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					Impacts of Land Use and Climate Change on
 Carbon Dynamics in South-Central Senegal

    Part II. Spatially Explicit Modeling of
              Carbon Dynamics


 Shuguang Liu1, Maguette Kaire3, Ousmane Diallo4,
           Eric Wood1, Larry Tieszen5

  Acknowledgements : Abdoulaye Welle4, Paul Woomer6


           1SAIC,    EROS Data Center, Sioux Falls,SD, U.S.A.
                         2ISMRR, Dakar, Senegal
        3Institute Senegalais Recherches Agricoles, Dakar, Senegal
                4Centre de Suivi Ecologique, Dakar, Senegal
   5U.S. Geological Survey, EROS Data Center, Sioux Falls, SD, U.S.A.
                     6SACRED/Africa, Nairobi,Kenya
Presentation Outline

1.   Background
2.   Objectives
3.   Field Measurements
4.   Spatially-explicit Modeling
5.   Results
6.   Summary
               Background
1. No-internationally-agreed methods exist for
   quantifying C emissions and sequestration
   over large areas.
2. Such methods are urgently needed for
   quantifying C sources and sinks from local to
   global scales (e.g., global C cycle and C
   sequestration projects).
3. The impacts of land use and climate change on
   carbon dynamics in African regions are not
   well-investigated.
                 Objectives

1. Adapt GEMS (general ensemble
   biogeochemical modeling system) for Africa
2. Quantify carbon dynamics in the Department
   of Velingara from 1900 to 2100
3. Assess the impacts of land use and climate
   change on carbon dynamics
4. Discuss carbon management options
 SOCSOM Field Sites
Department of Velingara
Velingara Study Sites –
Land Use / Land Cover
            Field Measurements of Carbon Stocks



Cover        Biomass                          SOC (0-40 cm)
             Mean           Range             Mean     Range
Cropland        1.9          0.9-4.0            29.9     15.0-56.0
Fallow          29.9        6.2-49.5             22.2      20.2-25.5
Forest          53.3      19.1-134.0             41.3      25.8-57.4
Parkland        20.0       19.4-20.5             18.8      17.0-19.8
Savanna         26.1       14.7-43.1             37.7      29.7-50.1

Data were collected around six villages in five land cover classes.
Unit: MgC ha-1
             Field Measurements of Carbon Stocks

       100
        90
        80
        70
        60
Mg C/ha 50
                                                                 C BIOMASS
        40                                                       SOC
        30
        20
        10
         0
             Cropland   Fallow     Forest     Parkland Savanna
                                 Land Cover
        Major Components of GEMS
          Structure of ENSEMBLE

 land cover                             Soil


Land use                                        climate




                                           N deposition
    .......


    Spatial and Temporal C Dynamics and Uncertainties
        Spatially-Explicit Biogeochemical Modeling

The General Ensemble biogeochemical Modeling System (GEMS) is developed to
simulate carbon dynamics over large areas. It consists of
Encapsulated ecosystem biogeochemical model(s).
Data assimilation system
                                   Data

Input/output processor
                                   Assimilation                                             Ecosystem
                                                                     Input Files
                                   System                                                 Biogeochemical
                                                                                              Model

User-friendly GUI              JFD Table                                                                   Output
                                                                                                             Files


                            JFD Cover                            Databases



                                                                Land Use
                                             Soils    Climate   Info Units




                             Overlay         Land Cover
                            Operation                                                              Time

