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.
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).
O modelo mostra a
conexão e o conflito da indústria entre o turismo florestal e o turismo de
montanha em Derby, Tasmânia. O objetivo desta simulação é descobrir o ponto de
equilíbrio para a coexistência.
Como funciona o
modelo?
Ambas as
indústrias podem fornecer contribuições económicas para a Tasmânia. Em primeiro
lugar, a venda de madeira através da exploração madeireira geraria renda. Além
disso, os gastos dos ciclistas de montanha gerariam renda. No entanto, a baixa
taxa de regeneração das árvores não pode encobrir a exploração madeireira, o
que influencia as belas vistas e as experiências dos ciclistas. Embora a
satisfação e a expectativa dependam das opiniões e da experiência, a demanda
pelo mountain bike também seria influenciada pelas visitas repetidas e pelo
boca a boca.
Informações
interessantes
Embora a
silvicultura possa fornecer uma grande contribuição económica para a Tasmânia,
o excesso de exploração madeireira vai contra a estrutura ESG, além de criar
conflito com o turismo de montanha. Desde que o número de visitas de cavaleiros
seja estável, o turismo pode sempre proporcionar uma maior contribuição
económica em comparação com a silvicultura. Portanto, o governo deveria
considerar o ponto de equilíbrio entre as duas indústrias.
This model (starting with a clone of a previous project on squirrels, mountain lions, and hunters) is a simplified version using only rabbits and snakes.
By modifying the birth and death rates, the variations in population change dramatically. Interestingly, in this iteration, the populations reach dismal lows, but always pick up later.
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.
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.
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.
The model shows the industry connection and conflict between Forestry and Mountain Tourism in Derby, Tasmania. The objective of this simulation is to find out the balance point for co-exist.
How Does the Model Work?
Both industries can provide economic contribution to Tasmania. Firstly, selling timbers through logging would generate income. Also, spendings from mountain bike riders would generate incomes. However, low tree regrowth rate can not cover up logging, which influences the beautiful vistas and riders' experiences. While satisfaction and expectation depend on vistas and experience, the demand of mountain biking would be influenced through repeat visits and world of mouth as well.
Interesting Insights
Although forestry can provide a great amount of economic contribution to Tasmania, over logging goes against ESG framework as well as creating conflict with mountain tourism. As long as the number of rider visits is stable, tourism can always provide a greater economic contribution compared to forestry. Therefore, the government should consider the balance point between two industries.
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.
Based on a dialogue on the System Dynamics mailing list regarding the current level of acceptance of System Dynamics after it has been promoted for over 70 years I dredged up the following set of influences as a thought exercise. This is an example of a Drifting Goals Archetype.
A Conveyor is essentially an infinite order exponential delay. This insight illustrates how increasing the order of an exponential delay begins to approximate a conveyor. The 10th order delay very closely aligns to the Delay 10 Conveyor.
