Dynamic models in biology

Dynamic Models in Biology

Volumn , Issue , 2011, Pages

  Ellner, Stephen P ^a   Guckenheimer, John ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84884081657     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Book

References (282)

1. Ferguson, N.M, C.A. Donnelly, and R.M. Anderson. 2001a. The Foot-and-Mouth epidemic in Great Britain: Pattern of spread and impact of interventions. Science 292: 1155-1160.
2. Ferguson, N.M., C.A. Donnelly, and R.M. Anderson. 2001b. Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain. Nature 413: 542-548.
3. Keeling, M.J., M.E.J.Woolhouse, D.J. Shaw, L. Matthews, M. Chase-Topping, D.T. Haydon, S.J. Cornell, J. Kappey, J. Wilesmith, and B.T. Grenfell. 2001. Dynamics of the 2001 UK Foot and Mouth epidemic: Stochastic dispersal in a heterogeneous landscape. Science 294: 813-817.
4. Bishop, L. 2002. Cleanup estimates to double. Ithaca Falls project will run over in time, money. Ithaca Journal (http://www.ithacajournal.com), October 4, 2002.
5. Blickhan, R., and R. Full. 1993. Similarity in multilegged locomotion: Bouncing like a monopode. Journal of Comparative Physiology A 173: 509-517.
6. Bradford, M. J., and J. R. Irvine. 2000. Land use, fishing, climate change, and the decline of Thompson River, British Columbia, coho salmon. Canadian Journal of Fisheries and Aquatic Science 57: 13- 16.
7. Carver, S. 2003. Control of a Spring-Mass Hopper. Ph.D. Thesis, Cornell University.
8. Clutton-Brock, T. H., I. R. Stevenson, P. Marrow, A. D. MacColl, A. I. Houston, and J. M. McNamara. 1996. Population fluctuations, reproductive costs, and life-history tactics in female Soay sheep. Journal of Animal Ecology 65: 675-689.
9. Dickson, T. R. 1968. The Computer and Chemistry; An Introduction to Programming and Numerical Methods. W. H. Freeman, San Francisco.
10. Easterling, M. R., M. Styblo, M. V. Evans, and E. M. Kenyon. 2002. Pharmacokinetic modeling of arsenite uptake and metabolism in hepatocytes-mechanistic insights and implications for further experiments. Journal of Pharmacokinetics and Pharmacodynamics 29: 207-234.
11. Ellner, S., A. Neori, M. D. Krom, K. Tsai, and M. R. Easterling. 1996. Simulation model of recirculating mariculture with seaweed biofilter: Development and experimental tests of the model. Aquaculture 143: 167-184.
12. Ellner, S. P., and J. Fieberg. 2003. Using PVA for management in light of uncertainty: Effects of habitat, hatcheries, and harvest on salmon viability. Ecology 84: 1359-1369.
13. EPA (U.S. Environmental Protection Agency). 1994a. Guidance Manual for the Integrated Exposure Uptake Biokinetic Model for Lead in Children. Publication number 9285.7-15-1, EPA 540-R-93-081, PB93-963510. Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency Washington, DC 20460. Online at http://www.epa.gov/superfund/ programs/lead/products.htm
14. EPA (U.S. Environmental Protection Agency). 1994b. Technical Support Document: Parameters and Equations Used in the Integrated Exposure Uptake Biokinetic (IEUBK) Model for Lead in Children (v 0.99d). Publication number 9285.7-22, EPA 540/R-94/040, PB94-963505. Online at http://www.epa.gov/superfund/programs/lead/products.htm
15. EPA (U.S. Environmental Protection Agency). 2002. User's Guide for the Integrated Exposure Uptake Biokinetic Model for Lead in Children (IEUBK). Windows version, 32 bit version. Publication number EPA 540-K-01-005. Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency, Washington, DC 20460. Online at http://www.epa.gov/superfund/ programs/lead/products.htm
16. Harris-Warrick, R., L. Coniglio, N. Barazangi, J. Guckenheimer, and S. Gueron. 1995. Dopamine modulation of transient potassium current evokes phase shifts in a central pattern generator network. J. Neuroscience 15: 342-358.
17. Hilborn, R. and M. Mangel. 1997. The Ecological Detective: Confronting Models with Data. Princeton University Press, Princeton, NJ.
18. Kendall, B. E., C. J. Briggs,W.W. Murdoch, P. Turchin, S. P. Ellner, E. McCauley, R. M. Nisbet, and S. N. Wood. 1999. Inferring the causes of population cycles: A synthesis of statistical and mechanistic modeling approaches. Ecology 80: 1789-1805.
19. Koditschek, D. and M. Buehler. 1991. Analysis of a simplified hopping robot. International Journal of Robotics Research 10: 587-605.
20. Krom, M. D., S. Ellner, J. van Rijn, and A. Neori. 1995. Nitrogen and phosphorus cycling in a prototype "non-polluting" integrated mariculture system, Eilat, Israel. Marine Ecology Progress Series 118: 25-36.
21. Levin P. S., R.W. Zabel, and J. G.Williams. 2001. The road to extinction is paved with good intentions: Negative association of fish hatcheries with threatened salmon. Proceedings of the Royal Society of London Series B 268: 1153-1158.
22. Michaelis, L., and M. L. Menten. 1913. Die Kinetik der Invertinwerkung. Biochemische Zeitschrift 49: 333-369.
23. Oosterhout, G. R., and P. R. Mundy. 2001. The Doomsday Clock 2001: An Update on the Status and Projected Time to Extinction for Snake River Wild Spring/Summer Chinook Stocks. Report prepared for Trout Unlimited. Online at http://www.decisionmatrix.net/models.htm and http://www.tu.org/pdf/newsstand/library/doomsday_clock_2001_report.pdf
24. Raibert, M. 1986. Legged Robots that Balance. MIT Press, Cambridge, MA.
25. Saranli, U., M. Buehler, and D. E. Koditschek. 2001. RHex: A simple and highly mobile hexapod robot. International Journal of Robotics 20: 616-631.
26. Segrè, D., D. Vitkup, and G. M. Church. 2002. Analysis of optimality in natural and perturbed metabolic networks. Proceedings of the National Academy of Sciences USA 99: 15112-15117.
27. Stone, C. J. 1982. Optimal rates of convergence for nonparametric regression. Annals of Statistics 10: 1050-1053.
28. Tilman, D. 1989. Ecological experimentation: Strengths and conceptual problems. pages 136-157 in G. E. Likens (ed.), Long-Term Studies in Ecology: Approaches and Alternatives. Springer-Verlag, New York.
