An optimal forager is an organism that maximizes their net gain of energy while foraging. Energy gain is a way that scientists can measure the fitness of an organism. As one would expect, the greater the net energy gain, the greater the fitness. When animals are in the wild, prey are distributed among patches of different densities. In an area of low prey density, a forager will have a low feeding rate. In an area of high prey density, a forager will have a high feeding rate. Organisms expend energy traveling to a new patch, and organisms must decide when it is time to leave a patch. Scientists can use a cumulative gain curve to show the rate of energy gain in one patch. To determine the maximum net gain of energy, they take the tangent of the line. If the animal leaves before or after that time point, they are not obtaining the maximum net energy. If scientists want to observe the maximum net energy of the whole environment, they use the same method and find the maximum for each patch.
To observe and describe behavior of consumers, scientists use an optimal foraging model. In this case, the Marginal Value Theorem is used. The model allows scientists to predict four situations. For one, foragers should capture more prey in patches with high prey density. They should remain here longer, too, and they should catch more prey in a timely manner. Finally, once the intake rate begins to decline in comparison to the environment, the forager should leave the patch. In other words, giving up time (GUT) should occur more quickly in areas of low prey density.
In this experiment, students aimed to use an optimal foraging model and act as foragers themselves. They foraged for beans in three patches of varying density. Students will spend more time scavenging in the patch with high density than that of average or poor density, where they will find more prey. This hypothesis is based on the predictions from the Marginal Value Theorem.
At Chamberlain Pavilion, three containers of rice and beans were placed at approximately two yards apart. Container one was a patch of low density with only five beans in the patch. Container two was a medium density patch with fifteen beans in it. The third container had the highest density with thirty beans. This set-up was repeated so there were four rows of the three containers. Students did not know the densities of the containers until the activity ended.
Each student foraged for two minutes. When time began, they traveled to a patch and foraged for beans with one hand. When they found a bean, they placed it in a bowl and swirled it around three times to mimic handling time. When they felt ready, the student left the patch and traveled to a new one to forage. They continued foraging until their two minutes were up. While the student foraged, a different student noted the time of arrival at each patch, the time of departure from each patch, the time at which each bean was found, and the ending time.
Students took this data to analyze. They recorded the patch density, or the total number of beans in each patch, and the beans they found in each patch. They recorded the seconds they spent in each patch. They also calculated capture rate in units of beans per second by dividing the total beans found in a given patch by the total time spend in the patch. Lastly, they calculated giving up time (GUT) for each patch by calculating the difference in the seconds between the last bean capture for a patch and the departure from that patch.
I captured four beans in 17 seconds at patch one. This gave a capture rate of 0.24 beans per second. The giving up time was two seconds. In the second patch, I found nine beans in 36 seconds. The calculated capture rate was 0.25 beans per second, and the giving up time was one second. Lastly, I found 17 beans in 58 seconds in the last patch for a rate of 0.29 beans per second. The final giving up time was five seconds.
Figure 1. The forager’s cumulative gain curve for each patch
The forager’s prey captures are plotted with time to create a cumulative gain curve.
Figure 2. Beans found in each patch in comparison to patch density
The blue column shows the number of beans found in each patch. The orange column shows the total number of beans in each patch. In patch one, 4 beans were found. The patch had 5 beans total. Patch two had a density of 15 beans with 9 found. Patch 3 had a density of 30, and 17 beans were found.
Figure 3. Time, in seconds, spent foraging in each patch
The forager spent 17 seconds in the lowest density patch, patch one (dark blue). The forager spent 36 seconds in the medium-density patch, patch two (silver). Finally, the forager spent 58 seconds in the high-density patch, patch three (light blue)
Figure 4. Capture rate in beans per second of each patch
The forager captured 0.24 beans per second in the lowest density patch, patch one (blue). Beans were captured at a rate of 0.25 beans per second in the medium-density patch, patch two (orange). Lastly, the forager captured 0.29 beans per second in the high-density patch, patch three (silver).
Figure 5. The giving up time in seconds at each patch
The forager had a giving up time of one second in the low-density patch, patch one (yellow). The GUT for the medium-density patch, patch two (orange), was two seconds. The forager had a GUT of 5 seconds in the high-density patch, patch three (green).
Discussion
The given figures analyze different predictions of the optimal foraging model. The first prediction of foragers capturing more prey in high-density patches is represented in Figure 2. Figure 2 shows that the organism captured more beans in the high-density patch, capturing seventeen beans in patch three. The organism only caught nine beans in the medium-density patch, and four beans in the low-density patch. This is consistent with the model. Figure 3 shows the results of testing the second prediction from the model. According to the model, foragers should spend more time in patches of high density. The results are consistent with this prediction as the forager spent the most time, 58 seconds, in the high-density patch. The forager spent 36 seconds in the patch of medium density and only 17 seconds in the patch with the lowest density.
Figure 4 aligns with the third prediction of the model; foragers should capture more prey in a timely manner in the high-density patch. In this experiment, the forager captured 0.29 beans per second in the high-density patch, which is higher than the rates of the medium and low-density patches, 0.25 and 0.25 respectively. The final prediction of the model is shown by Figure 5. GUT is supposed to occur more quickly in patches of low density. The results from the experiment deviate slightly from the experiment. The forager did exhibit the longest giving up time in the high-density patch with 5 seconds. However, the forager had a GUT of two seconds in the first patch and one second in the second patch. The first patch was of lower density than the second, but the GUT was a second longer.
With Figure 1, it can be seen that the foraging does exhibit rather optimal timing. The slopes of the lines are relatively straight for all plots. So, while foraging, the organism was consistently capturing beans and spent more time capturing more prey in the high-density patch. This supports my hypothesis that foragers would capture more prey and spend more time in the patch of the highest prey density. However, I don’t think that the optimal foraging theory is accurate to apply to humans. This reflects the GUT in Figure 5. In the first patch, I had a GUT of only one second. That was because I had watched others and figured out that it was low density. I found that the second patch was in the middle, but I didn’t know how many beans were in it.
I would expect foragers to fulfill the predictions of the optimal foraging theory in a situation where they aren’t being hunted themselves. Every moment spent out hunting for an organism may mean they’re being hunted as well. So, in an ecosystem with a complex feeding web, however, I don’t think these predictions would hold up quite as well.
Exploring Ecology 