Rosemary Gillespie (biologist)

Transcription

PROFESSOR: So good morning. So next week your exam is at this time. And please look online to see where your, where the section is. It might not be the same section listed in the catalog. So make sure you check on the bCourses site or ask your GSI. So just to review this week. So I'll be here at this time today and Wednesday. And Dr. Shabel at this time on Friday. We're not broadcasting these. And then also right after this period if you want to stick around, I'm going to move to 2195. It's the, it's a lab down here at the end of the hall, 2195. I'll write that down here. And I'll be there 9:00 to 10:00 today and then also Wednesday. And then, oh, and Tuesday also. And then on Thursday from 2:00 to 4:00 in the same lab I'll have a review session as well. And all that's posted on the bCourses website. So we can do this however you like. But what I might suggest is that in these two periods how many people do we think will show up on Wednesday too? Okay. So what I was thinking is I'd spend about five minutes on each lecture and do half today and half on Wednesday morning, 8:00 to 9:00, does that sound okay? And then at the end of each one you can ask some questions about, about those terms for that, for that lecture. So let's get started here. Yeah? STUDENT: Can you turn the mike [inaudible] PROFESSOR: How's that? Can you hear me? Yeah? So is it okay if we watch these? Can you see that okay, or do you want to see the slides? What's the best? Because it takes me quite a bit of time to go through them. STUDENT: Professor? PROFESSOR: Yeah. STUDENT: [inaudible] PROFESSOR: Okay. STUDENT: Thank you. PROFESSOR: So is it on? Oh, dear. Okay. Can you, is that better? No? Speech volume, how's that? STUDENT: Yeah. PROFESSOR: Okay. Sorry about that. Okay, can you see these? All right, so the first lecture was about physical geography. And the important point here is that the, the environment's important and all of ecology in life is hierarchical. And we had these different kinds of hierarchies here. You know this is, this is not so great. So, let's see. Zoom to fit. Let's see. There we go. Excellent. Thanks. Okay. So the, thank you whoever said that. The important, sorry, the point here was biology is hierarchical. And we've talked in Bio 1A, if you've taken that, we had molecules and cells and so on, and organs, tissues. And then in ecology we think of again this hierarchy from individuals, communities, ecosystems, sometimes we think about a landscape scale and biosphere. So you need to know all of those and sort of how they go together. And we can think of this sort of structure for many different kinds of organisms, including, you know, things in your, your gut. We can think in your, in your stomach. We can think, or your intestines, we can think of that community as a set of interacting organisms too in the ecosystem which is the physical sort of environment of your, of your body. We talked about seasonality, climate and warning. So climate is sort of the longer term average. Seasonality is the fluctuations, of course, annually. And weather is what's happening here and now, the conditions that you see outside. I, I think I talked about microclimate which is the local conditions of the climate. It could be a small scale, like within a room, that could be a microclimate. Or at the botanical garden, when you walked into the redwood forest, that could be microclimate or the climate under a leaf or under shade. And we distinguished that from macroclimate. And I don't think I mentioned that in lecture. I had a couple questions. Macroclimate is landscape scale or continents or biomes. So it's a broader view of climate. Question? STUDENT: [inaudible] PROFESSOR: Oh, in this graph they have precipitation and temperature on the two axes. And the yellow just, if you use these particular sets of axes, where these lines cross, that means that there's not much water at that time of year. So this is for San Francisco, for example. You don't need to know this. But the blue line is the water. The red line is the temperature. And this just shows that there's a time of year when the temperature's pretty high compared to the precipitation. But this kind of depends on what the axes are and so I didn't mention that. But these kinds of graphs are important because they do show the temporal pattern annually of precipitation and temperature. And we talked about Mediterranean systems, for example. Okay. I think this is pretty self-explanatory. This one a lot of people asked about. So the sunlight hits the earth. It's hottest at the equator. And there are two reasons for this. One, it's directly overhead, so at the poles, the sun has to go through the, the atmosphere at an angle. And also at the poles, because of that angle, any, any part of light that hits the earth is actually spread out over a larger area. And for that reason there's more solar radiation at the equator. And the winds shown here are these big cycles of winds that actually leave the earth and go into the upper atmosphere and then come down. That's what these big arrows are. So at the equator the sun is hot. It heats up the air. The air goes up into the air. At the same time, it cools and can't hold as much moisture. So a lot of moisture drops at the tropics. And that's very important. And then