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Application of site-specific biomass models to quantify spatial distribution of stocks and historical emissions from deforestation in a tropical forest ecosystem

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Abstract

Allometric equations developed for the Lama forest, located in southern Benin, West Africa, were applied to estimate carbon stocks of three vegetation types: undisturbed forest, degraded forest, and fallow. Carbon stock of the undisturbed forest was 2.7 times higher than that in the degraded forest and 3.4 times higher than that in fallow. The structure of the forest suggests that the individual species were generally concentrated in lower diameter classes. Carbon stock was positively correlated to basal area and negatively related to tree density, suggesting that trees in higher diameter classes contributed significantly to the total carbon stock. The study demonstrated that large trees constitute an important component to include in the sampling approach to achieve accurate carbon quantification in forestry. Historical emissions from deforestation that converted more than 30% of the Lama forest into cropland between the years 1946 and 1987 amounted to 260,563.17 tons of carbon per year (t CO2/year) for the biomass pool only. The study explained the application of biomass models and ground truth data to estimate reference carbon stock of forests.
1 23
Journal of Forestry Research
ISSN 1007-662X
Volume 29
Number 1
J. For. Res. (2018) 29:205-213
DOI 10.1007/s11676-017-0411-x
Application of site-specific biomass models
to quantify spatial distribution of stocks
and historical emissions from deforestation
in a tropical forest ecosystem
Cedric A.Goussanou, Sabin Guendehou,
Achille E.Assogbadjo & Brice Sinsin
1 23
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ORIGINAL PAPER
Application of site-specific biomass models to quantify spatial
distribution of stocks and historical emissions from deforestation
in a tropical forest ecosystem
Cedric A. Goussanou
1
Sabin Guendehou
1,2
Achille E. Assogbadjo
1
Brice Sinsin
1
Received: 19 July 2016 / Accepted: 22 October 2016 / Published online: 9 May 2017
Northeast Forestry University and Springer-Verlag Berlin Heidelberg 2017
Abstract Allometric equations developed for the Lama
forest, located in southern Benin, West Africa, were
applied to estimate carbon stocks of three vegetation types:
undisturbed forest, degraded forest, and fallow. Carbon
stock of the undisturbed forest was 2.7 times higher than
that in the degraded forest and 3.4 times higher than that in
fallow. The structure of the forest suggests that the indi-
vidual species were generally concentrated in lower
diameter classes. Carbon stock was positively correlated to
basal area and negatively related to tree density, suggesting
that trees in higher diameter classes contributed signifi-
cantly to the total carbon stock. The study demonstrated
that large trees constitute an important component to
include in the sampling approach to achieve accurate car-
bon quantification in forestry. Historical emissions from
deforestation that converted more than 30% of the Lama
forest into cropland between the years 1946 and 1987
amounted to 260,563.17 tons of carbon per year (t CO
2
/
year) for the biomass pool only. The study explained the
application of biomass models and ground truth data to
estimate reference carbon stock of forests.
Keywords Biomass Reference level Site-specific
biomass model Spatial distribution Tropical forest
ecosystem
Introduction
The concentration of greenhouse gases (GHG) continues to
increase in the atmosphere as a result of human activities
(IPCC 2013; Houghton 2012). Because of the negative
impact this change in chemical composition of the atmo-
sphere has on climate change, mitigation actions are
especially needed (IPCC 2006,2013; UNFCCC 2009;
UNEP 2014) to re-duce global warming. Carbon seques-
tration by forest ecosystems has been identified as one
promising solution (UNFCCC 2011; Wani 2014). The
international community has given the opportunity to
developing countries to contribute to the global efforts to
combat climate change through the implementation of
REDD?activities, including reducing emissions from
deforestation and from forest degradation, conserving for-
est carbon stocks, sustainably managing forests and
enhancing forest carbon stocks (UNFCCC 2009,2011).
One of the requirements to undertake these activities is to
develop a forest reference emission level and/or forest
reference level. Currently, according to the information
reported to the secretariat of the United Nations Frame-
work Convention on Climate Change (UNFCCC 2016),
only few countries in Africa are engaged in the REDD?
process. One of the difficulties identified was related to the
lack of data and tools such as allome-tric equations as well
as to the technical capacity to develop and apply such tools.
Project funding: This study was conducted as part of the project
‘Pilot site: quantification and modelling of forest carbon stocks in
Benin’’ funded by the Global Climate Change Alliance and the
European Union (No. 00009 CILSS/SE/UAM-AFC/2013).
The online version is available at http://www.springerlink.com.
Corresponding editor: Tao Xu.
&Cedric A. Goussanou
cedricgoussanou@gmail.com
1
Laboratory of Applied Ecology, Faculty of Agronomic
Sciences, University of Abomey-Calavi,
01 PO Box 526, Cotonou, Republic of Benin
2
Benin Centre for Scientific Research and Innovation,
03 PO Box 1665, Cotonou, Republic of Benin
123
J. For. Res. (2018) 29(1):205–213
https://doi.org/10.1007/s11676-017-0411-x
Author's personal copy
The knowledge of the distribution of carbon stocks
accordingto land uses and of the mitigation potential of forests
is essential for efficient forest management. It contributes to
the assessment of forest carbon stocks at a global scale.
