Land use scenario development

Workshop Regional changes of land use for climate change adaptation and mitigation

24-25 May 2011, Zamorano

By Wilbert van Rooij

Netherlands Environmental Assessment Agency (PBL)

seconded to Aidenvironment

• Multi-scale• Multi-theme• Multi-sectoral and thus• Multi-disciplinary

Environmental science – a complex issue

An assessment of the current status is complex, the assessment of the future status even more

What is a scenario?

Scenarios are credible, challenging, and relevant stories about how the future might unfold that can be told in both words and numbers.

Scenarios are plausible descriptions of how the future may develop, based on a coherent and internally consistent set of assumptions about key relationships and driving forces.

Scenarios are not forecasts, projections, or predictions.

Scenarios – overview

Scenarios:

• Have the ability to address complex issues in an integrated manner.

• Have the ability to deal with surprises, system changes, alternatives.

• Are an excellent tool for communication

• Possibilities for participation are large.

Purposes of using (participatory) scenarios

Environmental scientists:

Scenarios are a good tool for an integrated analysis of a complex problem. Scenarios provide in-depth insight in complex societal problems.

Focus on results

Social scientists:

Scenarios are a good tool for communication, conflict management, and long-term participation. Scenarios provide an excellent tool for communication. Focus on process

Types of scenarios

A Project goal - exploration vs decision support: I. Inclusion of norms? : descriptive vs normativeII. Vantage point: forecasting vs backcastingIII. Subject: issue-based, area-based, institution-basedIV. Time scale: long term vs short termV. Spatial scale: global/supranational vs national/local

B Process design – intuitive vs formal: VI. Data: qualitative vs quantitativeVII. Method of data collection: participatory vs desk researchVIII. Resources: extensive vs limitedIX. Institutional conditions: open vs constrained

C Scenario content - complex vs simple: X. Temporal nature: claim vs snapshotXI. Variables: heterogeneous vs homogenousXII. Dynamics: peripheral vs trendXIII. Level of deviation: alternative vs conventionalXIV. Level of integration: high vs low

Scenarios, models, and participation

Traditional approach

Integrated approach

Example scenario for Global assessment 1:

The Millennium Ecosystem Assessment(full Storyline-And-Simulation approach)

Millennium Ecosystem Assessment

An international scientific assessment of the consequences of ecosystem changes for human well-being:

Modeled on the IPCC

Providing information requested by:

Convention on Biological Diversity (CBD)

Convention to Combat Desertification (CCD)

Ramsar Convention on Wetlands

Convention on Migratory Species (CMS)

other partners including the private sector and civil society

With the goals of:

stimulating and guiding action

building capacity

MA Conceptual FrameworkGlobal

= Strategies and Interventions= Strategies and Interventions

Regional

Human Wellbeing & Poverty Reduction

Health and disease Environmental security Cultural security Economic security Equity

Proximate Drivers Climate change Land and water use & cover

change Factor inputs (e.g. irrigation,

fertilizers) Pollution Harvest Nutrient release Species introductions

Primary Drivers Demographic change Economic change (incl

globalization, trade, market, & policy framework)

Social and political change (inclgovernance, institutional, & legal framework)

Technological change Lifestyle and behavioral change

Local

Life on Earth

Ecosystems &Their Services

Supporting (biodiversity and ecosystem processes)

Provisioning (food, water, fiber, fuel, other biological products)

Cultural (social, aesthetic)

MA Scenarios

Not predictions – scenarios are plausible futures

Both quantitative models and qualitative analysis used in scenario development

Scenario Storylines

Global Orchestration Globally connected society that focuses on global trade and economic liberalization and takes a reactive approach to ecosystem problems but that also takes strong steps to reduce poverty and inequality and to invest in public goods such as infrastructure and education.

Order from Strength Regionalized and fragmented world, concerned with security and protection, emphasizing primarily regional markets, paying little attention to public goods, and taking a reactive approach to ecosystem problems.

Scenario Storylines

Adapting Mosaic Regional watershed-scale ecosystems are the focus of political and economic activity. Local institutions are strengthened and local ecosystem management strategies are common; societies develop a strongly proactive approach to the management of ecosystems.