29. White, P., P. Van Leeuwen, B. Davis, M. Maddaloni, K. Hogan, A. Marcus, and R. Elias. 1998. U.S. Environmental Protection Agency: The conceptual structure of the integrated exposure uptake biokinetic model for lead in children. Environmental Health Perspectives 106 (Suppl. 6): 1513.
30. Wilson, P. H. 2003. Using population projection matrices to evaluate recovery strategies for Snake River spring and summer Chinook salmon. Conservation Biology 17: 782-794.
31. Abrams, P. A. 1993. Does increased mortality favor the evolution of more rapid senescence? Evolution 47: 877-887.
32. Anderson, R. M. and R. M. May. 1992. Infectious Disease of Humans: Dynamics and Control. Oxford University Press, Oxford.
33. Benton, T. G., T. C. Cameron, and A. Grant. 2004. Population responses to perturbations: Predictions and responses from laboratory mite populations. Journal of Animal Ecology 73: 983-995.
34. Berry, K. H. 1997. The desert tortoise recovery plan: An ambitious effort to conserve biodiversity in the Mojave and Colorado Deserts of the United States. Pages 430-440 in Proceedings: Conservation, Restoration, and Management of Tortoises and Turtles: An International Conference. New York Turtle and Tortoise Society.
35. Brault, S., and H. Caswell. 1993. Pod-specific demography of killer whales (Orcinus orca). Ecology 74: 1444-1454.
36. Brook, B. W., J. J. O'Grady, A. P. Chapman, M. A. Burgman, R. Akcakaya, and R. Frankham. 2000. Predictive accuracy of population viability analysis in conservation biology. Nature 404: 385-387.
37. Caswell, H. 2001. Matrix Population Models: Construction, Analysis, and Interpretation, 2nd edition. Sinauer Associates, Sunderland, MA.
38. Charlesworth, B. C. 1994. Evolution in Age-Structured Populations, 2nd edition. Cambridge University Press, Cambridge U.K. (1st edition 1980).
39. Childs, D. Z., M. Rees, K. E. Rose, P. J. Grubb, and S. P. Ellner. 2003. Evolution of complex flowering strategies: An age- and size-structured integral projection model. Proceedings of the Royal Society B 270: 1829-1839.
40. Childs, D. Z., M. Rees, K. E. Rose, P. J. Grubb, and S. P. Ellner. 2004. Evolution of size dependent flowering in a variable environment: Construction and analysis of a stochastic integral projection model. Proceedings of the Royal Society B 271: 425-434.
41. Crouse, D. T., L. B. Crowder, and H. Caswell. 1987. A stage-based population model for loggerhead sea turtles and implications for conservation. Ecology 68: 1412-1423.
42. Crowder, L. B., D. T. Crouse, S. S. Heppell, and T. H. Martin. 1994. Predicting the impact of turtle excluder devices on loggerhead sea turtle populations. Ecological Applications 4: 437-445.
43. Cushing, J. M., R. F. Costantino, B. Dennis, R. A. Desharnais, and S. M. Henson. 2002. Chaos in Ecology: Experimental Nonlinear Dynamics. Academic Press, San Diego.
44. Dennis, B., R. A. Desharnais, J. M. Cushing, and R. F. Costantino. 1997. Transitions in population dynamics: equilibria to periodic cycles to aperiodic cycles. Journal of Animal Ecology 66: 704-729.
45. Dennis, B., R. A. Desharnais, J. M. Cushing, S. M. Henson, and R. F. Costantino. 2001. Estimating chaos and complex dynamics in an insect population. Ecological Monographs 71: 277-303.
46. Dixon, P. M., and R. E. Cook. 1990. Life History and Demography of Northern Monkshood (Aconitum noveboracense) in New York State. Report, Cornell Plantations, Ithaca, NY.
47. Dixon, P. M., N. Friday, P. Ang, S. Heppell, and M. Kshatriya. 1997. Sensitivity analysis of structuredpopulation models for management and conservation. Pages 471-513 in S. Tuljapurkar and H.Caswell (eds.), Structured Population Models in Marine, Terrestrial and Freshwater Systems. Chapman and Hall, London.
48. Doak, D., P. Kareiva, and B. Klepetka. 1994. Modeling population viability for the desert tortoise in the Western Mojave desert. Ecological Applications 4: 446-460.
49. Easterling, M. R., S. P. Ellner, and P. Dixon. 2000. Size-specific sensitivity: Applying a new structured population model. Ecology 81: 694-708.
50. Ellner, S. P., J. Fieberg, D. Ludwig, and C. Wilcox. 2002. Precision of population viability analysis. Conservation Biology 16: 258-261.
51. Ellner, S. P., and J. Fieberg. 2003. Using PVA for management despite uncertainty: Effects of habitat, hatcheries, and harvest on salmon. Ecology 84: 1359-1369.
52. Fieberg, J., and S. P. Ellner. 2000. When is it meaningful to estimate an extinction probability? Ecology 81: 2040-2047.
53. Fisher, R. A. 1930. The Genetical Theory of Natural Selection. Oxford University Press, Oxford. Second ed. Dover, New York, 1958.
54. Hairston, N. G., S. Ellner, and C. M. Kearns. 1996. Overlapping generations: the storage effect and the maintenance of biotic diversity. Pages 109-145 in O. E. Rhodes, R. K. Chesser, and M. H. Smith (eds), Population Dynamics in Ecological Space and Time. University of Chicago Press, Chicago.
55. Henson, S. M., R. F. Costantino, J. M. Cushing, R. A. Desharnais, B. Dennis, and A. A. King, 2001. Lattice effects observed in chaotic dynamics of experimental populations. Science 294: 602-605.
56. Heppell, S. S., L. B. Crowder, and D. T. Crouse. 1996. Model to evaluate headstarting as a management tool for long-lived turtles. Ecological Applications 6: 556-565.
57. Heppell, S. S., D. R. Crouse, and L. B. Crowder. 1998. Using matrix models to focus research and management efforts in conservation. Pages 148-168 in S. Ferson and M. Burgman (eds.), Quantitative Methods for Conservation Biology. Springer, New York.
58. Holmes, E. E., andW. F. Fagan. 2002. Validating population viability analysis for corrupted data sets. Ecology 83: 2379-2386.
59. Horn, R. A. and C. R. Johnson. 1985. Matrix Analysis. Cambridge University Press, Cambridge U.K. IUCN 2001. IUCN Red List Categories and Criteria: Version 3.1. Report, IUCN Species Survival Commission. IUCN, Gland, Switzerland and Cambridge, U.K. Online at http://www.iucn.org/ themes/ssc/realists/RLcats2001booklet.html
60. Johnson, K. H., and C. E. Braun. 1999. Viability and conservation of an exploited sage grouse population. Conservation Biology 13: 77-84.