Forest timber exploitation and establishment of cropland
are among the main drivers of deforestation in Africa (FAO
2010; Vinya et al. 2011; Ratnasingam et al. 2014). As a
result, in many areas, forests are no longer uniform
ecosystems but include in different vegetation types such
as natural forest, degraded forest and fallows. These last
two types of vegetation offer the possibility to implement
reforestation and forest management activities to re-
establish the forest. The topic of assessments of forest
carbon stocks has been addressed by several studies (Mo-
hanraj et al. 2011; Alvarez et al. 2012; Tang et al. 2012)but
those conducted in Africa used default data and expert
judgments (Ekoungoulou et al. 2014; Liu et al. 2014). To
improve the assessment of carbon stocks and mitigation
potential of African forests, the use of country-specific data
and tools such as allometric equations is needed (Guen-
dehou et al. 2012; Goussanou et al. 2016).
Hirata et al. (2008), Guo et al. (2010), Djomo et al. (2011),
Liu et al. (2012,2014), Galeana-Pizan
˜a et al. (2014) and
Rudiyanto et al. (2015) have studied the distribution of car-
bon stocks in tropical regions using remote sensing, mod-
elling and geographical information systems (GIS). But
other studies (Wulder et al. 2008; Du et al. 2014; Vichar-
nakorn et al. 2014; Chen et al. 2015) reported that these
approaches need also ground truth data for validation.
Forest distribution maps are available in Benin but these
maps do not show the distribution of carbon stocks. These
dis-tribution maps would be useful to develop a baseline in
order to assess the performance of the implementation of
mitiga-tion actions such as reducing emissions from
deforestation and forest degradation, sustainably managing
forests, con-serving and enhancing carbon stocks
(UNFCCC 2011).
The objective of this study was to develop a carbon map
for the Lama forest, a semi-deciduous forest in southern
Be-nin using site-specific allometric equations and data.
The study also intended to give examples of how the ref-
erence and the distribution of carbon stocks could be
addressed at a sub-national level as a transition to national
carbon mapping. Factors affecting variation of carbon
stocks are also discussed.
Materials and methods
Study area
The study area was the Lama forest reserve, a semi-
deciduous forest ecosystem located in southern Benin
(Nagel et al. 2004) between 6550and 7000Latitude
North and 2040and 2120Longitude East. The map of
the location of the study area was presented in Gous-
sanou et al. (2016). The forest covers an area of
16,250 ha including 4777 ha of natural forest entirely
protected, referred to as the ‘Noyau Central’. The climate
is tropical moist (IPCC 2006). Monthly average tem-
peratures vary from 25 to 29 C and the mean annual
rainfall is 1200 mm. Monthly rainfalls exceed 100 mm
except for January, February and March which are the
warmest months. Two rainy seasons occur between mid-
March and mid-July and between mid-September and
mid-November.
The soil in the area is hydromorphic clayey vertisol
(40–60% of clay) characterized by poor drainage and a
pH range of 5–5.5 in the 0–30 cm horizon (Ku
¨ppers
et al. 1998). The vegetation types include an undisturbed
forest, a degraded forest and fallow (Bonou et al. 2009).
Land classification is based on the extent of historical
deforestation activities that have affected the natural
forest. Between 1946 and 1987, 9000 ha of natural forest
was converted to cropland (Emerich et al. 1999). The
undisturbed forest refers to the part of the study area that
has remained intact while degraded forest and fallow
refer to areas that were subject to less perturbations and
severe disturbances respectively. Since the interruption of
agricultural activities between 1986 and 1987, protection
measures, including some afforestation activities through
enrichment, have taken place in areas previously dis-
turbed. Applying the default transition period of 20 years
(IPCC 2006), degraded forest and fallow, which were in
transition from cropland to forest land, have been clas-
sified forest since 2009 but under categories degraded
and fallow. In 1986, the areas reported by von Bothmer
et al. (1986) were 3784 ha for undisturbed forest,
5827 ha for degraded forest, 5800 ha for fallow land and
840 ha for plantation forest. The undisturbed and
degraded forests are dominated by species such as
Afzelia africana (Sm.), Ceiba pentandra (L.) Gaertner,
Diospyros mespiliformis (Hochst. Ex A.DC.), Dialium
guineense (Wild), Mimusops andongensis Hiern. (Sapo-
taceae), Celtis brownii (Rendle.), Holarrhena floribunda
(G. Don) Durand et Schinz, Malachanta alnifolia (Bak)
Pierre, Drypetes floribunda (Mu
¨ll. Arg.) Hutch and
Cynometra megalophylla Harms. The fallows are char-
acterized by open canopy forests containing dominant
species such as Anogeissus leiocarpa (DC.) Guill. &
Perr. Lonchocarpus sericeus (Poir.) Kunth, Albizia zygia
(DC.) J.F. Macbr. and Ficus sur (cv. Forssk.). The
dominance of the tree species was determined on the
importance value index (Goussanou et al. 2016). The
plantation is composed of species such as Tectona
grandis and Gmelina arborea.
206 C. A. Goussanou et al.
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Sampling design and data collection
The sampling design followed the approach described by
Guendehou et al. (2012) and Goussanou et al. (2016). Data
on tree dimensions (ground diameter, dbh, diameter along
the stem and height) and wood samples were collected
between October 2013 and February 2014, in 45 plots of
50 m 950 m distributed across all vegetation types. The
45 plots were distributed proportional to the area of each
vegetation type and this resulted in 20, 10, and 15 plots
established in the undisturbed forest, degraded forest and
fallow respectively. The data collected and additional data
from Guendehou et al. (2012) were used to develop spe-
cies-specific and generic biomass models (Goussanou et al.