the wind has to come down somewhere. And so it happens to come down at about 30 degrees north and south latitude. It's quite dry air when it comes back down to earth. And so that's why many of the desert regions are 30 degrees north and south latitude. And then because the earth is spinning and because of the differences in size at these different latitudes of the earth, that creates these large patterns of wind movement along the earth. And so these trade winds, for example, coming from the north curl in that direction because actually the, the earth is bigger a little bit farther down towards the equator than at the top. And so the winds appear to be slowing down compared to the speed of the earth and in moving in the other direction at the top. And because of these cycles of winds, that creates in the water these cycles of water. And so there are these gyres, these big sort of cycles of water in the Pacific north and south, in the Atlantic north and south, in the Indian Ocean that are set up to spin in a certain direction because of the winds that are above them. And I asked you to learn three currents: The California current which is this cold one which we come back to because of upwelling; the Gulf Stream which is in the northeast U.S., a warm current; and this Arctic circumpolar current that's moving all the way around the bottom of the ocean just above Antarctica. And one of the things we've seen which relates to carbon dioxide seasonally and the amount of photosynthesis is that there's a lot more land mass in the Northern Hemisphere than the Southern Hemisphere. And in fact, it's possible to have a current move all the way around the earth in the south. Topography matters. We talked about a rain shadow which is as the clouds that have a lot of moisture move uphill, they cool again. They drop moisture. And we can see that right here in the Bay Area. We see this side of the mountains just here up the hill as wet. And you go over the hill into Walnut Creek, it's a lot drier. And we call that a rain shadow on the other side, which is a place that the rain doesn't, doesn't fall. So topography is also important for where the precipitation happens and, and water flow as well. Okay. And then this whole example about the work that I do with Rosemary Gillespie has to do with the fact that because we know something about the patterns of the winds and because we know something about the patterns of the water flow, we can make predictions as to what the biota should look like on these remote islands or anywhere on earth for that matter. And if these organisms moved around the earth because of dispersal, we should expect them to resemble the places where they came from. So we can use these patterns of winds and water to make predictions about where things on earth should look similar or where different kinds of organisms should be on earth. So that's a hypothesis based on dispersal. And I contrasted that to a hypothesis based on vicariance in the second lecture. And that's important. Those two things are, are quite important. That was the whole point of that one, so any words here that are difficult? Let's see. Oh, I do expect you to know the names for the, at least the people that I, I put on these sheets. So Haeckel. It was his idea, this word ecology. Homeostasis is just the idea that organisms respond to their habitat in a, a sense that's not necessarily evolutionary, so we can have homeostasis because of responses in physiology or behavior or even sometimes morphology seasonally. And all those responses can be to better equip an organism to deal with a certain environment but don't have to be, they don't have to be evolutionary. Yeah. STUDENT: [inaudible] PROFESSOR: The landscape and biome. So landscape is one of those classes or those categories of biological organization that came between ecosystem and the whole biosphere. And a biome is a, so that could, landscape could be anywhere. But a biome is a particular set of organisms that's found in a particular place. And there was this set of biomes that I expected to know which we'll come to for both terrestrial and aquatic systems. Okay. Great. So where was my thing here? So we started talking about biomes which is how life is organized on earth. And there's some commonalities that we see across continents having to do with the weather and the climate. And one of these we see, or an example are the Mediterranean climates that we're experiencing here. And we see the same thing in other places on earth. And I think it's important to know what that is. And also you should know why that graph on the upper right there is inverse or, or shows a different pattern, the inverse pattern. And, of course, that's because it's a map of South Africa which has their winter when we have summer and so on. So biomes, the general idea is from von Humboldt who came up with this classification system of different kinds of environments and the organisms that were found there. And we think of terrestrial biomes typically defined by vegetation and the latitude, where they are on earth. And I'm go -- it's quite likely that I would give you a graph like this with some circles here and I'll say, well which one is the desert without labeling it or which one is the tropical rainforest? And the important thing here is that these terrestrial biomes