Welcome Back Bloggers!
Today, I’ll be talking about leaves. Yep, leaves. Sounds a little boring when you think of the simple word “leaves” but I assure you, it’s more interesting than you think.
Specifically, I’ll be talking about Oak leaves. In this lab, we could’ve used one of two types of Oak leaves; Red or White.
Here’s what a Red Oak leaf looks like:
Here’s what a White Oak leaf looks like:
Just by looking at it, it is pretty easy to distinguish between the two. The Red Oak has a lot pointier edges whereas the White Oak is rather smooth all the way around.
For this lab, we were to choose one specific type of tree and grab 10 leaves (intact) from the inner portion of the tree (closer to the trunk) and 10 leaves from the outer portion of the tree. These 20 leaves were to be taken from the same tree and separated into ziplock bags based on where they came from the tree. I chose the Red Oak for this experiment.
Referencing back to basic knowledge, we know that all green plants go through a process called photosynthesis. But here’s the important part… Tree leaves need to capture light for photosynthesis, right? However, they need to minimize heat. Tree leaves need to take in carbon dioxide, right? However, they need to be careful to not lose too much water. It’s all a matter of balance or else they die.
So now with that known, which part of the tree will thrive the most? The outer leaves that are exposed to light way more often, or the inner leaves that still receive light but not nearly as much?
My hypothesis was that “If the outer leaves are more exposed to sunlight, then they will be greener (more vibrant), bigger, and fresher than the inner leaves from the same tree. Without testing anything, I simply made this hypotheses by looking at the tree I was taking data from. As soon as I walked up to the Red Oak tree, I thought to myself that it was pretty healthy. However, when I started picking off leaves from the inside of the tree, I didn’t think the tree was as healthy any more. Visually, the leaves were smaller, less vibrant in color, and almost wilted and crackly. Of course, I can’t base an entire experiment off of just looks, so I had to collect and analyze the data.
Once we had all the leaves, it was time to record our data. We looked at the surface area of the leaf in centimeters squared in order to study within-individual variation. I’m not going to lie… this was a time-consuming and very repetitive process. In order to measure the surface area, we had to trace all 20 leaves on this 1cm by 1cm grid graph paper. After tracing the leaves, we were to count every single square inside the leaf (if more than half of the square was taken up, you would still count it). Once recorded, we were to give our numbers to the professor in order to collect a class data of everyone’s leaves. Remember that some leaves were from a White Oak while others were from a Red Oak.
Let’s look at the results!
This bar graph below only show my personal results with my 20 leaves from the Red Oak tree. As you can tell, the inner surface area is less than the outer surface area, just like I predicted. However, is this statistically significant?
Down below is the t-test with the p-value. All we really need to look at is the p-value with the two tails. Anything greater than 0.05 is not statistically significant. However, our p-value shows a number way below 0.05! This means our data is statistically significant and that my hypothesis was right!
Now, let’s look at the class data for the Red Oak trees!
As you can tell from the graph below, there is less of a difference between the inner and outer portion of the tree in the class data. Visually, it is unlikely that this data is statistically significant but let’s take a look at the p-value.
Here’s the t-test for the class data on the Red Oak trees. Again, the only really important thing to look at is the p-value with the two tails. Since the p-value is way above 0.05, the data is not anywhere near statistically significant. When referring to the class data for Red Oak trees, my hypothesis is wrong.
Lastly, let’s look at the class data for the White Oak trees!
As you can see from the graph below, there is a way bigger difference between the inner and outer section of the tree in this class data for the White Oak than there was for the Red Oak class data. Let’s see if it’s significant enough!
Here is the t-test for the class data on the White Oak tree. At first, the results scared me. I thought they turned out to be not significant at all which messed with my head. Then I realized that it was in scientific notation and that the real number was actually 0.00000087703. So, this turned out to be the most statistically significant data out of all the groups!
So why would we be interested in understanding within-individual variation in trees? How do you technically explain within-individual variation?
I really like the way this scientist, Peter Chesson, explains it in a peer reviewed article called Predator-Prey Theory and Variability. He states: “… individuals in the same population are treated as identical in all aspects of the phenotype that matter. Variability, or randomness, enters as a within-individual process having the same probability distribution for every individual regardless of its phenotype. This within-individual variation may be compared with the toss of a coin. The outcome (heads or tails) is unpredictable not because this coin differs from other coins unpredictably, nor because the environment of the toss is unpredictable, but as a result of unpredictable factors inseparable from the particular toss of the coin”.
Ecologists and farmers both want to know the importance of variation for basically the same reasons. Both want to know how it can benefit something and they want to be able to understand it if something goes wrong. For a farmer, they would need to record the surface area of a plant in order to know if their crops are thriving or not. This could potentially save them a lot of money in the future. Like Chesson said, “unpredictable factors” can effect the variation.
In another science article called In ‘Science’: Wildflowers combat climate change with diversity by Adrienne Berard, the article discusses a study with seep monkey wildflowers (Mimulus guttatus) and how the wildflower changes in an area that has very frequent climate fluctuations.
Josh Puzey, assistant professor of biology at William and Mary, was the one explaining how the variation worked between the seep monkey wildflowers. According to Puzey, he and his team were “able to identify specific regions in the genome that control flowering time and flowering size. They found that the same region controls both traits . . . the flowers had evolved over time to maintain genetic variation in flower size, because it helped them survive”.
In the end, Puzey and his team ended up finding that the seep monkey wildflowers are very well-adapted to climate fluctuations. Luckily for these flowers, that means that they would most likely survive and adapt to rapidly changing global climate change. However, not all other plants are this lucky. Like many know already, climate change has many consequences on multiple factors, not just the flowering time in flowers. Because of the change in flowering time, this effects the schedule of pollinators. As the chain continues, consequences get worse. The bottom line is: even if one species of plant manages to adapt and thrive in an environment where climate change is rapidly growing, it does not mean the rest of the environment is safe.
We don’t want to end up like this:
This is what is happening:
We can’t take advantage of the Earth and pretend we’ll be ok later in the future with the way we’re treating the planet right now. Right now, we’re being selfish and not thinking about the future generations. A well maintained Earth = Happy Earth = Happy People.
See you guys next week!
Chesson, P.L. 1978. Predator-prey theory and variability. Ann. Rev. Ecol. Syst. 9, 323-347.