TechnoGarden Globally connected world relying strongly on environmentally sound technology, using highly managed, often engineered, ecosystems to deliver ecosystem services, and taking a proactive approach to the management of ecosystems in an effort to avoid problems.

Changes in indirect drivers

In MA Scenarios: Population projected to

grow to 8–10 billion in 2050

Per capita income projected to increase two- to fourfold

Crop Land

Changes in crop land and forest area under MA Scenarios

Changes in direct drivers

Forest Area

Changes in direct drivers

Habitat transformation: Further 10–20% of

grassland and forestland is projected to be converted by 2050

Overexploitation, overfishing: Pressures continue to

grow in all scenarios

Invasive alien species: Spread continues to

increase

Observed recent impacts of climate changes on ecosystems: Changes in species distributions Changes in population sizes Changes in the timing of reproduction or migration events Increase in the frequency of pest and disease outbreaks Many coral reefs have undergone major, although often

partially reversible, bleaching episodes when local sea surface temperatures have increased

Changes in direct drivers:Climate Change

Potential future impacts By the end of the century, climate change and its impacts may be

the dominant direct driver of biodiversity loss and changes in ecosystem services globally

Harm to biodiversity will grow worldwide with increasing rates of change in climate and increasing absolute amounts of change

Some ecosystem services in some regions may initially be enhanced by projected changes in climate. As climate change becomes more severe the harmful impacts outweigh the benefits in most regions of the world

Net harmful impact on ecosystem services The balance of scientific evidence suggests that there will be a

significant net harmful impact on ecosystem services worldwide if global mean surface temperature increases more than 2o C above preindustrial levels (medium certainty). This would require CO2 stabilization at less than 450 ppm.

Changes in direct drivers:Climate Change

Changes in ecosystem services under MA Scenarios

Demand for food crops is projected to grow by 70–85% by 2050, and water withdrawals by 30-85%

Food security is not achieved by 2050, and child undernutrition would be difficult to eradicate (and is projected to increase in some regions in some MA scenarios)

Globally, the equilibrium number of plant species is projected to be reduced by roughly 10–15% as the result of habitat loss over the period of 1970 to 2050 (low certainty)

Child undernourishment in 2050 under MA Scenarios

2nd example Global assessment: OECD ENVIRONMENT OUTLOOK: TRAFFIC LIGHTS

• Some air pollutants (lead, CFCs, NOx, SOx)

• Forest coverage in OECD regions

• Water use

• Surface water quality

• Hazardous waste & toxic emissions

from industry

• Energy production & use

• Forest quality in OECD regions

•Waste management

•GHG emissions

• Motor vehicle & aviation air pollution

• Municipal waste gen.

• Agricultural pollution &

groundwater quality

• Over-fishing

• Biodiversity & tropical forest

coverage

• Chemicals in the environment

Approach to quantifying scenarios in IMAGE model

IMAGE 2 model

Global change

WaterGAP model

World water resources

Modelling

course ITC-MNP:

GLOBIO 3.0

22

Calculate environmental changes

- Land use (incl forestry)- Climate- N-deposition- Infrastructure- Fragmentation

Use GLOBIO to calcultate MSA

Bas Eickh

out, IMAG

E: from

global to

local

23

Land-use change

Changes in population and economy

Changes in diet: more or less meat; more or less animal products like milk

Changes in agricultural trade assumptions

Changes in food requirements for animals (more or less residues, more or less grass)

Changes in feed efficiency per animal

Bas Eickh

out, IMAG

E: from

global to

local

24

Where does the food and feed demand come from?

Using a macro-economic agricultural trade model

Inputs like capital, labour and land determine amount of production per region

Price elasticities determine type of agricultural product and technology developments

25

Taking environmental constraints into account

Sou

rce

: V

an M

eijl

et a

l., 2

005

economic policyglobal technical progress social development

consumption patterninternational cooperation

sectoral technical progress

production, yield, mana- feed

gementfactor conversion

Land use and environmental development

(IMAGE)

World Vision(four scenarios

story lines)

Population growthEconomic growth

Demand on and trade in agricultural products (GTAP)

Bas Eickh

out, IMAG

E: from

global to

local

26

Outlook

Increase in food and feed demand

Global trade regimes will change

Other service will be required from land (bio-energy)

Competition for land both globally and locally

27

But this was very globalHow can this be used for national scenario development?

