This goal captures the ability of coastal marine environments to store carbon in key habitats.
Highly productive coastal wetland ecosystems store substantially more carbon than terrestrial forests and have the highest sequestration rates of any habitats on earth. They are also threatened by under-regulated coastal development but are amenable to restoration and conservation efforts. This goal intends to capture the ability of the coastal habitats to remove carbon given the amount of carbon they store and/or their carbon uptake rate and the condition of the habitat.
A score of 100 means all habitats that contribute to carbon removal are still intact or have been restored and they can function to their full carbon burial potential.
Habitat-based goals (Storage, Coastal Protection, and Biodiversity) should be considered together during the data gathering process because these goals use the same data.
STEP 1: Identify relevant habitats
You will first determine the habitats in your study that contribute to carbon sequestration and storage.
Examples of habitats that are important for carbon sequestration and storage are mangroves, saltmarshes, and seagrasses. It is possible that there are other carbon-sequestering habitats present in your study area. But we recommend using habitats that can store carbon on the order of 100 years, thereby limiting the types of habitat types that be relevant to this goal.
Seaweeds and coral store carbon for less than 100 years, and are not included in the carbon storage goal. Although the pelagic oceanic carbon sink (phytoplankton) plays a large role in the sequestration of anthropogenic carbon, the pelagic ocean mechanisms are not amenable to local or regional management intervention. Phytoplankton contribute to carbon fixation when they die and sink to the sea bottom at sufficient depth. However, if those phytoplankton are eaten, the carbon is cycled back into the system and not sequestered. Something that could potentially be included in the carbon storage goal is mollusc shells, if they are added to a landfill and not recycled in the sea. If information on mariculture production and waste disposal are available, this could be an interesting addition to carbon storage at a regional scale.
STEP 2: Determine contribution of each habitat
Within a region the capacity of the habitat to remove carbon is based on the amount of habitat (typically, area, km^2) and its carbon storage and/or uptake rates. These values are used to weight the contribution of each habitat to the region score.
This information will require searching the literature for descriptions of the organic nutrient uptake of each habitat. Ideally these studies should represent your study area. For example, were the studies done with a young mangrove forest, or an older one, which might have different growth rates?
Understanding habitat carbon storage rates is an area of ongoing research.
STEP 3: Determine habitat condition
The score for this ultimately depends on the health of each habitat. A score of 100 means all habitats that contribute to carbon removal are still intact or have been restored and they can function to their full carbon burial potential.
The reference point for assessing the condition of habitats will likely be temporal, meaning you will compare the current area of these habitats to some area in the past, and thus historic data are needed. Reference points could also be set by with a proportion increase (or decrease) of known conditions.
Review the section on Biodiversity sub-goal: Habitats for guidance on habitat extent and condition.
|Developing the Model
|Setting the Reference Point
|Seagrasses, tidal marshes and mangroves, were assessed. The whole extent of mangroves was included, including parts on land or in river deltas. The status was measured as a function of its current condition relative to a reference condition and a variable that weights the relative contribution of each habitat type to total carbon storage.
|Reference conditions were set as the current condition or area of coastal plant habitat coverage relative to that in ~1980. Relative contribution was measured as the amount of area each habitat covers relative to the total area covered by all three habitats given available data.
|This was not a very ambitious reference point.
|Global 2013 - 2015
|The goal model was the same as in Global 2012. Mangrove data included 1km inland in addition to 1km offshore.
|The reference point was the same as Global 2012.
|There were improvements in data processing.
|The goal model was the same as in Global 2012. The greatest data gaps were for sea grasses.
|Different reference points were set for each habitat. For salt marshes, the reference year was 1975, mangroves were 1980, and salt marshes were 1979 - 1981. Estimations were used to retroactively determine the reference condition for mangroves and salt marshes.
|The same approach was used as in Global 2012, with local data used as available.
|U.S. West Coast 2014
|Salt marshes and seagrass beds were considered. Extent was used and habitat health was not used.
|Temporal reference points were set for each habitat. For salt marshes, the percentage of pre-industrialized habitat coverage for sand dunes, the habitat extent between the 1950s and 1960s.
|The study required reconstructions of historic habitat extents in order to set more ambitious targets.
|This goal was excluded from Israel’s assessment. No data was available on the only carbon-fixing ecosystem found in the Israeli Mediterranean (ie. seagrass), and this region generally has extremely low productivity.
|Ecuador - Gulf of Guayaquil 2015
|The modeling approach is the same as Global 2012. But only mangrove was calculated here because of its importance for carbon storage relative to other types of habitats.
|Reference point is the existing mangrove coverage for 1991.
|Values are measured in units of area (km2).
|The approach is the same as Global 2012. But China’s model included a new variable, relative carbon sequestration rate of each habitat.
|A temporal reference point for each habitat is set to its condition in 1980’s. Time-series data on condition of each habitat was not obtainable. However, rough estimate of relative change in coverage areas since the 1980’s was found in literature.
|Relative carbon sequestration rate, together with habitat extent, provide a more complete picture of how habitats contribute to CS than extent alone could do.