florian c forests and livelihoods : assessment, research

Improved forestmanagement inCentral African

concessions

Florian CLAEYS

ContextCentral Africa and climatechange

Forestry and adaptation

MethodologyDatasets

Model

Feasibility study

ResultsForest and climate

Carbon stock change

Harvest profiles

Carbon BEP

Conclusion

Références

Financing improved forest management by carbonvaluation, a bioeconomic modelling approach applied to

Central African concessions

Florian CLAEYS

Forests and Livelihoods : Assessment, Research andEngagement (FLARE)

Musée de l’Homme, ParisNovember 28th, 2015

Improved forest management in Central African concessions 0 / 15


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MethodologyDatasets

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Summary

ContextCentral Africa, a climate change hotspotForestry and adaptation in Central Africa

MethodologyForest inventory and climate time seriesForest dynamics modelFeasibility study of IFM projects

ResultsForest dynamics and climate changeCarbon stock changeHarvest profilesCarbon BEP

Conclusion



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MethodologyDatasets

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Central Africa, a climate change hotspotI Extreme seasonal temperature and precipitation (Diffenbaugh

and Giorgi 2012)

The occurrence of the 1986-2005 maximum JJA seasonal temperature in the 2016-2035, 2046-2065 and2080-2099 periods of RCP4.5 (left) and RCP8.5 (right). The panels show the absolute occurrences as thepercent of years in each 20-year period. The frequency of occurrence of the 1986-2005 maximum JJAseasonal temperature value is, by definition, 5 % at each grid point during the 20-year 1986-2005 period.



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Forestry and adaptation in Central Africa

I Great emphasis on mitigation, with REDD+ (Bele et al. 2011,

Somorin et al. 2012)

I Climate change adaptationI Hydrology and energy : wetter wet seasons, drier dry seasons

(Beyene et al. 2014, Faramarzi et al. 2013)I Agriculture : reduction of yields and productivities (Dinar et al. 2012,

Knox et al. 2012)

I Rise of forest adaptation issuesI Research projects by GIZ, CIFOR and CIRAD (Sonwa et al. 2014)I Integration of adaptation in REDD+ (Elias et al. 2014)

I Which prospects for Improved forest management (IFM) ?I Voluntary change of logging practices (Griscom and Cortez 2013)I Carbon credits valued through voluntary markets (Goldstein et al. 2014)I Carbon-based compensatory approach (Karsenty et al. 2012)I Case of Central African forest concessionaire (Bayol et al. 2012; 2014)



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MethodologyDatasets

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M’Baïki dataset

M’Baïki dataset (Bedel et al. 1998)

I Central AfricanRepublic (CAR)

I 6×4 ha : BoukokoI 4×4 ha : La Lolé

I 30 yrs long monitoring1982-2012

I 239 speciesI 37 539 treesI 639 815 measures

I 3 treatments

I ControlI LoggingI Logging and thinning



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Climate dataset

I Simulation data

I Atmospheric model CMIP5-CNRM (Voldoire et al. 2013)

I 2 RCP (Representative Concentration Pathways)

I RCP 4.5 and RCP 8.5



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Forest dynamics model

I Usher matrix model (Usher 1966; 1969)

I Issue of sample size (Picard et al. 2008)

I Species clustering into groups (Gourlet-Fleury et al. 2005)

I 3 processesI GrowthI DeathI Recruitment

I Variables selection for each group (Monni and Tadesse 2009)

I 9 variablesI 2 diameter variablesI 2 competition indicesI 5 climate variables



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Logging company model

UML simplified representationForest resources

SpeciesDiametersQualityCarbon

Logging choices

Commercial speciesFCDMCD

22 ; 25 yrs ; 80 cm

Standing timber

Surface

100 000 ha

Cutting

CapacityYield

8 000 tr.yr−1 ; 100 %

Logyard

Sawmill

CapacityYield

70.103 m3.yr−1 ; 30 %

Outputs yard

Kilns

CapacityYield

6.103 m3.yr−1 ; 90 %

Export yard

Timber revenue



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MethodologyDatasets

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Feasibility study of IFM projectsI Simulation over 2012-2100

I M’Baïki 2012 control average standI Modelled steady stateI Current climate, RCP 4.5, RCP 8.5