Use global model results as a context (what food feed, bio-energy and timber demand is required in your region)

Use global results as an input where possible (climate change, nitrogen deposition)

Use local experts to assess region-specific aspects (land-use change)

The MA is a multi-scale assessment

with multiple layers of nesting

e.g. Central America

e.g. Honduras

e.g. El Paraíso

29

Methodology of multi scaled assessment:Eururalis

Examples Sub Global Assessments (SGAs).

Multi-scale assessments

Story of the present: Writing post-its

Discussing relationships between factors

Final product

Climate

Water

Land usechange

Population,Migration

Environmentaleducation

RegionalPolicies

Agrarian Policies

Desertification

Creating the scenarios

Presenting the scenarios

Backcasting exercise:Multifunctional sustainable agriculture (BiB)

Quick reference scenario exercise

Phase 1 Phase 2 Phase 3 Phase 4

Scenario exercise

Source: Ecosystems and human well-being: A manual for Assessment

Practitioners Neville Ash et all, 2010

Phase 1: How to set up a scenario exercise

Understand context, aim of scenario exercise

Identify and agree on type of support to be given

Agree on expected outcome in terms of process and product

Define scope: Budget and time frame

Geographical scale and time horizonType of scenarios and analysis

Set up a project team and environment:Establish authorising environment

Decide who to involve in the process and whenDefine role of stakeholders

1

2

3

4

5

Phase 2: How to develop scenarios

Identify main concerns and stakeholder questionsand understand how past changes have come about

Establish scenario development procedure and decide on method( inductive, deductive or incremental

Analyse main drivers of change in futureDiscuss possible trends for each driver

Identify the main uncertainties for the futureDevelop a set of scenario logics

Describe scenario assumptions and story lines based on identified drivers and scenario

Optional: use models to quantify main trends and assumptions

Stage 1

2

3

4

1

Stage 2

Stage 3

Phase 3: How to analyze scenarios

Determine whether, what and how to quantify. Check:Need and role quantitative information

Availability of quantification toolsAvailability of budget and time

Time horizon of analysisWhich need to be assessed

To what extent models need to be coupled

Analyze implications of individual scenariosOptional: Quantify driving forces and impacts

Assess ecosystems and human well being implications

Optional: Analyze specific response options

Analyze across the set of scenarios:Identify reasons for differences across scenarios

Identify differing, similar and offsetting trendsOptional: Analuze response options in scenarios

2

3

1

Policy options:

e.g. climate adaptation

and mitigation

Phase 4: How to use and communicate scenarios

Map target audience and context conditions: Do a network analysis regarding actors, relationships,

information needs and habits

Map purpose to context:Check consistency ,credibility, saliency and legitimacyAssess what can reasonably be done with resources

Develop outreach and communication strategyDevelop clear success criteria

Ensure steady high level support and backing

Resent scenarios to target audience(s)Discuss implications, response options and lessons

learnt

Evaluate and monitor outreach action against your success criteria

1

2

3

4

5

Practical steps: Storyline And Simulation approach

Narrativestorylines

Model runs

Practice: What are the scenario archetypes?

Solidarity/Pro-activeSelf-interest/Reactive

Regional

Global

IPCC SRES A1GEO-3 Markets FirstOECD ReferenceMA Global OrchestrationMedAction Big is Beautiful

IPCC SRES B1GEO-3 Sustainability First

MA Techno GardenMedAction Knowledge is King

IPCC SRES A2GEO-3 Security First

MA Order from StrengthMedAction Big is Beautiful?

IPCC SRES B2

MA Adaptive Mosaic

Practice: What are the scenario archetypes?

