Ecological Circuitry Collaboratory

BIBLIOGRAPHY

Many of the readings on modeling come from Tony Starfield, others have been added by collaboratory participants.

General Modeling | Population models | Ecosystem Models | Spatial Models | Expert Systems and Qualitative Models | Linear Programming and Optimization | Decision-making under uncertainty | Publishing Models | Interdisciplinary Modeling | Biodiversity and Ecosystem Function | Philosophy and Practice of Science | Likelihood Models | Mercury

General Modeling

• Beres, D.L. and D.M. Hawkins. 2001. Plackett-Burman technique for sensitivity analysis of many-parametered models. Ecological Modelling 141: 171-183.
• Canham, C. D., Cole, J. J., and Lauenroth, W., eds. in press The Role of Models in Ecosystem Science, Cary Conference IX. Springer-Verlag, NY.
• Carpenter, S., W. Brock and P. Hanson, 1999. Ecological and social dynamics in simple models of ecosystem management, Conservation Ecology 3(2):4.
• DeAngelis, D. L. and L. J. Gross, eds. 1992. Individual-based models and approaches in ecology: populations, communities, and ecosystems. Chapman & Hall, N.Y. 525 pp.
• Lemons, J., ed. 1996. Scientific uncertainty and environmental problem solving. Blackwell Science, Cambridge, Mass. 433 pp.
• O'Neill, R. V., D. L. DeAngelis, J. B. Waide and T. F. H. Allen. 1986. A hierarchical concept of ecosystems. Princeton University Press, Princeton. 253 pp.
• Oreskes, N., K. Shrader-Frechette and K. Belitz. 1994. Verification, validation and confirmation of numerical models in the earth sciences. Science 263: 641-646.
• Tukey, J. W. 1977. Exploratory data analysis. Addison-Wesley, Reading, Mass. 688 pp.
• Schrage, M. 1999, Serious Play: How the Worlds Best Companies Simulate to Innovate, Harvard Business School Press.
• Starfield, A.M. 1997. A pragmatic approach to modeling for wildlife management. J. Wildl. Manage. 61:261-270.
• Wallace, W. A., ed. 1994. Ethics in Modeling. Oxford, OX, U.K. 266 pp.

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Population models

• Anderson, D. R. 1974. Optimal exploitation strategies for an animal population in a Markovian environment: a theory and an example. Ecology 56: 1281-1298.
• Beddington, J. R. and R. M. May. 1977. Harvesting natural populations in a randomly fluctuating environment. Science 197:463-465.
• Clark, C. W. and D. E. Tait. 1982. Sex-selective harvesting of wildlife populations. Ecological Modelling 14: 251-260.
• Starfield, A. M., J. D. Roth and K. Ralls. 1995. "Mobbing" in Hawaiian monk seals: the value of simulation modeling in the absence of apparently crucial data. Conservation Biology 9(1): 166-174.
• Stocker, M. and C. J. Walters. 1984. Dynamics of a vegetation-ungulate system and its optimal exploitation. Ecological Modelling 25: 151-165.
• Temple, S. A. and J. R. Cary. 1988. Modeling dynamics of habitat-interior bird populations in fragmented landscapes. Conservation Biology 2: 340-347.

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Ecosystem Models

• Cohen, Y., Pastor, J., Vincent, T.L. 2000. Evolutionary strategies and nutrient cycling in ecosystems. Evolutionary Ecology Research 2: 719-743.
• Starfield, A. M. and F. S. Chapin. 1996. A dynamic model of transient changes in arctic and boreal vegetation in response to climate and land use change. Ecological Applications 6(3): 842-864.
• Starfield, A. M., D. H. M. Cumming, R. D. Taylor and M. S. Quadling. 1993. A frame-based paradigm for dynamic ecosystem models. AI Applications 7(2&3): 1-13.
• Tester, J. R. A. M. Starfield and L. E. Frelich. 1997. Modeling for ecosystem management in Minnesota pine forests. Biological Conservation 80: 313-324.

