Bridging the divide between theoretical and empirical approaches has long been a challenge in ecology. This point was emphasized clearly by Gause in his classic monograph over eighty years ago. On the empirical side, the challenge is to get data on relevant spatial and temporal scales with appropriate ecological complexity with experimental designs that have appropriate control of as many factors as possible. The approach taken by Gause of using microcosms, and more recent work with both microcosms and mesocosms is one way to obtain the kinds of data needed. But this approach has been criticized for lack of ecological realism and there are also great challenges with obtaining very large data sets at appropriate spatial scales. Here, I will consider how using data from agricultural systems can be a way to look at ecological questions that could not be easily investigated empirically in any other way. I will consider both advantages and challenges generally and use specific examples that show novel results are possible.
Results/Conclusions
Data from agricultural systems has been used very productively in a variety of ways. There have been many studies that have focused on insects in experimental systems modeled after agricultural systems, including classic studies on spatial population dynamics. Additionally, if fisheries and aquaculture are considered as agricultural systems, the role played by data from these systems has been particularly important. There are also many terrestrial agricultural systems where essentially ‘psuedo-experimnts’ or detailed observations at extremely large spatial or temporal scales have been carried out in commercial agricultural settings. Specific published examples, including the role of different genotypes on population dynamics in an almond orchard, observations of spatio-temproal dynamics of nut production in a pistachio orchard, dynamics of mites in apple orchards, spatial spread of biocontrol agents, dynamics of red scale (Aonidiella aurantii) and its parasitoids in citrus orchards, and other systems both demonstrate novel ways that ecological theory can be tested and used as well as indicating challenges. I will emphasize both the results and their implications for ecological theory that could not be obtained in standard ways by considering the importance of the scales possible, and the techniques needed to analyze and use these data and implications for management.