-lying areas. It is assumed that newly inundated areas would be restored to tidal marsh or mangrove.

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Layer: Potential Coastal Wetland Carbon Sequestration by 2050 (Top 20th %ile Risk Scenario) Tonnes C per ha (55)

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Layer: Potential Coastal Wetland Carbon Sequestration by 2100 (Top 20th %ile Risk Scenario) Tonnes C per ha (56)

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Description: Potential soil carbon sequestration (tonnes C) per hectare for Australian coastal wetland ecosystems (saltmarsh, mangrove, and seagrass) in Victoria was calculated from 2020 to 2050 and 2020 to 2100 using the InVEST Coastal Blue Carbon Model v3.7 (Natural Capital Project). Annual carbon sequestration rates for each ecosystem were extrapolated over time to estimate net carbon sequestration. Restored ecosystems had sequestration rates that were initially lower than undisturbed ecosystems but caught up over time. Loss of soil carbon from erosion took place within the first decade after erosion. This layer represents potential carbon sequestration (tonnes C) per hectare by 2100 under the Erosion of the Top 20th Percentile Risk Area scenario. Coastal areas were ranked based on a relative risk index for erosion using the Victorian Coastal Climate Change Risk Assessment (DELWP 2015). Current coastal ecosystems falling with the areas in the top 20th percentile of risk index ranks were assumed to erode to either mudflat or open water, losing soil carbon. Coastal ecosystems outside of these areas.

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Layer: Economic Value w/10% increase in Seagrass (Port Phillip Bay) (72)

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Description: Heatmap showing the economic benefit per recreational fishing trip corresponding to an increase of 10% in seagrass coverage in Port Phillip (red displays >$50 grading to <$1 AUD per trip in blue). These values were derived by valuing potential seagrass restoration, resulting in an increase in seagrass coverage by 10%, in fishing blocks across Port Phillip with costs of travel and time taken to get to a location in the corresponding blocks by recreational fishers. As this restoration is hypothetical, the value is mapped to the fishing blocks that were used in the recreational fishing boat ramp surveys. Areas in black are Marine Protected Areas where no fishing is allowed.

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Layer: King George Whiting Juvenile Density (Port Phillip Bay) (73)

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Layer: Marine Protected Areas - Victoria (74)

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Layer: New South Wales & Victoria Coastal Ecosystems (Contemporary) (76)

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Description: Extents of coastal wetland ecosystems (mangrove, saltmarsh, and seagrass) across New South Wales (NSW) and Victoria (VIC) in Australia. Polygons for NSW were downloaded from http://www.dpi.nsw.gov.au/about-us/research-development/flagship-projects/spatial-data-portal and VIC data came from Boon et al. 2011.

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Layer: Historic Victoria Coastal Ecosystems (Pre-1750) (80)

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Description: This dataset displays the extent of our knowledge regarding the distribution of saltmarshes globally, drawing from occurrence data (surveyed and/or remotely sensed). The dataset was developed to provide a baseline inventory of the extent of our knowledge regarding the global distribution of saltmarshes, which are ecosystems located in the intertidal zone of sheltered marine and estuarine coastlines. These ecosystems comprise brackish, shallow water with salt-tolerant plants such as herbs, grasses and shrubs, and are commonly found at temperate and high latitudes. Saltmarshes are of ecological importance as they underpin the estuarine food web. In particular, saltmarshes serve as nesting, nursery and feeding grounds for numerous species of birds, fish, molluscs and crustaceans, including commercially important fish species such as herring (Clupea harengus), and are also home to a number of Endangered and Critically Endangered species.

Copyright Text: Mcowen C, Weatherdon LV, Bochove J, Sullivan E, Blyth S, Zockler C, Stanwell-Smith D, Kingston N, Martin CS, Spalding M, Fletcher S (2017). A global map of saltmarshes. Biodiversity Data Journal 5: e11764. Paper DOI: https://doi.org/10.3897/BDJ.5.e11764; Data URL: http://data.unep-wcmc.org/datasets/43 (v.5)

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Layer: Marine and Coastal World Heritage Sites (111)

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Description: Marine and Coastal World Heritage Sites https://whc.unesco.org/en/marine-programme/

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Layer: Australia Mapping Ocean Wealth (112)

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Layer: Coastal Protection X (113)