61. Kareiva, P., M. Marvier, and M. McClure. 2000. Recovery and management options for spring/summer Chinook salmon in the Columbia River basin. Science 290: 977-979.
62. Kirkwood, T.B.L., and S. N. Austad. 2000. Why do we age?. Nature 408: 233-238.
63. Lande, R. 1988. Demographic models of the Northern Spotted Owl (strix occidentalis caurina). Oecologia 7S: 601-607.
64. Ludwig, D. 1999. Is it meaningful to estimate a probability of extinction?. Ecology 80: 298-310.
65. McCarthy, M. A, S. J. Andelman, and H. P. Possingham. 2003. Reliability of relative predictions in population viability analysis. Conservation Biology 17: 982-989.
66. McEvoy, P. B. and E. M. Coombs. 1999. Biological control of plant invaders: Regional patterns, field experiments, and structured population models. Ecological Applications 9: 387-401.
67. Morris, W. F. and D. F. Doak. 2002. Quantitative Conservation Biology: Theory and Practice of Population Viability Analysis. Sinauer, Sunderland, MA.
68. Parker, I. M. 2000. Invasion dynamics of Cytisus scoparius: A matrix model approach. Ecological Applications 10: 726-743.
69. Reed, J. M., L. S. Mills, J. B. Dunning, Jr., E. S. Menges, K. S. McKelvey, R. Frye, S. R. Beissinger, M.-C. Anstett, and P. Miller. 2002. Emerging issues in population viability analysis. Conservation Biology 16: 7-19.
70. Rees, M., and K. E. Rose. 2002. Evolution of flowering strategies in Oenothera glazioviana: An integral projection model approach. Proceedings of the Royal Society B 269: 1509-1515.
71. Rees, M., D. Z. Childs, K. E. Rose, and P. J. Grubb. 2004. Evolution of size dependent flowering in a variable environment: Partitioning the effects of fluctuating selection. Proceedings of the Royal Society B 271: 471-475.
72. Reznick, D. N. M. J. Bryant, D. Roff, C. K. Ghalambor, and D. E. Ghalambor. 2004. Effect of extrinsic mortality on the evolution of senescence in guppies. Nature 431: 1095-1099.
73. Rockwell, R. F., E. G. Cooch, and S. Brault. 1997. Dynamics of the mid-continent population of lesser snow geese: Projected impacts of reductions in survival and fertility on population growth rates. Pages 73-100 in B. Batt (ed.), Arctic Goose Habitat Working Group Report. U.S. Fish and Wildlife Service, Washington, DC, and Canadian Wildlife Service, Ottowa, ON.
74. Roff, D. A. 2001. Life History Evolution. Sinauer Associates, Sunderland, MA.
75. Shea, K., and D. Kelly. 1998. Estimating biocontrol agent impact with matrix models: Carduus nutans in New Zealand. Ecological Applications 8: 824-832.
76. Stearns, S. C. 2000. Life history theory: Successes, limitations, and prospects. Naturwissenschaften 87: 476-486.
77. Tuljapurkar, S. 1990. Population Dynamics in Variable Environments. Springer-Verlag, New York.
78. USFWS. 1988. Endangered Species Act of 1973 as amended through the 100th Congress. U.S. Department of Interior, Fish and Wildlife Service, Washington, DC.
79. Valverde, T. and J. Silvertown. 1998. Variation in the demography of a woodland understorey herb (Primula vulgaris) along the forest regeneration cycle: Projection matrix analysis. Journal of Ecology 86: 545-562.
80. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2002. Analysis and Management of Animal Populations. Academic Press, New York.
81. Wood, S. N. 1997. Inverse problems and structured population dynamics. Pages 555-586 in S. Tuljapurkar and H. Caswell (eds.), Structured Population Models in Marine, Terrestrial and Freshwater Systems. Chapman and Hall, New York.
82. Anderson, C., and C. Stevens. 1973. Voltage clamp analysis of acetylcholine produced end-plate current fluctuations at frog neuromuscular junction. Journal of Physiology 235: 655-691.
83. Colquhoun, D., and A. Hawkes. 1995. The principles of the stochastic interpretation of ion-channel mechanisms. Pages 397-481 in Single Channel Recording, 2nd edition, B. Sakmann and E. Neher, eds., Plenum, New York.
84. Colquhoun, D., and B. Sakmann. 1985. Fast events in single-channel currents activated by acetylcholine and its analogues at the frog muscle end-plate. Journal of Physiology 369: 501-557.
85. Colquhoun, D., and B. Sakmann. 1998. From muscle endplate to brain synapses: A short history of synapses and agonist-activated ion channels. Neuron 20: 381-387.
86. Diaconis, P., S. Holmes, and R. Montgomery. 2004. Dynamical bias in the coin toss. Online at http://www-stat.stanford.edu/ cgates/PERSI/by_year.html
87. Hille, B. 2001. Ion Channels of Excitable Membranes, 3rd edition, Sinauer Associates, Sunderland, MA, Chapter 2 and pp. 172-185.
88. Hodgkin, A., and A. Huxley. 1952. A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology 117: 500-544.
89. Johnston, D., and S. Wu. 1995. Foundations of Cellular Neurophysiology, MIT Press, Cambridge, MA.
90. Kandel, E., J. Schwartz, and T. Jessell. 1991. Principles of Neural Science. Appleton and Lange.
91. Katz, B., and S. Thesleff. 1957. A study of the "desensitization" produced by acetylcholine at the motor end-plate. Journal of Physiology 138: 63-80.
92. Keynes, R., E. Rojas, R. Taylor, and J. Vergara. 1973. Calcium and potassium systems of a giant barnacle muscle fiber under membrane potential control. Journal of Physiology 229: 409-455.
93. Knuth, D. E. 1981. The Art of Computer Programming. Vol. 2, Seminumerical Algorithms. 2nd edition. Addison-Wesley, Reading, MA.
94. Lawler, G. 1995. Introduction to Stochastic Processes Chapman & Hall, London, pp. 53-61.
95. Lecar, H., G. Ehrenstein, and R. Latorre. 1975. Mechanism for channel gating in excitable bilayers. Annals of the New York Academy of Science 264: 304-313.
96. Morris, C., and H. Lecar. 1981. Voltage oscillations in the barnacle giant muscle fiber. Biophysical Journal, 35: 193-213.
97. Neher, E., and B. Sakmann. 1976. Single channel currents recorded from membrane of denervated frog muscle fibres. Nature 260: 799-802.
