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Population Growth in a Structured Population

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Title: Population Growth in a Structured Population


1
Population Growth in a Structured Population
  • Glenn Ledder
  • University of Nebraska-Lincoln
  • http//www.math.unl.edu/gledder1
  • gledder_at_math.unl.edu

Supported by NSF grant DUE 0536508
2
Population Growth
  • Unstructured population model
  • a model that counts all individuals together
  • (discrete exponential function bt )
  • Structured population model
  • a model that counts individuals by category
  • (not an elementary mathematical function)

3
Outline
  1. Introduce mathematical modeling.
  2. Introduce the mathematical model concept.
  3. Use unstructured population growth as an example.
  4. Model structured population growth.

4
Mathematical Modeling
Real World
Conceptual Model
Mathematical Model
approximation
derivation
analysis
validation
  • A mathematical model represents a simplified view
    of the real world.
  • We want answers for the real world.
  • But there is no guarantee that a model will give
    the right answers!

5
Mathematical Model
Mathematical Model
Input Data
Output Data
Key Question
What is the relationship between input and
output data?
6
Unstructured Population Growth --Approximation
Real World
Conceptual Model
Mathematical Model
approximation
derivation
analysis
validation
  • Tomorrows population depends only on todays
    population.
  • All individuals alive tomorrow are born today or
    survive from today to tomorrow.

7
Unstructured Population Growth -- Derivation
Real World
Conceptual Model
Mathematical Model
approximation
derivation
analysis
validation
Nt Nt1 todays and tomorrows populations
f s fecundity and survival parameters
Fecundity Survival
Growth Rate Population
8
Unstructured Population Growth -- Analysis
Real World
Conceptual Model
Mathematical Model
approximation
derivation
analysis
validation
Fecundity Survival
Growth Rate Population
Nt N0 (f s)t
Nt1/Nt f s
9
Unstructured Population Growth --Validation
Real World
Conceptual Model
Mathematical Model
approximation
derivation
analysis
validation
  • Misses elements of chance.
  • Misses environmental limitations.
  • Pretty good for a short-time average.

10
Structured Population Growth
  • Some populations have distinct reproductive and
    non-reproductive stages.
  • Can we make a model for a structured population?
  • Will we find Nt1/Nt f s ?

11
Getting Started
  • A conceptual model requires scientific insight.
  • We should observe experiments.
  • Experiments for structured population growth are
    tricky, expensive, and time-consuming.

12
  • Presenting Bugbox-population, a real biology lab
    for a virtual world.
  • http//www.math.unl.edu/gledder1/BUGBOX/
  • Boxbugs are simpler than real insects
  • They dont move.
  • Development rate is chosen by the experimenter.
  • Each life stage has a distinctive appearance.

larva pupa adult
  • Boxbugs progress from larva to pupa to adult.
  • All boxbugs are female.
  • Larva are born adjacent to their mother.

13
Structured Population Dynamics
  • Species 1
  • Let Lt be the number of larvae at time t.
  • Let Pt be the number of juveniles at time t.
  • Let At be the number of adults at time t.

Lt1 f At
Pt1 Lt
At1 Pt
14
Structured Population Dynamics
  • Species 2
  • Let Lt be the number of larvae at time t.
  • Let Pt be the number of juveniles at time t.
  • Let At be the number of adults at time t.

Lt1 f At
Pt1 p Lt
At1 Pt
15
Structured Population Dynamics
  • Species 3
  • Let Lt be the number of larvae at time t.
  • Let Pt be the number of juveniles at time t.
  • Let At be the number of adults at time t.

Lt1 f At
Pt1 p Lt
At1 Pt a At
16
Structured Population Dynamics
  • Species 4
  • Let Lt be the number of larvae at time t.
  • Let Pt be the number of juveniles at time t.
  • Let At be the number of adults at time t.

Lt1 s Lt f At
Pt1 p Lt
At1 Pt a At
17
Computer Simulation Results
A plot of Xt/Xt-1 shows that all variables tend
to a constant growth rate ?
The ratios LtAt and PtAt tend to constant
values.
18
Equation for Growth Rate
Nt1/Nt ? k (constant)
k (k-a) (k-s) pf
There is always a unique k that is larger than
both a and s.
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