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Quantifying Fire Severity and Carbon and Nitrogen Pools and Emissions in Alaska's Boreal Black Spruce Forest

Material Information

Title:
Quantifying Fire Severity and Carbon and Nitrogen Pools and Emissions in Alaska's Boreal Black Spruce Forest
Creator:
Boby, Leslie A
Place of Publication:
[Gainesville, Fla.]
Publisher:
University of Florida
Publication Date:
Language:
english
Physical Description:
1 online resource (57 p.)

Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Interdisciplinary Ecology
Committee Chair:
Schuur, Edward A.
Committee Members:
Mack, Michelle C.
Johnstone, Jill
Graduation Date:
12/14/2007

Subjects

Subjects / Keywords:
Interdisciplinary Ecology -- Dissertations, Academic -- UF
alaska, boreal, burn, carbon, fire, nitrogen, wildfire
Organic soils ( jstor )
Fire severity ( jstor )
Combustion ( jstor )
Genre:
Electronic Thesis or Dissertation
born-digital ( sobekcm )
Interdisciplinary Ecology thesis, M.S.

Notes

Abstract:
Fire severity can be defined as the amount of biomass combusted by wildfire. Stored carbon (C) and nitrogen (N) are emitted into the atmosphere as wildfires consume vegetation and soil organic layers, thus C and N emissions should be related to fire severity. Since boreal forests store 30% of the world's terrestrial C and are subject to high-intensity, stand-replacing wildfires, it is critical to be able to estimate C fluxes from wildfires. Furthermore, quantifying fire severity is important for predicting post-fire vegetation recovery and future C sequestration. We re-constructed pre-fire organic soil layers and quantified fire severity levels from the 2004 wildfires in Interior Alaska with the adventitious root height (ARH) method. We tested the ARH method in unburned stands and by comparing our reconstructed values in burned stands with actual pre-fire measurements. We found that ARH correlated to organic soil height in unburned stands (with a small offset of 3 cm). We measured organic soil (using the ARH method) and stand characteristics in boreal black spruce forest and estimated the amount of soil and canopy biomass consumed by fire. We compared these results to the composite burn index (CBI), a standardized visual method, which has not been widely used in the boreal forest. CBI assessments were significantly related to our ground and canopy fire severity estimates. We calculated C and N pools using C and N concentration and bulk density estimates from soils sampled in burned and unburned stands. We conclude that the ARH method can be used to reconstruct pre-fire organic soil depth, C and N pools and to assess fire severity. Furthermore, CBI shows promise as a way of estimating fire severity quickly and is a reasonably good predictor of biomass and soil C loss. ( en )
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (M.S.)--University of Florida, 2007.
Local:
Adviser: Schuur, Edward A.
Statement of Responsibility:
by Leslie A Boby.

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright Boby, Leslie A. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Classification:
LD1780 2007 ( lcc )

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LIST OF TABLES


Table page

3-1 Post-fire soil organic horizons' mean depth, bulk density (pb), C and N
con centration ...................................... ......................................................4 5

3-2 Soil characteristics by horizon for 28 unburned sites. ...................................................... 45

3-3 Soil organic layers, tree canopy and ecosystem mass and C combustion as well as C
em missions com pared to CBI scores .............................................................................. 46









weak, on the whole, it may be that there is not that much canopy combustion variability to

capture.

Interestingly enough, our canopy and organic soil combustion loss estimates were not

significantly related to each other, which is consistent with the different kinds of combustion.

While canopy combustion is usually burned during active, high-intensity fire (with visible

flames), organic soil mostly burns during slower, smoldering combustion for often-long periods

of time (days or months).

Other Methods of Measuring Fire Severity and Emissions

Organic Soil

Several studies have used the amount of organic soil consumed or remaining after a fire, by

weight, depth or visual class, as a method of measuring fire severity, however, these

measurements were not linked to pre-fire organic soil amounts. There was no standardized

method of quantifying organic soil consumption as a parameter for fire severity, in the literature.

Most studies classified fire severity into unburned, low, moderate and severe categories based

qualitatively on the amount of organic soil consumed (Turner et al. 1997, Wang et al. 2001, de

Groot et al. 2004, Greene et al. 2004, Johnstone and Kasischke 2005, Johnstone and Chapin

2006). Conversely, other studies assessed fire severity by measuring post-fire organic soil depth.

Bergner et al. 2004 stated that a mean post-fire SOL depth of 7.5 cm was a low severity class,

while 2.1 cm could be considered a severe bum. Areseneault (2001) used a combination of the

thickness of the remaining humic layer and canopy consumption measurements to estimate fire

severity, however this method cannot assess those sites with little to no post-fire organic soil.

In assessing these other fire severity methods, it is important to note that measuring post-

fire organic soil is very different from estimating combustion. Post-fire SOL depth is linked to

post-fire successional vegetation trajectories, however, it does not indicate how much matter was

50









Tree Biomass, Stand Structure and Combustion

Besides our soil measurements, we also characterized forest structure at the burned and

unburned sites. We measured the diameter of trees at breast height (DBH; 1.4 m) for all trees

greater than or equal to 1.4 m tall and basal diameter for trees less than 1.4 m tall that were

rooted within six, 2 x 5 m subplots along the transects. Fallen trees were included in this census

if we estimated that they had been rooted in the subplot. We used these values to calculate tree

density, basal area and aboveground biomass (excluding the bole). We visually estimated % fire

consumption in five classes (0, 25, 50, 75 or 100 percent) of four components of the tree canopy:

cones, needles, fine branches and coarse branches. To calculate pre-fire biomass of canopy

(excluding tree bole) components, we grouped trees into three diameter and height classes and

applied allometric equations that predicted standing dry biomass from DBH of individual trees.

Classes consisted of 1) DBH greater than 2.7 cm and height greater than 1.4 m (Mack et al. In

Press), 2) DBH less than 2.7 cm and height greater than 1.4 m (M.C. Mack, unpublished data)

and 3) height less than 1.4 m (M.C. Mack, unpublished data).

We combined the visual estimates of% consumption times the pre-fire biomass to

determine canopy biomass fire consumption (in g of dry mass) for each tree. Moreover, we

calculated canopy C and N pools and subsequent emissions for each canopy component. We

used 50% C concentrations for estimating C biomass and 0.4% N for cones, fine branches and

coarse branches and 1% N for needles (Gower et al 2000).

Unburned Sites

In addition to soil and tree measurements in burned sites, we measured soil characteristics

and forest structure in 28 unburned sites using an identical experimental design. Since we

measured ARH in burned sites as a proxy for pre-fire organic soil depth, we also measured ARH

in relation to the surface of the green moss at the tree bases (Question 1). We measured SOL









LIST OF FIGURES


Figure pe

2-1 Map of interior Alaska, including a map of the areas burned by wildfire in 2004 and
stu d y site s ........................................................................... 2 5

3-1 Frequency, mean and horizon depths of post-fire organic soils at burned sites ...............36

3-2 Mean soil organic nitrogen and carbon pools in post-fire soil organic layers by
horizon and depth class .................. ......................................... ... ........ 37

3-3 Percent frequency of sites and tree density in basal area classes across 38 sites
bu rn ed in 2 004 .. .................................................................................3 8

3-4 Frequency of 28 unburned sites among 9 adventitious root height depth offset
classes.......................................................... ...................................3 9

3-5 Depth of soil organic horizons at randomly located points compared to depths at tree
base points across 38 sites burned in 2004. ............................................ ............... 40

3-6 Difference between soil organic layer depths at randomly located sampling points
and depth at tree base points compared to mean tree density/ha...................................41

3-7 Total soil organic layer depth compared to soil horizon depth and horizon depth as
percent of total depth.. ............................ ..... .. .. .. ........ .. ............42

3-8 Mean carbon (C) emissions and percent of total C combustion by post-fire soil
organic lay er depth classes......................................................................... .................. 43

3-9 Mean nitrogen (N) emissions and percent of total N combustion for four post-fire
soil organic layer depth classes across 38 burned sites.................... ............ ............... 44









Horizon Depths in Relation to Total Organic Soil Depth

We used the ARH measurements to estimate pre-fire SOL depth at the tree bases within

the intensive burned sites. Therefore pre-fire SOL depth is equal to post-fire organic soil depth

plus ARH and a correction factor of 3.2 cm to account for displacement in location of uppermost

roots relative to the top of the green moss layer, as determined from the unburned stands (see

results, section III-B). After estimating pre-fire depth using the adventitious method, we

estimated pre-fire depths of each individual horizon (question 4).

Since we measured SOL height in the unburned sites, we compared those sites' individual

horizon depths to the total SOL depth (question 4) and other forest stand structural variables (tree

density, BA, etc.). We examined the relationship between total organic soil depth and each

individual horizon from the 28 unburned sites and found that green moss (GM) was a constant

depth for all points, while brown moss (BM), fibric (F) and humic (H) horizons were generally

constant proportions (See results, section III-E). In other words, green moss was a similar

thickness no matter how deep the organic soil, while the other horizons varied as a constant

proportion of overall organic matter thickness. Consequently, all of the other horizons (BM, F

and H) were estimated as a proportion of the total mean depth and equaled 14, 46 and 29 percent

respectively. These proportions and the GM constant were applied to the re-constructed pre-fire

organic soil depth. The reconstructed horizon depths were then used to calculate pre-fire C and N

pools as well as combustion losses.

Pre- and Post-Fire C and N Pools

To quantify pre and post-fire C and N pools, we used values from our burned and

unburned sites and accounted for post-fire differences (question 6). To start with, we calculated

mean site values for each horizon's p b and percent C and N from destructively harvested cores









the fire severity varied among and within the fires from low to high. Unburned sites were

chosen from those described in Hollingsworth et al. (2006) and were selected to correspond to

general locations and edaphic conditions of the burned sites.

Experimental Design and Measurements

In June 2005, we established plots to estimate pre and post fire soil organic carbon and

nitrogen pools in 38 burned sites for intensive study. The experimental unit was a 30 m x 30 m

square plot which was sampled with a 1 x 30 m belt transect. Measurements in the plots included

post-fire organic soil depth, carbon (C) and nitrogen (N) pools; tree density, basal area (BA) and

canopy consumption. As part of a broader study, post-fire vascular plant species cover and

composition, and tree seed rain and seedling recruitment were also measured in these plots.

Identical belt transects were established in adjacent unburned forest stands in the summer of

2006 in order to obtain the values necessary to reconstruct pre-fire soil C and N pools. These

sites are referred to as 'burned' and 'unburned,' respectively in this paper.

Patterns of Post-Fire Soil Organic Matter

Across all burned sites, combustion ranged from low, wherein a large proportion of the fibric

or upper duff layer had not burned, to high, where the fibric layer was completely combusted and

the humic or lower duff layer was partially or fully combusted (Rowe et al 1983). Within these

sites, depth of remaining soil organic layers (SOL) were measured at 11 randomly selected

points on a transect in order to characterize site-wide post-fire SOL. At each point, we measured

the depth of each of the following horizons: dead moss (undecomposed or slightly decomposed

dead moss), fibric (moderately decomposed organic matter with more roots than moss or Oe

horizon) and humic (highly humified or decomposed organic matter or the interface between the

humic horizon and the A horizon) down to the mineral soil horizon (Canadian Agricultural

Services Coordinating Committee 1988, Soil Survey Staff 1998, Neff et.al. 2005).









A





I


Is
15


0
H-








0-
IM


MDD


1 iaoo

@,^Q


I I
03 5J.I- 10 10.0-15 1 .01-20
BU, AMNi Ea'


Figure 3-3. Percent frequency of sites and tree density in basal area classes across 38 sites burned
in 2004. A) Frequency of sites. B) Tree density per hectare.


>2A









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

QUANTIFYING FIRE SEVERITY AND CARBON AND NITROGEN POOLS AND
EMISSIONS IN ALASKA'S BOREAL BLACK SPRUCE FOREST

By

Leslie A. Boby

December 2007

Cochair: Edward A. G. Schuur
Cochair: Michelle Mack
Major: Interdisciplinary Ecology

Fire severity can be defined as the amount of biomass combusted by wildfire. Stored

carbon (C) and nitrogen (N) are emitted into the atmosphere as wildfires consume vegetation and

soil organic layers, thus C and N emissions should be related to fire severity. Since boreal forests

store 30% of the world's terrestrial C and are subject to high-intensity, stand-replacing wildfires,

it is critical to be able to estimate C fluxes from wildfires. Furthermore, quantifying fire severity

is important for predicting post-fire vegetation recovery and future C sequestration. We re-

constructed pre-fire organic soil layers and quantified fire severity levels from the 2004 wildfires

in Interior Alaska with the adventitious root height (ARH) method. We tested the ARH method

in unburned stands and by comparing our reconstructed values in burned stands with actual pre-

fire measurements. We found that ARH correlated to organic soil height in unburned stands

(with a small offset of 3 cm). We measured organic soil (using the ARH method) and stand

characteristics in boreal black spruce forest and estimated the amount of soil and canopy biomass

consumed by fire. We compared these results to the composite bur index (CBI), a standardized

visual method, which has not been widely used in the boreal forest. CBI assessments were

significantly related to our ground and canopy fire severity estimates. We calculated C and N









Tree Biomass, C and N Pools and Combustion

We used allometric biomass equations to calculate pre-fire canopy biomass and combined

these with visual combustion estimates to calculate canopy biomass consumed by fire. Mean

pre-fire total canopy biomass throughout all sites was 8,686 1,080 kg/ha (mean 1 SE).

Conversely, canopy biomass losses were 6,618 960 kg/ha (mean 1 SE), with a mean

proportional consumption across all sites of 64% 4 (mean 1 SE). We did not include the bole

in our measurements since it was almost always charred or black from ash, regardless of the

severity of the fire, and therefore difficult to visually estimate consumption. This likely results in

an underestimate of canopy consumption.

Assuming a general canopy C concentration of 50% and N concentrations of 1% for

needles and 0.4% for cones, fine and coarse branches, pre-fire C and N biomass mean values

were 0.43 0.05 kg/m2 and 0.0054 0.001 kg/m2 (mean SE) and ranged from 0.001 to 1.21

kg/m2 for C and 0.0001 to 0.01 kg/m2 for N. Conversely, C and N losses from combustion were

0.37 0.05 kg/m2 and 0.005 0.0006 kg/m2 (mean SE), respectively, and ranged from 0.001

to 1.16 kg C/m2 and <0.0001 to 0.014 kgN/m2 (figure 3-9 a and b). These canopy C and N

combustion values are equivalent to mean canopy losses of 80.2% + 2.5 and 80.6 % 2.7

respectively.

CBI and Combustion Losses

We compared our organic soil and canopy combustion estimates with CBI scores from

each site (Question 5). We evaluated the following CBI scores in relation to our measurements:

total (a total site value), overstory (upper and mid-canopy trees and tall shrubs), understory

(substrate and vascular plants) and substrate (soil organic layers and litter). CBI scores range

from 1 (low severity) to 3 (high severity) and mean total CBI scores were 2.3 0.07 (mean 1









2004, Purdon et al. 2004) and 3) remote sensing, such as Landsat or aerial photography, that

combines reflectance from remaining canopy and ground layers (Bigler et al. 2004, Epting and

Verbyla 2005, Roy et al. 2006). Within most of these studies, organic soil and canopy

consumption were visually estimated and some of these studies used more than one method to

estimate fire severity. Subsequently, these estimates of fire severity were used as a parameter for

predicting future change in canopy and understory composition, or for quantifying carbon fluxes.

All of these methods are based on surveying post-fire conditions. The Composite Burn Index

(CBI) has been developed as a standardized visual estimate method of measuring fire severity

within the United States that combines information on soil and canopy combustion together (Key

and Benson 2005). CBI was developed in the continental United States but has not been

extensively tested for its applicability to boreal systems. Fire severity levels are often based on

visual combustion estimates, but in order to estimate the proportion of biomass consumed by

fire, it is necessary to estimate the pre-fire biomass. In other words, in order to consistently

calculate how much was lost during the fire, it is necessary to know or estimate what was there

before the fire.

In our study, we tested a method for determining pre-fire conditions and subsequent

combustion losses by measuring post-fire forest stand conditions. In particular, we wanted to

discover if a method of measuring adventitious root height on black spruce boles could be used

to: 1) reconstruct pre-fire organic soil height, 2) quantify pre and post-fire carbon and nitrogen

pools, and 3) constrain wildfire organic soil combustion estimates. We used comparisons

between burned and unburned black spruce forest stands to address the following questions:

1. Is adventitious root height above post-fire organic soil equivalent to unburned and pre-fire
organic soil height?

2. Does the adventitious root height method bias our estimates of soil consumption because pre-
fire and residual organic soil depth is measured only at the base of trees?









CHAPTER 3
RESULTS

Burned Black Spruce Stands

Post-fire SOL depth, tree basal area and density as well as post-fire soil C and N pools

varied considerably across the 38 burned sites. Post-fire SOL depth ranged from 0-21 cm with 16

sites having 5 cm or less of organic matter depth, 15 sites having 7-15 cm of organic matter left

and 7 sites having 15-21 cm of organic matter remaining (Figure 3-la). Across all sites, average

soil organic horizon depths ranged from a shallow humic layer remaining to the full soil profile

(Figure 3-1b). SOC pools followed similar trends and ranged from 0.43 to as much as 14 kg

C/m2, with an average of 3.46 0.46 kg C/m2 (Figure 3-2a). SON pools varied from 0.017 -

0.403 kg N/ m2 and averaged 0.126 0.016 kg N/ m2 (mean 1 SE) across all 38 sites (Figure 3-

2b).

Tree densities at burned sites ranged from 2,000 to 8,000 trees per hectare (Figure 3-3a).

Additionally, basal area ranged from 0-5 m2 per hectare to as much as 30 m2 per hectare with 11

sites in the lowest basal area class, 15 sites between 5-10 m2 per hectare and 12 sites between 10-

30 m2 per hectare (Figure 3-3b). Stand age ranged from 30 176 years with a mean of 91.3 4.7

years old (mean 1 SE; J. F. Johnstone, unpublished manuscript). Age was not related to basal

area or stand density (data not shown). Mean tree density across all sites was 6,210 750.8 trees

per hectare and mean basal area was 9.4 1.2 m2 per hectare (both values mean 1 SE).

Unburned stands had generally the same characteristics as burned stands, however, tree density

and basal area were significantly greater; 17,148 147 trees per hectare and 16.8 2.2 m2 per

hectare (both values mean 1 SE).









