They Don’t Know When to Quit: Investigating “Overharvesting” in a Simulated Berry -Picking Experiment

Overview

Harvard Medical School From assessing mammograms to finding lost keys, visual searches are ubiquitous. This study employs a berry-picking scenario to study the effect of external distractions on optimal decision-making. In our model, berries are harvested at various different patches, and movement between patches involves a “travel time” during which no berries may be picked. Previous research on similar visual foraging tasks has supported the marginal value theorem (MVT), stating that individuals generally move from one patch to another when their instantaneous rate of picking drops below the overall rate. However, our unique investigation included a multiple item tracking (MIT) distraction during the travel time between patches, and as a result participants were observed to spen d longer than optimal time in the patch — deviating from MVT predictions. The observed overharvesting was hypothesized to result from the participants' lack of awareness of their real - time “current" overall rate. Though patch leaving behavior is governed b y the overall rate as stated by the MVT, this rate can only be calculated once the experiment concludes. To rectify this, a “current" overall rate was calculated and updated by click for comparison with the instantaneous rate. Data analysis showed a decrease in overharvesting when comparing instantaneous rates with a by -click updated “current" overall rate rather than the overall rate calculated post -experiment. Despite these improvements, a definitive underlying cause remains yet to be determined. Regardle ss, these findings provide valuable insight into patch leaving behavior — applicable to not only berry patches but also medical scan analysis, resource management, and more.