Optimal management of a stochastically varying population when policy adjustment is costly

Ecological Applications

Volumn 26, Issue 3, 2016, Pages 808-817

  Boettiger, Carl ^a   Bode, Michael ^b   Sanchirico, James N ^c   Lariviere, Jacob ^d   Hastings, Alan ^c   Armsworth, Paul R ^d  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF MELBOURNE   (Australia)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d UNIVERSITY OF TENNESSEE   (United States)

Author keywords

Adjustment costs; Ecological management; Fisheries; Optimal control

Indexed keywords

ADJUSTMENT MECHANISM; COST ANALYSIS; ECONOMIC IMPACT; ECOSYSTEM MANAGEMENT; ENVIRONMENTAL ECONOMICS; ENVIRONMENTAL POLICY; FISHERY MANAGEMENT; STOCHASTICITY;

ANIMAL; BIOLOGICAL MODEL; ECONOMICS; FISH; FISHERY; LEGISLATION AND JURISPRUDENCE; MARKOV CHAIN; PHYSIOLOGY; POLICY; POPULATION DYNAMICS; TIME FACTOR;

ANIMALS; FISHERIES; FISHES; MODELS, BIOLOGICAL; POPULATION DYNAMICS; PUBLIC POLICY; STOCHASTIC PROCESSES; TIME FACTORS;

EID: 84964849110     PISSN: None     EISSN: 19395582     Source Type: Journal    
DOI: 10.1890/15-0236/suppinfo     Document Type: Article

References (38)

