Biomass Mapping in the Forests of Kenya for the GEF UNEP Carbon

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Biomass Mapping in the Forests of Kenya for the GEF UNEP Carbon Powered By Docstoc
					       Above Ground Biomass Sampling in Kenya’s Forests for
              the GEF/UNEP Carbon Benefits Project:
            Potential for a Tier 3 National Carbon Map




     Mike Smalligan, Research Forester
 Global Observatory for Ecosystem Services
Forest Department, Michigan State University
               August 2011                         GIS Data – World Resources Institute
                                                        MODIS Percent Tree Cover
                                                  http://www.wri.org/publication/content/9291
                                       Location of MSU Biomass Sampling

                                       Central:
                                       Aberdares
                                       Mt Kenya




   Western:
   Kakamega
   Mau
   Lambwe




                                                           Eastern:
GIS Data – World Resources Institute
                                                           Arabuko-Sokoke
     Closed Forest (>65%)                                  Tsavo
     Open forest (40-65%)
     Very Open Forest (15-40%)
      Number of Fixed Area Biomass Plots
• MSU has collected 144 biomass plots throughout Kenya
• MSU established partnerships with other organizations (GOK, NGOs, researchers)
  that have shared their 411 plots of biomass field data
    FOREST LAND COVER

    Natural Forests                                        Plantation Forests

    Location           MSU   Partners                      Location             MSU     Partners
    Arabuko             6       97                         Aberdares             22         3
    Kakamega            20     141                         Kakamega              34        34
    Mau                 3                                  Lambwe                1
    Tsavo               3      115                         Mau                   2
                        32     353                         Mt Kenya              27        21
                                                                                 86        58

    NON-FOREST LAND COVER

    Agriculture                         Agroforestry                        Fencerows

    Location           n                Location       n                    Location       n
    Kakamega           13               Nyando         5                    Kakamega       8



    TOTAL                      MSU       Partners
    Forest Plots               118         411
    Non-Forest Plots            26           0
    Total Plots                144         411
                                                        Above Ground Biomass in Plantation Forests
                                                                         (MSU data only – t C/ha)




                                                                                              Tier 1 AGB tC/ha
                                                                         Central:             Moist >20yrs
                                                                         Aberdares            - Broadleaf 71
                                                                         Mt Kenya             - Pinus       56
   Western:                              84.3                                                 Montane >20yrs
   Kakamega                             tC/ha
                                                                  88.6
                                                                                              - Broadleaf 71
                                        n=34                                                  - Pinus       47
   Mau                                                           tC/ha
   Lambwe                                                         n=27
                                    15.8        79.9      66.4                                Source: Table 4.8 in Vol 4,
                                    tC/ha       tC/ha    tC/ha                                2006 IPCC Guidelines
                                     n=1         n=2     n=22




 GIS Data – World Resources Institute
      MODIS Percent Tree Cover
http://www.wri.org/publication/content/9291
                                                         Above Ground Biomass in Natural Forests
                                                                   (MSU data only – t C/ha)




                                                                                        Tier 1 AGB tC/ha
                                                                                        Wet         146
                                                                                        Moist       122
                                                                                        Montane      89
   Western:                              126.6                                          Dry          56
   Kakamega                              tC/ha                                          Shrub        33
                                         n=20
   Mau                                                                                  Source: Table 4.7 in Vol 4,
                                                  86.5                                  2006 IPCC Guidelines
                                                 tC/ha
                                                  n=3




                                                                           33.2
                                                                                         Eastern:
                                                                           tC/ha         Arabuko-Sokoke
                                                                    7.7
                                                                   tC/ha
                                                                           n=6           Tsavo
 GIS Data – World Resources Institute                               n=3
      MODIS Percent Tree Cover
http://www.wri.org/publication/content/9291
  WRI Forest Land Cover Map does not classify dry forests in SE Kenya




GIS Data – World Resources Institute
     Closed Forest (>65%)
     Open forest (40-65%)
     Very Open Forest (15-40%)                      http://www.wri.org/publication/content/9291
                                       Transects in Rukinga Ranch classified as “open shrubs”




GIS Data – World Resources Institute
     Closed Shrubs
     Open Shrubs (45-40%)
     Open Low Shrubs (65-40%)                                              http://www.wri.org/publication/content/9291
Closed Canopy Forests correlated with Annual Rainfall




                             Forest    Approx. Rainfall
                             Kakamega        >1700
                             Aberdares       >1700
                             Mt Kenya        >1700
                             Mau          800-1700
                             Lambwe      1200-1400
                             Arabuko           1000
                             Tsavo        500-800




