Population Ecology PDF

Topic 15 Population ecology Learning Outcomes Estimate population sizes based on the mark-recapture method Analyze graphically the demographics of a population over time Determine the type of survivorship curve based on demographic parameters from a life table Contrast exponential...

Topic 15 Population ecology Learning Outcomes Estimate population sizes based on the mark-recapture method Analyze graphically the demographics of a population over time Determine the type of survivorship curve based on demographic parameters from a life table Contrast exponential and logistic growth models Compare values of parameters in various growth model and predict the changes in population sizes Explain how life history traits can influence the lifetime fitness of an individual Identify graphically the presence of a trade-off in life history traits 2 https://www.wooclap.com/BIO1130 3  Topic 15 Population ecology 15.1 – Population size and demographics Population dynamics Population: group of individuals of a single species living in the same area and interbreed, producing fertile offspring. Population ecology: the study of populations in relation to their environment including environmental influences of population density and distribution, age structure, and variations in population size Population dynamics: the study of how complex interactions between biotic and abiotic factors influence variations in population size 5 Estimating population size Often it is impossible to count all individuals in a population  Extrapolation from a sub-sample 6 Estimating population size Often it is impossible to count all individuals in a population  Extrapolation from a sub-sample Mark-recapture method: To estimate the population size N: N=? 7 Estimating population size Often it is impossible to count all individuals in a population  Extrapolation from a sub-sample Mark-recapture method: To estimate the population size N: 1. Sample s individuals Sampled individuals (s) N=? 8 Estimating population size Often it is impossible to count all individuals in a population  Extrapolation from a sub-sample Mark-recapture method: To estimate the population size N: 1. Sample s individuals 2. Mark all s individuals Sampled individuals (s) Mark all individuals sampled N=? 9 Estimating population size Often it is impossible to count all individuals in a population  Extrapolation from a sub-sample Mark-recapture method: To estimate the population size N: 1. Sample s individuals 2. Mark all s individuals 3. Release all s individuals back N=? 10 Estimating population size Often it is impossible to count all individuals in a population  Extrapolation from a sub-sample Mark-recapture method: To estimate the population size N: 1. Sample s individuals 2. Mark all s individuals 3. Release all s individuals back 4. Resample r individuals Sample individuals again (r) N=? 11 Estimating population size Often it is impossible to count all individuals in a population  Extrapolation from a sub-sample Mark-recapture method: To estimate the population size N: 1. Sample s individuals 2. Mark all s individuals 3. Release all s individuals back 4. Resample r individuals 5. Count the number m of re-sampled marked individuals Sample individuals again (r) Count the marked individuals (m) N=? 12 Estimating population size Often it is impossible to count all individuals in a population  Extrapolation from a sub-sample Mark-recapture method: To estimate the population size N: 1. Sample s individuals 2. Mark all s individuals 3. Release all s individuals back 4. Resample r individuals 5. Count the number m of re-sampled marked individuals 6. Estimate the population size using: m s = r N sr 4×3 N = = = 12 Sample individuals again (r) m 1 Count the marked individuals (m) N=? 13 Estimating population size But mark-recapture methods make a few assumptions: Marked and unmarked individuals have the same probability of being sampled (shy versus bold) The marking of individuals does not affect the probability of being re-sampled (experience) The marked individuals have mixed completely back into the population No individuals are born, die, immigrate or emigrate during the re-sampling interval Population density (number of individuals per unit area or volume) can change over time through: (+) Immigration and birth (-) Emigration and deaths Change in population size = births + immigrants – deaths - emigrants 14 Demographics Demography: the study of changes over time in the vital statistics in populations, especially birthrates and death rates A life table can summarize the survival and reproduction rates of individuals in specific age groups in a population. A life table tracks a female cohort (born at the same time) because they are the only ones producing offspring.  Constant death rate in the Belding’s ground squirrel (log scale graph!)  Higher reproduction rate at age 4. 15 Demographics Survivorship curve: proportion of individuals in a cohort that are still alive at each age. Type I: low death rate of juveniles and adults followed by a rapid increase in old age groups (ex: mammals, few offspring, parental care) Type II: constant death rate (that you can see on a log scale!). A constant death rate means that the mortality is the same for juveniles, adults and old age groups (meaning, constant throughout the organism’s lifespan). Type III: high mortality for the young followed by a flattening of the death rate in adults (ex: many fish, large number of offspring, no parental care) 16  Topic 15 Population ecology 15.2 – Modeling population growth Exponential population growth Change in population size = births + immigrants – deaths – emigrants N = population size ∆𝑁 ∆N = change in population size =𝐵 − 𝐷= 𝑅 ∆𝑡 t = time ∆𝑁 =𝑟 ∆ 𝑡 𝑁 ∆t = time interval (generation time) ∆𝑡 B = births 𝑑𝑁 =𝑟𝑁 for each instant in time (infinitesimal time duration) D = deaths 𝑑𝑡 R = number of individuals added r∆t = individual growth rate contribution to the population growth r = per capita change in population size at each instant time (intrinsic growth rate of a single individual) 18 Exponential population growth Exponential population growth: Growth of a population in ideal, unlimited environment, represented by J-shaped curve when population sizes is plotted overt time. 