98. Alon, U. 2003. Biological networks: the tinkerer as an engineer. Science 301: 1866-1867.
99. Atkinson, M., M. Savageau, J. Myers, and A. Ninfa. 2003. Development of genetic circuitry exhibiting toggle switch or oscillatory behavior in Escherichia coli. Cell 113: 597-607.
100. Brown, K., and J. Sethna. 2003. Statistical mechanics approaches to models with many poorly known parameters. Physical Review E 68: 021904.
101. Caswell, H. 1988. Theory and models in ecology: A different perspective. Ecological Modelling 43: 33-44.
102. Christopher, R., A. Dhiman, J. Fox, R. Gendelman, T. Haberitcher, D. Kagle, G. Spizz, I. G. Khalil, and C. Hill. 2004. Data-driven computer simulation of human cancer cell. Annals of the NY Academy of Science 1020: 132-153.
103. Elowitz, M., and S. Leibler. 2000. A synthetic oscillatory network of transcriptional regulators. Nature 403: 335-338.
104. Ferber, D. 2004. Microbes made to order. Science 303: 158-161.
105. Gardner, T., C. Cantor, and J. Collins. 2000. Construction of a genetic toggle switch in Escherichia coli. Nature 403: 339-342.
106. Gavrilets, S. 2003. Models of speciation: What have we learned in 40 years?. Evolution 57: 2197-2215.
107. Ginzburg, L. R., and C.X.J. Jensen. 2004. Rules of thumb for judging ecological theories. Trends in Ecology and Evolution 19: 121-126.
108. Hall, C.A.S. 1988. An assessment of several of the historically most influential theoretical models in ecology and of the data provided in their support. Ecological Modelling 43: 5-31.
109. Hasty, J., D. McMillen, and J. Collins. 2002. Engineered gene circuits. Nature 402: 224-230.
110. Hess, G. R. 1996. To analyze, or to stimulate, is that the question?. American Entomologist 42: 14-16.
111. Kohn, K. 1999. Molecular interaction map of the mammalian cell cycle control and DNA repair system. Molecular Biology of the Cell 10: 2703-2734.
112. Lander, A. D. 2004. A calculus of purpose. PLoS Biology 2: 712-714.
113. May, R. M. 1974. Stability and Complexity in Model Ecosystems, 2nd edition. Princeton University Press, Princeton, NJ.
114. Peck, S. L. 2004. Simulation as experiment: A philosophical reassessment for biological modeling. Trends in Ecology and Evolution 19: 530-534.
115. Tyson, J. J., K. Chen, and B. Novak. 2001. Network dynamics and cell physiology. Nature Reviews: Molecular Cell Biology 2: 908-916.
116. Blanchard, P., R. Devaney, and G. Hall. 2002. Differential Equations, 2nd edition. Brooks/Cole.
117. Guckenheimer, J., and P. Holmes. 1983. Nonlinear Oscillations, Dynamical Systems, and Bifurcation of Vector Fields. Springer-Verlag.
118. Hirsch, M. W., S. Smale, and R. L. Devaney. 2004. Differential Equations, Dynamical Systems, and an Introduction to Chaos. Elsevier, Amsterdam.
119. Rinzel J. and B. Ermentrout. 1998. Analysis of neural excitability and oscillations. Pages 251-292 in C. Koch and I. Seger (eds), Methods in Neuronal Modeling. MIT Press, Cambridge.
120. Strogatz, S. 1994. Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry and Engineering. Perseus Publishing.
121. Anderson, R. A., and R. M. May. 1992. Infectious Diseases of Humans: Dynamics and Control. Oxford University Press, Oxford, U.K.
122. Blower, S. M., H. B. Gershengorn, and R. M. Grant. 2000. A tale of two futures: HIV and antiretroviral therapy in San Francisco. Science 287: 650-654.
123. Blower, S. M., A. N. Aschenbach, H. B. Gershengorn, and J. O. Kahn. 2001. Predicting the unpredictable: Transmission of drug-resistant HIV. Nature Medicine 7: 1016-1020.
124. Blower, S. M., A. N. Aschenbach, and J. O. Kahn. 2003. Predicting the transmission of drug-resistant HIV: Comparing theory with data. The Lancet Infectious Diseases 3: 10-11.
125. Butler, J. C., et al. 1996. The continued emergence of drug-resistant Streptococcus pneumoniae in the United States: An update from the CDC's Pneumococcal Sentinel Surveillance System. Journal of Infectious Diseases 174: 986-993.
126. CDC (Centers for Disease Control and Prevention). 2000. Gonorrhea-United States, 1998. Morbidity and Mortality Weekly Report 29: 538-542.
127. J. M. Coffin. 1995. HIV population dynamics in vivo: Implications for genetic variation, pathogenesis, and therapy. Science 267: 483-489.
128. Campbell, C. L., and L. V. Madden. 1990. Introduction to Plant Disease Epidemiology. John Wiley & Sons, New York.
129. Davidson, D. R. 1995. Influenza Outbreak in Basic Training, Fort Benning, GA. Medical Surveillance Monthly Report 1:7. U.S. Department of Defense, U.S. Army Center for Health Promotion and Preventive Medicine (Provisional), Aberdeen Proving Ground, MD 21010-5422.
130. Dye, C., B. G. Williams, M. A. Espinal, and M. C. Raviglione. 2002. Erasing the world's slow stain: Strategies to beat multidrug-resistant tuberculosis. Science 295: 2042-2046.
131. Earn, D.J.D., P. Rohani, B. M. Bolker, and B. T. Grenfell. 2000. A simple model for complex dynamical transitions in epidemics. Science 287: 667-670.
132. Ellner, S. P., B. A. Bailey, G. V. Bobashev, A. R. Gallant, B. T. Grenfell, and D. W. Nychka. 1998. Noise and nonlinearity in measles epidemics: Combining mechanistic and statistical approaches to population modeling. American Naturalist 151: 425-440.
133. Finkenstadt, B. F., and B. T. Grenfell. 2000. Time series modelling of childhood diseases: A dynamical systems approach Journal of the Royal Statistical Society Series C-Applied Statistics 49: 187-205.
134. Grenfell, B. T., and R. M. Anderson. 1985. The estimation of age related rates of infection from case notifications and serological data. Journal of Hygiene 95: 419-436.
135. Grenfell, B. T., O. N. Bjornstad, and B. F. Finkenstadt. 2002. Dynamics of measles epidemics: Scaling noise, determinism, and predictability with the TSIR model. Ecological Monographs 72: 185-202.