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Spatial Models

• Cale, W. G., G. M. Henebry and J. A. Yeakley. 1989. Inferring process from pattern in natural communities. BioScience 39: 600-605.
• Rupp, T.S., A.M. Starfield and F.S. Chapin III. 2000. A frame-based spatially explicit model of subarctic vegetation response to climatic change: comparison with a point model. Landscape Ecology 15:383-400.
• Rupp, T.S., F.S. Chapin and A.M. Starfield. 2000. Response of subarctic vegetation to transient climatic change on the Seward Peninsula in north-west Alaska. Global Change Biology 6:541-555.

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Expert Systems and Qualitative Models

• Davis, J. R., J. H. L. Hoare and P. M. Nanninga. 1986. Developing a fire behaviour expert system for Kakadu National Park, Australia. Journal of Environmental Management 22: 215-227.
• Loehle, C. 1987. Applying artificial intelligence techniques to ecological modelling. Ecological Modelling 38: 191-212.
• Noble, I. R. 1987. The role of expert systems in vegetation science. Vegetation 69: 115-121.
• Plant, R. E. and N. D. Stone. 1991. Knowledge-based systems in agriculture. McGraw-Hill, N.Y. 364 pp.
• Starfield, A. M. 1990. Qualitative, rule-based modeling. BioScience 40: 601-604.
• Starfield, A. M., B. P. Farm and R. H. Taylor. 1989. A rule-based ecological model for the management of an estuarine lake. Ecological Modelling 46: 107-119.

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Linear Programming and Optimization

• Bottoms, K. E. and E. T. Bartlett. 1975. Resource allocation through goal programming. Journal of Range Management 28(6): 442-447.
• Charnes, A., K. E. Haynes, J. E. Hazleton and M. J. Ryan. 1975. A hierarchical goal-programming approach to environmental land use management. Geographical Analysis 7: 121-130.
• Chechile, R. A. and S. Carlisle, eds. 1991. Environmental decision making: a multidisciplinary perspective. van Nostrand, Reinhold, N.Y. 296 pp.
• Ignizio, J. P. 1982. On the (re)discovery of fuzzy goal programming. Decision Science 13: 331-336.
• Mangel, M. and C. W. Clark. 1988. Dynamic modeling in behavioral ecology. Princeton Univ. Press, Princeton. 308 pp.
• Porterfield, R. L. 1974. A goal programming model to guide and evaluate tree improvement programs. Forest Science 22(4): 417-430.
• Snyder, S. A., L.E. Tyrell and R.G. Haight, 1999, An optimization approach to selecting research natural areas in national forests, Forest Science 45(3):458-469.

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Decision-making under uncertainty