Key, C. H. and N. C. Benson. 2005. Landscape Assessment: Ground measure of severity, the
Composite Burn Index; and Remote sensing of severity, the Normalized Burn Ratio.
Pages 25-36 in D.C. Lutes, R. E. Keane, J. F. Caratti, C. H. Key, N. C. Benson, S.
Sutherland and L. J. Gangi. FIREMON: Fire Effects Monitoring and Inventory System.
USDA Forest Service, Rocky Mountain Research Station, Ogden, UT. Gen. Tech. Rep.
RMRS-GTR-164-CD: LA1-51

Krause, C. and H. Morin. 2005. Adventive-root development in mature black spruce and balsam
fir in the boreal forests of Quebec, Canada. Canadian Journal of Forest Research 35:
2642-2654.

LeComte, N. M. Simard and Y. Bergeron. 2006. Effects of fire severity and initial tree
composition on stand structural development in the coniferous boreal forest of
northwestern Quebec, Canada. Ecoscience 13 (2): 152-163.

Lentile, L. B., Z. A. Holden, A. M. S. Smith., M. J. Falkowski,., A. T. Hudak, P. Morgan, S. A.
Lewis, P. E. Gessler, and N. C. Benson. 2006. International Journal of Wildland Fire 15:
319-345.

McGuire, A. D., R.A. Meier, Q. Zhuang, M. Manander, T. S. Rupp, E. Kasischke, D. Verbyla,
D. W. Kicklighter and J. M. Mellilo. 2000. The role of fire disturbance, climate and
atmospheric CO2 in the response of historical carbon dynamics in Alaska from 1950-
1995: a process-based analysis with the Terrestrial Ecosystem Model. Page 3 in M. J.
Apps and J. Marsden, editors. The Role of Boreal Forests and Forestry in the Global
Carbon Budget. Abstracts. 8-12, May 2000, Edmonton, Alta. Canadian Forest Service,
Northern Forestry Centre, Edmonton, Alberta, Canada.

Miyanishi, K. and E. A. Johnson. 2002. Process and patterns of duff consumption in the
mixedwood boreal forest. Canadian Journal of Forest Research 32: 1285-1295.

Neff, J. C., J. W. Harden, and G. Gleixner. 2005. Fire effects on soil organic matter content,
composition, and nutrients in boreal interior Alaska. Canadian Journal of Forest Research
35: 2178-2187.

Payette, S. 1992. Fire as a controlling process in the North American boreal forest. Pagesl44-165
in H. H. Shugart, R. Leemans and G. B. Bonan, editors. A systems analysis of the global
boreal forest. Cambridge University Press, Cambridge, U.K.

Purdon, M., S. Brais and Y. Bergeron. 2004. Initial response ofunderstory vegetation to fire
severity and salvage-logging in the southern boreal forest of Quebec. Applied Vegetation
Science 7: 49-60.

Rowe, J. S. 1983 Concepts of fires effects on plant individuals and species. Pages 135-154, in R.
W. Wein, D. A. Maclean, editors. The role of fire in northern circumpolar ecosystems.
NY, pp. 135-154.









Roy, D. P., L. Boschetti and S. N. Trigg. 2006. Remote sensing of fire severity: assessing the
performance of the normalized bur ratio. Geoscience and Remote Sensing Letters 3 (1),
112-116.

Turner, M. G., W. H. Romme, R. H. Gardner, W. H. Hargrove.1997. Effects of fire size and
Pattern on Early Succession in Yellowstone National Park. Ecological Monographs
67(4): 411-433.

Yarie J. and S. Billings. 2002. Carbon balance of the taiga forest within Alaska: present and
future. Canadian Journal of Forest Research 32: 757-767.

Wang, G. G. 2002. Fire severity in relation to canopy composition within burned boreal
mixedwood stands. Forest Ecology and Management 163: 85-92.









CHAPTER 4
DISCUSSION

Existing methods estimate fire severity in boreal forest by examining post-fire conditions.

This is adequate for capturing canopy severity as tree boles can be used relatively accurately to

reconstruct pre-fire aboveground biomass conditions. In contrast, depth measurements of post-

fire organic soil may not in themselves accurately represent pre-fire depths, or how much organic

soil was lost. This study provides evidence that adventitious root heights (ARH) on burned black

spruce trees can be used, once adjusted, as a proxy for pre-fire organic soil height. This extends

previous observations that were made in a few sites (Kasischke and Johnstone 2005). By

reconstructing pre-fire soil depths, this ARH method was used in combination with post-fire soil

depth measurements to quantify fire severity, and C and N emissions from fire in boreal black

spruce forest. Lastly, this method was also used to validate CBI, a semi-quantitative visual

estimate of fire severity, in this forest type.

Adventitious Root Height

Here we described a new method for quantifying fire severity by first estimating pre-fire

organic soil depths. The adventitious root method includes measuring, at tree bases, the post-fire

SOL depth and height to highest adventitious root on tree bole at a number of points within a

site. When we measured this in unburned sites as well, we found that the adventitious root did

correspond to organic soil height, but overall the highest root was 3.2 cm (mean across unburned

sites) below the top of the green moss layer. Thus, the pre-fire SOL depth is a combination of

post-fire SOL depth, adventitious root height plus 3.2 cm (for the offset). In addition, found no

significant difference between our re-constructed pre-fire depths and actual pre-fire organic soil

measurements (Hollingsworth, unpublished data), which offers further support to the ARH

method. However, measuring SOL only at tree bases underestimates post-fire organic soil by









about 6%. Although, there is this post-fire depth discrepancy between tree and randomly located

points, there is no pre-fire difference (as measured in the unburned sites), suggesting that organic

soil at the base of trees bums more. We developed corrections to account for these post-fire

differences for each horizon, since each has unique bulk densities, C and N concentrations and

total depth does not capture this variability. While, the ARH method can be useful across a wide

range of sites and severities, it may not be as effective at sites in which the trees have fallen over

and there is almost no residual organic soil. Trees can root in organic soil and if that all burns

away then the tree will fall over. ARH can still be measured on the tree bole to the root collar

(area where large roots separate), but measuring this way could omit a significant amount of

organic soil.

C and N Pools

After reconstructing pre-fire depth, we used these values to reconstruct pre-fire soil C and

N pools and calculate emissions as well. We calculated the mean unburned equivalent proportion

of total pre-fire depth for each of three horizons, which were: 14% (BM), 46% (F) and 30% (H).

GM was calculated to be a constant mean value of 2.5 cm, which was generally consistent across

all sites as it is the photosynthesizing horizon. Post-fire C and N pools were calculated using

actual post-fire SOL depths and mean values from each burned site for C and N concentration

and bulk density for the intact horizons. Pre-fire horizon depths were estimated from

reconstructed pre-fire depth and then mean values for C and N concentration and bulk density

from all of the unburned sites were used to reconstruct C and N pools for the burned biomass.

Finally, emissions were: re-constructed pre-fire pool minus the post-fire pool.

In the course of reconstructing organic soil C and N pools, it was necessary to make a few

assumptions and to use averages from all unburned sites. We controlled organic soil depth, since

post-fire SOL depth as well as height to adventitious root on the bole of a tree are easily

48










A

O014 5 1 Canoiy N














B 23:1




012 :1












0 0.1- I0.R4 13.142
eoei ft s ac i pi dJ a (n)

Figure 3-9. Mean ( 1 SE) N emissions and percent of total N combustion for four post-fire soil
organic layer (SOL) depth classes across 38 burned sites. A) Nitrogen emissions. B)
Percent of total N combustion. Canopy does not include tree boles. Ratios of organic
soil to canopy emissions (kg/m2) and combustion (%) are indicated at top of each
column.




























B T* 10:1








14:1

2:1




05 5.1.10 10.1-15 15.1.20
Ptr-flnm SL deptqlb dKUn en'i

Figure 3-8. Mean ( 1 SE) carbon (C) emissions and percent of total C combustion by post-fire
soil organic layer (SOL) depth classes. A) Carbon emissions. B) Percent of total
carbon combustion. Canopy does not include tree bole. Ratios of organic soil to
canopy emissions (kg/m2) and combustion (%) are indicated at top of each column.









Reconstructing Pre-Fire Depth of the Soil Organic Layer

Because adventitious root development is stimulated by moss and humus cover (Krause

and Morin 2005, and Johnstone and Kasischke 2005), we explored the applicability of using the

adventitious root scars on burned trees to estimate pre-fire organic soil depth (Question 1).

Johnstone and Kasischke (2005) hypothesized that the height of the ARH in burned stands

indicated the minimum height of the pre-fire SOL surface, or more specifically, the top of the

green moss layer. To test this hypothesis, we measured the height of the ARH in relation to the

top of the green moss layer, hereafter the adventives root height offset (ARHo), in our 28

unburned sites. ARHo ranged from -7.9 cm below the green moss layer to +3.2 cm above

(Figure 3-4) with a mean value of-3.2 + 0.43 cm (mean + 1 SE).

To better understand factors that might explain ARHo variation, we identified moss type

and measured distance to tree from sampling point, DBH of tree, pH, soil moisture, depth of total

organic soil and depth of each layer (GM, BM, F and H). Across all sites, most sampling points

were occupied by feather moss (254), with substantially fewer points occupied by sphagnum

(35), unidentified moss species (12) or lichen (1). Site mean ARH offset was not related to

moss type, distance to tree, mineral soil pH, soil moisture, total SOL depth or basal area (data not

shown). ARHo was, however, significantly positively related to tree DBH (ARHo = -5.07 + 0.31

* DBH, R2=0.23, F1, 26=7.59, P=0.01). Because this predictor did not explain much of the

variation in the ARHo, we used the mean offset of-3.2 cm to correct our calculations of pre-fire

SOL depth (sections D and E below).

Intra-site Variation in Post-Fire Soil Organic Layer Characteristics

After ascertaining that the ARH method was effective for determining pre-fire SOL depth,

we determined whether measuring post-fire SOL depth only at tree bases might bias our

estimates of mean SOL at a site (Question 2). Across the burned sites, total organic soil depth









QUANTIFYING FIRE SEVERITY AND CARBON AND NITROGEN POOLS AND
EMISSIONS IN ALASKA'S BOREAL BLACK SPRUCE FOREST

























By
Leslie A. Boby













A MASTERS THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2007











Table 3-3. Soil organic layers (SOL), tree canopy and ecosystem mass and C combustion as well
as C emissions compared to CBI scores (Total, understory, substrate and overstory)
for 38 sites in Alaskan forests burned in 2004.
Measurement CBI* Equation R2 P- value


Soil organic
layers (SOL)


% depth
combustion


% mass
combustion


% C combustion


C emissions
(kg/m2)


Tree canopy


Ecosystem


% mass
combustion


% C combustion

C emissions
(kg/m2)

% mass
combustion
% C combustion
C emissions
(kg/m2)


Tot
Und
Sub

Tot
Und.
Sub
Tot
Und.
Sub

Tot
Und
Sub

Tot
Over
Tot
Over


-28.54 + 42.0 (CBI-Tot)
-3.05 + 32.11 (CBI-Und)
33.67+ 17.61 (CBI-Sub)

-39.7 + 45.0 (CBI-Tot)
-13.0 + 34.7 (CBI-Und)
27.5 + 18.6 (CBI-Sub)
-66.3 + 52.56 (CBI-Tot)
-36.6 + 41.1 (CBI-Und)
9.84 + 22.9 (CBI-Sub)

-3.0 + 2.60 (CBI-Tot)
-1.42 + 1.97 (CBI-Und)
0.83 + 1.08* (CBI-Sub)

34.3 + 16.51 (CBI-Tot)
9.6 + 2.83 (CBI-Over)
48.6 + 14.15 (CBI-Tot)
8.39 + 28.7 (CBI- Over)


Tot -0.25 + 0.28 (CBI-Tot)
Over -0.74 + 0.45 (CBI-Over)

Tot -37.0 + 43.9 *(CBI -Tot)
Tot -61.1 + 50.6 (CBI- Tot)

Tot -3.26 + 2.85 (CBI- Tot)


*CBI-scores by strata: total (Tot), understory (Und), substrate (Sub) and overstory (Over).


0.57
0.56
0.42

0.63
0.63
0.45
0.54
0.56
0.44

0.44
0.43
0.33

0.14
0.44
0.15
0.44


<.0001
<.0001
<.0001

<.0001
<.0001
<.0001
<.0001
<.0001
<.0001

<.0001
<.0001
0.0002

0.02
<.0001
0.02
<.0001


0.14 0.03
0.27 0.002


0.64
0.56


<.0001
<.0001


0.45 <.0001









measured stand-level variables to GM and BM horizons to better understand why these layers

varied as a percent of total depth. Green moss depth was not related to tree density or basal area

We measured p b, and C and N concentrations in the burned and unburned sites and coupled

these values with SOL depths to quantify pre-fire and post-fire C and N pools (Question 6, See

methods section F). In the burned sites, soil core sampling points were not stratified by random

or tree points (Table 3-1). Conversely, the eight unburned soil sample cores were extracted at

tree and randomly located points (four each); there were no significant differences between p b,

and C and N concentrations between these two sampling schemes (data not shown, Table 3-2).

Mean C and N concentrations for the horizons ranged from 32.9 -42.5% and 0.08 1.07%,

respectively. Only the F horizon, where roots are likely to be most dense (Neff et al. 2005), had

significantly different gravimetric moisture content (paired-t1, 27= -2.24, P=0.03; random mean=

251.1 + 41.1 and tree mean= 213.4% 32.7 moisture (mean 1 SE)). Moisture content was not

significantly different at random versus tree points for the other three horizons (data not shown).

Reconstructed post-fire SOC pools ranged from 0.33 kg/m2 to 10.63 kg/m2 (for a site with

very little burning) with a mean of 2.99 0.40 kg/m2 (mean 1 SE) while SON pools ranged

from 0.01 kg/m2 to 0.30 kg/m2 with a mean of 0.11 0.02 kg/m2 (mean 1 SE). Reconstructed

post-fire element pools were 17.0 + 3.9 (SOC) and 19.3 + 3.8 % (SON) less than direct pool

measurements (Section A above; SOC paired-t1, 37= 3.31, P=0.002 and SON paired-ti, 37= 3.45,

P=0.001). Additionally, the proportion of SOC and SON lost ranged from as low as 0% to as

high as 94% for with mean losses of 52.9% + 4.8 and 49.8% 5.04 (mean 1 SE) respectively,

across the 38 sites (Figures 3-8 and 3-9). SOC emissions were 41.6 5.6 times greater than SON

emissions.









pools using C and N concentration and bulk density estimates from soils sampled in burned and

unburned stands. We conclude that the ARH method can be used to reconstruct pre-fire organic

soil depth, C and N pools and to assess fire severity. Furthermore, CBI shows promise as a way

of estimating fire severity quickly and is a reasonably good predictor of biomass and soil C loss.









Other Methods of Measuring Fire Severity and Emissions..................................................50
O rg an ic S oil .............................................................................................................. 50
Canopy Consumption and Tree Mortality .............................................. ...............51
C and N P ools ....................................................................................................... ..... 51
C onclu sions.......... ..........................................................52

L IST O F R E F E R E N C E S ...................................................................................... ...................53

B IO G R A PH IC A L SK E T C H .............................................................................. .....................57














































6












O DM ------
20 -X Depth = 0.67+ 1.1 Depth,
R "l.91, P O.OOOI

15- r Depth, = 0.73 + 0.91 DepthT
S, R'= 0.71, P <0.00I0
8 *k .J lk -----A
10- Depth, = 0.62+ 0.71 DepthT
_A ,. -~ Rt= 0.77, P <0.0001
STotal -
S t' DepthR = 0.69+ DepthT
O( RI= 0.91, P <0.0001


0 5 10 15 20 25
Depth, tree points (cm)


Figure 3-5. Depth of soil organic horizons at randomly located points (DepthR) compared to
depths at tree base points (DepthT) across 38 sites burned in 2004. Values are means
of 11 tree and 11 random points, from each site. Horizons are: dead moss (DM), fibric
(F) and humic (H) as well as total depth.









Table 3-1. Post-fire soil organic horizons' mean depth, bulk density (pb), C and N concentration
(Mean 1 SE). Values are means from 38 Alaskan sites burned in 2004.
Horizon Mean depth (cm) p b (g/cm3) C cone. (%) N Conc. (%)
Dead moss (DM) 1.12 0.3 0.04 0.004 40.2 1.4 0.97 0.1
Fibric (F) 3.69 + 0.5 0.10 + 0.01 41.4 + 0.8 1.28 + 0.04
Humic (H) 8.15 + 1.0 0.21 + 0.01 30.0 + 1.0 1.25 + 0.04

Table 3-2 Soil characteristics by horizon for 28 unburned sites (mean 1 SE). Values Include
mean depth, bulk density (pb) and C and N concentration.
Horizon Mean depth (cm) p b (g/cm3) C conc. (%) N Conc. (%)
Dead moss (DM) 1.12 0.3 0.04 0.004 40.2 1.4 0.97 0.1
Fibric (F) 3.69 + 0.5 0.10 + 0.01 41.4 + 0.8 1.28 + 0.04
Humic (H) 8.15 + 1.0 0.21 + 0.01 30.0 + 1.0 1.25 + 0.04









lost. However, fire severity is defined by amount lost and not amount left behind, therefore, it is

important to note that the two measurements are not comparable.

Canopy Consumption and Tree Mortality

Our canopy component biomass combustion estimates may be a more comprehensive

visual way of quantifying tree fire severity in terms of biomass lost and incorporating it into

total ecosystem fire severity. Canopy consumption and tree mortality estimates have been used in

previous studies as measures of fire severity, however very few studies used only canopy

consumption or mortality. The boreal forest often experiences complete canopy mortality while

soil fire severity patterns are much more variable (Miyanishi and Johnson 2002) and therefore

canopy measurements alone are inadequate. Proportion of canopy mortality was used as one fire

severity quantifier within three studies (Greene et al. 2004, Johnstone et al. 2004 and Purdon

2004), though only the second study used this parameter exclusively. Some of these studies used

degree of consumption or percentage of tree mortality as indicators. However, total ecosystem

fire severity estimates cannot necessarily be quantified strictly from the canopy.

C and N Pools

Carbon and nitrogen pools in boreal forests as well as emissions from forest fires are

poorly constrained and limited by uncertainties in quantifying pre-fire spatial surface variation as

well as organic soil biomass consumed (Neff et al. 2005, French et al. 2004). Many studies

calculate carbon emissions from fire as a product of the fuel combusted during the fire and the

area that burned (Amiro et al. 2001) or have quantified carbon also using carbon density and

emission factors (French et al. 2004). Models are used to calculate carbon and nitrogen pools and

subsequent emissions with a certain degree of error that is propagated throughout the model and

much of this uncertainty is due to variability in organic soil C loss (French et al. 2004, Neff et al.

