Upcoming Seminars: EECB seminars – 4:00 Thurs in OSN 102

1. Upcoming Seminars: • EECB seminars – 4:00 Thurs in OSN 102 • Thurs Feb 12: Mark Lindberg (U. A. Fairbanks) “Patterns and rates of dispersal in avian populations: Is scale important?”

2. Outline Introduction to population ecology Spatial structure Plant interactions and density dependence Age and size structure Plant demography Population growth models and parameters Life tables Survivorship curves

3. Reading Assignments Textbook chapter 4 and 5 Radford et al. 2002. Austral Ecology 27:258-358. Supplemental (not required) Allcock and Hik 2004. Oecologia 138:231-241. Silvertown and Lovett-Doust 1993. Introduction to plant population biology. Blackwell Scientific Publications, London.

4. Population Biology Population: collection of individuals of the same species living in the same area Population structure: spatial, age, size Population biology tries to explain origin of structure types, how they interact, and how they change with time.

5. Spatial Structure Patterns of distribution: random, dispersed, clumped. Patterns affected by biological and abiotic interactions. Test for randomness mean:variance ratio, Poisson analysis

6. Spatial Structure Why does pattern matter?

7. Spatial Structure Why does pattern matter? • Interpret causes of patterns • Stratification • Appropriate sampling regimes (density, frequency, non-quadrat) • Affects interactions

8. Plant interactions Space affects population biology in two ways: “neighborhood” – area of genetic or ecological influence Density – number of plants per unit area. Affects resource competition. Density influences growth, survival, fitness.

9. Law of Constant Yield Biomass/unit area increases with density, then levels off and becomes independent of density. Y=wmN(1 + aN)-1 Y= Yield wm=max potential biomass/plant N=density A=area necessary to achieve wm

10. Law of Constant Yield At high density Y is constant and proportional to wma-1 and w=Y/N. Plant size is inversely proportional to density : w=wm(1+aN)-1 Generalization: to allow for changing curves at high density (some species DECLINE in yield) replace –1 exponent with “-b”

11. Competition-Density Effect w=wm(1+aN)-b describes variation in weight with density at a given moment in time. Parameters vary during growth and with environmental conditions. Competition also leads to reduction in N over time (self-thinning)

12. “-3/2 power law” Self-thinning: smaller individuals die, reducing density as plant size and competition increases. Density dependent mortality. w=cN-k and log w = log c – k log N -k = slope of “self thinning line” (boundary) log c = constant between 3.5 and 5 -k is usually –3/2

13. Dense populations reach boundary line before sparse ones Slope of w:N constant across very different plant groups Controversy about “law” but there is a geometrical explanation (Yoda 1963) Plant weight proportional to volume (L3), plant sits on area (L2). When plant occupies all available space, ratio of weight to area CANNOT exceed 3:2

14. Age and Size Structure Size distribution of a given age rarely normal. Plants usually display highly skewed frequency distribution ( L shaped curve)

15. Skewed size distribution Two causes: Growth rate is normally distributed, and faster growing plants change normal size distribution to skewed. Larger plants suppress smaller ones (asymmetric competition). Self-thinning in even aged stand can return normal size/age distribution in time.

16. Age and Size Structure Maturity affected by size Size affected by environmental conditions and intraspecific competition Age-based models of populations often not appropriate for plants…use stage (or size) based

17. Modular growth • Plants have indeterminate growth • Plants grow by adding modules (roots, stems, leaves, clones) • Genet = one genetic individual (e.g. aspen grove) • Ramet = clonally produced part of a plant (may be essentially independent)

18. Demography Study of changes in population size and structure over time. Nt+1=Nt + B – D + I – E Nt+1/Nt = Finite rate of increase = λ when λ = 1 population is stable When λ < 1 population is shrinking When λ> 1 population is growing

19. Modeling populations: unrestricted growth Compare population at time t to population at time t+1 (difference equation) Nt+1=RNt+Nt or Nt+1=λNt λ=R+1 and R=geometric rate of increase For arbitrary time step: NT=N0λT For instantaneous growth (continuous time; differential equation) dN/dt=rN(t) and N(T)/N(0)=erT So N(T)=N(0)erT

20. Modeling populations: unrestricted growth N Time

21. Unrestricted growth What sorts of populations exhibit exponential or geometric growth? Unrestricted resources No competition or other limitations

22. Unrestricted growth What sorts of populations exhibit exponential or geometric growth? Unrestricted resources No competition or other limitations Invasive species, expanding populations Exponential decline: constant mortality rate > birth rate

23. Density dependent growth Biological factors interact to produce a negative feedback between N and R. Examples: Resources decrease (are used up) Available space is filled Interference (agression etc) may increase More efficient predation as prey density increases Emmigration or dispersal increases Immigration decreases

24. Density dependent growth Can model density dependent growth with logistic equation: dN/dt=rN((K-N)/N) K= population at equilibrium carrying capacity At K population growth rate is zero

25. Density dependent growth As intrinsic rate of increase goes up, behaviour of model changes: Carrying capacity: one equilibrium value for N Stable limit cycles: N oscillates among several values As R increases, number of values in cycle doubles (for 2.1<R<2.57) Eventually (R>2.57) dynamics are CHAOTIC. Not random, highly density dependent, but unpredictable.

26. Time lags can also create cycles: Resource availability changes with time and population size (eg herbivores and food source) dN/dt=rN((K-N(t-T))/K) Classic example: lynx and hares…

27. Characteristics of populations Ecologists use life tables and fecundity schedules to organize demographic data: Age or stage-specific survivorship, birth rates, death rates, reproductive value etc. Can be based on cohorts (cohort life table) or age/stage classes (static life table) May contain the following parameters: Age/stage, number surviving (Nx), survivorship (lx=Nx/N1), mortality (dx=(lx-1-lx)), mortality rate (qx=dx/lx), fecundity (bx= offspring per individual), reproductive value (Vx = bx+ Σ(lx+I/lx)bx+I)

28. Type I Type II Type III Survivorship Curves Plots of number of survivors (log scale) versus age/stage. Three basic shapes: different life histories.

29. Type I Type II Type III Survivorship What do the shapes of the survivorship curves mean? Examples?

30. Importance

31. Importance Demography affects current distributions, historical range shifts/spread, gene frequencies, and population structures. Population dynamics important for commercial species: yield, growth, survival, etc. Use population models to create management plans for both endangered and invasive species Herbivory (eg stock production) can affect population parameters of range species: Riginos and Hoffman (2003). Journal of Applied Ecology 40:615-625.

32. Lab: life cycle diagrams, matrix models, life tables, and their applications for management Next lecture: metapopulations, life history strategies, allocation.