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Introduction to Section 10 minutes Drivers of Change 30 minutes Deforestation vs Degradation 10 minutes Direct vs Indirect 10 minutes Method for estimating change 10 minutes Exercise Example 30 minutes 20 minutes Summary 10 minutes

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NameAffiliationNameAffiliation David Saah; Co-LeadUniversity of San Francisco, SIGPhan Xuan ThieuVinh University, Vietnam Mohd Zaki Hamzah; Co-LeadUniversity Putra MalaysiaChalita SriladdaUSAID-LEAD Khamla Phanvilay, Co-LeadNational University of LaosHoang Thi Thu DuyenVietnam Forestry University, Vietnam Cao Thuy AnhDalat University, VietnamLadawan PuangchitKasetsart University, Thailand Chalermpol SamranpongChiang Mai University, ThailandDo Anh TuanVietnam Forestry University, Vietnam Pham Thanh NamUSAID LEAF VietnamLyna KhanRoyal University of Phnom Penh, Cambodia Peter StephenUSAID LEAF BangkokLe Ba ThuongVietnam Forestry University, Vietnam Hoang Vinh PhuVinh University, VietnamNapat JakwattanaUniversity of Phayao, Thailand Vipak JintanaKasetsart University, ThailandNur Anishah Binti AzizUniversity Kebangsaan Malaysia Kulala MulungPNG University of TechnologyRatcha ChaichanaKasetsart University, Thailand Somvilay ChanthalounnavongNational University of LaosSureerat LakanavichianChiang Mai University, Thailand Thavrak HuonRoyal University of Agriculture, CambodiaVongphet SihapanyaNational University of Laos Athsaphangthong MunelithUSAID LEAF LaosDavid GanzUSAID LEAF Bangkok Attachai JintrawetChiang Mai University, ThailandChi Pham, Project CoordinatorUSAID LEAF Bangkok Chanin ChiumkanokchaiUSAID LEAF BangkokKent ElliottUS Forest Service Lam Ngoc TuanDalat University, VietnamBeth LebowUS Forest Service Mark FennUSAID Vietnam Forests & DeltasGeoffrey BlateUS Forest Service

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Low Emission Land Use Planning (LELUP) Section 2. Assessment of Current and Historical Condition 2.2. Understanding Historical Land Use Change and Current Condition Regional Climate Change Curriculum Development

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ENABLING ENVIRONMENT ASSESSMENT OF CURRENT CONDITION ANALYSIS OF FUTURE OPTIONS NEGOTIATING & PRIORITIZING IMPLEMENTA- TION PLAN MONITORING & EVALUATION Low Emission Land Use Planning 1.1. Regulatory Assessments 1.2. Stakeholder Engagement 1.3. Planning & Development Goals & Objectives 2.1. Environment, Social, & Economic Data Needs 2.2. Understanding Historic Land Use Change

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At the end of this session, learners will be able to: Determine drivers (or causes) of historical land use change and the actors involved in these processes. Evaluate process (spatial and non-spatial) to help quantify historical land use change. Quantify the current resource condition from which to compare future change.

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Session Introduction Drivers of Change Deforestation vs. Degradation Direct vs. Indirect Drivers Method for estimating change Exercise Example Summary

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Rules of the Game Time/Space Drivers of Change Goal / Objective NOW Past Trend / Current Condition BAU

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Agricultural expansion Timber production Infrastructure development Economic growth Demographic changes Governance Technology Environmental issues

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Rate of agricultural expansion in Southeast Asia increased from 0.7% pa between 1997 and 2002 to 1.2% between 2002 and 2007 and 1.7% between 2007 and 2009

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Resurgence after 2001

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Road network expansion greatest in Viet Nam and Thailand

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Economies growing rapidly and demands on forest resources will increase Poverty and migration remain key issues

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Southeast Asia population: 593 million in 2010 657 million in 2020 Rapid urbanization: 47% urban in 2010 54% in 2020

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Corruption worsening except in Indonesia and Brunei Source: World Bank

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Productivity enhancement Processing technologies

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Displacement of timber demand to other countries following logging bans and forest protection should be considered.

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Deforestation The long-term or permanent conversion of land from forested to non-forested land Example where definition is for 20% forest cover Forest 20% Canopy 90% Canopy Non-Forest < 20% Canopy 10% Canopy

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Degradation Changes within the forest which negatively affect the structure or function of the stand or site, and thereby lower the capacity to supply products and/or services. Example where definition is for 20% forest cover Forest 20% Canopy 80% Canopy Forest Still 20% Canopy 50% Canopy

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Forest definition (canopy cover %) 10% tree cover 25% tree cover 30% tree cover Forest Area (M ha)433736 Aboveground forest carbon (Mt C)4,9714,4984,410 Belowground forest carbon (Mt C)1,3351,2031,179 Total Forest carbon (Mt C)6,3065,7015,589 Average Carbon Density (t C/ha)147152153 Source: http://rainforests.mongabay.com/deforestation/2000/Papua_New_Guinea.htmhttp://rainforests.mongabay.com/deforestation/2000/Papua_New_Guinea.htm

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Country Average Loss in Forest (ha yr -1 ) Average Loss as a % of Cover in 2000 (%) Bangladesh8,1630.4% Bhutan3,8580.2% Cambodia56,5320.6% India205,2460.5% Indonesia690,2080.7% Laos85,9650.5% Malaysia230,9881.1% Nepal16,0850.3% PNG48,5900.1% Philippines38,2200.4% Thailand133,6080.8% Vietnam54,3640.4% Total1,571,8260.5%

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Deforestation Data Agriculture is the key driver of deforestation (about 80%) Both commercial and subsistence Food demand is projected to increase by 70% globally over the next 40 years

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Drivers different for forest degradation Primarily logging and fuel-wood charcoal In subtropical Asia timber logging is key driver In Africa it is wood for fuel Deforestation Data

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Sources (+) and sinks (-) of carbon (TgC yr -1 ) from activities contributing to deforestation and forest degradation in tropical regions.