• Baird, B. F. 1989. Managerial decisions under uncertainty: an introduction to the analysis of decision making. J. Wiley & Sons, N.Y. 530 pp.
• Behn, R. D. and J. W. Vaupel. 1982. Quick analysis for busy decision makers. Basic Books, N.Y. 415 pp.
• Campbell, G. E. and G. A. Mendoza. 1988. Adapting modeling to generate alternatives (MGA) techniques to forest level planning. Journal of Environmental Management 26: 151-161.
• Daellenbach, H. G. 1994. Systems and decision making: a management science approach. J. Wiley & Sons, N.Y. 545 pp.
• DiNardo, G., D. Levy and B. Golden. 1989. Using decision analysis to manage Maryland's river herring fishery: an application of AHP. Journal of Environmental Management 29: 193-213.
• de Geus, A. P. 1988, Planning as learning, Harvard Business Review, March-April 1988:70-74.
• Eden, C. 1989. Using cognitive maps for strategic options development and analysis (SODA), in J. Rosenhead (ed.) Rational Analysis for a Problematic World, John Wiley.
• Goodwin, P. and G. Wright. 1991. Decision analysis for management judgment. J. Wiley & Sons, N.Y. 308 pp.
• Gregory, R., R. Keeney and D. von Winterfeldt. 1992. Adapting the environmental impact statement process to inform decision makers. Journal of Policy Analysis & Management 11(1): 58-75.
• Keeney, R. 1992. Value focused thinking: A path to creative decision making. Harvard University Press, Cambridge, MA. 416 pp.
• Kirkwood, C. W. Strategic Decision Making: Multiobjective Decision Analysis with Spreadsheets.
• Maguire, L. A. and R. C. Lacy. 1990. Allocating scarce resources for conservation of endangered subspecies: partitioning zoo space for tigers. Conservation Biology 4(2): 157-166.
• Massey, A. and W.A. Wallace, 1996, Understanding and facilitating group problem structuring and formulation: mental representations, interactions and representation aides, Decision Support Systems 17:253-274.
• Mendoza, G. A. and W. Sprouse. 1989. Forest planning and decision making under fuzzy environments: an overview and illustration. Forest Science 35(2): 481-502.
• Oliver, R. M. and J. Q. Smith, eds. 1990. Influence diagrams, belief nets and decision analysis. J. Wiley & Sons, N.Y. 465 pp.
• Phillips, L. D. and M. C. Phillips. 1993. Facilitated work groups: theory and practice. Journal of the Operational Research Society 44: 533-549.
• Ralls, K. and A. M. Starfield. 1995. Choosing a management strategy: two structured decision-making methods for evaluating the predictions of stochastic simulation models. Conservation Biology 9(1): 175-181.
• Saaty, T. L. 1982. Decision making for leaders: the analytical hierarchy process for decisions in a complete world. Lifetime Learning Publications. Belmont, CA. 291 pp.
• Stewart, T. J. 1992. A critical survey of the status of multiple criteria decision making theory and practice. Omega 20: 569-586.
• Tversky, A. and D. Kahneman. 1974. Judgment under uncertainty: heuristics and biases. Science 185:1124-1131.
• von Winterfeldt, D. and W. Edwards. 1986. Decision analysis and behavioral research. Cambridge University Press, N.Y. 604 pp.
• Wack, P. 1985. Scenarios: uncharted waters ahead, Harvard Business Review, Sept-Oct 1985, 73-89.

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Publishing Models

• Aber, J.D. 1997. Why don't we believe the models? Bulletin of the Ecological Society of America, 78(3):232-233. Suggests content that all modeling papers should contain.

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Interdisciplinary Modeling

• Nicolson, C.R., Starfield, A.M., Kofinas, G.P., and Kruse, J.A. 2002. Ten heuristics for interdisciplinary modeling projects. Ecosystems 5:376-384.

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Biodiversity and Ecosystem Function

• Hunt, H. W. and D. H. Wall. 2002. Modelling the effects of loss of soil biodiversity on ecosystem function. Global Change Biology 8(1): 33-50.
• Grime, J. P. 1997. Ecology - Biodiversity and ecosystem function: The debate deepens. Science 277(5330): 1260-1261.
• Huston, M. A. 1997. Hidden treatments in ecological experiments: Re-evaluating the ecosystem function of biodiversity. Oecologia 110(4): 449-460.
• Loreau, M., Naeem, S., Inchausti, P., Bengtsson, J., Grime, J. P., Hector, A., Hooper, D.U., Huston, M. A., Raffaelli, D., Schmid, B., Tilman, D., Wardle, D.A. 2001. Ecology: Biodiversity and ecosystem functioning: Current knowledge and future challenges. Science 294(5543): 804-808.
• Naeem, S. 2002. Ecosystem consequences of biodiversity loss: The evolution of a paradigm. Ecology (Washington D C) 83(6): 1537-1552.

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Philosophy and Practice of Science

• Levin, S. A. 1992. The problem of pattern and scale in ecology. Ecology 73(6):1943-1967.
• Weiner, J. 1995. On the practice of ecology. Journal of Ecology 83: 153-158.

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Likelihood Models

• Hilborn, R. and Mangel, M. 1997. The Ecological Detective. Princeton University Press.
• Pacala, S. W., Canham, C. D., Saponara, J., Silander, J. A., Jr., Kobe, R. K., Ribbens, E. 1996. Forest models defined by field measurements: estimation, error analysis and dynamics. Ecological Monographs 66(1):1-43.

