Lecture 13 notes
Population Dynamics Part 2 (Dave Allan)
Refer to Ricklefs Ch. 10, 12
Main points: adding necessary complications of age, spatial, and temporal distributions to our original model from last time (Nt = λtN0) to make it more realistic
- Age-specific rates
- lx – survivorship function – probability of a newborn surviving until age x, with convention that l1=1
- mx / bx / fx – maternity/birth/fecundity function (all synonymous) – number of females born to a female of age x (Question: does that mean biologists should think it's crazy that most human populations are taught to prefer sons instead?)
- sx – survival rate – proportion of individuals of age x surviving the next year (x+1), or lx+1/lx= sx
- mortality rate = 1/sx
- These rates can be found using data (following a cohort in a certain population and seeing how many survive over the years, how many female offspring they produce, etc.)
- Structural implications
- When you look at a larger picture (more time), these vital rates and age structure determine population change
- R0 = net reproductive rate, or the number of daughters of a single individual in her lifetime = Σ(lxmx) from x=1 to max age
- From this we can calculate a mean generation time T=Σ(xlxmx)/ Σ(lxmx), a female’s age when she has her median daughter
- You can then estimate λ as well: λ=R01/T
- Consider that if the mean generation time T=1, the reproductive rate R0 would be equivalent to λ.
- If a population is under constant environmental conditions then, a stable age structure will develop. (in real life this doesn’t happen much)
- Populations with the same vital rates will always reach the same stable age distribution (SAD) regardless of where you start from.
- Alternative modeling method: Leslie Matrix to simplify running of demographic models → Nt=MtN0, where M is a Leslie matrix
- See http://en.wikipedia.org/wiki/Leslie_matrix for more
- The actual link to the site: Leslie_matrix
- An application of the Leslie Matrix model: population viability analysis (PVA)
- use it to assess and predict population dynamic for rare populations, where there is less margin for error – how should we manage them, conserve?
- identify threats faced by species and finding likelihood of species survival for given time
- rare species’ probability of extinction is measurable: p(E)
- demographic/deterministic factors could result in λ<1, which leads to extinction (birth rates < death rates)
- stochastic (chance variation – lack of food, or uneven sex ratio of offspring…) factors could also lead to extinction despite λ>1 or =1.
- What we need is to maintain several populations, each with a minimum population size
- PVA uses both these factors too evaluate “extinction vortex”, a downward cycling towards extinction: small population size → increased inbreeding/genetic drift → decreased reproduction and survival → reduced λ → small population size…
- Use PVA for planning research and data collection, assessing vulnerability on scarce resources, and ranking management options for species
Spatial structure and distribution of populations
- Species populations are made up of sub-populations, distributed in a larger total geographic occupied area, so that the population has spatial structure/spacing, which varies over time
- Fundamental niche – range of environmental conditions in which an organism can live
- Realized niche/habitat – where organism actually lives, subset of fundamental niche, determined by predators, competitors, pathogens, etc.
- Dave Allan quote: “Most invasive species are wimps, but some are Godzilla types” – referring to African tilapias (a Godzilla type)
- Migratory species are NOT species that undergo “great” migrations over long distances every year (Monarch butterflies or geese), but species who occupy large ranges, locally.
- Require existence of spatially distant habitats and migratory pathway
- Metapopulation – patches of equal quality, but anything outside is unhabitable.
- Size can vary
- Viewed as a “population of populations” linked by immigration and emigration – how many patches are occupied? (instead of how many individuals per patch)
- dP/dt = cP(1-P)-eP, where c is colonization rate and e is extinction rate. (regarding populated proportion of patches)
- P*=1-e/c (fraction patch occupancy at equilibrium)
- If c<e, extinction; but if c>e, species will persist
- Source-sink dynamics – patches vary in quality, and in-between areas are still uninhabitable. But dispersal between these patches are critical to maintaining populations in them.
- Patch connectivity must be maintained – but if they are too connected, then they are basically one population; alternatively if they are not connected enough, thee will be no “rescue” effect between them
- Implications of population structure
- Species formation – isolated patches are more likely to develop into species
- Genetic variation and interchange – subpopulations could have different selection pressures, depending on how their own patch is different
- Population viability – rescuing of other populations
- Management of populations and habitat are linked
page revision: 12, last edited: 21 Nov 2009 02:01