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Spatial and temporal determinants of anthropogenic forest fires in the Amazon

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Forest fires are becoming more frequent and larger, and most are triggered by human activities. Carbon emissions from fire-related forest degradation are growing in importance as emissions from deforestation drop, so effectively measuring and monitoring forest fires is a crucial component for the success of REDD (Reducing Emissions from Deforestation and forest Degradation). In this presentation, Ane Alencar from IPAM explains their research on forest fires, and the implications of fires for forest degradation and future carbon emissions.

Ane Alencar gave this presentation on 8 March 2012 at a workshop organised by CIFOR, ‘Measurement, Reporting and Verification in Latin American REDD+ Projects’, held in Petropolis, Brazil. Credible baseline setting and accurate and transparent Measurement, Reporting and Verification (MRV) of results are key conditions for successful REDD+ projects. The workshop aimed to explore important advances, challenges, pitfalls, and innovations in REDD+ methods — thereby moving towards overcoming barriers to meeting MRV requirements at REDD+ project sites in two of the Amazon’s most important REDD+ candidate countries, Peru and Brazil. For further information about the workshop, please contact Shijo Joseph via s.joseph (at) cgiar.org

Publicada em: Educação, Tecnologia, Negócios
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Spatial and temporal determinants of anthropogenic forest fires in the Amazon