                       Potential correlation with
                       dry forest land cover

                                    GIS Data – World Resources Institute
                                           Kenya annual Rainfall
                               http://www.wri.org/publication/content/9291
                                               FAO Ecofloristic Zones for Kenya with closed forests




Data from http://cdiac.ornl.gov/epubs/ndp/global_carbon/carbon_documentation.html and WRI Land Cover
FAO Ecofloristic Zones outlined on WRI Elevation
FAO Ecofloristic Zones outlined on WRI Annual Rainfall


                               Apply carbon values to Landsat
                               forest fractional cover map
                               according to ecofloristic zone
                               modified by annual rainfall
                     Kakamega Forest
• Easternmost equatorial rainforest in Africa

• Project Partners: ICRAF, Eco2librium, Glenday

• 54 sample plots in the forest land cover
   – 20 plots in natural forest – 126.6 tC/ha
   – 34 plots in plantations –     84.3 tC/ha
   – Overall forest carbon density of 100 tC/ha (n=54)

• 21 sample plots in landscapes with trees outside the forest
   – 13 plots in agriculture – 13.9 tC/ha
   – 8 plots in fencerows – 37.2 tC/ha
   – Overall landscape carbon density of 22.8 tC/ha (n=21)
     Kakamega Forest - External Data Sources

• Glenday and Eco2librium used IPCC Moist Forest equations (based on
  Brown 97) to determine biomass
   – Glenday -    200 t C/ha AGB for indigenous forests (n=46)
   – Eco2librium - 191 t C/ha AGB for indigenous forests (n=95)

• IPCC Moist overestimates AGB compared to CBP equations by ~35%
   – Eco2librium – 191 t C/ha for indigenous only
       • AGB drops 36% to 121 t C/ha using CBP allometry
   – Glenday – 207 t C/ha for indigenous forest (MSU analysis of Glenday data)
       • AGB drops 37% to 131 t C/ha using CBP allometry
   – Glenday – 134.3 t C/ha for plantation forests (MSU analysis of Glenday data)
       • AGB drops 30% to 94.9 t C/ha using CBP allometry


• MSU measured 126.6 t C/ha in natural forests (n=20)
• Average of adjusted Glenday and Eco2librium is 124.6 t C/ha (n=141)
       CBP – New Allometry for Yala Watershed

• The Yala River originates in the NW corner of the Mau forest complex and
  flows west to Lake Victoria along the southern edge of the Kakamega
  Forest
   •   1200-2200 m elevation, 1500 mm annual rainfall, 20° C mean annual temperature


• ICRAF developed general allometric equations for multiple tree species in
  the Yala Watershed

• ICRAF destructively sampled more than 84 trees
    – 16 in Lower Yala, 38 in Middle Yala, 18 in Upper Yala for equations
    – Additional 12 trees harvested to validate the models

• ICRAF developed allometric equations to predict above ground biomass
  using DBH (cm) or crown area (m2) as inputs
    – AGB = exp(-2.403) * (DBH^2.472)
    – AGB = exp(1.8128) * (crown area^1.2535)
    – BGB = AGB * 0.24
                              Mau Forest

• Largest forest complex in Kenya

• Project Partners: none

• 5 sample plots in the forest
    – 3 plots in natural forest – 86.5 t C/ha
    – 2 plots in plantations – 79.9 t C/ha
    – Overall forest carbon density of 83.8 t C/ha (n=5)

• No sample plots in landscapes outside the forest

• External Data Sources: none
    – Use CBP allometric equation
         Lower Nyando and Lambwe Forest

• Project Partners: ICRAF

• 1 sample plot in the Lambwe Forest
   – No plots in natural forest
   – 1 plot in a young cypress plantation – 15.8 t C/ha

• 5 sample plots in non-forest landscapes in the lower
  Nyando Watershed
   – 5 ICRAF agroforestry demonstration plots – 18.7 t C/ha

• External Data Sources: none
   – Use Brown 97 Dry forests allometry
                                        Mount Kenya

•   Project Partners: KEFRI

•   These data are a partial revisit of a 2009 KEFRI inventory for plantation biomass
    carbon
     – Potential for determining biomass growth rates in plantation forests

•   27 sample plots in the forest
     – No plots in the natural forest
     – 27 plots in plantations of various ages and species – 88.6 t C/ha
          •   5 plots in very old Juniperus prosera have AGB of 171.5 t C/ha


•   No sample plots in landscapes outside the forest

•   External Data Sources: KEFRI
     – 2009 KEFRI inventory used volume equations to determine biomass
     – Use CBP allometric equation
                                 Aberdares

• Project Partners: KEFRI

• These data are a partial revisit of a 2009 KEFRI inventory for plantation
  biomass carbon
    – Potential for determining biomass growth rates in plantation forests

