Center For International Forestry Research Cifor ntro International Of La Papa Cip

Lima, Peru

Center For International Forestry Research Cifor ntro International Of La Papa Cip

Lima, Peru
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Manuri S.,Australian National University | Brack C.,Australian National University | Nugroho N.P.,Research Institute for Forestry Technology on Watershed Management | Hergoualc'h K.,Center For International Forestry Research Cifor ntro International Of La Papa Cip | And 5 more authors.
Forest Ecology and Management | Year: 2014

To assist countries to reduce emissions from deforestation and forest degradation, the United Nations has introduced the REDD+. mechanism. This performance-based incentive mechanism requires accurate quantification of carbon stock and emissions. However, currently there are limited existing local or regional equations for estimating aboveground biomass in peat swamp forests. The main objective of this study was to define the most accurate models for aboveground biomass estimation in Indonesian peat swamp forests. We found that the pan-tropical equations performed better in estimating biomass of peat swamp forests than did existing local equations. We developed new equations, based on 148 trees from 24 families with diameter at breast height in the range of 2-167. cm collected from peat swamp forests in the western part of Indonesia. Statistical indicators showed that the best model form was the common linear one using log-transformed data. Estimated biomass values needs to be back-transformed applying correction factors. The ratio estimator correction factor which derives from the ratio between the average of measured biomass and the average of predicted biomass, was found to provide the lowest mean deviation. The existing pan-tropical equations performed similarly to our mixed species and dipterocarp models but they systematically under- or over-estimated the biomass of certain species groups, especially non-dipterocarp trees. We also found that grouping by family (dipterocarp vs. non-dipterocarp) and wood density class (hardwood vs. softwood) significantly improved the accuracy of biomass estimation. In the absence of wood density values, wood density-class specific equations, instead of mixed-species equations improved the accuracy of biomass estimates. © 2014 Elsevier B.V.


Hergoualc'h K.,Center for International Forestry Research | Hergoualc'h K.,Center For International Forestry Research Cifor ntro International Of La Papa Cip | Verchot L.V.,Center for International Forestry Research
Mitigation and Adaptation Strategies for Global Change | Year: 2014

Tropical peat swamp forests, which are predominantly located in Southeast Asia (SEA) and play a prominent role as a global carbon store, are being intensively degraded and converted to agricultural lands and tree plantations. For national inventories, updated estimates of peat emissions of greenhouse gases (GHG) from land use (LU) and land-use change in the tropics are required. In this context, we reviewed the scientific literature and calculated emission factors of peat net emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in seven representative LU categories for SEA i.e. intact peat swamp forest, degraded forest (logged, drained and affected by fire), mixed croplands and shrublands, rice fields, oil palm, Acacia crassicarpa and sago palm plantations. Peat net CO2 uptake from or emissions to the atmosphere were assessed using a mass balance approach. The balance included main peat C inputs through litterfall and root mortality and outputs via organic matter mineralization and dissolved organic carbon. Peat net CO2 loss rate from degraded forest, croplands and shrublands, rice fields, oil palm, A. crassicarpa and sago palm plantations amounted to 19.4 ± 9.4, 41.0 ± 6.7, 25.6 ± 11.5, 29.9 ± 10.6, 71.8 ± 12.7 and 5.2 ± 5.1 Mg CO2 ha-1 y-1, respectively. Total peat GHG losses amounted to 20.9 ± 9.4, 43.8 ± 6.8, 36.1 ± 12.9, 30.4 ± 10.6, 72 ± 12.8 and 8.6 ± 5.3 Mg CO2-equivalent ha-1 y-1 in the same LU categories, respectively. A single land-clearing fire would result in additional emissions of 493.6 ± 156.0 Mg CO2-equivalent ha-1. © 2013 Springer Science+Business Media Dordrecht.

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