The patterns and consequences of post-fire successional trajectories in Alaska’s boreal
forest
The “Generators”
- Fire severity
- Abiotic and biotic site characteristics
The consequences for
-Nitrogen cycling, carbon storage and other key ecosystem processes
-Future landscape and vegetation patterns (including biome shifts)
• 90 sites established in 2004 burns along Dalton, Taylor, and Steese Highways
• 32 intensive study sites– arranged across combinations of high-low site moisture &
high-low burn severity• 7 treeline sites• Detailed pre-fire stand data available for 14 sites• Reconstruction of pre-fire conditions at remaining sites
JFSP Study design
Dry
Wet
Low High
JFSP Study design
N
5 15 2510 20 300
V V V V V V V
Belt transect for stand structur e and tr ee cookies
V V V V V V V
S S S S S S S
S S S S S S S
O O O O O O O O OO
O O O O O O O O OO
Set aside for potential destructive sampling
N N N N N N
N N N N N N
N = Mineralization
S = SeedlingsV =Vegetation plots
O = Organic depthsSAMPLING SCHEMEFOR EACH PLOT
X X
X
XX
X =Stakes= Areas sensitive to disturbance
Belt transect for stand structur e and tr ee cookies
What drives natural post-fire seedling recruiment?
Differential sensitivity of functional groups to site characteristics and fire regime
-Spruce recruitment (as measured by post-fire seedling density) is most influenced by elevation, pre-fire spruce density, and site moisture. Fire severity (CBI) and stand age had weaker effects
-50 % of Deciduous recruitment can be explained by fire severity; also important were elevation, latitude, moisture, and distance to nearest unburned deciduous stand.
- The ratio of spruce/deciduous recruitment is driven by the relationship between deciduous and fire severity.
Important role of fire severity in “tipping” the balance between coniferous and deciduous dominance
Johnstone, Hollingsworth, Chapin, and Mack (in prep) Global Change Biology
What drives post-fire vegetation composition?
Bernhardt, Hollingsworth, Chapin, and Viereck (in prep) Journal of Vegetation Science
- Energy balance
NECB?
↓ N avail.
↓ productivity
↑[CO2]
↑ T
↑ Fire
Frequency, intensity, and area
↑[CO2]
↑ T
↑ Fire
NECB+
↓ N avail.
↓ productivity
Frequency, intensity, and area
FireN availability
• N pool size• N turnover time• Environment for decomposition• Plant species composition
– Pool size– TT– Environment– Uptake and use
Net loss of N from forest floor/organic soil =
Pre-fire forest floor N pool - Remaining N pool
[+ Ash from plants and upper layers]
[- Leaching, erosion, gaseous loss]
Calculating soil N loss
Mean offset between adv.
roots and moss across 30 unburned sites: 3.2 ±
0.3 cm
Adventitious root
Adventitious root collar to burned soil = depth of organic matter combusted
Residual organic soil depth, bulk density and [N]
N pool in missing layers = root collar depth x empirical relationships derived from unburned stands
Dry WetMoisture class
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.10
0.11
0.12
N loss (
kg
N m
-2)
• Mean =80 ± 4 g·N m-2
• 1-94 % of pre-fire organic layer N pool
Soil organic layer N loss across sites
HighLow
Burn severity
Moisture: F=0.69, P=0.41Severity:F=4.62. P=0.04M x S: F=0.19, P=0.67
• N inputs are low•Alder fixation max.•Lichen/moss norm. (<0.1 g·N m-2 yr-1)
• Mean stand age: 94 ± 5.4 yrs
• Mining N? Alder inputs? Occult N?
*
www.gina.alaska.edu
Comparing the boreal forest to the Arctic
Anaktuvuk River Fire 2007
An opportunity for synthesisbetween a fire-naïve versus a fire-experienced biome
Research Questions
• How much carbon and nitrogen was lost during the Anaktuvuk River Fire?
• Do our known relationships between seedling regeneration, vegetation composition, and site characteristics hold true for tundra fires?
Estimating pre-fire soil organic matter pools
Meristem to Mineral Soil Depth (cm)
10 15 20 25 30 35
Org
anic
Lay
er D
epth
(cm
)
5
10
15
20
25
30
Meristem to mineral soil depth (cm)
Org
anic
layer
depth
(cm
) R2=0.94, P=<0.01
Pre-fire pools and fire-driven losses of nitrogen from tundra and
taigaPools MATBlack spruce
Pre-fire O layer Mean: 280 200(g N m-2) Range: 206 to 578 50 to 429
N: 20 90
O layer N loss 33 103(g N m-2) 7to 209 30 to 180
% O layer N loss 10.4 502 to 36 1 to 94
0.0 100 200 300 400 500
Dry, highDry, lowWet, highWet, low
Pre-fire N pool (g N m-2)
N loss versus pre-fire N pool
High-Dry R2=0.61, P<0.02No relationship for other categories
All sites R2=0.86, P<0.001
Black spruce taigaMoist Acidic Tundra
0 100 200 300 400 500 600X
0
50
100
150
200
250
NLOST
N loss
(kg
N m
-2)
• 9 transects across the Anaktuvuk River fire sampled• 10 points along each transect sampled and combined
for a) mineral soil and b) organic soils• Germinated alder and spruce seedlings• Autoclaved Tanana River silt as growth substrate• Innoculated with organic or mineral soil from 9 sites (18
treatments)• Minimal fertilizer (want them to survive but not thrive)
Plant methods
Preliminary results
00.51
1.52
2.53
3.54
4.5
1 2
gro
wth
(m
m)
control
low
high
Spruce
Alder
0
1
2
3
4
5
6
1 2
grow
th (m
m) control
organic
mineral
Spruce Alder
aa
b
Conclusions• In taiga, sites with more accumulated N lost a
smaller % of total N, while sites with more N lost a larger %– Fire driven N loss reinforces landscape patterns
of N accumulation• In arctic tundra, sites with more accumulated N lost
more N – Fire smoothes landscape heterogeneity in N
accumulation• In arctic tundra, effects of mycorrhizal innoculum
on plant height growth is related to soil horizon, not fire severity