                                                                                   Spatial and Temporal Changes of Land Cover,
                                                                                       Carbon Stock in Vegetation and Soils
                                                     GIS Coverages
               Modeling Environment Specifications
jfd_vlg.xtr       JFD file
var_order_vlg.xtr     variable order in the JFD file
/edcsnw64/data/sliu/velingara/edc100files       default century 100 files
status0.bin      file name specifying the starting status of simulations; use NONE if no file
2                previous status based on potential vegetation types (=1), or JFD cases (=2)
status1.bin      file name specifying the ending status of simulations; use NONE if no file
0                spinning up run under potential vegetation (=1), otherwise (=0)
0                    MONTE_CARLO (yes = 1; no=0)
5             Number of runs for each unique JFD case
2                Land cover choice (1 --- ag census data; 2 --- GIS grid Time Series; 3 --- both)
6                total number of LC datasets
9                max number of years that remote sensing can pick up clearcutting activities
1900             Init_landcov
1973             lc0
1978             lc1
1984             lc2
1990             lc3
1999             lc4
soil.data         soil data base
soil_dr_vlg.data        soil drainage data
prec_tab.txt                    monthly precipitation
MinTemp.txt                     monthly min temperature
maxTemp.txt                     monthly max temperature
croprotat.data    crop trasition probability generated from NRI
n_depo.txt     atmospheric deposition data base
lc2cent.map     land cover codes and default site file
crop_comp.data    crop composition data
fallow.data       fallow info
manager.data    data on fire, forest harvest, grazing etc.
                                                                               Default site file
                                                                               Tree or crop species
        Mapping                                                                Rotation probability
                                                                               Harvesting practices
        Land Cover to                                                          Fertilization
        CENTURY                                                                Irrigation
                                                                               Grazing
                                                                               Organic matter addition
                                                                               Land fire
                                                                               Cultivation
                            type
lc_Code colInComp Trends_class         abgc_rank   Deflt_site_fCENTTREE       Crp_Harv
                                                                       CENTCROP          fert   irri   FIRE   graz   OMAD   cult   trem
      133     101        14        0           0   barren.100 CZERO    CZERO  NONE       NONE   NONE   NONE   NONE   NONE   NONE   NONE
      233     102        15        0           0   barren.100 CZERO    CZERO  NONE       NONE   NONE   NONE   NONE   NONE   NONE   NONE
      300     100        30        3           1               DDWD
                                                   vlg_fallow.100      TKNZ   NONE       NONE   NONE   BSH1   VLG    NONE   NONE          2
      603     201         3        3           5               DDWD
                                                   vlg_savwd.100       TKNZ   NONE       NONE   NONE   BSH2   VLG    NONE   NONE          4
      613     202         4        3           3   vlg_bush.100DDWD    TKNZ   NONE       NONE   NONE   BSH1   VLG    NONE   NONE          2
      623     203         5        3           8               DDWD
                                                   vlg_dsavwd.100      TKNZ   NONE       NONE   NONE   BSH2   VLG    NONE   NONE          4
      633     204         6        3           7               DDWD
                                                   vlg_dsavwdb.100     TKNZ   NONE       NONE   NONE   BSH2   VLG    NONE   NONE          4
      643     205         8        3           8               DDWD
                                                   vlg_ddecw.100       TKNZ   NONE       NONE   NONE   BSH3   VLG    NONE   NONE          4
      653     206         9        3          10               GALA
                                                   vlg_evergr.100      TKNZ   NONE       NONE   NONE   BSH4   VLG    NONE   NONE          2
      663     207        12        3          10               GALA
                                                   vlg_evergr.100      TKNZ   NONE       NONE   NONE   BSH4   VLG    NONE   NONE          2
      673     208        13        3           2               DDWD
                                                   vlg_shrsav.100      TKNZ   NONE       NONE   NONE   BSH1   VLG    NONE   NONE          2
      933     209        10        0           0   barren.100 CZERO    CZERO  NONE       NONE   NONE   NONE   NONE   NONE   NONE   NONE
      810       1         1        2           0   vlg_ag.100 CZERO    MLT    VLG_G      NONE   NONE   NONE   NONE   VLG3   AT     NONE
      820       2         1        2           0   vlg_ag.100 CZERO    SRGM   VLG_G      NONE   NONE   NONE   NONE   VLG3   AT     NONE
      830       3         1        2           0   vlg_ag.100 CZERO    COT    COTG       N1     NONE   NONE   NONE   VLG3   AT     NONE
      840       4         1        2           0   vlg_ag.100 CZERO    GNUT   GN_L       NONE   NONE   NONE   NONE   VLG3   AT     NONE
      850       5         1        2           0   vlg_ag.100 CZERO    MZUN   VLG_G      NONE   NONE   NONE   NONE   VLG3   AT     NONE
      890       6         1        2           0   vlg_ag.100 CZERO    RICE   RIWS       N1     A95    NONE   NONE   NONE   HT     NONE
      810       1         2        2           0   vlg_ag.100 CZERO    MLT    VLG_G      NONE   NONE   NONE   NONE   VLG1   AT     NONE
      820       2         2        2           0   vlg_ag.100 CZERO    SRGM   VLG_G      NONE   NONE   NONE   NONE   VLG1   AT     NONE
      830       3         2        2           0   vlg_ag.100 CZERO    COT    COTG       N1     NONE   NONE   NONE   VLG1   AT     NONE
      840       4         2        2           0   vlg_ag.100 CZERO    GNUT   GN_L       NONE   NONE   NONE   NONE   VLG1   AT     NONE
      850       5         2        2           0   vlg_ag.100 CZERO    MZUN   VLG_G      NONE   NONE   NONE   NONE   VLG1   AT     NONE
               Crop Composition (%)
              and its Temporal Change