2016). The collected samples were used to determine wood
densities in the laboratory.
Computation of biomass and carbon stocks
Data from diameter at breast height (dbh) and stem height
measurements were used as inputs to the twenty-three
species-specific biomass models and generic model
developed by previous studies (Guendehou et al. 2012;
Goussanou et al. 2016) to estimate stem biomass. The
stocks were calculated at plot level by applying the specific
models to species for which models were developed and by
using the generic model for non-dominant species for
which enough data was not available to develop specific
models. Stem biomass stock for each plot was derived
following Eq. 1and for each vegetation type using Eq. 2.
The stem biomass stocks were multiplied by the available
biomass expansion factor (BEF) and the root-to-shoot ratio
(IPCC 2006; Mokany et al. 2006) to derive the total above-
and below-ground biomass (Eq. 3). Total biomass per ha
for each vegetation type was the ratio of total biomass to
the total area of the vegetation type. Biomass for all veg-
etation types was then summed to derive the biomass of the
whole stand.
Bstemp¼XijðBsmiþBgmjÞð1Þ
where Bstemp=biomass stock in plot p,Bsm
i
=biomass
stock derived from specific model applied to dominant
species i(kg), Bgm
j
=biomass stock derived from generic
model applied to non-dominant species j(kg).
BstemVegetation type v¼XpBstemp;vð2Þ
where Bstem
vegetation type v
=total stem biomass of vege-
tation type v, Bstem
p,v
=stem biomass stock in plot p
belonging to vegetation v
TBvegetation type v ¼Bstemvegetation typev BEF ð1þRÞ
ð3Þ
where, TB
vegetation type v
=total above and below ground
biomass stock of vegetation type v(kg), BEF =biomass
expansion factor, 3.4 (IPCC 2006), R=root-to-shoot ratio,
0.24 (IPCC 2006).
The biomass was converted to carbon stock using the
average carbon content (48.7 ±0.8% dry matter) derived
from Guendehou et al. (2012).
Data analysis
The structure of the forest with respect to the distribution of
tree density and basal area, according to diameter classes
within and across vegetation types, was assessed by
graphical observations using the statistical computing
software R (R Development Core Team 2012) (Fig. 1).
The variation of biomass stock within and between
vegetation types was analyzed and correlated with param-
eters including tree density, basal area and stem height.
Density refers to the average number of trees per plot and
basal area is the sum of the cross-sectional area at 1.3 m
above the ground level of all trees in a plot (Bonou et al.
2009). In order to perform this analysis, all data (stem
density, basal area and biomass) were distributed in five
diameter classes: B15, 15–30, 30–45, 45–50, [50 cm.
Individuals for which the dbh was B15, were considered
small trees according to the National Office of Wood.
ArcGIS 10 was used to map the distribution of carbon
stocks according to vegetation type using the map of the
Lama forest developed by Bonou et al. (2009). From vector
format of vegetation map, we added attribute fields ‘‘type
of vegetation’’, ‘‘area’’ and ‘‘carbon’’. The attribute ‘‘type
of vegetation’’ referred to undisturbed forest, degraded
forest and fallow. The attribute ‘‘area’’ was the measure of
each unit of vegetation type. The attribute ‘‘carbon’’ was
obtained as a multiplication of the attribute ‘‘area’’ of the
‘type of vegetation’’ by the mean value of the carbon stock
associated with the vegetation type concerned. These
vegetation layers with all attributes were stored in the GIS
for visualization. The vegetation layer was display based
on the attribute ‘‘carbon’’. The carbon stocks were dis-
tributed in nine classes: \10, 10–15, 15–20, 20–25, 25–30,
30–35, 35–40, 40–45,[45 t C/0.25 ha (Fig. 2). The ranges
were derived based on the carbon estimated at the plot
level (Table 2).
Results
Forest structure
There were no significant differences with respect to spe-
cies richness across vegetation types. Thirty-eight, 37 and
Application of site-specific biomass models to quantify spatial distribution of stocks and207
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36 species were identified in undisturbed forest, degraded
forest and fallow respectively (Table 1). Low values of
Shannon diversity index indicated less diverse species
communities across vegetation types while Pielou evenness
values revealed that species were somewhat evenly dis-
tributed in the vegetation types. Large differences were not
observed with respect to Shannon diversity and species
evenness (Table 1).
In each vegetation type, the lowest tree density was
found in higher diameter classes, suggesting that more
individuals were detected in lower diameter classes. There
was a relatively good representation of trees for diameter
classes less than 30 cm. The density is higher in undis-
turbed forest (542 stem ha
-1
) than in fallow
(349 stem ha
-1
) and in degraded forest (340 stem ha
-1
)
(Table 1, Fig. 1). Nearly 50% of trees measured in all
Fig. 1 Distribution of tree density (a) basal area (b) and total biomass (c) according to diameter classes across vegetation types
Fig. 2 Map of carbon stocks in Lama Forest Reserve
208 C. A. Goussanou et al.
123
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diameter classes were located in the undisturbed forest.
Large variations of density and basal area among vegeta-
tion type were observed.
