 Our next speaker is Nathan Lyons, who is a research professor at Tulane University. And Nathan has a broader interest in fluvial and tectonic geomorphology. He's a passionate modeler and as such involved and very active in the land lab project. And Nathan will today present life in landscape efflution models, investigations of climate and tectonics as drivers of biological efflution. So Nathan, if you're there, go ahead. Good, Albert. And so in my talk, I will be focusing on long term, long big time scale processes, climatic and tectonic forcings. That is not to say that these forcings don't have shorter time scale implications. The implications be, most importantly, the effect of climate and tectonics on biodiversity. And so central to this talk are landscape evolution models. And so at the core landscape evolution models, they begin with rock uplift, mass being uplifted, increasing the elevation of the ground surface. Superimposed on that is stream incision. And here you can see how effective stream incision is to remove all that material. Unfortunately, I don't have time to go through each of these parameters and talk about the details of them. I included them here in gray just to show at their most basic implementation, these processes are quite simple as they're implemented in landscape efflution. And that's just a stream power incision. That's a common simple formulation stream incision. And last, hill slope diffusion can see its effect on the landscape to round ridges, smooth hillsides. It is a sort of gravitational transport that moves hillslopes, moves a mass more so at the smaller scale compared to stream incision that seems more effective at greater scales. So it's really these three processes uplift stream incision, hill slope diffusion, that sort of kicked off the landscape evolution modeling that really got its stronghold in the 1990s. Since then, of course, there has been quite a bit of increases in the amount of processes, the complexities built into these processes. This is just a small sample. And I included these 10 or so because they also happen to be processes built into land lab. The land lab is a software as Greg introduced that can be used to model surface dynamics. One can a user, any of us can plug and play or mix and match processes to build a model to explore the research questions that we have. The new version, land lab two, now I can learn about it in the journal or surface dynamics. More pertinent to this talk is a new component I created called species evolver. And this component can be used to simulate biological evolutionary processes as they interact with the landscape and the land lab surface processes. And species evolver operates a geologic macro evolutionary time scales within landscapes. And so these tools in this line of research in general, aim to help us investigate biological evolution response to climatic and tectonic forcings and how we can use landscape evolution models. In this pursuit and hopefully we can learn not only about biological evolution but something about climate and tectonics as Brad discussed in the introduction. The feedback is what I think is really interesting and potentially what, for example, that the example he used was vegetation and slope stability and how biological history may impact sediment transport as well as erosion. So back to the block diagram and so in this block diagram we can see at the time as the landscape responds to the slip of a fault. You can perhaps imagine the landscape populated with simulated species and the response of the landscape to that fault may redistribute the species and affect the evolutionary processes. So I'd like to demonstrate these tools in action and two examples of first have to do with fish and stream rearrangement. And so this study is largely motivated by the global distribution of species richness. Richness is for other geologists in the room like myself not too long ago didn't know this term and so this just indicates the number of species in an area and here it's the number of species in a one degree grid cell. And what I see first is it seems like there's a high richness of freshwater species perhaps fish are concentrated in the tropics but that's not the only thing that's going on. It's not dark blue exactly in the tropics and light blue everywhere else. So there's other factors at play. So what I'm proposing here is that landscape evolution models can be used to explore these other processes and these other factors that might affect richness and biodiversity. So on the right side is an animated I will play an animation of species involved or implemented in a model created with land lab. Ever first look at the lower left towards a diagram of the model. And so there are a stream network straight into the north and to the south. Each color stream network is a distinct continuous stream network. And once the model starts there very soon after it starts there will be a vertical fault that uplifts the right side of the model grid about 40 meters higher than relative to the left side. Now explain the evolution dynamics as the models is going. And so with the gray scale you can see it gets really wide at the beginning indicating there's been that uplift of block in the stream rearrange and there's quite a few stream captures in the center center and top center. The stream capture would be here is one right about here. That happens at the beginning of the model run. It's a transfer of stream segment from one watershed to another. And because the species of simulated fish fish have been populated to this landscape, a population, a subpopulation of species are being transferred from one network to another. And so that means that a species has