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Ecology 10.docx

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Western University
Biology 2483A
Mark Moscicki

Ecology-Lecture 10 Oct 15 2013 Population Dynamics  The ways in which populations change in abundance over time. The number of individuals in a population can change from one time period to the next.  Population size changes as a result of four processes: Birth, death, immigration, and emigration.  Nt+1=Nt + B - D + I - E  Nt=population size at time t  B=number of births  D=number of deaths  I=number of immigrants  E=number of emigrants between time t and time t+1 (In between one year and the next) Patterns of Population Growth  Populations exhibit a wide range of growth patterns. The four main patterns are exponential growth, logistic growth, population fluctuations, and regular population cycle.  These four patterns are not mutually exclusive. A single population can experience each of them at different times Exponential Growth  Typically occurs when conditions are favourable  Population increases (or decreases) by a constant proportion at each point in time  N(t+1)=ƛNt if reproduction occurs at discrete time periods  dN/dt=rN if reproduction is continuous  This cannot increase forever! When conditions are favourable, a population can increase exponentially for a limited time. These occur within the established range of a species (good weather for several years straight) When a species reaches a new area, (either by its own dispersal or human assistance) exponential growth can occur if conditions are favourable. The population may grow exponentially until density-dependent factors regulate its numbers.  An example of how dispersal leads to exponential growth is provided by the cattle Egret subspecies. These cattle have succesfully colonized new regions by long distance or jump dispersal events (long distance over inhospitable habitats; oceanic islands) Local populations in the new region then increase in size and expand by short distance dispersal events to occupy nearby areas of suitable habitat. Logistic Growth  Population approaches an equilibrium over time in which the population does not really change  These populations first increase, then fluctuate by a small amount around the carrying capacity  Plots of real populations rarely match the logistic curve exactly. "Logistic growth" is used broadly to indicate any population that increases initially, then levels off at the carrying capacity  Sheep abundance in Tasmania over time is only roughly similar to the characteristic S shape of a logistic curve. The population initially increases rapidly. Later, the population numbers fluctuate above and below a max sustainable population size  In dN/dt=rN(1-N/K), K (carrying capacity) is assumed to be constant. For K to be constant, the birth rates and death rates must be constant over time at any given density (cannot change from year to year) This rarely happens in nature. Birth and death rates do vary over time, likely as a result of changing environmental conditions. Thus we expect carrying capacity to fluctuate  The diagram allows you to determine the carrying capacity. This is found graphically by plotting births and deaths and finding the point in which they intersect. In the first image, they intersect at one point (K) The image to the right shows broader bands for births and deaths. They intersect at a broad range of values. (hence the fluctuation) Population Fluctuations  In all populations, numbers rise and fall over time Figure 10.6 Population Fluctuations (also shown in Sheep)  Most common pattern  Fluctuations can be deviations from a growth pattern. (seen in shape-deviation from logistic) If population EXACTLY matched the logistic growth curve, it would not be considered a flutuation  They may occur as erratic increases/decreases from an overall mean value  Phytoplankton abundance sometimes increased/decreased within a matter of just a few days (lake Erie) This could reflect changes in environmental factors such as nutrient supplies, temperature or predator abundance  In some cases, these fluctuations are small (Tasmanian sheep) but in other cases it may lead to a population explosion at certain times Population Outbreak  Number of individuals increases rapidly  Mnemiopsis jellyfish  Rapid variations in population sizes over time have also been observed in many terrestrial systems (insects) These population explosions can have detrimental effects  An ongoing outbreak of the mountain Pine beetle has killed hundreds of millions of trees across British Columbia. This has altered forest composition , and C02 is released as the trees decay (17.6 megatons every year) --> Increased global warming :( Population Cycles  Some populations have alternating periods of high and low abundance at regular intervals Figure 10.9 A Population Cycle  Populations of small rodents, such as lemmings and voles, typically reach a peak every 3-5 years  Different factors may drive population cycles in rodents. These may be due to