Presentation - Weather-Chaos Group - University of Maryland

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

The Rich-and-Poor model for Human and Nature

Dynamics

Safa Motesharrei Jorge Rivas Eugenia Kalnay

**University** **of** **Maryland**

Feb 6, 2012

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Outline

Motivation

The Predator-Prey Model

Outline **of** this **Presentation**

Introduction

Outline

Motivation

The Predator-Prey Model

HANDY: Human And Nature DYnamics

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Scenarios

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Summary and Conclusions

Summary

Conclusions

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Outline

Motivation

The Predator-Prey Model

Motivation

◮ Earth System Models have been developed since 1960s

◮ They started with just a model for the atmosphere

◮ New components like ocean, land, sea-ice, carbon cycle,

vegetation, etc. were added over the past few decades

◮ However, the Human System is still a missing component

◮ Our goal: build a Human-Earth System model including all

major feedbacks, such as climate change ⇔ population growth

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Outline

Motivation

The Predator-Prey Model

The Predator-Prey Model

◮ A major inspirations for HANDY

◮ AKA Lotka-Volterra

◮ Derived independently by two mathematicians, Alfred Lotka

and Vitto Volterra, in the early 20th century

◮ Describes the dynamics **of** competition between two species,

say, wolves and rabbits

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Outline

Motivation

The Predator-Prey Model

Predator-Prey System **of** Equations

◮ The governing system **of** equations is

⎧

⎨

⎩

ẋ = (ay)x − bx

ẏ = cy − (dx)y

(1)

◮ x: predator (wolf) population

y: prey (rabbit) population

◮ a: determines the predator’s birth rate

b: the predator’s death rate

◮ c: the prey’s birth rate

d: determines the predation rate

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Outline

Motivation

The Predator-Prey Model

Equilibrium Points

The predator and prey populations show periodic, out **of** phase

variations about the equilibrium values:

⎧

⎨ x e = c/d

⎩

y e = b/a

(2)

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Outline

Motivation

The Predator-Prey Model

Typical Solution

200 wolves

800 rabbits

Predator and Prey Populations

150 wolves

600 rabbits

100 wolves

400 rabbits

0 100 200 300 400 500 600 700 800 900 1000

Time (year)

x Predator : Current

y Prey : Current

wolves

rabbits

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

An Overview **of** HANDY

◮ A minimalist coupled model

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

An Overview **of** HANDY

◮ A minimalist coupled model

◮ Explores the essential dynamics **of** interaction between

population and natural resources

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

An Overview **of** HANDY

◮ A minimalist coupled model

◮ Explores the essential dynamics **of** interaction between

population and natural resources

◮ Portrays how different factors like inequality or high depletion

rate can independently lead to a “Collapse”

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

An Overview **of** HANDY

◮ A minimalist coupled model

◮ Explores the essential dynamics **of** interaction between

population and natural resources

◮ Portrays how different factors like inequality or high depletion

rate can independently lead to a “Collapse”

◮ Introduces “Carrying Capacity” as a measure for early

detection **of** a collapse

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

An Overview **of** HANDY

◮ A minimalist coupled model

◮ Explores the essential dynamics **of** interaction between

population and natural resources

◮ Portrays how different factors like inequality or high depletion

rate can independently lead to a “Collapse”

◮ Introduces “Carrying Capacity” as a measure for early

detection **of** a collapse

◮ Offers a practical definition for carrying capacity

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

An Overview **of** HANDY

◮ A minimalist coupled model

◮ Explores the essential dynamics **of** interaction between

population and natural resources

◮ Portrays how different factors like inequality or high depletion

rate can independently lead to a “Collapse”

◮ Introduces “Carrying Capacity” as a measure for early

detection **of** a collapse

◮ Offers a practical definition for carrying capacity

◮ Shows in order to reach an equilibrium, high unemployment is

inevitable when productivity per worker is high

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

HANDY Equations

⎧

ẋ P = β P x P − α P x P

⎪⎨ ẋ R = β R x R − α R x R

(3)

ẏ = γy(λ − y) − δx P y

⎪⎩

ẇ = δx P y − C R − C P

◮ x R : Rich — Non-working population (AKA Free-Riders)

◮ x P : Poor — Labor force in charge **of** production

◮ y: Nature — An aggregate **of** physical and natural resources

◮ w: Wealth — Controlled by the Rich

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Parameters and Functions in HANDY

◮ β R and β P : Birth rates (constant) for the rich and the poor

◮ δ: Productivity per capita

AKA the “Production” or “Depletion” factor

◮ λ: Nature’s Capacity

◮ γ: Nature’s Regeneration rate

◮ κ: “Inequality” factor

◮ C R and C P : Consumption rates for the Rich and the Poor

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Consumption Rates in HANDY

◮ Consumption rates are given by

⎧

(

C P = min

⎪⎨

⎪⎩

C R = min

1,

(

1,

)

w

sx P

w th

)