                Sorghu          Ground-
Year   Millet     m      Cotton  nuts     Maize   Rice
1973   18.3      2.7     28.9    35.1      9.2    5.8
1978   26.2      8.8     16.1    25.4     12.0    11.4
1984   11.3      17.4    32.0    15.6     16.3    7.3
1990    9.5      21.6    14.7    15.9     27.2    11.1
1999    7.1      26.7    12.1    29.0     18.2    6.9
                    Two Fallow Scenarios


Land Cover                     Time In Crop          Time in Fallow (Years) Probability o
                                  (years)
                        minimum maximum             minimum maximum
                        Business as usual
Intensive Agriculture        4             8             0            2         0.14
Extensive Agriculture        3             6             3            6         0.50
Bushland, old fields         0             0             6           15         1.00
                        Agricultural Intensification Scenation
Intensive Agriculture        4             8             0            1         0.08
Extensive Agriculture        3             6             1            2         0.25
Bushland, old fields         3             6             3           10         0.59
      Crop Rotation Probability

    COT FAL GN MA MIL RI        SO
COT 0.31 0.08 0.33     0 0.28 0    0
FAL  0.16  0.5 0.06    0 0.28 0    0
GN   0.34 0.06 0.38    0 0.22 0    0
MA      0    0    0 0.52    0 0 0.48
MIL  0.26  0.1 0.34    0 0.3  0    0
RI      0    0    0    0    0 1    0
SO      0    0    0 0.45    0 0 0.55
                               Land Cover Change
                                                               Year

Land Cover Class                                 1973   1978   1984   1990   1999
Dense Savanna Woodland                            30     29     26     25     21
Dry Deciduous Woodland                            23     21     18     17     16

Dense Savanna Woodland with bowe                  15     14     14     14     14

Extensive Ag land with some fallow (1-3 years)    9      11     8      9      13
Bushland, Old Fields                              0      0      5      3      13

Intensive Ag land with few fallow (0-1 year)      6      8      14     17     8
Savanna Woodland                                  8      8      6      6      5

Moist semi-evergreen woodland, gallery forest     4      4      3      3      3
Riparian forest                                   3      3      3      3      2
Shrub Savanna                                     2      2      2      2      2
 Projected Climate Change From 7 GCMs
                                                       (derived from Hulme et al., 2001)


                                  20

                                  10
                                             y = 0.0638x - 126.8
Change in Temp (C) and Prec (%)




                                                   2
                                                  R = 0.9993
                                   0
                                                                                      y = 0.0142x - 27.708
                                                                                             2
                                  -10                                                       R = 0.9819
                                                                                                                A2-high-temp
                                                                                                                B1-low-temp
                                  -20
                                                                                                                A2-high-prec-JJA
                                                                             y = -0.2125x + 427.29
                                  -30                                                                           B1-low-prec-JJA
                                                                                  R2 = 0.9968

                                  -40
                                                          y = -0.525x + 1043.9
                                  -50                          R2 = 0.9979

                                  -60
                                    1980   2000        2020    2040      2060        2080        2100    2120
                                                                      Year
    Joint Frequency Distribution Table
         1 324       7      1   12   13     13   13   13   13     37
         2   57      7      1   12   11     11   11   11   11     37
         3 2442     17      1   12   13     13   13   13   13     37
         4 459      17      1   12   11     11   11   11   11     37
         5 799      17      1   12    5      5    5    5    5     37
         6 1499     17      1    8    5      5    5    5    5     67
         7    7     17      1   12   13     13   13   13   13     67
         8 117      16      1   12   13     13   13   13   13     37
         9 486      17      1   10   10     10   10   10   10     37
        10   54     17      1   10   10     10   10   10   10     67
        11   36     16      1   12   13     13   13   13   13     95
        12    3     16      1   12    5      5    5    5    5     37
        13   28     16      1    8    5      5    5    5    5     95


Index                                     Land Covers
                  Climate                                       Soil
        Frequency        Reserve
                Data Assimilation System

      1   324     7    1   12    13     13   13   13   13     37
      2    57     7    1   12    11     11   11   11   11     37



          Climate                     Land Covers           Soil Database
          Database
                      Reserved?          Management
                                         Practices, etc.

                 Weather file
CENTURY
input files      Site file
                 Schedule file
                 Etc.
Graphic User Interface in ARC/INFO


              Visualizing Simulated Results
Graphic User Interface in ARC/INFO

      Visualizing Simulated Results
Temporal Change of Spatial Patterns
   Future Management and Climate
             Scenarios

• Agricultural intensification / more or less
  fallow
• Climate change (none, low, high)
• Forest (low cutting, high cutting)
  Climate Change and Carbon Mgmt. - 2000 to 2100


• No Climate Change Scenario (NCCS).

