A pest known as a grape-leaf hopper can cause considerable losses in vineyards. Periodically it was found that a natural parasite, anagrus epos, drastically reduced the size of the hopper population. This, in turn, led to a reduction in food (hoppers) available to the parasite and the parasite population declined until the hopper population increased again. This cycle would repeat.It was found that the parasite, anagrus epos, also feeds on a non-pest leaf hopper which feeds on blackberries. By planting small patches of wild blackberries in the vineyards, the growers were able to maintain a stable parasite population that was large enough to control population explosions of both leaf hoppers.
Clone of Grape-leaf Hopper system
At first, I cloned the System Dynamics Model from the "Predator-Prey Interactions" tutorial. After I did this for populations of squirrels and mountain lions instead of moose and wolves, the model showed that the more squirrels mountain lions catch, the more the mountain lion population grows, and the squirrel population declines. The squirrel death rate, therefore, depends on the number of mountain lions and the mountain lion birth rate depends on the number of squirrels.
I complicated the model by adding 15 hunters to the landscape. Now, the model starts with 150 squirrels, 100 mountain lions, and 15 hunters. This model operates under the assumption that hunters want to kill mountain lions, who presumably try to eat the farm animals that represent the hunters' livelihoods. I made the mountain lion death rate dependent on the number of hunters, and the model changed such that the squirrel population exploded and the mountain lion population approached extinction every 20 years. I based this model on a real event, which took place and is still taking place in the Sierra Nevada. Squirrel populations there apparently reached record levels when farmers seeking to protect their land killed off the vast majority of the mountain lion population there. Now, hunters in the area kill squirrels for sport because they disrupted the food chain so irrevocably.
Clone of First SD Model: Predator Prey Model with Squirrels, Mountain Lions, and Hunters
An Initial System Dynamics Model for GFS in certain region(s) of Africa
Clone of GFS Raw Input Food Production
Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).
Clone of Z Clone of Sterman Model (2002)
This forecasting model can be used to predict global data center electricity needs, based on understanding usage growth. Please note that the corresponding problem description, model developments, and results are discussed in the following paper:
Koot, M., & Wijnhoven, F. (2021). Usage impact on data center electricity needs: A system dynamic forecasting model. Applied Energy, 291, 116798. DOI: https://doi.org/10.1016/j.apenergy.2021.116798.
Usage impact on global data center electricity needs
At first, I cloned the System Dynamics Model from the "Predator-Prey Interactions" tutorial. After I did this for populations of squirrels and mountain lions instead of moose and wolves, the model showed that the more squirrels mountain lions catch, the more the mountain lion population grows, and the squirrel population declines. The squirrel death rate, therefore, depends on the number of mountain lions and the mountain lion birth rate depends on the number of squirrels.
I complicated the model by adding 15 hunters to the landscape. Now, the model starts with 150 squirrels, 100 mountain lions, and 15 hunters. This model operates under the assumption that hunters want to kill mountain lions, who presumably try to eat the farm animals that represent the hunters' livelihoods. I made the mountain lion death rate dependent on the number of hunters, and the model changed such that the squirrel population exploded and the mountain lion population approached extinction every 20 years. I based this model on a real event, which took place and is still taking place in the Sierra Nevada. Squirrel populations there apparently reached record levels when farmers seeking to protect their land killed off the vast majority of the mountain lion population there. Now, hunters in the area kill squirrels for sport because they disrupted the food chain so irrevocably.
Clone of First SD Model: Predator Prey Model with Squirrels, Mountain Lions, and Hunters
Overview
This model which simulates the competition of Logging with Mountain Tourism in Derby, Tasmania. This main reason of this simulation is to find if logging will affect the mountain tourism and by any chance they can co-exist.
How the model works.
