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

1. Spatial and Temporal Determinants of
Anthropogenic Forest Fires in the Amazon:
implications for forest degradation and future
carbon emissions
Ane Alencar, Gregory Asner,
Daniel Zarin, Francis Putz

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. 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. Dense
Study sites
Open
Transitional

5. Part 1 Landsat
bands
CLAS-BURN
Mapping 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
Final
Reference:* Asner, G. P., M. Keller, R. Pereira, J. C. Zweede, and fire scar map
J. N. M. Silva. 2004. Canopy damage and recovery following
selective logging in an Amazon forest: Integrating field and satellite
studies. Ecological Applications 14:280-298.

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. Burn Scar Index for unburned forest
and old and recent burns burned

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) burned
Dense 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. Fire sizes
Forest types have distinct fire
behavior in terms of size and total
area burned:
Majority of Dense forest fires scars
are small (< 100 ha)
In contrast to transitional forest where
most of the fire scars are large
Large fires also burned more area in
open and transitional forests
Fires between 100- 1000 ha in size
burn in average about the same area
each year in all forest types

10. Fire frequency
Most of the area burned was affected but 1
fire during the period

11. Dense
Fire interval
For 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. Dense
Fire Season
Fire season in the 3 Open
regions are getting about
one month late
Transitional

13. Fire intensity and effects
Relationship between frequency and canopy cover

14. Burn frequency
Impacts of burn frequency in forest 0
structure
3
*Explains 65% of variation

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 deforested
Dense 2,274,133 29% 19% 38%
Open 2,324,883 54% 39% 48%
Transitional 1,369,228 50% 38% 46%

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. Extrapolating results and creating
fire probabilities
for wet, average and dry years

18. Forest fires
in 3 distinct
climate
conditions

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. 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 30.2 104.3
1 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 was
converted 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 the
released emissions during the fire itself.

21. Estimated area at risk of burning,
area burned and CO2 emissions by
forest type and climatic conditions
for the Brazilian Amazon
Area total by Estimated area
Forest forest type at risk of burning Estimated area burned Estimated emission
Type (thousand (thousand km2) (thousand km2) (Pg CO2 yr-1)
km2) WET AVE DRY WET AVE DRY WET AVE DRY
Dense 1,783.8 2.4 21.3 160.3 0.3 2.2 6.1 0.01 0.07 0.18
Open 884.5 4.5 35.6 121.3 1.6 10.2 22.3 0.04 0.22 0.49
Transitional 504.7 3.1 13.5 81.8 1.6 5.5 23.5 0.04 0.14 0.58
Total 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. 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. Thank you
Academic Support Funding support
NSF – DDRI
Dan Zarin, Jack Putz, Greg Asner, Wendell
NSF DEB-0410315
Cropper,Charles Wood,
NASA NESSF Program
Daniel 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