2005). Furthermore, some models have not estimated C emissions from wildfires, which will

51









Statistical Analysis

In analyzing data, we determined each 'site' to be a unit and therefore, used the means of

the 11 sampling points within each site to characterize a site. Thus for the burned sites, we had

n= 38 sites and for the unburned sites, we had n= 28 sites. Data were normally distributed for our

analyses. We performed a series of paired t-tests to compare randomly selected versus tree base

sampling points (within sites) (Questions 3 and 4) Additionally, we explored relationships

between: randomly located and tree sampling point depth differences in burned sites and

adventitious height in the unburned sites to organic soil height, tree density and basal area

(Question 2); CBI scores and combustion rates in burned sites as well in a series of regressions

(Question 5). We compared our quantified fire severity for each site with the CBI score for each

site in a regression analysis.









Soil Organic Layer C and N Pools and Combustion

We measured p b, and C and N concentrations in the burned and unburned sites and

coupled these values with SOL depths to quantify pre-fire and post-fire C and N pools (Question

6, See methods section F). In the burned sites, soil core sampling points were not stratified by

random or tree points (Table 3-1). Conversely, the eight unburned soil sample cores were

extracted at tree and randomly located points (four each); there were no significant differences

between p b, and C and N concentrations between these two sampling schemes (data not shown,

Table 3-2). Mean C and N concentrations for the horizons ranged from 32.9 42.5% and 0.08 -

1.07%, respectively. Only the F horizon, where roots are likely to be most dense (Neff et al.

2005), had significantly different gravimetric moisture content (paired-ti, 27= -2.24, P=0.03;

random mean= 251.1 + 41.1 and tree mean= 213.4% 32.7 moisture (mean 1 SE)). Moisture

content was not significantly different at random versus tree points for the other three horizons

(data not shown).

Reconstructed post-fire SOC pools ranged from 0.33 kg/m2 to 10.63 kg/m2 (for a site with

very little burning) with a mean of 2.99 0.40 kg/m2 (mean 1 SE) while SON pools ranged

from 0.01 kg/m2 to 0.30 kg/m2 with a mean of 0.11 0.02 kg/m2 (mean 1 SE). Reconstructed

post-fire element pools were 17.0 + 3.9 (SOC) and 19.3 + 3.8 % (SON) less than direct pool

measurements (Section A above; SOC paired-ti, 37= 3.31, P=0.002 and SON paired-ti, 37= 3.45,

P=0.001). Additionally, the proportion of SOC and SON lost ranged from as low as 0% to as

high as 94% for with mean losses of 52.9% + 4.8 and 49.8% 5.04 (mean 1 SE) respectively,

across the 38 sites (Figure 3-8, a-d). SOC emissions were 41.6 5.6 times greater than SON

emissions.









TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ..............................................................................................................4

L IST O F T A B L E S ..................................................................................................... . 7

L IST O F FIG U R E S ............................................................................... 8

ABSTRAC T ...........................................................................................

1 IN TR O D U C TIO N .................. ..................................................................... 11

2 M ETH OD S ................. ........ .. ...................................... .......... .............. 16

Study A rea ................................... ...........................................................16
Experim ental D esign and M easurem ents ........................................ .......... ............... 17
Patterns of Post-Fire Soil Organic M atter ......................................................................... 17
Sampling Design: Randomly Located and Tree Base Points........................................18
Pre-fire O rganic Soil D epth.................................................. ............................... 18
C and N Sam pling ...........................................................................18
Tree Biomass, Stand Structure and Combustion..........................................................19
U nb u rn ed S ites ................................................................19
Lab Analysis ....................... ..................................... ........ 20
Horizon Depths in Relation to Total Organic Soil Depth.....................................................21
Pre- and Post-Fire C and N Pools ..................................................................... 21
CBI and Combustion .................................... .. .... .... ............ .... 23
Statistical A nalysis................................................... 24

3 R E SU L T S .............. ... ................................................................26

Burned B lack Spruce Stands ....................... ................................................................. 26
Reconstructing Pre-Fire Depth of the Soil Organic Layer .............................................27
Intra-site Variation in Post-Fire Soil Organic Layer Characteristics..........................27
Fire Severity of O organic Soil .......................................................................... .............. 29
Reconstructing Depth of Organic Soil Horizons ..................................... ...............30
Reconstructing Depth of Organic Soil Horizons ..................................... ...............32
Soil Organic Layer C and N Pools and Combustion ................................... .................33
Tree Biomass, C and N Pools and Combustion................................... ....................... 34
C B I and C om bu stion L losses ......................................................................... ...................34

4 D ISC U S SIO N ..............................................................................................47

A dventitiou s R oot H eight ......................................... .. .. ....................................................47
C an d N P o ols ......... ... ....... .. .. .......... ... .. ................................................ 4 8
C anopy F ire Severity and B iom ass.............................................................. .....................49
C B I ........................................................... .................................... . 4 9









CHAPTER 2
METHODS

Study Area

We established 90 sites in forest stands that burned in the summer of 2004 in three

different fires (Dalton Complex, Taylor Complex and Boundary Fire) and 28 unburned forest

sites paired with the three fires. The approximately 250 000 km2 study area (figure 2-1) that

encompasses these sites is located within central interior Alaska with boundaries extending north

to the Brooks range (-67 deg N), south to the Alaska Range (-63 deg N), east to the Alaska-

Canada border (-142 deg W) and west to the Dalton Highway (-150 deg W) (Hollingsworth et

al 2006). The area includes small mountain ranges, slightly sloped uplands along with large

flatland areas and broad floodplains adjacent to braided rivers (Hollingsworth et al 2006). Open

to closed-canopy black spruce (Picea mariana) in mostly even-aged stands was the dominant

vegetation type in our study area with occasional white spruce (Picea glauca) and deciduous

species such as aspen (Populus tremuloides) and birch (Betula papyrifera). Vegetation across the

study area includes three black spruce community types: acidic black spruce/ lichen forest,

nonacidic black spruce/rose/horsetail forest and tree-line black spruce woodland (Hollingsworth

et al 2006). Temperatures across this region are extreme and range from -70 C to 350 C with

mean annual precipitation at about 285 mm including about 35% from snow (Hinzman et al

2005). Soils of interior Alaska are generally undeveloped and primarily (-90%) consist of

Inceptisols, Gelisols, Histosols and Entisols (Ahrens et al 2004).

For our study, we selected sites that represented a range of fire severity or for which we

had pre-fire data (Hollingsworth et al. 2006). We intensively studied a subset of 38 of these sites

(six of which were at tree-line), which were chosen to maximize variation in fire severity and

edaphic conditions. These sites were selected from areas burned by the three different wildfires;




























To Alaska,
Thanks for all the wonderful memories









was 8.2 1.0 cm (mean 1 SE) at randomly located sampling points and was comprised of three

horizons with the following mean depths: 1.1 + 0.3 cm (DM), 3.7 0.5 cm (F) and 3.3 0.4 cm

(H) (mean 1 SE; Table 3-1). Total organic soil depth was slightly (6.4%) but significantly

shallower at tree bases (7.5 0.9 cm, mean 1 SE), than at randomly located sampling points

(paired-ti, 37=2.40, P=0.02). Site means at tree base and randomly located organic soil depths

were highly correlated (Figure 3-5). The difference in mean total depth was primarily due to

shallower DM horizon depth near trees (0.4 0.2 cm (mean 1 SE); paired-t 1,37=3.30, P=0.02).

H horizon depth, by contrast, was greater near trees, 3.8 0.5 cm (mean 1 SE); paired-t1, 37=-

2.20, P=0.03).

Shallower residual SOL depths under trees versus randomly located points may have been

due to: (1) greater organic consumption under trees (Miyanishi and Johnson 2002 and our

Question 2) or (2) less pre-fire organic matter accumulation under trees or a combination of both

factors (Question 3). However, we found that in unburned forest stands, total SOL depth under

trees was not significantly different from SOL depth at randomly located points (paired-t1, 27=

0.37, P=0.71), suggesting that shallower SOL depths under trees in the burned sites were due to

greater combustion under trees. Across the unburned sites, mean total SOL depth at random

points was 24.8 1.3 cm (mean 1 SE). Bulk density ( p b ), soil moisture and C and N

concentrations were not different at tree and random points for all organic soil horizons but did

differ between horizons (Table 3-2). Although GM and BM horizons accounted for 24% of the

total SOL depth at random points, they only accounted for 10.4% of total profile organic matter,

11.9% of the total SOC pool and 8.8% of the total SON pool.

Since we determined that the random/tree depth bias was not due to pre-fire depth

disparities, we considered whether other stand characteristics explained the bias. Random versus









3. Are post-fire depth disparities at sampling points located randomly or at tree bases due to
systematic differences in combustion rates or pre-fire organic soil depths under trees?

4. How are the depths of individual soil horizons related to total organic soil depth?

5. Does the adventitious root collar method correlate with the visually-estimated Composite
Burn Index?

6. What is the relationship between C and N emissions and burn severity?

This study presents data from a range of black spruce forests distributed across gradients of

moisture availability and fire severity that were used to characterize stand-level patterns of fire

severity across the landscape.









Sampling Design: Randomly Located and Tree Base Points

In addition to our randomly located sampling points, we also measured SOL depth near the

base of trees. Tree sampling points were chosen at the tree nearest to a given random sampling

point and SOL depth was sampled as close to the bole as possible, although, the distance to bole

varied due to large roots that prohibited digging. At tree sampling points, we also measured the

height from the top of the remaining SOL to the highest adventitious root on the bole of the tree,

henceforth referred to as adventitious root height (ARH). Since pre-fire SOL depth was only

reconstructed at tree sampling points, we compared SOL depth at tree base and random sampling

points (burned and unburned sites) in a t-test to determine if sampling only at trees would bias

our measurements (Question 2).

Pre-fire Organic Soil Depth

We then combined ARH with post-fire SOL depth (at tree bases) to estimate pre-fire SOL

depth. Thus, pre-fire SOL depth was equal to post-fire SOL depth plus ARH. SOL combustion

was the difference between pre-fire SOL depth and post-fire SOL depth. To test if our

reconstructed pre-fire SOL depths were accurate (Question 1), we compared our values to actual

pre-fire SOL measurements (Hollingsworth et al 2006).

C and N Sampling

In addition to measuring SOL depth, we also sampled soils at four sampling points that

were representative ofintra-site variation in fire severity. Organic soil horizons were sampled

volumetrically and separated into the horizons noted above; dead moss (DM), fibric (F) and

humic (H). Mineral soil was sampled via volumetric coring at 0-5 cm, 5-10 cm depths. Soil

samples were stored in coolers with ice packs in the field and in freezers prior to laboratory

analyses.









SE), while mean substrate, understory and overstory CBI scores were: 1.9 0.14, 2.2 0.09 and

2.5 0.06 (mean 1 SE). Generally, substrate and understory scores were more frequently

lower while canopy scores were often higher and total CBI scores were relatively evenly

distributed among the score classes between 1.5 and 3.

The overstory CBI score was positively related to % of canopy biomass and C combusted

and explained 44% of the variation (Table 3-3), but was negatively related to C emitted (27% of

variation). Total CBI score only explained <15% of the variation in all canopy measures (Table

3-3). Total, understory, and substrate CBI scores were significantly related to all SOL

measurements and between 33-63% of the variation were explained. Although, only one

comparison between substrate CBI and SOL C emissions had an R2 value as low as 33% and the

rest were 42% or greater (Table 3-3). Total CBI scores were negatively related to ecosystem

mass and C combustion and C emissions and explained <45% of the variation (Table 3-3). In

general, CBI scores were good estimates of % mass lost (for all components), however, it was

not good at estimating the amount of C emissions. However, CBI was better for estimating SOL

or forest floor C emissions than canopy C emissions. Since CBI is a visual estimate, there may

be some variation in C concentration or other variables that is not easily visually detected.









CHAPTER 1
INTRODUCTION

Wildfire is the major disturbance in Alaska's boreal forest and consequently is one of the

major factors that controls the distribution of soil and plant carbon (Harden et al. 2000). Fires

vary considerably in severity, or the amount of surface and canopy fuel consumed (Wang 2002).

Fire severity is a measure that integrates active fire characteristics and immediate fire effects,

and is estimated as the proportion of biomass combusted (Lentile et al. 2006). Wildfires burn

heterogeneously throughout the boreal landscape, leading to varying levels of fire severity in

post-fire ecosystems. Aspect, elevation, soil moisture, and weather conditions concomitantly act

with variations in vegetation fuel types and forest structure to influence fire severity patterns as

well (Johnson 1992). Furthermore, interannual variation in area burned is high and the severity

(Harden et al. 2000) and configurations (Kasischke and Johnstone 2005) of wildfire effects are

often linked to seasonal changes in fuel conditions. Patterns of fire severity influence post-fire

vegetation composition and regrowth (Arseneault 2001, Johnstone and Chapin 2006, Wang

2002), and subsequent carbon uptake or emissions (LeComte et al. 2006). Therefore, in order to

measure the magnitude of the fire disturbance and understand effects on soil and plant carbon

accumulation, it is necessary to develop quantitative measures to describe fire severity.

Boreal forests of interior Alaska are dominated by even-aged stands of black spruce (Picea

mariana) and white spruce (Picea glauca) that are generally rooted in thick (5- >50 cm) layers of

organic material overlying mineral soil. These surface organic horizons are largely derived from

live and dead mosses and inputs from vascular plant litter, root turnover and lichen (Miyanishi

and Johnson 2002). According to the Canadian system of soil classification, these organic soil

horizons can be categorized as litter (recently cast and unaltered plant remains), fibric (slightly

decomposed, but still identifiable material) and humic (more decomposed and not identifiable),









BIOGRAPHICAL SKETCH

Leslie A. Boby attended Morgan Park High School in Chicago, graduating in 1995. She

studied at University of Illinois, Urbana-Champaign, IL and obtained a Bachelors of Science

degree in biology in 1999. Immediately following university, Leslie moved to Africa and served

as a Peace Corps volunteer in rural Ndori, Kenya and taught agroforestry techniques to farmers.

After returning to the U.S., Leslie moved out to New Mexico in 2002 and worked for the Bureau

of Land Management as a wildland firefighter and biological technician. She continued further

west and worked as a field assistant at an Audubon Sanctuary in southern California. Leslie

returned to university life in 2005 as a graduate student at the University of Florida in

Gainesville, FL. She completed her Masters thesis in interdisciplinary ecology in December

2007. Her next objective is to return to the working world and obtain a position as a land

manager burning forests and fighting exotic species.













2004 wildfires in interior Alaskan boreal forest
and study sites


N


0 375 75 150 225 300
SMiles


Data Source:
Ecoregions by USGS 1996
All_BAERpermanent layer (fire), BLM 2004
GPS points by Andy Ruth, 2005
Roads and names, USGS 1996

Map created by LeslieA. Boby

Figure 2-1. Map of interior Alaska, including a map of the areas burned by wildfire in 2004 and
study sites.


Cities andtowns
- Roads
Dalton Complex sites
Taylor Complex study sites
o Boundary Fire study sites
Area burned by wildfire, 2004
I I Intenor boreal forest









depths at 11 randomly located points and at 11 points at tree bases along a 30-m belt transect in

each site. Tree density, DBH and species identity were estimated in six- 2 m x 5 m subplots.

SOL horizons were divided into similar categories as the bum plots but the dead moss horizon

was referred to as brown moss (BM) and we added a fourth horizon, green moss (GM). We

volumetrically sampled soils and measured horizons as described above at eight points (four tree

bases and four randomly located). Finally, we compared horizon depths, bulk density ( p b) and C

and N concentration at tree and randomly located points in unbumed forest stands to discover if

there were biases due to tree proximity (Question 3).

Lab Analysis

Approximately 370 cores comprising -1500 total soil samples were collected from 37

burned and 28 unbumed sites. We calculated the volume of each soil layer from surface area and

depth measurements and processed soils in the lab to obtain oven dry soil weight, p b (g/cm3),

moisture content (g/g), pH and carbon and nitrogen content. Soils were homogenized and any

material that could not be mixed such as coarse (>5 mm sticks) or rocks were removed from the

sample and the weight and volume of the rocks was subtracted from total wet sample weight and

volume. Sub samples were initially weighed wet and then dried at 105 deg C for 24-48 hours to

determine moisture content. Additional sub samples (dried at 65 deg C) were rolled into tins and

carbon and nitrogen content was determined using a Costech Elemental Analyzer (Costech

Analytical, Los Angelas, California, USA). We measured pH of all burned soil samples and a

sub-set of the first mineral layer of the unburned soil samples using the WBL method No. 2

(Thomas 1996).









Reconstructing Depth of Organic Soil Horizons

After reconstructing SODpre-F depth with the ARH method, we also had to divide

total depth into horizons to quantify C and N pools (Questions 4 and 6). We examined a number

of factors in the unburned forest stands to determine if they could be used as predictors of the

depth of the soil horizons, focusing on stand characteristics that could also be easily measured at

burned sites. First, we compared the depth of each horizon to the total SOL depth and all were

significantly positively related (Figure 3-7a). Next, we found that the F and H horizons as a

percent of total depth were not significantly related to total depth. The GM horizon was

negatively related to total depth, while the BM horizons were positively related (Figure 3-7b).

For F and H, we used a constant mean proportion (derived from the unburned sites) of

46% and 30%, respectively, to divide the total SOD into horizons. We compared other easily

measured stand-level variables to GM and BM horizons to better understand why these layers

varied as a percent of total depth. Green moss depth was not related to tree density or basal area

(data not shown), but it was only 10.4 0.62% of total soil organic matter depth and it was not

highly variable, with a mean of 2.4 0.14 cm (mean 1 SE) and a range between 0.82 and 3.9.

Therefore, we used the mean value as a constant for all GM layers. Brown moss depth was

13.7% 1.91 (mean 1 SE) of total organic soil depth and was significantly related to basal area

(BM depth = -6.07 0.14 (BA/ha), R2=0.18, F1, 25=5.50, P=0.03) and total depth (Figure 3-7a).

Combining the two variables in a multiple regression did not increase the predictive power above

that of total depth alone (data not shown). However, the negative intercept of the equation

resulted in improbable values for sites with shallow organic layers. Therefore, we calculated BM

depth as a constant proportion of total depth (13.7%).









become increasingly important as fire frequency may be increased due to climate change (Yarie

and Billings 2002). Neff et al. in 2005 used a "Tau" model to calculate burned and unburned C

pools and they stated that Tau consistently underestimated the heterogeneity of the soil horizons

and thus C pools. Our adventitious root height method accounts for some of this soil surface

spatial variation as well as depth and C and N concentration variation.