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Mercury

• Raloff, J. 2003. Why the mercury falls: heavy-metal rains may trace oxidants, including smog. Science News 163:72-74.
• Lindberg, S.E., Dong, W., Meyers, T. 2002. Transpiration of gaseous elemental mercury through vegetation in a subtropical wetland in Florida. Atmospheric Environment 36:5207-5219.
• Zhang, H. and Lindberg, S.E. 1999. Processes influencing the emission of mercury from soils: a conceptual model, J. Geophys. Res: 104, 21889-21896.
• Lindberg, S. E., P. J. Hanson, T.P. Meyers, and K-Y Kim. 1998. Micrometeorological studies of air/surface exchange of mercury over forest vegetation and a reassessment of continental biogenic mercury emissions. Atmos. Envir. 32:895-908.
• Carpi, A. and S.E. Lindberg. 1998. Application of a teflon dynamic flux chamber for quantifying soil mercury fluxes: tests and results over background soils. Atmos. Envir. 32:873-882.
• Lindberg, S. E. and W. J. Stratton. 1998. Atmospheric mercury speciation: Concentrations and behavior of reactive gaseous mercury in ambient air. Envir. Sci. & Technol. 32:49-57.
• Hanson, P. J., T. Tabberer, and S. E. Lindberg. 1997. Emissions of Mercury Vapor from Tree Bark. Atmos. Envir. 31: 777-780.
• Kim, KH., P. J. Hanson, M. O. Barnett, and S. E. Lindberg. 1997. Biogeochemistry of mercury in the air-soil-plant system. Met. Ions Biol. Syst., 34: 185212.
• Lindberg, S. E. 1996. Forests and the Global Biogeochemical Cycle of Mercury: The Importance of Understanding Air/vegetation Exchange Processes. IN: Baeyens, W., Ebinghaus, R., Vasiliev, O. (eds.): Global and Regional Mercury Cycles: Sources, Fluxes and Mass Balances. NATOASISeries, Vol. 21, Kluwer Academic Publishers, Dordrecht, The Netherlands, 359-380.
• Meyers, T.P., M.E. Hall, and S.E. Lindberg. 1996. Use of the modified Bowen ratio technique to measure fluxes of trace gases. Atmos. Envir. 30: 3321-3329.
• Kim, K.H., Lindberg, S. E., and Meyers, T. P. 1995. Micrometeorological measurements of mercury fluxes over background forest soils in eastern Tennessee. Atmos. Envir. 27:267-282.
• Kim, K.-H and S. E. Lindberg. 1995. Design and initial tests of a dynamic enclosure chamber for measurements of vapor-phase mercury fluxes over soils. Water, Air, Soil, Pollut. 80: 1059-1068.
• Vermette, S.J., S.E. Lindberg, and N. Bloom. 1995. Field tests for a regional mercury deposition network: Sampling design and test results. Atmos. Envir. 29: 1247-1252.
• Johnson, D. W. and S. E. Lindberg. 1995. Sources, sinks, and cycling of mercury in forested ecosystems. Water, Air, Soil, Pollut. 80: 1069-1077.
• Lindberg, S.E., J.G. Owens, and W. Stratton. 1994. Application of throughfall methods to estimate dry deposition of mercury. IN J. Huckabee and C. Watras, (Eds.), Mercury as A Global Pollutant, pp. 261-272. Lewis Publ.
• Lindberg, S.E., T.P. Meyers, G.E. Taylor, R.R. Turner, and W.H. Schroeder. 1992. Atmosphere/surface exchange of mercury in a forest: Results of modeling and gradient approaches. J. Geophys. Res. 97: 2519-2528.
• Lindberg, S. E., R.R. Turner, T.P Meyers, G.E Taylor, and W.H. Schroeder. 1991. Atmospheric concentrations and deposition of airborne mercury to Walker Branch Watershed. Water, Air, Soil, Pollut. 56:577-594.

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