Basal area varied significantly between vegetation types
ranging from 9.27 m
2
ha
-1
(fallow) to 18.60 m
2
ha
-1
(undisturbed forest) (Table 1). In fallow and degraded
forest, diameter classes between 15 and 30 cm contained
higher values of basal area which decreased in high
diameter classes (Fig. 1). In undisturbed forest the increase
in basal area from lower to higher diameter classes was
observed.
In summary, tree density and basal area were the
parameters which affected the most the distribution of
biomass and carbon stocks in the forest (Table 1).
Biomass and carbon stocks
In general, in all vegetation types the lowest biomass was
found in lower diameter classes. In undisturbed forest, the
distribution of biomass according to dbh classes showed an
increasing trend, suggesting that the higher diameter clas-
ses, the higher the biomass and that large proportions of
biomass were located in larger trees (Fig. 1). Across all
dbh classes, more than 50% of the total biomass in the
forest was found in the undisturbed forest (Fig. 1). Carbon
stock in all plots in the undisturbed forest was higher in
comparison to that in the degraded forest and fallow
(Tables 2,3). Carbon stock in the degraded forest was
higher in the middle diameter classes and decreased
slightly for higher diameter classes. With regard to the
fallow area, the carbon stock was almost constant for
dbh [10 cm. Diameter classes between 15 and 50 cm
contributed the most to biomass storage.
The plot that contained the highest biomass (257.74 t
dm) was in the undisturbed forest and the one with the
lowest (17.57 t dm) was in the fallow (Table 2). The
observed order of magnitude of the average total biomass
per plot was: undisturbed forest [degraded forest [fallow
(Table 2).
In each vegetation type, there was large variation of
biomass stock across plots (Table 2). The estimated coef-
ficient of variation (CV) was 27% for undisturbed forest,
32% for degraded forest and 48% for fallow. The biomass
per ha in the undisturbed forest was 2.7 times and 3.4 times
higher than stocks estimated in the degraded forest and
fallow respectively (Tables 2,3).
Emissions from historical deforestation
Deforestation activities that took place in the Lama forest
between 1946 and 1987 converted 9000 ha of natural forest
into cropland (Emerich et al. 1999). Assuming that all the
biomass was entirely removed during the conversion and
considering the carbon stock per ha in Table 3, the emis-
sions from historical deforestation amounted to 260
563.17 t CO
2
/year. Enough data was not available to
quantify the emissions from other carbon pools including
dead organic matter and soil.
Discussion
Forest structure
The low values of tree density observed in the degraded
forest and fallow could be interpreted as the result of his-
torical anthropogenic activities, including harvesting and
agriculture that modified the structure of the forest.
Emerich et al. (1999) reported that nearly 9000 ha of nat-
ural forest were converted into cropland. Harvesting was
also reported by Lokonon (2008). The predominance of
trees in lower diameter classes, i.e. younger trees (Fig. 1a)
is very interesting for the survival of the forest. This could
be explained as a positive effect of the protection measures
implemented over several years which enable the regen-
eration of the forest. The higher potential of regeneration in
the undisturbed forest was in line with (Jayakumar and
Nair 2013; Kimaro and Lulandala 2013), suggesting that
disturbed forests take time to regenerate in the absence of
management. Mean values of tree density obtained in this
study were 155, 330 and 188% higher than the values
reported by Emrich et al. (1999), Bonou et al. (2009), and
Vitoule (2012) respectively. This may be explained by the
diameter size (dbh C5 cm) considered in our study,
Table 1 Vegetation type characteristics
Parameters Undisturbed forest (mean ±SE) Degraded forest (mean ±SE) Fallows (mean ±SE)
Species richness (S, species) 38 37 36
Tree density (tree/ha) 542 340 349
Shannon diversity (H, bits) 3.11 4.03 3.58
Pielou evenness (Eq) 0.59 0.77 0.69
Basal area (G, m
2
/ha) 18.60 ±1.31 11.53 ±0.88 9.27 ±0.89
SE standard error
Application of site-specific biomass models to quantify spatial distribution of stocks and209
123
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whereas dbh C10 cm was considered for the other studies.
Data collected in this study has revealed that species
richness and diversity have been reestablished following
protective measures, including afforestation activities,
indicating a homogenous repartition of species in the Lama
forest. The basal area in this study was higher than those
previously found by Bonou et al. (2009) and Vitoule (2012)
due to probable differences in sampling, in particular in
this study trees in lower diameter classes. The combined
effect of high tree density observed in lower diameter
classes and presence of large trees in undisturbed forest
explains the high basal area detected in undisturbed forest.
Biomass and carbon stocks
The biomass of the three forest types (undisturbed forest,
degraded forest and fallow) fall within the range (50–749 t
dm ha
-1
) reported in other studies conducted in tropical
forests (Clark et al. 2001, Cummings et al. 2002; Sierra
et al. 2007; Lewis et al. 2009; Djuikouo et al. 2010; Djomo
et al. 2011; Lewis et al. 2013). The above- ground biomass
reported by IPCC (2006) for tropical moist deciduous
forest in Africa was 260 t dm ha
-1
(IPCC range 160–430).
