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Population size

From Wikipedia, the free encyclopedia

In population genetics and population ecology, population size (usually denoted N) is a countable quantity representing the number of individual organisms in a population. Population size is directly associated with amount of genetic drift, and is the underlying cause of effects like population bottlenecks and the founder effect.[1] Genetic drift is the major source of decrease of genetic diversity within populations which drives fixation and can potentially lead to speciation events.[1]

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  • Population Ecology: The Texas Mosquito Mystery - Crash Course Ecology #2
  • Human Population Size
  • Population growth and population size

Transcription

In our series on Biology, we spent many weeks together talking about the physiology of animals and plants. And how cells work together to make tissues, to make organs, to make organ systems, to make us the hunks of meat and vegetables that we are. In understanding the whole organism, it's important to know what's going on at all those levels. And the same is true for Ecology, only instead of zooming in and out on different levels within a living thing, we can zoom in and out on the earth. Depending on the power of the magnification, we can understand a whole range of things about our planet. For instance, we can look at groups within a species and how they live together in one geographic area. That's Population Ecology. There's also Community Ecology, where you look at groups of different organisms living together and figure out how they influence each other. And then, the most zoomed-out we get is Ecosystem Ecology, the study of how all living and nonliving things interact within an entire ecosystem. So let's start by zooming in, with Population Ecology. The study of groups within a species that interact mostly with each other, to understand why those populations are different in one time and place than they are in another. How, you may be asking yourself, is that in any way useful to anyone ever? Well, it's actually super useful to everybody, always! Let's look, for instance, at the outbreak of West Nile virus that struck Dallas, Texas in the summer of 2012. In Dallas County, 12 people died from the virus as of the filming of this and nearly 300 people had been infected. But in 2011, the whole state of Texas reported only 27 cases of West Nile, and only 2 deaths. That seems kind of significant. So, what's up? It turns out that this is a population ecology problem. West Nile is a mosquito-borne illness, and the population of mosquitoes in Dallas in 2012 busted through brick walls like the Kool-aid man, spreading West Nile like crazy. So why did this outbreak happen in 2012 and not the year before? And why did it happen in Texas and not in New Jersey? The answer is population ecology! Before we start solving any disease outbreak mysteries, we gotta understand the fundamental principles of population ecology. For starters, a population is just a group of individuals of one species who interact regularly. How often organisms interact has a lot to do with geography: You're gonna have a lot more face time with folks you live near than those who live farther away. As a result, individuals who are closer to you will be the ones you'll compete with for food, and living space, mates, all that stuff. But in order to understand why populations are different from time to time, and place to place, a population ecologist needs to know a few things about a population, like its density. In this instance, how many mosquitoes there are in the greater Dallas area that might come into contact with each other. A population's density changes due to a number of factors, all of which are pretty intuitive: It increases when new individuals are either are born or immigrate, that is, move in, and it decreases because of deaths or emigration, or individuals moving out. Simple enough. But as a population ecologist, you also need to know about the geographic arrangement of the individuals within the population. This is their dispersion. Like, are the mosquitos all clumped together? Are they evenly spaced across the county? Is there some kind of random spacing? The answer to these questions give scientists a snapshot of a population at a given moment. And to figure out a puzzle like the West Nile outbreak, which involves studying how a population has changed over time, you have to investigate one of population ecology's central principles: population growth. There are all kinds of factors that drive population growth, and they can vary radically from one organism to the next. Things like fecundity, how many offspring an individual can have in a lifetime, make a huge difference in the size of a population. So, for instance, why do mosquito populations seem to grow so quickly, while the endangered black rhino may never recover from a single act of poaching? For starters, mosquitoes can have 2,000 offspring in their two-week lifetime, while the rhino can have, like, 5 in 40 years. Still, a population doesn't usually or even ever grow to its full potential, and it can't keep growing indefinitely. To understand how how fast or slow, and high or low, a population actually grows, you need to focus on what's keeping growth in check. These factors are, appropriately, called limiting factors. Say you're a mosquito in Dallas in 2011, the year before the outbreak. Back then, the growth rate wasn't what it was in 2012. So, something was keepin' ya down. To figure out what your limiting factors were, you have to first narrow down what you need as a mosquito, to live and reproduce successfully. First you've got to find your food. Now, you mosquitos, you eat all kinds of things, but in order to reproduce, assuming you're a female, you need a blood meal. So you have to find a vertebrate and suck some of its blood out. Presumably there's no shortage of vertebrates walking around Dallas for you to suck blood out of. I have good friends who are vertebrates in Dallas. You might even be able to suck some of their blood. Next, temperature: Because you mosquitoes are ectothermic, it has to be warm in order for you to be active. And Texas is plenty warm, and the winter of 2011 and 2012 was especially balmy. In fact, the summer of 2012 was exceptionally hot, which helps speed up the mosquito life cycle. So, that's one limiting factor that's been removed for Dallas area mosquitoes. Moving on to mates: If you're a female mosquito you need to find a nice male mosquito with a job, and preferably his own car, because you know Dallas is a pretty big city, to mate with. This isn't actually all that hard because of the way that mosquitoes do it, males just gather into a mosquito cloud at dusk every night during mating season, and all a female has to do is find her local dude-cloud and fly into it in order to get mated with. Easy cheese! Finally, space: And, ah-ha! Because here we have another important clue. Mosquitoes need to lay their eggs in stagnant water. And if there's anything mosquito larvae hate, it's a rainstorm flushing out the little puddle of water they've been living in. And since Dallas