1. Species conservation in the face of political uncertainty Martin Drechsler/Frank Wätzold (UFZ) 1. Motivation 2. Literature 3. Basic model structure 4. Model analysis 5. Model results 6. Final remarks Introduction

2. Examples point to the risk of a „roll back“ in environmental policy, meaning there is „political uncertainty “! Motivation

3. Political uncertainty is particularly problematic when there is the risk of irreversible damage, like the extinction of an endangered species What are the options of a present government that has the goal of long-term protection of species but has to expect that a future government will give less priority to species conservation? Focus on species that require protection measures and corresponding financial compensation on a regular basis

4. Motivation Uncertainty exists over the the availability of a budget in future periods, such that future budgets may be lower than today with a certain probability Problems of similar structure arise from economic fluctuations as well as fluctuating donations to non-commercial conservation funds like WWF An institutional framework for transferring financial resources into the future may be an independent foundation that in each period decides how much money shouod be spent for conservation in the present period and how much should be saved for future efforts

5. Motivation Aim of the paper Develop a conceptual model for this dynami optimisation problem to gain a better understanding of relevant ecological and economic parameters and their interaction in time.

6. Integration of ecological and economic knowledge in models  Ando, A, Camm, J., Polasky, S., Solow, A. (1998) Science  Perrings, C. (2003) Discussion paper  Baumgärtner (2003) Ecosystem Health Literature Dynamic models for biodiversity conservation  Johst, K., Drechsler, M., Wätzold, F. (2002) Ecological Economics  Costello, C., Polasky, S. (2002) Discussion paper Micro- and macroeconomic dynamic consumption models  Leland (1968) Quarterly Journal of Economics

7. Ecological benefit function Basic model structure Starting point: Maximise the survival probability of a species,  T, over T+1 periods The survival probability over T+1 periods, each of length  t, then is with t the species-specific extinction rate and  t the length of the period For period t:

8. According to Lande (1993) and Wissel et al. (1994) the extinction rate in period t is given by with K t : habitat capacity ã : species specific parameter  : positive and inverse proportional to the variance in the population growth rate Basic model structure

9. Initial habitat capacity be K (0). If certain measures are carried out in a given period then the habitat capacity in that period (but no longer) increases to K (0) +  t. Species-friendly land-use measures cause costs (assuming constant marginal costs, such that  t =bc t ). with The conservation objective of the (present) government can be formulated as the maximisation of the survival probability over T+1 periods: Basic model structure

10. Government Agency Fund F t Measures costing c t und increasing habitat capacity by k t Grant g t Payment p t Basic model structure

11. Value function p t : control variable (payment) Model analysis (Equation of motion)Boundary conditions Intertemporal allocation problem under uncertainty. Solution via stochastic dynamic programming:

12. Solution for period T-1 Interiour solution Corner solution Model analysis Solution for period T h t : deterministic component of the grant  : stochastic variation (s.d.) of the grant

13. Model analysis Solution p T-k * depends only on the number of consecutive periods with interior solution (without a corner solution in between) following the Present period T-k In the deterministic case the future and particularly the number of future consecutive periods with interiour solution is known. In the stochastic case the probability distribution of the number of consecutive periods with interiour solution can be approximated.

14. Optimal payments (dotted line) when grants (solid line) first fall, then rise and then fall again. The evolution of the fund is presented by the dashed line. Model results - Example 1: no stochasticity

15. Distribution of the number l of consecutive periods with interiour solution: P(l) Optimal Payment under the assumption of exactly l periods with interiour solution following: p t (l) Uncertainty reduces the optimal payment („precautionary saving“, Leland 1968). The larger , the more is saved Model results - Example 2: stochasticity, no trend Optimal payment in period t=0:  : uncertainty in the grants  : ecological parameter (shape of the benefit function) h: mean of the grants

16. Model results - Example 3 : negative trend plus stochasticity, 3 periods t=0,1,2  : Uncertainty in the grants  : ecological parameter h 0 : grant in periode t=0  : negative trend in the grants C: constante For small and for large  (uncertainty in the grants): But latter equation can be approximated by former with error <3%. Therefore the effect of  is clear with negligible error. Uncertainty reduces the optimal payment („precautionary saving“) Für median  : p 0 * can increase with  („precautionary spending“) – effect of  ambiguous!

17. Final remarks Even allocation of the payments should be aimed at, as long as the boundary conditions (non-negativity of the fund) allow for it Consideration of interest rates complicated and ambiguous Stochasticity large or small against the trend: stochasticity reduces the optimal payment, i.e. save more - the larger  (i.e., in species with weakly fluctuating population growth), the more should be saved Stochasticity of similar magnitude as the trend: stochasticity may increase optimal payment, but only marginally Further research: Analysis of the problems of political uncertainty with respect to a concrete species conservation programme