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The domino effect: A network analysis of regime shifts drivers and causal pathways Juan Carlos Rocha, R. Oonsie Biggs & Garry Peterson Stockholm Resilience Center Tuesday, March 15, 2011

The domino effect: A network analysis of regime shifts drivers and causal pathways

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We present an exploratory analysis of the causal interactions among global change drivers of regime shifts, based on information collated in the Regime Shifts Database*. We reviewed the documented evidence of over 20 policy-relevant regime shifts in ecosystems. Information on the dynamics of each regime shift was synthesized using causal-loop diagrams, a generic structure map of the system. We then identified the main drivers of change, the key impacts on ecosystem services, as well as possible cross-scale interactions among regime shifts drivers using network analysis.

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Page 1: The domino effect: A network analysis of regime shifts drivers and causal pathways

The domino effect: A network analysis of regime shifts

drivers and causal pathways

Juan Carlos Rocha, R. Oonsie Biggs & Garry PetersonStockholm Resilience Center

Tuesday, March 15, 2011

Page 2: The domino effect: A network analysis of regime shifts drivers and causal pathways

Interaction of regime shifts drivers?

Anthropocene and the likelihood of regime shifts

1. What is more important? What we should be worry about?

2. What are the possible connections among RS?

3. What are the impacts of climate change in RS?

4. Where are they more likely to happen?

Rockström et al., 2009

Tuesday, March 15, 2011

Page 3: The domino effect: A network analysis of regime shifts drivers and causal pathways

Regime shifts that matter to people

Regime shift: Large, abrupt, persistent change in the structure and function of a system.

Policy relevant = Substantial change in Ecosystem Services

Tuesday, March 15, 2011

Page 4: The domino effect: A network analysis of regime shifts drivers and causal pathways

Global change drivers

“...any natural or human-induced factor that directly or indirectly causes a change in an ecosystem. A direct driver unequivocally influences ecosystem processes. An indirect driver operates more diffusely, by altering one or more direct drivers” (MEA 2005)

Our drivers are the result of literature review for each regime shift.

Tuesday, March 15, 2011

Page 5: The domino effect: A network analysis of regime shifts drivers and causal pathways

The objective of this paper is to perform an exploratory analysis of the causal interactions among global change drivers of regime shifts.

1. What are the major global change drivers of regime shifts?

2. What are the impacts of regime shifts on global change drivers?

3. What are the possible cascading effects of regime shifts and its drivers?

RS1 RS2 RS3

D1

D1 D2 D3

RS1

RS1 RS2D1 ...

Regime shifts

Drivers

Cascading effects

Q2Q1

Q3

Tuesday, March 15, 2011

Page 6: The domino effect: A network analysis of regime shifts drivers and causal pathways

Regime shift database

Tuesday, March 15, 2011

Page 7: The domino effect: A network analysis of regime shifts drivers and causal pathways

Regime shift database

Tuesday, March 15, 2011

Page 8: The domino effect: A network analysis of regime shifts drivers and causal pathways

Description of the alternative regimes and reinforcing feedbacks

The drivers that precipitate the regime shift

Impacts on ecosystem services and human well-being

Management options

www.regimeshifts.org

Regime shift database

Tuesday, March 15, 2011

Page 9: The domino effect: A network analysis of regime shifts drivers and causal pathways

Current data: 19 Regime Shifts descriptions + CLD.

N Policy relevant Regime Shifts Mechanism Reversibility

1 Bivalves collapse Established H

2 Coral transitions Established H

3 Coral bleaching Established H

4 Desertification Contested H, I

5 Encroachment Established H

6 Eutrophication Established H, I, R

7 Fisheries collapse Contested U

8 Marine foodwebs collapse Contested U

9 Forest - Savanna Established I

10 Hypoxia Established H, R

11 Kelp transitions Established H, R

12 Soil salinization Established H, I

13 Steppe - Tundra Established I

14 Tundra - Forest Established I

15 Monsoon circulation Established I

16 Thermohaline circulation collapse Established I

17 Greenland ice sheet collapse Established I

18 Arctic salt marshes Established I

19 Arctic ice collapse Established I

Reversibility: H = Hysteretic; I = Irreversible; R= Reversible; U = Unknown

Causal-loop diagrams is a technique to map out the

feedback structure of a system (Sterman 2000)

