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Webinar: Wildfire management, emissions and NDCs in the dry tropics
25 November 2020
Integrated Fire Management, prescribe...
Brazil
Area: 8,514,215 km2
About half of Brazil is covered by natural
vegetation
Ecosystems: Amazon, Caatinga, Atlantic
Fo...
• Cerrado covers almost 25% of Brazil’s total area –
• Protected areas: 8.2% Conservation Units; 4.3% Indigenous Lands
• T...
Fire regimes and wildfire impacts
• Extensive and frequent late season wildfires
• 2012: more than 60% of land use related...
• 2007 to 2010 Ibama and Funai (National Foundation for Indigenous
People) - Saving traditional knowledge and cultural and...
(Falleiro, 2011)
Meyers, 2006
Paradigm shift
Total area of indigenous lands and traditional
territories managed – 52.1%
Indigenous Land hectares
Kalunga 261,827.4
Avá-...
Methodology - Indigenous Lands
1. Systematization of indigenous and traditional knowledge of fire use
2. Fuel load maps – ...
Prescribed Burning
Fuel
management
Fruiting
Fuel
management
Zero fire
Rainy season
(January to
March)
End of rainy
season
...
Preliminary results – Indigenous Lands
Indigenous Lands Araguaia, Xerente, Funil, Kraholândia, Paresi, Utiariti, Juininha,...
Preliminary results – Indigenous Lands – evaluation of trees
Chart 01: Mortality between different fire
regimes
Chart 02: ...
Macro results – Conservation Units
Burned areas
Macro results – Conservation Units – Serra Geral do Tocantins
Fire occurrence: early, mid, late Area of the largest fire 2...
Challenges and future
• 2016 – adoption of Paris agreement
• NDC – reduce greenhouse gas emissions by 37% below 2005 level...
© Remote Sensing Solutions GmbH 2020
https://www.embrapa.br/cerrados/colecao-entomologica/bioma-cerrado
Photos: J. Franke
© Remote Sensing Solutions GmbH 2020
▪ Development of a fuel load mapping approach
▪ Direct support of the IFM
▪ Through c...
© Remote Sensing Solutions GmbH 2020
The benefit of fuel load mapping for IFM
Up-to-date geospatial information on
the fue...
© Remote Sensing Solutions GmbH 2020
What is the effect of IFM in the Cerrado?
▪ Was the fragmentation of the fire regime ...
© Remote Sensing Solutions GmbH 2020
Implementation in Google Earth Engine
Combustible Biomass model:
Using pre- and post-...
© Remote Sensing Solutions GmbH 2020
Status of prescribed burning in protected areas (2020)
Protected areas with IFM:
▪ TI...
© Remote Sensing Solutions GmbH 2020
Fragmentation of fire regime
© Remote Sensing Solutions GmbH 2020
Fragmentation of fire regime
© Remote Sensing Solutions GmbH 2020
Comparison of 21,512 hotspots in protected areas (PA) with and without IFM
2013-2020
...
© Remote Sensing Solutions GmbH 2020
Significant trend of increased EDS fires (R²=0.6) by also reduced M/LDS fires
Analysi...
© Remote Sensing Solutions GmbH 2020
Analysis of the effect of IFM on fire seasonality
EDS – MDS – LDS fires
© Remote Sensing Solutions GmbH 2020
Significant trend of reduced M/LDS BA through IFM (R²=0.64) indicates a reduction of ...
© Remote Sensing Solutions GmbH 2020
Combustible
biomass
model
EO data on
burned area
2019 Refinement of the 2006 IPCC AFO...
© Remote Sensing Solutions GmbH 2020
Given the baseline EDS vs. M/LDS shift in burned areas from the four
protected areas ...
© Remote Sensing Solutions GmbH 2020
Analysis of the effect of IFM on LDS fuel load
© Remote Sensing Solutions GmbH 2020
~0.29 t/ha accumulation of combustible biomass (2014-2020)
~total increase of 348,704...