136. Hall, A., P. Pomeroy, and J. Harwood. 1992. The descriptive epizootiology of phocine distemper in the UK during 1988/89. Science of the Total Environment 115: 31-44.
137. Hethcote, H. W., and James A. Yorke. 1984. Gonorrhea Transmission Dynamics and Control. Lecture Notes in Biomathematics Vol. 56. Springer-Verlag, New York.1
138. Ho, D. D., A. U. Neumann, A. S. Perelson, W. Chen, J. M. Leonard, and M. Markowitz. 1995. Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection. Nature 373: 123-126.
139. Hudson, P. J., A. Rizzoli, B. T. Grenfell, H. Heesterbeek, and A. P. Dobson. 2002. The Ecology ofWildlife Diseases. Oxford University Press, Oxford.
140. Kermack, W. O., and W. G. McKendrick. 1927. A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London, Series A 115: 700-721.
141. Kermack, W. O., and W. G. McKendrick. 1932. Contributions to the mathematical theory of epidemics. II. The problem of endemicity. Proceedings of the Royal Society of London, Series A 138: 55-83.
142. McCallum, H., N. Barlow, and J. Hone. 2002. How should pathogen transmission be modelled? Trends in Ecology and Evolution 16: 295-300.
143. Moreno, Y., R. Pastor-Satorves, and A. Vespignani. 2002. Epidemic outbreaks in complex heterogeneous networks. European Physics Journal B 26: 521-529.
144. Newman, M. E. J. 2003. The structure and function of complex networks. SIAM Review 45: 167-256.
145. Nowak, M. A., and R. M. May. 2000. Virus Dynamics: Mathematical Principles of Immunology and Virology. Oxford University Press, Oxford, U.K.
146. Perelson, A. S., A. U. Neumann, M. Markowitz, J. M. Leonard, and D. D. Ho. 1996. HIV-1 dynamics in vivo: Virion clearance rate, infected cell life-span, and viral generation time. Science 271: 1582- 1586.
147. Perelson, A. S., and P. W. Nelson. 1999. Mathematical analysis of HIV-1 dynamics in vivo. SIAM Review 41: 3-44.
148. Rohani, P., D. J. D. Earn, and B. T. Grenfell. 1999. Opposite patterns of synchrony in sympatric disease metapopulations. Science 286: 968-971.
149. Ross, R. 1916. An application of the theory of probabilities to the study of a priori pathometry. Part I. Proceedings of the Royal Society of London, Series A 92: 204-230.
150. Schaffer, W. M., L. M. Olsen, G. L. Truty, and S. L. Fulmer. 1990. The case for chaos in childhood epidemics. Pages 138-166 in S. Krasner (ed.), The Ubiquity of Chaos. American Association for the Advancement of Science, Washington, DC.
151. Wei, X. P., S. K. Ghosh, M. E. Taylor, V. A. Johnson, E. A. Emini, P. Deutsch, J. D. Lifson, S. Bonhoeffer, M. A. Nowak, B. H. Hahn, M. S. Saag, and G. M. Shaw. 1995. Viral dynamics in humanimmunodeficiency- virus type-1 infection. Nature 373: 117-122.
152. York. J. A., H. W. Hethcote, and A. Nold. 1978. Dynamics and control of the transmission of gonorrhea. Sexually Transmitted Diseases 5: 51-56.
153. Barkley, D. 1994. Euclidean symmetry and the dynamics of rotating spiral waves. Physical Review Letters 72: 164-167.
154. Barkley, D. ezspiral_3_1.tar.gz, http://www.maths.warwick.ac.uk/ barkley/ez_software.html
155. Berg, H. C. 1983. Random Walks in Biology. Princeton University Press, Princeton, NJ.
156. Bray, W.C. 1921. A periodic reaction in homogeneous solution and its relation to catalysis. Journal of the American Chemical Society 43: 1262-1267.
157. Edelstein-Keshet, L. 1988. Mathematical Models in Biology. Random House, New York.
158. Epstein, I. R., and K. Showalter. 1996. Nonlinear chemical dynamics: Oscillations, patterns and chaos, Journal of Physical Chemistry 100: 13132-13147.
159. Field, R. J., and Burger, M. (eds.). 1985. Oscillations and Traveling Waves in Chemical Systems. Wiley, New York.
160. Fox, J. J., R. F. Gilmour, Jr., and E. Bodenschatz. 2002. Conduction block in one dimensional heart fibers. Physical Review Letters 89: 198101-4.
161. Gierer, A., and H. Meinhardt. 1972. A theory of biological pattern formation. Kybernetik 12: 30-39.
162. Goel, N., and N. Richter-Dyn. 1974. Stochastic Models in Biology. Springer, New York.
163. Gurdon, J., and P.-Y. Bourillot. 2001. Morphogen gradient interpretation. Nature 413: 797-803.
164. Hodges, A. 2000. Alan Turing: The Enigma Walker & Co., London.
165. Keener, J. P. 1989. Knotted scroll wave filaments in excitable media. Physica D 34: 378-390.
166. Monteiro, A., V. French, G. Smit, P. Brakefield, and J. Metz. 2001. Butterfly eyespot patterns: Evidence for specification by a morphogen diffusion gradient. Acta Biotheoretica 49: 77-88.
167. Murray, J. D. 1993. Mathematical Biology. Springer, New York.
168. Odell, G., and G. Oster. 1980. The mechanical basis of morphogenesis III: A continuum model of cortical contraction in amphibian eggs. Journal of Mathematical Biology 65-89.
169. Odell, G., G. Oster, B. Burnside, and P. Alberch. 1980. A mechanical model for epithelial morphogenesis. Journal of Mathematical Biology 9: 291-295.
170. Odell, G., G. Oster, P. Alberch, and B. Burnside. 1981. The mechanical basis of morphogenesis I: Epithelial folding and invagination. Developmental Biology 85: 446-462.
171. Strigini, M., and S. Cohen. 1999. Formation of morphogen gradients in the Drosophila wing. Seminars in Cell and Developmental Biology. 10: 335-344.
172. Strogatz, S. 2003. Sync: The Emerging Science of Spontaneous Order. Hyperion, New York.
173. Turchin, P. 1998. Quantitative Analysis of Movement: Measuring and Modeling Population Redistribution in Animals and Plants. Sinauer Associates, Sunderland MA.
174. Turing, A. M. 1952. The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London, Series B 237: 37-72.
175. Winfree, A. T. 1987. When Time Breaks Down. Princeton University Press, Princeton, NJ.
176. Winfree, A. T. 1991. Varieties of spiral wave behavior: An experimentalist's approach to the theory of excitable media. Chaos 1: 303-334.
