1 Models in Ecosystem Science Charles D. Canham, Jonathan J. Cole, and William K. Lauenroth The Role of Modeling in Ecosystem Science Quantitative models play an important role in all of the sciences. Models can range from simple regression equations and analytical models to complex nu- merical simulations. Their roles can vary from exploration and problem formu- lation to sophisticated predictions upon which management decisions are based. In the most basic sense, models express the logical consequences of a set of hypotheses and generate predictions (in the strictest sense) that can be com- pared with observations in the quest to falsify those hypotheses. Beyond this, the definitions and utility of models become controversial, and further discus- sion of models usually sparks an often intense debate over a host of both practi- cal and philosophical issues. The ninth Cary Conference, held May 1–3, 2001, at the Institute of Ecosystem Studies, was designed to explore those debates, and to evaluate the current status and role of modeling in ecosystem science. Beyond their fundamental use in testing hypotheses, models serve a number of functions in our quest to understand ecosystems. Quantitative models allow the investigator to observe patterns embedded in the data, to synthesize data on disparate components into an integrated view of ecosystem function, and ulti- mately to predict the future behavior of some aspects of the ecosystem under given scenarios of future external drivers (Figure 1.1). While the participants of Cary Conference IX found broad consensus for these uses of quantitative mod- els, the conference also revealed strongly held preferences for different ap- proaches to modeling. One of the major axes of contention, for example, was the tension between favoring simple or parsimonious models (Chapters 4 and 8) versus models that were more mechanistically rich (Chapter 5). Under the sur- face of this usually jovial disagreement between modelers of different schools lie deep philosophical differences about the nature of scientific understanding itself. In Chapter 2, Oreskes, the lone philosopher at the conference has articu- lated some of the relationships between science, philosophy, and modeling.