Solidarity/Pro-activeSelf-interest/Reactive

Regional

Global

Global Markets

Global Sustainability

ContinentalBarriers

Regional Sustainability

Example: Characteristics of Global Markets scenario

Main drivers

Population growth: low increase quality of life

Economic development: very rapid

Technology development: rapid new inventions, but no magic

Environmental attitude: reactive no environmental laws and policies

Trade increase (globalisation)

Institutional strength policies help economy

State of environment very poor

Main objective economic growth

46

Wilbert van Rooij, March 2009

Determine local consequences climate change on main drivers

E.g. on Agriculture:

Change of productivity because of floods, drought, salinization ; migration of land use to other areas

extensification vs intensification import of foodcrops?

E.g. on Biodiversity: Habitat change

Increased pressure on natural resources because of migration

Etcetera

Effects of climate change on land use scenario

Link with policy alternatives for climate change adaptation and mitigation + biodiversity conservation

Land use scenario should be as specific as possible on policy options or alternatives for climate adaptation and mitigation

and biodiversity conservation.

Example: Possible options in relation to biodiversity conservation:

• Extension of protected area system• Conversion to organic type of farming• Investing in intensification of agriculture (new technologies)• Reforestation programmes• Avoiding land abandonment• Sustainable use of natural ecosystems

Link with CLUE-s model

Demand:How much will be the change (in ha) of all major land uses?

Spatial policies:New national parks, restricted areas, agricultural development zones

Location characteristics:Infrastructure (new roads?) = change in accessibilitySoil (soil degradation?)Population (migration because of globalisation?)Etc.

Conversion settingsTransition possibilities from one land use type to another

Link with CLUE-s model

National scenarios – essential characteristics

The scenario should be:

1. Consistent with the assumptions of a selected archetype scenario

2. Consistent with current national trends

3. Creative! (do not use archetype as straitjacket)

4. As specific as possible on policy options for conversation

5. Linked with CLUE-s where possible

51National scenarios – essential elements

Your scenario could have information on:

Factors: Sectors: Actors:

Economic development Agriculture* Government

Population growth Tourism Businesses

Consumption pattern Energy NGOs

Technology Water

Environmental Policies Forestry

Scientists Protected area

Institutions Urban area

State of environment etc.(Biodiversity!) * Share intensive / extensive agr.

area

Translating storylines

Quantitative differences in land use areas (demand) Agricultural demand Intensification Reforestation Focus on export crops (perrennials)

Spatial differences (conversion matrix/region file) Parks Restricted areas

Behavioural differences (suitability maps/elasticities) Subsidies Awareness (erosion?) Learning Farming system change

Quantifying demand changes for input CLUE

Arable land / Grassland Compare with trend from FAO and IMAGE simulations Only use trend (e.g. % change between 2000 and 2030) Divide by perennial/arable crops depending on scenario

conditions

Nature Agricultural expansion mostly at cost of nature?

Quantification of land use scenarios essential for model to allocate future land use production of future land use map

54

Example FAO statistics

55

Example IMAGE simulation output

56

Wilbert van Rooij, May 2011

Bridging gap between numeric and geographical data:Baseline scenario1: Extract numeric data from available resources: A: Global: FAO (website), Global Assessments (MA, OECD, GBO, IPCC) B: National: Development reports (agricultural + forestry department Outlooks (Vietnam: Agenda 21, MDG report, etc) Census data from statistical department Specialists (Socio-Economists. Agronomists, Forestry planners, Environmentalists, etc)

2: Aggregate land use classes So that you can compare spatial and numeric data and for which you have future data

3: Create trends, historical and for planned time horizon

4: Compare geographical areas aggregated land use classes of the land use map with the areas derived from non spatial sources

5: Interpret reasons for difference, adjust numeric data and use relative differences for creation of demand table

57

Wilbert van Rooij, March 2009

Bridging gap between numeric and geographical data:Baseline scenario + policy option

Determine different trends in land use change because of implementation of selected policy option(s)

Analyze national policies / plans with respect to climate adaptation and mitigationExample adaptation:

Support to farmers who want to change land use type: for example to more drought resistant crop types

Example mitigation: Increasing imports reduces pressure on natural resources

• And finally quantify these changes in the demand table for this policy option. Per policy option 1 demand table.