sort themselves out based on precipitation and also temperature. So tundra, for example, in the northern parts of the earth, tundra is a place where there's very little precipitation and it's always quite cold. A tropical rainforest, for example, is always wet and, and always very warm. So for these I think it would be reasonable to expect you to at least be able to distinguish the different biomes that I listed at the end of the, of the lecture. And different authors and different ecologists identify slightly different biomes and so I gave you a list that I thought was quite important. And you can see some of the biomes here on the earth. So then we talked a little bit about those. The aquatic biomes are identified mostly by the physical environment. And we have saltwater ones which is the ocean. Of course, that's the most water on earth. We also have freshwater ones, lakes and rivers. In the oceans there's some other kinds of environments, including intertidal areas, estuaries, coral reefs, and this steep abyssal zone which we'll come to in a minute. We talked a little bit about freshwater systems and how seasons can affect life in lakes, especially in the temperate areas. And what happens here is that because water is actually most dense at 4 degrees, that means that when it's frozen, the ice floats on top of the water. And this is one of the important things about why we have life on earth because when it freezes, life can still happen or, or survive at the bottom of freshwater lakes and rivers. And in the summertime, well, that's the wintertime, you have ice at the top, warmer but still cold water at the bottom. In the summertime the warm water's at the top, and in the fall and the spring we get this seasonal turnover. And this is a physical turnover of the water. And that also mixes the whole freshwater ecosystem. So this is a different kind of turnover than when we talked about species composition turnover with secession which we'll come to in a little bit. Okay, continental drift. I don't expect you to remember much about continental drift except that researchers now know a lot about continental drift. And they know roughly when these different continents split apart and came back together. And some of these plates are moving now and they're very important. The big earthquake that was just in Nepal, for example, had to do with this, I forgot which plate that is. The Indian plate smashing into the plate that represents Asia and all the uplifting that happens there. With plates coming together organisms also can come together. And we call that biotic exchange, like when North and South America came together. And there are also places where plates are splitting apart. And organisms are stuck on those plates and move around the earth on those plates. And that's this process of vicariance. And one example are organisms that have their relatives on the southern continents that were all formed together. And I gave you some examples of how we understand that. Oh, this, this was just the idea that we can have these big barriers also in the ocean. Sometimes we think of the ocean as a big bathtub with water just moving around but in fact there are a lot more barriers than, than typically you might expect. So this was just an example of a bunch of organisms that are found in the southern continents. And it was historically thought of as an example of where their current distribution reflected the fact that they were on these continents for a very long time. And we can use what we know about the geology of these continents and when they broke apart to test that hypothesis. And it turns out that for a lot of the organisms, the dates at which, or at least molecular data shows us that they split apart. It matches when we think the geology split apart. But for some of them like between a industrial I can't and New Zealand, which actually split apart a whole long time ago, one of the earliest splits was Australia and New Zealand. The dates show us that these taxa are much more closely related than you'd expect from the date when the continent split apart. So probably there was some dispersal from Australia and New Zealand. And that makes sense. They're not that far away. So the example isn't that important except that we can use what we know about the history of the earth to make predictions again about where organisms should be in their relationships. And that's a very different kind of hypothesis from dispersal. Okay, and humans do a lot to the earth of course as well. All right. So anything here that's difficult? So these are the, the biomes that I expected you to know. So for each of these, you don't need to know in great detail but if I were to give you a set of characteristics of the desert or of temperate grassland, and I gave you a set of choices of biomes, you know, you should know which is which. Also roughly where they are found on earth. And if I gave you one of those graphs of temperature and precipitation, and different blobs, you should know where those, which is, which is which. At least for the most obvious ones. There were also a bunch of zones in the, in the aquatic systems. So remember that the terrestrial ecosystem, terrestrial biomes are defined by vegetation and latitude. And in aquatic systems they're defined by physical conditions, especially light and