Project wildlife populations (3) shared
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)
REServ Eastern oyster ecology and economics Long Island Sound
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem. Also factored in is soil OM and solar radiation.
Really Bad Population Model - Greg Martin
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)
Clone of Clone of Prisoner's dilemma with replicator equation
Huemul-ciervo_colorado(sin_caza)-Ks_constantes
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Clone of Plant, Deer and Wolf Population Dynamics G-IV Intro
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)
Clone of Population classes
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)
Clone of REServ Eastern oyster ecology and economics Long Island Sound
Système dynamique Lotka-Volterra
Lotka-Volterra
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)
Clone of Population classes
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)
Clone of Eastern oyster population model Long Island Sound
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Plant, Deer and Wolf Population Dynamics
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 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)
REServ Eastern oyster 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)
Clone of IDREEM example oyster population model
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Clone of Plant, Deer and Wolf Population Dynamics G-IV Intro
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Clone of Plant, Deer and Wolf Population Dynamics G-IV Intro
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Clone of Plant, Deer and Wolf Population Dynamics
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Deer and Wolf Population Dynamics
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Clone of Plant, Deer and Wolf Population Dynamics
Clone of Basic BIDE equation
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Clone of Plant, Deer and Wolf Population Dynamics
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Clone of Plant, Deer and Wolf Population Dynamics
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Clone of Plant, Deer and Wolf Population Dynamics - ISD OWL