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 .
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