(4)

w

κsx R

w th

◮ s: Consumption rate per capita, AKA the “Subsistence

Salary”

◮ w th : a “Threshold” value for wealth below which famine

starts, determined by the Rich

w th = ρx P + κρx R . (5)

◮ ρ: minimum required consumption per capita

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Death Rates in HANDY

◮ α R and α P : Death rates for the Rich and the Poor

⎧

⎪⎨

⎪⎩

(

α P = α m + max 0, 1 − C )

P

(α M − α m )

sx

( P

α R = α m + max 0, 1 − C )

R

(α M − α m )

sx R

◮ α m : Minimum (Normal) death rate

◮ α M : Maximum death rate, prevails when w = 0

◮ α R and α P can be equivalently expressed in terms **of**

w

w th

(6)

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Equilibrium Values when x R = 0

◮ Assume β R = β P = β

◮ β satisfies α m ≤ β ≤ α M

◮ Define dimensionless 0 ≤ η α M − β

α M − α m

≤ 1

◮ Equilibrium values are then given by

⎧

⎪⎨

⎪⎩

x P,e = γ ( s )

λ − η

δ δ

y e = η s (7)

δ

w e = ηρx P,e

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Carrying Capacity

◮ Define χ, the Carrying Capacity for population, to be equal to

x P,e

χ γ δ

(λ − s δ η )

(8)

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Carrying Capacity

◮ Define χ, the Carrying Capacity for population, to be equal to

x P,e

χ γ δ

(λ − s δ η )

(8)

◮ χ is maximized when the Nature’s regeneration rate is

maximal

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Carrying Capacity

◮ Define χ, the Carrying Capacity for population, to be equal to

x P,e

χ γ δ

(λ − s δ η )

(8)

◮ χ is maximized when the Nature’s regeneration rate is

maximal

◮ From y e = λ 2

, we can find the optimal δ

δ ∗ 2ηs

λ

(9)

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Carrying Capacity

◮ Define χ, the Carrying Capacity for population, to be equal to

x P,e

χ γ δ

(λ − s δ η )

(8)

◮ χ is maximized when the Nature’s regeneration rate is

maximal

◮ From y e = λ 2

, we can find the optimal δ

δ ∗ 2ηs

(9)

λ

◮ This gives us the Optimal Carrying Capacity

χ M = γ λ

δ ∗ 2 = γ ( ) λ 2

(10)

ηs 2

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Equilibrium when x R ≥ 0 and κ = 1

◮ Fix κ ≡ 1 to reach an equilibrium state for which x R ≥ 0

◮ Need a dimensionless free parameter ϕ that fixes the ratio **of**

the Rich to the Poor

ϕ = x R

x P

(11)

◮ Equilibrium values **of** the system can then be expressed as

⎧

⎪⎨

⎪⎩

x P,e = γ δ

x R,e = ϕx P,e

( s λ − η (1 + ϕ))

δ

y e = η s (1 + ϕ)

δ

(12)

w e = ηρ(1 + ϕ)x P,e

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

An Overview **of** HANDY

HANDY Equations and Parameters

Equilibrium Values and the Carrying Capacity

Maximum Equilibrium Population when x R ≥ 0 and κ = 1

◮ Total (equilibrium) population x e = x P,e + x R,e can be

maximized by an appropriate choice **of** δ

δ ∗ = 2ηs (1 + ϕ) (13)

λ

◮ Maximum total population is then given by

x e,M = (1 + ϕ) γ λ

δ ∗ 2 = γ ( ) λ 2

(14)

ηs 2

◮ From (14), maximum total population is independent **of** ϕ and

conforms to the optimal carrying capacity given above by (10)

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

S**of**t Landing to the Optimal Equilibrium

80,000 ppl

100 eco$

400 eco$

Population, Nature, and Wealth

40,000 ppl

50 eco$

200 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Oscillatory Approach to Equilibrium

100,000 ppl

100 eco$

2,000 eco$

Population, Nature, and Wealth

50,000 ppl

50 eco$

1,000 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Cycles **of** Prosperity and Collapse

100,000 ppl

100 eco$

2,000 eco$

Population, Nature, and Wealth

50,000 ppl

50 eco$

1,000 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Full Collapse

100,000 ppl

100 eco$

2,000 eco$

Population, Nature, and Wealth

50,000 ppl

50 eco$

1,000 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

S**of**t Landing to Equilibrium

80,000 ppl

100 eco$

400 eco$

Population, Nature, and Wealth

40,000 ppl

50 eco$

200 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Oscillatory Approach to Equilibrium

80,000 ppl

100 eco$

2,000 eco$

Population, Nature, and Wealth

40,000 ppl

50 eco$

1,000 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Cycles **of** Prosperity and Collapse