I "Extension of rotation age" (ERA) projects (VCS 2013)

I Alternative logging scenarioI Felling cycle duration (FCD) : [25 ;50] yrsI Minimum cutting diameter (MCD) : [80 ;120] cm

I Baseline : {25 yrs;80 cm} ; 2 trees.ha−1.yr−1

I Break-even analysisI Net present value (NPV)

I Shortfalls from reduced timber loggingI Revenu from carbon credit sales

I Calculations assumptionsI Net margin : 10 %I Buffer rate : 20 %I Discount rate : sensitivity analysis



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Forest dynamics and climate change

Mortality rate Recruitment rate

I High dependence between forest dynamics and climateI Temperature more influential than rainfalls

I High impact of climate change : severe thinning

I Acceleration of transformation from 2030



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Carbon projections to 2100

Time variation of carbon gain for several alternative scenarios to the baseline logging scenario (intCO2

.ha−1), under several RCP.

I Increased carbon stocks with climate change :I CO2 fertilization (Lewis et al. 2009)

I Opposite effects between logging and climate change

I Different temporalities in FCD and MCD effects



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Harvest projections to 2100

Current climate RCP 4.5 RCP 8.5

I Step-like reduction of timber incomeI Primary forest premium (Putz et al. 2012)

I No logging scenario is exception to thisI Unsustainability of management plans (Zimmerman and Kormos 2012)

I No economic effect of climate changeI Discrepancy between impacts on forest stands and logger’s

perceptionI Urgent need for adapted incentives or rules



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MethodologyDatasets

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Carbon break-even price

BEP (in e.t−1CO2

) depending FCD and MCD Discount rate sensitivity.

I Feasibility of ERA projectsI Forest carbon as a cheap mitigation option (Grieg Gran 2006; 2008)I True for primary forests (non-restrictive management rules)

I Major issues of acceptability and perennialityI Mismatch between public and private interestsI Increased expensiveness for further logged forests



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ConclusionI Key messages

I Two major challenges for Central African productionforests

I Climate change : adaptation and mitigationI Timber production in the long run

I Weaknesses of current logging practicesI Unsustainability of a mining-like harvestingI Insensitivity to climate change impacts on forest stands

I Potential of a carbon-based compensatory approachI Short-term : feasible in some limited casesI Long-term : not a solution

I ProspectsI Improve the realism of model

I Dynamic model of logger’s choicesI Broaden the scope of study

I Other climate modelsI Company heterogeneityI Other IFM projects : post-logging silviculture



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References IN. Bayol, B. Demarquez, C. de Wasseige, R. Eba’a Atyi, J.-F. Fisher, R. Nasi, A. Pasquier, X. Rossi,

M. Steil, and C. Vivien. Forest management and the timber sector in Central Africa. In C. DeWasseige, P. De Marcken, N. Bayol, F. Hiol Hiol, P. Mayaux, B. Desclée, R. Nasi, A. Billand,P. Defourny, and R. Eba’a Atyi, editors, The Forests of the Congo Basin–State of the Forest 2010,pages 43–61. Publication Office of the European Union, 2012.

N. Bayol, F. Anquetil, C. Bile, A. Bollen, M. Bousuqet, B. Castadot, P. Cerutti, J. Avit Kougape, M. Leblanc,H. Lescuyer, Q. Meunier, E. Melet, A. Penelon, V. Robligio, R. Tsanga, and C. Vautrin. Filières boisd’œuvre et gestion des forêts naturelles : les bois tropicaux et les forêts d’Afrique centrale face auxévolutions des marchés. In C. De Wasseige, D. Louppe, F. John, K. Heiner, B. Bedoret, D. deBeauffort, and C. Halleux, editors, Les forêts du Bassin du Congo - État des Forêts 2013, pages47–66. Weyrich Édition, Weyrich, Belgique, 2014.

F. Bedel, L. Durrieu de Madron, B. Dupuy, V. Favrichon, V. Maître, A. Bar-Hen, and P. Narboni.Dynamique de croissance dans des peuplements exploités et éclaircis de forêt dense africaine : ledispositif de M’Baïki en République Centrafricaine (1982-1995), volume 1 of Série FORAFRI.CIRAD Forêt, Montpellier, France, 1998.

