Insight diagram

Exploring the conditions of permanent coexistence, rather than gradual disappearance of disadvantaged competitors. ​Z506 p32-35 System Zoo 3 by Hartmut Bossel.

Clone of Competition for Resources
Insight diagram
Just a little model put together for training purposes
Population with slider input model
Insight diagram
Simulation of how tiger population and anti poaching efforts effect the black market value of tiger organs.
Clone of Tiger Population and Black Market Value
Insight diagram
  • Between 1999 and 2006 Koala population had dropped 26% in Queensland. 
  • By 2008 it was estimated there were around 2300 Koalas with more than a 50% population loss in less than 3 years. 
  • Main threats for Koala survival are a loss of habitat, vehicular trauma, dog attacks, urbanisation, disease and climate change.

    http://www.ehp.qld.gov.au/wildlife/koalas/research/pdf/koala-coast-report2010.pdf

Koala populations in SE Queensland
Insight diagram

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

First homework insight
Insight diagram
This is a basic population estimator. Default values approximate recent data for the Czech Republic (Czechia).
Population Projection of Czech Republic
Insight diagram
Shows the ecological impact of population.
Population Ecological Impact-Netherlands
Insight diagram
Population Dynamics
Insight diagram
Adapted from Hartmut Bossel's "System Zoo 3 Simulation Models, Economy, Society, Development."

​Population model where the population is summarized in four age groups (children, parents, older people, old people). Used as a base population model for dealing with issues such as employment, care for the elderly, pensions dynamics, etc.
Bossel: Z602 Population with four age groups
Insight diagram
Simulation of how tiger population and anti poaching efforts effect the black market value of tiger organs.
Clone of Tiger Population and Black Market Value
Insight diagram
Sakums Adazhiem
Insight diagram
World4 is a predictive model for world population. Population has grown hyper-exponentially in the last millenium, with the doubling time decreasing from 900 years  in 1000 CE to a minimum of ~35 years in 1963 CE. Technology is defined as that which decreases the death rate and/or increases the effective birth rate (i.e. by decreasing infant mortality). Technology grows exponentially, therefore population fits a hyper-exponential (exponent within an exponent). Models for the end of growth are explored using equations that express the ways humans are depleting Earth's biocapacity, the nature of resource depletion, and the relationship between natural resources and human carrying capacity. This simple model, containing just two closed systems, captures the subtle shifts in the population trajectory of the last 50 years. Specifically, hyperexponential growth has given way to subexponential growth. A peak is predicted for the time around 2028.  [Bystroff, C. (2021). Footprints to singularity: A global population model explains late 20th century slow-down and predicts peak within ten years. PloS one, 16(5), e0247214.]
Worl4.6 is a clone of World4.5 for exploring changes. WHat happens if there is a delay in the change of the growth rate? What happens if the fertility rate is a function of resource availability? What happens if climate change causes an increased death rate through catastrophes? What happens if policies are enacted to save wildlife?
World4.6
Insight diagram
Adapted from Hartmut Bossel's "System Zoo 3 Simulation Models, Economy, Society, Development."

​Population model where the population is summarized in four age groups (children, parents, older people, old people). Used as a base population model for dealing with issues such as employment, care for the elderly, pensions dynamics, etc.
Clone of Z602 Population with four age groups
Insight diagram

The Logistic Map is a polynomial mapping (equivalently, recurrence relation) of degree 2, often cited as an archetypal example of how complex, chaotic behaviour can arise from very simple non-linear dynamical equations. The map was popularized in a seminal 1976 paper by the biologist Robert May, in part as a discrete-time demographic model analogous to the logistic equation first created by Pierre François Verhulst

Mathematically, the logistic map is written

where:

 is a number between zero and one, and represents the ratio of existing population to the maximum possible population at year n, and hence x0 represents the initial ratio of population to max. population (at year 0)r is a positive number, and represents a combined rate for reproduction and starvation. To generate a bifurcation diagram, set 'r base' to 2 and 'r ramp' to 1
To demonstrate sensitivity to initial conditions, try two runs with 'r base' set to 3 and 'Initial X' of 0.5 and 0.501, then look at first ~20 time steps

Clone of The Logistic Map
Insight diagram
Shows the ecological impact of population.
Clone of Population Ecological Impact-Morocco
Insight diagram
WIP Ideas for a hybrid budding SD plus ABM depression dynamics model
Hybrid Depression Dynamics Model
Insight diagram
Simulation of how tiger population and anti poaching efforts effect the black market value of tiger organs.
Clone of Tiger Population and Black Market Value
Insight diagram

​Predator-prey models are the building masses of the bio-and environments as bio masses are become out of their asset masses. Species contend, advance and scatter essentially to look for assets to support their battle for their very presence. Contingent upon their particular settings of uses, they can take the types of asset resource-consumer, plant-herbivore, parasite-have, tumor cells- immune structure, vulnerable irresistible collaborations, and so on. They manage the general misfortune win connections and thus may have applications outside of biological systems. At the point when focused connections are painstakingly inspected, they are regularly in actuality a few types of predator-prey communication in simulation. 

 Looking at Lotka-Volterra Model:

The well known Italian mathematician Vito Volterra proposed a differential condition model to clarify the watched increment in predator fish in the Adriatic Sea during World War I. Simultaneously in the United States, the conditions contemplated by Volterra were determined freely by Alfred Lotka (1925) to portray a theoretical synthetic response wherein the concoction fixations waver. The Lotka-Volterra model is the least complex model of predator-prey communications. It depends on direct per capita development rates, which are composed as f=b−py and g=rx−d. 

A detailed explanation of the parameters:

  • The parameter b is the development rate of species x (the prey) without communication with species y (the predators). Prey numbers are reduced by these collaborations: The per capita development rate diminishes (here directly) with expanding y, conceivably getting to be negative. 
  • The parameter p estimates the effect of predation on x˙/x. 
  • The parameter d is the death rate of species y without connection with species x. 
  • The term rx means the net rate of development of the predator population in light of the size of the prey population.

Reference:

http://www.scholarpedia.org/article/Predator-prey_model

 

Lotka-Volterra Model: Prey-Predator Simulation
Insight diagram
Murali Krishnan_ Employment and Unemployment rate
Insight diagram
FORCED GROWTH GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION 
 BEWARE pushing increased growth blows the system!
(governments are trying to push growth on already unstable systems !)

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept and flawed strategy of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

Clone of FORCED GROWTH INTO TURBULENCE
Insight diagram
Acest model este adaptat după reprezentarea lui Harmut Bossel, în lucrarea  "System Zoo 3 Simulation Models, Economy, Society, Development."
Utilizarea modelului ne poate ajuta pentru a vizualiza evolutia populatiei pe grupe de varsta sau pentru a gestiona probleme cum ar fi ocuparea forței de muncă.
Clone of Clone of Z602 Population with four age groups
Insight diagram
OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

Clone of OVERSHOOT GROWTH INTO TURBULENCE
Insight diagram
Shows a projection of birth and death rate over time, creating the elements of the demographic transition. This one is for Tanzania.
Tanzania Population Projection 2045
Insight diagram
Simple BIDE model
Population - BIDE