1. Based on Week 2's lab, what "feeding types" could have caused some of the observed damage in each of the systems? Any guesses as to what caused (including non-insects) the feeding damage in each of the systems? Aside from feeding, what other types of damage did you see? Were there any signs of "indirect" damage?

The kind of feeding damage seen in week 3’s lab appears linked to chewing mouth parts, which are typical of borer worms associated to corn and sorghum. Here it is important to note that different species may be causing the same kind of damage in both corn and sorghum (i.e., ear borers see figure 1). In the case of soybean, the round damages seem associated to leaf beetles, specifically leaf bean beetles, which are usually associated to those kinds of damage (figure 2). However, in both cases it was possible to see other kind of damage aside from feeding. In the case of corn, the damage caused by worm borers may be allowing the entrance of opportunistic fungi pathogens that proliferate in the areas affected by caterpillars, and in soybean leaflets there are additional damage that are not necessarily caused by leaf beetles but probably by harsh environmental conditions such as heavy winds and hail.

2. What was the sampling unit in each of the cropping systems? What was the sample size for each cropping system? Briefly explain your estimation method for each system.

The sample unit in corn was the ear and the sample size was 30; in sorghum the sample unit was the sorghum head and the sample size was 30; and in the case of soybean the sample unit was the soybean leaflet and the sample size was 50. The estimation method in each system consisted in the visual estimation of the percent damage.

3. Is estimating damage an "absolute" or "relative" measure? Explain your reasoning.

Estimating damage in this laboratory session is a relative measure because it does not intend to estimate the number of insects in absolute terms (i.e., in a predefined unit of measure such as field area, plant part, etc.), instead of that it provides a representation of the insects population by means of a qualitative scoring of their damage.

4. Based on your experience with the three crops, what possible factors affected your accuracy (hint: think about the sample units used within in cropping system)? Please be sure to talk about each crop.

In the case of Sorghum and Soybean my accuracy was of 78 and 81% respectively, which means that in a 78-81% of the cases my predicted level of damage was in agreement with the observed (actual damage). On the other hand, my estimation of damage in Corn was only 18% in agreement with the observed damage. My estimation of the levels of damage seems to be more accurate when evaluating soybean leaflets and sorghum heads than when evaluating corn ears. The sample size could be one of the factors related to my lack of accuracy in Corn (maybe more ears would increase my level of accuracy in corn). Besides, the different sizes of the ears evaluated could represent an additional challenge at the moment of calculating the percent of damage. However, an additional factor could be related to my lack of accuracy when evaluating corn ears. It is possible to suggest that the kind of damage and the visual impact that it creates in the sampler could represent a tendency to either underestimate or overestimate the level of damage. That is, when evaluating soybean leaflets and Sorghum heads, at first sight, the contrast between the affected and the healthy areas is related to estimating the percentage of clean areas in the soybean leaflets, and to estimate the pale areas in the sorghum heads (figure 3). On the other hand, when evaluating the damage in corn the sampler attention may not be necessarily focused in the borers tunneling and/or the kernel missing, but affected by the nasty display of the pathogenic fungi associated (figure 3), that could be ultimately incentivizing higher scores in percent damage and reducing accuracy.

5. Compare your results with those in the rest of the class. How did you do? Did you over- or under-estimate percent damage? Who best estimated damage in each of the cropping systems? How could you use this information when making future estimates?

As in my particular case the class exhibited a tendency to express more accuracy when evaluating sorghum heads and soybean leaflets, whereas a low level of accuracy was found when evaluating corn ear damage. In the case of sorghum 64% of the students showed a R2 equal or higher than 70%; at the same time soybean 82% of the students showed a R2 equal or higher than 70%. On the other hand, in corn only two students showed a R2 equal or higher than 50%. With that said, it is possible to consider that samplers could be affected by the kind of damage expressed in the different crops. As mentioned previously, the visual impact of the damage in corn may be affecting the level of accuracy in the evaluation driving an overestimation of the real percent of damage. As a matter of fact, almost all students (with the exception of only one) showed slopes that were less than 1, which means we were overestimating the level of damage in corn ears. In my case the slope was 0.44 which means that my predicted levels of damage were higher than the actual damage by more than 100%.

6. Discuss any challenges with this exercise or possible implications for over or underestimating damage observed in the field as it relates to pest management.

As seem in the exercise different factors could be affecting the efficiency and the accuracy at evaluating the level of damage in different crops. A factor discussed in this post has to do with the visual impact of certain kind of damages that tend to drive the sampler to an overestimation of the pest impact in the field. The previous situation could represent an investment in control tactics that are not precisely necessary by the time of the evaluation and would represent a waste of money and effort. To have the chance to check on the qualitative evaluations and the levels of damage obtained (as in this exercise checking on predicted vs. observed levels of damage) would be very helpful at refining the accuracy of the samplers without reducing efficiency.

7. Statistics

Crop	Mean percent damage	Standard deviation	Standard error of mean	Coefficient of variation
Soybean	13.7	15.4	2.2	15.9
Corn	7.0	6.5	1.2	17.0
Sorghum	34.8	34.7	6.3	18.2