Tuesday, March 15, 2011

Page 10: The domino effect: A network analysis of regime shifts drivers and causal pathways

Centrality Definition

Degree The number edges a vertex is connected to (Newman 2010): In-degree and Out-degree

Betweenness The extent to which a vertex lies on paths between other vertices (Newman 2010)

Eigenvector A vertex is important if it is directly or indirectly connected to other vertices that are in turn important (Allesina and Pascual 2009), like Google PageRank

Methods: Network Analysis

Degree centrality

Tuesday, March 15, 2011

Page 11: The domino effect: A network analysis of regime shifts drivers and causal pathways

Centrality Definition

Degree The number edges a vertex is connected to (Newman 2010): In-degree and Out-degree

Betweenness The extent to which a vertex lies on paths between other vertices (Newman 2010)

Eigenvector A vertex is important if it is directly or indirectly connected to other vertices that are in turn important (Allesina and Pascual 2009), like Google PageRank

Methods: Network Analysis

Betweenness centrality

Tuesday, March 15, 2011

Page 12: The domino effect: A network analysis of regime shifts drivers and causal pathways

Centrality Definition

Degree The number edges a vertex is connected to (Newman 2010): In-degree and Out-degree

Betweenness The extent to which a vertex lies on paths between other vertices (Newman 2010)

Eigenvector A vertex is important if it is directly or indirectly connected to other vertices that are in turn important (Allesina and Pascual 2009), like Google PageRank

Methods: Network Analysis

Eigenvector centrality

Tuesday, March 15, 2011

Page 13: The domino effect: A network analysis of regime shifts drivers and causal pathways

1. What are the major global change drivers of regime shifts?

Arctic Ice−Sheet CollapseArctic Salt−Marshes

Tundra − ForestSteppe − Tundra

Thermohaline CirculationGreenland Ice−sheet Collapse

Marine FoodwebsMonsoon

DesertificationForest − Savanna

Bush EncroachmentSoil Salinization

Kelps TransitionsCoral Bleaching

Bivalves CollapseHypoxia

Fisheries CollapseLake Euthrophication

Coral Transitions

Drivers per Regime Shift

0 5 10 15 20

Atmospheric CO2

Floods

Nutrients input

Turbidity

Fishing

Urban growth

Erosion

Deforestation

Agriculture

Human population

Demand

Global warming

Top drivers

0 2 4 6 8 10 12

RS1 RS2 RS3

D1

Tuesday, March 15, 2011

Page 14: The domino effect: A network analysis of regime shifts drivers and causal pathways

1. What are the major global change drivers of regime shifts? RS1 RS2 RS3

D1

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 19 22

Indegree

Num

ber o

f ver

tex

010

2030

4050

60

1 2 3 4 5 6 7 8 9 11 12 14 15 17

Outdegree

Num

ber o

f ver

tex

020

4060

80

Incoming linksOutgoing links

Num

ber

of v

erte

x

Num

ber

of v

erte

x

Few nodes have a lot of links!Tuesday, March 15, 2011

Page 15: The domino effect: A network analysis of regime shifts drivers and causal pathways

1. What are the major global change drivers of regime shifts?

0 5 10 15

05

10

Indegree

Out

degr

ee

Absorption of solar radiation

AdvectionAerosol concentration

Agriculture

Albedo

Algae

Aquifers

Arctic sea ice volume

Atmospheric CO2

Atmospheric temperature

Basal lubrication

Biodiversity

Biomass

Bivalves abundance

Brown clouds

Canopy−forming algae

Carbon extractionCarbon storage

CHL structureCO2 emissions

Consumption preferences

Convection

Coral abundance

Cropland

Cropland−Grassland area

Daily relative cooling

Deforestation

Demand

Density contrast in the water column

Disease outbreak

Dissolved oxygen

Droughts

Dust

ENSO−like events frequency

Erosion

Evaporation Evapotranspiration

Exposed soilsFeces deposition

Fertilizers use

Fire frequency

Fish

FishingFloods

Flushing

Forest

Fossil fuel burning FreshwaterGesseGlacier exposure to wave actionGlacier undercutting

Global warming

Grass dominance

Grazers

Grazing

Greenhouse gases

Greenland ice sheet volume

Ground water tableHabitat structural complexityHeat flux in summer

Herbivores

Human population

HuntingHurricanesIce calving ratesIce cyclonic circulationIce front retreatIce sliding velocityIce−ocean heat exchangeIllegal logging