Conclusions

C and N fluxes are intrinsically linked to fire effects and fire severity in the boreal forest;

therefore, it is imperative to have a satisfactory way of measuring fire severity throughout the

boreal landscape. Since, many studies use fire severity as a gradient or parameter for examining

other ecosystem processes, fire severity is often not directly quantified, but estimated. These

studies also indicate that the co-factors that influence fire severity, such as seasonality of burn,

weather, and topography and soil moisture are good indices for estimating fire severity. Methods

such as CBI show strong potential to be a satisfactory way of standardizing fire severity.

Since most boreal forests experience almost total canopy death, it would seem that

measuring fire severity in the canopy alone does not accurately capture the variability found

within sites. In summary, it seems that fire severity estimates could be best quantified by a

combination of SOL combustion measurements (depth or percentage removed), soil moisture

content, site drainage and seasonality or timing of burn. The ARH method accounts for organic

soil combustion and surface and depth spatial variation thereby overcoming some of the

limitations of previous boreal forest C and N estimates and fire losses.









de Groot, W. J., R. W. Wein. 2004. Effects of fire severity and season of bum on Betula
glandulosa growth dynamics. International Journal of Wildland Fire 13: 287-295.

French, N. H. F., P. Goovaerts, and E. S. Kasischke. 2004. Uncertainty in estimating carbon
emissions from boreal forest fires. Journal of Geophysical Research 109, D14SO8.

Harden, J. W., S. E. Trumbore, B. J. Stocks, A. Hirsch, S. T. Gowers, K. P. O'Neill and E. S.
Kasischke. 2000. The role of fire in the boreal carbon budget. Global Change Biology 6:
174-184.

Hinzman, L., L. A. Viereck, P. Adams, V. E. Romanovsky, and K. Yoshikawa. 2005. Climatic
and permafrost dynamics in the Alaskan boreal forest. Pages 39-61 in M. Oswood and
F.S. Chapin III, editors. Alaska's changing boreal forest. Oxford University Press, New
York, NY, USA.

Hollingsworth, T. N., M. D. Walker, F. S. Chapin III and A. L. Parsons. 2006. Scale-dependent
environmental controls over species composition in Alaskan black spruce communities.
Canadian Journal of Forest Research 36: 1781- 1796.

Johnson, E. A. 1992. Fire and Vegetation Dynamics: Studies from the North American boreal
forest Pages 39-77. Cambridge University Press. Cambridge, England.

Johnstone, J. F. 2006. Response of boreal plant communities to variations in previous fire-free
interval. International Journal of Wildland Fire 15: 497-508.

Johnstone, J. F., F. S. Chapin III, J. Foote, S. Kemmett, K. Price and L. Viereck. 2004. Decadal
observations of tree regeneration following fire in boreal forests. Canadian Journal of
Forest Research 34: 267-273.

Johnstone, J. F. and E. S. Kasischke. 2005. Stand-level effects of soil burn severity on post-fire
regeneration in a recently burned black spruce forest. Canadian Journal of Forest
Research 35: 2151-2163.

Johnstone, J. F. and F. S. Chapin III. 2006. Effects of soil bum severity on post-fire tree
recruitment in boreal forest. Ecosystems 9: 14-31.

Kasischke, E. S., N. L. Christensen Jr., B. J. Stocks. Fire, Global warming and the carbon
balance of boreal forests. 1995. Ecological Applications 5(2) 437-451.

Kasischke, E. S., N. H. F. French, K. P. O'Neill, D. D. Richter, L. L. Bourgeau-Chavez and P. A.
Harrell. 2000. Influence of fire on long-term patterns of forest succession in Alaskan
boreal forests. Pages 214-238 in E. S. Kasischke and B. J. Stocks, editors. Fire,climate
change and Carbon cycling in the boreal forest. Springer-Verlag, New York, NY, USA.

Kasischke, E. S. and J. F. Johnstone. 2005. Variation in post-fire organic layer thickness in a
black spruce forest complex in interior Alaska and its effects on soil temperature and
moisture. Canadian Journal of Forest Research 35: 2164-2177.











A + GM--
Depth = 1.29 + 0.05 Depth
RI= 0.21, P 0.01
,' *0 BM .-.
J O Depth,, = -5.53 + 0.91 Depth,
1" 0* R'= 0.71, P 0.0001
OF ---
Ji1 DO A Depth, =-0.3S + 0.48 Depth,,
SA R 0.50, P 0.001
& H --
0 DepthH =3.69 +0. 16DqydrLi
SR'= 0.27, P= 0.005



B j. + GM-
A El iGiM = 16 0.22 Depth.
E0 A O D E R7= 0.22, P- 0.001
E[ BP l D BM .....-
-_- % M % BM = 7.5+0.85 Depth,
,.-- E B ] l R= 0.34, P= 0.0001
0,.- 1' A A DF ---
S-- .- 4%F = 40.1+ 0.22 1Depthe
16m AE ] RI= U-02, P==0.45


I, ~WI -3.3 + 0.63 1J~pthm
S1 R= 0.02, P= 0.45
M ,.-^'- H ----



0-
0 S 10 15 25 3 3 40 45


Figure 3-7. Total soil organic layer depth compared to soil horizon depth and horizon depth as
percent of total depth across 28 unburned Alaskan boreal forest sites. There are four
organic soil horizons: green moss (GM), brown moss (BM), fibric (F) and humic (H).
A) Soil horizon depth comparison. B) Horizon depth as percent of total depth.









with mineral soil below (Canada Soil Survey Committee 1978). These thick horizons of organic

material on the mineral soil surface make boreal forests vastly different from other temperate

forests in carbon sequestration and emissions as well as fire effects. Soil carbon pools in the

boreal forest are estimated to be 20-60% of the world's terrestrial soil carbon pool (Dixon et al.

1994, McGuire et al. 2000). The Alaskan boreal forest, which is estimated to cover about 17

million ha, stores about 4.8 Mg C of this C or 27.6 Mg C/ha (Yarie and Billings 2002). Outputs

from the surface organic horizon are controlled by heterotrophic respiration of organic matter,

and by fire consumption (Harden et al. 2000). Fire return intervals are estimated to be

approximately 80-150 years for the boreal forest (Johnson 1992, Payette et al. 1992). However,

climate change is expected to increase the frequency and the intensity of wildfires as well as the

duration of the fire season (Flannigan et al. 2000). Disturbance from wildfire regenerates the

forest into early successional states of forest stands that include deciduous tree species such as

aspen (Populus tremuloides) and Alaskan birch (Betula neoalaskana). These young forests have

different carbon dynamics than the mature forest and tend to decrease the carbon sink (Amiro et

al. 2003). Wildfire severity has a strong influence on the composition of early successional

forests and thus carbon dynamics over time (Johnstone 2006, Aresenault 2001, LeComte et al.

2006).

Fire behavior and severity patterns in the boreal forest differ greatly from many other fire

regimes due to the high fire intensity and flame length that characterizes boreal fires (Johnson

1992). Additionally, the canopy often burns in a fast-paced, high intensity crown fire which often

results in near total canopy death (Johnson 1992) while the thick organic soil horizons may burn

in active flames or in smoldering consumption (Miyanishi and Johnson 2002). This combination

of high frequency of 100% aboveground plant mortality plus the importance of quantifying the
































Advenltitious R~oot Offhst (AR~HQI vae IcmI)


Figure 3-4. Frequency of 28 unburned sites among 9 adventitious root height depth offset
(ARHo) classes (cm). ARHo are differences in depth between adventitious root and
the surface of the green moss horizon. ARHo estimates above are derived from mean
site values.












D IF .......
DepthR Depth=
-0.46 + 1.4 x0 I04"
(density/ha)
R = 0.4, P=-0.02
A H
Depth, DeplhT=
0.49 2.0 x 104
(density/ha)
R' = 0.28, P<0.001


0 5000 10000 15000 20000 25000
Mean tree density/ha


Figure 3-6. Difference between SOL depths at randomly located (DepthR) sampling points and
depth at tree base points (DepthT) compared to mean tree density/ha across 38 sites
burned in 2004. The fibric (F) and humic (H) horizons are shown.








A 3


3,


1t

15



i



14
-9

3-
B I!

11-





j:J


~1~


10.1-IS 15.1-20


ram Kx. Bd i dam IOB


Figure 3-1. Frequency, mean and horizon depths of post-fire organic soils at burned sites. A)
Frequency of mean (+ 1 SE) depth. B) Horizon depths of post-fire soil organic layers
*indicates the number of sites in each class


m. -


5.1 D1


0-5


| Fibric

i Itimif









Next, since we calculated the SODpre-F at tree bases, we used our random/tree bias

corrected residual SOL depth to estimate total SOL combustion:

%SOL combustion = ((SODpre-F SODcorr.post-F)/ SODpre-F) 100

Percent SOL combustion across all sites was generally high with a mean value of 66.8 %

+ 3.7 (mean 1 SE), with loss ranging from 34 to 96% of the organic soil depth. In the original

experimental design, our aim was to select burn sites along a continuum from low to high fire

severity, but our measurements show that overall most of the sites were burned severely.

Since the ARH method is based on accurately reconstructing pre-fire depth, compared

our estimates with data collected prior to the wildfire (Hollingsworth et al. 2006) for 13 of our

burned sites (Question 1). Our reconstructed SOL depth of 26.6 1.66 cm, (mean 1 SE) for

these sites was not significantly different from measured pre-fire depths of 23.3 1.55 cm (mean

+ 1 SE, Hollingsworth unpublished data; paired-ti, 12=1.65, P=0.13).

Reconstructing Depth of Organic Soil Horizons

After reconstructing SODpre-F with the ARH method, we also had to divide total depth into

horizons to quantify C and N pools (Questions 4 and 6). We examined a number of factors in the

unburned forest stands to determine if they could be used as predictors of the depth of the soil

horizons, focusing on stand characteristics that could also be easily measured at burned sites.

First, we compared the depth of each horizon to the total SOL depth and all were significantly

positively related (Figure 3-7a). Next, we found that the F and H horizons as a percent of total

depth were not significantly related to total depth. The GM horizon was negatively related to

total depth, while the BM horizons were positively related (Figure 3-7b).

For F and H, we used a constant mean proportion (derived from the unburned sites) of 46%

and 30%, respectively, to divide the total SOD into horizons. We compared other easily









LIST OF REFERENCES


Ahrens, R. J., J. G. Bockheim and C. Ping. 2004. The Gelisol order in soil taxonomy. Pages 2-10
in J. Kimble, editor. Cryosols: permafrost-affected soils. Springer-Verlag, New York,
NY, USA.

Amiro, B. D., B. J. Stocks, M. E. Alexander, M. D. Flannigan and B. M. Wotton. 2001. Fire,
climate change, carbon and fuel management in the Canadian boreal forest. International
Journal of Wildland Fire 10: 405-413.

Amiro, B. D., J. I., MacPherson, R. L. Desjardins, J. M. Chen, J. Liu. 2003. Post-fire carbon
dioxide fluxes in the western Canadian boreal forest: evidence from towers, aircraft and
remote sensing. Agricultural and Forest Meteorology 115: 91-107.

Areseneault, D. 2001. Impact of fire behavior on post-fire forest development in a homogenous
boreal landscape. Canadian Journal of Forest Research 31: 1367-1374.

Bergner, B., J. Johnstone and K. K. Treseder. 2004. Experimental warming and bum severity
alter soil CO2 flux and soil functional groups in a recently burned boreal forest. Global
Change Biology 10: 1196-2004.

Bigler, C., D. Kulakowski. and T. T. Veblen. 2005. Multiple disturbance interactions and
drought influence fire severity in Rocky Mountain subalpine forests. Ecology 86 (11):
3018-3029.

Canada Soil Survey Committee 1978. The Canadian system of soil classification.Canadian
Department Agriculture Publishers 1646.

Dixon, R. K., S. Brown, R. A. Houghton, A. M. Solomon, M. C. Trexler and J. Wisniewski
1994. Carbon pools and flux of global forest ecosystems. Science. 263: 185-190.

Epting, J. and D. Verbyla. 2005. Landscape-level interactions of pre-fire vegetation, burn
severity, and post-fire vegetation over a 16-year period in interior Alaska. Canadian
Journal of Forest Research 35: 1367-1377.

Flannigan, M. D., B. J. Stocks. and B. M. Wotton. 2000. Climate change and forest fires. The
Science of the total environment 262: 221-229.

Gower, S. T., A. Hunter, J. Campbell, J. G. Vogel, H. Veldhuis, J. Harden, J. M. Norman, C. J.
Kucharik and D. Anderson. 2000. C Nutrient dynamics of the BOREAS southern and
northern forests. Ecoscience. 4, 481-490.

Greene, D. F., J. Noel, Y. Bergeron, M. Rousseau, and S. Gauthier. 2004. Recruitment of Picea
mariana, Pinus banksiana and Populus tremuloides across a burn severity gradient
following wildfire in the southern boreal forest of Quebec. Canadian Journal of Forest
Research 34: 1845-1857.









volume or depth of surface fuel consumption means that methods of quantifying fire severity in

other temperate ecosystems cannot necessarily be easily applied to the boreal forest. Although

fires in the boreal forest can be high intensity, there is considerable variability in ground fire

severity ranging from lightly-scorched to fully-combusted organic soil leaving just ash and

mineral soil, which is a strong control on post-fire vegetation (Johnstone and Chapin 2006).

Deciduous trees such as aspen (Populus tremuloides) may show a positive correlation with high

fire severity while black spruce shows a negative response to increasing bum severity (Johnstone

and Kasischke 2005). Early post-fire stand density and composition are good predictors of

future stand patterns (Johnstone et. al 2004). Therefore, constraining fire severity in the boreal

forest may also be helpful in predicting future forest stand patterns.

Fire severity is a good indicator of the carbon flux from fire in the boreal forest (Kasischke

et al. 1995), and an accurate method of measuring it would enhance carbon accounting. Fire

severity, by definition, is directly linked to the amount of biomass that is consumed during a fire,

and therefore it can be a good indicator of how pools of carbon change during a disturbance

cycle (Kasischke et al. 2000). As atmospheric carbon dioxide levels continue to rise throughout

the world and influence changing fire regimes, it is important to be able to quantify these boreal

forest carbon pools and the response to disturbance.

Within studies examining effects of wildfires on ecosystem recovery and carbon storage

patterns, many different methods have been used to quantify fire severity. Three main methods

that have commonly been used by most studies to estimate fire severity in the boreal forest are:

1) depth of post-fire organic soil and mass remaining, and depth of organic soil consumed

(deGroot et al. 2004, Johnstone and Chapin 2006, Kasischke and Johnstone 2005, Miyanishi and

Johnson 2002), 2) the amount of canopy biomass consumed (Aresenault 2001, Greene et al.









035
A

O Dead lmosm

F ibric


In lf Hurnic





R. -------------
0
B
9








2.



1I I I


M 3.1-ID 19.145 13.1-248
Pftetm OL .d h Singes (ein)

Figure 3-2. Mean soil organic nitrogen and carbon pools in post-fire soil organic layers by
horizon and depth class. A) Soil organic nitrogen. B) Soil organic carbon.









tree differences (depth at randomly sampled points minus depth at tree bases) in total depth or

individual horizon depths were not significantly related to mean site DBH or basal area (data not

shown). Tree density, by contrast, was significantly related to the F and H horizons' random

versus tree difference; these horizons comprise >80% of total depth (figure 3-6). However, tree

density was not significantly related to the total SOL or DM depth (data not shown).

In order to account for the random/tree depth bias in our reconstruction of pre-fire and

post-fire SOL, we calculated a correction factor for each horizon that accounted for the random

versus tree depth bias (random: tree ratio). Bias-corrected depths for the DM and F horizons

were not related to stand structure and thus were:

DMcorrected= 1.1 Dmtree + 0.7
Fcorrected = 0.9 Ftree +0.7
Hcorrected = 0.7 Htree + 0.6

Adding the corrected values yields a total corrected post-fire SOL depth (SODcorr. post-F),

therefore:

SODcorr.post-F = DMcorrected + Fcorrected + Hcorrected.

We used these depth corrections with our pre-fire depth estimates to calculate post-fire

organic soil depth and subsequently organic soil consumption at each tree sampling point.

Fire Severity of Organic Soil

We combined our measurements from burned and unburned stands to calculate organic soil

combustion as a percentage of total original SOL depth and then used those same depths with

p b, %C and %N to estimate SOL mass, and SOC and SON combustion. We first used the

following equation to estimate pre-fire SOL depth (SODpre-F) for our burned sites.

SODpre-F = SODpost-F + ARH + ARo.









at all burned (n= 4) and unburned (n=8) sites. These mean burned site values were used with the

post-fire, randomly located sampling point horizon depths (n=l 1) to calculate general post-fire

soil organic carbon (SOC) and soil organic nitrogen (SON) pools :

Post-fire SOC or SON pool (kg/m2)=


S( b DM depth DM % CDM(or % NDM))+( p b F depthF % CF (or % NF)) + ( b H
depthH % CH (or % NH))

Our next step, however, was to reconstruct pre-fire soil C and N pools for the burned sites

and subsequent combustion emissions. However, if we simply added on the missing depth to our

post-fire pools, we might not account for missing mass. Besides, horizons that were present, but

partially burned may have had burned material deposited from the horizon or vegetation above

them, which could alter, and in most cases enhance, the nutrient content and bulk density relative

to the equivalent unburned horizon (Neff et al. 2005). Including this residual material as

indicative of the pre-fire pool size of the layer would result in an over-estimate of the pre-fire

pool for that horizon.

In order to correct for these deposits, we used values from both burned sites (b), which

were mean site values and unburned (u) values, which were the means from all the unburned

sites. We calculated pool size for each of the 11 tree base points using the following values to

account for the deposits. If DM were present (thus, F and H were intact), then we used the

following values:

1. DM = depthb, p b u, [C or N],,
2. Fibric (F) = depthb, p b b, [C or N]b,
3. Humic (H) = depthb, p b b, [C or N]b.

If the F horizon were present, then we used these values:

1. F = depthb, p b u, [C or N]u, b b,
2. H = depthb, p b b, [C or N]b.









Finally, if only the H horizon were present then we calculated the nutrient pool using these

values: depthb, p b u, [C or N],. By using the unburned values for the partially burned horizons,

we were able to avoid mixed values from possible ash deposits.

We applied these rules when re-constructing pre-fire pools. Thus, we used the post-fire

values for p b, [C] and [N] for intact burned layers and the unburned mean values for partially or

wholly consumed horizons in combination with the reconstructed pre-fire depths (at each tree

point) to calculate SOC and SON pools. Finally, the pre and post-fire values were compared to

estimate SOC and SON losses (kg/m2).

