October 29, 2014 1
Long-term monitoring of rangelands
Impacts of fire, tree cutting and livestock grazing on
carbon sequestration in West Africa
Jonas Koala1,2, Mohammed Said2, Louis Sawadogo1, Patrice
Savadogo1, Didier Zida1, Ermias Aynekulu3 and de Leeuw, Jan3
1Institut de l'Environnement et de Recherches Agricoles (INEREA)
2International Livestock Research Institute (ILRI), 3World
Agroforestry (ICRAF)
6TH All Africa Conference of Animal Agriculture (AACAA), KICC,
Nairobi, 27th – 30th October, 2014

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Background
A critical pre-requisite to managing savanna woodland
for carbon storage and sequestration is a good
knowledge about tree and shrub biomass.
Providing accurate measurements of carbon stock is
difficult without precise measurements of biomass.
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Shrub savanna
Agroforestry parkland Tree and shrub savanna
Tree savanna

Agent of vegetation dynamic
Fire Grazing
Tree cutting

Long term monitoring of tree
growth at plot level
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Study sites locations

Experimental design
 Each experimental site
18ha
 Split into 8 blocks
 4 blocks fenced to
exclude (non-grazed)
and the other four
were open for grazing
 Each block further
divided 8 plots of 0.25
ha (50 x 50m)
separated from each
other by 20–30m fire-
breaks

Long-term monitoring of tree
growth at plot level
• Every five year:
complete
inventory of the
trees on each plot
(measurement of
dbh, height, crown
area)
• Once a year
monitoring of the
regeneration
DbH
Dbase
Height

Evaluation of grass biomass
Once a year monitoring of the grass layer
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Above ground biomass
Species specific equations were
developed for
 Acacia dudgeoni
 Acacia macrostachya,
 A. leiocarpa,
 C.ghasalense,
 C. glutinosum,
 C. micranthum,
 C. nigricans,
 C.febrifuga,
 D. microcarpum,
 E.africana,
 P. thonningii
 V. paradoxa
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0 1 2 3 4 5 6 7
0
1
2
3
4
5
6
7
Observed (Log)
Predicted(Log)
R-sq=0.900 Res.df=93 F=218.7 p<0.001 SEE=0.318
Wt=0.213+0.132Db+0.204Dbh+0.0007H-0.005DbxDbh
C. nigricans
1 2 3 4 5 6 7
1
2
3
4
5
6
7
Observed (Log)
Predicted(Log)
R-sq=0.731 Res.df=1170 F=532.8 p<0.001 SEE=0.352
Wt=0.758+0.028Db+0.237Dbh+0.0009H-0.003DbxDbh
+0.0001DbxH-0.0002DbhxH
D. microcarpum
2 4 6 8
2
4
6
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Observed (Log)
Predicted(Log)
R-sq=0.905 Res.df=112 F=162.8 p<0.001 SEE=0.401
Wt=-0.889+0.107Db+0.304Dbh+0.004H-0.006DbxDbh-0.00002DbxH
-0.0002DbhxH+0.000004DbxDbhxH
A. leiocarpa
1 2 3 4 5 6
1
2
3
4
5
6
Observed (Log)
Predicted(Log)
R-sq=0.693 Res.df=438 F=250.2 p<0.001 SEE=0.461
Wt=0.358+0.100Db+0.169Dbh+0.001H-0.004DbxDbh
P. thonningii
Allometric equations for above ground biomass
of some key species of savanna woodland
Source: Didier

Direct roots biomass
assessment
 Monolith
extraction to
assess
disturbances
effects on root
biomass at plot
level
 Excavation to
assess in species
Anogeissus
leiocarpa, Detarium
microcarpum;
Piliostigma
thonningii and
Vitellaria paradoxa
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Allometric equations for Belowground biomass of
Four key species of savanna woodland
Source: Koala et al. in prep

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Treatments Total roots biomass weight (t/ha)
Mean±SE CI 95 %
LS US
CONTROL 16.79±1.55 13.745 19.837
Grazing 11.09±1.76 7.638 14.545
Early Fire 17.37±1.69 14.038 20.693
Cutting 12.09±1.85 8.471 15.719
Grazing x Fire 15.66±1.84 12.041 19.278
Grazing x Cutting 17.54±1.85 13.908 21.168
Fire x Cutting 16.53±1.58 13.429 19.636
Grazing x Fire x Cutting 11.69±2.16 7.453 15.937
Total roots biomass at layer 0-50 cm in savanna woodland
based on grazing, early fire and selective trees cutting and
their interactions
Source: Koala et al. in prep

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Source: Satcie Wolney Natural Capital Project

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Source: Satcie Wolney Natural Capital Project

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Source: Satcie Wolney Natural Capital Project

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