 Yeah, so so vegetation monitoring is kind of the the nuts and bolts of what I do day-to-day and have for about 25 years throughout the Midwest mid-south collecting data usually in conjunction with with O fire ecology studies and long-term management projects some of the projects we have are 20 plus years old And it's it's a doubly difficult thing to do because you're really balancing taxonomy in the field field taxonomy and applied ecology conservation Concepts as you go along things like like what Alan's doing with the the floor the southeast really makes a lot easier the Better we can identify things the quicker we can identify things And the more we can start getting a handle on ecological concepts the the easier this that's a Venn diagram of two very difficult different worlds or taxonomy and conservation The better they start moving Vegetation speaks volumes when you when you look at a when you look at a vegetation, you look at the community level dynamic Vegetation over management time Plants are are they are the key to that because they're the primary producers all energy that moves through systems starts with plants capturing light energy Making it into chemical energy, which basically literally fuels the entire system and then these systems are always changing We know in the in the images there on the screen the left side is sort of a Stable old growth sort of system that if you came back 10 years later It's likely to look very much like that on the right side of the screen the image there is a log landing with Burn weed Eric tighties and logs and you come back in 10 years. It's not going to look like that It's going to change faster. So the the relativity of change in systems is one of the things That makes us need to monitor so we know we know there's things are changing. We know they're going somewhere. Monitoring kind of helps us get an idea of where they came from and where they are going. The methodologies that I tend to use I've used a lot over the years and and My my my organization has basically become the data collecting wing for most state and private conservation organizations in my region at least. And so we use a lot of different methodologies. What I find best is we tend to use 25 quarter meter quadrats and sort of a grid pattern similar to the bottom left of the screen. And we can expand that to larger communities like prairies or we can shrink it down into to woodland woodland communities as well. The analysis is where the sort of nuts and bolts come from we collect data. But then the question is what do you do with it when you have it. That's that's the hard part. That's where the interpretation comes in. And so you got to know what you're looking at and what variables are going to be. What you're looking at and what variables are important. There's the classic traditional diversity variable variables that most monitoring programs projects look at richness, which is simply the number of species you might have an A plot or whatever your whatever your sampling design is Shannon diversity or some form of diversity is the distribution of those species. So you have certain number of species, but as are are they distributed evenly or they all run one corner diversity explains a lot More stable more complex more mature systems tend to have higher diversity and higher richness. Dominance is something that I like to look at to you can look at like the top two or three dominant species how they change over time. And then something that a lot of people don't use that's less less common as a florist equality assessment. And that's using coefficients of conservatism see values that's a number of scientists species. Zero through 10 based on though how good of an indicator they are of an intact old stable sort of system. So mean C value the average of those numbers that are plot becomes very important and is kind of the crux of interpretation I think and I'll give an example of that in a moment. And then physiognomy, the ratio of annuals, perennials, grasses, Forbes trees, yada yada young. And here's the example that I like to give. These are traditional variables you got richness and diversity on an XY axis these are 12 prairie plots of varying condition. And so you've got a nice nice strong sort of linear relationship there, and you would interpret that as on the bottom left, low diversity prairies, in this case, tend to also have low richness, and then on the top right, you have a greater diversity greater number of species we tend to find this over and over and over. Um, but the notice the red and black dots at the top right at the very end of the end of the line there. Those from experience and from having collected the data. Those are two very different prairies. The red one is actually closer to an old field. It's got fescue it's kind of beat up. It's an old hay field and old graze field, the black dot, in that case, is one of the highest quality grade a prairies that we have in the region. And so it's odd that those rank so close together. Um, switching slides here now we've got sort of a negative correlation between diversity and dominance so when you have a dominant species of something's more. If you have something like big bluestem in this case and a prairie that's more common the more common it is the more the more abundant it is, the less capacity there is for other things to be there so richness and diversity and things will go down. But again, the main point here is that the red and black dots again, a really poor quality prairie and a high quality prairie are scoring on what you would perceive as to be the better grade. And there's those dots again. So, so it really, we're really missing an element here and that's that's why we use fluorescent quality assessment it gives us some directionality to to management and when we do our monitoring, we can see where something is going where it's been. Those three variables richness diversity and dominance plotted here against C value on the excess access so as you go from left to right here we're increasing in C value and C value should be later successional longer live more perennial more stable vegetation types. And so what you find like on the on the left side here is with diversity that red dot the prairie that is that red dot it pops over there on the left side is being lesser quality than on the right side. And you