saw a pretty severe drought in the summer of 2012, there were lots of pockets of stagnant nasty mosquito water sitting around, acting as nurseries for many, many, West Nile-infected mosquitoes. So, when we look at this evidence, we find at least two limiting factors for Dallas' mosquito population growth that were removed in 2011: the constraints of temperature and space. It was plenty hot and there were lots of egg-laying locations, so the bugs were free to go nuts. Population ecologists group limiting factors like these into two different categories: density- dependent and density-independent. They do it this way because we need to know whether a population's growth rate is being controlled by how many individuals are in it, or whether it's being controlled by something else. And the reason these limitations matter is because they affect what's known as the carrying capacity of the mosquitos' habitat: That's the number of individuals that a habitat can sustain with the resources that it has available. So, density-dependent limitations are factors that inhibit growth because of the environmental stress caused by a population's size. For example, there may simply not be enough food, water, and space to accommodate everyone. Or maybe because there are so many individuals, a nearby predator population explodes, which helps keep the population in check. Things like disease can also be a density-dependent limitation. Lots of individuals living in close quarters can make infections spread like crazy. Now I don't think that the Dallas mosquitoes are going to run out of vertebrates to dine on anytime soon. But, let's say hypothetically that the explosion of local mosquito populations caused a similar explosion in the number of Mexican free-tailed bats, the official flying mammal of the state of Texas. And they eat mosquitoes. That would be a limiting factor that was density-dependent. More mosquitoes leads to more bats, which leads to fewer mosquitos. It's pretty simple. When density-dependent limitations start to kick in and start to limit a population's growth, that means that the habitat's carrying capacity has been reached. But the other type of limiting factor, the density independent ones, have nothing to do with how many individuals there are or how dense the population is. A lot of times these limitations are described in terms of some catastrophe: a volcanic eruption, a monsoon, a Chernobyl. In any case, some crucial aspect of the population's lifestyle changes enough that it makes it harder to get by. But these factors don't have to be super dramatic. Going back to mosquitoes: Say, in 2013, there's a huge thunderstorm, a real gully-washer, in Dallas every day for three months. That's going to disturb the clutches of mosquito eggs hanging out in the stagnant water, so the number born that year would be substantially smaller. By the same token, if the temperature swung the other way and it was unseasonably cold all summer, the bugs' growth rate would drop. Now, the truth is, there are a billion and a half situations, both big and small, that could lead to a population either reaching its carrying capacity or collapsing because of external factors. It's a population ecologist's job to figure out what those factors are. And that is what math is for! Our friend math says that any population of anything... anything, will grow exponentially unless there's some reason that it can't. Exponential growth means that the population grows at a rate proportional to the size of the population. So here at the beginning of 2012, we might only have had 1,000 mosquitoes in Dallas, but then after, say, one month, we got 3,000. Now, with 3 times as many reproducing mosquitoes, the population grew three times as fast as when there were 1,000. So then there are 9,000, at which point, it's growing three times as fast as when there were 3,000. And on and on into infinity. And in this scenario, the mosquitos are all, "CARRYING CAPACITY MY CHITIN-COVERED BUTT! THERE'S NO STOPPING US!" But you know that doesn't really happen. I mean, it can happen for a while, humans have been on an exponential growth curve since the industrial revolution, for example. But eventually, something always knocks the population size back down. That thing might be a density- dependent factor like food scarcity or an epidemic, or a density-independent one, like an asteroid that takes out the whole continent. Regardless, this exponential growth curve can't go up forever. And when those factors come into play, a population experiences only logistic growth. This just means that the population is limited to the carrying capacity of its habitat, which, when you think about it, ain't too much to ask. See how this graph flattens up at the top? The factor that creates that plateau is almost always a density-dependent limitation. As you add mosquitoes, eventually the rate of population growth is going to slow down because they run out of food or space, and when we get to where the number levels off, that number is the carrying capacity of the mosquito population in that particular habitat. Now, let's apply all of these ideas using a simple equation that will allow us to calculate the population growth of anything we feel like. I know it's math but, wake up because this is important! The city of Dallas is depending on you! Let's calculate the growth of Dallas' mosquito population over a span of two weeks. All we have to do to get the rate of growth, that's R, is take the number of births... births, minus the number of deaths and then divide that all by the initial population size. Which we generally just call N. So, let's say we start with an initial population of 100 mosquitoes, and each of those mosquitoes lives an average of 2 weeks. So our deaths, over a span of two weeks, will be 100. Half of these mosquitoes are going to be female, so 50 of them. And they can produce about 2,000 babies in their lifetime, so that's times 2,000. [Yeesh!] So 50 mommy mosquitos times 2,000 babies per mommy and you get births equaling 100,000 little baby mosquitos. Once we plug in all the numbers into this equation, even though this is totally a hypothetical, we will see the true scope of Dallas' mosquito problem. So, blink! In two weeks, the population had 100,000 babies and only 100 of them died. So this is a population growth rate, if you do the math, of 999. This means that for every mosquito out there at the beginning of two weeks, there will be 999 more at the end of two weeks. That is a 99,800% increase... by Thor's Hammer! Again, these are hypothetical numbers, but it gives you a sense of how a population can just go out of control when all the factors that we talk about go in its favor. And you guys haven't even seen trouble until you see what the graph of human population looks like over the last couple of millennia. But to find out more about that, you're going to have to join us next week. Until then, thank you for watching this episode of Crash Course Ecology. And thanks to everyone who helped put it together. The table of contents is over there if you want to go re-watch anything and if you have any questions for us, we're on Facebook and Twitter and of course, in the comments below. See you next time.