M. Y. Bele, O. Somorin, D. J. Sonwa, J. N. Nkem, and B. Locatelli. Forests and climate change adaptationpolicies in cameroon. Mitigation and Adaptation Strategies for Global Change, 16(3) :369–385, 2011.

T. Beyene, F. Ludwig, and W. Franssen. The potential consequences of climate change in the hydrologyregime of the Congo River Basin. In A. Häensler, D. Jacob, P. Kabat, and F. Ludwig, editors, ClimateChange Scenarios for the Congo Basin, volume 11. Climate Service Centre Report, Hamburg,Germany, 2014.

N. S. Diffenbaugh and F. Giorgi. Climate change hotspots in the CMIP5 global climate model ensemble.Climatic change, 114 :813–822, 2012.

A. Dinar, R. Hassan, R. Mendelsohn, J. Benhin, et al. Climate change and agriculture in Africa : impactassessment and adaptation strategies. Routledge, 2012.

M. Faramarzi, K. C. Abbaspour, S. A. Vaghefi, M. R. Farzaneh, A. J. Zehnder, R. Srinivasan, and H. Yang.Modeling impacts of climate change on freshwater availability in africa. Journal of hydrology, 480 :85–101, 2013.



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References IIA. Goldstein, G. Gonzalez, and M. Peters-Stanley. Turning over a New Leaf : State of the Forest Carbon

Markets 2014. Forest Trends’ Ecosystem Marketplace, 2014.

S. Gourlet-Fleury, L. Blanc, N. Picard, P. Sist, J. Dick, R. Nasi, M. Swaine, and E. Forni. Groupingspecies for predicting mixed tropical forest dynamics : looking for a strategy. Annals of forest science,62(8) :785–796, 2005.

M. Grieg Gran. The Cost of Avoiding Deforestation : Report prepared for the Stern Review of theEconomics of Climate Change. International Institute for Environment and Development, London,United Kingdom, 2006.

M. Grieg Gran. The Cost of Avoiding Deforestation : Update of the report prepared for the Stern Reviewof the Economics of Climate Change. International Institute for Environment and Development,London, United Kingdom, 2008.

B. W. Griscom and R. Cortez. The case for improved forest management (IFM) as a priority REDD+strategy in the tropics. Tropical Conservation Science, 6(3), 2013.

A. Karsenty, N. Tulyasuwan, Global Witness, and D. Ezzine de Blas. Financing options to support REDD+activities. CIRAD, Montpellier, 2012. Report for the European Commission DG Climate Action.

J. Knox, T. Hess, A. Daccache, and T. Wheeler. Climate change impacts on crop productivity in Africaand South Asia. Environmental Research Letters, 7(3) :034032, 2012.

S. L. Lewis, G. Lopez-Gonzalez, B. Sonke, K. Affum-Baffoe, T. R. Baker, L. O. Ojo, O. L. Phillips, J. M.Reitsma, L. White, J. A. Comiskey, M.-N. D. K, C. E. N. Ewango, T. R. Feldpausch, A. C. Hamilton,M. Gloor, T. Hart, A. Hladik, J. Lloyd, J. C. Lovett, J.-R. Makana, Y. Malhi, F. M. Mbago, H. J.Ndangalasi, J. Peacock, K. S.-H. Peh, D. Sheil, T. Sunderland, M. D. Swaine, J. Taplin, D. Taylor, S. C.Thomas, R. Votere, and H. Woll. Increasing carbon storage in intact african tropical forests. Nature,457(7232) :1003–1006, 2009.

S. Monni and M. G. Tadesse. A stochastic partitioning method to associate high-dimensional responsesand covariates. Bayesian Analysis, 4(3) :413–436, 2009.

N. Picard, F. Mortier, and P. Chagneau. Influence of estimators of the vital rates in the stock recovery ratewhen using matrix models for tropical rainforests. Ecological Modelling, 214(2) :349–360, 2008.



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References IIIF. Putz, P. Zuidema, T. Synnott, M. Peña-Claros, M. Pinard, D. Sheil, J. Vanclay, P. Sist, S. Gourlet-Fleury,

B. Griscom, J. Palmer, and R. Zagt. Sustaining conservation values in selectively logged tropicalforests : the attained and the attainable. Conservation Letters, 5(4) :296–303, 2012.

