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REDD-plus after Cancun: Moving from Negotiation to Implementation -Building REDD-plus Policy Capacity for Developing Country Negotiators and Land Managers-

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Presentation on theme: "REDD-plus after Cancun: Moving from Negotiation to Implementation -Building REDD-plus Policy Capacity for Developing Country Negotiators and Land Managers-"— Presentation transcript:

1 REDD-plus after Cancun: Moving from Negotiation to Implementation -Building REDD-plus Policy Capacity for Developing Country Negotiators and Land Managers- at Hotel Nikko Hanoi, Hanoi, Vietnam, 18-20 May 2011 Developing Robust MRV Systems: Learning from Country Experience in Indonesia Mitsuru Osaki*, Farhan Helmy**, Doddy Skadri**, and Kazuyo Hirose*** *Research Faculty of Agriculture, Hokkaido University, Japan **National Council on Climate Change (DNPI), Indonesia ***Center of Sustainability Science (CENSUS), Hokkaido University, Japan

2 General Introduction

3 Net primary production decreased 1% (0.55 petagrams of carbon over 10 years) globally from 2000 to 2009 Maosheng Zhao, et al.: Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009 Science 329, 940 (2010) The past decade (2000 to 2009) has been the warmest since instrumental measurements began, which could imply continued increases in NPP; however, our estimates suggest a reduction in the global NPP of 0.55 petagrams of carbon. Large-scale droughts have reduced regional NPP, and a drying trend in the Southern Hemisphere has decreased NPP in that area, counteracting the increased NPP over the Northern Hemisphere.

4 Net primary production increased 6% (3.4 petagrams of carbon over 18 years) globally during 1982 to 1999 Ramakrishna R. Nemani, et al : Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999. Science 300, 1560 (2003); We present a global investigation of vegetation responses to climatic changes by analyzing 18 years (1982 to 1999) of both climatic data and satellite observations of vegetation activity. Our results indicate that global changes in climate have eased several critical climatic constraints to plant growth, such that net primary production increased 6% (3.4 petagrams of carbon over 18 years) globally. The largest increase was in tropical ecosystems. Amazon rain forests accounted for 42% of the global increase in net primary production, owing mainly to decreased cloud cover and the resulting increase in solar radiation.

5 Project Introduction

6 Study Site from 1997 Central Kalimantan, Indonesia Peatland Mega Rice Project Palangkaraya Study Topics: ・ Green House Gasses Flux (CO 2, CH 4, N 2 O) ・ Fire Detection and Protection ・ Water Table Monitoring and Management ・ Peatland Ecology ・ Integrated Farming

7 Sources: 1) Forestry Statistics of Indonesia 2007, Ministry of Forestry, Jakarta 2008. 2) Wetlands International - Indonesia Programme, Bogor July 2008. LocationTotal Forest area 1) Mha (x 1,000 ha)93,924.33 (100%) Peatland area 2) Mha (x 1,000 ha)21,000 (100%) Legend: Kalimantan 28.200 (30.06%) 5.800 (27.50%) Sumatera 14.700 (15.60%) 7.200 (34.30%) Jawa/Madura 3.000 (3.30%) na Bali/Nusa Tenggara 2.700 (2.88%) na Papua/West Papua 32.400 (34.45%) 8.000 (38.10%) Sulawesi 8.900 (9.45%) na Maluku/North Maluku 4.000 (4.28%) na Forest and Peatland Areas in Indonesia 7

8 What Factors Regulate Carbon in Tropical Peat? Carbon Emission by Fire Water Carbon Emission by Microorganism Degradation Deforestation ・ Dryness of ground surface ・ Decrease water holding capacity Drainage ・ Decrease water table Carbon Loss through Water Ecosystem Change ・ Farming/ Vegetation Tree Growth/Mort ality

9 PALSAR, AMSR-E (4), (5), (6), (7) GOSAT (1) Satellite Airborne /UAV Ground Tower(1) Terra & Aqua MODIS (2) LiDAR (4), (5), (7) UAV(1), (3) Landsat, SPOT, Quickbird, TerraSAR, AVNIR-2, ASTER, Hisui, (3), (8) (5)Peat subsidence (6)Water level, Soil moisture (4)Forest biomass change (3)Deforestation, Forest degradation, Species mapping (1) CO 2 concentration FES-C (1) *FES-C : Fiber Etalon Solar measurement of CO 2 Lateral CO 2 Flux Vertical CO 2 Flux DGPS(5) Chamber(1) Water Gauge(6) (7)Peat dome detection & Peat thickness Drilling(7) (2)Wildfire detection & Hotspot ( 8)Water soluble organic carbon Red: Instrument Black: Target Key Elements for Carbon Flux Estimation (Integrated MRV system proposed as Sapporo Initiative)

10 (1) Emissions by fires

11 Fire Detection New Generation Fire Detection Doubled S/N ratio (ASTER comparing to MOD14, and Algorism Improvement) – 80% more HS and & 10% less False Alarm – Smoldering, small fire or slush and burn – Geographical distribution is completely different – Suitable to decide firefighting strategy and confirm extinction MOD14Proposed Toshihisa Honma, Hokkaido University, Japan

12 Example of Thermograph Image of flight observation RGBIR UAV (Unmanned aerial vehicle) flight observation and Wireless Sensor Network are indispensable as well as ground observations. Toshihisa Honma, Hokkaido University, Japan