CBI and Combustion

Our final objective for this study was to discern whether CBI, a quick visual assessment

method would be related to our more intensive assessment with adventitious roots and stand

structure (Question 5). CBI is a standardized index that was developed by the US Forest service

and can be used to 'score' fire severity and then link it to remote sensing data. CBI was designed

to capture the variability of burns within five vertical strata: 1. substrate (litter and duff), 2.

herbaceous and small trees and shrubs (less than 1 meter), 3. tall shrubs and trees (1-5 meters), 4.

intermediate trees or sub-canopy trees, and 5. upper canopy or dominant trees (Key and Benson

2005). The five vertical strata were also grouped for further analysis (according to CBI

standards) into the understory score (1 and 2) and the overstory score (3, 4 and 5). We chose the

overstory score for comparison to our canopy biomass loss estimates since our canopy biomass

estimates included all trees that would be equivalent to intermediate and tall trees. We compared

total CBI scores as well as overstory, understory and substrate CBI scores (Verbyla, unpublished

data 2005), to our organic soil and tree canopy biomass combustion assessments.









measured in a burned site. Then, we used mean values from across all unburned sites to obtain

bulk density and C and N concentration values for each horizon. Using these mean values for all

sites does not capture all of the variability inherent in these organic nutrient pools; however, it is

an attempt to more accurately calculate pre-fire and post-fire pools and emissions on the ground

than previous studies. Therefore, post-fire SOL depth and re-constructed pre-fire depth become

the independent variables in calculating C and N pools.

Canopy Fire Severity and Biomass

Canopy fire severity and biomass losses were estimated by Canopy (minus bole)

combustion was visually assessed and then allometric equations were used to determine biomass

from DBH and biomass combusted. C concentration in the canopy biomass is about 50% and N

concentration ranges from 0.4-1%, so canopy C and N pools were calculated too. Finally, fire

severity was analyzed as the missing amount of biomass from the ground and the canopy and

mean losses across our sites were about 65% of biomass. We compared our time-consuming

destructive fire severity measurements to a quicker visual assessment (CBI) to see how well CBI

worked.

CBI

Our data suggests that CBI shows promise as a quick method of assessing fire severity on

the ground. Total CBI scores were significantly but weakly related to percent biomass consumed

for canopy (minus the bole) but were highly correlated with organic soil combustion. However,

since most wildfires in black spruce forest are considered stand-replacement, it can be argued

that there is not as much variability in stand consumption as there is in organic soil combustion

(at least that can be visually estimated quickly). In other words, since the majority of trees die in

most wildfires in black spruce forests, it can be difficult to differentiate between varying degrees

of severity. Therefore, even though the correlation between CBI and our combustion estimates is

49









ACKNOWLEDGMENTS

I would like to thank my advisors, Drs. Michelle Mack and Ted Schuur, and committee

member, Dr. Jill Johnstone thanks for the excellent training, support and opportunity to work on

a great project with great people. I thank all of the folks in the Mack and Schuur labs for your

assistance (especially Grace Crummer, Yadny Acosta, Ashley Williams, Mike Goldschlag, Nina

Lavato, etc.). I thank all of folks in Alaska who assisted me: Laura Gutierrez, Adrienne Frisbee,

Dana Nossov, Emily Tissier, Teresa Hollingsworth, Emily Bemhardt, Terry Chapin, etc. Finally,

I would like to thank Dean and Lucy for supporting me to the end of my writing.

































2007 Leslie A. Boby




Full Text

PAGE 1

1 QUANTIFYING FIRE SEVERITY AND CA RBON AND NITROG EN POOLS AND EMISSIONS IN ALASKAS BOREAL BLACK SPRUCE FOREST By Leslie A. Boby A MASTERS THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2007

PAGE 2

2 2007 Leslie A. Boby

PAGE 3

3 To Alaska, Thanks for all the wonderful memories

PAGE 4

4 ACKNOWLEDGMENTS I would lik e to thank my advisors, Drs. Michelle Mack and Ted Schuur, and committee member, Dr. Jill Johnstone thanks for the excelle nt training, support and opportunity to work on a great project with great people. I thank all of the folks in the Mack and Schuur labs for your assistance (especially Grace Crummer, Yadny Acos ta, Ashley Williams, Mike Goldschlag, Nina Lavato, etc.). I thank all of folks in Alaska who assisted me: Laura Gutierrez, Adrienne Frisbee, Dana Nossov, Emily Tissier, Teresa Hollingsworth, Emily Bernhardt, Terry Chapin, etc. Finally, I would like to thank Dean and Lucy for s upporting me to the end of my writing.

PAGE 5

5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4LIST OF TABLES................................................................................................................. ..........7LIST OF FIGURES.........................................................................................................................8ABSTRACT.....................................................................................................................................91 INTRODUCTION..................................................................................................................112 METHODS.............................................................................................................................16Study Area..............................................................................................................................16Experimental Design and Measurements............................................................................... 17Patterns of Post-Fire Soil Organic Matter.......................................................................17Sampling Design: Randomly Located and Tree Base Points.......................................... 18Pre-fire Organic Soil Depth............................................................................................. 18C and N Sampling........................................................................................................... 18Tree Biomass, Stand Stru cture and Combustion............................................................. 19Unburned Sites................................................................................................................19Lab Analysis...........................................................................................................................20Horizon Depths in Relation to Total Organic Soil Depth....................................................... 21Preand Post-Fire C and N Pools........................................................................................... 21CBI and Combustion..............................................................................................................23Statistical Analysis........................................................................................................... .......243 RESULTS...............................................................................................................................26Burned Black Spruce Stands..................................................................................................26Reconstructing Pre-Fire Depth of the Soil Organic Layer..................................................... 27Intra-site Variation in Post-Fire So il Organic Layer Characteristics......................................27Fire Severity of Organic Soil.................................................................................................. 29Reconstructing Depth of Organic Soil Horizons....................................................................30Reconstructing Depth of Organic Soil Horizons....................................................................32Soil Organic Layer C and N Pools and Combustion..............................................................33Tree Biomass, C and N Pools and Combustion...................................................................... 34CBI and Combustion Losses.................................................................................................. 344 DISCUSSION.........................................................................................................................47Adventitious Root Height.......................................................................................................47C and N Pools.........................................................................................................................48Canopy Fire Severity and Biomass......................................................................................... 49CBI..........................................................................................................................................49

PAGE 6

6 Other Methods of Measuring Fi re Severity and Em issions.................................................... 50Organic Soil.....................................................................................................................50Canopy Consumption and Tree Mortality....................................................................... 51C and N Pools..................................................................................................................51Conclusions.............................................................................................................................52LIST OF REFERENCES...............................................................................................................53BIOGRAPHICAL SKETCH.........................................................................................................57

PAGE 7

7 LIST OF TABLES Table page 3-1 Post-fire soil organic horiz ons m ean depth, bulk density ( b), C and N concentration......................................................................................................................453-2 Soil characteristics by horizon for 28 unburned sites........................................................ 453-3 Soil organic layers, tree canopy and ecos ystem mass and C combustion as well as C emissions compared to CBI scores.................................................................................... 46

PAGE 8

8 LIST OF FIGURES Figure page 2-1 Map of interior Alaska, including a map of the areas burned by wildfire in 2004 and study sites. ..........................................................................................................................253-1 Frequency, mean and horiz on depths of post-fire orga nic soils at burned sites................ 363-2 Mean soil organic nitrogen and carbon pools in post-fire soil organic layers by horizon and depth class...................................................................................................... 373-3 Percent frequency of sites and tree de nsity in basal area classes across 38 sites burned in 2004...................................................................................................................383-4 Frequency of 28 unburned sites among 9 a dventitious root height depth offset classes................................................................................................................................393-5 Depth of soil organic horizons at randomly located points compared to depths at tree base points across 38 sites burned in 2004........................................................................ 403-6 Difference between soil organic layer depths at randomly located sampling points and depth at tree base points compared to mean tree density/ha...................................... 413-7 Total soil organic layer depth compared to soil horizon depth and horizon depth as percent of total depth......................................................................................................... 423-8 Mean carbon (C) emissions and percen t of total C combustion by post-fire soil organic layer depth classes................................................................................................. 433-9 Mean nitrogen (N) emissions and percen t of total N combustion for four post-fire soil organic layer depth cla sses across 38 burned sites......................................................44

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9 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science QUANTIFYING FIRE SEVERITY AND CA RBON AND NITROG EN POOLS AND EMISSIONS IN ALASKAS BOREAL BLACK SPRUCE FOREST By Leslie A. Boby December 2007 Cochair: Edward A. G. Schuur Cochair: Michelle Mack Major: Interdisciplinary Ecology Fire severity can be define d as the amount of biomass combusted by wildfire. Stored carbon (C) and nitrogen (N) are emitted into the atmosphere as wildfires consume vegetation and soil organic layers, thus C and N em issions should be related to fire severity. Since boreal forests store 30% of the worlds terrestrial C and are subject to high-inte nsity, stand-replacing wildfires, it is critical to be able to estimate C fluxes from wildfires. Furthermore, quantifying fire severity is important for predicting post-fire vegetation recovery and future C sequestration. We reconstructed pre-fire organic soil layers and quantified fire severi ty levels from the 2004 wildfires in Interior Alaska with the adventitious root height (ARH) method. We tested the ARH method in unburned stands and by comparing our reconstruc ted values in burned stands with actual prefire measurements. We found that ARH correlate d to organic soil height in unburned stands (with a small offset of 3 cm). We measured organic soil (using the ARH method) and stand characteristics in boreal black spruce forest and estimated the amount of soil and canopy biomass consumed by fire. We compared these results to the composite burn index (CBI), a standardized visual method, which has not been widely used in the boreal forest. CBI assessments were significantly related to our ground and canopy fire severity estimates. We calculated C and N

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10 pools using C and N concentration and bulk density estimates from soils sampled in burned and unburned stands. We conclude that the ARH method can be used to reconstruct pre-fire organic soil depth, C and N pools and to assess fire severity. Furthermore, CBI shows promise as a way of estimating fire severity quickly and is a reas onably good predictor of bi omass and soil C loss.

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11 CHAPTER 1 INTRODUCTION W ildfire is the major disturbance in Alaskas boreal forest and conse quently is one of the major factors that controls the distribution of soil and plant ca rbon (Harden et al. 2000). Fires vary considerably in severity, or the amount of surface and canopy fuel consumed (Wang 2002). Fire severity is a measure that integrates activ e fire characteristics and immediate fire effects, and is estimated as the proportion of biomass combusted (Lentile et al. 2006). Wildfires burn heterogeneously throughout the boreal landscape, l eading to varying levels of fire severity in post-fire ecosystems. Aspect, elevation, soil mois ture, and weather conditions concomitantly act with variations in vegetation fuel types and forest structure to influence fire severity patterns as well (Johnson 1992). Furthermore, interannual vari ation in area burned is high and the severity (Harden et al. 2000) and configur ations (Kasischke and Johnstone 2005) of wildfire effects are often linked to seasonal changes in fuel conditions Patterns of fire severity influence post-fire vegetation composition and regrowth (Ars eneault 2001, Johnstone and Chapin 2006, Wang 2002), and subsequent carbon uptake or emissions (L eComte et al. 2006). Th erefore, in order to measure the magnitude of the fire disturbanc e and understand effects on soil and plant carbon accumulation, it is necessary to develop quantitative measures to describe fire severity. Boreal forests of interior Al aska are dominated by even-age d stands of black spruce ( Picea mariana) and white spruce (Picea glauca) that are generally rooted in thick (5>50 cm) layers of organic material overlying mineral soil. These su rface organic horizons are largely derived from live and dead mosses and inputs from vascular plant litter, root turnover and lichen (Miyanishi and Johnson 2002). According to the Canadian syst em of soil classification, these organic soil horizons can be categorized as litter (recently cas t and unaltered plant remains), fibric (slightly decomposed, but still identifiable material) and humic (more decomposed and not identifiable),

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12 with mineral soil below (Canada Soil Survey Committee 1978). These thick horizons of organic material on the mineral soil surface make boreal forests vastly different from other temperate forests in carbon sequestration and emissions as well as fire effects. Soil carbon pools in the boreal forest are estimated to be 20-60% of the worlds terrestrial soil carbon pool (Dixon et al. 1994, McGuire et al. 2000). The Alaskan boreal fo rest, which is estimated to cover about 17 million ha, stores about 4.8 Mg C of this C or 27.6 Mg C/ha (Yarie and Billings 2002). Outputs from the surface organic horizon are controlled by heterotrophic respiration of organic matter, and by fire consumption (Harden et al. 2000). Fi re return intervals are estimated to be approximately 80-150 years for the boreal fore st (Johnson 1992, Payette et al. 1992). However, climate change is expected to increase the freque ncy and the intensity of wildfires as well as the duration of the fire season (Flannigan et al. 2000 ). Disturbance from wildfire regenerates the forest into early successional states of forest stands that include deci duous tree species such as aspen ( Populus tremuloides) and Alaskan birch ( Betula neoalaskana). These young forests have different carbon dynamics than the mature forest and tend to decrease the carbon sink (Amiro et al. 2003). Wildfire severity has a strong infl uence on the composition of early successional forests and thus carbon dynamics over time (J ohnstone 2006, Aresenault 2001, LeComte et al. 2006). Fire behavior and severity patterns in the bor eal forest differ greatl y from many other fire regimes due to the high fire intensity and flam e length that characterizes boreal fires (Johnson 1992). Additionally, the canopy often burns in a fast-paced, high inte nsity crown fire which often results in near total canopy death (Johnson 1992) while the thick organic soil horizons may burn in active flames or in smoldering consumption (Miyanishi and Johnson 2002). This combination of high frequency of 100% aboveground plant mort ality plus the importance of quantifying the

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13 volume or depth of surface fuel consumption means that methods of quantifying fire severity in other temperate ecosystems cannot necessarily be easily applied to the boreal forest. Although fires in the boreal forest can be high intensity, there is considerable variab ility in ground fire severity ranging from lightly-scorched to fu lly-combusted organic soil leaving just ash and mineral soil, which is a strong control on postfire vegetation (Johnstone and Chapin 2006). Deciduous trees such as aspen ( Populus tremuloides ) may show a positive correlation with high fire severity while black spruce shows a negative response to increasing burn severity (Johnstone and Kasischke 2005). Early post-fire stand density and composition are good predictors of future stand patterns (Johnstone et. al 2004). Therefore, constraini ng fire severity in the boreal forest may also be helpful in predicting future forest stand patterns. Fire severity is a good indicator of the carbon flux from fire in the boreal forest (Kasischke et al. 1995), and an accurate method of meas uring it would enhance carbon accounting. Fire severity, by definition, is directly linked to the amount of biomass that is consumed during a fire, and therefore it can be a good i ndicator of how pools of carb on change during a disturbance cycle (Kasischke et al. 2000). As atmospheric carbon dioxide leve ls continue to rise throughout the world and influence changing fire regimes, it is important to be able to quantify these boreal forest carbon pools and the response to disturbance. Within studies examining effects of wildfi res on ecosystem recovery and carbon storage patterns, many different methods have been used to quantify fire severity. Three main methods that have commonly been used by most studies to estimate fire severity in the boreal forest are: 1) depth of post-fire organic soil and mass re maining, and depth of organic soil consumed (deGroot et al. 2004, Johnstone and Chapin 2006, Kasischke and Johnstone 2005, Miyanishi and Johnson 2002), 2) the amount of canopy biomass consumed (Aresenault 2001, Greene et al.

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14 2004, Purdon et al. 2004) and 3) remote sensin g, such as Landsat or aerial photography, that combines reflectance from remaining canopy a nd ground layers (Bigler et al. 2004, Epting and Verbyla 2005, Roy et al. 2006). Within most of these studies, organic soil and canopy consumption were visually estimated and some of these studies used more than one method to estimate fire severity. Subsequently, these estimates of fire severity were used as a parameter for predicting future change in canopy and understory composition, or for quantifying carbon fluxes. All of these methods are based on surveying pos t-fire conditions. The Composite Burn Index (CBI) has been developed as a standardized visu al estimate method of me asuring fire severity within the United States that combines inform ation on soil and canopy combustion together (Key and Benson 2005). CBI was developed in the co ntinental United States but has not been extensively tested for its applicability to boreal sy stems. Fire severity levels are often based on visual combustion estimates, but in order to es timate the proportion of biomass consumed by fire, it is necessary to estimate the pre-fire biomass. In other wo rds, in order to consistently calculate how much was lost during the fire, it is necessary to know or estimate what was there before the fire. In our study, we tested a method for determ ining pre-fire conditions and subsequent combustion losses by measuring post-fire forest st and conditions. In particular, we wanted to discover if a method of measuring adventitious root height on bl ack spruce boles could be used to: 1) reconstruct pre-fire orga nic soil height, 2) quantify pre and post-fire carbon and nitrogen pools, and 3) constrain wildfi re organic soil combustion estimates. We used comparisons between burned and unburned black spruce forest stands to address th e following questions: 1. Is adventitious root height above post-fire organic soil equi valent to unburned and pre-fire organic soil height? 2. Does the adventitious root height method bias our estimates of soil consumption because prefire and residual organic soil depth is measured only at the base of trees?

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15 3. Are post-fire depth disparities at sampling points located randoml y or at tree bases due to systematic differences in combustion rates or pre-fire organic soil depths under trees? 4. How are the depths of individual soil horizons related to total organic soil depth? 5. Does the adventitious root collar method corre late with the visually -estimated Composite Burn Index? 6. What is the relationship between C and N emissions and burn severity? This study presents data from a range of black spruce forests distributed across gradients of moisture availability and fire severity that were used to characterize standlevel patterns of fire severity across the landscape.

