DOI: 10.5061/dryad.j6q573nfn
title: Prey diversity constrains the adaptive potential of predator foraging traits

description: Predators are generally under selective pressure to get better at
 foraging, leading to steeper functional responses and stronger
 predator-prey interactions. Yet strong interactions can de-stabilize food
 webs, and most interactions across ecological communities are thought to
 be weak. This conflict between evolutionary and community expectations for
 the strength of predator-prey interactions represents a fundamental gap in
 our understanding of how the evolution of foraging plays out in food webs.
 Here we help to resolve the conflict by showing analytically that the
 expectation for the evolution of steeper functional responses is relaxed
 in communities with diverse prey types. We simulate communities with
 varying prey richness and show that increasing prey richness can indeed
 constrain the adaptive potential of predator foraging traits, but that at
 low prey richness predators can evolve to have a stronger interaction with
 prey that have high net energy yields. Our results also indicate that
 handling time plays a role in determining whether predators may evolve to
 have a stronger interaction with abundant prey, suggesting that the
 evolution of keystone predator modules in food webs is most likely when
 handling times are negligible. Our results also provide a new mechanism
 predicting more diffuse interactions in diverse tropical communities
 relative to more species-poor communities at higher latitudes.
description: The data uploaded here are abundances and traits through time
 generated in simulations. Each file is a replicate given a level of prey
 species richness (1, 2, 4, 8) and interspecific competition (0.5 or 1,
 with 1 reflecting neutrality). Each file is named according to the run,
 e.g. "GEM_output_alpha=0.5_2_1_prey_high_h" is the output for
 competition of 0.5 (complementary prey species) with 2 prey types and
 replicate 1. In this case, we are also specifying a high handling
 time. These data can be imported and analyzed however
 you want, but the code we used is provided in the file called
 "Plot_GEMv5_multi_prey_multi_run4.m". This is a Matlab file. It
 will import each of the simulation files and reproduce the figures in the
 manuscript. It requires the function "jbfill.m".
 The remaining files are code to run the simulations. See
 "Usage notes" for explanation.
description: This set of Matlab scripts and functions will initiate and
 perform the GEM simulation. Start with
 "Call_multi_prey_GEM.m", which is where you will specify prey
 levels to use, type of competition, and number of replicates. This file
 then calls the primary GEM function in a loop. The primary GEM function
 saves the simulations each in turn as the script runs through the levels
 and replicates. The primary GEM function is
 "GEMv5_multi_prey.m". This is a function and needs to be called.
 It is set up to run in parallel, so careful attention must be paid to
 changes in the script structure. This function depends on other
 subfunctions: "V4_pick_individuals.m",
 "V5_medians_and_cis.m", "V4_initiate_populations.m",
 and "create_multi_prey_model.m" that handle the repeated
 tasks.