A model which simulates the competition between logging versus adventure
tourism (mountain bike ridding) in Derby Tasmania.
How the model works:
Trees grow, and we cut them down because of the demand for Timber and
sell the logs. Mountain bikers and holiday visitors will come to the park and
this depends on experience and recommendations. Past experience and
recommendations depend on the Scenery, number of trees compared to the visitor
and Adventure number of trees and users. Park capacity limits the number
of users. To utilize highest park capacity, they need to promote to
the holiday visitor segment as well. Again, the visit depends on the scenery.
So, both mountain biking and forestry (logging) businesses need to contribute a
significant amount of revenue to CSR for faster regrowth of trees.
Interesting insights
It looks like a lot of logging doesn't stop people from mountain biking.
Faster replantation of the tree will balance out the impact created by
logging which will give the visitor a positive experience
and the number of visitors is both improved.
To keep the park's popularity in check, the price of wood needs to be high.
Also, it looks like mountain biking only needs a narrow path.
CSR contribution to nature can be a crucial factor.
Simulation model of Mountain biking versus logging MD Raihanul Islam, ID 591146
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.
Simple SD version of Wheaton 1999 stock flow representation of DiPasquale-Wheaton 4 Quadrant steady state model (4QM) from Eskanasi 2014 and Zhang 2018 theses
A sample model for class discussion modeling COVID-19 outbreaks and responses from government with the effect on the local economy. Govt policy is dependent on reported COVID-19 cases, which in turn depend on testing rates less those who recover
Assumptions
Govt policy reduces infection and economic growth in the same way.
Govt policy is trigger when reported COVID-19 case are 10 or less.
A greater number of COVID-19 cases has a negative effect on the economy. This is due to economic signalling that all is not well.
Interesting insights
Higher testing rates seem to trigger more rapid government intervention, which reduces infectious cases. The impact on the economy though of higher detected cases though is negative.
Clone of Burnie COVID-19 outbreak demo model version 2
Model showing the effect of bank lending of deposited money as a multiplier in the creation of new money. Multiplier effect is shown as related to the bank reserve requirement on deposited funds.
The model simulates the comparison between mountain biking industry and forestry/logging in Derby Tasmania.
How the model works
On the left-hand side, Derby Mountain biking, tourists visit the mountain according to reviews and recommendation of mountain scenery and entertainment activities. The number of people who hire bikes and who choose to dine on the mountain are limited by bike availability. Both bike hiring and biker dining contribute to tourist revenue in Derby. On the right-hand side, forest trees grow at certain rates, but are negatively affected by timber demand. Timber logging generate revenue, which depends on sale price and associated cost.
Interesting insights
Although forestry contributes more revenue in a certain time, it seems that Derby Mountain bike generate more tourist revenue from dining services and bike hiring in a long term.
Simulation of Derby Mountain biking versus logging
This is a Model of COVID-19 outbreak in Burnie, Tasmania which shows the government actions in response to the pandemic COVID-19 and its affects on the Economy. The government health policy changes depending on the reported cases, which is a dependent upon the testing rate.
Assumptions
Lockdown and travel ban were the main factor in government policy. It negatively impacts on the Economic growth as individuals are not going out which is directly affects the business around the world, in this insight 'Burnie'. This reduces the economic growth and the factors positively effecting economic growth such as Tourism.
Government policies has a negative impact on Exposer of individuals. Moreover, it also has a negative impact on chances of infection when exposed as well as other general infection rate.
Interesting Insight
There is a significant impact of test rating on COVID-19 outbreak. Higher rates increases the government involvement, which decreases cases as well as the total death.
In contrast, lower testing rates increase the death rate and cases.
Tourism which plays a avital role in Tasmanian Economy greatly affects the Economic Growth. The decline of Tourism in parts of Tasmania such as Burnie, would directly decrease the economy of Tasmania.
This model is designed to simulate the outbreak of Covid-19 in Burnie in Tasmania, death cases, the governmental responses and Burnie local economy.
More importantly, the impact of governmental responses to both Covid-19 infection and to local economy, the impact of death cases to local economy are illustrated.
The model is based on SIR (Susceptible, Infected and recovered) model.
