Current and future carbon content of standing biomass in Gishwati Forest Reserve, Rwanda
Alex Boland, David Courard-Hauri (mentor), Rebecca Chancellor and Aaron Rundus
Environmental Science & Policy Program, College of Arts & Sciences
Abstract
Materials & Methods Continued
Results Continued
Figure 1: Plots in Gishwati forest. Each plot is 50 m x 20 m, and all trees with DBH > 10 cm were measured within the plot.
Figure 2: Growth rates of tropical forests (from Brown and Lugo (1990)). Points are values from
the literature, and the solid line is the best-t value using maximum likelihood estimation. Dotted
lines represent 90% confidence limits.
We determine the carbon content of standing biomass in the
Gishwati forest reserve in northwestern Rwanda, and estimate
the growth potential of naturally regenerated forest there. In
surveying UNFCC Clean Development Mechanism projects, we
suggest that current methods of growth rate projection for
mixed, non-plantation forests may significantly overestimate the
amount of carbon sequestered, and identify an alternative
method for the calculation of sequestration potential. We
find that the Gishwati forest is expected to sequester an average
of 0.885 tonnes C/ha per annum over the next 30 years.
Background
Gishwati Forest Reserve is located in the Albertine Rift which is home
to 567 endemic plant species and numerous endemic primates. The
montane regions of this habitat host the largest number of
threatened and endemic species which make it a key area for
protection of biodiversity. The most significant threat facing the
montane regions of the Albertine Rift is the increasing demand for
farmland and fuel wood. The sale of carbon credits from the Giswati
Forest Reserve could achieve biodiversity conservation, climate
change mitigation, water purification, tourism opportunities and the
protection of agricultural resources. However, current methods for
estimating sequestration in a growing, mixed forest risk significant
overestimation of sequestration potential because they are often
based upon growth rates and growth potential from plantation data.
Therefore, the focus of this study was to produce an accurate
estimate of carbon sequestered in Gishwati forest and propose a
method that reduces the potential for overestimation.
Materials & Methods
Study Site: Gishwati Forest Reserve is located in Western
Rwanda in the Albertine Rift. It receives roughly 1884 mm
annual rainfall and its elevation ranges from 2020-2500 m. The
core forest consists of 886 ha of second growth montane forest.
Data Collection: Chancellor and Rundus led a team in 2010 to
record tree species density and diversity in the core forest. 10
transects spaced at 400 m intervals with plots spaced every
500 m along the transects were created (see figure 1). 2290
total trees were recorded and DBH and height were measured
for each tree.
Data Analysis: We used 5 seperate allometic equations (see
Table 1) for aboveground biomass (AGB) from published
literature that fit the characteristics of rainfall, elevation and
climate for Gishwati Forest.
The results of these were averaged in order to remove bias, except in the case of
Symphonia globulifera for which a species specific allometirc equation was used. We
estimated average biomass for core forest and edge separately, and then determined
total AGB. BGB was calculated from our AGB estimate, and we used a ratio of 0.55
(FAO) to convert total dry biomass to carbon content. For growth rates, we used
maximum likelihood estimation to calculate a best fit line to data points from a study on
tropical moist and wet forests and corrected the asymptote to 269.3 t/ha satelite
estimations for the Gishwati region based on satellite data. From the graph we created
a new equation to estimate carbon sequestered at any point in time for Gishwati Forest
Reserve.
Allometric Equation Type
Equation
Belowground Biomass
BGB = 346.9(AGB/1000)0.8836
Species Specific: Symphonia globulifera
FAO tropical dry forest (rainfall >900 mm/yr)
AGB = (-0.009 + 0.000205(D1.4431)(H1.2301))p/1000
AGB = 34.4703 – 8.0671D + 0.6589D2
FAO tropical moist forest (rainfall >1500 mm/yr) AGB = e-3.1141 + 0.9719lnD2H
FAO generic pan-tropical forest
AGB = 0.0899(D2Hp)0.9522
Large data set pan-tropical forest
AGB = (p/0.6)e-3.742 + 3.45 ln D -0.148(lnD)2
Large dataset moist tropical forest
AGB = 0.509pHD2
FAO Carbon content
Courard-Hauri et al. Gishwati carbon content
C = 0.55B
C =0.65555 *
169.3t
t + 14:6
Table 1: Table of allometric equations used in the calculation of total Biomass. Where FAO is the Food and Agricultural Organization of the
United Nations, AGB is aboveground biomass in kg/ha, BGB is belowground biomass in kg/ha, D is diameter at breast height in cm, H is
height in m, p is density in grams/cm3, C is Carbon in tC/ha and t is time in years
Results
The calculated total biomass for the Gishwati Forest core was 111.4 t/ha (92.4 t/ha AGB
and 18.9 t/ha BGB) and total edge biomass was 86.6 t/ha (71.5 t/ha AGB and 15.1 t/ha
BGB). There are 59.0 tC/ha throughout the forest and 52,271 tC total. The effective age
of the forest was calculated to be 16.1 years, and so a sequestration potential of
0.885 tC/ha per annum over the next 30 years can be determined from Figure 2..
Discussion & Conclusions
We believe that the model presented in this study is more
accurate and generalizable than the current method of using
plantations as a model for forest growth. Our method
requires the construction of an annual increment curve since
we believe it is more critical to correctly estimate the
expected steady-state value than the increment in any given
year since a misestimated steady-state can lead to significant
error in predicting total carbon accumulated over a projects
life time.
References
Bacinni, A., et al. (2008). A first map of tropical Africa's above-ground biomass derived from
satellite imagery. Environmental Research Letters, 3:1-9.
CDM (2009). Project 1578: Uganda Nile Basin reforestation project No. 3; appendix 7. Technical
report, United Nations Framework on Climate Change, Clean Development Mechanism.
Chave, J., et al., (2005). Tree allometry and improved estimation of carbon stocks and balance in
tropical forests. Oecologia, 145:87-99.
Chave, J., et al. (2004). Error propagation and scaling for tropical forest biomass estimates.
Philosophical Transactions of the Royal Society of London, B, 359:409-420.
Eggeling, W. (1940). The Indigenous Trees of Uganda. PhD thesis, University of Edinburgh.
GPFLR (2010). Global Partnership on Forest Landscape Reforestation, Gishwati Area Conservation
Program. www.forestlandscaperestoration.org/regional-networks/eastcentralafrica/gishwati/.
Moya, R. and Munoz, F. (2010). Physical and mechanical properties of eight fast-growing
plantation species in Costa Rica. Journal of Tropical Forest Science, 22:317-328.
Plumptre, A.,et al. (2003). The biodiversity of the Albertine rift. Technical report, Albertine Rift
Technical Reports No. 3.
Ponce-Hernandez, R. (2004). Assessing Carbon Stocks and Modeling Win-Win Scenarios of Carbon
Sequestration through Land-Use Changes. Food and Agriculture Organization of the United
Nations, Rome.
Sun, C., et al. (1996). Tree phenology in a tropical montane forest of Rwanda. Biotropica, 28:668681.
UNFCCC (2009). Ar-ams0004: Simplifed baseline and monitoring methodology for small-scale
agroforestry-afforestation and reforestation project activities under the clean development
Mechanism-version 2.0. Technical report, United Nations Framework Convention on Climate
Change.
UNFCCC (2011). Project cycle search page: Afforestation and reforestation.