Complexity in quantitative food webs.

Food webs depict who eats whom in communities. Ecologists have examined statistical metrics and other properties of food webs, but mainly due to the uneven quality of the data, the results have proved controversial. The qualitative data on which those efforts rested treat trophic interactions as present or absent and disregard potentially huge variation in their magnitude, an approach similar to analyzing traffic without differentiating between highways and side roads. More appropriate data are now available and were used here to analyze the relationship between trophic complexity and diversity in 59 quantitative food webs from seven studies (14-202 species) based on recently developed quantitative descriptors. Our results shed new light on food-web structure. First, webs are much simpler when considered quantitatively, and link density exhibits scale invariance or weak dependence on food-web size. Second, the "constant connectance" hypothesis is not supported: connectance decreases with web size in both qualitative and quantitative data. Complexity has occupied a central role in the discussion of food-web stability, and we explore the implications for this debate. Our findings indicate that larger webs are more richly endowed with the weak trophic interactions that recent theories show to be responsible for food-web stability.

Phylogenetic constraints and adaptation explain food-web structure.

Food webs are descriptions of who eats whom in an ecosystem. Although extremely complex and variable, their structure possesses basic regularities. A fascinating question is to find a simple model capturing the underlying processes behind these repeatable patterns. Until now, two models have been devised for the description of trophic interactions within a natural community. Both are essentially based on the concept of ecological niche, with the consumers organized along a single niche dimension; for example, prey size. Unfortunately, they fail to describe adequately recent and high-quality data. Here, we propose a new model built on the hypothesis that any species' diet is the consequence of phylogenetic constraints and adaptation. Simple rules incorporating both concepts yield food webs whose structure is very close to real data. Consumers are organized in groups forming a nested hierarchy, which better reflects the complexity and multidimensionality of most natural systems.

Sampling effects and the robustness of quantitative and qualitative food-web descriptors.

Food-web descriptors serve as a means for among-web comparisons that are necessary for the discovery of regularities in respect to food-web structure. Qualitative descriptors were however found to be highly sensitive to varying levels of sampling effort. To circumvent these shortcomings, quantitative counterparts were proposed which take the magnitude of trophic interaction between species into consideration. For 14 properties we examined the performance with increasing sampling effort of a qualitative, an unweighted quantitative (giving the same weight to each taxon), and a weighted quantitative version (weighing each taxon by the amount of incoming and outgoing flows). The evaluation of 10 extensively documented quantitative webs formed the basis for this analysis. The quantitative versions were found to be much more robust against variable sampling effort. This increase in accuracy is accomplished at the cost of a slight decrease in precision as compared to the qualitative properties. Conversely, the quantitative descriptors also proved less sensitive to differences in evenness in the distribution of link magnitude. By more adequately incorporating the information inherent to quantitative food-web compilations, quantitative descriptors are able to better represent the web, and are thus more suitable for the elucidation of general trends in food-web structure.