This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
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Small replicator equation setup (2d) with prisoner's dilemma payoff matrix (can be adjusted): (dx/dt)_i = x_i*((A*x)_i-x^T*A*x)
Small replicator equation setup (2d) with prisoner's dilemma payoff matrix (can be adjusted): (dx/dt)_i = x_i*((A*x)_i-x^T*A*x)
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Eastern oyster growth model calibrated for Long Island Sound

This is a one box model for an idealized farm with one million oysters seeded (one hectare @ a stocking density of 100 oysters per square meter)

1. Run WinShell individual growth model for one year with Long Island Sound growth drivers;

2. Determine the scope for growth (in dry tissue weight per day) for oysters centered on the five weight classes)

3. Apply a classic population dynamics equation:

dn(s,t)/dt = -d[n(s,t)g(s,t)]/ds - u(s)n(s,t)

s: Weight (g)
t: Time
n: Number of individuals of weight s
g: Scope for growth (g day-1)
u: Mortality rate (day-1)

4. Set mortality at 30% per year, slider allows scenarios from 30% to 80% per year

5. Determine harvestable biomass, i.e. weight class 5, 40-50 g (roughly three inches length)
with the carrying capacity instead of mortality rate.
K = Carrying capacity (g m-2)
This is a demonstration of how logistic growth can be modeled with either one or two stocks. However, the two-stock case shows how the implementation of the carrying capacity is somehow less arbitrary than in the one-stock case.
Wolf and Deer population interaction geog 166
Small replicator equation setup (2d) with prisoner's dilemma payoff matrix (can be adjusted): (dx/dt)_i = x_i*((A*x)_i-x^T*A*x)
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Système dynamique Lotka-Volterra
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Simple model illustrating the population dynamics equation:

dn(s,t)/dt = -d[n(s,t)g(s,t)]/ds - u(s)n(s,t)

s: Weight (g)
t: Time
n: Number of individuals of weight s
g: Scope for growth (g day-1)
u: Mortality rate (day-1)
Eastern oyster growth model calibrated for Long Island Sound
Developed and implemented by Joao G. Ferreira and Camille Saurel; growth data from Eva Galimany, Gary Wickfors, and Julie Rose; driver data from Julie Rose and Suzanne Bricker; Culture practice from the REServ team and Tessa Getchis. This model is a workbench for combining ecological and economic components for REServ. Economic component added by Trina Wellman.

This is a one box model for an idealized farm with one million oysters seeded (one hectare @ a stocking density of 100 oysters per square meter)

1. Run WinShell individual growth model for one year with Long Island Sound growth drivers;

2. Determine the scope for growth (in dry tissue weight per day) for oysters centered on the five weight classes)

3. Apply a classic population dynamics equation:

dn(s,t)/dt = -d[n(s,t)g(s,t)]/ds - u(s)n(s,t)

s: Weight (g)
t: Time
n: Number of individuals of weight s
g: Scope for growth (g day-1)
u: Mortality rate (day-1)

4. Set mortality at 30% per year, slider allows scenarios from 30% to 80% per year

5. Determine harvestable biomass, i.e. weight class 5, 40-50 g (roughly three inches length)
Eastern oyster growth model calibrated for Great Bay.

Developed and implemented by Joao G. Ferreira and Camille Saurel; growth data, driver data, and culture practice from Phil Trowbridge, Ray Grizzle, and Suzanne Bricker.

This is a one box model for an idealized farm with one million oysters seeded (one hectare @ a stocking density of 100 oysters per square meter)

1. Run WinShell individual growth model for one year with Great Bay growth drivers;

2. Determine the scope for growth (in dry tissue weight per day) for oysters centered on the five weight classes)

3. Apply a classic population dynamics equation:

dn(s,t)/dt = -d[n(s,t)g(s,t)]/ds - u(s)n(s,t)

s: Weight (g)
t: Time
n: Number of individuals of weight s
g: Scope for growth (g day-1)
u: Mortality rate (day-1)

4. Set mortality at 30% per year, slider allows scenarios from 30% to 80% per year

5. Determine harvestable biomass, i.e. weight class 5, 40-50 g (roughly three inches length)
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.