𝑑𝑁 Exponential population growth: =𝑟𝑁 𝑑𝑡 r is constant but the number of individuals added to the entire population each generation increases. Assume (typical of population with) unlimited resources (no competition), that colonize a new environment, newly introduced species or rebound from a catastrophic event. 19  Logistic population growth But resources are finite! The population grows exponentially until it reaches an upper limit (habitat-specific). Carrying capacity (K): maximum population size that a particular environment can sustain. K can also vary in space and time depending on the abundance of limiting resources.  Decrease in the per capita birth rate and/or increase in death rate  We can rewrite 𝑑𝑁 =𝑟𝑁 to take into account the effect of the carrying capacity on population growth: 𝑑𝑡 𝑑𝑁 (𝐾 − 𝑁 ) Logistic population growth: =𝑟𝑁 𝑑𝑡 𝐾 ( 𝐾 − 𝑁is)the fraction of K available for population growth, and ( 𝐾 is −the 𝑁 )per capita population growth 𝑟 𝐾 𝐾 that takes into account the effect of the limited (density-dependent) resources on each individual. 20 Logistic population growth 𝑑𝑁 =𝑟𝑁 (𝐾 − 𝑁 ) 𝑑𝑡 𝐾 (𝐾 − 𝑁) If the population size N is small, the per capita population growth𝑟 will be close to r 𝐾 (exponential phase).  this means that there are a lot of resources per capita (for each individual). If the population size N is large, resources are limiting and( 𝐾 − 𝑁 ) is close to zero… so the per capita ( 𝐾 −is𝑁 population growth ) to zero. close 𝐾 𝑟 𝐾  this means that there are not enough resources per capita (for each individual). If N = K, the population stops growing (stationary phase). Logistic population growth produces a sigmoid (S-shaped) growth curve and the increase in population size is the fastest at intermediate population sizes when there are: Many reproducing individuals Lots of resources available 21 Logistic population growth cale! Logistic population are typical of microorganism cultures. Log s But the logistic model can often be too simplistic! It assumes that: Populations can adjust instantaneously to the increase in density (they might instead overshoot their carrying capacity K). The environment stays the same (predators can regulate the population size) 22  Topic 15 Population ecology 15.4 – Life history traits Life history Life history: all traits that affect an organisms schedule of reproduction and survival Example of life history traits: Mass at birth Age of sexual maturity Frequency of reproduction Reproductive lifespan Number of offspring (seeds, litter, clutch size) Investment in parental care Senescence Age at death (longevity) These traits are closely related to the lifetime fitness of an individual. 24 Life history trade-offs Reproduction Resources are finite!  energy is allocated to different life history traits  trade-off in this allocation. Survival E.g., trade-off between the number of offspring and the amount of resources invested in each offspring. Egg size and fecundity in Drosophila melanogaster in a selection experiment: Egg sizes increased in the large-egg selected lines Egg sizes decreased in the small-egg selected lines  Phenotypic negative correlations between egg size and fecundity in the large-eggs selected lines. Schwartzkopf et al. 1999 25 Life history trade-offs There seems to be two life history strategies: many small offspring or few large offspring Ecologists have tried to link these different strategies to the logistic growth model 𝑑𝑁 (𝐾 − 𝑁 ) =𝑟𝑁 𝑑𝑡 𝐾 r-selection: selection that favours traits at low densities, for a high reproductive success: mature rapidly early age of first reproduction y r strateg short lifespan large number of offspring few reproductive events high mortality rate low offspring survival rate have minimal parental care/investment  density-independent selection (low competition) E.g. weeds growing in an abandoned field 26 Life history trade-offs There seems to be two life history strategies: many small offspring or few large offspring Ecologists have tried to link these different strategies to the logistic growth model 𝑑𝑁 (𝐾 − 𝑁 ) =𝑟𝑁 𝑑𝑡 𝐾 K-selection: selection that favours traits at high densities, at or near the carrying capacity K: mature more slowly late age of first reproduction K strategy longer lifespan have few offspring at a time more reproductive events low mortality rate high offspring survival rate have high parental investment  density-dependent selection (high competition) E.g. mature trees growing in an old-growth forest 27 Life history trade-offs K-strategies and r-strategy are two extremes of a range of life history strategies found in an ecological succession (transition in the species composition of a community following a disturbance). r K Reproduction The reproductive output of Trade-off r strategies resemble that of type III survivorship curves. Survival A word of caution: K and r are not used anymore by ecologists!… Reproduction …the evolution of life-history traits can be better explained by age-specific mortality rather than just density dependence Weak (whether at carrying capacity K or not). trade-off ! …and trade-off may not be as pronounced if individuals vary Survival a lot in the total amount of resources they acquire! 28