  1. 1. Spatial and Temporal Determinants ofAnthropogenic Forest Fires in the Amazon: implications for forest degradation and future carbon emissions Ane Alencar, Gregory Asner, Daniel Zarin, Francis Putz
  2. 2. In the past • Forest fires were rare and mostly driven by extreme drought events • Ignition sources were mostly natural and the forest was more resistant to fire Today• Forest fires are becoming more frequent, larger and perhaps mostly driven by anthropogenic changes in landscape than climatic events• Most of forest fires are anthropogenic, caused by escaped fires from human activities
  3. 3. Understanding forest fire(surface or understory fires) 1. Tracking forest fire history (Learn from past fire events) 2. Understand changes in fire regime (Spatial and temporal) 3. Estimate regional behavior of forest fires (Build the relationship with climate, land use, landscape structure, etc)
  4. 4. DenseStudy sites Open Transitional
  5. 5. Part 1 Landsat bands CLAS-BURNMapping landscape PV, NPV, Shade Reflectance bands forest burn scars (PV-NPV)-Shade) Iso-Data (PV-NPV)+Shade) (clouds and defor. Mapping) •Development of a new index called Burn Scar Index (BSI) BSI image Forest mask •This index was based on an automatic calibration and sub-pixel analysis Overlay routine called CLAS-BURN, based on CLAS. Masked BSI image •CLAS* stands for Carnegie Landsat Analysis System developed by the fire scar Asner Lab thresholds and filtering FinalReference:* Asner, G. P., M. Keller, R. Pereira, J. C. Zweede, and fire scar mapJ. N. M. Silva. 2004. Canopy damage and recovery followingselective logging in an Amazon forest: Integrating field and satellitestudies. Ecological Applications 14:280-298.
  6. 6. photosynthetic vegetation (PV) non-photosynthetic veg. (NPV) Shade/Burn (SB) R:SB, G:PV, B:NPV Burn Scar Index (BSI) Burn Scar map Burned forest accuracy: Dense forest 0.89; Open forest 0.79; Transitional forest 0.88
  7. 7. Burn Scar Index for unburned forest and old and recent burns burned
  8. 8. Part 2 Changing fire regimes Burn Extent By forest type Average Average % of total % of forest Forest area annual annual forest area (ha)* burned deforestation area deforested area (ha) burnedDense 2,274,133 19,932 29,393 15% 29%Open 2,324,883 104,711 62,821 44% 54%Transitional 1,369,228 80,189 27,901 41% 50%
  9. 9. Fire sizesForest types have distinct firebehavior in terms of size and totalarea burned:Majority of Dense forest fires scarsare small (< 100 ha)In contrast to transitional forest wheremost of the fire scars are largeLarge fires also burned more area inopen and transitional forestsFires between 100- 1000 ha in sizeburn in average about the same areaeach year in all forest types
  10. 10. Fire frequencyMost of the area burned was affected but 1 fire during the period
  11. 11. Dense Fire intervalFor the area that burned more than two times: Fire interval for the dense forest appear Open to be every 5 to 6 years, coincident with ENSO Fire interval for transitional forest have a higher return after 2 or 3 years, fuel limitation Transitional
  12. 12. DenseFire SeasonFire season in the 3 Openregions are getting aboutone month late Transitional
  13. 13. Fire intensity and effectsRelationship between frequency and canopy cover
  14. 14. Burn frequency Impacts of burn frequency in forest 0 structure 3*Explains 65% of variation
  15. 15. Part 3 Fate of burned forest 19 to 38% of the deforested area was burned 38 to 48% of the burned area was deforested % of total % of forest % of total area burned area Forest area area deforested that that was (ha)* deforested was burned deforestedDense 2,274,133 29% 19% 38%Open 2,324,883 54% 39% 48%Transitional 1,369,228 50% 38% 46%
  16. 16. Relatioship with forest Dense clearings Fires penetrate deeper in Transitional forests than the other forest types Open 90% of the area burned is within 5 km from a clearing The highest frequencies also happen within 1 km from a forest edge Transitional
  17. 17. Extrapolating results and creating fire probabilities for wet, average and dry years
  18. 18. Forest firesin 3 distinct climate conditions
  19. 19. Fire probabilities based on PAW and fragmentation for wet, average and dry years Some of the areas (blue circle) already showing influence of fragmentation in changing the likelihood of fire in average rainfall years, and even in wet years. These areas are believed to have reached the tipping point where fragmentation has played a more important role to the forest fire occurrence than climate. The dry years fire probability map indicate the areas under higher risk of forest fires, where forest is flammable due to extreme drought and high ignition sources probabilities.
  20. 20. Estimated commited CO2 emissions from deforestation and forest fires for the three forest types during the last 24 years Forest fire-driven committed CO2 emissions2 Deforestation (Tg yr-1) Forest types -driven CO2 Average emissions1 annual area Average (Tg yr -1) burned Wet years years Dry years Dense 17.6 6.0 0.1 2.4 14.7 Open 27.6 23.0 3.7 15.7 48.8 Transition 13.8 19.9 3.6 12.2 40.9 59.0 48.8 7.4 30.2 104.31 The CO2 emissions for each forest type were calculated using the Saatchi et al. (2007) biomass map, in which the average biomass value for each vegetation type wasconverted to Carbon and multiplied by the annual area deforested, and then converted to CO2.2 The committed CO2 emissions from forest fires was based on the average tree mortality due to forest fires reported on literature (Alencar et al 2006), not including yet thereleased emissions during the fire itself.
  21. 21. Estimated area at risk of burning,area burned and CO2 emissions byforest type and climatic conditions for the Brazilian Amazon Area total by Estimated areaForest forest type at risk of burning Estimated area burned Estimated emissionType (thousand (thousand km2) (thousand km2) (Pg CO2 yr-1) km2) WET AVE DRY WET AVE DRY WET AVE DRYDense 1,783.8 2.4 21.3 160.3 0.3 2.2 6.1 0.01 0.07 0.18Open 884.5 4.5 35.6 121.3 1.6 10.2 22.3 0.04 0.22 0.49Transitional 504.7 3.1 13.5 81.8 1.6 5.5 23.5 0.04 0.14 0.58Total 3,172.9 10.0 70.4 363.5 3.5 18.0 51.9 0.08 0.43 1.25 The estimated area burned can be approximately the same in average rainfall years than the average annual deforestation rates during the last decade.The estimated area burned is the portion of the estimated area under risk of burn that is located up to 5km from forest clearings
  22. 22. Main results• (1) severe droughts are the main temporal determinant of forest fires having overall emissions that were 76% higher than average deforestation emissions;• (2) although, since these are not wildfires but escaped fires from anthropogenic land use sources, the spatial distribution of these fires revealed a pattern where ~90% of the area burned occurs within 10 km of official roads, 1-2km of deforested clearings, and within highly fragmented areas;• (3) the spatial and temporal characteristics of ENSO fires disproportionate impact dense forests;• (4) escaped forest fire emissions are historically large, especially in ENSO years, and growing in importance as deforestation emissions drop and escaped fire emissions increase, associated with increasing importance of small slash-and-burn clearings
  23. 23. Thank you Academic Support Funding support NSF – DDRI Dan Zarin, Jack Putz, Greg Asner, Wendell NSF DEB-0410315 Cropper,Charles Wood, NASA NESSF ProgramDaniel Nepstad, Paulo Brando, Jennifer Balch and Tropical Conservation and Development Claudia Stickler, Mike Coe Program -TCD Compton Foundation Amazon Conservation Leadership Initiative – ACLI Moore Foundation Florida-Brazil Program