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CAUSAL LOOP DIAGRAM FOR THE ARTICLE : MANILA'S WHITE SAND BEACH, A THREAT TO MARINE LIFE

Paul Gabriel Fajardo

Model based on chapter 10 (opportunity cost) of the book Modeling Dynamic Economic Systems

Opportunity cost

AR

310

Farming_small vs large

Paul

8 months ago

Clone of Pesticide Use in Central America for Lab work

This model is an attempt to simulate what is commonly referred to as the “pesticide treadmill” in agriculture and how it played out in the cotton industry in Central America after the Second World War until around the 1990s.

The cotton industry expanded dramatically in Central America after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This expansion was accompanied by a huge increase in industrial pesticide application which would eventually become the downfall of the industry.

The primary pest for cotton production, bol weevil, became increasingly resistant to chemical pesticides as they were applied each year. The application of pesticides also caused new pests to appear, such as leafworms, cotton aphids and whitefly, which in turn further fuelled increased application of pesticides.

The treadmill resulted in massive increases in pesticide applications: in the early years they were only applied a few times per season, but this application rose to up to 40 applications per season by the 1970s; accounting for over 50% of the costs of production in some regions.

The skyrocketing costs associated with increasing pesticide use were one of the key factors that led to the dramatic decline of the cotton industry in Central America: decreasing from its peak in the 1970s to less than 100,000 hectares in the 1990s. “In its wake, economic ruin and environmental devastation were left” as once thriving towns became ghost towns, and once fertile soils were wasted, eroded and abandoned (Lappe, 1998).

Sources: Douglas L. Murray (1994), Cultivating Crisis: The Human Cost of Pesticides in Latin America, pp35-41; Francis Moore Lappe et al (1998), World Hunger: 12 Myths, 2nd Edition, pp54-55.

Clone of REM 221 - Causal Loop diagramming

HOANG MINH NGUYEN

climate change

jieyi zhang

Current and proposed Structure of CCP and related Models expanding on the details provided in the Project Completion plan IM-101760

Structure of the CCP Models

Geoff McDonnell

Rating Matrix of S&P

Rating Matrix

Antonio Espana

This model is comparing healthy and sick residents in Burnie, Tasmania after the Covid-19 Outbreak in 2020. It will also show how the Burnie economy is effected by the disease, how the Government Health Policies are implemented and how they are enforced.

This model is based on the SIR, Susceptible, Infection, Recovery (or Removed) These are the three possible states related to the members of the Burnie population when a contagious decease spreads.

The Government/Government Health Policy, played a big part in the successful decrease in Covid-19 infections. The Government enforced the following.
- No travel (interstate or international)
- Isolation within the residents homes
- Social distancing by 1.5m
- Quarantine
- Non essential companies to be temporarily closed
- Limitations on public gatherings
- And limits on time and kilometers aloud to travel from ones home within a local community

This resulted in lower reported infection rates of Covid-19 and higher recovery rates.

In my opinion: When the first case was reported the Government could have been even faster to enforce these rules to decrease the fatality rates further for the Burnie, population.

Assumption: Government policies were only triggered when 10 cases were recorded.
Also, more cases that had been recorded effected the economic growth during this time.

Interesting Findings: In the simulation it shows as the death rates increases towards the end of the week, the rate of testing goes down. You would think that the government would have enforced a higher testing rate over the duration of this time to decrease the number of infections, exposed which would increase the recovery rates faster and more efficiently.

Figures have been determined by the population of Burnie being 19,380 at the time of assignment.

Complex Systems How Burnie Tasmania dealt with Covid-19 Outbreak BMA708

Kate Elizabeth Craddock

Do you like travelling? Find out how we can help make it more sustainable!

Images used:

Suitcase:

http://vignette2.wikia.nocookie.net/animaljam/images/a/ab/Travel-suitcase_(1).png/revision/latest?cb=20140907211051

Fiji: http://cdn.newsapi.com.au/image/v1/91c1263a2a357b3673af8ff8362c0c8d?width=1024

Hotels:

https://taj.tajhotels.com/content/dam/luxury/hotels/taj-palace-delhi/images/master2/16x7/38849817-H1-Exterior_1-16x7.jpg

Poverty:

http://www.montana.edu/extensionecon/images/povertywordcloud.jpg

Leverage Point

https://image.slidesharecdn.com/genderinintegratedsystemsresearchbycynthiamcdougallseniorscientistgenderequitythemeleader-150311041710-conversion-gate01/95/gender-in-integrated-systems-research-by-cynthia-mcdougall-senior-scientist-gender-equity-theme-leader-25-638.jpg?cb=1426065542

Sources:

https://www.statista.com/statistics/270422/forecast-for-2020-arrivals-of-foreign-tourists-worldwide/

http://www.sustainabletourism.net

Week 10 Lecture- Dr. David Tindall Lecture pdf

https://www.adb.org/countries/fiji/poverty

Economic Impact of Tourism on Fiji's Economy: Empirical Evidence from Computable General Equilibrium Model by Paresh Kumar Narayan

https://www.wttc.org/-/media/files/reports/economic%20impact%20research/countries%202015/fiji2015.pdf

http://sustainabletravel.org/our-work/regional-alliances/pacific/hotel-sustainable-resources-pacific/

http://reusegraywater.com/about-us/

Rubin, K.E., The Valuation of Hotels and Motels for Assessment Purposes, 1984

https://en.wikipedia.org/wiki/Leverage-point_modeling

Meadows, D.H., & Wright, D. (2009). Thinking in systems: a primer, London: Earthscan.

Sustainable Tourism (Final)

Claire Huang

DPSIR Framework to Analyze EcoPeace Middle East's Good Water Neighbours Strategy

Alistair Chean

Barangay IRAWAN Systems Model

Biophysical, Socio-cultural & Economic Data of Bgy. IRAWAN

Sitti Mashita J. Kilis

ECONOMIC INEQUALITY IN SOUTH DAKOTA

Jacinda Maassen

Michael Marmot's Eur J Epidemiol Essay 2017 See also IM-62760 Social determinants of health from Michael Marmot's ABC 2016 Boyer Lectures on Social Justice and the Health Gap

Social Justice, Epidemiology and Health Inequalities

Geoff McDonnell

economic inequality

Vo Thi Hoang Anh

A restatement of the ISDC Nijmegen 2006 paper Exploring the Political and Economic Dimensions of Health Policy This may benefit from simplification and using cultural theory. See IM-57161 for extension

Political Economy of Health Services

Geoff McDonnell

5

This page provides a structural analysis of POTUS Candidate Jim Gilmore's economic policy based on the information at: http://www.gilmoreforamerica.com/jims-growth-code/ The method used is Integrative Propositional Analysis (IPA) available: http://scipolicy.org/uploads/3/4/6/9/3469675/wallis_white_paper_-_the_ipa_answer_2014.12.11.pdf

DRAFT IPA of Jim Gilmore Economic Policy

Steve Wallis

My InsightPublic Opinion Toward Immigration Reform: The Role of Economic Motivations

Luca Makarushka-Napp

Economic forecast model

Олександра Тризна

This high-level simulation model presented by Jay Forrester in his book World Dynamics, simulates socio-economic-environmental world system. The world Model was created in a time where pollution and other negative effects of industrialization and economic growth started to become recognized in 1970. For this exam purpose, we have rebuilt the model to do some experiments and analyze the results.

World Model2