177. Winfree, A. T., S. Caudie, G. Chen, P. McGuire, and Z. Szilagy. 1996. Quantitative optical tomography of chemical waves and their organizing centers. Chaos 6: 617-626.
178. Winfree, A. T., and S. H. Strogatz. 1983. Singular filaments organize chemical waves in three dimensions: 3. Knotted waves. Physica D 9: 333-345.
179. Witkowski, F. X., L. J. Leon, P. A. Penkoske, W. R. Giles, W. L. Ditto, and A. T. Winfree. 1998. Spatiotemporal evolution of ventricular fibrillation. Nature 392: 78-82.
180. Adami, C. 2002. Ab initio modeling of ecosystems with artificial life. Natural Resource Modeling 15: 133-145.
181. Blower, S. M., and H. Dowlatabadi. 1994. Sensitivity and uncertainty analysis of complex models of disease transmission: An HIV model, as an example. International Statistical Review 2: 229-243.
182. Blower, S. M., H. B. Gershengorn, and R. M. Grant. 2000. A tale of two futures: HIV and antiretroviral therapy in San Francisco. Science 287: 650-654.
183. Bolker, B. M., and S.W. Pacala. 1999. Spatial moment equations for plant competition: Understanding spatial strategies and the advantages of short dispersal. American Naturalist 153: 575-602.
184. Bolker, B. M., S. W. Pacala, and S. A. Levin. 2000. Moment methods for stochastic processes in continuous space and time. Pages 388-411 in Dieckmann et al. (2000).
185. Bonabeau, E. 2002. Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, U.S.A. 99, Suppl. 3: 7280-7287.
186. Brook, B. W., J. R. Cannon, R. C. Lacy, C. Mirande, and R. Frankham. 1999. Comparison of the population viability analysis packages GAPPS, INMAT, RAMAS, and Vortex for the whooping crane (Grus americana). Animal Conservation 2: 23-31.
187. Chan, K., A. Saltelli, and S.Tarantola. 2000. Winding Stairs: A sampling tool to compute sensitivity indices. Statistics and Computing 10: 187-196.
188. Chow, S. S., C. O.Wilke, C. Ofria, R. E. Lenski, and C. Adami. 2004. Adaptive radiation from resource competition in digital organisms. Science 305: 84-86.
189. Chowdhury, D., K. Nishinari, and A. Schadschneider. 2004. Self-organized patterns and traffic flow in colonies of organisms: from bacteria and social insects to vertebrates. Phase Transitions 77: 601-624.
190. Cleavelend, S., G. R. Hess, A. P. Dobson, M. K. Laurenson, H. I. McCallum, M. G. Roberts, and R. Woodroffe. 2002. The role of pathogens in biological conservation. Pages 139-150 in Hudson et al. (2002).
191. DeAngelis, D. L., and L. J. Gross (eds.). 1992. Individual-Based Models and Approaches in Ecology. Chapman and Hall, New York.
192. DeAngelis, D. L., L. J. Gross, M. A. Huston, W. F. Wolff, D. M. Fleming, E. J. Comiskey, and S. M. Sylvester. 1998. Landscape modeling for everglades ecosystem restoration. Ecosystems 1: 64-75.
193. Dieckmann, U., R. Law, and J.A.J. Metz. 2000. The Geometry of Ecological Interactions: Simplifying Spatial Complexity. Cambridge University Press, Cambridge, U.K.
194. Durrett, R. 1999. Stochastic spatial models. SIAM Review 41: 677-718.
195. Durrett, R., and S. A. Levin. 1994. The importance of being discrete (and spatial). Theoretical Population Biology 35: 252-283.
196. Eames, K.T.D. and M. Keeling. 2003. Contact tracing and disease control. Proceedings of the Royal Society of London, Series B 270: 2565-2571.
197. Ellner, S. P., and John Fieberg. 2003. Using PVA for management despite uncertainty: Effects of habitat, hatcheries, and harvest on salmon. Ecology 84: 1359-1369.
198. Enquist, B. J., and K. J. Niklas. 2001. Invariant scaling relations across tree-dominated communities. Nature 410: 655-660.
199. Gould, S. J. 1990. Wonderful Life: The Burgess Shale and The Nature of History. W. W. Norton and Company, New York.
200. Harvell, C. D., K. Kim, J. M. Burkholder, R. R. Colwell, P. R. Epstein, J. Grimes, E. E. Hofmann, E. K. Lipp, A.D.M.E. Osterhaus, R. Overstreet, J.W. Porter, G.W. Smith, and G. R. Vasta. 1999. Emerging marine diseases: Climate links and anthropogenic factors. Science 285: 1505-1510.
201. Helbing, D., I. J. Farkas, and T. Vicsek. 2000. Simulating dynamical features of escape panic. Nature 407: 487-490.
202. Hess, G. 1996. Disease in metapopulation models: Implications for conservation. Ecology 77: 1617-1632.
203. Hiebeler, D. 2000. Populations on fragmented landscapes with spatially structured heterogeneities: Landscape generation and local dispersal. Ecology 81: 1629-1641.
204. Hudson, P. J., A. Rizzoli, B. T. Grenfell, H. Heesterbeek, and A. P. Dobson (eds.). 2002. The Ecology of Wildlife Diseases. Oxford University Press, Oxford, U.K.
205. Hurtt, G. C., S. W. Pacala, P. R. Moorcroft, J. P. Caspersen, E. Shevliakova, and B. Moore. 2002. Projecting the future of the US Carbon sink. Proceedings of the National Academy of Sciences U.S.A. 99: 1389-1394.
206. Huston, M., D. deAngelis, and W. Post. 1988. New computer models unify ecological theory. Bio- Science 38: 682-691.
207. Jansen, M.J.W., W.A.H. Rossing, and R. A. Daamen. 1994. Monte Carlo estimation of uncertainty contributions from several independent multivariate sources. Pages 334-343 in J. Gasman and G. van Straten (eds.), Predictability and Nonlinear Modelling in Natural Sciences and Economics. Kluwer Academic, Dordrecht.
208. Keeling, M. J., H. B. Wilson, and S. W. Pacala. 2000. Reinterpreting space, time lags, and functional responses in ecological models. Science 290: 1758-1761.
209. Lacy, R. C., M. Borbat, and J. P. Pollak. 2003. VORTEX: A stochastic simulation of the extinction process, version 9. Chicago Zoological Society, Brookfield, IL. Online at http://www.vortex9.org
210. Lenski, R. E., C. Ofria, R. T. Pennock, and C. Adami. 2003. The evolutionary origin of complex features. Nature 423: 139-144.