© Remote Sensing Solutions GmbH 2020
Additional GHG mitigation potentials through sequestration
© Remote Sensing Solutions GmbH 2020
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Integrated Fire Management, prescribed burning, and mitigation potentials under NDCs in the Cerrado, Brazil

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Presented by Lara Steil (Brazilian National Center for prevention and fighting wildfire, Brazil) at webinar: "Wildfire management, emissions and NDCs in the dry tropics", on 25 November 2020

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Integrated Fire Management, prescribed burning, and mitigation potentials under NDCs in the Cerrado, Brazil

  1. 1. Webinar: Wildfire management, emissions and NDCs in the dry tropics 25 November 2020 Integrated Fire Management, prescribed burning, and mitigation potentials under NDCs in the Cerrado, Brazil Lara Steil – lara.steil@ibama.gov.br Coordinator of Interagency and Burning Control Department National Centre for Prevention and Fighting Fire – Prevfogo – Brazil Jonas Franke – franke@rssgmbh.de Managing Director of RSS - Remote Sensing Solutions GmbH, Munich
  2. 2. Brazil Area: 8,514,215 km2 About half of Brazil is covered by natural vegetation Ecosystems: Amazon, Caatinga, Atlantic Forest, Pampa, Pantanal and Cerrado (Hardesty et al, 2005)
  3. 3. • Cerrado covers almost 25% of Brazil’s total area – • Protected areas: 8.2% Conservation Units; 4.3% Indigenous Lands • The richest biodiversity savanna in the world • Complex vegetation typified as a fire-prone ecosystem • Mosaic of physiognomies: from grasslands to woodland and closed forest • Savanna wetlands and gallery forests are also included
  4. 4. Fire regimes and wildfire impacts • Extensive and frequent late season wildfires • 2012: more than 60% of land use related GHG emissions (fire and deforestation) emerged from Cerrado • Lack of a program for fire protection • Policies and techniques for total fire suppression prevailing • Biodiversity loss and increasing GHG • Losses of traditional and indigenous knowledge
  5. 5. • 2007 to 2010 Ibama and Funai (National Foundation for Indigenous People) - Saving traditional knowledge and cultural and ecological parameters of use of fire which are well known in indigenous lands (Irantxe, Myky, Paresi, Tirecatinga e Utiariti); • Monthly calendar showing the key natural resources and associated potential damage caused by fire according to the period of the year (flowering, fruiting, nesting, reproduction),
  6. 6. (Falleiro, 2011)
  7. 7. Meyers, 2006 Paradigm shift
  8. 8. Total area of indigenous lands and traditional territories managed – 52.1% Indigenous Land hectares Kalunga 261,827.4 Avá-Canoeiro 38,000.0 Bakairi 61,405.5 Juininha 70,537.5 Paresi/Formoso 583,336.0 Utiariti 412,304.2 Xerente/Funil 183,245.9 Kraholândia 302,533.4 Apinajé 141,904.2 Araguaia 1,358,499.5 Porquinhos 79,520.3 Governador 41,643.8 Araribóia 413,288.0 Krikati 144,775.8 Kadiweu 538,535.8 TOTAL 4,631,357.1 2 3 10 20 24 36 0 10 20 30 40 2014 2015 2016 2017 2018 *2019 Conservation Units
  9. 9. Methodology - Indigenous Lands 1. Systematization of indigenous and traditional knowledge of fire use 2. Fuel load maps – community validation 3. Planning of prescribed burnings: definition of objectives and priority areas for conservation – community participation 4. Implementation: preparation (communities), registration (burning plans) and execution (evaluation of burning factors and techniques) 5. Follow-up: evaluation and monitoring of the effects of burning
  10. 10. Prescribed Burning Fuel management Fruiting Fuel management Zero fire Rainy season (January to March) End of rainy season (April and May) Beginning of dry season (June and July) Dry season (August to December) Early prescribed fire Late prescribed fire WildfireMid prescribed fire Objectives
  11. 11. Preliminary results – Indigenous Lands Indigenous Lands Araguaia, Xerente, Funil, Kraholândia, Paresi, Utiariti, Juininha, Bakairi and traditional Quilombola territory Kalunga, 2002-2014: without management 2015-2016: transitional period 2017-2018: with management
  12. 12. Preliminary results – Indigenous Lands – evaluation of trees Chart 01: Mortality between different fire regimes Chart 02: Mortality between different periods of prescribed burning
  13. 13. Macro results – Conservation Units Burned areas
  14. 14. Macro results – Conservation Units – Serra Geral do Tocantins Fire occurrence: early, mid, late Area of the largest fire 2010 - 2017
  15. 15. Challenges and future • 2016 – adoption of Paris agreement • NDC – reduce greenhouse gas emissions by 37% below 2005 levels by 2025 and 43% below 2005 levels by 2030 • Multistakeholders: government, private sector, communities, indigenous and traditional people • Improve integrated fire management • Impact of fires on GHG emissions / fire emission baseline and estimate • Development of three government level competence • National policy on Integrated Fire Management • Coordination among the agencies
  16. 16. © Remote Sensing Solutions GmbH 2020 https://www.embrapa.br/cerrados/colecao-entomologica/bioma-cerrado Photos: J. Franke
  17. 17. © Remote Sensing Solutions GmbH 2020 ▪ Development of a fuel load mapping approach ▪ Direct support of the IFM ▪ Through capacity-building activities, the approach could be established as an operational tool of IFM in the Cerrado. ▪ National and state level authorities have successfully institutionalized the approach and it was incorporated into IFM policies in Brazil (e.g. the Brazilian IFM National Fire Policy and the Cerrado Prevention and Control Action Plan (PPCerrado). Prevention, control and monitoring of wildfires in the Cerrado Photo: A.A. Hoffmann
  18. 18. © Remote Sensing Solutions GmbH 2020 The benefit of fuel load mapping for IFM Up-to-date geospatial information on the fuel condition, fuel load and fuel connectivity that helps to plan and prioritize EDS prescribed burning in the field, but also to evaluate the effect of IFM strategies.
