Globally, carbon-rich mangrove forests are deforested and degraded due to land-use and land-cover change (LULCC). The impact of mangrove deforestation on carbon emissions has been reported on a global scale; however, uncertainty remains at subnational scales due to geographical variability and field data limitations. We present an assessment of blue carbon storage at five mangrove sites across West Papua Province, Indonesia, a region that supports 10% of the world's mangrove area. The Additional supporting information may be found online in the Supporting Information section. How to cite this article: Sasmito SD, Sillanpää M, Hayes MA, et al. Mangrove blue carbon stocks and dynamics are controlled by hydrogeomorphic settings and land-use change. Glob
Abstract. Estimation of belowground carbon stocks in tropical wetland forests requires funding for laboratory analyses and suitable facilities, which are often lacking in developing nations where most tropical wetlands are found. It is therefore beneficial to develop simple analytical tools to assist belowground carbon estimation where financial and technical limitations are common. Here we use published and original data to describe soil carbon density (kgC m −3 ; C d ) as a function of bulk density (gC cm −3 ; B d ), which can be used to rapidly estimate belowground carbon storage using B d measurements only. Predicted carbon densities and stocks are compared with those obtained from direct carbon analysis for ten peat swamp forest stands in three national parks of Indonesia. Analysis of soil carbon density and bulk density from the literature indicated a strong linear relationship (C d = B d ×495.14+5.41, R 2 = 0.93, n = 151) for soils with organic C content > 40 %. As organic C content decreases, the relationship between C d and B d becomes less predictable as soil texture becomes an important determinant of C d . The equation predicted belowground C stocks to within 0.92 % to 9.57 % of observed values. Average bulk density of collected peat samples was 0.127 g cm −3 , which is in the upper range of previous reports for Southeast Asian peatlands. When original data were included, the revised equation C d = B d × 468.76 + 5.82, with R 2 = 0.95 and n = 712, was slightly below the lower 95 % confidence interval of the original equation, and tended to decrease C d estimates. We recommend this last equation for a rapid estimation of soil C stocks for well-developed peat soils where C content > 40 %.
Aboveground forest structure, biomass, and primary productivity in a tropical heath forest in Central Kalimantan (Indonesian Borneo) were examined using data from 1‐ha plots and stand‐level allometric equations developed from harvested tree samples. The study site experienced a severe drought in 1997–1998 associated with the El Niño Southern Oscillation event. The drought effect on heath forest productivity was also assessed by evaluating changes in wood mass increment rates. Allometric relationships suggested that heath forest trees had leaves with smaller specific leaf area (SLA), and large heath forest trees allocate more to leaf mass compared to mixed dipterocarp forest trees. Aboveground biomass (for trees ≥ 4.8 cm DBH) in two 1‐ha plots, P1 and P4, totaled 244.8 and 232.0 Mg/ha. Aboveground wood mass increment rate was –0.1 and 4.7 Mg/ha/yr in P1 and P4 during the drought period (from February to August 1998), while it quickly recovered to 8.1 and 8.5 Mg/ha/yr during the post‐drought period (from August 1998 to August 1999 for P1 and from August 1998 to November 1999 for P4). This suggests a severe impact of the drought on heath forest productivity. Leaf characteristics of heath forest such as small SLA and long‐lived leaves probably play a significant role in effective assimilation and maintenance of heath forest productivity under stressful conditions.
Estimation of soil carbon stocks in tropical wetlands requires costly laboratory analyses and suitable facilities, which are often lacking in developing nations where most tropical wetlands are found. It is therefore beneficial to develop simple yet robust analytical tools to assess soil carbon stocks where financial and technical limitations are common. Here we use published and original data to describe soil carbon density (gC cm<sup>−3</sup>; C<sub>d</sub>) as a function of bulk density (g dry soil cm<sup>−3</sup>; B<sub>d</sub>), which can be used to estimate belowground carbon storage using Bd measurements only. Predicted carbon densities and stocks are compared with those obtained from direct carbon analysis for ten peat swamp forest stands in three national parks of Indonesia. Analysis of soil carbon density and bulk density from the literature indicated a strong linear relationship (C<sub>d</sub> = B<sub>d</sub> × 0.49 + 4.61, <i>R</i><sup>2</sup> = 0.96, <i>n</i> = 94) for soils with an organic C content >40%. As organic C content decreases, the relationship between C<sub>d</sub> and B<sub>d</sub> becomes less predictable as soil texture becomes an important determinant of C<sub>d</sub>. The equation predicted soil C stocks to within 0.39% to 7.20% of observed values. When original data were included in the analysis, the revised equation: C<sub>d</sub> = B<sub>d</sub> × 0.48 + 4.28, <i>R</i><sup>2</sup> = 0.96, <i>n</i> = 678 was well within the 95% confidence intervals of the original equation, and tended to decrease C<sub>d</sub> estimates slightly. We recommend this last equation for a rapid estimation of soil C stocks for well developed peat soils where C content >40%
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