Conservation effort and assessment of population size in fluctuating environments

Journal of Theoretical Biology

Volumn 224, Issue 2, 2003, Pages 167-182

  Yokomizo, Hiroyuki ^a   Haccou, Patsy ^b   Iwasa, Yoh ^a  

^a KYUSHU UNIVERSITY   (Japan)

^b LEIDEN UNIVERSITY   (Netherlands)

Author keywords

Assessment; Conservation; Extinction Risk; Optimal management; Uncertainty

Indexed keywords

ASSESSMENT METHOD; CONSERVATION; ENDANGERED SPECIES; POPULATION SIZE;

ACCURACY; ARTICLE; ECONOMICS; ENVIRONMENTAL FACTOR; ENVIRONMENTAL PROTECTION; MATHEMATICAL ANALYSIS; POPULATION SIZE; PRIORITY JOURNAL; SPECIES EXTINCTION;

EID: 0043123312     PISSN: 00225193     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0022-5193(03)00144-9     Document Type: Article

References (17)

1. Cassey P., Ussher G.T. Estimating abundance of tuatara. Biol. Conserv. 88:1999;361-366.
2. Doherty P.F., Marschall E.A., Grubb T.C. Balancing conservation and economic gain. a dynamic programming approach Ecol. Econ. 29:1999;349-358.
3. Driscoll D.A. Counts of calling males as estimates of population size in the endangered frogs Geocrinia alba and G. vitellina. J. Herpetol. 32:1998;475-481.
4. Haccou P., Iwasa Y. Optimal mixed strategies in stochastic environments. Theor. Popul. Biol. 47:1995;212-243.
5. Haight R.G. Comparing extinction risk and economic cost in wildlife conservation planning. Ecol. Appl. 5:1995;767-775.
6. Iwasa Y., Haccou P. ESS emergence pattern of male butterflies in stochastic environments. Evol. Ecol. 8:1994;503-523.
7. Kangas A., Kurki S. Predicting the future of Capercaillie (Tetrao urogallus) in Finland. Ecol. Modelling. 134:2000;73-87.
8. Lubow B.C. Optimal translocation strategies for enhancing stochastic metapopulation viability. Ecol. Appl. 6:1996;1268-1280.
9. Maunder M.N., Starr P.J., Hilborn R. A Bayesian analysis to estimate loss in squid catch due to the implementation of a sea lion population management plan. Mar. Mammal Sci. 16:2000;413-426.
10. McCarthy M.A., Possingham H.P., Gill A.M. Using stochastic dynamic programming to determine optimal fire management for Banksia ornata. J. Appl. Ecol. 38:2001;585-592.
11. Omlin M., Reichert P. A comparison of techniques for the estimation of model prediction uncertainty. Ecol. Modelling. 115:1999;45-59.
12. Pascual M.A., Hilborn R. Conservation of harvested populations in fluctuating environments. the case of the Serengeti wildebeest J. Appl. Ecol. 32:1995;468-480.
13. Punt A.E., Hilborn R. Fisheries stock assessment and decision analysis. the Bayesian approach Rev. Fish Biol. Fisher. 7:1997;35-63.
14. Robertson A., Simmons R.E., Jarvis A.M., Brown C.J. Can bird atlas data be used to estimate population-size-a case-study using Namibian endemics. Biol. Conserv. 71:1995;87-95.
15. Stuart, A., Ord, J.K., 1994. Kendall's Advanced Theory of Statistics, Vol. 1, 6th Edition. Wiley, Halsted Press, New York, pp. 193-194.
16. Walsh P.D., White L.J.T., Mbina C., Idiata D., Mihindou Y., Maisels F., Thibault M. Estimates of forest elephant abundance. projecting the relationship between precision and effort J. Appl. Ecol. 38:2001;217-228.
17. Yokomizo H., Yamashita J., Iwasa Y. Optimal conservation effort for a population in a stochastic environment. J. Theor. Biol. 220:2003;215-231.