• Aucun résultat trouvé

Economics of species change under risk of climate change and increasing information : a (Quasi-)Option value analysis

N/A
N/A
Protected

Academic year: 2021

Partager "Economics of species change under risk of climate change and increasing information : a (Quasi-)Option value analysis"

Copied!
12
0
0

Texte intégral

(1)

HAL Id: hal-01000307

https://hal.archives-ouvertes.fr/hal-01000307

Submitted on 5 Jun 2020

HAL is a multi-disciplinary open access

archive for the deposit and dissemination of

sci-entific research documents, whether they are

pub-lished or not. The documents may come from

teaching and research institutions in France or

abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est

destinée au dépôt et à la diffusion de documents

scientifiques de niveau recherche, publiés ou non,

émanant des établissements d’enseignement et de

recherche français ou étrangers, des laboratoires

publics ou privés.

Economics of species change under risk of climate

change and increasing information : a (Quasi-)Option

value analysis

Marielle Brunette, Sandrine Costa, Franck Lecocq

To cite this version:

Marielle Brunette, Sandrine Costa, Franck Lecocq. Economics of species change under risk of climate

change and increasing information : a (Quasi-)Option value analysis. Tackling climate change : the

contribution of forest scientific knowledge, Groupement d’Intérêt Public ”Ecosystèmes Forestiers”

(GIP ECOFOR). Paris, FRA., May 2012, Tours, France. 11 diapositives. �hal-01000307�

(2)

Economics of Species Change under Risk of Climate

Change and Increasing Information: A (Quasi-)Option Value

Analysis

Marielle Brunette (LEF, Nancy) Sandrine Costa (MOISA, Montpellier)

and Franck Lecocq (CIRED, Paris)

“Tackling climate change: the contribution of forest scientific knowledge”, Tours,

(3)

Context

• Impact of climate change on :

Forest Ecosystems

- Increase temperature from 1.5˚C to 5˚C

- More intense precipitations during winter and longer droughts during summer

- Impact on phenology and reproduction of trees, on growth, on prevalence of risks

Forest Species

- Scots Pine (Kint et al., 2009)

- Norway Spruce (Briceno-Elizondo et al., 2006)

- Oak (Becker et al., 1994)

- European Beech (Nigh, 2006)

• Characteristics of forest sector : long-term and irreversible decisions.

• One solution to adapt forest to CC : shifts to climatically more robust species → Studied from a biophysical point of view but economic assessment are scarce : Hanewinkel et al. (2010), Yousefpour et al. (2010).

→ No consideration of : 1/ uncertainty about impact of CC on forest ecosystem ; 2/ increasing information

(4)

Objective

• Objective : to study the question of species choice in the context of climate change taking into account uncertainty about impact of CC on forest ecosystem and increasing information

• Methodology : Cost-Benefit Analysis + Quasi-option value (Arrow and Fisher (1974), Henry (1974))

− Benefit to get information earlier, with implications both for private decision-making and public policies

− Mitigation decisions on climate change

− Forestry : management decisions under timber price volatility

• Framework : conversion of Norway spruce stands to Douglas-fir.

• Results : conditions under which species shifts make sense, optimal timing of species shifts, value of additional information.

(5)

The Case study

• Norway spruce (NS) : commonplace in Europe, resistant to cold, not very sensitive to last frosts, sensitive to water stress and droughts.

• Adaptation strategies :

- uneven-aged system

- conversion towards tree species more adaptated to future climatic condition : European beech in German Black Forest, Scots Pine in Northern Finland, Douglas-fir in French Black Mountain.

⇒ We explore the economics of replacing NS with Douglas-fir in the context of the French Black Mountain

• Assumptions : monospecific, even-aged NS stand that has just been clear-cut, and in which natural regeneration is present.

- Continuation of past practices would call for a new cycle of NS based on regeneration

- An alternative sylvicultural trajectory would be to clear the stand and plant Douglas-fir.

• Two scenarios regarding the impact of CC on NS : either there is a high mortality of NS (with probability p) over the next spruce rotation (70 years) or there is not (with (1 − p))

• Increasing information : uncertainty on the CC effects on NS will be resolved in n years (n = 5 or n = 10)

,→we assume that in one century, NS will not be adaptated to the stand anymore (it will be necessary to shift to Douglas-fir for the secodn rotation).

(6)

Immediate choice

Strategy 1: regenerating NS now with view to shifting to Douglas-fir after end of

rotation

Strategy 2: planting Douglas-fir now with natural regeneration of Douglas-fir in

subsequent rotation

A. Analysis of strategy 2

Benefit (e/ha)

Operations (years) Plantation Natural regeneration

Initial cost Plantation(0) : -2132 Clearing(3) : -1212

Thinning (14) “d ´epressage” -920 -1170 Thinning (24) 885 885 Thinning (37) 1305 1305 Thinning (51) 2989 2989 Thinning (68) 10584 10584 Thinning (71) 5170 5170 Harvest (74) 18315 18315

Net Present Value NPV(DF,plant) = 452 NPV(DF,rege) = 1362

• Douglas-fir is assumed suited both to current and future climate, so that the yields and financial payoffs of strategy 2 are independent of the NS mortality scenario.

• Discount rate : 4%

• LEV (DF ) = NPV (DF , plant) +NPV (DF ,rege)

(1+r )74 ×

(1+r )74

(7)

Strategy 1 with and without CC

B. Analysis of strategy 1 without CC

Operations (years) Benefit (e/ha)

Clearing (0) -597 Thinning (20) “d ´epressage” -1023 Thinning (40) 1242 Thinning (50) 1518 Thinning (60) 2139 Harvest (70) 19417

Net Present Value NPV(NS) = 859

• LEV (NS) = NPV (NS) +LEV (DF )(1+r )70 =888e/ha

• LEV (NS) > LEV (DF ) → without CC, the best strategy would be to keep NS for one more rotation and then after to change to DF.

