Food Webs Ecologists are beginning to understand how stoichiometry and nutritional balance affect population and food web dynamics Nevertheless, it is extremely likely that herbivore growth is often less than maximal solely because their environment does not provide sufficient quantities of all key nutritional requisites In fact, the greatest disparity in biochemical, elemental, and stoichiometric composition in the entire food web occurs at the link where herbivores convert plant material into animal tissue The implication is clear: Even in a world full of green energy, many or most herbivores cannot obtain enough requisite resources to grow, survive, or reproduce at high rates Nutritional shortages regulate herbivore numbers and often limit their effects on plant biomass Recent theoretical studies of the role of food quality in terms of edibility and nutrient content show that low food quality can greatly influence consumer–resource interactions This has two important consequences First, low food quality reduces the growth rate of the consumer, making that interaction more stable Second, in systems in which multiple resources could be limiting, the addition of large amounts of a single resource (such as nitrogen or phosphate) may increase that resource to a level at which it is no longer limiting; however, a second resource would become limiting and so on This sequential limiting of resources means that the addition of a single resource would not push the system into highly unstable dynamics, reducing the probability that the ‘‘paradox of enrichment’’ occurs Rosenzweig introduced the concept of the paradox of enrichment to explain the addition of a resource leading to the collapse of a consumer–resource interaction This happens because the addition of the resource drives the population of the consumer to a higher level that results in overcompensation by the consumer (predator) driving the resource (prey) extinct However, most systems have several potentially limiting resources For example, Leibold’s study of ponds found that nitrogen additions not lead to strong trophic cascades or the paradox of enrichment because light becomes limiting with relatively modest nitrogen additions Interaction Strength One goal of functional webs is the quantification of interaction strengths within food webs Various definitions have been used for ‘‘interaction strengths.’’ In Lotka–Volterra models, interaction strengths are due solely to the direct interactions between species pairs and are measured on a per capita basis Estimations of the strength of these direct interactions are fraught with difficulties Measurements in artificial systems may not allow for behavioral responses For example, Sih has shown that prey species have different escape mechanisms or routes depending on the species of predator Thus, when in the presence of two predators, the response of a prey may result in its increased susceptibility to one or the other predator due to a behavior that is not evidenced when only the one predator is present Measurements in natural systems are also problematic because they may not account for indirect interactions Many studies have elucidated the interaction strength among pairs of species However, indirect effects may play a strong role in determining the realized interaction strength Thus, Paine has 507 argued that interaction strengths should always be measured in the field with the full complement of natural species present and that these measurements should incorporate all indirect effects The realized interaction strength accounts for all direct and indirect interactions For example, predator–prey interactions are functionally negative due to the direct effect However, the indirect effect of a predator may reduce the number of competitors of the prey species, thus resulting in an overall positive interaction strength (direct ỵ indirect effects) Therefore, potentially strong indirect effects can make mechanistic interpretation of experimental results among species difficult Path analysis, a new statistical method, has been used to evaluate causal hypotheses concerning the strengths of interactions in many systems Path analysis is essentially a multiple regression on each species in which specific causal relationships (e.g., alternative food web configurations), specific experimental treatments, and other interactions are diagrammed in a community interaction web The community interaction is essentially a food web to which nonconsumptive interactions, such as pollination, competition, and mutualisms are added Hypotheses for the causal relationships between pairs of species not directly linked can become quite complicated However, path analysis can test different hypothesized community web structures by accounting for both direct and indirect relationships Then, experimental manipulations (e.g., species removals or additions) can test predictions of the path analysis Can Energetic Webs Provide Insight into Population and Community Dynamics? A problem in food web studies is how to connect the great amount of quantitative information in energetic webs to population and community dynamics described by functional webs Much progress would occur if we could determine the dynamical importance of a particular species or feeding link from an inspection of the magnitude of energy transfer or diet composition Unfortunately, no clear answer is forthcoming In fact, it appears that even highly quantified information such as the number of calories passed along a certain pathway or the frequency of prey in the diet of a consumer conveys little information about the dynamics of interacting populations because these descriptive parameters not correlate with interaction strength There is no clear rationale to argue that food web dynamics and energetics are necessarily correlated; indeed, logic and evidence suggest that dynamics often cannot be predicted from data on diet or energy flow The degree of resource suppression is not a function of energy transfer Consumer regulation of populations need involve little energy transfer and few feeding interactions For example, removing predatory rats from New Zealand islands increased lizard abundance 3–30 times although lizards formed o3% of rat’s diet Key regulatory factors may produce much less overall mortality than other factors Brief, intense predation episodes may net little energy for the predator but may be central to prey dynamics The consumption of young stages (seeds, eggs, and larvae) may provide trivial energy to a consumer but can