 So one of the big things is that the diversity in the roots differ by plan home. So the plans were different. Here we have on the x-axis, the different time points, y-axis is the richness of the different plans. And for bacteria and fungi, we can see how overall, yes, they start different at the very beginning, but towards the end they look fairly similar, or they have similar value, similar richness. But on the contrary, we can see on the roots for both bacteria and fungi across all time points, Kentucky had higher richness compared to swishgrass. Also, we wanted to see how the community structures of these plants, like if they were, like yes, we are looking at some differences in richness, but how that would relate to the community structure. Like, do they have a similar community structure? And so far, it turns out that they don't. So they have different communities, red being Kentucky, green being swishgrass. We can see here in the raster sphere how they are grouping together in this PCA plot. So in this graph, you are looking at how the closer they are grouped, the more similar they are, the farther apart, the opposite they are. And we can also see in the same way how in the roots in the bacteria community, they are different. We have red here, green here. And for fungi, it's same in the raster sphere for bacteria, we have two different distinct groups based on the plants. Here, even though it was to the Permanawa significant, and we can see red and green separated, they're still more spread out. I'm still trying to wrap my head about this part that it may be due to the fact that the microbes that are getting recruited to their roots might be more similar, even though it tends to be more post-oriented, still it's more similar because you have fewer microbes coming in and getting recruited by the plants. On the other hand, so we are looking, let's take a moment so we have different richness, different community structure. So how would that relate if we want to see it in a composition of that community? Here, for this purpose of this talk, I'm just going to be focusing on the rhizosphere. The trends are similar in both rhizosphere and root. And here we can see in this, the x-axis are all the samples ordered by the time points. Y-axis is relative abundance from 0 to 100%. And I'm just showing you guys the top 10 families. And you'll see a lot of colors, but I just want to highlight a particular one for an example that is the family Santa Monada CI. We can see here how in Kentucky bluegrass is higher than swishgrass. So we saw this and we were like, OK, is there another way we can test these differences? And we did what is called a differential abundance analysis. So we were looking to see have another statistical test to see the differences. And Y-axis is the log 2 full change. So how different they are. And the Y-axis here is the p-value. So how significant it is. And here, anything that is in the positive values in the log 2 full change, it is favored towards swishgrass. And everything that is on the negative values are favored towards Kentucky bluegrass. And here we can see again, Santa Monada CI that is being favored by Kentucky bluegrass that we can relate to the composition that is higher than swishgrass. And in addition, we went like, yes, we are seeing these differences, but we wanted to narrow it down a little bit more to show it across time and have a couple of other examples as well. So here we can, we have Keton audio bacteria that it was higher across time through in swishgrass. Immunobacter CI was higher in Kentucky bluegrass throughout, even though it fluctuated, their abundance. You can see it is still higher than swishgrass. And we have Santa Monada CI, the micro, the family that I was using as an example to show you guys all of these differences that it was throughout all the time points, it was higher in Kentucky bluegrass than swishgrass. So as we saw in the bacterial community, we also saw similar patterns in the fungal community. So again, y-axis is the samples ordered in time. The y-axis is relative abundance. And here I went to get you guys to look at the light green order, in the case of the fungi, that we can see how in Kentucky there's no a whole lot, but in swishgrass there is more. Again, we did a differential abundance analysis where we can see Ipocrealis being favored towards swishgrass. So we can see how here we definitely have more of them. And through these other statistical analysis, we can see it again being favored towards swishgrass. And again, we did present them across different times. And here we can see x-axis is the different time points relative abundance of the different fungal orders. And we can see how Ipocrealis seems to be higher in Kentucky bluegrass. But then as was shown previous that it was favored, we have Ipocrealis to be higher in swishgrass throughout time as well. So we are looking at to see all of these differences starting from the richness across the different plants, the community structure of these plants, how the composition of these communities is affected by the different plant hoses. So we wanted to tie in everything and look at to the root exudates. And so this is a PCA plot looking at all the metabolites that were identified. And to my surprise, because this is the first time working with this type of data, I have found that, of course, swishgrass and Kentucky bluegrass have a different metabolic profile. And just to, for an example, here I'm just showing a couple of different metabolic classes. And we can see how they is here in this first one, how they have the three different time points from second, third, and fifth. How here we can see an increase towards the end in swishgrass, aliphatic compounds. We have a different weight, different relative abundance of these compounds, similar in cyclinucleotides and actinamines. We can see also they are different. So this is just an example. I will have to go in and see a specific metabolite, because here I'm just grouping them in their different classes. But this is just to highlight that in their metabolic purex weight profile, they are different. And we can reflect to how different they are in the community, structure, richness, and compositional. So big conclusion is Kentucky bluegrass and swishgrass, they are different in both communities and exodates. And a couple of the implication of this work to all the labor that you guys are doing in researching pool grasses is how these differences can be inferred, how Kentucky bluegrass in a dominating in a grassland, it definitely will impact below ground dynamics. In addition, we have to think about how are the aspects of the microbial community with the sum of all the physiological strategies that Kentucky bluegrass have can dominate or keep dominating native ecosystem. And finally, one thing is that in another project that goes through different management practices, we already seen with the reduction of Kentucky bluegrass, we have an increase in microbial diversity. So this is actually really cool that we have all of these differences. It is dominating, but when we have management practices in play, we start seeing differences in the microbial community. And finally, I want to thank everyone, Dr. Banagy, Dr. Kevin Sereveg, Chandi Kaiser, and everyone for having me today, giving you guys this talk. And thank you.