ImmigrationImpoundmentsInfrastructure developmentInvasive species

Irrigation

Land conversionLand−Ocean pressure gradient

Land−Ocean temperature gradient

Landscape fragmentation/conversion

Latent heat releaseLeakageLifting condensation level

Lobsters and meso−predators

Local water movements

Logging industryLow tides frequency

Macroalgae abundance

Macrophytes

Meltwater drainage

Meltwater runoff

Microbial activity

Mid−predators

MoistureMonsoon circulationMortality rate

Native vegetationNekton

Noxious gasesNutrient availability

Nutrient cycling

Nutrients input

Ocean acidificationOcean anthropogenic CO2 uptake

Open surface

Open water

Openings in ice coverOrganic matterOther competitorsOverturning

Palatability

Permafrost degradationPerverse incentives Phosphorous in water

PhytoplanktonPlanktivore fish

Plankton and filamentous algae

Pollutants

Precipitation

Productivity

Rainfall deficit

Rainfall variability

RanchingRiver runoffRoughnessSalinity

Savanna

Sea surface levelSea tides

SedimentsSewage

Shadow_rooting

Shrubs

Snowing driftingSoil drainage / aerationSoil impermeability

Soil moisture

Soil productivity

Soil quality

Soil salinity

Soil temperature

Solar radiation

SpaceSST

Steppe

Stratification

Stress beneath iceSubsidiesSulfide release Surface air temperatureTechnology TemperatureThermal annomaliesThermal low pressure

Top predators

TradeTragedy of the commonsTree maturity

Tundra

Turbidity

Turf−forming algae

Unpalatability Upwellings

Urban growth

Urban storm water runoff

Urchin barren

Vapor

Vegetation

Warm water inflow Water availability

Water column density contrastWater consumption

Water demandWater densityWater infrastructure

Water mixing

Water temperature

Water vapor

Wind fetch

Wind stress

Woody plants dominance

Woody vegetationYoung thin ice in winter

Zooplankton

Zooxanthellae

RS1 RS2 RS3

D1

0.00 0.01 0.02 0.03 0.04 0.05 0.06

0.00

0.01

0.02

0.03

0.04

0.05

0.06

Eigenvector

Betw

eenn

ess

Absorption of solar radiation

AdvectionAerosol concentration

Agriculture

Albedo

Algae

Aquifers

Arctic sea ice volume

Atmospheric CO2

Atmospheric temperature

Basal lubrication Biodiversity

Biomass

Bivalves abundance

Brown cloudsCanopy−forming algaeCarbon extractionCarbon storage

CHL structureCO2 emissionsConsumption preferencesConvection

Coral abundance

Cropland

Cropland−Grassland area

Daily relative cooling

DeforestationDemand

Density contrast in the water column

Disease outbreak

Dissolved oxygen

Droughts

Dust

ENSO−like events frequency

Erosion

EvaporationEvapotranspiration

Exposed soilsFeces deposition Fertilizers use

Fire frequency

Fish

Fishing

Floods

Flushing

Forest

Fossil fuel burning

Freshwater

GesseGlacier exposure to wave action

Glacier undercutting

Global warming

Grass dominance

GrazersGrazing

Greenhouse gases

Greenland ice sheet volume

Ground water tableHabitat structural complexity

Heat flux in summer

Herbivores

Human populationHuntingHurricanes

Ice calving ratesIce cyclonic circulation

Ice front retreat

Ice sliding velocity

Ice−ocean heat exchangeIllegal loggingImmigrationImpoundmentsInfrastructure developmentInvasive species

Irrigation

Land conversion

Land−Ocean pressure gradient

Land−Ocean temperature gradient

Landscape fragmentation/conversionLatent heat release

LeakageLifting condensation levelLobsters and meso−predatorsLocal water movementsLogging industryLow tides frequency

