DOI: 10.5061/dryad.x69p8czns
title: Data and R code for: Handling- or digestion-limited predator: the role of body masses and habitat complexity in predator-prey feeding interaction

description: Predator functional response is a key element of feeding interactions that
 quantify the per capita feeding rates of predators depending on
 prey density, and variation in its parameters is strongly associated with
 interaction strength and population dynamics. We studied 18 functional
 responses of the marine whelk-bivalve systems across three levels of
 predator body size and three prey species at two habitat structures. We
 found that the marine whelk can be a handling-limited predator which
 received less attention so far. We propose that the handling-limited
 predator can further be categorized into two types: pursuing-limited
 (where maximum feeding rate could be influenced by habitat complexity) and
 ingesting-limited (where maximum feeding rate is impacted not by habitat
 complexity, but predator-prey body mass ratios and prey defense strategy).
 Our results show that handling time scales negatively with predator-prey
 body mass ratios, but there are layers of complexity nested within this
 trend. We first provide an underlying mechanism of this trend is the
 transition from handling to digestion limitation with increasing
 predator-prey body mass ratios. In addition to confirming known body mass
 ratios and habitat structure effects, our study confirms the importance of
 prey types. Our study reveals that simple assumptions about body masses
 and prey defense strategy may usefully refine estimates of feeding
 interactions in complex food webs.
description: # Data and R code for: Handling- or digestion-limited predator: the role
 of body masses and habitat complexity in predator-prey feeding interaction
 [https://doi.org/10.5061/dryad.x69p8czns](https://doi.org/10.5061/dryad.x69p8czns)![](data:image/png;base64,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) Datasets are feeding interactions among different sizes of whelks and bivalve preys. Date of data collection: 2015 ## Description of the data and file structure 1\. Title of Dataset: Data and R code for: Handling- or digestion-limited predator: the role of body masses and habitat complexity in predator-prey feeding interaction 2\. Clam.09.21.CSV, Scallop.09.21.CSV and Oyster.09.21.CSB are the predation data of three sizes of whelks on clams, scallops and oysters, respectively in simple and complex substrates. 3\. Variables for the above datasets * Prey: Prey type was exposed to whelks * Size: Predators (i.e. whelk) size with three levels: Small, Medium and Large * N0: Initial density of prey * Neaten_s: Number of preys were eaten by the whelk in four days in simple substrates ## Code/Software The R code is used for the model fitting and analysis for the manuscript on MEPS. The version of R is 4.3.1.