The above-ground biomass for undisturbed forest (536.10 t
dm ha
-1
) from Table 3using the root-to-shoot ratio (0.24)
of IPCC (2006) was 33% higher than the upper limit of the
IPCC range. The above-ground biomass for degraded for-
est and fallow (201.89 and 160.35) were within the IPCC
range. The higher biomass in the undisturbed forest may be
attributed to the fact that this forest is semi-deciduous
while IPCC values were applicable to deciduous forests.
Lower biomass stocks found in the degraded forest and
fallow were apparently a direct consequence of historic
deforestation and degradation activities implemented
between 1946 and 1987 affecting tree density. Variation of
biomass due to historical disturbances has been demon-
strated by others (Chazdon 2003; Mani and Parthasarathy
2009; Omeja et al. 2012; Lindner and Sattler 2012; Her-
na
´ndez-Stefanoni et al. 2014; Lin et al. 2015; Osazuwa-
Peters et al. 2015) who reported higher biomass in pre-
served areas than on former clear-cut sites in tropical
regions The higher biomass in undisturbed forest could be
explained by higher tree density and also the presence of
trees with high potential of carbon storage, including
Afzelia africana,Cassipourea congoensis, Ceiba pentan-
dra,Dialium guineense,Diospyros abyssinica and
Diospyros mespiliformis, already reported by Guendehou
et al. (2012) and Goussanou et al. (2016). The proportion of
higher biomass found in higher diameter classes confirmed
that large trees contribute significantly to carbon storage
and should not be excluded from sampling for forest car-
bon estimation. This finding was consistent with results
from Alves et al. (2010) and Lindner (2010).
Emissions from historical deforestation
Countries such as Brazil, Colombia and Guyana have
submitted emissions associated with deforestation in the
context of REDD?and have gone through the technical
assessment process of the UNFCCC secretariat (UNFCCC
2016). The emissions associated with deforestation repor-
ted in this study (260,563.17 t CO
2
/year) were lower than
those reported by Brazil (907,959,466 t CO
2
/year),
Colombia (51,599,618.7 t CO
2
/year) and Guyana
Table 2 Distribution of stem biomass (t dm) and total above and below ground biomass (t dm) across plots
Vegetation type Np Nt Stem biomass stock at plot level
(t dm)/0.25 ha
Total above and below ground
biomass stock at plot level
(t dm)/0.25 ha
Total above and below ground
carbon stock at plot level
(t)/0.25 ha
Range Mean SE Range Mean SE Range Mean SE
Undisturbed forest 20 2711 20.55–61.13 39.42 2.37 86.62–257.74 166.19 9.97 42.19–125.52 80.93 4.86
Degraded forest 10 851 7.45–20.42 14.84 1.52 31.43–86.11 62.59 6.41 15.30–41.93 30.48 3.12
Fallow 15 1312 4.17–22.21 11.79 1.46 17.57–93.62 49.71 6.17 8.56–45.59 24.21 3
Np number of plots, Nt number of sampled trees, tdmtons dry matter, SE standard error
Area of a plot =0.25 ha
Table 3 Distribution of total biomass and carbon stock across vegetation types
Vegetation type Sum biomass stock from
sampled plots (t dm)
Biomass stock per
ha (t dm) ±SE
Carbon stock per
ha (t C) ±SE
Area (ha) Total biomass
stock (t dm)
Total carbon
stock (t C)
Undisturbed forest 3323.74 664.75 ±39.8 323.73 ±19.42 2076.73 1,380,506.27 672,306.55
Degraded forest 625.85 250.34 ±25.64 121.92 ±12.49 1075.67 269,283.23 131,145.69
Fallow 745.62 198.83 ±24.67 96.83 ±12.01 1624.6 323,019.22 157,310.36
210 C. A. Goussanou et al.
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(46,301,251 t CO
2
/year). The differences may be explained
by national circumstances such as the area deforested, the
period of the historical deforestation and the forest types.
Under REDD?few countries in Africa have started the
preparation of the forest reference emission levels and
published data are not at the moment available to make a
comparison with our study.
Conclusions
This study is an example of the application of biomass
models to derive forest carbon stocks, their spatial distri-
bution and historical emissions associated with deforesta-
tion. From the distribution of biomass according to
diameter classes, the study confirmed that trees in higher
diameter classes should not be ignored when developing a
sampling approach to estimate carbon stocks in forest
ecosystems. The approach applied in this study could be
used as a basis for establishing forest reference emission
levels (FREL) or forest reference levels (FRL) in the
context of REDD?. In order to quantify emissions from
deforestation and to develop a national FREL/FRL, his-
torical data on changes in forest area as well as biomass
models for other ecosystems would be required. National
FREL/FRL also requires the inclusion of other
REDD?activities (reducing emissions from forest degra-
dation, conservation of forest carbon stocks, sustainable
management of forests, and enhancement of forest carbon
stocks) and carbon pools including dead organic matter and
soil.
Acknowledgements We thank the Permanent Interstates Committee
for Drought Control in the Sahel (CILSS) and the Regional Centre
AGRHYMET for the technical assistance provided during the
implementation phase of the project.
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... Several studies have reported great heterogeneity in the C stocks of these pools according to land cover, land use and soil type [10][11][12][13][14][15][16][17][18]. In most cases, natural formations or formations with the least human disturbance such as forests store more C in their aboveground biomass and soils per unit area than any other type of land use [15,[19][20][21][22][23]. Tree plantations also show high C stocks but often less than primary or secondary forest [24]. ...