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16 CHAPTER 2 METHODS Study Area We established 90 sites in forest stands th at bu rned in the su mmer of 2004 in three different fires (Dalton Comple x, Taylor Complex and Boundary Fire) and 28 unburned forest sites paired with the three fi res. The approximately 250 000 km2 study area (figure 2-1) that encompasses these sites is located within central interior Alaska with boundaries extending north to the Brooks range (~67 deg N), south to the Alaska Range (~63 deg N), east to the AlaskaCanada border (~142 deg W) and west to the Dalton Highway (~150 deg W) (Hollingsworth et al 2006). The area includes small mountain rang es, slightly sloped uplands along with large flatland areas and broad floodplains adjacent to braided rivers (H ollingsworth et al 2006). Open to closed-canopy black spruce ( Picea mariana) in mostly even-aged st ands was the dominant vegetation type in our study area with occasional white spruce ( Picea glauca ) and deciduous species such as aspen ( Populus tremuloides ) and birch ( Betula papyrifera ). Vegetation across the study area includes three black sp ruce community types: acidic black spruce/ lichen forest, nonacidic black spruce/rose/horsetail forest and tree-line black spruce woodland (Hollingsworth et al 2006). Temperatures across this region are extreme and range from -70 C to 35 C with mean annual precipitation at a bout 285 mm including about 35% from snow (Hinzman et al 2005). Soils of interior Alaska are generall y undeveloped and primarily (~90%) consist of Inceptisols, Gelisols, Histosols and Entisols (Ahrens et al 2004). For our study, we selected sites that represente d a range of fire severity or for which we had pre-fire data (Hollingsworth et al. 2006). We intensively studied a subset of 38 of these sites (six of which were at tree-line), which were c hosen to maximize variation in fire severity and edaphic conditions. These sites were selected from areas burned by the three different wildfires;

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17 the fire severity varied among and within the fires from low to high. Unburned sites were chosen from those described in Hollingsworth et al. (2006) and were se lected to correspond to general locations and edaphic cond itions of the burned sites. Experimental Design and Measurements In June 2005, we established plots to estim ate pre and post fire soil organic carbon and nitrogen pools in 38 burned sites for intensiv e study. The experim ental unit was a 30 m x 30 m square plot which was sampled with a 1 x 30 m be lt transect. Measurements in the plots included post-fire organic soil depth, carbon (C) and nitrogen (N) pools; tree density, basal area (BA) and canopy consumption. As part of a broader study, post-fire vascular pl ant species cover and composition, and tree seed rain and seedling recru itment were also measured in these plots. Identical belt transects were established in ad jacent unburned forest st ands in the summer of 2006 in order to obtain the values necessary to reconstruct pre-fire so il C and N pools. These sites are referred to as burned and unburned, respectively in this paper. Patterns of Post-Fire Soil Organic Matter Across all burned sites, com bustion ranged from low, wherein a large pr oportion of the fibric or upper duff layer had not burned, to high, where th e fibric layer was completely combusted and the humic or lower duff layer was partially or fully combusted (Rowe et al 1983). Within these sites, depth of remaining soil organic layers (SOL) were measured at 11 randomly selected points on a transect in order to characterize site -wide post-fire SOL. At each point, we measured the depth of each of the following horizons: dead moss (undecomposed or slightly decomposed dead moss), fibric (moderately decomposed or ganic matter with more roots than moss or Oe horizon) and humic (highly humified or decomposed organic matter or the interface between the humic horizon and the A horizon) down to th e mineral soil horizon (Canadian Agricultural Services Coordinating Committee 1988, So il Survey Staff 1998, Neff et.al. 2005).

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18 Sampling Design: Randomly Located and Tree Base Points In addition to our random ly located sampling poi nts, we also measured SOL depth near the base of trees. Tree sampling points were chosen at the tree nearest to a given random sampling point and SOL depth was sampled as close to the bole as possible, although, the distance to bole varied due to large roots that prohibited digging. At tree sampli ng points, we also measured the height from the top of the remaining SOL to the highest adventitious root on the bole of the tree, henceforth referred to as adventitious root height (ARH). Since pre-fire SOL depth was only reconstructed at tree sampling poi nts, we compared SOL depth at tree base and random sampling points (burned and unburned sites) in a t-test to determine if sa mpling only at trees would bias our measurements (Question 2). Pre-fire Organic Soil Depth We then combined ARH with post-fire SOL de pth (at tree b ases) to estimate pre-fire SOL depth. Thus, pre-fire SOL depth was equal to post-fire SOL depth plus ARH. SOL combustion was the difference between pre-fire SOL dept h and post-fire SOL de pth. To test if our reconstructed pre-fire SOL depths were accurate (Q uestion 1), we compared our values to actual pre-fire SOL measurements (Hollingsworth et al 2006). C and N Sampling In addition to m easuring SOL depth, we also sampled soils at four sampling points that were representative of intra-site variation in fire severity. Organic so il horizons were sampled volumetrically and separated into the horizons noted above; dead moss (DM), fibric (F) and humic (H). Mineral soil was sampled via volum etric coring at 0-5 cm, 5-10 cm depths. Soil samples were stored in coolers with ice packs in the field and in freezers prior to laboratory analyses.

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19 Tree Biomass, Stand Structure and Combustion Besides our soil m easurements, we also charac terized forest structure at the burned and unburned sites. We measured the diameter of trees at breast height (DBH; 1.4 m) for all trees greater than or equal to 1.4 m tall and basal diameter for trees less than 1.4 m tall that were rooted within six, 2 x 5 m subplot s along the transects. Fallen trees were included in this census if we estimated that they had been rooted in the subplot. We used these values to calculate tree density, basal area and aboveground biomass (excludi ng the bole). We visually estimated % fire consumption in five classes (0, 25, 50, 75 or 100 pe rcent) of four compon ents of the tree canopy: cones, needles, fine branches and coarse branches. To calculate pre-fire biomass of canopy (excluding tree bole) components, we grouped trees into three diameter and height classes and applied allometric equations that predicted stan ding dry biomass from DBH of individual trees. Classes consisted of 1) DBH greater than 2.7 cm and height greater than 1.4 m (Mack et al. In Press), 2) DBH less than 2.7 cm and height greater than 1.4 m (M.C. Mack, unpublished data) and 3) height less than 1.4 m (M.C. Mack, unpublished data). We combined the visual estimates of % c onsumption times the pre-fire biomass to determine canopy biomass fire consumption (in g of dry mass) for each tree. Moreover, we calculated canopy C and N pools and subsequent emissions for each canopy component. We used 50% C concentrations for estimating C biom ass and 0.4% N for cones, fine branches and coarse branches and 1% N for needles (Gower et al 2000). Unburned Sites In addition to soil and tree m easurements in bur ned sites, we measured soil characteristics and forest structure in 28 unburned sites using an identical ex perimental design. Since we measured ARH in burned sites as a proxy for pre-fire organic soil depth, we also measured ARH in relation to the surface of th e green moss at the tree bases (Q uestion 1). We measured SOL

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20 depths at 11 randomly located points and at 11 po ints at tree bases along a 30-m belt transect in each site. Tree density, DBH and species identity were estimate d in six2 m x 5 m subplots. SOL horizons were divided into similar categories as the burn plots but the dead moss horizon was referred to as brown moss (BM) and we added a fourth horizon, green moss (GM). We volumetrically sampled soils and measured horizons as described above at ei ght points (four tree bases and four randomly located). Finally, we compared horizon de pths, bulk density ( b) and C and N concentration at tree and randomly located poi nts in unburned forest stands to discover if there were biases due to tree proximity (Question 3). Lab Analysis Approxim ately 370 cores comprising ~1500 tota l soil samples were collected from 37 burned and 28 unburned sites. We calculated the volum e of each soil layer from surface area and depth measurements and processed soils in the lab to obtain oven dry soil weight, b (g/cm3), moisture content (g/g), pH a nd carbon and nitrogen content. Soils were homogenized and any material that could not be mixed such as coarse (>5 mm sticks) or rocks were removed from the sample and the weight and volume of the rocks wa s subtracted from total wet sample weight and volume. Sub samples were initially weighed we t and then dried at 105 deg C for 24-48 hours to determine moisture content. Additional sub samp les (dried at 65 deg C) were rolled into tins and carbon and nitrogen content was determined us ing a Costech Elemental Analyzer (Costech Analytical, Los Angelas, Califor nia, USA). We measured pH of all burned soil samples and a sub-set of the first mineral layer of the unburned soil samples using the WBL method No. 2 (Thomas 1996).

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21 Horizon Depths in Relation to Total Organic Soil Depth We used the ARH measurem ents to estimate pr e-fire SOL depth at the tree bases within the intensive burned sites. Theref ore pre-fire SOL depth is equal to post-fire organic soil depth plus ARH and a correction factor of 3.2 cm to account for displacement in location of uppermost roots relative to the top of the green moss layer, as determ ined from the unburned stands (see results, section III-B). After estimating prefire depth using the a dventitious method, we estimated pre-fire depths of each individual horizon (question 4). Since we measured SOL height in the unburned sites, we compared those sites individual horizon depths to the total SOL dept h (question 4) and other forest stand structural variables (tree density, BA, etc.). We examined the relationship between total organic soil depth and each individual horizon from the 28 unburned sites an d found that green moss (GM) was a constant depth for all points, while brown moss (BM), fibr ic (F) and humic (H) horizons were generally constant proportions (See results, section III-E). In other words, green moss was a similar thickness no matter how deep the organic soil, while the other hor izons varied as a constant proportion of overall organic matter thickness. Cons equently, all of the other horizons (BM, F and H) were estimated as a proportion of the to tal mean depth and equaled 14, 46 and 29 percent respectively. These proportions and the GM consta nt were applied to the re-constructed pre-fire organic soil depth. The reconstructe d horizon depths were then used to calculate pre-fire C and N pools as well as combustion losses. Preand Post-Fire C and N Pools To quantify pre and post-fire C and N pools, we used values from our burned and unburned sites and accounted for post-fire differences (question 6). To start with, we calculated mean site values for each horizons b and percent C and N from destructively harvested cores

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22 at all burned (n= 4) and unburned (n =8) sites. These mean burned site values were used with the post-fire, randomly located sampli ng point horizon depths (n=11) to calculate general post-fire soil organic carbon (SOC) and soil organic nitrogen (SON) pools : Post-fire SOC or SON pool (kg/m2) = ( b _DM depth DM % CDM (or % NDM)) + ( b _F depthF % CF (or % NF)) + ( b _H depthH % CH (or % NH)) Our next step, however, was to reconstruct pr e-fire soil C and N pools for the burned sites and subsequent combustion emissions. However, if we simply added on the missing depth to our post-fire pools, we might not account for missing mass. Besides, horizons that were present, but partially burned may have had bur ned material deposited from th e horizon or vegetation above them, which could alter, and in most cases enhan ce, the nutrient content and bulk density relative to the equivalent unburned horizon (Neff et al 2005). Including this residual material as indicative of the pre-fire pool size of the layer would result in an over-es timate of the pre-fire pool for that horizon. In order to correct for these deposits, we used values from both burned sites ( b), which were mean site values and unburned ( u) values, which were the m eans from all the unburned sites. We calculated pool size for each of the 11 tree base points using the following values to account for the deposits. If DM were present (thu s, F and H were intact), then we used the following values: 1. DM = depthb, b _u, [C or N]u, 2. Fibric (F) = depthb, b _b, [C or N]b, 3. Humic (H) = depthb, b _b, [C or N]b. If the F horizon were present, then we used these values: 1. F = depthb, b u, [C or N]u, b_b, 2. H = depthb, b _b, [C or N]b.

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23 Finally, if only the H horizon we re present then we calculate d the nutrient pool using these values: depthb, b _u, [C or N]u. By using the unburned values fo r the partially burned horizons, we were able to avoid mixed values from possible ash deposits. We applied these rules when re-constructing pr e-fire pools. Thus, we used the post-fire values for b, [C] and [N] for intact burne d layers and the unburned mean values for partially or wholly consumed horizons in combination with th e reconstructed pre-fire depths (at each tree point) to calculate SOC and SON po ols. Finally, the pre and post-fi re values were compared to estimate SOC and SON losses (kg/m2). CBI and Combustion Our final objective for this study was to disc ern whether CBI, a quick visual assessment m ethod would be related to our more intensive assessment with adventit ious roots and stand structure (Question 5). CBI is a standardized index that was developed by the US Forest service and can be used to score fire severity and th en link it to remote sens ing data. CBI was designed to capture the variability of burns within five vertical strata: 1. subs trate (litter and duff), 2. herbaceous and small trees and shrubs (less than 1 meter), 3. tall shrubs and trees (1-5 meters), 4. intermediate trees or sub-canopy trees, and 5. upper canopy or dominant trees (Key and Benson 2005). The five vertical strata were also gr ouped for further analysis (according to CBI standards) into the understory score (1 and 2) an d the overstory score (3, 4 and 5). We chose the overstory score for comparison to our canopy bi omass loss estimates since our canopy biomass estimates included all trees that would be equivalent to intermediate and tall trees. We compared total CBI scores as well as ove rstory, understory and substrate CBI scores (Verbyla, unpublished data 2005), to our organic soil and tree canopy biomass combustion assessments.

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24 Statistical Analysis In analy zing data, we determined each site to be a unit and therefore, used the means of the 11 sampling points within each site to character ize a site. Thus for the burned sites, we had n= 38 sites and for the unburned sites, we had n= 28 sites. Data were normally distributed for our analyses. We performed a series of paired t-test s to compare randomly selected versus tree base sampling points (within sites) (Questions 3 a nd 4) Additionally, we explored relationships between: randomly located and tree sampling poi nt depth differences in burned sites and adventitious height in the unbur ned sites to organic soil heig ht, tree density and basal area (Question 2) ; CBI scores and combustion rates in burned sites as well in a series of regressions (Question 5). We compared our quantified fire severity for each site with the CBI score for each site in a regression analysis.

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25 Figure 2-1. Map of interior Alas ka, including a map of the areas burned by wildfire in 2004 and study sites.

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26 CHAPTER 3 RESULTS Burned Black Spruce Stands Post-fire S OL depth, tree basal area and densit y as well as post-fire soil C and N pools varied considerably across the 38 burned sites. Post-fire SOL dept h ranged from 0-21 cm with 16 sites having 5 cm or less of organic matter dept h, 15 sites having 7-15 cm of organic matter left and 7 sites having 15-21 cm of organic matter remain ing (Figure 3-1a). Ac ross all sites, average soil organic horizon depths ranged from a shallow humic layer remaining to the full soil profile (Figure 3-1b). SOC pools followed similar tre nds and ranged from 0.43 to as much as 14 kg C/m2, with an average of 3.46 0.46 kg C/m2 (Figure 3-2a). SON pools varied from 0.017 0.403 kg N/ m2 and averaged 0.126 0.016 kg N/ m2 (mean 1 SE) across all 38 sites (Figure 32b ) Tree densities at burned sites ranged from 2,000 to 8,000 trees per hectare (Figure 3-3a). Additionally, basal area ranged from 0-5 m2 per hectare to as much as 30 m2 per hectare with 11 sites in the lowest basal area class, 15 sites between 5-10 m2 per hectare and 12 sites between 1030 m2 per hectare (Figure 3-3b). Stand age ranged from 30 176 years with a mean of 91.3 4.7 years old (mean 1 SE; J. F. Johnstone, unpublished manuscr ipt). Age was not related to basal area or stand density (data not shown). Mean tree density across all sites was 6,210 750.8 trees per hectare and mean basal area was 9.4 1.2 m2 per hectare (both values mean 1 SE). Unburned stands had generally the same character istics as burned stands, however, tree density and basal area were sign ificantly greater; 17,148 147 trees per hectare and 16.8 2.2 m2 per hectare (both values mean 1 SE).

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27 Reconstructing Pre-Fire Dept h of the Soil Organic Layer Because adv entitious root development is stimulated by moss and humus cover (Krause and Morin 2005, and Johnstone and Kasischke 2005), we explored th e applicability of using the adventitious root scars on burned trees to estim ate pre-fire organic so il depth (Question 1). Johnstone and Kasischke (2005) hypothesized that the height of the ARH in burned stands indicated the minimum height of the pre-fire SOL surface, or mo re specifically, the top of the green moss layer. To test this hypothesis, we measured the height of the ARH in relation to the top of the green moss layer, hereafter th e adventives root height offset (ARHo), in our 28 unburned sites. ARHo ranged from -7.9 cm below the gr een moss layer to +3.2 cm above (Figure 3-4) with a mean value of -3.2 0.43 cm (mean 1 SE). To better understand factors that might explain ARHo variation, we identified moss type and measured distance to tree from sampling point, DBH of tree, pH, soil mo isture, depth of total organic soil and depth of each layer (GM, BM, F and H). Across all sites, most sampling points were occupied by feather moss (254), with s ubstantially fewer point s occupied by sphagnum (35), unidentified moss species (12) or lichen (1). Site mean ARH offset was not related to moss type, distance to tree, mineral soil pH, soil moisture, total SOL depth or basal area (data not shown). ARHo was, however, significantly po sitively related to tree DBH (ARHo = -5.07 + 0.31 DBH, R2=0.23, F1, 26=7.59, P=0.01). Because this predictor di d not explain much of the variation in the ARHo, we used the mean offset of -3.2 cm to correct our calculations of pre-fire SOL depth (sections D and E below). Intra-site Variation in Post-Fire Soil Organic Layer Characteristics After ascertaining that the ARH m ethod was effective for determining pre-fire SOL depth, we determined whether measuring post-fire SOL depth only at tree bases might bias our estimates of mean SOL at a site (Question 2). Across the burned sites, total organic soil depth

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28 was 8.2 1.0 cm (mean 1 SE) at randomly located sampling points and was comprised of three horizons with the following mean depths: 1.1 0.3 cm (DM), 3.7 0.5 cm (F) and 3.3 0.4 cm (H) (mean 1 SE; Table 3-1). Total organic soil dept h was slightly (6.4% ) but significantly shallower at tree bases (7.5 0.9 cm, mean 1 SE), than at randomly located sampling points (paired-t1, 37=2.40, P=0.02). Site means at tree base a nd randomly located organic soil depths were highly correlated (Figure 3-5). The difference in mean total depth was primarily due to shallower DM horizon depth near trees (0.4 0.2 cm (mean 1 SE); paired-t 1,37=3.30, P=0.02). H horizon depth, by contrast, was greater near trees, 3.8 0.5 cm (mean 1 SE); paired-t1, 37=2.20, P=0.03). Shallower residual SOL depths under trees vers us randomly located points may have been due to: (1) greater organic consumption under trees (Miyanishi and Johnson 2002 and our Question 2) or (2) less pre-fire organic matter acc umulation under trees or a combination of both factors (Question 3). However, we found that in unburned forest stands total SOL depth under trees was not significantly different from SOL depth at randomly located points (paired-t1, 27= 0.37, P=0.71), suggesting that shallowe r SOL depths under trees in th e burned sites were due to greater combustion under trees. Across the unburned sites, m ean total SOL depth at random points was 24.8 1.3 cm (mean 1 SE) Bulk density ( b ), soil moisture and C and N concentrations were not different at tree and random points for all organic soil horizons but did differ between horizons (Table 3-2). Although GM and BM horizons accounted for 24% of the total SOL depth at random points, they only account ed for 10.4% of total profile organic matter, 11.9% of the total SOC pool and 8.8% of the total SON pool. Since we determined that the random/tree de pth bias was not due to pre-fire depth disparities, we considered whet her other stand characteristics e xplained the bias. Random versus

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29 tree differences (depth at randomly sampled points minus depth at tree base s) in total depth or individual horizon depths were not significantly related to mean si te DBH or basal area (data not shown). Tree density, by contra st, was significantly related to the F and H horizons random versus tree difference; these horizons comprise > 80% of total depth (figure 3-6). However, tree density was not significantly related to the total SOL or DM depth (data not shown). In order to account for the random/tree depth bias in our reconstruction of pre-fire and post-fire SOL, we calculated a correction factor for each horizon that accounted for the random versus tree depth bias (random: tree ratio). Bias-corrected de pths for the DM and F horizons were not related to stand structure and thus were: DMcorrected= 1.1 Dmtree + 0.7 Fcorrected = 0.9 Ftree +0.7 Hcorrected = 0.7 Htree + 0.6 Adding the corrected values yields a total corrected post-fire SOL depth (SODcorr. post-F), therefore: SODcorr.post-F = DMcorrected + Fcorrected + Hcorrected. We used these depth corrections with our pre-fire depth estimates to calculate post-fire organic soil depth and subsequently organic soil consumption at each tree sampling point. Fire Severity of Organic Soil We com bined our measurements from burned and unburned stands to calculate organic soil combustion as a percentage of total original SO L depth and then used those same depths with b, %C and %N to estimate SOL mass, and SOC and SON combustion. We first used the following equation to estimate pre-fire SOL depth (SODpre-F) for our burned sites. SODpre-F = SODpost-F + ARH + ARHo.

