Data from: How do foragers decide when to leave a patch? A test of alternative models under natural and experimental conditions - Marshall, Harry H.; Carter, Alecia J.; Ashford, Alexandra; Rowcliffe, J. Marcus; Cowlishaw, Guy (Dryad, 2013)
1. A forager’s optimal patch-departure time can be predicted by the
prescient marginal value theorem (pMVT), which assumes they have perfect
knowledge of the environment, or by approaches such as Bayesian-updating
and learning rules, which avoid this assumption by allowing foragers to
use recent experiences to inform their decisions. 2. In understanding and
predicting broader scale ecological patterns, individual-level mechanisms,
such as patch-departure decisions, need to be fully elucidated.
Unfortunately, there are few empirical studies that compare the
performance of patch-departure models that assume perfect knowledge with
those that do not, resulting in a limited understanding of how foragers
decide when to leave a patch. 3. We tested the patch-departure rules
predicted by fixed-rule, pMVT, Bayesian-updating and learning models
against one another, using patch residency times recorded from 54 chacma
baboons (Papio ursinus) across two groups in natural (n = 6,594 patch
visits) and field-experimental (n = 8,569) conditions. 4. We found greater
support in the experiment for the model based on Bayesian-updating rules,
but greater support for the model based on the pMVT in natural foraging
conditions. This suggests that foragers may place more importance on
recent experiences in predictable environments, like our experiment, where
these experiences provide more reliable information about future
opportunities.5. Furthermore, the effect of a single recent foraging
experience on patch residency times was uniformly weak across both
conditions. This suggests that foragers’ perception of their environment
may incorporate many previous experiences, thus approximating the perfect
knowledge assumed by the pMVT. Foragers may, therefore, optimise their
patch-departure decisions in line with the pMVT through the adoption of
rules similar to those predicted by Bayesian-updating.
Experimental patch visitsThe dataset of 8,569 patch visits in a field
experiment used in the analysis of patch-departure decisions in
experimental conditions.Marshalletal2013-JAE-experimentdata.csvNatural
patch visitsThe dataset of 6,175 patch visits used in the analysis of
patch-departure decisions in natural
conditions.Marshalletal2013-JAE-naturaldata.csvR code used in analysesThe
R code used in the analysis of patch-departure
decisionsMarshalletal2013-JAE-Rcode.txt
Keywords: primate; habitat predictability; Bayesian-updating; Papio ursinus; patch-departure-rules; marginal value theorem