Woodland caribou is a species at risk because of northward expansion of resource development activity.  Some herds are in dire condition and well below self-sustainability, while others are only moderately below self-sustaining levels.  Given limited conservation dollars, what are the most effectiv
Triage Population Ecology Caribou Wolves Moose Conservation
Woodland caribou is a species at risk because of northward expansion of resource development activity.  Some herds are in dire condition and well below self-sustainability, while others are only moderately below self-sustaining levels.  Given limited conservation dollars, what are the most effective conservation actions, and how much money needs to be spent?  Which herds should be a priority for conservation efforts? The purpose of this model to provide insight into these difficult conservation questions.  

This model was developed by Rob Rempel and Jen Shuter at the Centre for Northern Forest Ecosystem Research, and was based in part on input from attendees of a modelling workshop ("Modelling the Caribou Questions") held at the 16th North American Caribou Workshop in Thunder Bay, Ontario, May 2016.
Testing of Caribou Conservation Sub-Models v2
Rob Rempel
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
Environment Populations Midterm Ecology
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Matthew Gall
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. It was "cloned" from a model that InsightMaker provides to its users, at https://insightmaker.com/insight/2068/Isle-Royale-Predator-Prey-Interactions Thanks Scott Fortmann-Roe.
Populations Math Modeling Mat375 Ecology Environment
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. It was "cloned" from a model that InsightMaker provides to its users, at
https://insightmaker.com/insight/2068/Isle-Royale-Predator-Prey-Interactions
Thanks Scott Fortmann-Roe.

I've created a Mathematica file that replicates the model, at
http://www.nku.edu/~longa/classes/2018spring/mat375/mathematica/Moose-n-Wolf-InsightMaker.nb

It allows one to experiment with adjusting the initial number of moose and wolves on the island.

I used steepest descent in Mathematica to optimize the parameters, with my objective data being the ratio of wolves to moose. You can try my (admittedly) kludgy code, at
http://www.nku.edu/~longa/classes/2018spring/mat375/mathematica/Moose-n-Wolf-InsightMaker-BestFit.nb

{WolfBirthRateFactorStart,
WolfDeathRateStart,
MooseBirthRateStart,
MooseDeathRateFactorStart,
moStart,
woStart} =
{0.000267409,
0.239821,
0.269755,
0.0113679,
591,
23.};

Clone of Isle Royale: Predator/Prey Model for Moose and Wolves
Clay Frink
This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.
Introductory Population Ecology

This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.

Clone of Bio 190: BIDE Model With Carrying Capacity
ella ah
This is a basic model for use with our lab section.  The full BIDE options.
Population Introductory Ecology

This is a basic model for use with our lab section.  The full BIDE options.

Cēsis līdz 2020
inita
4
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
Midterm Populations Mat375 Environment Ecology
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

Thanks to Jacob Englert for the model if-then-else structure.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of MAT 375 Midterm file: Model of Isle Royale: Predator Prey Interactions
Matthew Gall
A simulation model that shows the relationship between the mountain biking trails in derby and the the effect it has on the tourism, 
BMA708 System Dynamics Ecology Tourish Economics
A simulation model that shows the relationship between the mountain biking trails in derby and the the effect it has on the tourism, 
Simulation of Derby Mountain Bike Vs Logging
Adarsh Yamphu
Insight diagram
Computer Modeling Ecology
Clone of wolf ~ logistic growth
deo
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
Midterm Environment Populations Ecology
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Matthew Gall
Insight diagram
Ecology Computer Modeling
Clone of wolf ~ logistic growth
Andrew Carlson
This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.
Introductory Population Ecology

This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.

Clone of Bio 190: BIDE Model With Carrying Capacity
Todd Levine
Insight diagram
Computer Modeling Ecology
Clone of wolf ~ logistic growth
Dominic Jones
This model simulates the competition between logging versus adventure tourism(mountain bike riding) in Derby Tasmania. The purpose of this model is that focus on the relationship between the timber industry and mountain bike tourism in adventure. It also reflects how well these two industries co-exi
BMA 708 System Dynamics Economy Ecology Tourism
This model simulates the competition between logging versus adventure tourism(mountain bike riding) in Derby Tasmania. The purpose of this model is that focus on the relationship between the timber industry and mountain bike tourism in adventure. It also reflects how well these two industries co-exist. 

How this model works
This model shows tree grow development. In order to maximize the profits from selling the logging, the demand for timbers will increase. 
The mountain bike visits depend on past experience and recommendations. In addition, past experience and recommendations depend on Scenery, which is determined by the number of trees and visitors and adventure number. However, park capacity limits the number of use mountain bikes, because the convince of parking is a consideration for the visitors. 
It seems like the high logging sale does not deter mountain bike activities. By reducing the parking capacity, visitor experience and number are increased. Because of the strong relationship between the mountain bike park and the explosion in visitor numbers. With the improvement in the number of visitors, the number of food and restaurants will go up as well. Because of the daily needs of the visitors. 