get these curvilinear relationships which are are themselves just fascinating them. But what you the take home from this is that richness and diversity, even dominance aren't really great indicators in and of themselves you need some sort of qualifier, you need a qualifying variable, which is what C value is we qualitatively determine that ragweed is more quality than platanthrocillary of a higher C value habitat specific organism. And then when we average those we get these relationships and different community conditions that we can track and follow over time. And so you really need a qualifying variable. What I often give is also you 100 cars for $1000. The first question you should want to know is, what is the condition of these cars, the quantity isn't really the point, the quality is, is ultimately what you're interested in. When we plot those mean CVAs we start seeing this distribution that curvilinear relationship with and we start graphing at across really degraded systems and then really high quality systems. We consistently find this curve that with my staff and I have started calling the floristic integrity curve. And the main point here with it is that that system maturation is not linear we tend to think of restoration and things like that as being. Okay, we go from point A to point B and that's a straight line, but it's not there's there's sort of a hump in the middle you get to this, we got called the, the dominance trough there where there's a point at which dominant vegetation overpowers, annuals by annuals things like that. And then you start building a second tier into a more stable long term system. And fun fact is as we start looking more into this relationship we start realizing that this is really a nitrogen dynamic. You can you can plot this and we started collecting soils, along with our monitoring programs to look at nitrogen, at least available nitrogen nitrate, primarily. And at the time that that succession all graded that maturation of living systems tends to pretty strictly a decreasing available nitrogen so we can we can start thinking of maturing systems or whether you have an old, old, stable high quality system that's probably going to be inherently low and available nitrogen, you increase nitrogen you tend to increase nitrophiles, which are annuals and and we sort of things. The monitor were kind of inadvertently monitoring, at least with C values, the change in nitrogen availability over time. And so some of the other some of the other results we get from this by looking at C values and looking at nitrogen and systems across long term projects that the projects I've been involved in. There are several things that tend to go against conventional thought. One is that, at least in the Midwest, somewhat in the Mid South, non dormant season fires. So, so spring fires summer fires things like that growing season fires tend to have negative impacts on the seed value they increase nitrogen from the ash and char that's from the fire. Another thing to intense to frequent the fires have negative impact packs and cause mortality, which increases nitrogen. What we also find is helpful fires kind of gives you just more of what's already there. I think there's a, there's a notion that burning will, you know, burn it and they will come data from study after study in our region and my region at least shows that you kind of just have more of what was already there. Which is good. If I, you know, you need a triage places that have a lot or have the most potential. And those are the ones that you should focus on. If you have a degraded sort of wood lot Prairie Glade, what have you know I'm not the fire is going to going to revive it. Think of it as the one of the paddles the defibrillator, you know, if somebody's been flat lined for an hour, you're probably not going to, you can shock them while you want it's not going to do anything. And again, nitrogen's the driver of a lot of this of system stability and system productivity, more than than people I think, more than I had realized and more than I, in my training or in conversation that had heard up. And sort of the, the take home of that is, is it all growth mature open ecologically complex systems grassy or wooded or are inherently low in nitrogen. And not necessarily just low in nitrogen it's usually a combination of the ratio of nitrogen to carbon. So that we find when we start doing soil data we find this 12 to one carbon to nitrogen ratio and pretty much anything 12 to one or higher it's really sort of intact systems, less than 12 to one carbon and nitrogen ratio and soils, we start seeing pretty much degraded systems old fields ag fields yada yada. So that's it. I encourage people to start using sampling a lot, following the soil changes because these are these are emblematic of microbial dynamics that we, we otherwise don't have really a lot of access to that's that's still in science and in its infancy. One of the hardest things about monitoring is what do you do with the data and what do you do with the information you get and this is where I've bumped against a lot of walls over time is that we collect data thinking that this is a learning process not a verifying process we're collecting data we're monitoring things so that we can change if something isn't working out. We're not collecting data to verify how awesome we are and how perfect the world is. So when you find results that are contrary the hardest thing about monitoring is then affecting change back into conventional thoughts across the board and I know very few exceptions data are chronically ignored when they don't support conventional thought and systems. So, anytime you're doing any type of monitoring, I often recommend and we've done this with a few clients is do is have a have a like a contractual written agreement that there are fail safes and monitoring that if you hit these trigger points or these thresholds. The reevaluation of what's the management methods of techniques should be should be done and that way you're not that way you're going into it were scientifically saying we don't know that this is right we don't know that we're doing everything perfect. What happens if we aren't how do we how do we how do we how do we correct companies have this it's called research and development. We're not great at it in conservation and I'll end it there.