Parent Layer: Australia Mapping Ocean Wealth

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Description: Heatmap of the category of coastal exposure (red displays highest coastal exposure to lowest in blue) The coastal exposure is defined by the Hazard Index (HI) that was calculated as follows: HI=√(7&R_hab R_geo R_rel R_win R_wav R_slr R_sur ) where the relative ranking (R) indicates parameter that affects hazard index including, the ranking of habitats (R_hab; is calculated by the habitat risk exposure function embedded in Coastal Vulnerability toolbox of InVEST model, Eq. xx), the effects of geomorphology type (R_geo) and coastal relief (R_rel), and the exposures from wind (R_win), waves (R_wav), sea level rise (R_slr), and storm surge potential (R_sur). R_hab=max(1,4.8-0.5 √((1.5 〖max〗_h^N (5-R_h ))^2+(∑_h^N▒〖(5-R_h )^2-〖max〗_h^N (5-R_h )^2 〗) )) Eq.xx Where N is the number of habitat layers within the maximum protection distance of that habitat type and R_h is the risk rank of habitat type h. The relative ranking is defined independently for each parameter to assign the level of exposures from high (rank = 5) to low (rank = 1). For almost all the parameters, except for habitats and geomorphology, the rank is calculated by classifying the values using quartile sampling distribution, from first quartile or top 20% (rank = 5) to fifth quartile (rank = 1). Meanwhile, the habitat and geomorphology ranking systems are following the methods proposed by Gornitz (1990), and also see Arkema et al. (2013).

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Layer: Habitat Roles (115)

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Description: Heatmap of the category of total habitat role in coastal protection (red displays highest habitat role grading to lowest in blue ). The value is calculated by, at first, subtracting the Hazard Index in “with” Habitat scenario from another Hazard Index in “without” Habitat scenario. Then, the value divided by the maximum Hazard Index (“without” Habitat scenario) is considered as Habitat Roles.

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Layer: Coastal Population (116)

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Description: Heatmap of the density of human population benefitted by coastal protection service provided by coastal wetlands (saltmarsh, mangroves and seagrass). Red displays >10,000 grading to < 500 people per 1 km2 in blue . The protected value is estimated by calculating the difference in the number of people exposed to coastal hazards “with” and “without” habitats included in the hazard index (see Coastal Exposure). There is a maximum distance limit by 1 km from the coastline to match the model resolution. (Data source: embedded in InVEST. The original source is Center for International Earth Science Information Network (CIESIN), Columbia University; and Centro Internacional de Agricultura Tropical (CIAT)). The data is at 100 m resolution and obtained from the InVEST 3.5.0 data package (Sharp et al., 2018) and Gridded Population of the World Version 3 (GPWv3): courtesy of CIESIN, Columbia University; and CIAT (2005).

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Layer: Protected Value (117)

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Description: Heatmap of total protected value (in Australian Dollar) due to coastal protection service provided by coastal wetlands (saltmarsh, mangroves and seagrass) for coastal counties in Australia (red displays >100 grading to <1 million AUD per coastal county in blue). The protected value is estimated by calculating the difference in the total value of property exposed to coastal hazards “with” and “without” habitats included in the hazard index (see Coastal Exposure). Finally, the total protected value is summed by county and by limiting maximum distance 1 km from the coastline to match the model resolution. (Data source: global exposure datasets from Global Assessment Report (2015) provided by United Nations Office for Disaster Risk Reduction (UNISDR)). It contains total economic capital stock values in 4 km resolution, then resampled into 1 km resolution. This is derived from the value of property within 1 km2 of the coastline where the presence of coastal wetlands reduces the impacts of inundation from storms.

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Layer: Protection Index - Mangroves (118)

Parent Layer: Coastal Protection X

Name: Protection Index - Mangroves

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Description: Heatmap of the percentage that mangrove ecosystems contribute to reduce coastal hazard index (see Coastal Exposure). Red displays >10 grading to 1 – 2 % in blue.

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Layer: Protection Index - Seagrass (119)

Parent Layer: Coastal Protection X

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Description: Heatmap of the percentage that seagrass ecosystems contribute to reduce coastal hazard index (see Coastal Exposure). Red displays >10 grading to 1 – 2 % in blue.

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Layer: Protection Index - Saltmarsh (120)

Parent Layer: Coastal Protection X

Name: Protection Index - Saltmarsh

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Description: Heatmap of the percentage that saltmarsh ecosystems contribute to reduce coastal hazard index (see Coastal Exposure). Red displays >10 grading to 1 – 2 % in blue.

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Layer: Blue Carbon X (121)

Parent Layer: Australia Mapping Ocean Wealth

Sub Layers:
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• Potential Coastal Wetland Carbon Sequestration by 2050 (SLR Scenario)
• Potential Coastal Wetland Carbon Sequestration by 2100 (SLR Scenario)
• Potential Coastal Wetland Carbon Sequestration by 2050 (Top 20th %ile Risk Scenario)
• Potential Coastal Wetland Carbon Sequestration by 2100 (Top 20th %ile Risk Scenario)
• Potential Coastal Wetland Carbon Sequestration by 2050 (Top 50th %ile Risk Scenario)
• Potential Coastal Wetland Carbon Sequestration by 2100 (Top 50th %ile Risk Scenario)
• Port Phillip and Western Port Mangrove Biomass Carbon Stock (Mgha-1)
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Layer: Seagrass Soil Carbon Stock (122)

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Description: Soil carbon stock for Australian seagrass ecosystems were associated with multiple environmental and anthropogenic variables across Australia in a boosted regression tree (BRT). The resulting associations from the BRT were used to extrapolate carbon stock values across the coverage of seagrass ecosystems in Australia.