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30 Next, since we calculated the SODpre-F at tree bases, we used our random/tree bias corrected residual SOL depth to estimate total SOL combustion: %SOL combustion = ((SODpre-F SODcorr.post-F)/ SODpre-F) 100 Percent SOL combustion across all sites was generally high with a mean value of 66.8 % 3.7 (mean 1 SE), with loss ranging from 34 to 96% of the organic soil dept h. In the original experimental design, our aim was to select bur n sites along a continuum from low to high fire severity, but our measurements show that ove rall most of the sites were burned severely. Since the ARH method is based on accurately reconstructing pre-fire depth, compared our estimates with data collected prior to the w ildfire (Hollingsworth et al. 2006) for 13 of our burned sites (Question 1). Our reconstructed SOL depth of 26.6 1.66 cm, (mean 1 SE) for these sites was not significantly different from measured pre-fire depths of 23.3 1.55 cm (mean 1 SE, Hollingsworth unpublished data; paired-t1, 12=1.65, P=0.13). Reconstructing Depth of Organic Soil Horizons After reconstructing SODpre-F with the ARH method, we also ha d to divide total depth into horizons to quantify C and N pools (Q uestions 4 and 6). We examined a number of factors in the unburned forest stands to determine if they could be used as predictors of the depth of the soil horizons, focusing on stand characteri stics that could also be easil y measured at burned sites. First, we compared the depth of each horizon to the total SOL depth and all were significantly positively related (Figure 3-7a). Next, we found that the F and H horizons as a percent of total depth were not significantly related to total de pth. The GM horizon was negatively related to total depth, while the BM horizons were positively related (Figure 3-7b). For F and H, we used a constant mean proporti on (derived from the unburned sites) of 46% and 30%, respectively, to divide the total SOD into horizons. We compared other easily

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31 measured stand-level variables to GM and BM horizons to better understand why these layers varied as a percent of total depth. Green moss dept h was not related to tree density or basal area We measured b, and C and N concentrations in th e burned and unburned sites and coupled these values with SOL depths to quantify pre-fire and post-fire C and N pools (Question 6, See methods section F). In the burned sites, soil co re sampling points were not stratified by random or tree points (Table 3-1). Conversely, the eigh t unburned soil sample core s were extracted at tree and randomly located points (four each); there were no significant differences between b, and C and N concentrations between these two sampling schemes (data not shown, Table 3-2). Mean C and N concentrations for the hor izons ranged from 32.9 .5% and 0.08 1.07%, respectively. Only the F horizon, where roots are likely to be most dense (Neff et al. 2005), had significantly different gravimetri c moisture content (paired-t1, 27= -2.24, P=0.03; random mean= 251.1 41.1 and tree mean= 213.4% 32.7 moisture (mean 1 SE)). Moisture content was not significantly different at random ve rsus tree points for the other three horizons (data not shown). Reconstructed post-fire SO C pools ranged from 0.33 kg/m2 to 10.63 kg/m2 (for a site with very little burning) with a mean of 2.99 0.40 kg/m2 (mean 1 SE) while SON pools ranged from 0.01 kg/m2 to 0.30 kg/m2 with a mean of 0.11 0.02 kg/m2 (mean 1 SE). Reconstructed post-fire element pools were 17.0 3.9 (SOC) and 19.3 3.8 % (SON) less than direct pool measurements (Section A above; SOC paired-t1, 37= 3.31, P=0.002 and SON paired-t1, 37= 3.45, P=0.001). Additionally, the proportion of SOC and SON lost ranged from as low as 0% to as high as 94% for with mean losses of 52.9% 4.8 and 49.8% 5.04 (mean 1 SE) respectively, across the 38 sites (Figures 3-8 and 3-9). SOC emissions were 41.6 5.6 times greater than SON emissions.

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32 Reconstructing Depth of Organic Soil Horizons After reconstructing SODpre-F depth with the ARH method, we also had to divide total depth into horizons to quantify C and N poo ls (Questions 4 and 6). We examined a number of factors in the unburned forest st ands to determine if they could be used as predictors of the depth of the soil horizons, focusing on stand characteristics that coul d also be easily measured at burned sites. First, we compared the depth of each horizon to th e total SOL depth and all were significantly positively related (Figure 3-7a). Next, we found that the F and H horizons as a percent of total depth were not significantly related to total depth. The GM horizon was negatively related to total depth, while the BM horizons were positively related (Figure 3-7b). For F and H, we used a constant mean propor tion (derived from the unburned sites) of 46% and 30%, respectively, to divide the tota l SOD into horizons. We compared other easily measured stand-level variables to GM and BM horizons to better understand why these layers varied as a percent of total depth. Green moss dept h was not related to tree density or basal area (data not shown), but it was only 10.4 0.62% of total soil organic matter depth and it was not highly variable, with a mean of 2.4 0.14 cm (mean 1 SE) and a range between 0.82 and 3.9. Therefore, we used the mean value as a cons tant for all GM layers. Brown moss depth was 13.7% 1.91 (mean 1 SE) of total organic soil depth and was significantly related to basal area (BM depth = -6.07 0.14 (BA/ha), R2=0.18, F1, 25=5.50, P=0.03) and total depth (Figure 3-7a). Combining the two variables in a multiple regres sion did not increase the predictive power above that of total depth alone (dat a not shown). However, the ne gative intercept of the equation resulted in improbable values for sites with shallo w organic layers. Therefore, we calculated BM depth as a constant proporti on of total depth (13.7%).

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33 Soil Organic Layer C and N Pools and Combustion We measured b, and C and N concentrations in the burned and unburned sites and coupled these values with SOL depths to quantify pre-fire and post-fire C and N pools (Question 6, See methods section F). In th e burned sites, soil core sampling points were not stratified by random or tree points (Table 3-1). Conversely, the eight unburned soil sample cores were extracted at tree and randomly located points (f our each); there were no significant differences between b, and C and N concentrations between th ese two sampling schemes (data not shown, Table 3-2). Mean C and N concentrations for the horizons ranged from 32.9 42.5% and 0.08 1.07%, respectively. Only the F horizon, where root s are likely to be most dense (Neff et al. 2005), had significantly diffe rent gravimetric moisture content (paired-t1, 27= -2.24, P=0.03; random mean= 251.1 41.1 and tree mean= 213.4% 32.7 moisture (mean 1 SE)). Moisture content was not significantly diffe rent at random versus tree points for the other three horizons (data not shown). Reconstructed post-fire SO C pools ranged from 0.33 kg/m2 to 10.63 kg/m2 (for a site with very little burning) with a mean of 2.99 0.40 kg/m2 (mean 1 SE) while SON pools ranged from 0.01 kg/m2 to 0.30 kg/m2 with a mean of 0.11 0.02 kg/m2 (mean 1 SE). Reconstructed post-fire element pools were 17.0 3.9 (SOC) and 19.3 3.8 % (SON) less than direct pool measurements (Section A above; SOC paired-t1, 37= 3.31, P=0.002 and SON paired-t1, 37= 3.45, P=0.001). Additionally, the proportion of SOC and SON lost ranged from as low as 0% to as high as 94% for with mean losses of 52.9% 4.8 and 49.8% 5.04 (mean 1 SE) respectively, across the 38 sites (Figure 3-8, a-d). SOC emissions were 41.6 5.6 times greater than SON emissions.

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34 Tree Biomass, C and N Pools and Combustion We used allom etric biomass equations to ca lculate pre-fire canopy biomass and combined these with visual combustion estimates to ca lculate canopy biomass consumed by fire. Mean pre-fire total canopy biomass throughout all sites was 8,686 1,080 kg/ha (mean 1 SE). Conversely, canopy biomass losses were 6,618 960 kg/ha (mean 1 SE), with a mean proportional consumption across all sites of 64% 4 (mean 1 SE). We did not include the bole in our measurements since it was almost always charred or black from ash, regardless of the severity of the fire, and therefore difficult to vi sually estimate consumption. This likely results in an underestimate of canopy consumption. Assuming a general canopy C concentration of 50% and N concentrations of 1% for needles and 0.4% for cones, fine and coarse br anches, pre-fire C and N biomass mean values were 0.43 0.05 kg/m2 and 0.0054 0.001 kg/m2 (mean SE) and ranged from 0.001 to 1.21 kg/m2 for C and 0.0001 to 0.01 kg/m2 for N. Conversely, C and N losses from combustion were 0.37 0.05 kg/m2 and 0.005 0.0006 kg/m2 (mean SE), respectively, and ranged from 0.001 to 1.16 kg C/m2 and <0.0001 to 0.014 kgN/m2 (figure 3-9 a and b). These canopy C and N combustion values are equivalent to mean canopy losses of 80.2% 2.5 and 80.6 % 2.7 respectively. CBI and Combustion Losses We com pared our organic soil and canopy comb ustion estimates with CBI scores from each site (Question 5). We evaluated the followi ng CBI scores in relation to our measurements: total (a total site value), overstory (upper and mid-canopy tree s and tall shrubs), understory (substrate and vascular plants) a nd substrate (soil organic layers and litter). CBI scores range from 1 (low severity) to 3 (high severity) and mean total CBI scores were 2.3 0.07 (mean 1

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35 SE), while mean substrate, understory and overstory CBI scores were: 1.9 0.14, 2.2 0.09 and 2.5 0.06 (mean 1 SE). Generally, substrate and unders tory scores were more frequently lower while canopy scores were often higher and total CBI scores were relatively evenly distributed among the score classes between 1.5 and 3. The overstory CBI score was positively relate d to % of canopy biomass and C combusted and explained 44% of the variation (Table 3-3), but was negatively related to C emitted (27% of variation). Total CBI score only explained 15% of the variation in all canopy measures (Table 3-3). Total, understory, and substrate CBI scores were si gnificantly related to all SOL measurements and between 33-63% of the variation were explained. Although, only one comparison between substrate CBI and SOL C emissions had an R2 value as low as 33% and the rest were 42% or greater (Table 3-3). Total CBI scores were negatively related to ecosystem mass and C combustion and C emissions and explained 45% of the variation (Table 3-3). In general, CBI scores were good estimates of % mass lost (for all components), however, it was not good at estimating the amount of C emissions However, CBI was better for estimating SOL or forest floor C emissions than canopy C emissi ons. Since CBI is a visual estimate, there may be some variation in C concentration or other va riables that is not easily visually detected.

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36 Figure 3-1. Frequency, mean and ho rizon depths of post-fire orga nic soils at burned sites. A) Frequency of mean (+ 1 SE) depth. B) Horiz on depths of post-fire soil organic layers *indicates the number of sites in each class

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37 Figure 3-2. Mean soil organic nitrogen and carbon pools in post-fire so il organic layers by horizon and depth class. A) Soil organi c nitrogen. B) Soil organic carbon.

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38 Figure 3-3. Percent frequency of s ites and tree density in basal ar ea classes across 38 sites burned in 2004. A) Frequency of sites. B) Tree density per hectare.

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39 Figure 3-4. Frequency of 28 unburne d sites among 9 adventitious root height depth offset (ARHo) classes (cm). ARHo are differences in depth between adventitious root and the surface of the green moss horizon. ARHo estimates above are derived from mean site values.

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40 Figure 3-5. Depth of soil organic horizons at randomly located points (DepthR) compared to depths at tree base points (DepthT) across 38 sites burned in 2004. Values are means of 11 tree and 11 random points, from each site Horizons are: dead moss (DM), fibric (F) and humic (H) as well as total depth.

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41 Figure 3-6. Difference between SOL depths at randomly located (DepthR) sampling points and depth at tree base points (DepthT) compared to mean tree density/ha across 38 sites burned in 2004. The fibric (F) and humic (H) horizons are shown.

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42 Figure 3-7. Total soil organic layer depth compar ed to soil horizon depth and horizon depth as percent of total depth across 28 unburned Alas kan boreal forest sites. There are four organic soil horizons: green moss (GM), brow n moss (BM), fibric (F) and humic (H). A) Soil horizon depth comparison. B) Horiz on depth as percent of total depth.

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43 Figure 3-8. Mean ( 1 SE) carbon (C) emissions a nd percent of total C combustion by post-fire soil organic layer (SOL) depth classes. A) Carbon emissions. B) Percent of total carbon combustion. Canopy does not include tree bole. Ratios of organic soil to canopy emissions (kg/m2) and combustion (%) are indicated at top of each column.

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44 Figure 3-9. Mean ( 1 SE) N emissions and percen t of total N combustion fo r four post-fire soil organic layer (SOL) depth cl asses across 38 burned sites. A) Nitrogen emissions. B) Percent of total N combustion. Canopy does not include tree boles. Ratios of organic soil to canopy emissions (kg/m2) and combustion (%) are indicated at top of each column.

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45 Table 3-1. Post-fire soil organic horizons mean depth, bulk density ( b), C and N concentration (Mean 1 SE). Values are means from 38 Alaskan sites burned in 2004. Horizon Mean depth (cm) b (g/cm3) C conc. (%) N Conc. (%) Dead moss (DM) 1.12 0.3 0.04 0.004 40.2 1.4 0.97 0.1 Fibric (F) 3.69 0.5 0.10 0.01 41.4 0.8 1.28 0.04 Humic (H) 8.15 1.0 0.21 0.01 30.0 1.0 1.25 0.04 Table 3-2 Soil characteristics by horizon for 28 unburned sites (mean 1 SE). Values Include mean depth, bulk density ( b) and C and N concentration. Horizon Mean depth (cm) b (g/cm3) C conc. (%) N Conc. (%) Dead moss (DM) 1.12 0.3 0.04 0.004 40.2 1.4 0.97 0.1 Fibric (F) 3.69 0.5 0.10 0.01 41.4 0.8 1.28 0.04 Humic (H) 8.15 1.0 0.21 0.01 30.0 1.0 1.25 0.04

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46 Table 3-3. Soil organic layers (SOL), tree canop y and ecosystem mass and C combustion as well as C emissions compared to CBI scores (T otal, understory, subs trate and overstory) for 38 sites in Alaskan forests burned in 2004. Measurement CBI* Equation R2 Pvalue Soil organic layers (SOL) % depth combustion Tot -28.54 + 42.0 (CBI-Tot) 0.57 <.0001 Und -3.05 + 32.11 (CBI-Und) 0.56 <.0001 Sub 33.67+ 17.61 (CBI-Sub) 0.42 <.0001 % mass combustion Tot -39.7 + 45.0 (CBI-Tot) 0.63 <.0001 Und. -13.0 + 34.7 (CBI-Und) 0.63 <.0001 Sub 27.5 + 18.6 (CBI-Sub) 0.45 <.0001 % C combustion Tot -66.3 + 52.56 (CBI-Tot) 0.54 <.0001 Und. -36.6 + 41.1 (CBI-Und) 0.56 <.0001 Sub 9.84 + 22.9 (CBI-Sub) 0.44 <.0001 C emissions (kg/m2) Tot -3.0 + 2.60 (CBI-Tot) 0.44 <.0001 Und -1.42 + 1.97 (CBI-Und) 0.43 <.0001 Sub 0.83 + 1.08 (CBI-Sub) 0.33 0.0002 Tree canopy % mass combustion Tot 34.3 + 16.51 (CBI-Tot) 0.14 0.02 Over 9.6 + 2.83 (CBI-Over) 0.44 <.0001 % C combustion Tot 48.6 + 14.15 (CBI-Tot) 0.15 0.02 Over 8.39 + 28.7 (CBIOver) 0.44 <.0001 C emissions (kg/m2) Tot -0.25 + 0.28 (CBI-Tot) 0.14 0.03 Over -0.74 + 0.45 (CBI-Over) 0.27 0.002 Ecosystem % mass combustion Tot -37.0 + 43.9 *(CBI Tot) 0.64 <.0001 % C combustion Tot -61.1 + 50.6 (CBITot) 0.56 <.0001 C emissions (kg/m2) Tot -3.26 + 2.85 (CBITot) 0.45 <.0001 *CBI-scores by strata: total (Tot), understory (Und), substrate (Sub) and overstory (Over).

