commercial inventories

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Modeling forest biomass of

Central Africa from extensive

commercial inventories

Quentin Molto

1

_{, Maxime Réjou-Méchain}

2

_{, Nicolas Bayol}

1

_,

Jean-François Chevalier

1

_{, Vivien Rossi}

2

_{, Guillaume Cornu}

2

_{, Fabrice}

Benedet

2

_{, and Sylvie Gourlet-Fleury}

2

1: FRMi: Forest Ressource Management

2: CIRAD, The Tropical Forest Goods and Ecosystem Services unit

EGU 2015 – Session BG2.1

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Context: Forest Carbon Management

• Worldwide tropical biomass maps:

– Saatchi, Sassan S., et al. "Benchmark map of forest carbon stocks in tropical regions

across three continents.“ (2011)

– Baccini, A. G. S. J., et al. "Estimated carbon dioxide emissions from tropical deforestation

improved by carbon-density maps." (2012)

• Comparison:

– Mitchard, Edward TA, et al. "Uncertainty in the spatial distribution of tropical forest

biomass: a comparison of pan-tropical maps." (2013)

Democratic

Republic of

the Congo

Central African Republic

Cameroon

Congo

Gabon

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Data (1)

• Inventories before exploitation or management (2000-2012)

• 41 different operators on about 80 concessions

• 130 000 plots of 0.5 hectares, DBH > 10cm

• terra firme forests

– Hansen, Matthew C., et al. "A method for integrating MODIS and Landsat data for systematic monitoring of forest cover and change in the Congo Basin." (2008)

– Betbeder, Julie, et al. "Mapping of Central Africa forested wetlands using remote sensing." (2014)

• Biomass estimation from trees diameter and wood density

– Chave, J., et al. "Improved allometric models to estimate the aboveground biomass of tropical trees." (2014)

• Biomass distribution:

Forest area:

169.10

6

ha

- for production

62.10

6

ha

- under concession

44.10

6

ha

- under management

26.10

6

ha

- present study

10.10

6

ha

Sources: de Wasseige & Wala Etina, EDF 2010 (2012) Bayol et al., EDF 2010 (2012) OIBT (2011)

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Data (2)

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Data (3)

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• Additive linear model

• Predictive variables:

– AGB published by Baccini et al. (2012) or Saatchi et al. (2011)

– Climate

(Platts, Philip J., Peter A. Omeny, and Rob Marchant. "AFRICLIM: high‐resolution climate projections for ecological applications in Africa." (2014))

– Canopy height

(Simard, Marc, et al. "Mapping forest canopy height globally with spaceborne lidar." (2011))

– Cloud frequency

– Variables computed from elevation

(SRTM)

• 50% of data for model test

• Variable selection: AIC

RMSE

_Baccini

= 93 Mg.ha-1

RMSE

_Saatchi

= 69 Mg.ha-1

RMSE

_ModelB

= 58 Mg.ha-1

RMSE

_ModelS

= 58 Mg.ha-1

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Conclusions

• The biomass of our plots is over-estimated by the

maps:

– Baccini et al. map: + 13 %

– Saatchi et al. map: + 6 %

• The difference between the maps and the plots

can be explained by environnmental or physical

data

• The area of agreement are not the same for both

maps

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Perspectives

• Model mixing the data sources

• Advanced models (non-linear, hierarchical)

• More elaborated physical variables

• Use of forestry knowledge

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Coefficients:

Estimate Std. Error t value Pr(>|t|) AGB_Baccini 0.694769 0.007835 88.670 < 2e-16 *** AnnualPrec -0.056760 0.007429 -7.640 2.61e-14 *** canopy_height 1.784464 0.301452 5.920 3.46e-09 *** Cloudfreq -13.289617 0.827024 -16.069 < 2e-16 *** Etpot 2.020002 0.194859 10.366 < 2e-16 *** MeanDiurnalTemp -13.887343 1.684180 -8.246 < 2e-16 *** MeanTemp -12.566067 1.934673 -6.495 9.15e-11 *** MeanTempColdQuart 13.655318 1.333757 10.238 < 2e-16 *** MeanTempWarmQuart -13.074458 1.863120 -7.018 2.58e-12 *** MinTempColder 5.256989 0.388219 13.541 < 2e-16 *** sd_mnt_250 13.455367 1.495951 8.995 < 2e-16 *** PrecSeas 1.086712 0.125684 8.646 < 2e-16 *** PrecWetMonth 0.394470 0.059784 6.598 4.62e-11 *** TempSeas 40.462190 3.906850 10.357 < 2e-16 *** Residual standard error: 52.25 on 4714 degrees of freedom Multiple R-squared: 0.9566, Adjusted R-squared: 0.9565 F-statistic: 7420 on 14 and 4714 DF, p-value: < 2.2e-16

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Appendix (2)

Coefficients:

Estimate Std. Error t value Pr(>|t|) AGB_Saatchi 0.755471 0.007856 96.170 < 2e-16 *** AnnualPrec 0.036648 0.005530 6.627 3.82e-11 *** canopy_height 1.914872 0.288046 6.648 3.31e-11 *** Cloudfreq -9.394081 0.804335 -11.679 < 2e-16 *** Etpot 1.757288 0.179243 9.804 < 2e-16 *** MaxTempWarmer 8.150076 0.503092 16.200 < 2e-16 *** MeanDiurnalTemp -18.935275 1.550417 -12.213 < 2e-16 *** MeanTemp -9.578816 2.087599 -4.588 4.58e-06 *** MeanTempColdQuart 13.953890 1.320395 10.568 < 2e-16 *** MeanTempWarmQuart -18.727840 2.125655 -8.810 < 2e-16 *** sd_mnt_250 14.437967 1.531020 9.430 < 2e-16 *** Ndrymonths -10.277298 1.644364 -6.250 4.47e-10 *** PrecDrierMonth -0.546279 0.082910 -6.589 4.92e-11 *** TempSeas 26.834582 3.505660 7.655 2.34e-14 *** Residual standard error: 52.65 on 4714 degrees of freedom Multiple R-squared: 0.9559, Adjusted R-squared: 0.9558 F-statistic: 7302 on 14 and 4714 DF, p-value: < 2.2e-16