1. Ecosystems (Socio-economics) Estimating the Impact of Climate Change on Landscape Value Aliza Fleischer 1, Denise Fouks 1 and Marcelo Sterenberg 2 1 Hebrew University of Jerusalem 2 Tel Aviv University GLOWA – Jordan River

2. Ecosystems (Socio-economics) Objective Evaluating the impact of climate change on the economic value of different natural landscape with an emphasis on the Galilee

3. Ecosystems (Socio-economics) Economic Impact of Global Climate Change on Grazing Land Economic Impact Landscape value Recreationalists’ welfare Grazing services Farmer’s income Ecosystem services Local population welfare

4. Ecosystems (Socio-economics) Topography South-facing slopes with stony and shallow soil (Terra rossa to desert lithosol on hard limestone and chalk) Temperature Mean annual temperature 14 0 C-23 0 C Rainfall Mainly winter - 5 summer months with no rainfall Range North-South: 780 to 90 mm ~ 480 km Humid Mediterranean - 780 mm Mediterranean - 540 mm Semiarid – 300 mm Arid – 90 mm The Climatic Gradient עין יעקב מטע להב שדה בוקר

5. Ecosystems (Socio-economics) Herbaceous biomass (ton Ha -1 ) Elevation (a.s.l) Temperature ( o C) Min. – Mean - Max. Rainfall (mm) Ecosystem type 0.832500 m13.5 - 18.1 - 23.4780Mesic Mediterranean (N 33 o 0' E 35 o 14') 0.741620 m12.8 – 17.7 - 23.6540Mediterranean (N 31 o 42' E 35 o 3') 0.576590 m13.2 – 18.4 – 24.8300Semiarid (N 31 o 23' E 34 o 54') 0.014470 m13.6 - 19.1 - 26.190Arid (N 30 o 52' E 34 o 46')

6. Ecosystems (Socio-economics) Methodology A stated preference survey was designed to ask respondents to choose their preferable program to reduce the ecological impacts from 5 sets of five programs. The alternative that has been chosen represent the maximum utility for the respondent. Let Uij be the utility for the i th individual from alternative j. X= attribute [1,k] β= coefficient of the attribute = random error term i.i.d

7. Ecosystems (Socio-economics) a Plan 5 Drastic reduction of the use of damaging materials and fuels Plan 4 Increased forestry & less use of harmful materials and fuels. Plan 3 Reduction of the use of damaging materials and fuels Plan 2 Forestry and Plant life development. Plan 1 No Action The landscape in the Galilee will not change. The landscape in the Galilee will have less plant life. The landscape in the Galilee will become semiarid and dry. The landscape in the Galilee will become dry and arid, also lost of plants life will occur. 80 NIS per household monthly. 60 NIS per household monthly. 30 NIS per household monthly. 0 NIS per household monthly.

8. Ecosystems (Socio-economics) Multinomial Logit Model The utility an individual gets from alternative j is: This probability an individual will choose this alternative is: In the Multi Logit Model (MNL) the probability is:

9. Ecosystems (Socio-economics) The IIA Assumption The MNL is subject to the independence of irrelevant alternatives (IIA) property. IIA= the odds ratios are independent of the other probabilities. IIA test = if an alternative is irrelevant omitting it from the model will not change parameter estimates systematically. We rejected the hypothesis and thus had to use a model not subjected to IIA.

10. Ecosystems (Socio-economics) Random Parameters Logit Model The utility function associated with the model is from the general form : is a random term with zero mean iid over alternatives and does not depend on parameters or data.

11. Ecosystems (Socio-economics) Random Parameters Logit Model In the RPL model the probability of choice can be simulated as: This model is not subjected to the IIA.

12. Ecosystems (Socio-economics) Alternatives Description Each alternative contains all four attributes. Alternatives differ in the levels of attributes. Levels UsedAttributes 4 levels; Ein ya’ako’v, Matta, Lahav, Sde boqer In biomass units Landscape Changes (measured in landscape pictures) 2 levels; Utilized or Not Utilized Forestry 3 levels; None, Limited, Vigorous Abatement 14 levels; 0, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200 Program Cost (measured in NIS per month)

13. Ecosystems (Socio-economics) Econometric Analysis - Specification The indirect utility function V is specified as linear in parameters. “Price” enters linearly. One dummy variable for “forestry”, two for “abatement” (in this estimation we only used one due to singularity) and three dummy variable for “landscape changes” The indirect utility function would look as follow:

14. Ecosystems (Socio-economics) Econometric Results Biomass *** significant at 1% ** significant at 5% * significant at 10% VariableParameterValueStd. Error CostMean of coefficient-0.033*0.008 Std. dev. of coefficient00 Biomass lossMean of coefficient-0.069*0.018 Std. dev. of coefficient0.260*0.081 ForestationMean of coefficient-0.2210.194 Std. dev. of coefficient2.507*0.223 ReductionMean of coefficient1.664*0.794 Std. dev. of coefficient2.752*0.977 R 2 (a) 0.18 Number of obs.1500= (500 x 3)

15. Ecosystems (Socio-economics) Econometric Results - WTP The willingness to pay in order to prevent landscape changes was calculated as the coefficient of the “landscape change” divided by the coefficient of “price”. is the utility differences between the state and without the programs to prevent landscape change

16. Ecosystems (Socio-economics) Welfare from landscape loss ($/ha) as a function of biomass loss real predicted

17. Ecosystems (Socio-economics) Income Loss as a Result of Decreases in Grassy Biomass Loss of grassy bio mass $/ha

18. Ecosystems (Socio-economics) Income Loss as a Result of Decreases in Grassy Biomass Loss of grass bio mass $/ha

19. Ecosystems (Socio-economics) YEARLY LOSS VALUE OF ECOSYSTEM SERVICES IN THE TRANSFORMATION FROM MESIC MEDITERRANEAN TO MEDITERRANEAN, SEMIARID AND ARID CLIMATES Loss of total biomass (ton ha -1 ) Total WTP to prevent loss of biomass b ($ 10 6 ha -1 ) Loss of herbaceous biomass (ton ha -1 ) Loss of grazing services for cattle c ($) Loss of grazing services for sheep c ($) Mesic Med. Med. 7.851.50.0095,7338,001 Mesic Med. Semiarid 13.085.80.25616,12822,554 Mesic Med. Arid 16.3107.60.81851,53472,135

20. Ecosystems (Socio-economics) Conclusions Local community is eliciting utility from landscape and is willing to pay for government mitigation measures. Loss of welfare for recreation services is larger than grazing services The higher the conceived landscape loss the higher is the payment. Policy makers have the public consent for taxing this generation in order for future generations to enjoy the landscape.