• Low Climate Change Scenario (LCCS).
     Precipitation: change(%) = -0.2125*year + 427.29, r2 = 0.99
     Temperature: change(%) = 0.0142*year – 27.71, r2 = 0.99


• High Climate Change Scenario (HCCS).
     Precipitation: change(%) = -0.525*year + 1043.9, r2 = 0.98
     Temperature: change(%) = 0.0638*year – 126.8, r2 = 0.99
                                                  Grain Yield

                         1. It was assumed that agricultural will not expand in 21st
                            century
                         2. High Climate Change Scenario (HCCS) poses a great
                            threat to food security
                          0.3

                         0.25
Grain Yield (MgC/ha/y)




                                                                                  HCCS, more CUT
                          0.2
                                                                                  LCCS, more CUT
                                                                                  NCCS, more CUT
                         0.15
                                                                                  HCCS, less CUT
                                                                                  NCCS, less CUT
                          0.1                                                     LCCS, less CUT

                         0.05

                           0
                           1800    1850    1900      1950   2000   2050    2100
                                                     Year
                                Net Primary Productivity
        1. NPP varies between 3 and 4 MgC/ha/y.
        2. Large inter-annual variability caused by precipitation
           fluctuation.
        3. NPP decreases under HCCS (i.e., large climate change)

                 4.5
                  4
                 3.5
NPP (MgC/ha/y)




                                                                     HCCS, more CUT
                  3
                                                                     LCCS, more CUT
                 2.5                                                 NCCS, more CUT

                  2                                                  HCCS, less CUT
                                                                     NCCS, less CUT
                 1.5                                                 LCCS, less CUT
                  1
                 0.5
                  0
                  1800   1850     1900   1950   2000   2050   2100
                                         Year
                                        Carbon in Live Biomass
            1. C stock in undisturbed dry and moist tropical forest is 88 and
               135 MgC/ha, respectively
            2. C stock has decreased by 46% from 1900 to 2000 in Velingara
            3. Woodfuel production has a larger impact than climate change

                        120

                        100
Live Biomass (MgC/ha)




                                                                             HCCS, more CUT
                         80
                                                                             LCCS, more CUT
                                                                             NCCS, more CUT
                         60
                                                                             HCCS, less CUT
                                                                             NCCS, less CUT
                         40                                                  LCCS, less CUT

                         20

                          0
                          1800   1850     1900   1950   2000   2050   2100
                                                 Year
                              Soil Organic Carbon
               1. SOC stock in undisturbed dry and moist tropical forest is
                  29 and 35 MgC/ha, respectively
               2. SOC stock has decreased by 9% from 1900 to 2000 in
                  Velingara
               3. The max difference caused by management and climate
                  change options is about 5 MgC/ha in 2100
               35

               30

               25                                                   HCCS, more CUT
SOC (MgC/ha)




                                                                    LCCS, more CUT
               20                                                   NCCS, more CUT
                                                                    HCCS, less CUT
               15
                                                                    NCCS, less CUT
               10                                                   LCCS, less CUT


                5

                0
                1800   1850    1900   1950    2000    2050   2100
                                       Year
                            Total C Stock in Vegetation and Soil
                   1. Total C stock has decreased 37% from 1900 to 2000
                   2. Live biomass reduction accounts for 88% of the total C
                      loss
                   3. Selective logging has a significant impact
                   4. Large climate change (HCCS) reduces C stock
                   160
                   140
                   120
Total C (MgC/ha)




                                                                          HCCS, more CUT
                   100                                                    LCCS, more CUT
                                                                          NCCS, more CUT
                    80
                                                                          HCCS, less CUT
                    60                                                    NCCS, less CUT
                                                                          LCCS, less CUT
                    40
                    20
                     0
                     1800    1850   1900    1950    2000   2050    2100
                                            Year
  Simulated Dynamics of Total C Stock Under Various
     Management and Climate Change Scenarios

     Climate:   NCCS NCSS LCSS LCSS HCSS HCSS
     Cutting:   more less more less more less

2000-2025       82   88    81   87    81   87

2025-2050       75   89    75   88    74   87

2051-2075       72   90    72   90    69   87

2076-2100       70   90    69   90    64   85

                                      (MgC ha-1)
                         Summary

•   The approach and model developed in this study is generic
    and can be easily adapted for the simulations of C dynamics
    in other areas.

•   Establishing a C sequestration project on the basis of a
    sustainable fuelwood and charcoal production system is the
    most feasible and practical option in the region at present.

•   The impact of agricultural sector on regional C dynamics is
    limited due to its limited spatial coverage. Consequently, few
    significant choices exist for setting up agriculture-based C
    sequestration projects in the region.

•   Agricultural sector might become an important player if
    agricultural land is expanded under pressure.

				
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