A global predictive model of carbon in mangrove soils
By Sunny L. Jardine, Juha Siikamäki. 2014
150 citations recorded by the source corpus.
Mangroves are among the most threatened and rapidly vanishing natural environments worldwide. They provide a wide range of ecosystem services and have recently become known for their exceptional capacity to store carbon. Research shows that mangrove conservation may be a low-cost means of reducing CO2 emissions. Accordingly, there is growing interest in developing market mechanisms to credit mangrove conservation projects for associated CO2 emissions reductions. These efforts depend on robust and readily applicable, but currently unavailable, localized estimates of soil carbon. Here, we use over 900 soil carbon measurements, collected in 28 countries by 61 independent studies, to develop a global predictive model for mangrove soil carbon. Using climatological and locational data as predictors, we explore several predictive modeling alternatives, including machine-learning methods. With our predictive model, we construct a global dataset of estimated soil carbon concentrations and stocks on a high-resolution grid (5 arc min). We estimate that the global mangrove soil carbon stock is 5.00 ± 0.94 Pg C (assuming a 1 meter soil depth) and find this stock is highly variable over space. The amount of carbon per hectare in the world’s most carbon-rich mangroves (approximately 703 ± 38 Mg C ha−1) is roughly a 2.6 ± 0.14 times the amount of carbon per hectare in the world’s most carbon-poor mangroves (approximately 272 ± 49 Mg C ha−1). Considerable within country variation in mangrove soil carbon also exists. In Indonesia, the country with the largest mangrove soil carbon stock, we estimate that the most carbon-rich mangroves contain 1.5 ± 0.12 times as much carbon per hectare as the most carbon-poor mangroves. Our results can aid in evaluating benefits from mangrove conservation and designing mangrove conservation policy. Additionally, the results can be used to project changes in mangrove soil carbon stocks based on changing climatological predictors, e.g. to assess the impacts of climate change on mangrove soil carbon stocks.
View Paper: https://www.semanticscholar.org/paper/b033cc15bd63685d876a28836929bed628fe2a96
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Citations in the corpus
- Mangrove Ecosystems: A Global Biogeographic Perspective (2017, unknown): “, scarce and uneven distributed sampling points across biogeographic regions), the lack of consistency in robust global sampling designs (Brown and Lugo 1984), and the choice of environmental predictors used in contemporary global mangrove C assessments (Hutchison et al. 2013; Jardine and Siikamäki”
- Global declines in human‐driven mangrove loss (2020, background): “…and global scales, including mangrove height (Simard et al., 2019), aboveground biomass/carbon (Simard et al., 2019; Tang et al., 2018) and soil carbon (Atwood et al., 2017; Jardine & Siikamäki, 2014; Rovai et al., 2018; Sanderman et al., 2018), and forest fragmentation (Bryan-Brown et al., 2020).”