Simulation of Derby Mountain bikes versus logging
Jayden Wu
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. Experiment with adjusting the initial number of moose and wolves on the island.
Environment Populations Ecology
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

Experiment with adjusting the initial number of moose and wolves on the island.
Clone of Isle Royale: Predator Prey Interactions
Robert L. Brown
​Physical meaning of the equations The Lotka–Volterra model makes a number of assumptions about the environment and evolution of the predator and prey populations: 1. The prey population finds ample food at all times. 2. The food supply of the predator population depends entirely on the
Ecology Biology Population Chaos Education
​Physical meaning of the equations
The Lotka–Volterra model makes a number of assumptions about the environment and evolution of the predator and prey populations:

1. The prey population finds ample food at all times.
2. The food supply of the predator population depends entirely on the size of the prey population.
3. The rate of change of population is proportional to its size.
4. During the process, the environment does not change in favour of one species and genetic adaptation is inconsequential.
5. Predators have limitless appetite.
As differential equations are used, the solution is deterministic and continuous. This, in turn, implies that the generations of both the predator and prey are continually overlapping.[23]

Prey
When multiplied out, the prey equation becomes
dx/dt = αx - βxy
 The prey are assumed to have an unlimited food supply, and to reproduce exponentially unless subject to predation; this exponential growth is represented in the equation above by the term αx. The rate of predation upon the prey is assumed to be proportional to the rate at which the predators and the prey meet; this is represented above by βxy. If either x or y is zero then there can be no predation.

With these two terms the equation above can be interpreted as: the change in the prey's numbers is given by its own growth minus the rate at which it is preyed upon.

Predators

The predator equation becomes

dy/dt =  - 

In this equation, {\displaystyle \displaystyle \delta xy} represents the growth of the predator population. (Note the similarity to the predation rate; however, a different constant is used as the rate at which the predator population grows is not necessarily equal to the rate at which it consumes the prey). {\displaystyle \displaystyle \gamma y} represents the loss rate of the predators due to either natural death or emigration; it leads to an exponential decay in the absence of prey.

Hence the equation expresses the change in the predator population as growth fueled by the food supply, minus natural death.


Clone of Prey&Predator
Mariane Kfoury
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
Ecology Populations Midterm Environment
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Alyssa Farmer
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
Midterm Populations Environment Ecology
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Austin Campbell
This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.
Population Ecology Introductory

This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.

Clone of Clone of Bio 190: BIDE Model With Carrying Capacity
Heidi Ballew
​The probability density function (PDF) of the normal distribution or Bell Curve of Normal or Gaussian Distribution is the mean or expectation of the distribution (and also its median and mode).   The parameter is its standard deviation with its variance then, A random variable with a Gaussi
Statistics Physics Distribution Voting MATHS Policy Science Curve Gaussian Democracy Bell Normal Intelligence Education Climate Density Probability Weather Function Ecology Politics
​The probability density function (PDF) of the normal distribution or Bell Curve of Normal or Gaussian Distribution is the mean or expectation of the distribution (and also its median and mode). 

The parameter is its standard deviation with its variance then, A random variable with a Gaussian distribution is said to be normally distributed and is called a normal deviate.
However, those who enjoy upskirts are called deviants and have a variable distribution :) 

A random variable with a Gaussian distribution is said to be normally distributed and is called a normal deviate.

If mu = 0 and sigma = 1

If the Higher Education Numbers Are Increased then the group decision making ability of society would be raised above that of a middle teenager as it is now
BUT 
Governments can control children by using bad parenting techniques, pandering to the pleasure principle, so they will make higher education more and more difficult as they are doing


85% of the population has a qualification level equal or below a 12th grader, 17 year old ... the chance of finding someone with any sense is low (~1 in 6) and the outcome of them being chosen by those who are uneducated in the policies they are to decide is even more rare !!!

Experience means little if you don't have enough brain to analyse it

Democracy is only as good as the ability of the voters to FULLY understand the implications of the policies on which they vote., both context and the various perspectives.   National voting of unqualified voters on specific policy issues is the sign of corrupt manipulation.

Democracy:  Where a group allows the decision ability of a teenager to decide on a choice of mis-representatives who are unqualified to make judgement on social policies that affect the lives of millions.
The kind of children who would vote for King Kong who can hold a girl in one hand and swat fighter jets out of teh sky off the tallest building, doesn't have a brain cell or thought to call his own but has a nice smile and offers little girls sweets.



Clone of Clone of ​The probability density function (PDF) of the normal distribution or Bell Curve Gaussian Distribution by Guy Lakeman
Andang Saefullah
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
Environment Populations Midterm Ecology
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Matthew Gall
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
Environment Populations Midterm Ecology
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Donna Odhiambo
Addition of Allee effect to Logistic Growth Insight 1540. From the Appendix of Marten Scheffer's 2009 Book Critical Transitions in Nature and Society p332 http://bit.ly/yrd3GN. The Allee affect describes a threshold density (smaller than the carrying capacity K) below which populations go into free
Ecology Health Care

Addition of Allee effect to Logistic Growth Insight 1540. From the Appendix of Marten Scheffer's 2009 Book Critical Transitions in Nature and Society p332 http://bit.ly/yrd3GN. The Allee affect describes a threshold density (smaller than the carrying capacity K) below which populations go into free fall extinction.

Allee Effect from Critical Transitions
Geoff McDonnell
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale websi
Populations Midterm Ecology Environment
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Andrew E Long
79
This model is a modified version of the 'Very Simple Ecosystem Model' (VSEM; Hartig et al. 2019). Controls have been added to gross primary productivity (GPP) and heterotrophic respiration (Rhetero) based on evapotranspiration rates. Reference: Hartig, F., Minunno, F., and Paul, S. (2019). Baye
GEG5224 Ecosystem Ecology Environment Carbon Productivity Decomposition Evapotranspiration
This model is a modified version of the 'Very Simple Ecosystem Model' (VSEM; Hartig et al. 2019). Controls have been added to gross primary productivity (GPP) and heterotrophic respiration (Rhetero) based on evapotranspiration rates.

Reference:
Hartig, F., Minunno, F., and Paul, S. (2019). BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics. R package version 0.1.7. https://CRAN.R-project.org/package=BayesianTools
Clone of Very Simple Ecosystem Model with Evapotranspiration (VSEM-ET)
Haythum Syed