58

Example scenario: Vietnam

1: Baseline scenario:

• Cropland demand: IMAGE OECD baseline scenario + 25% for 2030

- Cropland diversification: extensive (80%) and intensive (20%)

• Plantation demand: increment of 500 km2/year.

• Primary forest assumed to remain constant

2: Biodiversity conservation policy option:• Primary forest: total forest cover (plantation + primary class) in 2030 will reach 40% of country land area

• Protected areas (PAs) increase from 7% to 10% of the land:

- existing parks and primary forests above 1000 m

• Strict law enforcement (no Land use change inside PA’s)

59

Forest scenario Vietnam used in Clue

   

Primary forest

Plantation

Nature Others Area

2000 0 26020 20763 36142 19691 13963 17846 47162 87488 11634 18229 28525 32,74632001 1 26124 21563 38226 21115 15830 15704 43870 86619 11657 18229 28525 32,74632002 2 26232 22411 40257 22375 17698 13820 40743 85493 11681 18229 28525 32,74632003 3 26344 23305 42238 23479 19565 12162 37772 84141 11704 18229 28525 32,74632004 4 26460 24244 44169 24434 21433 10702 34950 82590 11727 18229 28525 32,74632005 5 26581 25227 46052 25247 23300 9418 32269 80863 11751 18229 28525 32,74632006 6 26708 26253 47617 26254 24513 8288 30049 79254 11774 18229 28525 32,74632007 7 26839 27312 49143 27150 25727 7293 27939 77508 11798 18229 28525 32,74632008 8 26975 28404 50631 27940 26940 6418 25936 75644 11821 18229 28525 32,74632009 9 27117 29527 52081 28630 28153 5648 24032 73674 11845 18229 28525 32,74632010 10 27265 30682 53495 29225 29367 4970 22224 71612 11869 18229 28525 32,74632011 11 27418 31866 52255 29730 30580 4374 20506 72088 11893 18229 28525 32,74632012 12 27578 33013 51045 30148 31793 3849 18874 72492 11916 18229 28525 32,74632013 13 27743 34124 49865 30485 33007 3387 17324 72834 11940 18229 28525 32,74632014 14 27913 35200 48715 30745 34220 2981 15851 73120 11964 18229 28525 32,74632015 15 28089 36242 47594 30931 35433 2623 14452 73357 11988 18229 28525 32,74632016 16 28271 37250 46501 31047 36647 2308 13123 73551 12012 18229 28525 32,74632017 17 28457 38227 45435 31096 37860 2031 11860 73708 12036 18229 28525 32,74632018 18 28648 39171 44395 31083 39073 1787 10660 73831 12060 18229 28525 32,74632019 19 28844 40085 43382 31009 40287 1573 9520 73924 12084 18229 28525 32,74632020 20 29044 40970 42394 30878 41500 1384 8438 73993 12108 18229 28525 32,7463

Heavily disturbed forest

Slightly disturbed forest

Regrowth shrub and bushes

Shifting cultivation (ext.agr)

Degraded lands

Intensive agriculture

Residential and urban land

Year

2000 is the baseline derived from the current land use map. The rest are projections from a scenario

Interpolation of land use area data60

  FRA2005 1990 1995 2000 2010Prim. for 118 100 93Sec. for 90 100 105

Select regression type: liner, logarithmic,

polynomial, etc.

61

Scenario information is used for the geographical allocation of future land use and to determine its pressure on biodiversity

101°15'0"E 103°30'0"E 105°45'0"E 108°0'0"E 110°15'0"E

landuse 2020 baselinePrimary Forest

Slight disturb forest

Heavily disturbed forest

Regrowth shrub and bushes

Plantation

Shifting cultivation

Degraded lands

Intensive agriculture

Residential and urban land

Nature

Others

²

125 0 12562.5 Kilometers

+

+

+

+

Lu model + Globio

MSA_lu2020

MSA_infr2020

MSA_frag2020

MSA_nitr2020

MSA_clim2020

Thank you for your attention!

Time for Questions .