Population | Insight Maker

Exercise 3

Jacinda Maassen

first attempt at an Insight model

simple population growth model

Kevin McCalib

Flows between acute hospital and aged care for older people. See IM-1012 for a simpler version

Aged Care and Hospital Flows

Geoff McDonnell

4

Shows the ecological impact of population.

Population Ecological Impact-Netherlands

Taylor Best

From NAP Toward Quality Measures for Population Health and the Leading Health Indicators Report with detailed Maternal Infant and Child Health Example Fig.3-5. Compare with WHO NCD Framework picture and IHI Whole system measures 2.0 (Added Nov 2016) See CLD conversion insight

Health Outcome Logic Model

Geoff McDonnell

3

Shows the ecological impact of population.

Population Ecological Impact-Bangladesh

Gregory Fulkerson

54

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)

FORCED GROWTH INTO TURBULENCE

Guy Lakeman

5

国連が公表している人口の将来推計とOECDが公表している各種経済統計を参考にして、2000年から2100年までの人口・経済見通しを作成するためのダイナミクスモデル。

①人口：年少(0-14歳)・再生産年齢人口(15-49歳)・後期生産年齢人口(50-64歳)・老年人口(65歳以上)にグループ分けし、出生数(再生産年齢人口×出生率)と死亡数(年代別死亡率×年代別人口の合計)を算出して総人口を推計

②経済：2000年のGDPをストックとして、コブ＝ダグラス型関数に基づき労働力人口(15歳以上人口×労働参加率)と資本ストック(総固定資本形成)および全要素生産性の成長率をフローとし、購買力平価レートの変化率も加味して将来のGDP(購買力平価換算)を算出

現状投影シナリオ：2000年から2100年までに制度や前提条件の極端な変更はなく、現状のトレンドが続くと想定される場合

World, Population, Economy, Projection Model 2000-2100

University Open Data

Dynamic simulation modelers are particularly interested in understanding and being able to distinguish between the behavior of stocks and flows that result from internal interactions and those that result from external forces acting on a system. For some time modelers have been particularly interested in internal interactions that result in stable oscillations in the absence of any external forces acting on a system. The model in this last scenario was independently developed by Alfred Lotka (1924) and Vito Volterra (1926). Lotka was interested in understanding internal dynamics that might explain oscillations in moth and butterfly populations and the parasitoids that attack them. Volterra was interested in explaining an increase in coastal populations of predatory fish and a decrease in their prey that was observed during World War I when human fishing pressures on the predator species declined. Both discovered that a relatively simple model is capable of producing the cyclical behaviors they observed. Since that time, several researchers have been able to reproduce the modeling dynamics in simple experimental systems consisting of only predators and prey. It is now generally recognized that the model world that Lotka and Volterra produced is too simple to explain the complexity of most and predator-prey dynamics in nature. And yet, the model significantly advanced our understanding of the critical role of feedback in predator-prey interactions and in feeding relationships that result in community dynamics.The Lotka–Volterra model makes a number of assumptions about the environment and evolution of the predator and prey populations:

1. The prey population finds ample food at all times.

2. The food supply of the predator population depends entirely on the size of the prey population.

3. The rate of change of population is proportional to its size.

4. During the process, the environment does not change in favour of one species and genetic adaptation is inconsequential.

5. Predators have limitless appetite.

As differential equations are used, the solution is deterministic and continuous. This, in turn, implies that the generations of both the predator and prey are continually overlapping.[23]

Prey

When multiplied out, the prey equation becomes

dx/dt = αx - βxy

The prey are assumed to have an unlimited food supply, and to reproduce exponentially unless subject to predation; this exponential growth is represented in the equation above by the term αx. The rate of predation upon the prey is assumed to be proportional to the rate at which the predators and the prey meet; this is represented above by βxy. If either x or y is zero then there can be no predation.

With these two terms the equation above can be interpreted as: the change in the prey's numbers is given by its own growth minus the rate at which it is preyed upon.

Predators

The predator equation becomes

dy/dt = -

In this equation, {\displaystyle \displaystyle \delta xy} represents the growth of the predator population. (Note the similarity to the predation rate; however, a different constant is used as the rate at which the predator population grows is not necessarily equal to the rate at which it consumes the prey). {\displaystyle \displaystyle \gamma y} represents the loss rate of the predators due to either natural death or emigration; it leads to an exponential decay in the absence of prey.

Hence the equation expresses the change in the predator population as growth fueled by the food supply, minus natural death.

Bio103 Predator-Prey Model ("Lotka'Volterra")

John Petersen

139

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

Michael Scallan

6

THE 2017 MODEL (BY GUY LAKEMAN) EMPHASIZES THE PEAK IN POLLUTION BEING CREATED BY OVERPOPULATION WITH THE CARRYING CAPACITY OF ARABLE LAND NOW BEING 1.5 TIMES OVER A SUSTAINABLE FUTURE (PASSED IN 1990) AND NOW INCREASING IN LOSS OF HUMAN SUSTAINABILITY DUE TO SEA RISE AND EXTREME GLOBAL WATER RELOCATION IN WEATHER CHANGES IN FLOODS AND DROUGHTS AND EXTENDED TROPICAL AND HORSE LATTITUDE CYCLONE ACTIVITY AROUND HADLEY CELLS

THE MODEL IS ZONE SPECIFIC AS GLOBAL WEATHER IS NOT HOMOGENEOUS BUT A COLLECTION OF HEAT BUMBPS DEPENDENT ON POPULATION SIZE OF URBAN HEAT ISLANDS AND MASSED CONURBATIONS AND AGGLOMERATIONS

The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

THIS MODEL BY GUY LAKEMAN, FROM METRICS OBTAINED USING A MORE COMPREHENSIVE VENSIM SOFTWARE MODEL, SHOWS CURRENT CONDITIONS CREATED BY THE LATEST WEATHER EXTREMES AND LOSS OF ARABLE LAND BY THE ALBEDO EFECT MELTING THE POLAR CAPS TOGETHER WITH NORTHERN JETSTREAM SHIFT NORTHWARDS, AND A NECESSITY TO ACT BEFORE THERE IS HUGE SUFFERING.

BY SETTING THE NEW ECOLOGICAL POLICIES TO 2015 WE CAN SEE THAT SOME POPULATIONS CAN BE SAVED BUT CITIES WILL SUFFER MOST.

CURRENT MARKET SATURATION PLATEAU OF SOLID PRODUCTS AND BEHAVIORAL SINK FACTORS ARE ALSO ADDED

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a low birth-rate, environmentally focused policy.

2017 Weather & Climate Extreme Loss of Arable Land and Ocean Fertility by Guy Lakeman - The World3+ Model: Forecaster

Guy Lakeman

31

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

Clone of Bio 190: BIDE Model With Carrying Capacity

Faqih Zulfikar

This model aims to analyze how conservation from 2013 to 2017 needs improving in order to meet the needs to repopulate the Florida panther based on Acreage of conservation. Human population and housing development challenge conservation efforts, this model produces scenarios that test policy efforts in repopulate the Florida Panther. Our goal is to conserve 16 million acres for a habitat with 500 panthers.

SOS 212: Final Project