Figure 1.
The Network of Trophic Interactions for Little Rock Lake, Wisconsin
Figure shows 997 feedings links (lines) among 92 taxa (nodes) [2]. The node color indicates the trophic level of the taxon, including (from bottom to top) algae, zooplankton, insects, and fishes; the link color corresponds to the type of feeding link, including herbivory and primary and secondary carnivory. This image was produced using FoodWeb3D software written by R. J. Williams and provided by the Pacific Ecoinformatics and Computational Ecology Lab (www.foodwebs.org).
Figure 2.
Bridging Dynamics across Organizational Scales
On the left is a detailed model in which individual interactions in a network are described explicitly. On the right, typical “mean field” models aggregate the population into compartments (here for the three subpopulations of susceptible, infected, and recovered individuals in the dynamics of an infectious disease with permanent immunity). Computational approaches can help us understand the relationship between dynamics at these two different scales, from the individual to the population level. We can start with a stochastic individual-based model and develop approximations that simplify it (A). From this process, we can learn about the opposite direction of formulating simple models directly without sufficient knowledge to first specify the detailed interactions and components (B). These simple models represent implicitly the effect of smaller scale variability.
Figure 3.
Phytoplankton Biomass Generated with a Coupled Biological–Physical Model Developed to Examine the Impact of Nitrogen Fixation in the Atlantic Ocean
In this large simulation [24], the ecosystem model consists of six variables and includes two different functional groups within the phytoplankton, for nitrogen and non-nitrogen fixers. The physical model includes 19 vertical layers but only a coarse horizontal resolution (2° × 2°). In particular, it does not resolve the mesoscale variability of the flows, at characteristic scales of 1 to 100 km, known as the “weather” of the ocean. The lower left panel illustrates the variability of phytoplankton at these smaller turbulent scales, with a simulation of a coupled ecosystem–eddy model (K. Boushaba, G. Flierl, and M. Pascual, unpublished data). We can ask how the effects of these smaller scales can be incorporated in models with a coarser resolution for larger oceanic regions. Even more fundamentally, what are the relevant spatial scales of coupling?