Macroalgae abundance

Macrophytes

Meltwater drainage

Meltwater runoffMicrobial activity

Mid−predatorsMoistureMonsoon circulation

Mortality rateNative vegetation Nekton

Noxious gases

Nutrient availabilityNutrient cycling

Nutrients input

Ocean acidification

Ocean anthropogenic CO2 uptake

Open surface

Open water

Openings in ice cover

Organic matterOther competitors

Overturning

PalatabilityPermafrost degradation

Perverse incentivesPhosphorous in water

Phytoplankton

Planktivore fishPlankton and filamentous algae

Pollutants

Precipitation

Productivity

Rainfall deficitRainfall variability

RanchingRiver runoff

Roughness

Salinity Savanna

Sea surface levelSea tides SedimentsSewage

Shadow_rooting

Shrubs

Snowing drifting

Soil drainage / aerationSoil impermeability

Soil moisture

Soil productivity

Soil quality

Soil salinitySoil temperature

Solar radiation

Space

SST

Steppe

Stratification

Stress beneath ice

SubsidiesSulfide release

Surface air temperature

TechnologyTemperature

Thermal annomalies

Thermal low pressureTop predators

TradeTragedy of the commonsTree maturityTundra

TurbidityTurf−forming algae

Unpalatability

Upwellings

Urban growthUrban storm water runoff

Urchin barrenVapor

Vegetation

Warm water inflowWater availability

Water column density contrastWater consumptionWater demand

Water density

Water infrastructure

Water mixing

Water temperatureWater vapor

Wind fetch

Wind stress

Woody plants dominance

Woody vegetation

Young thin ice in winter Zooplankton

Zooxanthellae

Local centrality Global centrality

Tuesday, March 15, 2011

Page 16: The domino effect: A network analysis of regime shifts drivers and causal pathways

Marine Regime Shifts

0.00 0.02 0.04 0.06 0.08 0.10 0.12

0.00

0.02

0.04

0.06

0.08

0.10

0.12

Eigenvector

Betw

eenn

ess

Agriculture

Algae

Atmospheric CO2

Biodiversity

Bivalves abundance

Canopy−forming algae

Consumption preferences

Coral abundance

Daily relative coolingDeforestationDemandDensity contrast in the water column

Disease outbreak

Dissolved oxygen

DroughtsENSO−like events frequency

Erosion

Fertilizers useFish

Fishing

FloodsFlushing

Global warming

Greenhouse gases

Habitat structural complexityHerbivores

Human populationHurricanesImpoundmentsInvasive speciesIrrigationLandscape fragmentation/conversionLeakage

Lobsters and meso−predators

Local water movementsLow tides frequency

Macroalgae abundance Macrophytes

Mid−predators

Mortality rate

Nekton

Noxious gases

Nutrients input

Ocean acidificationOrganic matter

Other competitorsPerverse incentivesPhosphorous in water

Phytoplankton

Planktivore fishPlankton and filamentous algae

PollutantsPrecipitationSedimentsSewage

Space

SST

StratificationSubsidiesSulfide releaseTechnologyThermal annomalies

Thermal low pressureTop predators

TradeTragedy of the commons

TurbidityTurf−forming algae

Unpalatability

Upwellings

Urban growthUrban storm water runoff

Urchin barrenWater column density contrast

Water mixing

Water temperature

Water vapor

Wind stress

Zooplankton

Zooxanthellae

0 5 10 15

05

10

Indegree

Out

degr

ee Agriculture Algae

Atmospheric CO2

Biodiversity

Bivalves abundance

Canopy−forming algae

Consumption preferences

Coral abundance

Daily relative cooling

DeforestationDemand

Density contrast in the water column

Disease outbreak

Dissolved oxygen

Droughts

ENSO−like events frequency

Erosion

Fertilizers use

Fish

Fishing

Floods

Flushing

Global warming

Greenhouse gases

Habitat structural complexity

HerbivoresHuman population

HurricanesImpoundmentsInvasive speciesIrrigation

Landscape fragmentation/conversion

Leakage

Lobsters and meso−predators

Local water movements

Low tides frequency

Macroalgae abundance

Macrophytes

Mid−predators

Mortality rate

Nekton

Noxious gases

Nutrients input

Ocean acidificationOrganic matterOther competitors

Perverse incentivesPhosphorous in water

PhytoplanktonPlanktivore fish

Plankton and filamentous algae

Pollutants

Precipitation SedimentsSewage

Space

SST

StratificationSubsidiesSulfide releaseTechnologyThermal annomalies

Thermal low pressure

Top predators

TradeTragedy of the commons

Turbidity

Turf−forming algae

Unpalatability Upwellings

Urban growth

Urban storm water runoff

Urchin barren

Water column density contrastWater mixing

Water temperature

Water vapor

Wind stress

Zooplankton

Zooxanthellae

RS1 RS2 RS3

D1

Local centrality Global centrality

Tuesday, March 15, 2011

Page 17: The domino effect: A network analysis of regime shifts drivers and causal pathways