80,000 ppl

100 eco$

2,000 eco$

Population, Nature, and Wealth

40,000 ppl

50 eco$

1,000 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Full Collapse

80,000 ppl

100 eco$

2,000 eco$

Population, Nature, and Wealth

40,000 ppl

50 eco$

1,000 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Preventing a Full Collapse by Increasing Unemployment

80,000 ppl

100 eco$

400 eco$

Population, Nature, and Wealth

40,000 ppl

50 eco$

200 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Population Collapse After an Established Equilibrium

600,000 ppl

100 eco$

400 eco$

Population, Nature, and Wealth

300,000 ppl

50 eco$

200 eco$

0 ppl

0 eco$

0 eco$

1750 1900 2050 2200 2350 2500 2650

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Cycles **of** Prosperity and Collapse

6,000 ppl

200 eco$

600 eco$

Population, Nature, and Wealth

3,000 ppl

100 eco$

300 eco$

0 ppl

0 eco$

0 eco$

1750 1950 2150 2350 2550 2750 2950 3150 3350 3550 3750

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Equitable Society: Rich = 0

κ = 1 (Rich ≥ 0)

Rich ≥ 0 and κ ≫ 1

Full Collapse

80,000 ppl

100 eco$

4,000 eco$

Population, Nature, and Wealth

40,000 ppl

50 eco$

2,000 eco$

0 ppl

0 eco$

0 eco$

1750 1825 1900 1975 2050 2125 2200

Time (Year)

"kappa * x R equivalent rich population" : Current

x P Poor Population : Current

chi population carrying capacity : Current

chi M optimal population carrying capacity : Current

y Nature : Current

w Accumulated Wealth : Current

ppl

ppl

ppl

ppl

eco$

eco$

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Summary

◮ Our final goal is to couple population endogenously with an

ESM

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Summary

◮ Our final goal is to couple population endogenously with an

ESM

◮ HANDY is a minimal model that was built to run

“thought-experiments” for a future Integrated Assessment

Human-Earth System model

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Summary

◮ Our final goal is to couple population endogenously with an

ESM

◮ HANDY is a minimal model that was built to run

“thought-experiments” for a future Integrated Assessment

Human-Earth System model

◮ The Predator-Prey model served as an inspiration for HANDY

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Summary

◮ Our final goal is to couple population endogenously with an

ESM

◮ HANDY is a minimal model that was built to run

“thought-experiments” for a future Integrated Assessment

Human-Earth System model

◮ The Predator-Prey model served as an inspiration for HANDY

◮ Equilibrium can be reached (S**of**t Landing or Oscillatory

Approach) if everyone works (Rich = 0)

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Summary

◮ Our final goal is to couple population endogenously with an

ESM

◮ HANDY is a minimal model that was built to run

“thought-experiments” for a future Integrated Assessment

Human-Earth System model

◮ The Predator-Prey model served as an inspiration for HANDY

◮ Equilibrium can be reached (S**of**t Landing or Oscillatory

Approach) if everyone works (Rich = 0)

◮ Collapse can happen if depletion per capita is too high even

for the case Rich = 0

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Summary

◮ Our final goal is to couple population endogenously with an

ESM

◮ HANDY is a minimal model that was built to run

“thought-experiments” for a future Integrated Assessment

Human-Earth System model

◮ The Predator-Prey model served as an inspiration for HANDY

◮ Equilibrium can be reached (S**of**t Landing or Oscillatory

Approach) if everyone works (Rich = 0)

◮ Collapse can happen if depletion per capita is too high even

for the case Rich = 0

◮ Equilibrium can also be reached when Rich ≥ 0 but requires

κ = 1

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Conclusions

◮ Simple models provide a great intuition and can teach us

invaluable points

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Conclusions

◮ Simple models provide a great intuition and can teach us

invaluable points

◮ It is crucial to have a measure that can give us an early

warning for a collapse

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Conclusions

◮ Simple models provide a great intuition and can teach us

invaluable points

◮ It is crucial to have a measure that can give us an early

warning for a collapse

◮ Carrying Capacity tells us when overshoot happens

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Conclusions

◮ Simple models provide a great intuition and can teach us

invaluable points

◮ It is crucial to have a measure that can give us an early

warning for a collapse

◮ Carrying Capacity tells us when overshoot happens

◮ Carrying Capacity can be practically defined by noticing the

decline in Wealth (Bubble Burst)

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY

Introduction

HANDY: Human And Nature DYnamics

Scenarios

Summary and Conclusions

Summary

Conclusions

Conclusions

◮ Simple models provide a great intuition and can teach us

invaluable points

◮ It is crucial to have a measure that can give us an early

warning for a collapse

◮ Carrying Capacity tells us when overshoot happens

◮ Carrying Capacity can be practically defined by noticing the

decline in Wealth (Bubble Burst)

◮ High unemployment and high production per capita are

directly related

Safa Motesharrei, Jorge Rivas, Eugenia Kalnay

HANDY