C. Analysis of strategy 1 with CC

n

Shift to Douglas-fir at n 1 revolution of Norway spruce and shift to Douglas-fir after final harvest

Shift to Douglas-fir now Strategy 2

Strategy 1

p

1-p

Information available on Norway Spruce’future mortality rate

- LEV (Strat1) = p(−597 +LEV (DF )−100

(1+r )n ) + (1 −

p)(NPV (NS) +LEV (DF )

(1+r )70)

- For n = 5, if p < 31.9% then it is better to regenerate NS

- For n = 10, if p < 30.2%, then it is better to regenerate NS

(8)

Sequential decision making

Strategy 3: choice between regenerating NS and planting DF is delayed until the

information about p is provided.

• Assumptions concerning this waiting period : no investment, thicker vegetation establishes

- Clearing cost of NS regeneration = 800e/ha for n = 5 and 900e/ha for n = 10 ,→NPV(NS, delay = 5) = 702e/ha ; NPV(NS, delay = 10) = 655e/ha

- Clearing cost before DF plantation increases of 100e/ha.

• Strategy tree becomes :

Strategy 2 Strategy 3 p 1-p p 1-p Information available on Norway spruce’ future mortality rate Strategy 1

Shift to Douglas-fir now Shift to Douglas-fir at n

Shift to Douglas-fir at n 1 rotation of Norway Spruce and shift to Douglas-fir after final harvest

Clearing for Norway Spruce at n. 1 rotation of Norway Spruce and shift to Douglas-fir after final harvest n LEV (Strat3) =p(LEV (DF )−100 (1+r )n ) +(1 − p)(NPV (NS, delay = n) +LEV (DF ) (1+r )70)

(9)

Comparison of the 3 strategies for n=5

Figure 3. Value of the “Delay” scenario (for n = 5) relative to the best scenario among spruce regeneration and planting Douglas-fir.

-400 -200 0 200 400 600 800 1000 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Probability of high mortality

/h a LEV(Strat 1) LEV(Strat 2) LEV(Strat 3)

• for n = 5 : p < 20.8% = strategy 1 ; for n = 10 : p < 25.4% = strategy 1

• for n = 5 : 20.8% < p < 53.8% = strategy 3 ; for n = 10 : p < 39.9% = strategy 3

• for n = 5 : p > 53.8% = strategy 2 ; for n = 10 : p > 39.9% = strategy 2

(10)

Quasi-option value

QOV is a way to measure the benefit of flexibility in an uncertain context : QOV = LEV (Strat3) − Max (LEV (Strat1), LEV (Strat2)).

,→positive QOV means that it is profitable to delay the decision

Figure 4. Quasi Option Value.

-250 -200 -150 -100 -50 0 50 100 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Probability of high mortality

Q

O

V information in 10 years

information in 5 years

(11)

Expected Value of Earlier Information (EVEI)

EVEI = Max (LEV5(Strat1), LEV5(Strat2), LEV5(Strat3)) −

Max (LEV10(Strat1), LEV10(Strat2), LEV10(Strat3))

Figure 6. Expected Value of Earlier Information.

0 10 20 30 40 50 60 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Probability of high mortality EVEI

• p ≤ 0.2 (low probabilities) : lower value of earlier information (< 12e/ha).

• p ≥ 0.6 (high probabilities) : lower value of earlier information (< 12e/ha).

• 0.2 < p < 0.6 (in-between probabilities) : higher value of earlier information comes from strategy 3 which is the best strategy for these intermediate probabilities ( 12e/ha < EVEI < 52e/ha).

⇒ EVEI is low for low or high probabilities ; in-between, EVEI is between around 10 and 50e/ha, it increases the LEV by 2 to 9%.

(12)

Conclusion

• QOV approach may be very useful to analyse decision making in species choice

• Summary of the results :

- without CC Strategy 1 dominates

- with CC, the dominating strategy depends on p, the probability of high mortality of NS ,→if the probability is low or high, it is more profitable to choose now

,→for intermediate value of the probability, it is more profitable to delay

• Value of information belongs to the interval [6-52]e/ha in our case study

• Some limits : DF is not perfectly adaptated to CC, delay of 5 or 10 years seem to be optimistic

Figure

Figure 3. Value of the “Delay” scenario (for n = 5) relative to the best scenario among  spruce regeneration and planting Douglas-fir
Figure 4. Quasi Option Value.
Figure 6. Expected Value of Earlier Information.

Références

Documents relatifs

Two genes, ODC and TRYR, showed a signi ficantly different change in expression level (slope of the expression curve) between the 2 groups of in vitro Sb V -S and Sb V -R

Second, in the current study, the tegument of female worms was slightly more affected and females died more rapidly when compared to male worms, in particular following in vitro

The first trial was initiated in the United States by the Gastrointestinal Tumor Study Group (GITSG) in 1974 [23], which was slow to accrue and was terminated early following

The last and single autopsy case of proven classic analgesic nephropathy, detected only with the present sophisti- cated histological study at the end of the year 2000, can thus

B-measure for the Model described in Subsection ( 3.1 ) with initial temperature equal to 15 ◦ C for the minimal temperature and 22 ◦ C for maximum temperature and maturity time

4: Average model checking results for rewards related to good answers, bad answers, non-interaction, and game leaving behavior.. In Figure 4, the rewards for good answers, bad

The main goal of this study is to evaluate the primary pro- ductivity of two contrasting years associated with La Ni˜na and El Ni˜no events in low and midland areas of

international initiatives such as the Global Observation for Forest Cover and land Dynamics (GOFC-GOlD) and the Global Forest Observations initiative (GFOi) of the Group on