Terrestrial Regime ShiftsRS1 RS2 RS3

D1

0 2 4 6 8

02

46

8

Indegree

Out

degr

ee

Absorption of solar radiationAdvectionAerosol concentration

AgricultureAlbedo

Aquifers

Atmospheric CO2Atmospheric temperature

BiomassBrown cloudsCarbon storage

Cropland−Grassland area Deforestation

DemandDroughts

DustENSO−like events frequency

ErosionEvapotranspiration

Fertilizers use

Fire frequency

Floods

Forest

Global warming

Grass dominance

Grazers

Grazing

Ground water table

Human population

Illegal loggingImmigration

Infrastructure development

Irrigation

Land conversionLand−Ocean pressure gradient

Land−Ocean temperature gradient

Latent heat releaseLifting condensation levelLogging industryMoisture

Monsoon circulation

Native vegetation

Palatability

Precipitation

Productivity

Rainfall deficit

Rainfall variability

Ranching Roughness

Savanna

Sea tidesShadow_rooting

Soil impermeability

Soil moistureSoil productivity

Soil quality Soil salinitySolar radiation

SpaceSST

Temperature

Tree maturity Vapor

VegetationWater availability

Water consumption

Water demandWater infrastructure

Wind stress

Woody plants dominance

0.00 0.02 0.04 0.06 0.08

0.00

0.02

0.04

0.06

0.08

Eigenvector

Betw

eenn

ess

Absorption of solar radiation

Advection

Aerosol concentration

Agriculture

Albedo

Aquifers

Atmospheric CO2

Atmospheric temperature

Biomass

Brown clouds

Carbon storage

Cropland−Grassland area

Deforestation

Demand

Droughts

DustENSO−like events frequency

Erosion

Evapotranspiration

Fertilizers use

Fire frequency

Floods

Forest

Global warming

Grass dominance

Grazers

Grazing

Ground water table

Human populationIllegal loggingImmigrationInfrastructure development

Irrigation

Land conversion

Land−Ocean pressure gradient

Land−Ocean temperature gradient

Latent heat release

Lifting condensation level

Logging industry

MoistureMonsoon circulation

Native vegetation

Palatability

Precipitation

Productivity

Rainfall deficitRainfall variability

RanchingRoughness

Savanna

Sea tides

Shadow_rooting

Soil impermeability

Soil moisture

Soil productivity

Soil quality

Soil salinitySolar radiation

Space

SSTTemperature Tree maturity

Vapor

VegetationWater availability

Water consumptionWater demand

Water infrastructure

Wind stress

Woody plants dominance

Local centrality Global centrality

Tuesday, March 15, 2011

Page 18: The domino effect: A network analysis of regime shifts drivers and causal pathways

2. What are the impacts of regime shifts on global change drivers?

Water infrastructureUpwellings

StratificationLand conversionInvasive species

GrazingENSO−like events frequency

DroughtsDemand

DeforestationAgriculture

Water demandNutrients input

IrrigationErosion

Disease outbreaksAtmospheric CO2

TurbidityGlobal warming

FishingFire frequency

How many regime shifts reinforce this driver?

0 1 2 3 4

Steppe − TundraKelps Transitions

Arctic Ice−sheet CollapseArctic Salt−Marshes

Thermohaline CirculationTundra − Forest

Fisheries CollapseLake EuthrophicationBush Encroachment

Coral TransitionsCoral Bleaching

Greenland Ice−sheet CollapseHypoxia

Bivalves CollapseMonsoon

Forest − SavannaMarine Foodwebs

Soil SalinizationDesertification

How many drivers are actually reinforced by regime shifts dynamics?