  19. 19. © Remote Sensing Solutions GmbH 2020 What is the effect of IFM in the Cerrado? ▪ Was the fragmentation of the fire regime successful (pyrodiversity)? ▪ Could IFM, and particularly increased EDS prescribed burning, change the seasonality of fire? ▪ If yes, did that lead to a reduction of the M/LDS burned areas? ▪ Is there a change in the amount of biomass/combustible fuel in the areas with IFM? ▪ Applying the IPCC approach, could IFM operations abate GHG emissions?
  20. 20. © Remote Sensing Solutions GmbH 2020 Implementation in Google Earth Engine Combustible Biomass model: Using pre- and post-fire biomass samples (Universidade de Brasília) Multiple linear regression with an adjusted R2 of 0.91 (p<0.001, standard error = 0.059): Mb=0,2193+(0,2825*NPV)+(-0,1964*Soil)
  21. 21. © Remote Sensing Solutions GmbH 2020 Status of prescribed burning in protected areas (2020) Protected areas with IFM: ▪ TI Xerente ▪ Estacao Ecologica Serra Geral Do Tocantins ▪ Parque Nacional Da Chapada Das Mesas ▪ Parque Estadual Do Jalapão Protected areas without IFM: ▪ Área De Proteção Ambiental Do Rio Preto ▪ Área De Proteção Ambiental Bacia Do Rio Pandeiros ▪ TI Kanela ▪ Área De Proteção Ambiental Bacia Do Rio De Janeiro
  22. 22. © Remote Sensing Solutions GmbH 2020 Fragmentation of fire regime
  23. 23. © Remote Sensing Solutions GmbH 2020 Fragmentation of fire regime
  24. 24. © Remote Sensing Solutions GmbH 2020 Comparison of 21,512 hotspots in protected areas (PA) with and without IFM 2013-2020 Analysis of the effect of IFM on fire seasonality
  25. 25. © Remote Sensing Solutions GmbH 2020 Significant trend of increased EDS fires (R²=0.6) by also reduced M/LDS fires Analysis of the effect of IFM on fire seasonality EDS – MDS – LDS fires
  26. 26. © Remote Sensing Solutions GmbH 2020 Analysis of the effect of IFM on fire seasonality EDS – MDS – LDS fires
  27. 27. © Remote Sensing Solutions GmbH 2020 Significant trend of reduced M/LDS BA through IFM (R²=0.64) indicates a reduction of -66%. EDS burned areas were increased by 69%. Analysis of the effect of IFM on burned areas MCD64A1 MODIS/Terra+Aqua Burned Area Monthly Dataset
  28. 28. © Remote Sensing Solutions GmbH 2020 Combustible biomass model EO data on burned area 2019 Refinement of the 2006 IPCC AFOLU Guidelines https://www.ipcc-nggip.iges.or.jp/public/2019rf/pdf/4_Volume4/19R_V4_Ch02_Generic%20Methods.pdf Calculating non-CO2 GHG mitigation potentials (IPCC) EDS and M/LDS comb. factor Emission factor Yearly GHG emissions: Lfire total = Lfire EDS + Lfire M/LDS Accounted for CH4 & N2O
  29. 29. © Remote Sensing Solutions GmbH 2020 Given the baseline EDS vs. M/LDS shift in burned areas from the four protected areas with IFM, the following non-CO2 GHG abatement potential through IFM is estimated: • Abatement potential of all PAs: 1.71 MtCO2-e over a period of six years (0.29 MtCO2-e yr-1) • Abatement potential for the whole Cerrado: 17.78 MtCO2-e over a period of six years (2.96 MtCO2-e yr-1) GHG mitigation potentials (IPCC approach)
  30. 30. © Remote Sensing Solutions GmbH 2020 Analysis of the effect of IFM on LDS fuel load
  31. 31. © Remote Sensing Solutions GmbH 2020 ~0.29 t/ha accumulation of combustible biomass (2014-2020) ~total increase of 348,704 t in the four protected areas ~increase in stored C of 165,635 t Analysis of the effect of IFM on LDS fuel load R²=0.88
  32. 32. © Remote Sensing Solutions GmbH 2020 Additional GHG mitigation potentials through sequestration
  33. 33. © Remote Sensing Solutions GmbH 2020

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