Graduate Faculty Memberships
Conservation Biology; Ecology, Evolution, and Behavior; Wildlife Conservation.
Modeling of populations and ecosystems.
I am an applied mathematician who enjoys using mathematics and computers to help solve 'real life' problems. I began by working with engineers, but started, some 20 years ago, to build models to aid management decisions in the game parks of Southern Africa. What was essentially a hobby grew into a new career. Today I would describe myself as an ecological modeler.
Two broad questions fascinate me. The first is how to use models effectively in ecology and conservation biology. It is obvious that the modeling approaches borrowed from engineers and physical scientists do not transplant well. My 1991 book with Andrew Bleloch develops a rather personal approach to ecological modeling, an approach that is still evolving. The second question is how to teach modelling to students who may not be skilled in mathematics and computing. Working from the hypothesis that modeling is a creative, logical subject rather than a mathematical one, and that it is learned (by doing) rather than taught (through lectures) I enjoy helping students to develop modeling skills. To be able to model alters the way a student looks at his or her subject; it is exciting to watch students discover this.
My current research work is in two separate areas. The first looks at how decisions are made in conservation biology and attempts to develop models that feed into a formal multi-objective decision process that reflects both the uncertainty inherent in conservation problems and the various interests of the players in conservation decisions. The two publications on the Hawaiian monk seal cited describe my most recent work in this area.
The second area of research work is in the development of new paradigms for modeling ecosystem dynamics. This work has drawn on developments in expert systems technology and has led to rule-based modeling approaches (where rules replace equations) as well as what I call "frame-based' modeling. The objective here is to be able to develop, very quickly, models that refine the gross features of system dynamics, and then to refine the models as necessary. So far this approach has been applied to forest succession in Minnesota, elephant-tree dynamics in Zimbabwe, and the transient effects of global warming on Alaskan tundra.
Starfield, A.M. and A.L. Bleloch. 1991. Building Models for Conservation and Wildlife Management. Second edition, The Burgess Press, Edina, Minnesota.
Starfield, A.M., K.A. Smith, and A.L. Bleloch. 1990. How to Model It: Problem-solving for the Computer Age. McGraw-Hill. New York. 206 pp.
T. Scott Rupp, A.M. Starfield and F.S. Chapin III. 2000. A frame-based spatially explicit model of subarctic vegetation response to climate change: comparison with a point model. Landscape Ecology 15:383-400.
Starfield, A.M. 1997. A pragmatic approach to modeling for wildlife management. J. Wildl. Manage. 61:261-270.
Tester, J.R., A.M. Starfield and L.E. Frelich. 1997. Modeling for ecosystem management in Minnesota pine forests. Biological Conservation 80: 313-324.
Starfield, A.M. and F.S. Chapin. 1996. A dynamic model of Arctic and boreal vegetation change in response to global changes in climate and land use. Ecological Applications 6(3):842-864.
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 9:175-181.
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 9:166-174.
Starfield, A.M. 1990. Qualitative, rule-based modeling. Bioscience 40(8):601-604.
Starfield, A.M. and A.L. Bleloch. 1983. Expert systems, an approach to problems in ecological management that are difficult to quantify. Int. J. Environmental Management. pp. 261-268.