The use of dendrochronology to detect spruce budworm outbreaks Group Leader: Cornelia Krause Mathieu...
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![Page 1: The use of dendrochronology to detect spruce budworm outbreaks Group Leader: Cornelia Krause Mathieu Bouchard Mariano Morales Kathie Weathers.](https://reader036.fdocuments.us/reader036/viewer/2022062314/56649da75503460f94a93cfb/html5/thumbnails/1.jpg)
The use of dendrochronology to detect spruce budworm
outbreaks
Group Leader: Cornelia Krause
Mathieu Bouchard
Mariano Morales
Kathie Weathers
![Page 2: The use of dendrochronology to detect spruce budworm outbreaks Group Leader: Cornelia Krause Mathieu Bouchard Mariano Morales Kathie Weathers.](https://reader036.fdocuments.us/reader036/viewer/2022062314/56649da75503460f94a93cfb/html5/thumbnails/2.jpg)
Disturbances in the Boreal Forest
• major forest disturbances– fire– insect outbreaks– other natural events: windthrows, floodings
• affect forest stand dynamics – mortality– change species composition
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Spruce Budworm
• feeds on recent needles, buds, flowers
• balsam fir most affected
• increased severity of the outbreaks during 20th century
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Spruce budworm
• outbreaks (abitibi)– 1919-1929– 1930-1950– 1970-1989
• growth reduction: 0-3y delay• volume • 57 million ha
affected
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Objectives
• impact of spruce budworm on host trees– Abies balsamea, Picea glauca, P. mariana
• correlation between 3 tree species
• cross date dead host trees
• relate dead material to last spruce budworm outbreak
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Methods
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1. Field• located in the 1760 fire, ancient cuttings
present• overstory : mixed boreal forest
– Balsam fir 13 trees sampled– White and black spruce 14 trees sampled– White birch (Betula papyrifera)– White cedar (Thuja occidentalis)
• dense understory : – Acer spicatum, Ferns (Athyrium felix-femina, ...)
• deadwood – Balsam fir 13 disks– White spruce 3 disks
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2. Dead wood analysis
• field classification of decomposition state– visual criteria
• 8 snag classes• 4 classes downed debris
• comparison: decomposition state vs time of death
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3. Outbreak period detection
• consecutive growth reductions
• quantify growth reduction – (outbreak, impact programs)
• comparison to non-host spp.
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Cores
1. age counts
2. pointer years
3. measure rings
4. cross date (light table)
5. cross date (cofecha)
Dead Wood
1. decomposition class
3. measure rings
5. cross date (cofecha)
4. Chronology building process
2. age counts
4. cross date (light table)
standardizationcorrelation coefficientsinterpretation
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Results
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Within-species comparisonCross dating results (Cofecha)
series species corr. coef.
years total y flag
3 Picea
mariana
0.425 1949-2002
54 1
7 Picea
glauca
0.485 1880-2002
123 1
7 Abies
balsamea
0.69 1932-2002
71 no
7 dead Abies b.
0.51 1914-2000
86 no
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Among-species comparisoncross dating results (Matrix)
Dead Abies b. Picea g. Picea m.
Dead 1.00 0.497* 0.659* 0.328*
Abies b. 1.00 0.736* -0.17
Picea g. 1.00 0.17
Picea m. 1.00
Period: 1949-2000
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Spruce and Fir Chronologies
2D Graph 1
Years1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 20100
1
2
2D Graph 2
Tre
e-rin
g W
idth
Inde
x
1
20
1
2
Picea glauca
Abies balsamea
Picea mariana
n=3
n=7
n=7
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2D Graph 5
YEARS
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Tre
e-rin
g W
idth
Inde
x
0
1
20
1
2
Abies balsamea chronologies
LIVE
DEAD
Trees died from 1979-2000
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Decay Class from Field Observation vs Chronology Date-of-death
0
1
2
3
4
5
6
7
8
9
10
1975 1980 1985 1990 1995 2000
Year of Death
Dea
th C
lass
moredecomposed
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Results and Conclusions
• last outbreak detected in 3 species– 1980s– toward end of ‘literature’ outbreak period
for Abitibi
• can date death of trees even with short chronologies (64 y average)
• building chronologies: need multiple lines of information
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If time were not a factor…
• non-host tree species (white cedar)
• more trees, more regions
• use of additional criteria for cross dating– e.g., light rings, dark rings
• older trees
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Many thanks to:
• Cornelia
• Bernard and field week organizers
• Linda and crew