13 Fire Expan. Simulation Simulation Result at 16:00, June25 (after 24 hours run). The expansion for the very slow expansion mainly to southward is overestimated. The rapid expansion toward eastward is underestimated because of the limit of time step. Toshihisa Honma, Hokkaido University, Japan

14 14 By Hidenori Takahashi, Japan

15

16 Peat Fire Index An indicator of peat fire damage ( Carbon emission data is offered by Dr. Erianto Indra Putra ) 1Mha MRP area in Kalteng PFI Carbon emission by peat fire (GtC/Mha) By Hidenori Takahashi, Japan

17 GHGs Emission by Peat Fire R. Hatano et al. (unpublished)

18 The organic matters eluted from burned soil ‣ Amount of eluviation greatly increases at 220 ℃ burn. ‣ Most part of eluted organic matters from burned soil have hydrophilic. (by Kuramitsu et al.) The peat land fire accelerate the eluviation of Carbon. Burned at 220 ℃ Burned at 350 ℃ Hydrophilic matters Hydrophobic acids 5 min 30 min Unburned soil

19 (2) Emission by oxidation of microorganisms

20 Eddy covariance technique Within the boundary layer, vertical flux is almost constant. If flux is measured at an appropriate height within the boundary layer, we can obtain flux averaged spatially over the fetch. CO 2 flux (Net ecosystem CO 2 exchange) is calculated as the covariance of vertical wind speed and CO 2 density. By Takashi Hirano (Hokkaido Univ., Japan)

21 Undrained forest (UDF) Drained forest (DF) Burnt forest after drainage (BC) By Takashi Hirano (Hokkaido Univ., Japan) (Unpublished)

22 Seasonal variation in NEE (net ecosystem CO 2 exchange) in DF site NEE was positive or neutral throughout 3 years (CO 2 source). CO 2 emission was the largest in the late dry season, partly due to the shading effect by smoke from farmland fires. CO 2 emission was the largest in 2002, an El Nino year, because of dense smoke from large-scale fires. CO 2 source CO 2 sink By Takashi Hirano (Hokkaido Univ., Japan) (Unpublished)

23 Inter-site comparison of annual CO 2 balance May 2004 to May 2005, Unit: gC m -2 yr -1 Positive NEE (CO 2 source strength): BC > DF > UDF SiteGPPRENEE UDF (undrained)40004103103 DF (drained)32873724437 BC (burnt & drained)10751899824 UDF also functioned as a CO 2 source to the atmosphere. → -1.4 mm yr -1 → -6.1 mm yr -1 → -11.6 mm yr -1 Peat decomposition  Peat growth rate in Indonesia : 1–2 mm yr -1 (Sorensen 1993)  Carbon accumulation rate in Palangkaraya: 56 gC m -2 yr -1 (0.8 mm y -1 ) (Page et al. 2004) Results of peat sampling By Takashi Hirano (Hokkaido Univ., Japan) (Unpublished)

24 Effects of water table (WL) on respiration in forest RE/GPP vs. WL for UDF & DF Soil respiration vs. WL for UDF by automated chamber systems Hirano et al., Ecosystems 2008

25 GWP= CO 2 flux + CH 4 flux ×23 + N 2 O flux ×296 GWP in forest → influenced by CO 2 GWP in cropland → influenced by N 2 O : CO 2 flux : CH 4 flux ×23 : N 2 O flux ×296 Some results of greenhouse gases emission from tropical peat soil, Indonesia Central Kalimantan, Indonesia; Arai et al., unpublished

26 (3) Carbon Loss through Waterborne Carbon

27 by I Tanaka et al., Unpublished Seasonal Changes of DOC Correlation between Water Table and DOC

28 Hyper sensor for carbon dissolved in water N2ON2O N2ON2O Colored Dissolved Organic Matter (CDOM) and Dissolved Organic Carbon (DOC) for Southern Finland and the Gulf of Finland by ALI image on14 July, 2002 (Kutser et al., 2005) Hyper sensor Monitoring target 1)Dissolved Organic Carbon (DOC) 2)Dissolved Inorganic Carbon (DIC) 3)Particulate Organic Carbon (POC) 4)Colored Dissolved Organic Matter (CDOM) *Potential carbon release from peat. Indonesian rivers transfer around 10% DOC of the global riverine DOC oceanic input (Baum et al.,2007). (Example)

29 Robust MRV Systems: Water Table is Key for Measuring!

30 Water Table is Key for Peatland Ecosystem!! 1) Oxidation 2) Fire Factors 3) Tree growth and Mortality 4) DOC 30

31 31 By Wataru Takeuchi, University of Tokyo, Japan Algorism

32 32 By Wataru Takeuchi, University of Tokyo, Japan

33

34 Simulator: SimCycle-Visit for East Asia Column averaged dry air mole fraction distribution of carbon dioxide for the month of September, 2009, obtained from IBUKI observation data (unvalidated) By JAXA Satellite GOSAT “IBUKI” Senescing: CO2 Top-down satellite airplane inverse model Bottom-up field survey flux obs. process model Integrated, practical carbon budget map ・ Carbon Emission by Fire ・ Carbon Loss through Water ・ Carbon Emission by Microorganisms Degradation ・ Tree Growth/Mortality Carbon-Water Simulator

35 Biomass Carbon Soil Carbon WetDry

36 Thank you for your attention


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