Genetic drift

Of the five conditions required to maintain Hardy-Weinberg Equilibrium, infinite population size will always be violated; this means that some degree of genetic drift is always occurring.[1] Smaller population size leads to increased genetic drift, it has been hypothesized that this gives these groups an evolutionary advantage for acquisition of genome complexity.[2] An alternate hypothesis posits that while genetic drift plays a larger role in small populations developing complexity, selection is the mechanism by which large populations develop complexity.[3]

Population bottlenecks and founder effect

Population bottlenecks occur when population size reduces for a short period of time, decreasing the genetic diversity in the population.

The founder effect occurs when few individuals from a larger population establish a new population and also decreases the genetic diversity, and was originally outlined by Ernst Mayr.[4] The founder effect is a unique case of genetic drift, as the smaller founding population has decreased genetic diversity that will move alleles within the population more rapidly towards fixation.

Modeling genetic drift

Genetic drift is typically modeled in lab environments using bacterial populations or digital simulation. In digital organisms, a generated population undergoes evolution based on varying parameters, including differential fitness, variation, and heredity set for individual organisms.[3]

Rozen et al. use separate bacterial strains on two different mediums, one with simple nutrient components and one with nutrients noted to help populations of bacteria evolve more heterogeneity.[2] A digital simulation based on the bacterial experiment design was also used, with assorted assignations of fitness and effective population sizes comparable to those of the bacteria used based on both small and large population designations[2] Within both simple and complex environments, smaller populations demonstrated greater population variation than larger populations, which showed no significant fitness diversity.[2] Smaller populations had increased fitness and adapted more rapidly in the complex environment, while large populations adapted faster than small populations in the simple environment.[2] These data demonstrate that the consequences of increased variation within small populations is dependent on the environment: more challenging or complex environments allow variance present within small populations to confer greater advantage.[2] Analysis demonstrates that smaller populations have more significant levels of fitness from heterogeneity within the group regardless of the complexity of the environment; adaptive responses are increased in more complex environments.[2] Adaptations in asexual populations are also not limited by mutations, as genetic variation within these populations can drive adaptation.[5] Although small populations tend to face more challenges because of limited access to widespread beneficial mutation adaptation within these populations is less predictable and allows populations to be more plastic in their environmental responses.[2] Fitness increase over time in small asexual populations is known to be strongly positively correlated with population size and mutation rate, and fixation probability of a beneficial mutation is inversely related to population size and mutation rate.[6]

LaBar and Adami use digital haploid organisms to assess differing strategies for accumulating genomic complexity. This study demonstrated that both drift and selection are effective in small and large populations, respectively, but that this success is dependent on several factors.[3] Data from the observation of insertion mutations in this digital system demonstrate that small populations evolve larger genome sizes from fixation of deleterious mutations and large populations evolve larger genome sizes from fixation of beneficial mutations.[3]  Small populations were noted to have an advantage in attaining full genomic complexity due to drift-driven phenotypic complexity.[3] When deletion mutations were simulated, only the largest populations had any significant fitness advantage.[3] These simulations demonstrate that smaller populations fix deleterious mutations by increased genetic drift.[3] This advantage is likely limited by high rates of extinction.[3] Larger populations evolve complexity through mutations that increase expression of particular genes; removal of deleterious alleles does not limit developing more complex genomes in the larger groups and a large number of insertion mutations that resulted in beneficial or non-functional elements within the genome were not required.[3] When deletion mutations occur more frequently, the largest populations have an advantage that suggests larger populations generally have an evolutionary advantage for development of new traits.[3]

