Fire and Forest Dynamics in Northern Boreal Forests
Post on 21-Jun-2015
327 Views
Preview:
DESCRIPTION
Transcript
Fire and Forest
Dynamics
in Northern Boreal
Forests
Jill JohnstoneBiology, University of Saskatchewan
Northern
boreal forest
• Conifer
dominated
• Cool soils,
slow growth &
decomposition
• Resistant to
change?
Fire and Global Change
Stocks et al. 1998
Chapin et al. 2005
Can we expect changes in
forest composition?
What are those likely to be?
Resilience and Response Dynamics
dynamic
equilibrium
directional
change
Resilience & Ecosystem Feedbacks
Dominant
species
RecruitmentInteractions
Competition, herbivory
Functional
traits
Disturbance
Black spruce
dominant
Local seed &
ResproutingSlow
growth
FIRE
Poor quality
seedbeds
(organic soil)
Slow nutrient turnover
Low competition
High moisture
High moss
Cool soils
Broadleaf
dominant
Resprouting &
Seed dispersalRapid
growthHigh quality
seedbeds
(mineral soil)
Rapid nutrient turnover
High competition
Low moisture
Low moss
Warm soils
FIRE
A. Black spruce domain B. Broadleaf forest domain
Alternate successional cycles
Johnstone et al. 2010, Can. J. Forest Research
Black spruce
dominant
Local seed &
ResproutingSlow
growth
FIRE
Poor quality
seedbeds
(organic soil)
Slow nutrient turnover
Low competition
High moisture
High moss
Cool soils
Broadleaf
dominant
Resprouting &
Seed dispersalRapid
growthHigh quality
seedbeds
(mineral soil)
Rapid nutrient turnover
High competition
Low moisture
Low moss
Warm soils
FIRE
A. Black spruce domain B. Broadleaf forest domain
Johnstone et al. 2010, Can. J. Forest Research
Alternate successional cycles
How do fire characteristics shape
patterns of forest resilience?
• Why study fire?
– Ubiquitous in western boreal region
– Sensitive to climate
– Post-fire recovery determines future forest
composition
Fire and successional
trajectories in black spruce
forests
Fire severity affects
seedbed quality
Burning of organic soils influences
patterns of post-fire recruitment
Patch effects of fire severityLow severity (organic)
– Poor seedbeds
– Recruitment requires high
seed inputs
– Favors serotinous conifers
High severity (mineral)
– Higher quality seedbeds
– Creates opportunities for
deciduous establishment
How does this influence forest
dynamics across
heterogeneous landscapes?
Fire severity and post-fire recovery
• Alaska 2004 fires
• 90 black spruce sites
• Initial stand recovery
• Environmental conditions
– Potential site moisture
– Elevation
– Potential insolation
• Pre-fire stand structure
– Stem density
– Stem basal area
• Fire severity
– Composite Burn Index (CBI)
– Residual organic layer depth
• Post-fire recruitment
– Tree seedling density
– 4 years post-fire
Field Data
Spruce seedling density
Boosted regression tree, prediction error=0.54
Johnstone et al. 2010, Global Change Biology
Deciduous seedling density
Boosted regression tree, prediction error=0.44
Johnstone et al. 2010, Global Change Biology
Relative spruce dominance:
Recovery of spruce trajectory
Boosted regression tree, prediction error=0.42
Johnstone et al. 2010, Global Change Biology
Controls on spruce forest resilience
• Severe fires reduce the
competitive advantage of spruce
and favor deciduous species
• Severe fires alter soil microclimate
• Site moisture
– Warm, dry soils favor aspen
– Severe fires are also more likely
• Young stands vulnerable to
change
Studies of fire frequency using
overlapping fires
historic fire
recent fire
overlap zones:
rapid disturbance return
image courtesy of David Milne, Yukon Gov.
0
5000
10000
15000
20000
25000
30000
35000
40000
total Picea Pinus Populus
ste
m d
en
sity (
#/h
a)
Burned at >80 yr.
Burned at <30 yr.
***
***
***
ns
Johnstone & Chapin 2006, Ecosystems
Repeat fires alter tree regeneration
Seed rain
Brown & Johnstone, unpublished
Seedling establishment
Brown & Johnstone, unpublished
How old does a stand need to be
before there is sufficient cone
production to support regeneration?
Cone Production
0
0.5
1
1.5
2
2.5
0 20 40 60 80
Tree Age
Nu
mb
er
of
Co
ne
s P
res
en
t o
n T
ree
(Lo
g1
0 s
ca
le)
n=170, p<0.001, r=0.360
n=14, p<0.001, r=0.723
Cones/tre
e (
log s
cale
)
Viglas & Johnstone, unpublished
Fire interval effects
• Repeat fires interrupt
conifer regeneration
cycles
– Reduced cone production
• Confers a regeneration
advantage to wind-
dispersed seeds
• Net effect is to shift
trajectories to deciduous
dominance
Black spruce
dominant
Organic
seedbeds
Slow growth
Low competition
High moisture
Cool soils
Slow turnover
Deciduous
dominant
Resprouting &
seed dispersal
Mineral soil
seedbeds
Rapid growth
High competition
Low moisture
Warm soils
Rapid turnover
Shifts in resilience cycles
Fire
Black spruce
dominant
Organic
seedbeds
Slow growth
Low competition
High moisture
Cool soils
Slow turnover
Deciduous
dominant
Resprouting &
seed dispersal
Mineral soil
seedbeds
Rapid growth
High competition
Low moisture
Warm soils
Rapid turnover
Shifts in resilience cycles
severe or short-interval
fire
long fire interval
Fire
Why is this important?
• Changes in forest cover affect:
– Carbon storage
– Energy and water transfer
– Wildlife and subsistence resources
– Feedbacks to future fire behavior
Fire severity and succession:
Impacts on future fire behavior
• High fire severity transforms black
spruce to deciduous forest
• Deciduous forest has lower flammability
Can fire-initiated changes create a
negative feedback to climate-driven
increases in fire activity?
ALFRESCO simulation experiment
• Spatial simulation model for boreal landscapes
• Succession influenced by fire severity
• 3 Severity Scenarios:
– Low (LSS): All fires burn with low severity (spruce trajectory)
– High (HSS): Maximum extent of high severity (decid. trajectory)
– Mix: Intermediate scenario
• High and moderate scenarios of climate warming
Area = ~ 2500 Area = ~1000
KEY:
Green & Yellow = Low Sev.
Red = High Sev. in HSS
Black = High Sev. in Mix + HSS
Cumulative area burned
High warming
Low warming
Johnstone, Rupp, et al., in review
Disturbance & climate interact
to alter black spruce resilience
tundra black spruce deciduous
dynamic
equilibrium
directional
change
Future Research
• Mechanistic understanding of plant-soil-
microbial feedbacks
• Quantifying thresholds and tipping
points
• Landscape prediction of vulnerability to
change
Conclusions
• Fire is both catalyst and driver of
change
• Critical post-fire reorganization phase
• Both frequency and severity shape future
succession
• Landscape context => vulnerability to
change
• Understanding the drivers of resilience is
key to predicting future change
Acknowledgements
Co-authors:
Carissa Brown
Terry Chapin
Teresa Hollingsworth
Michelle Mack
Mark Olsen
Scott Rupp
Ted Schuur
David Verbyla
Jayme Viglas
top related