• 22 sample plots in the forest
    – No plots in the natural forest
    – 22 plots in plantations of various ages and species – 66.4 t C/ha

• No sample plots in landscapes outside the forest

• External Data Sources: KEFRI
    – 2009 KEFRI inventory used volume equations to determine biomass
    – Use CBP allometric equation
                       Arabuko-Sokoke Forest

• Largest intact coastal dry forest in Kenya

• Project Partners: KEFRI, Glenday

• KEFRI has 21 permanent sample plots in A-S

• 6 sample plots in the forest (outside the PSP)
    – 6 plots in the natural forest – 33.2 tC/ha
    – No plots in plantations

• No sample plots in landscapes outside the forest

• External Data Sources: KEFRI, Glenday
    – KEFRI did not determine biomass in their permanent sample plots
    – Analysis of Glenday data: AGB = 38 t C/ha (n=97)
         • Both MSU and Glenday used Brown 97 dry forest equations
   Arabuko-Sokoke Forest – External Data Sources

Comparison of 6 MSU fixed area plots in several forest types with Glenday Data


            MSU Plot ID     AGB t C/ha     Forest Type        2 Plot Ave
                215           31.2         Cynometra              33.6
                216           36.1         Cynometra
                217           37.3         Brachystegia           43.2
                218           49.2         Brachystegia
                219           35.2         Brachystegia/Mixed     29.2
                220           23.2         Brachystegia/Mixed
           Average            35.4



           Glenday          AGB t C/ha     Forest Type
                               35          Cynometra
                               46          Brachystegia
                               38          Mixed

           Note: Brown 97 Dry for MSU and Glenday
                            Tsavo Dry Forests

• Wildlife Work’s Rukinga Ranch is first VCS REDD project in Africa

• Project Partners: Wildlife Works

• 3 sample plots in the forest (revisit of 3 WW plots)
    – 3 plots in natural forest – 7.7 t C/ha
    – No plots in plantations

• No sample plots in landscapes outside the forest

• External Data Sources: Wildlife Works
    –   Very large database for VCS project – 115 fixed area plots
    –   Wildlife Works developed their own species and general allometric equations
    –   Use WW general allometric equation
    –   WW reports area weighted mean of 7.9 t C/ha (6 strata in 30,000 ha)
         • WW used their species level equations; MSU used WW general equation
                           Biomass Conclusions
•   Indigenous forests in western Kenya: AGB = 124.1 tC/ha
     – 3 independent data sets are ±9.3% at 95% CL (n=164)
     – IPCC Tier 1 defaults are very close for moist and montane



•   Plantation forests in western Kenya: AGB = 84.3 t C/ha
     – Very heterogeneous according to species and age but the mean of 3 independent data sets are
       ±12.5% at 95% CL (n=119)
     – IPCC Tier 1 defaults appear to underestimate biomass in Kenyan plantations

•   Non-forest landscapes in western Kenya: AGB = 22.8 t C/ha
     – Very heterogeneous land use systems with ±53.6% at 95% CL (n=21)

•   Coastal forests in eastern Kenya: AGB = 37.7
     – 2 independent data sets are ±9.0% at 95% CL (n=103)
     – IPCC Tier 1 defaults are almost double our field measurements for dry coastal forests

•   Inland dry forests in eastern Kenya: AGB = 10.6 t Ch/ha
     – WW area weighted mean is 7.9 t C/ha
     – 2 independent data sets are ±14.4% at 95% CL (n=116)
     – IPCC Tier 1 defaults are 4x higher than our field measurements for “shrub” land cover
Recommendations for a National Remote Sensing Map for REDD

• Use wall to wall Landsat analysis to develop a forest / non- forest land
  cover map for all of Kenya
    – Use Fractional Cover or Disturbance Index to down calibrate forest cover
    – Identify natural and plantation forests

• Use field inventory data for AGB to determine the carbon density of
  specific ecosystems and forest types (natural or plantation)

• Use FAO Ecofloristic Zones with Annual Rainfall and/or Elevation to stratify
  carbon density for national map
    – Tropical rainforest = IPCC
    – Tropical moist      = IPCC
    – Tropical montane
         • 1000 to 2000 m = 124 t C/ha natural and 84 t C/ha plantation
         •       >2000 m = 87 t C/ha natural and 80 t C/ha plantation
         • Non-forest     = 23 t C/ha if >1000 mm
    –  Tropical dry        = 38 t C/ha
    – Tropical Shubland
         • > 500 mm         = 10 t C/ha
         • < 500 mm         = 0 t C/ha

				
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