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Antlion Foraging: Tracking Prey Across Space And Time

Ecology, Oct, 1999 by Philip H. Crowley, Mary C. Linton

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In contrast to the assessment window and displacement distance, relocation thresholds of gain rate may be determined less directly by spatial and temporal autocorrelation patterns. The threshold may generally tend to increase with window size to compensate for the enforced immobility of the evaluation period, and the threshold should decrease with displacement to contain the overall relocation costs. Taken together, the relationships summarized in Fig. 1 imply more frequent relocations when the spatial scale is large, although no clear predictions emerge for different scales of temporal autocorrelation (but see the Discussion). Moreover, the logic underlying these relationships assumes that relocation costs may play a large part in determining both how a trap builder gains spatiotemporal information and how it uses the information gained.

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SIMULATIONS

The simulation algorithm is presented in Fig. 2. A computer program, written in Borland Pascal (available on request from the senior author), was used to implement the algorithm. The program began by accessing the data arrays and then looped through the 5670 strategies composed of all combinations of the four components [TABULAR DATA FOR TABLE 1 OMITTED] previously described. Each strategy was evaluated separately for each of the eight site-year-transect combinations; for each of the four site-year combinations over both transects within a site; for each site over years and transects; and overall across all sites, years, and transects. For each strategy and each site-year-transect combination, 1000 replicates were run. Each replicate represented an antlion that was started at a random locus within a 50-locus transect and was allowed to obtain the food reward available at its location on each of the days in the data set. Thus, results from this main analysis were derived from simulated foraging by 45 360 000 antlion larvae (5670 strategies x 8 site-year-transect combinations x 1000 replicate antlions). Additional analyses of this same magnitude were conducted to evaluate the role of rebuilding costs in determining optimal strategies, by multiplying the costs of movement and of pit reconstruction by 0, 0.1, 0.25, 0.5, 2, and 5.

A difficulty with this approach was deciding what information to provide an antlion about its immediate past foraging success at its starting date and location, because this information was not contained in the data set. Without such information, the antlion would be unable to relocate until a full interval of days had passed, which might introduce a substantial bias into the analysis. We attempted to minimize this problem in the following way. Each antlion began with an interval of information about its "virtual past" at the present location, derived by sampling with replacement from the first seven days of actual data for that location. This ensured that the antlion began with a plausible initial evaluation of the location, and might or might not initiate a pit relocation within the first interval of foraging. The number of days of data chosen for sampling to provide this virtual past seemed, in preliminary runs, to have little effect on the results; the 7-d period was therefore chosen arbitrarily.

Antlion Foraging: Tracking Prey Across Space And Time

Ecology, Oct, 1999 by Philip H. Crowley, Mary C. Linton

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