hallo! carol horvitz professor of biology university of miami, florida, usa plant population...
TRANSCRIPT
![Page 1: Hallo! Carol Horvitz Professor of Biology University of Miami, Florida, USA plant population biology, spatial and temporal variation in demography applications](https://reader036.vdocument.in/reader036/viewer/2022062421/56649da85503460f94a95a73/html5/thumbnails/1.jpg)
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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Institute for Theoretical and Mathematical Ecology
University of MiamiCoral Gables, FL USA
Mathematics
Steve CantrellChris CosnerShigui Ruan
BiologyDon De AngelisCarol HorvitzMatthew Potts
Marine ScienceJerry AultDon Olson
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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
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Population dynamics: changes in size and shape of populations
Demographic structure age stage size space year habitat
Modeling dynamics life table matrix life cycle graph
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Age vs. stage?
Regression Log-linear
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Projection
n(t+1) = A n(t)
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Population projection matrix
Stage attimet+1
Stage at time t
seed seedling juvenile reproductive
seed 0.1
seedling 0.2
juvenile 0
reproductive
0
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Population projection matrix
Stage attimet+1
Stage at time t
seed seedling juvenile reproductive
seed 0
seedling 0.1
juvenile 0.3
reproductive
0.1
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Population projection matrix
Stage attimet+1
Stage at time t
seed seedling juvenile reproductive
seed 0
seedling 0
juvenile 0.1
reproductive
0.2
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Population projection matrix
Stage attimet+1
Stage at time t
seed seedling juvenile reproductive
seed 12
seedling 0
juvenile 0
reproductive
0.4
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Population projection matrix
Stage attimet+1
Stage at time t
seed seedling juvenile reproductive
seed 0.1 0 0 12
seedling 0.2 0.1 0 0
juvenile 0 0.3 0.1 0
reproductive
0 0.1 0.2 0.4
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Life cycle graph
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try it
Start with 10 in each stage class multiply and add row times column
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Population projection matrix
0.1 0 0 12
0.2 0.1 0 0
0 0.3 0.1 0
0 0.1 0.2 0.4
10
10
10
10
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try it
Start with 10 in each stage class
Start with 72, 17, 6 and 5 in the stage classes
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Population projection matrix
0.1 0 0 12
0.2 0.1 0 0
0 0.3 0.1 0
0 0.1 0.2 0.4
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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
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Projection
n(1) = A n(0)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)
time
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Projection
n(t+1) = A n(t)
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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)
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Projection
n(t) = At n(0)
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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.
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Projection
n(t+1) = A n(t)
n(t+1) = n(t)
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Projection
n(t+1) = A n(t)Examples: stable stage
reproductive valuessensitivity to perturbation
time variantdensity dependentother
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Projection exercises
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
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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