O. A. Somorin, H. C. P. Brown, I. J. Visseren-Hamakers, D. J. Sonwa, B. Arts, and J. Nkem. The congobasin forests in a changing climate : policy discourses on adaptation and mitigation (REDD+). GlobalEnvironmental Change, 22(1) :288–298, 2012.

D. J. Sonwa, P. Scholte, W. Pokam, P. Schauerte, M. Tsalefac, C. Bouka Biona, C. Peach Brown,A. Haensler, F. Ludwig, F. K. Mkankam, A. Mosnier, W. Moufouma-Okia, F. Ngana, and A.-M. Tiani.Climate change and adaptation in Central Africa : past, scenarios and options for the future. In C. DeWasseige, D. Louppe, F. John, K. Heiner, B. Bedoret, D. de Beauffort, and C. Halleux, editors, Lesforêts du Bassin du Congo - État des Forêts 2013, pages 99–119. Weyrich Édition, Weyrich,Belgique, 2014.

M. Usher. A matrix approach to the management of renewable resources, with special reference toselection forests. Journal of Applied Ecology, pages 355–367, 1966.

M. Usher. A matrix model for forest management. Biometrics, pages 309–315, 1969.

VCS. Agriculture, Forestry and Other Land Use ( AFOLU) Requirements – VCS Version 3 RequirementsDocument 8 October 2013, v3.4. Verified Carbon Standard, 2013.

B. L. Zimmerman and C. F. Kormos. Prospects for sustainable logging in tropical forests. BioScience, 62(5) :479–487, 2012.

P. Elias, S. Leonard, L. Cando, G. Fedele, D. Gaveau, B. Locatelli, C. Martius, D. Murdiyarso,W. Sunderlin, and L. Verchot. Synergies across a REDD+ landscape : Non-carbon benefits, jointmitigation and adaptation, and an analysis of submissions to the SBSTA. CIFOR Infobrief, 71, 2014.

A. Voldoire, E. Sanchez-Gomez, D. Salas y Mélia, B. Decharme, C. Cassou, S. Sénési, S. Valcke,I. Beau, A. Alias, M. Chevallier, M. Déqué, J. Deshayes, H. Douville, E. Fernandez, G. Madec,E. Maisonnave, M.-P. Moine, S. Planton, D. Saint-Martin, S. Szopa, S. Tyteca, R. Alkama,S. Belamari, A. Braun, L. Coquart, and F. Chauvin. The CNRM-CM5.1 global climate model :description and basic evaluation. Climate Dynamics, 40(9-10) :2091–2121, 2013. ISSN 0930-7575.



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Acronyms IBEP break-even priceCAR Central African Republic

CIFOR Centre for International Forestry ResearchCMIP5 Coupled Model Intercomparison Project Phase 5CIRAD Centre for International Cooperation in Agricultural Research for Development

(Centre de coopération internationale en recherche agronomique pour ledéveloppement, Montpellier, France)

CNRM French National Centre for Meteorological Research (Centre national derecherches météorologiques, Toulouse, France)

ERA "Extension of rotation age/cutting cycle"ERA "Extension of rotation age"FCD felling cycle duration

FLARE Forests and Livelihoods : Assessment, Research and EngagementGIZ Deutsche Gesellschasft für Internationale Zusammenarbeit Société allemande de

coopération internationaleIFM Improved forest managementJJA June-July-August

MCD minimum cutting diameterNPV net present valueRCP Representative Concentration Pathway

REDD+ "Reducing emissions from deforestation and forest degradation and the role ofconservation, sustainable management of forests and enhancement of forestcarbon stocks in developing countries"

SBSTA Subsidiary Body for Scientific and Technological AdviceUML Unified Modeling LanguageVCS Verified Carbon Standard



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MethodologyDatasets

Model

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Harvest profiles

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Conclusion

Références

Financing improved forest management by carbonvaluation, a bioeconomic modelling approach applied to

Central African concessions

Florian CLAEYS

Forests and Livelihoods : Assessment, Research andEngagement (FLARE)

Musée de l’Homme, ParisNovember 28th, 2015


florian c forests and livelihoods : assessment, research

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