whether it's saltwater and freshwater. All right. Yep? STUDENT: [inaudible] PROFESSOR: Yeah, people would, would think of, she said are the different zones in the ocean different biomes? People would think of those as different biomes. So, for example, the pelagic zone, what's happening in the open ocean with all those phytoplankton out there, that's a different biome than the intertidal zone, for example. Or the benthic zone which is the bottom. Okay? Question? STUDENT: [inaudible] PROFESSOR: An ecotone is just where two different kinds of ecological communities come in contact with each other or are close to each other. So an example of an ecotone in here is where you might have redwood trees and then chaparral right next to them. And so you have a very different kind of ecological community. Anything else here? Okay. Lecture three started our set of lectures on populations -- is this useful? Is this, are we good? Yeah -- started our, our set of lectures on population biology. We introduced a few words that helped us describe populations. One of those is range. What is the geographical extent of organisms? And here's a desert pupfish and a whale that have sort of the examples of sort of the extremes of range. We talked about what is population size. And it can be either the whole population or it could be the density, that is numbers per unit area. And we talked about ways that you might monitor population size. You can tag animals. You can mark them in different ways. You can follow them over time. And we talked about an approach called mark and recapture where you go out and mark some individuals. You assume that they mix randomly. And then you go back and you take a second sample. And based on the ratios of those that you captured first and those that you went back and captured next that were marked, you can figure out what the population size is. And we talked about different assumptions that go into that, that estimation. We talked about biological dispersion. And this is dispersion, not dispersal, which is the act of moving to different places. So dispersion is how organisms are distributed in space. And there are three sort of general categories: Uniform or regular, random, and clumped. Random is just what it sounds like, random. The nearest, the distance between any two individuals is essentially a random distribution. Uniform or regular, if you looked at any two individuals and looked at its nearest neighbor, that distance to the nearest neighbor would be pretty much the same for all the individuals you looked at. And then for clumped distribution, if you looked at nearest neighbors, you and your neighbor would be very, very close. And much closer than you might expect just by chance. So those are three different kinds of distributions. And we gave some examples of those in nature. Any questions about that? So this is certainly something you have to think about when you're, if you wanted to sample a population and figure out how many individuals there, there are. We talked about patches and scale. You can have habitat patches or islands if you will at, at almost any scale, you know from big island in the Pacific to little puddles. And it depends sort of on the organism and how it disperses, how important those patches are. I gave you one example of patches in the Bay Area for this butterfly that, that seems to live on serpentine habitats. And we called this a metapopulation because you have different populations that come and go in space and time. Question? STUDENT: [inaudible] PROFESSOR: Yeah, his, well scale, his question is, well, is scale important here? And it is. Depending on, on how, how closely you're focused, if you took this clumped distribution and you looked right at that clump it might be random for that clump. But if you zoom out, it, it looks clumped. So certainly scale is important in, in these kinds of things. Just as it is in sampling. Okay. We talked about human population size. And this was quite confusing and I got a lot of emails about this. And this is an important question that you need to be able to deal with. Why is the growth rate declining and the population size is still zooming upward? So growth rate in percent is the, the increase every year in numbers of people as a percent. And since the 1960s, this growth rate if you will, a little r, has actually slowed down. But it's still greater than zero which means that the population still growing. And if you multiply this number times the population size each year, it's still something that looks like exponential growth. So even though the growth rate is slowing, because you're multiplying this number even though it's slightly smaller every year, by the population size now, the population still expanding at a great rate. And demographers don't really agree on what the population of earth will be, but there are many, many projections for what that might be. Okay. We talked about this ED model, which is numbers of individuals equals the numbers of births minus the numbers of deaths. And you can look at this either just from one generation to the next or one season to the next. But you can also look at it as a rate that is the rate at which numbers increase or decrease per unit time. And that's typically shown like DNDT or numbers of individuals over change in time. And the idea is