... Tropical forests remain among the main focal points for initiatives to sequester large amounts of C, as well as to recover from biodiversity loss [25,26]. Face to wide spatial variation in forest C below ground and above ground biomass [15,21], understanding the relationship between C storage potential and tree species composition of such ecosystem is compulsory for implementation of management strategies for tropical forest [27,28]. On the contrary, from a given region, soils of croplands have the lowest carbon stocks with variations caused by soil type and agricultural practices [29]. ...
... There are also few studies that have examined the relationship between biodiversity and biomass C stock [11]. In Benin, most studies on C stocks have focused on the impact of cropland practices on soil C stocks [17,20,42] or on forest biomass C stocks [21]. It is then necessary to characterize the C stocks of all the land uses in these landscapes. ...
... The Lama forest reserve is one of the largest remnants of dense semideciduous forest in Dahomey gap with a specific and particular floristic diversity (Djego, 2003). This reserve has been partially affected by historical anthropogenic activities, leading to a mosaic vegetation with different natural regeneration patterns (Bonou et al., 2009, Goussanou et al., 2017. Four major vegetation types have been distinguished in this reserve: the typical non-degraded dense forest, the old pre-forest fallow, the young pre-forest fallow, and the degraded dense forest (Bonou et al., 2009). ...
... (Sapotaceae) and the intensity of past human disturbances in this forest. Alike, Goussanou et al. (2017) reported that the carbon stock in the Lama forest reserve is higher in undisturbed sites than in degraded and fallow ones. This forest offers then a worthy case study to evaluate implications of the SSB for semi-deciduous forest restoration while accounting for past human disturbances. ...
... The Lama forest reserve is a semi-deciduous forest located in southern Benin (Nagel et al., 2004) between 6 • 55 and 7 • 00 North latitude and 2 • 04 and 2 • 12 East longitude (See Fig. 1). It covers 16,250 ha including 4,777 ha of natural forest entirely protected since 1986 and known as the 'Noyau Central' (Goussanou et al., 2017). The Lama forest reserve is characterized by moist tropical climate (IPCC, 2006). ...
Article
The soil seed bank (SSB) in forests is a key indicator of their resilience after disturbances. Despite the growing interest in describing patterns of SSB and understanding potential processes underpinning those patterns, we still know little about SSB patterns and drivers in semi-deciduous tropical forests. Using the regeneration emergence method, we assessed the patterns of SSB (i) across four vegetation types with variable intensity of past human disturbances: typical dense forest - degraded dense forest - young preforest fallow - old preforest fallow, and (ii) in relationships to soil depth (0–5 cm, 5–10 cm, 10–15 cm, 15–20 cm) in a protected tropical semi-deciduous dense forest in Benin, West-Africa. The standing vegetation (adults and regeneration) data and soil samples were collected using a systematic sampling of 60 plots of 10 m × 10 m in the four vegetation types. Herbaceous plants dominated (67% − 78%) the SSB. From the SSB, five tree species emerged: Ceiba pentandra (L.) Gaertn., Dialium guineense Willd., Ficus sur Forssk., Leucaena leucocephala (Lam.) De Wit, and Lonchocarpus sericeus (Poir.) Kunth. Regarding tree species, the total densities of germinated seeds (seeds.m−2) were higher in typical dense forest (28.00 ± 7.22) and young preforest fallow (16.67 ± 7.07) than in old preforest fallow (10.00 ± 6.75) and degraded dense forest (8.89 ± 3.81). When only tree species were considered, the SSB was more diverse and dense in typical dense forest than in other vegetation types suggesting negative effect of past human disturbances on SSB. The similarity of the species composition between the SSB and the surrounding vegetation was low (Jaccard's similarity index ranged from 0 to 17.64%, indicating that the majority of tree species in the surrounding vegetation were absent in the SSB. This study highlighted a need of planting effort of native tree species to restore degraded areas.
... However, the distribution of carbon or biomass stock in tropical forests is not uniform and varies according to region and forest types. Goussanou et al. (2017) reported the following values for total biomass per hectare (including above and below ground): 664.75 tonnes dry matter (t DM) for undisturbed forest, 250.34 t DM for degraded forest and 198.83 t DM for fallow in West Africa. The Intergovernmental Panel on Climate Change (IPCC) suggested, for Africa, different default values for tropical rain forest (310 t DM ha −1 ), tropical moist deciduous forest (260 t DM ha −1 ), tropical dry forest (120 t DM ha −1 ), tropical shrubland (70 t DM ha −1 ) and tropical mountain (40-190 t DM ha −1 ) (IPCC 2006). ...
... The Intergovernmental Panel on Climate Change (IPCC) suggested, for Africa, different default values for tropical rain forest (310 t DM ha −1 ), tropical moist deciduous forest (260 t DM ha −1 ), tropical dry forest (120 t DM ha −1 ), tropical shrubland (70 t DM ha −1 ) and tropical mountain (40-190 t DM ha −1 ) (IPCC 2006). Given this large variation in carbon stocks, there is a need to conduct site-specific biomass measurement rather than using data derived elsewhere as default (Guendehou et al. 2012;Goussanou et al. 2016). ...
