Leaf Injury Assignment- Spring 24

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Kennesaw State University *

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3370L

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Biology

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Apr 3, 2024

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Inferring patterns of herbivory from leaf injury BACKGROUND Much plant tissue in the world is consumed by a myriad of herbivorous animals. Some herbivores specialize on particular species and on particular parts of the plant, while other species are more general. Not surprisingly plants have evolved defenses to counter herbivory, involving both mechanical and biochemical responses. For example, plants whose tissues have been injured by herbivores can respond by translocating toxic secondary metabolic products to these injured areas. Herbivores can in turn evolve behaviors to respond to these defenses. The Plain Tiger Danaus chrysippus caterpillar carves out circular trenches in the leaves of milkweed, severing leaf veins to prevent defensive chemicals from entering this tissue in the middle. Often times in the study of ecological systems, important events are too rare to be observed, or are hidden from view of the ecologists. For example, how likely would it be that one would one would observe owls preying on rodents during a dark night of observation? As a result, ecologists must often rely on indirect measures to estimate the nature and intensity of ecological events. In this lab, we will survey patterns of injury to leaves as a way of inferring processes associated with herbivory. Alternatively, we could bring an herbivore into the lab and observe it feeding on a given plant, but removed from its natural setting we could not be confident on whether what we observed in the lab actually occurs in nature. You will not test specific hypotheses in this lab. Often in science, exploratory quantitative data sets are generated in order to establish trends from which hypotheses can then be formulated. In the first week’s lab, our hypotheses were generated from casual observations. By sampling quantitatively, we can be more confident that the trends we thought we observed really do exist (i.e. are statistically significant) before we spend a lot of time testing ideas on why those trends exist. In other words, we should establish that there is a difference before testing why there is a difference . INSTRUCTIONS Work in groups of two. From the forest near the science building, collect at least 30 leaves of one plant species, placing them in a plastic bag. Try to collect these as haphazardly as possible (in other words do not base your selection on whether they have damage or not). Collect only leaves on the surface of the forest floor (leaves deeper down in the litter are more likely to have tissue missing due to decomposition rather than from herbivory). Return to lab and measure the following on each of 25 of the leaves you collected, then switch your leaves for another group’s leaves ( MUST BE DIFFERENT SPECIES ) and repeat the measurements:  Taxon (type) of leaf  Length of leaf (in centimeters); measure to nearest mm (ex: 12.4 cm)  Number of injuries along margin of the leaf  Number of injuries (holes) away from the leaf margin (count only those that penetrate all the way through the leaf)  Total percent of tissue removed from each leaf (estimated as falling in one of the three injury categories listed on the following data sheet).

Estimated amount of tissue missing (indicate with check mark √ and check only one) Taxon (type of leaf) Length (cm) Number of injuries along margin Number of injuries away from margin No tissue missing Minimal damage 0- 10% Substantial damage >10% 1 White oak 21cm 3 5 1 1 2 White oak 18.5cm 2 1 1 1 3 22.5cm 5 12 1 1 4 13.5cm 5 3 1 5 22.4cm 5 40 1 1 6 17.2cm 1 0 0 1 7 12.3cm 0 0 0 8 19.7cm 2 2 1 1 9 19.9cm 1 1 1 1 10 15.2cm 4 10 1 1 11 16.1 3 7 1 1 12 15.5cm 1 4 1 1 13 18.3cm 4 5 1 1 14 15.1cm 3 22 1 1 15 9.5cm 2 1 1 1 16 17.1cm 2 1 1 1 17 13.2cm 5 4 1 1 18 18.4cm 3 7 1 1 19 15.1cm 6 25 1 1 20 12.0 2 4 1 1 21 11.0cm 6 4 1 1 22 10.0cm 1 2 1 1 23 11.6 1 1 1 1 24 11.7cm 1 2 1 1 25 12.2cm 3 15 1 1

