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Mangrove blue carbon strategies for climate change mitigation are most effective at the national scale

Carbon fixed by vegetated coastal ecosystems (blue carbon) can mitigate anthropogenic CO 2 emissions, though its effectiveness differs with the spatial scale of interest. A literature review compiling carbon sequestration rates within key ecosystems confirms that blue carbon ecosystems are the most efficient natural carbon sinks at the plot scale, though some overlooked biogeochemical processes may lead to overestimation. Moreover, the limited spatial extent of coastal habitats minimizes their potential at the global scale, only buffering 0.42% of the global fossil fuel carbon emissions in 2014. Still, blue carbon plays a role for countries with moderate fossil fuel emissions and extensive coastlines. In 2014, mangroves mitigated greater than 1% of national fossil fuel emissions for countries such as Bangladesh, Colombia and Nigeria. Considering that the Paris Agreement is based on nationally determined contributions, we propose that mangrove blue carbon may contribute to climate change mitigation at this scale in some instances alongside other blue carbon ecosystems.
- National University of Singapore Singapore
Carbon Sequestration, Climate Change, Carbon, Wetlands
Carbon Sequestration, Climate Change, Carbon, Wetlands
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).234 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