that you're multiplying this, this growth rate times the numbers of individuals in the population. And that's essentially an exponential growth rate. So in this case the per capita rate of increase, little r, equals the birth rate minus the death rate. Make sense? So there are two ways to look at populations, either the numbers of individuals from one time to the next or the changes in rates of births and deaths. Question? STUDENT: [inaudible] PROFESSOR: Oh, okay. Yeah, I was, I was a bit sloppy. So this is the change in numbers over time. And the little r is the, is the, the constant that tells you how fast that's happening. So little, yeah, so I, I should be careful about, so little r is the per capita rate of increase, so the little r is the rate of increase for every individual. And then we multiply that by the number of individuals. And that's the total population increase or decrease over time. Thanks. STUDENT: [inaudible] PROFESSOR: Yeah. STUDENT: [inaudible] PROFESSOR: What's the what? STUDENT: [inaudible] PROFESSOR: Oh, the intrinsic rate or innate rate and your book talks about this, sometimes we like to think about what's the rate, the per capita rate of increase, what could it be if the conditions were optimal? So what's the most that it could be? And then you'll see that show up in some equations later. So that's the, the, sometimes books will call it the r max. What's the maximum that this per capita rate of increase could be? And then we're going to use that in our models and then we're going to take away individuals or add individuals based on other factors. Your book talks about that if you need to know more about that. This was just interesting because the earth varies, of course, in density of individuals but also birth rates and, and death rates for some reasons that you know a lot about, having to do with economies and opportunities and different kinds of cultures. We talked about population pyramids which can be used to predict something about the future size of the population from those that are expanding rapidly with a lot of individuals and the younger generations. So this is males and females and age here. Typically they show a bar for the, you know, the age at which females are likely to start having babies. And then, and age at which retirement happens. And if there are a lot of individuals at the younger populations, we expect that this will be a population that is expanding because these younger people will have babies in the future and a lot of them. And then populations where there are fewer individuals in the younger generations, when they grow up, they will not have as many children as the older generations. And then we looked at some of these age structures for different communities around the world. And there's some interesting things that you can track changes in generations and what happens in one generation. Like baby booms can be seen in the next generation. And we can see that in the U.S. and our baby booms, and then the, the boomlet which is the children of the baby boomers. And you can also see that we can make predictions about the future which in this, in our country anyway, there are going to be a lot of people who are over, this is age 80, there will be a lot of people over age 80. And in fact our current system can't pay for them. So your generation, there's not enough of you to actually pay for the retirement of all those people. And so we'll have to think about this. But what these graphs show is that we can use information about demography to make these kinds of predictions. And China also is very interesting. They had a one-child policy. And you can see the impact of that in that generation but also subsequent generations as well. An example of sea otters in California. So let's see. Anything here? So for this mark and recapture equation, it's likely I would give you that equation and then ask you to solve a problem. So you'd have to know sort of how to do that and what those terms are. But you could figure that out if you had to. Just think, well, there's some number out there that I need to know that's N. Some of those I'm going to mark and put back into the population. I'm going to sample some number of those later. And some of those will be marked. We good? We talked about life cycles and life tables, so a life cycle is just the schedule of, of events in an organism's life. And I used the a tick example because it's not just one year, it's two. And it's relevant. Here we have ticks. We also have Lyme disease. And I, it was just an interesting example. But a life table is how we organize births and deaths with age for an organism. And so this is a tool that let us make statements about again population growth. And it also let us look at things like environmental factors. And I gave you this example of the Galapagos finches where in 1983 there you can see it was a really good year. Lots of rain. And there are a lot of individuals here that were born. And then the red bar there was a year where it was a drought. And you know the conditions were bad. There wasn't much food and fewer individuals were born. So just an example of a life table that's different from a life cycle which is just a description of activities through a life. We can do these same things for human populations. We sort of identified two different