DOI: 10.5061/dryad.w6m905r2f
title: Integrating predator energetic balance, risk-taking behavior and microhabitat in functional response to untangle indirect interactions in a multispecies vertebrate community

description: Predator-prey interactions in natural communities are complex, with
 predators often exploiting multiple prey types and generating indirect
 interactions among them. Ecological theory has traditionally modeled these
 interactions using functional responses models which are based on foraging
 rates, not energy transfers. This approach overlooks how the energy
 acquisition rate of a predator can alter its behavior and, in turn, the
 strength of species interactions. Here, we integrate predator energetics
 into a functional response model to represent trade-offs predators face
 when foraging on prey that vary in risk and abundance across heterogeneous
 landscapes. We compared model predictions to 20 years of prey species
 density and reproductive success data. The mechanistic model was
 parameterized for an Arctic tundra vertebrate community, where the Arctic
 fox feeds on cyclic lemmings and eggs of sandpipers (non-risky prey) and
 gulls (risky prey that often nest in partial refuge like islands). In this
 system, predator-mediated interactions generate apparent mutualism between
 lemmings and birds, but its strength varies between species, and the
 mechanisms underlying this interaction remain unclear. We found that fox
 energetic balance was highly related to lemming density, with a threshold
 of 89 lemmings per km2 required for a positive energetic balance.
 Model-predicted gull nest acquisition rates were lowest on islands when
 the energetic balance of foxes was positive, and highest for nests on the
 shore when foxes were in deficit. The model that incorporated predator
 risk-taking behavior and energetic balance produced variation in gull
 hatching success that most closely matched empirical observations. We
 documented for the first time that a shift in predator energetic balance,
 triggering changes in attack and capture probabilities on a risky prey,
 can be a key mechanism underlying the apparent mutualism between lemmings
 and gulls. In contrast, for non-risky prey, the indirect effect can be
 essentially driven by changes in predator movement. These findings
 highlight how prey characteristics can lead to different mechanisms behind
 similar indirect interactions. Taken together, our results indicate that
 mechanistic models integrating species traits, landscape features, and
 energy-dependent behavioral adjustments can improve our ability to
 quantify interaction strengths in natural communities.
description: **Dataset**: Hatching Success and Lemming Density **General Description**
 The *Gull_hatching_success_data.csv* dataset contains observations of
 glaucous gull hatching success in relation to summer lemming density on
 Bylot Island, Nunavut, Canada from 2004 to 2023. Each row represents a
 monitored nest with information on the exposure period (in days), lemming
 density, hatching success, and nest site location. **Variables**
 ***Year*** Year of observation (numeric, e.g., 2004). ***Exposure_time***
 Exposure time was computed by determining the number of days between the
 date of nest discovery and one of the following dates: (1) for successful
 nests, the observed or estimated hatching date or the date of the last
 visit if no information on hatching date was available, (2) for failed
 nests, the observed predation date or the midpoint between the date on
 which fate was determined and the last date the nest contained eggs. Nests
 with undetermined fate were not included in the analysis.
 ***Density_Lemming*** Estimated density of lemmings (individuals per
 hectare). We estimated lemming density using live trapping from 2004 to
 2023 (see Fauteux et al. 2018 for methods). To obtain an estimate of the
 total lemming density during the gull incubation period, we summed the
 density of the two lemming species and averaged the estimates for June and
 July. ***Hatching_Success*** Nest hatching success (binary variable): 1 =
 at least one egg hatched 0 = complete failure (no eggs hatched)
 ***Nest_Site_Location*** Location of the nest site (categorical): Island =
 nest located on an island Shore = nest located on the shoreline