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Layer: Mangrove and Tidal Marsh Soil Carbon Stock (123)

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Description: Soil carbon stock for Australian tidal marsh and mangrove ecosystems were associated with multiple environmental and anthropogenic variables across Australia in a boosted regression tree (BRT). The resulting associations from the BRT were used to extrapolate carbon stock values across the coverage of tidal marsh and mangrove ecosystems in Australia.

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Layer: Potential Coastal Wetland Carbon Sequestration by 2050 (Levee Removal + SLR scenario) (124)

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Description: Potential soil carbon sequestration (tonnes C) per hectare for Australian coastal wetland ecosystems (saltmarsh, mangrove, and seagrass) in Victoria was calculated from 2020 to 2050 and 2020 to 2100 using the InVEST Coastal Blue Carbon Model v3.7 (Natural Capital Project). Annual carbon sequestration rates for each ecosystem were extrapolated over time to estimate net carbon sequestration. Restored ecosystems had sequestration rates that were initially lower than undisturbed ecosystems but caught up over time. This layer represents potential carbon sequestration (tonnes C) per hectare by 2050 under the Levee Removal Plus Sea Level Rise Scenario, in which current coastal ecosystems remain in place for the entire modelling period and coastal levees are breeched, returning tidal inundation to low-lying area in the vicinity of breeched structures. Sea level rise would augment inundation over time. It is assumed that newly inundated areas would be restored to tidal marsh or mangrove.

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Layer: Potential Coastal Wetland Carbon Sequestration by 2100 (Levee Removal + SLR scenario) (125)

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Description: Potential soil carbon sequestration (tonnes C) per hectare for Australian wetland ecosystems (saltmarsh, mangrove, and seagrass) in Victoria was calculated from 2020 to 2050 and 2020 to 2100 using the InVEST Coastal Blue Carbon Model v3.7 (Natural Capital Project). Annual carbon sequestration rates for each ecosystem were extrapolated over time to estimate net carbon sequestration. Restored ecosystems had sequestration rates that were initially lower than undisturbed ecosystems but caught up over time. This layer represents potential carbon sequestration (tonnes C) per hectare by 2100 under the Levee Removal Plus Sea Level Rise Scenario, in which current coastal ecosystems remain in place for the entire modelling period and coastal levees are breeched, returning tidal inundation to low-lying area in the vicinity of breeched structures. Sea level rise would augment inundation over time. It is assumed that newly inundated areas would be restored to tidal marsh or mangrove.

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Layer: Potential Coastal Wetland Carbon Sequestration by 2050 (SLR Scenario) (126)

Parent Layer: Blue Carbon X

Name: Potential Coastal Wetland Carbon Sequestration by 2050 (SLR Scenario)

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Description: Potential soil carbon sequestration for Australian coastal wetland ecosystems (saltmarsh, mangrove, and seagrass) in Victoria was calculated from 2020 to 2050 and 2020 to 2100 using the InVEST Coastal Blue Carbon Model v3.7 (Natural Capital Project). Annual carbon sequestration rates for each ecosystem were extrapolated over time to estimate net carbon sequestration. Restored ecosystems had sequestration rates that were initially lower than undisturbed ecosystems but caught up over time. This layer represents potential carbon sequestration (tonnes C) per hectare by 2050 under the Sea Level Rise Scenario, in which current coastal ecosystems remain in place for the entire modelling period and sea level rise returns tidal inundation to low-lying areas. It is assumed that newly inundated areas would be restored to tidal marsh or mangrove.

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Layer: Potential Coastal Wetland Carbon Sequestration by 2100 (SLR Scenario) (127)

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Description: Heatmap showing the economic benefit per trip corresponding to the current value of seagrass coverage in Western Port (red displays >$50 grading to <$1 AUD per trip in blue). These values were derived by valuing the amount of seagrass in fishing blocks across the bay with the costs of travel and time taken to get to a location in the corresponding blocks by recreational fishers. The blocks have been clipped to the current seagrass extents. Areas in black are Marine Protected Areas where no fishing is allowed.

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Description: Heatmap showing the economic benefit per recreational fishing trip corresponding to an increase of 10% in seagrass coverage in Western Port (red displays >$50 grading to <$1 AUD per trip in blue). These values were derived by valuing potential seagrass restoration, resulting in an increase in seagrass coverage by 10%, in fishing blocks across Western Port with cost of travel and times taken to get to a location in the corresponding blocks by recreational fishers. As this restoration is hypothetical, the value is mapped to the fishing blocks that were used in the recreational fishing boat ramp surveys. Areas in black are Marine Protected Areas where no fishing is allowed.

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Layer: King George Whiting Juvenile Density (Port Phillip Bay) (146)

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Layer: Marine Protected Areas - Victoria (147)

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