Estimated amount of tissue missing (indicate with check mark √ and check only one) Taxon (type of leaf) Length (cm) Number of injuries along margin Number of injuries away from margin No tissue missing Minimal damage 0- 10% Substantial damage >10% 1 beech 11.6 0 3 0 1 2 10.0cm 3 2 1 1 3 11.2cm 1 5 1 1 4 10.5cm 3 7 1 1 5 9.5cm 2 5 1 1 6 10.6cm 2 50 1 1 7 11.8 0 19 1 1 8 11.4 0 7 1 1 9 9.0cm 0 13 1 1 10 9.0 1 2 1 1 11 12.0cm 1 60 1 1 12 9.1 2 3 1 1 13 8.3 3 1 1 1 14 9.5cm 1 2 1 1 15 6.91 3 8 1 1 16 7.9cm 1 4 1 1 17 10.7cm 0 5 1 1 18 12.5 1 1 1 1 19 10.2 3 40 1 1 20 6.4 2 3 1 21 8.2 3 3 1 1 22 8.3 3 1 1 1 23 9.3 2 4 1 1 24 9.2cm 3 2 1 1 25 8.0 2 16 1 1

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ASSIGNMENT SEE NEXT PAGE FOR REQUIREMENTS FOR FULL CREDIT FOR EACH STATS TEST TYPE 1) Examine the data set. “ Explore ” the data by plotting two variables against one another, or by calculating and comparing some means and standard deviations. From this, identify two trends (relationships) or lack of trends among variables. Do NOT compare average leaf length between two species (you will get a 0 on analyses comparing mean leaf lengths). Using an appropriate statistical technique, determine whether the relationships are significant. For each trend or lack of trend, you should: a. Prepare a graph b. Describe the trend in a sentence or two c. Report the type of the statistical test used and the results of the test. Be sure to report the P-value if needed and whether it is considered significant or not. Do NOT use same stats tests for the two trends! Change trends if this is the case (-10% if you use same stats test) 2) From your analysis of the data, generate two possible hypotheses that might explain the trends you found . Make sure the hypotheses you generate are not the same ones you tested or could test with our data set . For example, do not use as a hypothesis “number of injuries will differ between the two plant species”, but instead come up with a hypothesis that tests why this might be (a biological/ecological explanation). Don’t be afraid to speculate here. 3) For each of the two hypotheses, come up with a hypothesis that proposes an alternative, different explanation as to why you found what you did. Note that I am not asking for a null hypothesis here. I am looking for biological explanations. 4) One partner turns in a MS Word or PDF of the report AND the Excel document showing your raw data and statistical tests (including the cells with the formulas/ commands to run the stats test). Be sure BOTH peoples names are on the documents, for example “Smith and Jones.docx” Flowchart of assignment requirements: Dataset Explore trend 1 stats test Describe trend (or lack of) Write two hypotheses/expanations graph Explore trend 2 stats test Describe trend (or lack of) Write two hypotheses/expanations graph

Required elements for each stats test type (you will choose which test you should run on your data for the questions you are asking) NOTE: remember to round off statistics as described in Lab 1 Part 2. (half-credit given if you do not round off and provide a bazillion decimals) T-test  Report values for: o Means o Standard error (half credit if standard deviation is given instead) o P-value o T-Stat  Graph o Appropriate type graph (bar or column chart) o Axis labels o Proper error bars  Do not choose Excel’s default error bar option, calculate standard error for each mean and then add the error bars as “custom values ” o Title or caption Chi-squared test (only for “counts”)  Report values for: o Contingency tables  Two separate tables  Observed  Expected o P-value  Graph o Appropriate graph type (bar or columns charts) o Axis labels o Title or caption o Legend Correlation  Report values for: o Correlation coefficient (r)  make sure to discuss whether this is positive or negative in your discussion and what that means  P-value o Graph  Appropriate graph type (x vs y AKA scatter plot)  Axis labels  Title or caption Linear Regression  Report values for o R 2 o Y=mx+b equation (AKA trendline, line of best fit, line of regression) o Any predicted values you may have made (ex: if X=…, what will Y equal?) o P value  Graph o Appropriate graph type (x vs y AKA scatter plot) o R 2 and equation on graph o X-axis is independent variable o Title or caption

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