Conference Background and Goals

       Quantitative models form a natural link between all of the other scientific endeavors in our field.  For the sake of simplicity we have placed these endeavors or goals into three broad categories:

·       Observation and experimentation on component or whole-ecosystem processes and properties:

·       Integrating and synthesizing these observations into coherent frameworks which provide the basis to understand how ecosystems function and are assembled.

·        Predicting, based on these frameworks, how processes vary among or within ecosystems over space and time.

     Although ecosystem science began as a holistic effort, an increasing proportion of ecosystem scientists devote their efforts to breaking down complex natural systems and understanding component processes.    As our understanding of ecosystem complexity increases, the fundamental goals of synthesis and prediction become even more challenging and quantitative modeling is of increasing importance.

      Quantitative models provide a means to test our understanding of ecosystems by allowing us to explore the interactions among observation, synthesis, and prediction.  The utility of  models for synthesis and prediction is obvious.   The role of quantitative models in informing and guiding observation and experimentation is perhaps less often appreciated, but equally valuable. 

     Modeling has clearly become an integral part of the “toolkit” of many ecosystem scientists.   It can also be argued, however, that a gulf has developed between empirical researchers and modelers, and that the gulf is an unhealthy symptom of lack of both communication and recognition of the critical role of models in all 3 of the fundamental goals of ecosystem science.

       Recent years have seen dramatic advancements in the computational power and mathematical tools available to modelers.  Methodological advances in areas ranging from remote sensing to molecular techniques have significantly improved our ability to parameterize and validate models at a wide range of spatial scales.   The body of traditional, mechanistic, empirical research is also growing phenomenally.   Ecosystem science is ripe for major gains in the synthetic and predictive power of its models, and that this comes at a time of growing need by society for quantitative models that can inform debate about critical environmental issues.