Contents lists available at ScienceDirect Forest Ecology and Management journal homepage: www.elsevier.com/locate/foreco Estimating biomass and carbon for Gilbertiodendron dewevrei (De Wild) Leonard, a dominant canopy tree of African tropical Rainforest: Implications for policies on carbon sequestration P.M. Umunay ⁎ , T.G. Gregoire, M.S. Ashton The School of Forestry and Environmental Studies, 360 Prospect St, Yale University, New Haven, CT 06511, United States ARTICLE INFO Keywords: Antithetic sampling Gilbertiodendron dewevrei Evergreen rainforest Randomized branch sampling ABSTRACT Estimates of global carbon stocks in standing forests are subject to uncertainty because of regional and tree species differences that are usually ignored in global allometric equations. The absence of appropriate site- specific and individual tree allometric equations has led to broad use of pan moist tropical equations, which use has raised questions on the accuracy of the resulting predictions of standing biomass. Here we develop site- specific individual tree allometric equations for estimating biomass of Gilbertiodendron dewevrei, a canopy tree that dominates extensive areas of forest in the Congo basin region. We applied both antithetic and randomized branch sampling to sample for total aboveground biomass components. We evaluated a series of regression models (linear and non-linear) for predicting total aboveground biomass as a function of commonly measured variables including diameter, basal area and total height of 43 sample trees for Ituri and Yoko forests in the Democratic Republic of Congo. We found the best model for total aboveground biomass to be a linear, 3-knot cubic spline model that used only basal area as a predictor with the lowest AIC and BIC of 602 and 610 re- spectively. The incorporation of height in biomass equations did not significantly improve model performance, while models with diameter alone or in combination with height perform poorly. Our results show that models using only basal area are sufficient to accurately estimate biomass for Gilbertiodendron dewevrei and carbon stock, which is an important outcome given that height measurements are usually difficult to acquire. We also de- monstrate that general models used can significantly overestimate amounts of carbon for Gilbertiodendron de- wevrei as compared to the site and species-specific regression model that we have developed. 1. Introduction The proposal of avoided deforestation, compensated reductions and reducing emissions from deforestation (REDD) has received a great amount of attention in the world’s climate change negotiations under the United Nations Framework Convention on Climate Change (UNFCCC) (Herold and Skutsch, 2011; Pelletier et al., 2011). In this scheme, which is still under evaluation and has to undergo negotiation, forested non-Annex I countries would receive financial credit for es- sentially reducing their emissions from deforestation. However, the implementation of the REDD mechanism in Central Africa is compli- cated by numerous issues, including the lack of accurate estimates of standing forest carbon stocks and the unknown rate of carbon seques- tration in natural forests (Henry et al., 2011). As tree biomass is approximately 50% of tropical forest carbon in the active part of carbon cycle (Brown and Lugo, 1982; Malhi and Grace, 2000), scientifically credible estimates of the total aboveground biomass in forest ecosystems are critical for verifying, monitoring and reporting on carbon projects. Estimation of forest carbon stocks in live trees is based on understanding allometric relationships between the measurements of trees (diameter, height and wood density) and bio- mass (Brown et al., 1989; Brown and Lugo, 1982; Chave et al., 2014, 2005; Ketterings et al., 2001; Malhi and Grace, 2000). Accurate allo- metric models can be developed using selected trees for destructive harvesting so as to measure morphological characteristics of tree ar- chitecture and biomass allocation to stem, branches and foliage; and then substantial analytical work needs to be done to relate the mea- sured sample biomass to the entire tree. Little is known about specific allometric relationships of tree species in Central African forests. This lack of information has raised discus- sions on the accuracy of the resulting predictions of standing biomass, since equations were derived from data collected outside Africa (Djomo et al., 2010; Vieilledent et al., 2012). The most commonly used allo- metric equations by Chave et al. (2005) have been mainly developed http://dx.doi.org/10.1016/j.foreco.2017.08.020 Received 25 June 2017; Received in revised form 8 August 2017; Accepted 11 August 2017 ⁎ Corresponding author. E-mail address: peter.umunay@yale.edu (P.M. Umunay). Forest Ecology and Management 404 (2017) 31–44 0378-1127/ © 2017 Elsevier B.V. All rights reserved. MARK