Supporting Information Appendix S2. Model-selection results for the strength of direct
predator effect on consumer foraging rate throughout the Southeastern Atlantic Bight (SAB).
Candidate models included a null model, two different single-factor models, and an additive twofactor model. Below the results, we outline the rationale for how each factor could influence the
degree to which predators affect the foraging rate of consumers. The difference between the
AICc of model i and the lowest AICc observed is denoted by ∆i. The model likelihood (wi)
represents exp(-∆i / 2), normalized by the sum of all model likelihoods; values close to 1 indicate
greater confidence.
Strength of direct predator effect on
consumer foraging rate
Null model
Water submergence
Resource availability
Resource availability +
Water Submergence
df
∆i
wi
3
4
4
5
2.9
6.7
0.0
4.5
0.169
0.026
0.729
0.075
Rationale
Water submergence of reef: Throughout the SAB, variation in the tidal submergence of a reef
could shift the nature of a predator-consumer interaction by altering the presence of pelagic
predators and the dissemination of their water-borne cues (Smee and Weissburg 2007).
Oyster recruitment: One resource that generally differs along coastlines is the supply of
invertebrate larvae. If hydrodynamic forces promote a spatial gradient in recruitment, then sites
with high recruitment would represent a spatially persistent elevation of resources. Because the
probability of consumer starvation should be lowest at high recruitment sites (Abrams 1991),
high resource availability should minimize the need for consumers to search for food and
therefore minimize the direct effect of predators on consumer foraging activity.