Variables:
The simulation takes into account the following variables:
Variables related to Covid-19: (1): Infection rate. (2): Recovery rate. (3): Death rate. (4): Immunity loss rate.
Variables related to Governmental policies: (1): Vaccination mandate. (2): Travel restriction to Burnie. (3): Economic support. (4): Gathering restriction.
Variables related to economic growth: Economic growth rate.
Adjustable variables are listed in the part below, together with the adjusting range.
Assumptions:
(1): Governmental policies are aimed to control(reduce) Covid-19 infections and affect (both reduce and increase) economic growth accordingly.
(2) Governmental policy will only be applied when reported cases are 10 or more.
(3) The increasing cases will negatively influence Burnie economic growth.
Enlightening insights:
(1) Vaccination mandate, when changing from 80% to 100%, doesn't seem to affect the number of death cases.
(2) Governmental policies are effectively control the growing death cases and limit it to 195.
Burnie Tasmania Covid - 19 outbreak simulation Model by Yankang Huang 541 277
Overview This model is a working simulation of the competition between the mountain biking tourism industry versus the forestry logging within Derby Tasmania.
How the model works
The left side of the model highlights the mountain bike flow beginning with demand for the forest that leads to increased visitors using the forest of mountain biking. Accompanying variables effect the tourism income that flows from use of the bike trails. On the right side, the forest flow begins with tree growth then a demand for timber leading to the logging production. The sales from the logging then lead to the forestry income. The model works by identifying how the different variables interact with both mountain biking and logging. As illustrated there are variables that have a shared effect such as scenery and adventure and entertainment.
Variables The variables are essential in understanding what drives the flow within the model. For example mountain biking demand is dependent on positive word mouth which in turn is dependent on scenery. This is an important factor as logging has a negative impact on how the scenery changes as logging deteriorates the landscape and therefore effects positive word of mouth. By establishing variables and their relationships with each other, the model highlights exactly how mountain biking and forestry logging effect each other and the income it supports.
Interesting Insights The model suggests that though there is some impact from logging, tourism still prospers in spite of negative impacts to the scenery with tourism increasing substantially over forestry income. There is also a point at which the visitor population increases exponentially at which most other variables including adventure and entertainment also increase in result. The model suggests that it may be possible for logging and mountain biking to happen simultaneously without negatively impacting on the tourism income.
Clone of Simulation of Derby Mountain biking versus logging
The statement that there can be no economic activity
without energy and that fossil fuels are
finite contrasts with the fact that money is not finite and can be created by governments
via their central banks at zero marginal cost whenever needed.
An important fact about COAL, GAS and OIL (especially when produced via fracking) is that their net energy ratios are falling rapidly.
In other words the energy needed to extract a given quantity of fossil fuels is
constantly increasing. The falling ratio 'EROI' (Energy Return on Energy Invested ) provides
yet another warning that we can no longer rely on fossil fuels to power our
economies. In 1940 it took the energy of only one barrel of oil to extract 100. Today the energy of 1 barrel of oil will yield only 15. We cannot wait until the ratio falls to 1/1 before we invest seriously in alternative sources of energy, because by then industrial society as we know it doday will have ceased to exist. An EROI of 1:1 means that it takes the energy of one barrel of oil to extract one barrel of oil - oil production would simply stop!
A simple model simulates the conflict between adventure tourism (mountain biking) and logging in Derby, Tasmania. It demonstrates how these industries co-exist and in what circumstances would affect the interests of both parties.
How does the model work?
The demand for mountain biking came from visitors' enjoyment of nature and desire for scenery. Adventure is driven by the excitement of visitors with their experience and friends' recommendations.
The demand for timber leads to the amount of logging, and its price per log impacts forest revenue. It brought employment opportunities to the local residents in Derby Mountain. The excessive deforestation affects landscapes and scenery, so regrowth is essential.
Interesting Insights
The major rebate is reducing park spaces will degrade visitors' experience of enjoyment with nature. Still, at the same time, logging brings significant business benefits to the local residents. The environmental effect of being well-managed between mountain bikes and logging needs to be depth-explored and balanced.
Simulation of Derby Mountain Bike Riding Versus Logging
