1. CLIMATE 2050
Montréal, 24-26 October, 2007
The contribution of forestry in
maintaining and expanding forestbased carbon sinks
Markku Kanninen, Robert Nasi, CIFOR
Alain Karsenty, CIRAD
1

2. 2

3. Why conserve tropical forests?
3

4. Changes, threats, risks
4

5. Forests and carbon sinks
► Contribution to carbon sinks
 Planting ‘new’ forests (A/R CDM)
 Avoiding deforestation (conserving forests)
► Contribution to GHG emissions
 Deforestation is responsible for 18 to 25% of
GHG annual emissions
 Bio-energy
5

6. Trends
► During
the last 40 years
 Deforestation: 500 M Ha
 Consumption of forest products: 50% increase
► During the next 40 years



►
Over 100 M Ha of new agricultural land needed
Consumption of forest products: 50% increase
40-50% of industrial wood from plantations
does not consider the issues related to biofuels
6

7. 7

8. The Clean Development Mechanism (CDM)
►
►
A PES scheme for reducing emissions through project
activities in developing countries
General rules of CDM: boundaries, baseline, additionality
and leakage
► Additionality: demonstrate that the project would not have been
undertaken without the incentive of carbon credits  industrial
plantation projects systematically rejected by CDM Executive Board
► Leakage: demonstrate the project will nor result in displacement of
the emissions elsewhere
►
Afforestation/Reforestation (A/R) projects



Addressing non permanence (temporary credits)
Human-induced activities only: no project in degraded forest
Ineligible if the land was covered by forest after 31/12/1989
8

9. Forestry CDM: a failure?
One registered project and a few more in the pipe
9

10. The difficulties faced by forestry CDM
 No real demand for temporary credits in a
context of relative oversupply of permanent
credits;
 EC do not allow European companies to use A/R credits to
fulfill their objectives of emission reductions
 In most tropical countries, difficulties to secure
land for plantations due to:
 land tenure issues,
 the bureaucratic process and low efficiency of the
administration,
 the poor governance and ill-functioning justice institutions
 Transaction costs are high, too high for small and
community-based projects
10

11. from Azevedo 2007
11

12. Avoided Deforestation (RED, REDD)
► Generic expression for RED (Reduction of
Emissions from Deforestation) or REDD (the 2nd
D initially for Developing countries but used now
for Degradation)
► To curb down deforestation – and biodiversity
loss- by rewarding good land use and forestry
practices (e.g. promotion of sustainable
forestry…)
► Reward will be through carbon credits (Kyoto
assets) or money equivalent (special fund?)
12

13. RED/REDD
► A mechanism proposed by PNG, Brazil and
others (e.g. Congo Basin’s countries), but with
different features
► The bottom line: financial rewards for countries
reducing their deforestation rates
► Major difficulties:



How to choose and set up baselines?
How to take into account degradation?
As a Kyoto (fungible credits, second commitment
period 2013-2017) or independent (special credits or
money) instrument?
13

14. Assessing deforestation
► Monitoring deforestation is difficult, but not
impossible
► The crux is about agreeing on the reference
baseline
 Most proposals suggest deriving the baseline from an
average of past trends of deforestation
 Others (e.g. Congo Basin countries) claim for an
adjustment factor allowing them to increase their future
deforestation while keeping a possibility to be rewarded
 Others (researchers) would prefer predictive baselines
based on anticipated rates of deforestation by country
14

15. Historical reference: winners and losers
►
Indonesia or Malaysia had high rates of deforestation in
the 80 and 90’s; forest tends now to concentrate on less
accessible lands: deforestation expected slow down for
‘mechanical’ reasons
 Future reductions likely to be non additional
 Would it be ‘fair’ to reward Indonesia and Malaysia with regard
to their policies vis-à-vis the forest in the past decades?
►
Peru, Bolivia, Congo Basin are likely to be the losers
under such baseline reference and claim for adjusting
the reference to anticipated trends of deforestation
15

16. Can we predict deforestation rates?
►
►
A possible solution would be to forecast a likely
“business as usual” deforestation rate
Chomitz et al. (2007) suggest modeling land-use
dynamics to calculate the baseline scenario.
 also pointing out correlations between deforestation rate in the
Amazon and beef price at farm gate or with rainfall…
►
(quite) predictable variables (e.g. population growth)
and (best educated) guesses:
 Speculative prices of major agriculture commodities, such as
soy, oil palm, beef…?
 Evolution of rainfall and the risk of forest fires in the context of
growing climate disorders?
16

17. Can governments do something?
► Most
factors influencing deforestation rates are
beyond the reach of governments (cash crop
commodities price changes, currency exchange
rates…)
► In complex systems, finding a direct plausible
causality link between public action and a number
hectares (not) deforested is very difficult (or
impossible?)
 Kaimowitz and Angelsen (1999) have shown the non consistent
effects of single variables (such as agricultural progress) on
deforestation
 If deforestation slows down, how to disentangle the effect of public
policies to the other factors insensitive of government action?
17

18. Exogenous factors
Type of measures
Non intentional
Endogenous
factors
Change in Agricultural
commodity prices
Changes in interest
rates
Extended climate
disorders
Cut in fertilizer
subsidies
Intentional
Endogenous
factors
Stringent enforcement
of land-use change
laws
Possibility to impute
the deforestation
reduction to the
public action
No
yes
yes
Possibility to quantify
the net impact on
deforestation
No
Very difficult
Possible
18

19. Carbon credits or what else?
►
Fears that AD would generate huge quantities of “hot air”
and a reduction of price of emission permits
► Recent report from CDM executive board suggests 20% of carbon
credits are “non additional”…
►
A possible alternative:
 De-coupling from Kyoto: money instead of carbon credits
through an international fund against deforestation
 Targeting, in priority, field actors instead of governments
 Using a range of PES to favor changes in farmers’ productive
practices and rewarding true conservation efforts (case by case
assessment)
 Working with governments to remove perverse incentives
(inappropriate subsidies, fiscal system…) and overcome
structural threats, such as land tenure insecurity, corruption,
justice…
19

20. Combining economic instruments and
law enforcement
►
►
Detecting forest infractions (by satellite) is less difficult
than enforcing law and effective sanctions…
How to avoid designing a scheme in which law compliers
will be at a disadvantage compared to violators?
 What conditions of eligibility?
 Setting differential regimes for compliers and non-compliers?
►
The minimum condition of success is strong signals of
political will to enforce the law: do we want to pay for
that?
 With the risk to be said : “ if you don’t pay I let my
forests being destroyed ”
►
The ultimate condition is (still) about choices and
behavior: forest are converted because it ‘pays’ to do so
(for cultivation, feeding beef, biofuels, paper…)
20

21. Conclusions – a way forward
► Synergies of C sequestration with other PES
schemes
► Diversified
rural economies and improved livelihoods
► CDM projects for biodiversity corridors
► Landscape level planning in watersheds
► Combine mitigation (C sequestration) measures
with adaptation to climate change
► CDM
projects to reduce vulnerability, minimize risks (forest
fires, flooding, etc.) or increase resilience of ecosystems
► Joint CDM / AD projects
► Promoting
sustainable forestry
21

22. Promoting sustainable forestry
► CDM for afforestation and reforestation



Gain experience in good management
Develop forest-based rural enterprises
Role of planted forests will increase in the future
in timber supply
► Avoided deforestation



High potential post 2012
Reduce emission and conserve biodiversity
Improve forestry practices and management
22

23. Thank you
23