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On the mechanistic understanding of predator feeding behavior using the functional response concept
Author(s) -
Papanikolaou Nikos E.,
Broufas George D.,
Papachristos Dimitrios P.,
Pappas Maria L.,
Kyriakaki Chara,
Samaras Konstantinos,
Kypraios Theodore
Publication year - 2020
Publication title -
ecosphere
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.255
H-Index - 57
ISSN - 2150-8925
DOI - 10.1002/ecs2.3147
Subject(s) - functional response , predator , predation , biology , numerical response , ecology , biological system
Functional response models describe the relationship between prey density and per capita prey consumption rate by a predator. Type II functional responses, in which density‐dependent predation occurs via a decelerating feeding rate, seem to prevail in nature and are commonly described by Holling’s disk equation. In the derivation of the disk equation, Holling did not include digestion time. Although some authors have later extended the interpretation of handling time by also including digestion time, this violates the key assumption of the disk equation that the processes of searching for and handling prey are mutually exclusive. The steady‐state satiation (SSS) equation is a functional response model that discriminates between handling and digestion time. The application of the SSS equation is underutilized so far in the ecological literature, probably due to its complexity. In this study, we first tested the viability of the SSS equation. Second, we investigated the mechanistic basis of the SSS equation, comparing the model’s predictions with directly observed data. For this purpose, we used predator–prey systems of different taxa, that is, the ladybird beetle Hippodamia variegata preying on the aphid Aphis fabae , the lacewing Chrysoperla agilis preying on the aphid Myzus persicae , and the predatory mite Iphiseius degenerans preying on the thrips Frankliniella occidentalis . Our results show that the SSS equation is viable and can realistically describe type II functional response. In all predator–prey systems we tested, the model fitted the data reasonably well and provided realistic estimation of its parameters.

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