Critical Mutation Rate

Critical mutation rate, or error threshold, limits the number of mutations that can exist within a self-replicating molecule before genetic information is destroyed in later generations.[7]

Contrary to the findings of previous studies,[8] critical mutation rate has been noted to be dependent on population size in both haploid and diploid populations.[9] When populations have fewer than 100 individuals, critical mutation rate can be exceeded, but will lead to loss of genetic material which results in further population decline and likelihood of extinction.[9] This ‘speed limit’ is common within small, adapted asexual populations and is independent of mutation rate.[10]

Effective population size (Ne)

The effective population size (Ne) is defined as "the number of breeding individuals in an idealized population that would show the same amount of dispersion of allele frequencies under random genetic drift or the same amount of inbreeding as the population under consideration." Ne is usually less than N (the absolute population size) and this has important applications in conservation genetics.[11]

Overpopulation may indicate any case in which the population of any species of animal may exceed the carrying capacity of its ecological niche.[12]

See also

References

  1. ^ a b c Wright S (November 1929). "The Evolution of Dominance". The American Naturalist. 63 (689): 556–561. doi:10.1086/280290. S2CID 85301374.
  2. ^ a b c d e f g h Rozen DE, Habets MG, Handel A, de Visser JA (March 2008). "Heterogeneous adaptive trajectories of small populations on complex fitness landscapes". PLOS ONE. 3 (3): e1715. Bibcode:2008PLoSO...3.1715R. doi:10.1371/journal.pone.0001715. PMC 2248617. PMID 18320036.
  3. ^ a b c d e f g h i j LaBar T, Adami C (December 2016). "Different Evolutionary Paths to Complexity for Small and Large Populations of Digital Organisms". PLOS Computational Biology. 12 (12): e1005066. arXiv:1604.06299. Bibcode:2016PLSCB..12E5066L. doi:10.1371/journal.pcbi.1005066. PMC 5140054. PMID 27923053.
  4. ^ Provine WB (July 2004). "Ernst Mayr: Genetics and speciation". Genetics. 167 (3): 1041–6. doi:10.1093/genetics/167.3.1041. PMC 1470966. PMID 15280221.
  5. ^ Lang GI, Botstein D, Desai MM (July 2011). "Genetic variation and the fate of beneficial mutations in asexual populations". Genetics. 188 (3): 647–61. doi:10.1534/genetics.111.128942. PMC 3176544. PMID 21546542.
  6. ^ Gerrish PJ, Lenski RE (1998). "The fate of competing beneficial mutations in an asexual population". Genetica. 102–103 (1–6): 127–44. doi:10.1023/a:1017067816551. PMID 9720276. S2CID 15148583.
  7. ^ Eigen M (October 1971). "Selforganization of matter and the evolution of biological macromolecules". Die Naturwissenschaften. 58 (10): 465–523. Bibcode:1971NW.....58..465E. doi:10.1007/bf00623322. PMID 4942363. S2CID 38296619.
  8. ^ Gillespie JH (November 2001). "Is the population size of a species relevant to its evolution?". Evolution; International Journal of Organic Evolution. 55 (11): 2161–9. doi:10.1111/j.0014-3820.2001.tb00732.x. JSTOR 2680348. PMID 11794777.
  9. ^ a b Aston E, Channon A, Day C, Knight CG (2013-12-27). "Critical mutation rate has an exponential dependence on population size in haploid and diploid populations". PLOS ONE. 8 (12): e83438. Bibcode:2013PLoSO...883438A. doi:10.1371/journal.pone.0083438. PMC 3873944. PMID 24386200.
  10. ^ Arjan JA, Visser M, Zeyl CW, Gerrish PJ, Blanchard JL, Lenski RE (January 1999). "Diminishing returns from mutation supply rate in asexual populations". Science. 283 (5400): 404–6. Bibcode:1999Sci...283..404A. doi:10.1126/science.283.5400.404. JSTOR 2896813. PMID 9888858.
  11. ^ Husemann M, Zachos FE, Paxton RJ, Habel JC (October 2016). "Effective population size in ecology and evolution". Heredity. 117 (4): 191–2. doi:10.1038/hdy.2016.75. PMC 5026761. PMID 27553454.
  12. ^ Population Reference Bureau PRB (December 1988). "What is overpopulation?". Population Education Interchange. 17 (4): 1–2. PMID 12281798.
This page was last edited on 3 December 2023, at 10:45
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