Both Timber harvesting and mountain tourism can bring the economic contribution to Tasmania. In the Logging industry, it helps increase the need of employment and at the same time logging generate the profit through selling those timbers. In the Mountain Tourism industry, it can get the revenue through couple of ways which include accommodation (approximately 3 days find in paper), Restaurant and parking fee. However, the low growth rate of the trees is not keeping up with the rate of logging, if the trees getting less in Derby mountain, it will affect the sights and the riding experience for tourists, which will affect the satisfaction and expectation as it depends on the sights and experience. The satisfaction and expectation will influence the number of visitors, if they satisfied, they can come again or tell others about the great experience, if not, more and more people will not come again.
Interesting insightsIt seems like logging has no significant negative effect to the mountain tourism, compare the forestry income with the tourism income, tourism income gradually higher than the forestry income at last, which means tourism is in a very important position, as long as the visitors are stable, tourism industry can provide greater economic contribution, stakeholders and governments can find the balance by maintain the status or better slightly reduce logging in order to make them co-exist.
Simulation of Derby Mountain biking versus logging
An Initial System Dynamics Model for GFS in certain region(s) of Africa
GFS Raw Input Food Production
Ciclo 1 extra repair consturction errors rework
Clone of Construction Rework SD
This is a model which explains the difference between Mountain bikes riding compared to logging in the Tasmanian forests.
Simulation of Derby Mountain bikes riding versus logging
Ciclo 1 extra repair consturction errors rework
Clone of Construction Rework SD
This is a model that simulates the competition between logging versus adventure tourism (mountain bike riding) in Derby Tasmania. The simulation is borrowed from the Easter island simulation
Simulation of Derby Mountain bikes versus logging
Internet of Things and Data Collection - Active and Passive Data.
Clone of Active and Passive Internet of Things
Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).
Clone of Sterman Model (2002)
This forecasting model can be used to predict global data center electricity needs, based on understanding usage growth. Please note that the corresponding problem description, model developments, and results are discussed in the following paper:
Koot, M., & Wijnhoven, F. (2021). Usage impact on data center electricity needs: A system dynamic forecasting model. Applied Energy, 291, 116798. DOI: https://doi.org/10.1016/j.apenergy.2021.116798.
Clone of Usage impact on global data center electricity needs
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
A System Dymanic Model of a Predator-Prey interactions using the real-life data. The predator on this model is Equatorial Spitting Cobra while the prey is Palawan Mountain Rat
Ph_PredatorPrey_AdelaVicente
Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).
Clone of Sterman Model (2002)
A model that shows how the digital advertising market is growing and how Google's share in this market, and subsequently their financial results, are influenced by investing in either three of the policy variables.
Clone of Google Adwords Model
Evolution of Covid-19 in Brazil:
A System Dynamics Approach
Villela, Paulo (2020)
paulo.villela@engenharia.ufjf.br
This model is based on Crokidakis, Nuno. (2020). Data analysis and modeling of the evolution of COVID-19 in Brazil. For more details see full paper here.
Clone of Evolution of Covid-19 in Brazil: A System Dynamics Approach
Foxes initial population is doubled
Clone of Investigation of Predator/Prey Modal 1 Scenario 2
A model situmalte the relationship between moutain bikes and logging industry in Derby, Tasmania, It explains more when the number of visitors increases or decreses.
How the model works
The left side shows when the number of travellers increase, the income from travellers rental of bike and stay of hotel increase simultaneously. However, there is a capacity for both parking lots and hotel venues, which means that the top ability of hospitality of Derby. The right side shows the logging industry of Derby and income from logging. It has a impact on how travellers would value Derby moutain.
Insights
As the number of travellers increase, it increases the total income of Derby, and in return, the local government will re-revest in Derby Moutain and will also maintain the forrestry logging industry.
Simulation of Derby Moutain Bikes Versus Biking
This forecasting model can be used to predict global data center electricity needs, based on understanding usage growth. Please note that the corresponding problem description, model developments, and results are discussed in the following paper:
Koot, M., & Wijnhoven, F. (2021). Usage impact on data center electricity needs: A system dynamic forecasting model. Applied Energy, 291, 116798. DOI: https://doi.org/10.1016/j.apenergy.2021.116798.
Clone of Clone of Usage impact on global data center electricity needs
