Predator-prey body size, interaction strength and the stability of a real food web

1. We examined the empirical relationship between predator-prey body size ratio and interaction strength in the Ythan Estuary food web.

Interaction strengths in food webs: issues and opportunities

1. Recent efforts to understand how the patterning of interaction strength affects both structure and dynamics in food webs have highlighted several obstacles to productive synthesis. Issues arise with respect to goals and driving questions, methods and approaches, and placing results in the context of broader ecological theory.

Weak interactions, omnivory and emergent food-web properties

Empirical studies have shown that, in real ecosystems, species-interaction strengths are generally skewed in their distribution towards weak interactions. Some theoretical work also suggests that weak interactions, especially in omnivorous links, are important for the local stability of a community at equilibrium. However, the majority of theoretical studies use uniform distributions of interaction strengths to generate artificial communities for study. We investigate the effects of the underlying interaction-strength distribution upon the return time, permanence and feasibility of simple Lotka-Volterra equilibrium communities. We show that a skew towards weak interactions promotes local and global stability only when omnivory is present. It is found that skewed interaction strengths are an emergent property of stable omnivorous communities, and that this skew towards weak interactions creates a dynamic constraint maintaining omnivory. Omnivory is more likely to occur when omnivorous interactions are skewed towards weak interactions. However, a skew towards weak interactions increases the return time to equilibrium, delays the recovery of ecosystems and hence decreases the stability of a community. When no skew is imposed, the set of stable omnivorous communities shows an emergent distribution of skewed interaction strengths. Our results apply to both local and global concepts of stability and are robust to the definition of a feasible community. These results are discussed in the light of empirical data and other theoretical studies, in conjunction with their broader implications for community assembly.

Validation of membrane protein topology models by oxidative labeling and mass spectrometry

Computer-assisted topology predictions are widely used to build low-resolution structural models of integral membrane proteins (IMPs). Experimental validation of these models by traditional methods is labor intensive and requires modifications that might alter the IMP native conformation. This work employs oxidative labeling coupled with mass spectrometry (MS) as a validation tool for computer-generated topology models. ·OH exposure introduces oxidative modifications in solvent-accessible regions, whereas buried segments (e.g., transmembrane helices) are non-oxidizable. The Escherichia coli protein WaaL (O-antigen ligase) is predicted to have 12 transmembrane helices and a large extramembrane domain (Pérez et al., Mol. Microbiol. 2008, 70, 1424). Tryptic digestion and LC-MS/MS were used to map the oxidative labeling behavior of WaaL. Met and Cys exhibit high intrinsic reactivities with ·OH, making them sensitive probes for solvent accessibility assays. Overall, the oxidation pattern of these residues is consistent with the originally proposed WaaL topology. One residue (M151), however, undergoes partial oxidation despite being predicted to reside within a transmembrane helix. Using an improved computer algorithm, a slightly modified topology model was generated that places M151 closer to the membrane interface. On the basis of the labeling data, it is concluded that the refined model more accurately reflects the actual topology of WaaL. We propose that the combination of oxidative labeling and MS represents a useful strategy for assessing the accuracy of IMP topology predictions, supplementing data obtained in traditional biochemical assays. In the future, it might be possible to incorporate oxidative labeling data directly as constraints in topology prediction algorithms.