methods. One is a cohort method where you look at a cohort like all the students at Berkeley from freshman, sophomore, junior, senior, super-senior, super-super-senior and so on. That's sort of the cohort method of tracking individuals through time. And there's also a method of making these life tables where you just sample a population and you know some of you would be freshman, some sophomores, some juniors, for example. And we can assume that what happened over your different periods at those different stages was the same. And we can make a life table that way too. So the cross-sectional idea is just look at a population at one period and collect that kind of data. Survivorship curves vary among species. And we identify three different types of these. You don't need to memorize which is one, two, or three, but just to realize that some organisms like us and elephants, we all live a long time mostly. And then typically die around the same time. Some organisms, there's a constant rate of death through the population. And then some organisms, most individuals don't live very long but some individuals live a long time. Okay. So the point of this slide was, we had talked about homeostasis before. But depending on the conditions in the environment, organisms respond, and that response you saw with the, the fecundity of the birds in the Galapagos, so when conditions are really good, for example, the organism can devote more energy for reproduction or growth. And when conditions are, are bad, they have to use a lot of their energy just to survive. And there isn't as much energy for reproduction. So that's sort of the basis for why we see these differences having to do with the environment. We talked about exponential growth. And here's your little r again. For little r of one and a little r of .5, these are both exponential curves if that there's some constant that's multiplied by the number of, of individuals, but they're different shapes because that little r is different. So in the human population, for example, with our little r that's decreasing, our curves are still looking exponential but they just have a, a more gradual increase. Malthus, this is one of the people I asked you to remember. He had this idea that we're not actually keeping up with the numbers of people with our agricultural system which he thought was increasing more in an arithmetic way, a straight line. Whereas exponential growth is multiplicative kind of pattern. And Darwin based a lot of his thinking about natural selection on Malthus's ideas. Of course, Darwin was interested in you know why don't all organisms survive and reproduce and what are the impacts of that? And some examples here for California. And we talked about the logistic growth which is a very simple way to control numbers in an equation. And there are many kinds of equations like this. And some are quite complicated but the logistic equation is just a simple one. And what's happening in the logistic equation is we had our exponential growth which is the left-hand side, and then we're adding a very simple equation having to do with carrying capacity, K. And you can see when N is close to K, then K minus N will be zero or close to zero. And the growth rate will be zero. So that's the case where N, the population size is actually at carrying capacity. If N is very small, then K minus N will be close to K. And so that part of the equation is one. And then at the very small n, then you have growth rate that is mostly exponential. So again, you don't have to produce that equation. But if I gave it to you, you could put in some numbers or make some statements about it. Go ahead. STUDENT: [inaudible] PROFESSOR: So the growth rate is, is decreasing. I showed you a graph of that. The per capita rate of increase is decreasing. Though the little r in these equations, in fact, this is a good one. Here the little r, in the blue line it's one. In the red line it's .5. But for both of these you would call that an exponential growth. It's just not quite the same curve. So what's happening is our human population, we're just taking a little longer to reach the, these immense population sizes. Okay? Okay. So how well does this do? In some cases it works really well. Sometimes we have populations that grow really quickly, use up their resources, and then fall below this carrying capacity and, and recover. Because of this, of these two extremes, in one case exponential growth and in one case populations that reach carrying capacity and stay at carrying capacity for a long time, when we think of how organisms adapt and are able to cope with those two conditions, it's useful to distinguish between these two different kinds of life histories. So a life history is just a pattern of births and deaths through life. And some people think of it as a, a strategy or a tradeoff. You can invest either in a lot of offspring all at once, or you can invest in very few offspring but take care of them. And so these are these two strategies that are selected organisms, those that put out a lot of offspring but don't take care of them and those that have fewer offspring, they take a longer time to develop, and typically parental care. So an example would be us and elephants. All right. And there are a bunch of other characteristics that go along with that. So two words