TY - JOUR
T1 - Food hoarding
T2 - Future value in optimal foraging decisions
AU - Gerber, Leah
AU - Reichman, O. J.
AU - Roughgarden, J.
N1 - Funding Information:
Much of this work was conducted while LRG was a Postdoctoral Associate at the National Center for Ecological Analysis and Synthesis, a Center funded by NSF (Grant #DEB-0072909), the University of California, and the UC Santa Barbara campus. We thank Barney Luttbeg, John Sabo, Eric Seabloom, Joel Brown and Anders Brodin for helpful comments on earlier drafts of this manuscript.
PY - 2004/6/15
Y1 - 2004/6/15
N2 - Traditionally, optimal foraging theory has been applied to situations in which a forager makes decisions about current resource consumption based on tradeoffs in resource attributes (e.g. caloric intake versus handling time). Food storage, which permits animals to manage the availability of food in space and time, adds a complex dimension to foraging decisions, and may influence the predictions of traditional foraging theory. One key question about the role of caching behavior in optimal foraging theory is the degree to which information about future value might influence foraging decisions. To investigate this question, we use a simple prey selection model that minimizes the time spent foraging and is modified to include food storage and changes in nutritional value through time. We used simulations to evaluate time spent in foraging activities per prey item and optimal foraging strategies (e.g. cache versus consume immediately) for 3125 parameter combinations, representing different abundance levels, handling times, and nutritional values. Using discriminant function analysis it was possible to distinguish situations where "caching" versus "immediate consumption" were optimal strategies with abundance as the single predictive variable. The circumstances where caching was optimal were characterized by a decline in prey abundance and an increase in nutritional value through time. These results provide a framework for identifying subtle differences in foraging behavior when future value is accounted for thereby improving our predictive understanding of how caching animals forage.
AB - Traditionally, optimal foraging theory has been applied to situations in which a forager makes decisions about current resource consumption based on tradeoffs in resource attributes (e.g. caloric intake versus handling time). Food storage, which permits animals to manage the availability of food in space and time, adds a complex dimension to foraging decisions, and may influence the predictions of traditional foraging theory. One key question about the role of caching behavior in optimal foraging theory is the degree to which information about future value might influence foraging decisions. To investigate this question, we use a simple prey selection model that minimizes the time spent foraging and is modified to include food storage and changes in nutritional value through time. We used simulations to evaluate time spent in foraging activities per prey item and optimal foraging strategies (e.g. cache versus consume immediately) for 3125 parameter combinations, representing different abundance levels, handling times, and nutritional values. Using discriminant function analysis it was possible to distinguish situations where "caching" versus "immediate consumption" were optimal strategies with abundance as the single predictive variable. The circumstances where caching was optimal were characterized by a decline in prey abundance and an increase in nutritional value through time. These results provide a framework for identifying subtle differences in foraging behavior when future value is accounted for thereby improving our predictive understanding of how caching animals forage.
KW - Caching
KW - Food hoarding
KW - Foraging behavior
KW - Future value
KW - Optimal foraging theory
KW - Risk-averse foraging
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U2 - 10.1016/j.ecolmodel.2003.10.022
DO - 10.1016/j.ecolmodel.2003.10.022
M3 - Article
AN - SCOPUS:2042453349
SN - 0304-3800
VL - 175
SP - 77
EP - 85
JO - Ecological Modelling
JF - Ecological Modelling
IS - 1
ER -