211. Lindenmayer, D. B., R. C. Lacy, and M. L. Pope. 2000. Testing a simulation model for population viability analysis. Ecological Applications 10: 580-597.
212. Lindenmayer, D. B., and R. C. Lacy. 2002. Small mammals, habitat patches and PVA models: a field test of model predictive ability. Biological Conservation 103: 247-265.
213. McKay, M. D. 1992. Latin Hypercube Sampling as a tool in uncertainty analysis of computer models. Pages 557-564 in J. J. Swain, D. Goldsman, R. C. Crain, and J. R. Wilson (eds.), Proceedings of the 1992Winter Simulation Conference. Association for Computing Machinery, Arlington, VA. Online at portal.acm.org
214. McKay, M. D., W. J. Conover, and R. J. Beckman. 1979. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 22: 239-245.
215. Miller, P. S., and R. C. Lacy. 2003. VORTEX: A stochastic simulation of the extinction process, version 9.21 user's manual. Conservation Breeding Specialist Group (SSC/IUCN), Apple Valley, MN. Online at http://www.vortex9.org/v921manual.pdf
216. Moorcroft, P. R., G. C. Hurtt, and S.W. Pacala. 2001. A method for scaling vegetation dynamics: The ecosystem demography model (ED). Ecological Monographs 74: 557-586
217. Ofria, C., and C. O. Wilke. 2004. Avida: A software platform for research in computational evolutionary biology. Artificial Life 10: 191-229.
218. O'Neill, B. 2003. Digital evolution. PLOS Biology 1: 11-14.
219. Parrish, J. K., S. V. Viscido, and D. Grünbaum. 2002. Self-organized fish schools: An examination of emergent properties. Biological Bulletin 202: 296-305.
220. Peck, S. L. 2004. Simulation as experiment: A philosophical reassessment for biological modeling. Trends in Ecology and Evolution 19: 530-534.
221. Penn, A. M., W. B. Sherwin, G. Gordon, D. Lunney, A. Melzer, and R. C. Lacy. 2000. Demographic forecasting in koala conservation. Conservation Biology 14: 629-638.
222. Rand, D. A. 1999. Correlation equations for spatial ecologies. Pages 99-143 in J. McGlade (ed.) Advanced Ecological Theory. Blackwell Scientific Publishing, London.
223. Ray, T. S. 1991. An approach to the synthesis of life. Pages 371-408 in C. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen (eds.), Artificial Life II. Santa Fe Institute Studies in the Sciences of Complexity vol. X. Addison-Wesley, Redwood City, CA.
224. Ray, T. S. 1992. Evolution, ecology and optimization of digital organisms. Santa Fe InstituteWorking Paper 92-08-042.
225. Rice, J. A., T. J. Miller, K. A. Rose, L. B. Crowder, E. A. Marschall, A. S. Trebitz, and D. L. DeAngelis. 1993. Growth rate variation and larval survival: Inferences from an individual-based size-dependent predation model. Canadian Journal of Fisheries and Aquatic Sciences 50: 133-142.
226. Smith, D. J., S. Forrest, D. H. Ackley, and A. S. Perelson. 1999. Variable efficacy of repeated annul unfluenza vaccination. Proceedings of the National Academy of Sciences USA 96: 14001-14006.
227. Snyder, R. E., and P. Chesson. 2004. How the spatial scales of dispersal, competition, and environmental heterogeneity interact to affect coexistence. American Naturalist 164: 633-650.
228. Sobol', I. M. 1993. Sensitivity analysis for nonlinear mathematical models. Mathematical Modeling and Computational Experiment 1: 407-414. [English translation from Matematicheskoe Modelirovanie 2: 112-118 (1990)].
229. van Balen, M. 2000. Pair approximations for different spatial geometries. Pages 359-387 in U. Dieckman, R. Law, and J.A.J. Metz (eds.), The Geometry of Ecological Interations: Simplifying Spatial Complexity. Cambridge University Press, Cambridge, U.K.
230. Waide, R. B., M. R. Willig, C. F. Steiner, G. Mittelbach, L. Gough, S. I. Dodson, G. P. Juday, and R. Parmenter. 1999. The relationship between productivity and species richness. Annual Review of Ecology and Systematics 30: 257-300.
231. Ward, J. R., and K. D. Lafferty. 2004. The elusive baseline of marine disease: Are diseases in ocean ecosystems increasing? PLOS Biology 2: 542-547.
232. Wilke, C. O., J. L. Wang, C. Ofria, R. E. Lenski, and Christoph Adami. 2001. Evolution of digital organisms at high mutation rates leads to survival of the flattest. Nature 412: 331-333.
233. Wilke, C. O., and C. Adami. 2002. The biology of digital organisms. Trends in Ecology and Evolution 17: 528-532.
234. Yedid, G., and G. Bell. 2001. Evolution in an electronic microcosm. American Naturalist 157: 465-487.
235. Banks, H. T., and K. A. Murphy. 1989. Estimation of nonlinearities in parabolic models for growth, predation, and dispersal of populations. Journal of Mathematical Analysis and Applications 141: 580-602.
236. Banks, H. T., L. W. Botsford, F. Kappel, and C. Wang. 1991. Estimation of growth and survival in size-structured cohort data-an application to larval striped bass (Morone saxatilis). Journal of Mathematical Biology 30: 125-150.
237. Bayarri, M. J., and J. O. Berger. 2004. The interplay of Bayesian and frequentist analysis. Statistical Science 19: 58-80.
238. Bickel, P. J, C.A.J. Klassen, Y. Ritov, and J. A. Wellner. 1993. Efficient and Adaptive Estimation for Semiparametric Models. Johns Hopkins University Press, Baltimore, MD.
239. Bolker, B. M., S. W. Pacala, and W. J. Parton, Jr. 1998. Linear analysis of soil decomposition: insights from the Century model. Ecological Applications 8: 425-439.
240. Burnham, K. P., and D. R. Anderson. 2002. Model Selection and Multi-Model Inference. Springer, New York.
241. Calder, C., M. Lavine, P. Muller, and J. S. Clark. 2003. Incorporating multiple sources of stochasticity into dynamic population models. Ecology 84: 1395-1402.
242. Caswell, H. 1976. The validation problem. Pages 313-325 in B. C. Patten (ed.), Systems Analysis and Simulation in Ecology. Academic Press, New York, Vol. 4.
243. Collins, A. S., S.C.J. Sumner, S. J. Borghoff, and M. A. Medinsky. 1999. A physiological model for tert-amyl methyl ether and tert-amyl alcohol: hypothesis testing of model structures. Toxicological Sciences 49: 15-28.