here. Semelparity is this idea that you're putting all your offspring out at once. Iteroparity is that you have different bouts of reproduction through your lifetime, like humans or elephants. Grasses and dandelions would be putting all their seeds out at once. Otherwise I think we talked about that. Density-dependent is the idea that you have some rate, birth rate or death rate that is changing in association with density. Density-independent is where those rates are not impacted by, by density. Yeah. STUDENT: So [inaudible] PROFESSOR: So, sorry, let's see, reproductive table, that would just be the schedule of reproduction. And I probably shouldn't have put that in there. So a life table would include both the reproduction and the survivorship. We're good? Yeah? STUDENT: [inaudible] PROFESSOR: The allee effect, the allee effect is just that at some very low densities the birth rate might be lower than you might expect because of the difficulty that organisms have in things like finding mates or creating conditions under which sort of optimal reproduction happens. And typically these are social animals. For example, if you have a lone wolf and there's one that you've heard about in the news that's roaming Northern California and Washington. If there's just one wolf out there, it's going to have a very low rate of birth because it can't find mates, so, so you need a certain number of individuals. So that's the sort of a non-linear effect at very low population sizes in reproductive rates. Okay. Do you want to do one more or do you want to quit? One more? All right. So this one was mostly some, some examples of how we're using that information. We talked again here about density-dependent and density-independent processes. Here's your allee effect. And just like the Equilibrium Theory of Island Biogeography, we typically think of, of little r or this rate of, of increase as being combination of birth rate and death rate. And where the birth rate and death rates sort of cross, where those lines cross is typically an equilibrium density. And your book has these diagrams and I think explains it quite well. We talked about different things that we can do to manage populations. We can control birth rates and death rates to manage populations for conservation, for example, by creating a corridors for animals to move about or breaking up places where we've disrupted their movement. We've talked about populations being connected and how dispersal causes or, or provides a means for individuals to move from different populations to others. I like these. Let's see. Oh, this one, I just threw this in because here we're controlling the physical conditions, in this case pH, to produce, to produce food which is I thought was quite interesting. So it doesn't have to be conservation. It doesn't have to be big mammals. You know, we're controlling population numbers here in a lot of things that we do, both for food but also health and medicine as well. Back to the human population again, again, this sort of gets at why is birth, why is the per capita growth rate of humans declining? And there are many things over the history of humans that would actually suggest that our birth rate should be increasing. For example, we dealt with better efficiency in food through the green revolution. We have industrial practices that provide more goods for us and so on. There are also places and you can see there in the history of human population where we've suffered because of diseases and so on. And so the growth rates here of the human population certainly have fluctuated. And one question is, you know, are we changing our carrying capacity or not in the human population? Are we, is that carrying capacity changing or are we changing something about the births and deaths? And there's no simple answer to that. But I think it's just something to think about. And we don't really know where the human population is going. But we do know that births and deaths and all the associated energy and everything else is not distributed evenly on earth. And that's something to think about as well. Okay. We spent some time on flu and other kinds of human diseases. And we'll come back to this. But the idea is that we can't typically model these in the same way that we modeled births and deaths of organisms that typically eat each other and die. And flu is interesting just because it's a, it's a disease that again we can control based on how people move around, but we also can, whoops, I didn't show it here. We can also create vaccines that target different kinds of flus and understanding where these different flus come from. Our common flu originates from a combination of different flus from ducks and pigs that have now come together and evolves and changes every year. So we can, the point of this whole lecture was really, we can manipulate populations, birth processes and death processes if we know something about their, their biology. And we can do this for all different kinds of means, including conservation, food, health, agriculture. Okay, so here's a bunch of different applications. Okay. So that's, that's lecture five. So next, this next hour I'm just going to answer questions down the hall, if you like that. And then on Wednesday, we'll finish up with the rest of lectures, sort of a review of this ... (cutoff).