Literature DB >> 18811411

Using spatially explicit models to characterize foraging performance in heterogeneous landscapes.

D Grünbaum1.   

Abstract

The success of most foragers is constrained by limits to their sensory perception, memory, and locomotion. However, a general and quantitative understanding of how these constraints affect foraging benefits, and the trade-offs they imply for foraging strategies, is difficult to achieve. This article develops foraging performance statistics to assess constraints and define trade-offs for foragers using biased random walk behaviors, a widespread class of foraging strategies that includes area-restricted searches, kineses, and taxes. The statistics are expected payoff and expected travel time and assess two components of foraging performance: how effectively foragers distinguish between resource-poor and resource-rich parts of their environments and how quickly foragers in poor parts of the environment locate resource concentrations. These statistics provide a link between mechanistic models of individuals' movement and functional responses, population-level models of forager distributions in space and time, and foraging theory predictions of optimal forager distributions and criteria for abandoning resource patches. Application of the analysis to area-restricted search in coccinellid beetles suggests that the most essential aspect of these predators's foraging strategy is the "turning threshold," the prey density at which ladybirds switch from slow to rapid turning. This threshold effectively determines whether a forager exploits or abandons a resource concentration. Foraging is most effective when the threshold is tuned to match physiological or energetic requirements. These performance statistics also help anticipate and interpret the dynamics of complex spatially and temporally varying forager-resource systems.

Year:  1998        PMID: 18811411     DOI: 10.1086/286105

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  10 in total

1.  Hierarchical patch dynamics and animal movement pattern.

Authors:  Per Fauchald; Torkild Tveraa
Journal:  Oecologia       Date:  2006-06-23       Impact factor: 3.225

2.  People's study time allocation and its relation to animal foraging.

Authors:  Janet Metcalfe; W Jake Jacobs
Journal:  Behav Processes       Date:  2009-12-21       Impact factor: 1.777

3.  Biased correlated random walk and foray loop: which movement hypothesis drives a butterfly metapopulation?

Authors:  Eliot J B McIntire; Ghislain Rompré; Paul M Severns
Journal:  Oecologia       Date:  2012-11-23       Impact factor: 3.225

4.  Dopamine and glutamate control area-restricted search behavior in Caenorhabditis elegans.

Authors:  Thomas Hills; Penelope J Brockie; Andres V Maricq
Journal:  J Neurosci       Date:  2004-02-04       Impact factor: 6.167

5.  Autonomous circuitry for substrate exploration in freely moving Drosophila larvae.

Authors:  Jimena Berni; Stefan R Pulver; Leslie C Griffith; Michael Bate
Journal:  Curr Biol       Date:  2012-08-30       Impact factor: 10.834

6.  Group dynamics and landscape features constrain the exploration of herds in fusion-fission societies: the case of European roe deer.

Authors:  Olivier Pays; Daniel Fortin; Jean Gassani; Jean Duchesne
Journal:  PLoS One       Date:  2012-03-30       Impact factor: 3.240

7.  Breeding success of a marine central place forager in the context of climate change: A modeling approach.

Authors:  Lauriane Massardier-Galatà; Jennifer Morinay; Frédéric Bailleul; Eric Wajnberg; Christophe Guinet; Patrick Coquillard
Journal:  PLoS One       Date:  2017-03-29       Impact factor: 3.240

8.  "Micropersonality" traits and their implications for behavioral and movement ecology research.

Authors:  Joseph D Bailey; Andrew J King; Edward A Codling; Ashley M Short; Gemma I Johns; Ines Fürtbauer
Journal:  Ecol Evol       Date:  2021-02-22       Impact factor: 2.912

9.  Adaptive Lévy processes and area-restricted search in human foraging.

Authors:  Thomas T Hills; Christopher Kalff; Jan M Wiener
Journal:  PLoS One       Date:  2013-04-05       Impact factor: 3.240

10.  Uniting statistical and individual-based approaches for animal movement modelling.

Authors:  Guillaume Latombe; Lael Parrott; Mathieu Basille; Daniel Fortin
Journal:  PLoS One       Date:  2014-06-30       Impact factor: 3.240

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.