0 1 2 3 4 5 6

D1 D2 D3

RS1

Tuesday, March 15, 2011

Page 19: The domino effect: A network analysis of regime shifts drivers and causal pathways

Arctic Icesheet collapse

Bivalves collapseCoral bleaching

Coral transitions

Desertification

Encroachment

EutrophicationFisheries collapse

Foodwebs

Forest to savanna

Greenland icesheet collapse

Hypoxia

Kelp transitions

Monsoon

Soil salinization

Thermohaline

Arctic salt marsh

Steppe to Tundra

Tundra to Forest

3. What are the possible cascading effects of regime shifts and its drivers? Reported by RSDB

Tuesday, March 15, 2011

Page 20: The domino effect: A network analysis of regime shifts drivers and causal pathways

Up to 68 new inconvenient feedbacks when coupling regime shifts pairs (e.g. Marine foodwebs collapse & Kelps transitions)

Most feedbacks are dominated by changes on biodiversity dynamics.

Paths with shared drivers but non-forming feedback are not included.

3. What are the possible cascading effects of regime shifts and its drivers? RS1 RS2D1 ...

Bivalves.collapse

Coral.Bleaching

Coral.Transitions

Lake.Eutrophication

Fisheries.collapse

Marine.foodwebs

Hypoxia

Kelps

Tuesday, March 15, 2011

Page 21: The domino effect: A network analysis of regime shifts drivers and causal pathways

Up to 159 new feedbacks, e.g. when coupling desertification and bush encroachment.

Most feedbacks include climate - vegetation interactions.

Scaling up and down dynamics characterize the couplings.

3. What are the possible cascading effects of regime shifts and its drivers? RS1 RS2D1 ...

Desertification

Bush.Encroachment

Forest...SavannaSoil.Salinization

Monsoon

Tuesday, March 15, 2011

Page 22: The domino effect: A network analysis of regime shifts drivers and causal pathways

Summary1. What are the major

global change drivers of regime shifts?

2.

Marine: - Nutrient inputs - Fishing

Terrestrial: - Fire frequency - Deforestation - Agriculture

2. What are the impacts of regime shifts on global change drivers?

4.

Drivers more reinforced: - Fire frequency - Turbidity - Fishing - Global warming

Drivers more reinforced: - Fire frequency - Turbidity - Fishing - Global warming

3. What are the possible cascading effects of regime shifts and its drivers?

Inconvenient feedbacks dominated by change in biodiversity

Inconvenient feedbacks dominated by scaling up/down dynamics

Tuesday, March 15, 2011

Page 23: The domino effect: A network analysis of regime shifts drivers and causal pathways

Regime shifts are tightly connected. The management of immediate causes or well studied variables might not be enough to avoid such catastrophes.

Agricultural processes and global warming are the main causes of regime shifts.

Network analysis might be a useful approach to address causality relationships

Interaction of regime shifts drivers?

Tuesday, March 15, 2011

Page 24: The domino effect: A network analysis of regime shifts drivers and causal pathways

Thanks! Drs. Oonsie Biggs & Garry Peterson for their supervision

RSDB folks for inspiring discussion and writing examples

SRC for an inspiring research space and funding!

What is a regime shift? Science pub May 2009 - SRC

Questions??e-mail: [email protected]: @juanrochaBlog: http://criticaltransitions.wordpress.com/

Tuesday, March 15, 2011

Page 25: The domino effect: A network analysis of regime shifts drivers and causal pathways

Q4. What are the possible cascading effects of regime shifts and its drivers?

6.5 · 106 possible paths

Longest path 6 degrees

Average distance 2.37

Sample: 400 shortest pathways

Tuesday, March 15, 2011

Page 26: The domino effect: A network analysis of regime shifts drivers and causal pathways

Q4. What are the possible cascading effects of regime shifts and its drivers?

Coral transitions

Coral bleaching

Tundra to forest

Kelp transitions

Hypoxia

Steppe to tundra

Fisheries collapse

Bivalves collapse

Lake eutrophication

Bush encroachment

Soil salinization

0 20 40 60 80

Domino effect

Strong Weak Fake

6.5 · 106 possible paths

Longest path 6 degrees

Average distance 2.37

Sample: 400 shortest pathways

- Spatial mismatch of drivers and ecosystem processes

(fragmentation)

- Demographic & economic drivers

- Spatial adjacency is required

- Agriculture related drivers- Physical processes: climate

change

Tuesday, March 15, 2011

Page 27: The domino effect: A network analysis of regime shifts drivers and causal pathways

Q4. What are the possible cascading effects of regime shifts and its drivers?

Exacerbation of feedback loops

Neighborhood effect

Diffuse connections

Cascading-down interactions

Cascading-up interactions

Tuesday, March 15, 2011