multiple populations and they become reproductively isolated over some time that could potentially lead to speciation as there is no gene flow anymore. Now that the stream capture has caused a fragmentation of the species range. So on the phylogenetic tree on the right can see how we began with a few number of species and giving the implemented evolutionary processes in the model that the biodiversity has increased by about 25% in this model run due to the rearrangement of streams. And so in that last animation I showed just one model run of one perturbation, the perturbation being the fault. This plot shows the results of several runs about 25,000 where each dot is one model run and the model runs the dots vary by the values of six parameters that are potentially critical to controlling species richness. So here you can definitely see despite the variability that there is some relationship between richness and the number of stream captures, but there is variability. And I can't hope to think of this paper by Antonelli at all of their work, this is empirical real data model data of empirical real data of climate and geologic variables and how they relate to species richness. And so you can see that there are trends globally. These are from data sets from mountains throughout the globe, but there's a great amount of variability. So I'm putting forth here that variability can be explored with landscape evolution models. And so with the modeling that I'm showing here, one additional control on richness appears to be the time to speciation that can be parameterized in the model. That's generally how quickly the simulated species evolve so that relationship between richness and stream capturing is steeper or more sensitive to when species evolve more rapidly than their slower evolving species. So on this first example to wrap this first example up to demonstrate that this process-based analysis of both the biology and geology side, that's just to really drill down into potentially global variability that we find elsewhere. And so another shorter example, before we're looking at landscapes in general and now looking at specific landscapes in Northern Andes and the more specific landscape or ecosystem type, the premise of the Northern Andes, their high elevation ecosystems above the forest line. You can see that they're exceptionally diverse in the Northern Andes where this research is being conducted and perhaps this diversity is one of the reasons that Humboldt was drawn to this reason a few years ago and where he recognized that vegetation zonates with elevation because air temperature decreases with elevation. And so some preliminary work research that is pivotal to this is work by Suzette Flanta that's mapped up the extent of primus over the last one million years and they were able to do that using pollen stored in a core extracted from a basin. And with that they were able to get several time slices of where these ecosystems were at given times over the last one million years. So Suzette and now I just have a preliminary model to show you today. Suzette and I created this model of just focusing on the eastern core Dillera of the Northern Andes and the plant species evolved by dispersal speciation and extinction processes built into species of all over the software. And the overall fitness said simply it's tuned to primal area said another way that extinction is exponentially more likely as area decreases. And so on the left side is that long rectangle of the eastern core Dillera. And this is the extent of the primal at about one million years ago and the number of taxa plant species. We begin with one just for simplicity in this presentation. And there's a lot of subplots here but we could just focus on this taxa richness subplot to see how richness changes over time. And you can see as the extent of primarous shrinks and grows there are several radiations of species and then there's that decay of extinction over time. And in the next slide we can talk about what's going on at least in the model. And so in that top plot we have climate peaks are hot. More interglacial these are more subglacial periods and then this is the model taxa richness. Let's focus just on this cluster of radiations about half a million years ago. And so it's really, so there's this the biggest glaciation during this timeframe was about 0.65 million years ago. And so as the primus is in a colder condition this is the mountain profile the primus is large and connected. And once the climate moves into an interglacial then the primus are broken up into a lot of smaller sub-premus. And that's similar to the captured fish stream example. This breaks up the populations into sub-populations that cuts off gene flow reproductively isolates them and increases richness. And so where this model is now and it's preliminary state I can't help but think of these two quotes that often brought together about the importance of evolution to understand biology and the importance of genetics to understand evolution. So I really think where this type of approach to modeling biological evolution really does need genetics implemented within it and what's genetics implemented in these models we can better represent the complexity and the realism of biological evolution as well as very importantly improve comparison between empirical model data. And lastly, envision that landscape evolution models can really support process-based research and biological evolution. So we can go beyond individual organisms go beyond variable correlations and start looking at the individual processes. And now that we have a landscape evolution model which I think has been missing a piece. Thank you all. Hope to take questions.