internal (hormonal or behavioural changes in response to crowding, and external (weather, food supplies, predators) factors  For collared lemmings in Greenland, field studies and modelling indicated that the 4 year cycle is driven by predators, such as the stoat which specializes on lemmings. In other studies, predator removal had no effect on population cycles. It was suggested that cycles are caused by lemmings and their food source. Factors driving population cycles may vary by place/species  Studies showed that predators are driving force behind cycles in voles. However, others showed that they had no effect  As the above conflicting results show, a universal cause of population cycles in small rodents has not emerged. It may be that ecological mechanisms that drive population cycles differ from place to place, and from one species to another  Some population cycles may stop if certain environmental factors change!  Lemming cycles have ceased to occur in some high latitude locations. Lemmings thrive when warmth from the ground melts a thin layer of the snow cover, leaving a small gap between the ground and the snow. Warmer winter temperatures have caused the snow to melt and refreeze, preventing the formation of these gaps. This has made it more difficult for lemmings to feed and avoid predators. Their populations have stopped cycling every 3-4 years (cease to rise in abundance every 3-4 years) Delayed Density Dependence  Delays are an important feature of interactions in nature  Delayed density dependence is defined as delays in the effect that density has on population size. The number of individuals born in a given time period is influenced by population densities that were present several time periods ago  Delayed density dependence can cause populations to fluctuate in size.  Example: A predator reproduces more slowly than its prey. If predator population is small, prey Damped Oscillations population may increase, then the predators will increase, but with a time lag. Many predators may reduce the prey population, and then the predator Stable Limit Cycle population will decrease again.  Predators and prey increase in density at different times (lag) When such a mismatch takes place, the predators may survive or reproduce poorly, and their numbers may drop. If prey numbers then increase (because there are now fewer predators) predator numbers may rebound, then fall again due to built in time lag (delay in response of predators to prey density could cause predator numbers to fluctuate over time)  The logistic equation can be modified to include time lags!  dN/dt=rN [1-N(t-T)/K] where N(t-T) represents the population size at time t-T. Incorporation of this term indicates that the population growth rate is reduced by the size of the population at time t-T in the past, not by the populations current size, Nt  The figure to the right shows logistic curves with delayed density dependence. When rT (growth rate and time lag) is small, the population exhibits logistic growth (top) At intermediate values of rT, the population exhibits damped oscillations (fluctuations about carrying capacity that become smaller over time)(middle) When rT is large, the population exhibits a stable limit cycle (regular cycle of ongoing fluctuations about the carrying capacity) (bottom)  Population fluctuations become more pronounced as the product rt increases. Essentially, when a population grows very rapidly (large r) or when there is a very large time lag ( large T) the size of the population can become much larger than the carrying capacity before its numbers begin to decline  J. Nicholson studied density dependence in sheep blowflies using laboratory experiments. These insects feed on dead animals but also attack living hosts. Blowflies are a pest of sheep. They feed, then lay eggs near open wounds on sheep. Maggots burrow inside sheep where they feed on internal tissues causing lesions/death. In the first experiment, adults were given unlimited food (able to lay eggs near sores), but larvae were restricted to 50 g of liver per day (maggots die). With abundant food, females laid enormous numbers of eggs, but when the eggs hatched, most maggots died because of lack of food. (high adult densities result in fewer eggs surviving. Negative effects of high adult densities were not felt until a later time (maggots hatch) since they had unlimited food. This resulted in an adult population size that fluctuated dramatically. (because few adult maggots were being produced. Eventually, the number of adults was so low that the few eggs they produced were able to give rise to a new generation of adults. Once this happened, the number of adults would begin to rise again, then crash, repeating the cycle just described.  In the second experiment, both adults and larvae were given limited food. The adult population size no longer showed repeated fluctuations. (fluctuations were reduced) This was a method of removing some of the effects of delayed density dependence.
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