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Hallo!

Hallo!. Carol Horvitz Professor of Biology University of Miami, Florida, USA plant population biology, spatial and temporal variation in demography applications to plant-animal interactions, invasion biology, global change, evolution of life span.

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Hallo!

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  1. Hallo! • Carol Horvitz • Professor of Biology • University of Miami, Florida, USA • plant population biology, spatial and temporal variation in demography • applications to plant-animal interactions, invasion biology, global change, evolution of life span

  2. Institute for Theoretical and Mathematical Ecology University of Miami Coral Gables, FL USA Mathematics Steve Cantrell Chris Cosner Shigui Ruan Biology Don De Angelis Carol Horvitz Matthew Potts Marine Science Jerry Ault Don Olson

  3. Dynamics of structured populations • N(t+1) = N(t) * pop growth rate • Pop growth rate depends upon • Survival and reproduction of individuals • Survival, growth and reproduction are not uniform across all individuals • Thus the population is structured

  4. Demographic structure age stage size space year habitat Modeling dynamics life table matrix life cycle graph Population dynamics: changes in size and shape of populations

  5. Regression Log-linear Age vs. stage?

  6. Projection n(t+1) = A n(t)

  7. Population projection matrix

  8. Population projection matrix

  9. Population projection matrix

  10. Population projection matrix

  11. Population projection matrix

  12. Life cycle graph

  13. try it • Start with 10 in each stage class • multiply and add • row times column

  14. Population projection matrix

  15. try it • Start with 10 in each stage class • Start with 72, 17, 6 and 5 in the stage classes

  16. Population projection matrix

  17. try it • Start with 10 in each stage class • n(2) = 121, 3, 4, 7 • Start with 72, 17, 6 and 5 in the stage classes • n(2) = 67,16, 6, 5 • population growth rate = 0.9564

  18. Projection n(1) = A n(0) time n(2) = A n(1) n(3) = A n(2) n(4) = A n(3) n(5) = A n(4) n(6) = A n(5)

  19. Projection n(t+1) = A n(t)

  20. Projection n(1)= A n(0) n(2)= AAn(0) n(3)= AAAn(0) n(4)= AAAAn(0) n(5)= AAAAAn(0) n(6)=AAAAAAn(0)

  21. Projection n(t) = At n(0)

  22. Projection n(t+1) = A n(t) Each time step, the population changes size and shape. The matrix pulls the population into different shapes. There are some shapes that are ‘ in tune ’ with the environment. For these, the matrix only acts to change the size of the population. In these cases the matrix acts like a scalar.

  23. Projection n(t+1) = A n(t) n(t+1) = n(t)

  24. Projection n(t+1) = A n(t) Examples: stable stage reproductive values sensitivity to perturbation time variant density dependent other

  25. Stable age distribution and population growth rate Reproductive value of different ages Not all matrices yield a stable age distribution concentration of reproduction in the last age oscillations Projection exercises

  26. Analytical entities • Dominant eigenvalue • Dominant right eigenvector (ssd) • Dominant left eigenvector (rv) • Derivative of population growth rate with respect to each element in the matrix • Derivative of the logarithm of population growth rate with respect to the logarithm of each element in the matrix

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