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47 CHAPTER 4 DISCUSSION Existing m ethods estimate fire severity in bor eal forest by examining post-fire conditions. This is adequate for capturing canop y severity as tree boles can be used relatively accurately to reconstruct pre-fire aboveground biomass conditi ons. In contrast, depth measurements of postfire organic soil may not in themselves accurately represent pre-fire depths, or how much organic soil was lost. This study provides evidence that a dventitious root height s (ARH) on burned black spruce trees can be used, once adjusted, as a proxy for pre-fire organic soil height. This extends previous observations that were made in a few sites (Kasischke and Johnstone 2005). By reconstructing pre-fire soil depths this ARH method was used in combination with post-fire soil depth measurements to quantify fire severity, a nd C and N emissions from fire in boreal black spruce forest. Lastly, this method was also used to validate CBI, a semi-quantitative visual estimate of fire severity, in this forest type. Adventitious Root Height Here we described a new m ethod for quantifying fire severity by first estimating pre-fire organic soil depths. The adventiti ous root method includes measuring, at tree bases, the post-fire SOL depth and height to highest adventitious root on tree bo le at a number of points within a site. When we measured this in unburned sites as well, we found that th e adventitious root did correspond to organic soil height, but overall th e highest root was 3.2 cm (mean across unburned sites) below the top of the green moss layer. Th us, the pre-fire SOL depth is a combination of post-fire SOL depth, adventitious root height plus 3.2 cm (for the offset). In addition, found no significant difference between our re-constructed pre-fire depths and actual pre-fire organic soil measurements (Hollingsworth, unpublished data), which offers further support to the ARH method. However, measuring SOL only at tree bases underestimat es post-fire organic soil by

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48 about 6%. Although, there is this post-fire dept h discrepancy between tree and randomly located points, there is no pre-fire diffe rence (as measured in the unburne d sites), suggesting that organic soil at the base of trees burns more. We deve loped corrections to account for these post-fire differences for each horizon, since each has uni que bulk densities, C and N concentrations and total depth does not capture this variability. While, the ARH method can be useful across a wide range of sites and severities, it may not be as e ffective at sites in which the trees have fallen over and there is almost no residual organic soil. Trees can root in organic soil and if that all burns away then the tree will fall over. ARH can still be measured on the tree bole to the root collar (area where large roots separate ), but measuring this way coul d omit a significant amount of organic soil. C and N Pools After reconstructing pre-fire depth, w e used thes e values to reconstruc t pre-fire soil C and N pools and calculate emissions as well. We cal culated the mean unburned equivalent proportion of total pre-fire depth for each of three horiz ons, which were: 14% (BM), 46% (F) and 30% (H). GM was calculated to be a constant mean value of 2.5 cm, which was generally consistent across all sites as it is the photosynt hesizing horizon. Post-fire C and N pools were calculated using actual post-fire SOL depths and mean values fr om each burned site for C and N concentration and bulk density for the intact horizons. Pr e-fire horizon depths were estimated from reconstructed pre-fire depth and then mean values for C and N concentration and bulk density from all of the unburned sites were used to re construct C and N pools for the burned biomass. Finally, emissions were: re-constructed prefire pool minus the post-fire pool. In the course of reconstructing organic soil C and N pools, it was necessary to make a few assumptions and to use averages from all unburne d sites. We controlled organic soil depth, since post-fire SOL depth as well as he ight to adventitious root on the bole of a tree are easily

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49 measured in a burned site. Then, we used mean values from across all unburned sites to obtain bulk density and C and N concentration values for each horizon. Using these mean values for all sites does not capture all of the variabili ty inherent in these organic nutrient pools; however, it is an attempt to more accurately calculate pre-fire and post-fire pools and emissions on the ground than previous studies. Therefore, post-fire SOL depth and re-constructed pre-fire depth become the independent variables in calculating C and N pools. Canopy Fire Severity and Biomass Canopy fire severity and biom ass losses were estimated by Canopy (minus bole) combustion was visually assessed an d then allometric equations were used to determine biomass from DBH and biomass combusted. C concentration in the canopy biomass is about 50% and N concentration ranges from 0.4-1%, so canopy C a nd N pools were calculated too. Finally, fire severity was analyzed as the missing amount of biomass from the ground and the canopy and mean losses across our sites were about 65% of biomass. We compared our time-consuming destructive fire severity measurements to a quicker visual assessment (CBI) to see how well CBI worked. CBI Our data suggests that C BI shows promise as a quick method of assessing fire severity on the ground. Total CBI scores were significantly but weakly related to percent biomass consumed for canopy (minus the bole) but were highly corr elated with organic soil combustion. However, since most wildfires in black spruce forest ar e considered stand-replacement, it can be argued that there is not as much variability in stand consumption as there is in organic soil combustion (at least that can be visually estimated quickly). In other words, since the majority of trees die in most wildfires in black spruce forests, it can be difficult to differentiate between varying degrees of severity. Therefore, even though the correlation between CBI and our combustion estimates is

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50 weak, on the whole, it may be that there is not that much canopy com bustion variability to capture. Interestingly enough, our canopy and organic soil combustion loss estimates were not significantly related to e ach other, which is consistent with the different kinds of combustion. While canopy combustion is usually burned duri ng active, high-intensity fire (with visible flames), organic soil mostly burns during slow er, smoldering combustion for often-long periods of time (days or months). Other Methods of Measuring Fire Severity and Emissions Organic Soil Several studies have used the am ount of organi c soil consumed or remaining after a fire, by weight, depth or visual cla ss, as a method of measuring fire severity, however, these measurements were not linked to pre-fire organic soil amounts. There was no standardized method of quantifying organic soil c onsumption as a parameter for fire severity, in the literature. Most studies classified fire severity into unbur ned, low, moderate and severe categories based qualitatively on the amount of organic soil consumed (Turner et al 1997, Wang et al. 2001, de Groot et al. 2004, Greene et al 2004, Johnstone and Kasischk e 2005, Johnstone and Chapin 2006). Conversely, other studies assessed fire severity by measuring post-fire organic soil depth. Bergner et al. 2004 stated that a mean post-fire SOL depth of 7.5 cm was a low severity class, while 2.1 cm could be considered a severe burn Areseneault (2001) used a combination of the thickness of the remaining humic layer and canopy consumption measurements to estimate fire severity, however this method cannot assess those sites with little to no pos t-fire organic soil. In assessing these other fire severity methods it is important to note that measuring postfire organic soil is very different from estimating combustion. Post-fire SOL depth is linked to post-fire successional vegetation tr ajectories, however, it does not indicate how much matter was

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51 lost. However, fire severity is defined by amount lost and not amount left behind, therefore, it is important to note that the two meas urements are not comparable. Canopy Consumption and Tree Mortality Our canopy component biomass combustion es timates may be a more comprehensive visual way of quantifying tree fire severity in terms of biomass lost and incorporating it into total ecosystem fire severity. Canopy consumption a nd tree mortality estimates have been used in previous studies as measures of fire severi ty, however very few studies used only canopy consumption or mortality. The boreal forest often experiences complete canopy mortality while soil fire severity patterns are much more va riable (Miyanishi and Johnson 2002) and therefore canopy measurements alone are inadequate. Propor tion of canopy mortality was used as one fire severity quantifier within three studies (Gr eene et al. 2004, Johnstone et al. 2004 and Purdon 2004), though only the second study used this parame ter exclusively. Some of these studies used degree of consumption or percenta ge of tree mortality as indicators. However, total ecosystem fire severity estimates cannot necessarily be quantified strictly from the canopy. C and N Pools Carbon and nitrogen pools in boreal f orests as well as emissions from forest fires are poorly constrained and limited by uncertainties in quantifying pre-fi re spatial surface variation as well as organic soil biomass consumed (Neff et al. 2005, French et al. 2004). Many studies calculate carbon emissions from fire as a product of the fuel combusted during the fire and the area that burned (Amiro et al 2001) or have quantified carbon also using carbon density and emission factors (French et al. 2004). Models are used to calc ulate carbon and nitrogen pools and subsequent emissions with a cert ain degree of error that is pr opagated throughout the model and much of this uncertainty is due to variability in organic soil C loss (French et al. 2004, Neff et al. 2005). Furthermore, some models have not estim ated C emissions from wildfires, which will

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52 become increasingly important as fire frequency may be increased due to climate change (Yarie and Billings 2002). Neff et al. in 2005 used a Tau model to cal culate burned and unburned C pools and they stated that Tau consistently undere stimated the heterogeneity of the soil horizons and thus C pools. Our adventitious root height method accounts for some of this soil surface spatial variation as well as depth and C and N concentration variation. Conclusions C and N fluxes are intrinsically link ed to fire effects and fire severity in the boreal forest; therefore, it is imperative to have a satisfactor y way of measuring fire severity throughout the boreal landscape. Since, many studies use fire severity as a gradient or parameter for examining other ecosystem processes, fire severity is of ten not directly quantified, but estimated. These studies also indicate that the co -factors that influence fire seve rity, such as seasonality of burn, weather, and topography and soil moisture are good indices for estimating fire severity. Methods such as CBI show strong potential to be a satisfactory way of standardizing fire severity. Since most boreal forests experience almost total canopy death, it would seem that measuring fire severity in the canopy alone does not accurately capture the variability found within sites. In summary, it seems that fire severity estimates could be best quantified by a combination of SOL combustion measurements (dep th or percentage removed), soil moisture content, site drainage and s easonality or timing of burn. Th e ARH method accounts for organic soil combustion and surface and depth spatial variation thereby overcoming some of the limitations of previous boreal forest C and N estimates and fire losses.

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53 LIST OF REFERENCES Ahrens, R. J., J. G. Bockheim and C. Ping. 2004. The Gelisol order in soil taxonomy. Pages 2-10 in J. Kimble, editor. Cryosols: permafrost-affected so ils. Springer-Verlag, New York, NY, USA. Amiro, B. D., B. J. Stocks, M. E. Alexander, M. D. Flannigan and B. M. Wotton. 2001. Fire, climate change, carbon and fuel management in the Canadian boreal forest. International Journal of Wildland Fire 10: 405-413. Amiro, B. D., J. I., MacPherson, R. L. Desjar dins, J. M. Chen, J. Liu. 2003. Post-fire carbon dioxide fluxes in the western Canadian boreal forest: evidence from towers, aircraft and remote sensing. Agricultural and Forest Meteorology 115: 91-107. Areseneault, D. 2001. Impact of fire behavior on post-fire forest development in a homogenous boreal landscape. Canadian J ournal of Forest Research 31 : 1367-1374. Bergner, B., J. Johnstone and K. K. Treseder 2004. Experimental warming and burn severity alter soil CO2 flux and soil functional groups in a recently burned boreal forest. Global Change Biology 10: 1196-2004. Bigler, C., D. Kulakowski. and T. T. Vebl en. 2005. Multiple disturba nce interactions and drought influence fire severity in Ro cky Mountain subalpine forests. Ecology 86 ( 11): 3018-3029. Canada Soil Survey Committee 1978. The Canadian system of soil classification.Canadian Department Agriculture Publishers 1646. Dixon, R. K., S. Brown, R. A. Houghton, A. M. Solomon, M. C. Trexler and J. Wisniewski 1994. Carbon pools and flux of global forest ecosystems. Science. 263: 185-190. Epting, J. and D. Verbyla. 2005. Landscape-level interactions of pre-fire vegetation, burn severity, and post-fire vegetation over a 16-ye ar period in interior Alaska. Canadian Journal of Forest Research 35: 1367-1377. Flannigan, M. D., B. J. Stocks. and B. M. Wo tton. 2000. Climate change and forest fires. The Science of the total environment 262: 221-229. Gower, S. T., A. Hunter, J. Campbell, J. G. Vogel, H. Veldhuis, J. Harden, J. M. Norman, C. J. Kucharik and D. Anderson. 2000. C Nutrient dynamics of the BOREAS southern and northern forests. Ecoscience. 4, 481-490. Greene, D. F., J. Noel, Y. Bergeron, M. Rousseau, and S. Gauthier. 2004. Recruitment of Picea mariana, Pinus banksiana and Populus tremuloides across a burn severity gradient following wildfire in the southern boreal fore st of Quebec. Canadian Journal of Forest Research 34 : 1845-1857.

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54 de Groot, W. J., R. W. Wein. 2004. Effects of fire severity and season of burn on Betula glandulosa growth dynamics. Internationa l Journal of Wildland Fire 13 : 287-295. French, N. H. F., P. Goovaerts, and E. S. Kasischke. 2004. Uncertainty in estimating carbon emissions from boreal forest fires. Journal of Geophysical Research 109, D14SO8. Harden, J. W., S. E. Trumbore, B. J. Stocks, A. Hirsch, S. T. Gowers, K. P. ONeill and E. S. Kasischke. 2000. The role of fire in the boreal carbon budget. Global Change Biology 6: 174-184. Hinzman, L., L. A. Viereck, P. Adams, V. E. Romanovsky, and K. Yoshikawa. 2005. Climatic and permafrost dynamics in the Alaskan boreal forest. Pages 39-61 in M. Oswood and F.S. Chapin III, editors. Alaskas changing boreal forest. Oxford University Press, New York, NY, USA. Hollingsworth, T. N., M. D. Walker, F. S. Chap in III and A. L. Parsons. 2006. Scale-dependent environmental controls over species composition in Alaskan black spruce communities. Canadian Journal of Forest Research 36: 17811796. Johnson, E. A. 1992. Fire and Vegetation Dynamics : Studies from the North American boreal forest Pages 39-77. Cambridge Univer sity Press. Cambridge, England. Johnstone, J. F. 2006. Response of boreal plant comm unities to variations in previous fire-free interval. International Journal of Wildland Fire 15 : 497-508. Johnstone, J. F., F. S. Chapin III, J. Foote, S. Kemmett, K. Price and L. Viereck. 2004. Decadal observations of tree regeneration following fire in boreal forests. Canadian Journal of Forest Research 34: 267-273. Johnstone, J. F. and E. S. Kasischke. 2005. Standlevel effects of soil bur n severity on post-fire regeneration in a recently burned black spruce forest. Canadian Journal of Forest Research 35 : 2151-2163. Johnstone, J. F. and F. S. Chapin III. 2006. E ffects of soil burn severi ty on post-fire tree recruitment in boreal forest. Ecosystems 9: 14-31. Kasischke, E. S., N. L. Christ ensen Jr., B. J. Stocks. Fire Global warming and the carbon balance of boreal forests. 1995. Ecological Applications 5(2) 437-451. Kasischke, E. S., N. H. F. French, K. P. ONeill, D. D. Richter, L. L. Bourgeau-Chavez and P. A. Harrell. 2000. Influence of fire on long-term patterns of forest succession in Alaskan boreal forests. Pages 214-238 in E. S. Kasischke and B. J. Stocks, editors. Fire,climate change and Carbon cycling in the boreal forest. Springer-Verlag, New York, NY, USA. Kasischke, E. S. and J. F. Johnstone. 2005. Varia tion in post-fire organi c layer thickness in a black spruce forest complex in interior Al aska and its effects on soil temperature and moisture. Canadian Journal of Forest Research 35 : 2164-2177.

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55 Key, C. H. and N. C. Benson. 2005. Landscape Assessment: Ground measure of severity, the Composite Burn Index; and Remote sensing of severity, the Normalized Burn Ratio. Pages 25-36 in D.C. Lutes, R. E. Keane, J. F. Caratti, C. H. Key, N. C. Benson, S. Sutherland and L. J. Gangi. FIREMON: Fire Effects Monitoring and Inventory System. USDA Forest Service, Rocky Mountain Research Station, Ogden, UT. Gen. Tech. Rep. RMRS-GTR-164-CD: LA1-51 Krause, C. and H. Morin. 2005. Adventive-root de velopment in mature black spruce and balsam fir in the boreal forests of Quebec, Cana da. Canadian Journal of Forest Research 35: 2642-2654. LeComte, N. M. Simard and Y. Bergeron. 2006. E ffects of fire sever ity and initial tree composition on stand structural developmen t in the coniferous boreal forest of northwestern Quebec, Canada. Ecoscience 13 (2) : 152-163. Lentile, L. B., Z. A. Holden, A. M. S. Smith., M. J. Falkowski,., A. T. Hudak, P. Morgan, S. A. Lewis, P. E. Gessler, and N. C. Benson. 2006. International Journal of Wildland Fire 15 : 319-345. McGuire, A. D., R.A. Meier, Q. Zhuang, M. Ma nander, T. S. Rupp, E. Kasischke, D. Verbyla, D. W. Kicklighter and J. M. Mellilo. 2000. Th e role of fire disturbance, climate and atmospheric CO2 in the response of historical carbon dynamics in Alaska from 19501995: a process-based analysis with the Terrestrial Ecosystem Model. Page 3 in M. J. Apps and J. Marsden, editors. The Role of Boreal Forests and Forestry in the Global Carbon Budget. Abstracts. 8-12, May 2000, Edm onton, Alta. Canadian Forest Service, Northern Forestry Centre, Edmonton, Alberta, Canada. Miyanishi, K. and E. A. Johnson. 2002. Process and patterns of duff consumption in the mixedwood boreal forest. Canadian Journal of Forest Research 32: 1285-1295. Neff, J. C., J. W. Harden, and G. Gleixner. 2005. Fire effects on soil or ganic matter content, composition, and nutrients in boreal interior Al aska. Canadian Journal of Forest Research 35: 2178-2187. Payette, S. 1992. Fire as a contro lling process in the North Amer ican boreal forest. Pages144-165 in H. H. Shugart, R. Leemans and G. B. Bonan, editors. A systems analysis of the global boreal forest. Cambridge Universi ty Press, Cambridge, U.K. Purdon, M., S. Brais and Y. Bergeron. 2004. Initia l response of understory vegetation to fire severity and salvage-logging in the southern boreal forest of Quebec. Applied Vegetation Science 7 : 49-60. Rowe, J. S. 1983 Concepts of fires effects on plant individuals and species. Pages 135-154, in R. W. Wein, D. A. Maclean, edito rs. The role of fire in nor thern circumpolar ecosystems. NY, pp. 135-154.

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56 Roy, D. P., L. Boschetti and S. N. Trigg. 2006. Re mote sensing of fire severity: assessing the performance of the normalized burn ratio. Geoscience and Remote Sensing Letters 3 (1) 112-116. Turner, M. G., W. H. Romme, R. H. Gardner, W. H. Hargr ove.1997. Effects of fire size and Pattern on Early Succession in Yellowstone National Park. Ecological Monographs 67(4) : 411-433. Yarie J. and S. Billings. 2002. Carbon balance of the taiga forest within Alaska: present and future. Canadian Journal of Forest Research 32: 757-767. Wang, G. G. 2002. Fire severity in relati on to canopy composition within burned boreal mixedwood stands. Forest Ecology and Management 163: 85-92.

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57 BIOGRAPHICAL SKETCH Leslie A. Boby attended Morgan Park High School in Chicago, graduating in 1995. She studied at U niversity of Illi nois, Urbana-Champaign, IL and obt ained a Bachelors of Science degree in biology in 1999. Immediately following uni versity, Leslie moved to Africa and served as a Peace Corps volunteer in rural Ndori, Kenya and taught agroforestry techniques to farmers. After returning to the U.S., Leslie moved out to New Mexico in 2002 and worked for the Bureau of Land Management as a wildland firefighter an d biological technician. She continued further west and worked as a field assistant at an A udubon Sanctuary in southern California. Leslie returned to university life in 2005 as a gradua te student at the University of Florida in Gainesville, FL. She completed her Masters th esis in interdisciplin ary ecology in December 2007. Her next objective is to return to the working world and obtain a position as a land manager burning forests and fighting exotic species.