Thursday, August 6, 2009 - 9:50 AM

SYMP 16-5: The model ecosystem as a paradigm of place-based research: Contrasting approaches to field station development within the UC Davis Natural Reserve System

Paul A. Aigner, Catherine E. Koehler, Virginia Boucher, and Shane Waddell. University of California, Davis

Background/Question/Methods

From the study of molecules to whole organisms, advances in biology have been facilitated by widespread reliance on model organisms—species that are intensively studied with the expectation that such study will yield broad insights about biological processes. We argue that model ecosystems can similarly facilitate the study of ecology. Using two examples from the UC Davis Natural Reserve System, we illustrate how the potential of field stations as model ecosystems can be systematically developed. 

Results/Conclusions

At the McLaughlin Reserve, development of the model ecosystem concept has been driven by the unique natural attributes of the site—extreme natural- and human-caused edaphic heterogeneity makes the reserve particularly well suited to the study of ecological genetics and spatial ecology in plants. Management of the reserve has focused on increasing the convenience and value of the site for conducting the types of experiments (e.g., reciprocal transplants and diversity manipulations) traditionally associated with these areas of study.  By contrast, the potential of the Quail Ridge Reserve to serve as a model ecosystem for the study of animal behavior stems largely from its unique technological infrastructure.  The reserve hosts the world’s largest wildland wireless mesh computer network, which combined with a bioacoustical monitoring system and an automated animal telemetry system that is in development enables researchers to design experiments in behavioral ecology that would otherwise not be possible. Both examples suggest that biological field stations can increase their value to science by developing facilities, infrastructure, data collections, and management policies that support a model ecosystem approach.