Estimating the aboveground biomass in an old secondary forest on limestone in the Moluccas, Indonesia: Comparing locally developed versus existing allometric models

Stas Suzanne M., Rutishauser Ervan, Chave Jérôme, Anten Niels P.R., Laumonier Yves. 2017. Estimating the aboveground biomass in an old secondary forest on limestone in the Moluccas, Indonesia: Comparing locally developed versus existing allometric models. Forest Ecology and Management, 389 : pp. 27-34.

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Quartile : Q1, Sujet : FORESTRY

Abstract : Deforestation and forest degradation are widespread in Indonesia and pose serious threats to biodiversity and other ecosystem services. The Indonesian government is implementing several Reduction of Emissions from Deforestation and Forest Degradation (REDD+) initiatives to help support the conservation of tropical forests, but the eastern part of Indonesia has yet to be included in this effort. Tropical forests growing on limestone are a prominent feature of that region, but little is known about their ecology and management, and only limited research has been conducted on biomass and the associated carbon storage capacity of these secondary forests. Here, we estimate the aboveground tree biomass (AGB) in an old secondary forest on limestone in Seram, the Moluccas, East Indonesia. We destructively sampled all aboveground vegetation in 0.04 ha forest and developed a local allometric model (n = 25; diameter-range of 10.4–41.7 cm). We tested and compared the performance of our locally developed model with existing local models and a recent pantropical model (Chave et al., 2014) at our site. Total AGB in the 1-ha forest plot was estimated at 177 Mg ha−1, of which 141 Mg ha−1 (80%) was allocated in trees ⩾10 cm diameter at breast height (dbh), 33 Mg ha−1 (19%) in trees <10 cm dbh and 2 Mg ha−1 (1%) in lianas and non-woody vegetation. Both our locally developed and the pantropical model estimated the biomass of harvested trees accurately (local model: bias = 0.1%, CV = 15.5%; pantropical model: bias = −7.7%, CV = 17.7%), while other local models had much lower performance (bias = −57.1 to −7.3%, CV = 59.2 to 75.8%). At plot-level, the AGB estimate of the pantropical model approached the estimate of our local model, while other local models considerably underestimated actual AGB. Together, our findings confirm that trees <10 cm dbh can store a large fraction of total AGB in secondary forests, and highlight the robustness of generic models. These results provide further guidance for accurate assessments of forest carbon stocks in Indonesia and more generally for REDD+ initiatives. (Résumé d'auteur)

Mots-clés Agrovoc : Forêt, forêt tropicale, forêt secondaire, Déboisement, Changement climatique, séquestration du carbone, réduction des émissions, services écosystémiques, protection de la forêt, Biodiversité, Biomasse, Modèle mathématique, Dynamique des populations

Mots-clés géographiques Agrovoc : Indonésie, Maluku

Classification Agris : K01 - Forestry - General aspects
K70 - Forest injuries and protection
P01 - Nature conservation and land resources
F40 - Plant ecology
U10 - Computer science, mathematics and statistics

Champ stratégique Cirad : Axe 6 (2014-2018) - Sociétés, natures et territoires

Auteurs et affiliations

  • Stas Suzanne M., Utrecht University (NLD)
  • Rutishauser Ervan, Carbofor-Expert (CHE)
  • Chave Jérôme, CNRS (FRA)
  • Anten Niels P.R., Utrecht University (NLD)
  • Laumonier Yves, CIRAD-ES-UPR BSef (IDN)

Source : Cirad-Agritrop (

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