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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
2
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.
3
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
6
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
10
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
11
12
13
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
8
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
14
15
Allometric equations for Belowground biomass of
Four key species of savanna woodland
Source: Koala et al. in prep
16
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
17
Source: Satcie Wolney Natural Capital Project
18
Source: Satcie Wolney Natural Capital Project
19
Source: Satcie Wolney Natural Capital Project
20

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Long-term monitoring of rangelands: Impacts of fire, tree cutting and livestock grazing on carbon sequestration in West Africa

  • 1. 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
  • 2. 2
  • 3. 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. 3
  • 4. Shrub savanna Agroforestry parkland Tree and shrub savanna Tree savanna
  • 5. Agent of vegetation dynamic Fire Grazing Tree cutting
  • 6. Long term monitoring of tree growth at plot level 6
  • 8. 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
  • 9. 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
  • 10. Evaluation of grass biomass Once a year monitoring of the grass layer 10
  • 11. 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 11
  • 12. 12
  • 13. 13 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 8 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
  • 14. 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 14
  • 15. 15 Allometric equations for Belowground biomass of Four key species of savanna woodland Source: Koala et al. in prep
  • 16. 16 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
  • 17. 17 Source: Satcie Wolney Natural Capital Project
  • 18. 18 Source: Satcie Wolney Natural Capital Project
  • 19. 19 Source: Satcie Wolney Natural Capital Project
  • 20. 20