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Biomass estimation of secondary forests is required to support the emission reduction of carbon dioxide through an enhancement of forest carbon stocks. Commonly, forest biomass is indirectly estimated using tree biomass allometric models that are developed based on a destructive sampling of sample trees. The availability of biomass allometric models for secondary forests in Indonesia is still limited, particularly for secondary forest ecosystems in eastern Indonesia. This study aimed to develop allometric biomass models for mixed-species trees in a secondary forest of East Halmahera, North Maluku, and to compare their accuracies with some other allometric biomass models that commonly used for estimating biomass of secondary forests. The tree biomass measurement was conducted by using a destructive sampling of 18 mixed-species trees (with diameter range of 5,4 – 36,9 cm) in a secondary forest. The samples of each tree component (stem, branch, twig, and leaf) were analyzed in a laboratory to determine the biomass of each sample tree. Allometric models were developed by using a non-linear regression analysis, which were then compared with other allometric models. This study revealed that the biomass of mixed-species trees in the study area could be estimated accurately using the M7 model that used diameter, height, and wood density variables. Such local allometric model was more accurate than other allometric models commonly used for estimating tropical forest biomass. Alternatively, the M3 model that used diameter and height variables could also be used when wood density data was not available. The local allometric models from this study can enrich the availability of biomass allometric models for secondary forest ecosystems in eastern Indonesia. Keyword: allometric model, destructive sampling, mixed-species, REDD+ , secondary forest

ALLOMETRIC MODELS FOR ESTIMATING TREE BIOMASS OF DRYLAND SECONDARY FOREST IN EAST HALMAHERA