244. Colwell, R. 1996. Global climate and infectious disease: The cholera paradigm. Science 274: 2025- 2031.
245. Cox, P., R. Betts, C. Jones, S. Spall, and I. Totterdell. 2000. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408, 184-187.
246. Cox, P. 2001. Description of the "TRIFFID" Dynamic Global Vegetation Model. Hadley Centre Technical Note 24. Available at http://www.met-office.gov.uk/research/hadleycentre/pubs
247. Cramp, D. G., and E. R. Carson. 1979. Dynamics of blood glucose and its regulating hormones. In D. A. Linkens (ed.), Biological Systems, Modeling and Control. IEE, London.
248. Davison, A. C., and D. V. Hinkley. 1997. Bootstrap Methods and Their Application. Cambridge University Press, Cambridge, U.K.
249. de Valpine, P. 2004. Monte Carlo state-space likelihoods by weighted posterior kernel density estimation. Journal of the American Statistical Association 99: 523-536.
250. Efron, B. 2004. The estimation of prediction error: Covariance penalties and cross-validation. Journal of the American Statistical Association 99: 619-632.
251. Ellner, S., A. R. Gallant, and J. Theiler. 1995. Detecting nonlinearity and chaos in epidemic data. Pages 229-247 in D. Mollison (ed.), Epidemic Models: Their Structure and Relation to Data. Cambridge University Press, Cambridge, U.K.
252. Ellner, S. P., B. A. Bailey, G. V. Bobashev, A. R. Gallant, B. T. Grenfell, and D. W. Nychka. 1998. Noise and nonlinearity in measles epidemics: combining mechanistic and statistical approaches to population modeling. American Naturalist 151: 425-440.
253. Ellner, S. P., Y. Seifu, and Robert H. Smith. 2002. Fitting population models to time series data by gradient matching. Ecology 83: 2256-2270.
254. Fussman, G., S. P. Elner, K. W. Shertzer, and N. G. Hairston, Jr. 2000. Crossing the Hopf bifurcation in a live predator-prey system. Science 290: 1358-1360.
255. Gallant, A. R. 1987. Nonlinear Statistical Models. Wiley, New York.
256. Gelman, A., D. B. Rubin, J. B. Carlin, and H. S. Stern. 2003. Bayesian Data Analysis, 2nd edition. Chapman & Hall/CRC Press, Boca Raton, FL.
257. Gourièroux, C., and A. Montfort. 1996. Simulation-based Econometric Inference. Oxford University Press, Oxford, U.K.
258. Hairston, N. G., Jr., C. M. Kearns, and S. Ellner. 1996. Phenotypic variation in a zooplankton egg bank. Ecology 77: 2382-2392.
259. Hett, J. M., and R. J. O'Neill. 1974. Systems analysis of the Aleut ecosystem. Artic Anthropology 11: 31-40.
260. Hilborn, R., and M. Mangel. 1997. The Ecological Detective: Confronting Models with Data. Princeton University Press, Princeton, NJ.
261. Kendall, B. E., C. J. Briggs, W. W. Murdoch, P. Turchin, S. P. Ellner, E. McCauley, R. Nisbet, and S. N. Wood. 1999. Why do populations cycle? A synthesis of statistical and mechanistic modeling approaches. Ecology 80: 1789-1805.
262. Ludwig, D., and C. J. Walters. 1985. Are age-structured models appropriate for catch-effort data? Canadian Journal of Fisheries and Aquatic Science 42: 1066-1072.
263. Niklas, K. J. 1994. Plant Allometry: the Scaling of Formand Process. University of Chicago Press, Chicago.
264. Nisbet, R. M., and W.S.C. Gurney. 1982. Modelling Fluctuating Populations. Wiley, New York.
265. NREL (Natural Resource Ecology Laboratory). 2001. Century soil organic matter model version 5, user's guide and reference. Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO. Online at http://www.nrel.colostate.edu/projects/century5
266. Parton, W., D. Schimel, C. Cole, and D. Ojima. 1987. Analysis of factors controlling soil organic levels of grasslands in the Great Plains. Soil Science Society of America Journal 51: 1173-1179.
267. Parton, W., J. Stewart, and C. Cole. 1988. Dynamics of C, N, P and S in grassland soils: A model. Biogeochemistry 5: 109-131.
268. Pascual, M., X. Rodo, S. P. Ellner, R. Colwell, and M. J. Bouma. 2000. Cholera dynamics and the El Niñ-Southern Oscillation. Science 289: 1766-1769.
269. Rees, M., A. Sheppard, D. briese, and M. Mangel. 1999. Evolution of size-dependent flowering in Onopordum illyricum: A quantitative assessment of the role of stochastic selection pressures. American Naturalist 154: 628-651.
270. Ruppert, D., M. P. Wand, and R. U. Carroll. 2003. Semiparametric Regression. Cambridge University Press, New York.
271. Seber, G.A.F., and C. J. Wild. 1989. Nonlinear Regression. Wiley, New York.
272. Turchin, P., and S. P. Ellner. 2000. Living on the edge of chaos: Population dynamics of Fennoscandian voles. Ecology 81: 3099-3116.
273. Turchin, P., S. N. Wood, S. P. Ellner, B. E. Kendall, W. W. Murdoch, A. Fischlin, J. Casas, E. McCauley, and C. J. Briggs. 2003. Dynamical effects of plant quality and parasitism on population cycles of larch budmoth. Ecology 84: 1207-1214.
274. Venables, W. N., and B. D. Ripley. 2002. Modern Applied Statistics with S, 4th edition. Springer, New York.
275. Veilleux, B. G. (1976). The analysis of a predatory interaction between Didinium and Paramecium. MS Thesis, University of Alberta.
276. Von Foerster, H., L. W. Amiot, and P. M. Mora. 1960. Doomsday: Friday, 13 November, A.D. 2026. Science 132: 1291-1295.
277. Waller, L. A., D. Smith, J. E. Childs, and L. A. Real. 2003. Monte Carlo assessments of goodness-of-fit for ecological simulation models. Ecological Modelling 164: 49-63.
278. West, G. B., J. H. Brown, and B. J. Enquist. 1997. A general model for the origin of allometric scaling laws in biology. Science 276: 122-126.
279. Wood, S. N. 1994. Obtaining birth and death rate patterns from structured population trajectories. Ecological Monographs 64: 23-44.
280. Wood, S. N. 1999. Semi-parametric population models. Aspects of Applied Biology 53: 41-50.
281. Wood, S. N. 2001. Partially specified ecological models. Ecological Monographs 71: 1-25.
282. Wood, S. N. 2003. Thin-plate regression splines. Journal of the Royal Statistical Society, Series B 65: 95-114.