508 Food Webs greatly depress prey abundance Pathogens and parasites form an extreme example: They take little energy, even when they decimate their host populations In a well-studied food web of the marine benthic community in the Antarctic, Dayton showed that the species apparently exerting the strongest effects on the structure and dynamics of this community would be deemed unimportant from analyses of diet, energy transfer, or biomass Such discoveries have stimulated many to argue that, without experimentation, one cannot a priori decide which are strong or weak links An apparently weak link (in terms of diet or energy transfer) can be a key link dynamically, and an important energetic link may affect dynamics little No necessary concordance of dynamics with either dietary or energetic measures exists This insight counters the use of energetics to recognize strong interaction links Modeling Food Webs To many ecologists, early food webs of Forbes, Summerhayes, and Elton and those of Lindeman emphasized the overwhelming complexity of natural systems and the need to simplify them into distinct trophic groups This perspective was culminated in the green-world hypothesis of Hairston et al (1960) Oksanen et al.’s (1981) EEH expanded this view for ecosystems that had fewer or more than three trophic levels and for which the exact number of trophic levels was set by productivity The top level would then regulate the one below it and this would release the one below it, etc In this sense, both GWH and EEH suggested that all ecosystems are essentially regulated from the top–down by predation Lindeman envisioned the food web (or as he called it, the ‘‘food-cycle’’) as a dynamic system in which energy and nutrients are transferred from one trophic level to the next and recycled This was an important departure from simply determining feeding connectedness (and from the GWH) in that ecosystems could be regulated from the bottom–up by the flow of energy and materials from the level below However, much more information and data are required to quantify the transfer of energy (and material) through food webs, but this view allows for a more analytical approach MacArthur focused the attention of ecologists on the trophic–dynamic approach with his hypothesis that increasing complexity of community organization leads to increasing dynamic stability The reasoning was simple: When predators have alternative prey, their own numbers rely less on fluctuations in numbers of a particular species Where energy can take more routes through a system, disruption of one pathway merely shunts more energy through another, and the overall flow continues uninterrupted MacArthur’s analytical approach linked community stability to species diversity and food web complexity and it stimulated a flurry of theoretical, comparative, and experimental work This work may be divided into two contemporary approaches that use food webs to study community structure The first approach involves the study of the properties of food web diagrams with the goal of uncovering general patterns that suggest mechanisms of community stability This is done both by comparing food webs from natural communities and by the use of simulation and mathematical modeling to study hypothetical food webs This research has yielded much of the terminology now associated with food webs and generated a body of food web theory that includes many hypotheses about community structure The second approach, which grew from early theoretical and experimental community studies, involves the dynamical analysis of food webs to determine not only the pattern of interactions among the populations in the community but also the relative strengths of those interactions Dynamic food web analysis also seeks to reveal interactions that are not obvious from simple food web diagrams, so-called indirect interactions This approach requires the careful merging of experimental and theoretical approaches The simplicity of the GWH enabled it to be a reasonable starting point to examine the dynamics of food webs In general, dynamical models are rooted in a tradition based on the application of Lotka–Volterra equations to communities and advocated by May (1973) One of the major conclusions from these phenomenological models is that complexity (e.g., omnivory and long chains) causes instability in model systems This conclusion was viewed with skepticism by empiricists because observations from field studies (such as work by MacArthur) suggested that increased complexity should result in increased stability Recent theoretical investigations into the relationship between stability and complexity have found that assumptions and structure of earlier models may have biased them toward decreased stability with increasing complexity Early theoretical studies of interactions and consequences of these interactions in food webs were based on equilibrium dynamics of Lotka–Volterra models The assumption that ecological systems or species populations have some ‘‘equilibrium’’ around which they fluctuate is totally unrealistic Furthermore, these early models ignored the central belief of many empiricists that most interactions between species were weak The outcome of many of these theoretical studies went against common sense intuition and the findings of empirical studies, including that omnivory was destabilizing and therefore rare and that complexity (greater diversity) was also destabilizing Recent studies that incorporated the findings of mostly weak interactions and nonequilibrium dynamics have found that omnivory and complexity may actually stabilize food webs This agrees with both the intuition and the current arguments of empiricists who find that many weak interactions occur within food webs and these promote stability Recent theoretical studies suggested three factors as important to reduce stability in earlier models: (1) linear Lotka–Volterra equations, (2) using equilibrium solutions to these equations, and (3) the distribution of interaction strengths overly estimated the number of strong links Many studies have shown that many predator–prey relationships are not linear, but instead predators exhibit saturation such as described by a Holling’s type II functional response Current models take advantage of this and use energetic uptake rates that saturate based on body size relationships Also, equilibrium solutions to Lotka–Volterra relationships can give biologically unrealistic results because the assumption of equilibrium does not appear to hold in many predator–prey relationships May and others used a uniform distribution in randomly created model food webs, which resulted in their