... Traditionally, biomass is measured through a destructive method, which consists of cutting down trees and measuring each compartment (Basuki et al. 2009;Nelson et al. 2009;Djomo et al. 2011;Ebuy et al. 2011;Fayolle et al. 2013;Ngomanda et al. 2014). Recently, several studies (Guendehou et al. 2012;Guendehou and Lehtonen 2014;Goussanou et al. 2016;Mensah et al. 2016) have underlined the negative impacts of this approach on forest ecosystems and climate change because it destroys the natural resources and releases large amount of carbon to the atmosphere. Given this impact, tree biomass measurement should be oriented towards non-destructive sampling (Vann et al. 1998;Nordh and Verwijst 2004;Guendehou et al. 2012). ...
Article
Full-text available
Allometric equations are required for a rapid estimation of commercial timber volume and forest biomass stocks. In order to preserve the forest ecosystem, this study applied a non-destructive sampling approach to measure biophysical properties of living trees. From these measurements, volume and biomass models were developed for 11 dominant tree species in a semi-deciduous natural forest and for Acacia auriculiformis in a plantation located in southern Benin. The observations were combined to develop also generic models applicable to non-dominant tree species. Wood samples of the tree species were collected with an increment borer and analysed in the laboratory to determine species-specific wood densities. The sample size was composed of 243 trees in natural forest and 21 trees in plantation. The measurements were conducted in 30 plots of 50 m × 50 m. The graphical assessment of correlation between model outputs (biomass and volume) and variables (diameter and height) and the statistical analysis confirmed that the logarithmic model with two variables had the best predictions. The assessment also confirmed that the model using diameter only as a variable had good predictions when observations on height were unavailable. The comparative analysis of model predictions showed that the generic model in this study over-estimated biomass by up to 74.80% for certain species and under-estimated biomass by 21.18% for other species. The study shows that there are no statistically significant differences between the wood densities in this research and that published in previous studies.
... The average aboveground carbon stock in the Dano watershed is low compared to the values recorded by Goussanou et al. [65] in the Lama forest, located in southern Benin and in the Miombo woodland in Tanzania [66] and in northern Mozambique [67]. This could be explained by better environmental conditions that would favor vegetation productivity in these areas, as observed by Ribeiro et al. [67] in the Miombo. ...
... The lower carbon stock found in shrub savanna and tree savanna were apparently a direct consequence of land degradation and deforestation affecting tree density [68]. Several studies in tropical regions have reported a higher biomass in preserved areas than in degraded vegetation [65,69,70]. The high biomass in croplands is attributed to the presence of high biomass trees while the shrub savanna and tree savanna are dominated by moderate to low biomass trees, which occur in high numbers. ...
Article
Full-text available
West African savannas are experiencing rapid land cover change that threatens biodiversity and affects ecosystem productivity through the loss of habitat and biomass, and carbon emissions into the atmosphere exacerbating climate change effects. Therefore, reducing carbon emissions from deforestation and forest degradation in these areas is critical in the efforts to combat climate change. For such restorative actions to be successful, they must be grounded on a clear knowledge of the extent to which climate change affects carbon storage in soil and biomass according to different land uses. The current study was undertaken in semi-arid savannas in Dano, southwestern Burkina Faso, with the threefold objective of: (i) identifying the main land use and land cover categories (LULCc) in a watershed; (ii) assessing the carbon stocks (biomass and soil) in the selected LULCc; and (iii) predicting the effects of climate change on the spatial distribution of the carbon stock. Dendrometric data (Diameter at Breast Height (DBH) and height) of woody species and soil samples were measured and collected, respectively, in 43 plots, each measuring 50 × 20 m. Tree biomass carbon stocks were calculated using allometric equations while soil organic carbon (SOC) stocks were measured at two depths (0–20 and 20–50 cm). To assess the impact of climate change on carbon stocks, geographical location records of carbon stocks, remote sensing spectral bands, topographic data, and bioclimatic variables were used. For projections of future climatic conditions, predictions from two climate models (MPI-ESM-MR and HadGEM2-ES) of CMIP5 were used under Representative Concentration Pathway (RCP) 8.5 and modeling was performed using random forest regression. Results showed that the most dominant LULCc are cropland (37.2%) and tree savannas (35.51%). Carbon stocks in woody biomass were higher in woodland (10.2 ± 6.4 Mg·ha−1) and gallery forests (7.75 ± 4.05 Mg·ha−1), while the lowest values were recorded in shrub savannas (0.9 ± 1.2 Mg·ha−1) and tree savannas (1.6 ± 0.6 Mg·ha−1). The highest SOC stock was recorded in gallery forests (30.2 ± 15.6 Mg·ha−1) and the lowest in the cropland (14.9 ± 5.7 Mg·ha−1). Based on modeling results, it appears clearly that climate change might have an impact on carbon stock at horizon 2070 by decreasing the storage capacity of various land units which are currently suitable. The decrease was more important under HadGEM2-ES (90.0%) and less under MPI-ESM-MR (89.4%). These findings call for smart and sustainable land use management practices in the study area to unlock the potential of these landscapes to sequestering carbon.
... Biomass production in G. arborea plantations is usually affected by physiological aspects of the plant (adaptation), forestry management, plantation system and age (Rasineni et al., 2011;Verma et al., 2017). Regardless of the type of plantation, pure or mixed, the stem of G. arborea is the component with the highest biomass production, which coincides with that documented in other studies (Arias et al., 2011;Cook et al., 2014;Goussanou et al., 2018). ...