1. Armsworth, P. R., and J. E. Roughgarden. 2003. The economic value of ecological stability. Proceedings of the National Academy of Sciences of the United States of America 100:7147-7151.
2. Armsworth, P. R., B. A. Block, J. Eagle, and J. E. Roughgarden. 2011. The role of discounting and dynamics in determining the economic efficiency of time-area closures for managing fishery bycatch. Theoretical Ecology 4:513-526.
3. Biais, G. 1995. An evaluation of the policy of fishery resources management by TACs in European Community waters from 1983 to 1992. Aquatic Living Resources 8:241-251.
4. Boettiger, C. 2015. An introduction to Docker for reproducible research, with examples from the R environment. ACM SIGOPS Operating Systems Review 49:71-79.
5. Boettiger, C., N. Ross, and A. Hastings. 2013. Early warning signals: the charted and uncharted territories. Theoretical Ecology 6:255-264.
6. Boettiger, C., M. Bode, J. N. Sanchirico, J. La Riviere, A. Hastings, and P. Armsworth. 2015. Repository for: Optimal management of a stochastically varying population when policy adjustment is costly. Zenodo. doi:10.5281/zenodo.21416.
7. Brown, G. 1974. An optimal program for managing common property resources with congestion externalities. Journal of Political Economy 82:163-173.
8. Clark, C. W. 2010. Mathematical bioeconomics: the mathematics of conservation. Third edition. Wiley & Sons, Hoboken, New Jersey, USA.
9. Clark, C. W., and M. Mangel. 2000. Dynamic state variable models in ecology. Oxford University Press, Oxford, UK.
10. Durrett, R., and S. A. Levin. 1994. The importance of being discrete (and spatial). Theoretical Population Biology 46:363-394.
11. Feichtinger, G., A. Novak, and F. Wirl. 1994. Limit cycles in intertemporal adjustment models. Journal of Economic Dynamics and Control 18:353-380.
12. Halpern, B. S., C. White, S. E. Lester, C. Costello, and S. D. Gaines. 2011. Using portfolio theory to assess tradeoffs between return from natural capital and social equity across space. Biological Conservation 144:1499-1507.
13. Homans, F. R., and J. Wilen. 1997. A model of regulated open access resource use. Journal of Environmental Economics and Management 32:1-21.
14. International Commission for the Conservation of Atlantic Tunas (ICCAT). 2009. Report of the 2008 ICCAT bluefin stock assessment session. ICCAT Collective Volume of Scientific Papers 64:1-352.
15. Kaitala, V. 1993. Equilibria in a stochastic resource management game under imperfect information. European Journal of Operational Research 71:439-453.
16. Laukkanen, M. 2003. Cooperative and non-cooperative harvesting in a stochastic sequential fishery. Journal of Environmental Economics and Management 45:454-473.
17. Lewis, T. R. 1981. Exploitation of a renewable resource under uncertainty. The Canadian Journal of Economics 14:422.
18. Ludwig, D. 1980. Harvesting strategies for a randomly fluctuating population. Journal du Conseil 39:168-174.
19. Mangel, M., and C. W. Clark. 1988. Dynamic modeling in behavioral ecology (J. Krebs and T. Clutton-Brock, editors). Princeton University Press, Princeton, New Jersey, USA.
20. McFadden, D. 1975. The revealed preferences of a government bureaucracy: theory. The Bell Journal of Economics 6:401.
21. McFadden, D. 1976. The revealed preferences of a government bureaucracy: empirical evidence. The Bell Journal of Economics 7:55.
22. McGough, B., A. J. Plantinga, and C. Costello. 2009. Optimally managing a stochastic renewable resource under general economic conditions. The B. E. Journal of Economic Analysis & Policy 9:1-31.
23. Neubert, M. G. 2003. Marine reserves and optimal harvesting. Ecology Letters 6:843-849.
24. Patterson, K. 2007. Social resistance to the obvious good: a review of responses to a proposal for regulation of european fisheries. American Fisheries Society Symposium 49:587-596.
25. Patterson, K., and M. Resimont. 2007. Change and stability in landings: the responses of fisheries to scientific advice and TACs. ICES Journal of Marine Science 64:714-717.
26. Porch, C. E. 2005. The sustainability of western Atlantic bluefin tuna: a warm-blooded fish in a hot-blooded fishery. Bulletin of Marine Science 76:363-384.
27. Reed, W. J. 1974. A stochastic model for the economic management of a renewable animal resource. Mathematical Biosciences 22:313-337.
28. Reed, W. J. 1979. Optimal escapement levels in stochastic and deterministic harvesting models. Journal of Environmental Economics and Management 6:350-363.
29. Safina, C. 1998. Song for the blue ocean: Encounters along the world's coasts. Henry Holt, New York, New York, USA.
30. Sanchirico, J. N., M. D. Smith, and D. W. Lipton. 2008. An empirical approach to ecosystem-based fishery management. Ecological Economics 64:586-596.
31. Scheffer, M., J. Bascompte, W. A. Brock, V. Brovkin, S. R. Carpenter, V. Dakos, H. Held, E. H. van Nes, M. Rietkerk, and G. Sugihara. 2009. Early-warning signals for critical transitions. Nature 461:53-59.
32. SEDAR. 2013. SEDAR 36 stock assessment report: south Atlantic snowy grouper. Page 146. SEDAR, North Charleston, South Carolina, USA.
33. Sethi, G., C. Costello, A. Fisher, M. Hanemann, and L. Karp. 2005. Fishery management under multiple uncertainty. Journal of Environmental Economics and Management 50:300-318.
34. Singh, R., Q. Weninger, and M. Doyle. 2006. Fisheries management with stock growth uncertainty and costly capital adjustment. Journal of Environmental Economics and Management 52:582-599.
35. Sissenwine, M. P., P. M. Mace, J. E. Powers, and G. P. Scott. 1998. A commentary on western Atlantic bluefin tuna assessments. Transactions of the American Fisheries Society 127:838-855.
36. Spulber, D. F. 1982. Adaptive harvesting of a renewable resource and stable equilibrium. Pages 117-139 in L. Mirman and D. Spulber, editors. Essays in the economics of renewable resources. North-Holland Publishing, Amsterdam, the Netherlands.
37. Walters, C. J. 1978. Some dynamic programming applications in fisheries management. Pages 233-246 in J. Petkau, editor. Dynamic Programming and its Applications, Proceedings of the International Conference on Dynamic Programming and its Applications. University of British Columbia, Vancouver.
38. Wirl, F. 1999. Complex, dynamic environmental policies. Resource and Energy Economics 21:19-41.