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Direct Drivers Infrastructure Extension Agricultural Expansion Wood Extraction Underlying Causes DemographicEconomicTechnologicalPolicyCultural

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Assessment of historical drivers of landscape change is essential: Are drivers directly or indirectly causing the problem? What is the scale at which the drivers operate? What is the drivers trend or trajectory? Do the drivers interact? Who are the key actors or stakeholders involved with the identified driver; and

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A very similar process can be used to identify historical and future threats (drivers) to key biodiversity assets. Direct Threats: Human activities: Unsustainable Timber Harvest Natural phenomena: Water availability limited in forest by city Natural phenomena whose impact is increased by other human activities Type conversion from Forest to scrubland and limited water

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In small groups, each student is to carefully read the case study and then discuss within their group the following questions: 1. What are the direct and indirect drivers of deforestation and forest degradation and the relationship between the two? 2. What is the scale and historical trend for each of the drivers? 3. Who are the actors involved for each of the identified drivers? 4. By assessing historical drivers of landscape change, what information can this provide the Florestania REDD+ Task Force in predicting future landscape change? Each student group will be required to provide a brief report on their findings.

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1. Prepare: Set time period for analysis. Ensure maps for individual date are consistent (definitions, classifications, sensors, etc). 2. Overlay: Use GIS or image processing software to overlay two land use maps from two different dates. Creates an attribute table where each polygon or pixel contains the recorded land use on both the 1 st and 2nd dates. 3. Simplify the attributes to a set of unique land use change transitions. 4. Create the land use change matrix:

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The current land use planning goals in Lam Dong Province, Vietnam are: CategoryObjectiveIndicator EnvironmentalMaintain at least 61% forest cover by 2015 Percent forest cover Maintaining or improving ecological integrity 1) Ratio of natural forest to plantations 2) Species type diversity 3) Richness Reduce GHG emissions in the AFOLU sector by 20% by 2020. Tons CO 2 equivalents (tCO 2 e)/year EconomicIncrease annual GDP growth rate from 12-15% GDP growth rate GDP per capita will reach USD 2,300 by 2015 GDP per capita SocialPopulation growth reduced to 1.3% (2015) and 1.2% (2020) Population growth rate by urban and rural sectors No poor households by 2020General poverty rate by urban and rural sectors

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Land cover change analysis 2000 2005 2010

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2005 B/leaf E/green forest Deciduou s forest Bamboo forest Mixed wood & bamboo Coniferuo s forest Mixed broadleaf & coniferuos forest Plantation Bared land Non forested land Total Broadleaf evergreen forest194,669362,48313,8881101542,7141,82714,111229,995 Deciduous forest2415,4170.0320.50.26408521,24818,217 Bamboo forest9380.037,7397,4312863,20270610,60660,660 Mixed wood&bamboo10,467446,30569,32740132,1679017,78797,054 Coniferuos forest16762623113,2279831,0471,9757,945125,402 Mixed broadleaf & coniferuos forest193171541219,9363532021,00022,121 Plantation1780.039375533537,1096018,20046,647 Bared land1,8841071,9632,604344924,4919,40713,82734,721 Non forested land26481,110563201339,515501330,335342,534 Total208,78715,62250,03093,960114,41821,25561,24216,975395.062977.354 Land Use Change Matrix, 2005-2010 (hectares)

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Landcover change analysis from 2005-2010 Remote Sensing- Derived Data

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REDD+ Activity Total Emissions and Removals MMT (CO 2 e) Historical Period 1990-19951995-20002000-20052005-2010 Deforestation 12.4 8.8 9.9 Forest Degradation 7.8 8.0 5.9 5.7 Forest Enhancement (2.4) (3.3) (3.4) (2.8) Afforestation and reforestation (1.0) (1.8) (1.7) Total 16.8 11.7 9.5 11.1 Annual 3.4 2.3 1.9 2.2

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Species Diversity Analysis 2000 2005 2010

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Species Diversity Analysis

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Population Growth Rates

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General Poverty Rate

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GDP per Capita Annual GDP Growth Rate

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ENVIRONMENTAL SOCIAL ECONOMIC GHG EMISSIONS & REMOVALS Convergence of Indicators

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Increased level of complexity will challenge land use planners and place additional pressures on land management agencies. Accurate and consistent historical data is notoriously difficult to gather. Connecting landscape data analysis and field level interpretation is a challenge.

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There is now increased investments (REDD+) that are investing in quantifying drivers of change that can be used for LE-LUP

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Key Reference material to support this session: Guidance on Low Emission Planning for the Forest and Land Use Sector, Section 2.2 Drivers of Landscape Change LEAF/ARKN-FCC (2014), Decision Support Tool: Identifying and Addressing Drivers of Deforestation and Forest Degradation (unpublished).