Article
Full-text available
Gmelina arborea (melina) es una especie forestal muy apreciada por su rápido crecimiento, además es de multipropósito por los diversos usos de su madera. El establecimiento de melina en plantaciones puras (PP) ha propiciado la realización de estudios dasométricos y de biomasa; por ende, en México también se han implementado, como alternativa, las plantaciones mixtas (PM); aunque estas están poco documentadas. Los objetivos del presente estudio fueron evaluar y comparar la altura total (H), diámetro (DAP), área basal estimada (AB), volumen (V) y biomasa de G. arborea en PP y PM de 15 años, ubicadas en el estado de Nayarit. Se consideraron tres parcelas de 1 000 m2, en las que se midieron a los individuos de la especie de interés el DAP, H, V y biomasa; asimismo, se recolectaron muestras de suelo. Los árboles de G. arborea en PM pesentó incrementos de 5.8 cm en el DAP, 0.04 m2 en AB, 12.2 % en la biomasa de hojas, 8.8 % en la de ramas, 7.7 % en fuste, 10 % en raíz y 7.6 % en la biomasa total por árbol; lo cual se corroboró con el análisis de ANOVA y la prueba de Tukey. La diferencia en densidad entre las plantaciones indicó un mayor rendimiento en biomasa para la PP (17.9 %). Mejores parámetros dasométricos y producción de biomasa, se asociaron a suelos con pH > 6 y relación C/N > 20. El óptimo rendimiento de G. arborea dependerá del arreglo forestal, el manejo y las características edáficas.
... As florestas tropicais em todo o planeta compartilham certas semelhanças estruturais, o que sugere que princípios gerais determinam sua distribuição (zona geográfica comum), densidade (número indivíduos e espécies) e tamanho das árvores (dimensões biométricas). Contudo, restrições ambientais tendem a provocar distinções entre as dimensões biométricas, o que afeta as estimativas gerais de fluxo e estoque de carbono por cada tipo florestal investigado (BROWN et al., 2006, GOUSSANOU et al., 2017. Para estudar essas diferenças, James et al. (2004) propõem a aplicação da teoria metabólica, através da fisiologia, do desempenho individual dos organismos e da estrutura geral das populações, comunidades e ecossistemas, utilizando os princípios da (física, da química e da biologia) destas florestas, estabelecendo as taxas de captação de recursos do meio ambiente e a alocação de recursos à sobrevivência, crescimento e reprodução que controla os processos ecológicos em todos os níveis de organização de indivíduos para a biosfera. ...
Thesis
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O estudo da relação do D~H (diâmetro-altura) em florestas tropicais melhora nosso entendimento sobre os estoques de biomassa e o papel que desempenham em relação à mitigação dos efeitos das mudanças climáticas no contexto regional e global. Nesse sentido, o objetivo deste estudo foi ajustar modelos alométricos D~H para diferentes tipos de florestas oligotróficas do centro-sul de Roraima, norte da Amazônia brasileira. O estudo tomou como base a medição do diâmetro e da altura de 350 árvores em um transecto permanente de 2.25 km com 5m de largura. O transecto corta um gradiente hidro-edáfico onde ocorrem três tipos florestais (campinarana, ecótono e ombrófila) definidos por condicionantes ambientais (classe de solo e duração da inundação). Os cinco modelos matemáticos testados foram não-lineares: Weibull, Michaelis-Menten, Log1, Log2 e Log3. Os critérios de seleção dos modelos foram o erro padrão dos resíduos (RSE), o coeficiente de determinação ajustado (R²adj) e o Critério de Informação Akaike (AIC). Os modelos alométricos específicos que definem a altura total de cada um dos três tipos florestais investigados são assintoticamente distintos entre si (p = <5%). Análise dos resíduos dos modelos não-lineares mais parcimoniosos mostraram uma tendência de superestimar as alturas totais para os três tipos florestais. O modelo melhor ajustado (Michaelis-Menten) indicou que os modelos gerais publicados previamente para as regiões tropicais usando o diâmetro como variável independente podem superestimar as alturas com base no diâmetro do caule. Os modelos gerais de Weibull superestimaram as alturas na área de estudo em (17.7-105.8%) nos três tipos florestais (campinaranas, ecótono e ombrófila), com exceção nos diâmetros >60cm no tipo florestal da ombrófila onde o modelo Sul Americano subestimou as alturas, porém, o modelo baseado no clima apresentou valores de (13.2-67.6%) superestimando as alturas com maior dimensão na campinarana, entretanto, na área de ecótono superestimou as alturas nos diâmetros <= 20 (cm) e as subestimou nos diâmetros > 38 (cm), na fitofisionomia da ombrófila as alturas foram superestimadas também nos diâmetros <= 20 (cm), e subestimadas nos diâmetros > 25 (cm). Conclui-se que a relação de diâmetro-altura difere entre a fitofisionomia da campinarana com (3-4 meses de inundação) em relação com a área de ecótono (1-2 meses de alagamento) e a floresta ombrófila (sem presença de inundação), indicando que ambientes mais restritos (campinaranas estabelecidas em zonas com maior período de inundação e solos mais pobres) possuem padrões biométricos menores em relação aos tipos florestais com menores restrições (floretas ombrófilas e ecótonos situados em zonas isentas ou com menor período de alagamento temporal).
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