Transcript Impact of snow molds on conifers of the ribbon forest

Impact of snow molds
on conifers of the ribbon
forest
Max Owens
EBIO 4100, Spring 2013
Winter Ecology
Mountain Research Station
University of Colorado-Boulder
Introduction
 Structure of the ribbon forest: snow accumulation has
multiple effects on trees (Knight 1994)
 Snow molds are specialized fungi that attack dormant
plants under cover of snow (Pokorny 2009)
 Many different species of cold-tolerant fungi are
present under the snow during winter and disappear
quickly after snowmelt (Schmidt et al. 2008)
Introduction
 These psychrophilic (cold-loving) fungi produce mycelia
during the severe conditions of winter. (Hoshino et al. 2009)
 How?
 Spruce sapling growth is strongly inhibited by presence
of snow mold. (Cunningham et al. 2006)
Introduction
 Opportunistic snow molds are insulated from harsh
climate of winter by the snowpack, and antagonists are
practically absent (Matsumoto 2009)
 For phytopathogenic fungi adapted to the cold, the
subnivean environment is the perfect place to
parasitize young trees
 Question: How does the depth of snow contribute to
the maintenance of the structure of the ribbon forest, as
related to the presence of phytopathogenic snow mold?
 Why it matters:
 Important factor in limiting growth of subalpine trees?
 Maintenance of ribbon forest, a common structure in
subalpine forests near tree line
 Climate change—precipitation on the rise at higher
elevations (Kittel 2013)
 Hypothesis: The added insulative value of deeper
snow creates a better environment for snow molds to
parasitize trees.
 Prediction: We would expect to see a greater
incidence of snow mold in the glades of the ribbon
forest, where snow is deeper.
Site
 Subalpine ribbon forest above Mountain Research
Station at ~3,330m (10,930 ft.)
[Google 2013]
Methods
 2 x 40m transect crossing
glade from ribbon to ribbon
 Snow depth, tree heights,
DBHs, and snow mold
evidence were measured.
 Snow was removed along
transect to expose small
trees, and snow was
removed to base of each tree
to expose any snow mold
damage
Methods
 If present, height of snow mold/snow mold damage
extent was measured
 Trees with a DBH of 8 cm or greater were excluded,
since trees this large generally did not have branches
beneath the snowpack
 Only one transect due to time constraints
 Used Excel and R to create plots, regressions and ttests
Results
Physical appearance of
infected trees
Discolored
needles, not
bundled
Bundled needles
• 2 main categories
• Bundled needles with black
mold in between
• Brown/black needles, not
bundled
• Several trees with healthy needles
below snowpack
Results
40
60
p-value: 0.268
R2: 0.292
20
Height of snow mold (cm)
80
Snow Depth vs. Height of Snow Mold
Regression
50
60
70
80
90
Snow depth (cm)
100
110
Results
100
Snow mold presence vs. Snow depth
T-test
60
40
0
20
Snow depth (cm)
80
p-value: 0.0302
Trees with snow mold
Trees without snow mold
Snow mold presence
Bundled
needles
Discolored,
not bundled
Healthy
needles
1 Engelmann
spruce
1 Engelmann
spruce
4 subalpine
firs
2 subalpine
firs
2 subalpine
firs
Results
T-test
p-value: 0.326
3
2
1
0
DBH (cm)
4
5
6
Snow mold presence vs. DBH
Trees with snow mold
Trees without snow mold
Snow mold presence
Results
 Regression of snow depth and height of snow mold
was not significant, but trended towards higher extent
of snow mold with greater snow depths
 Significant difference in snow depths between trees
with and without snow mold
 Not enough data to differentiate snow mold
presence/appearance between different tree species
 No significant difference in tree size between trees with
and without snow mold
Discussion
 Deeper snow creates favorable environmental
conditions (insulation, moisture) for snow mold to infect
trees
 Persistence of snow is critical (Matsumoto 2009)
 Snow mold infection inhibits spruce growth, and one of
the primary drivers of snow mold infection of saplings was
snow duration (Cunningham et al. 2006)
 Snow mold-tree interactions play at least some part in
the complex maintenance of ribbon forest structure
Discussion
 Further research
 Replicates of this study to create an accurate profile of
snow mold height extent with snow depth (is there an
optimal depth for infection?)
 A direct correlation between snow mold and snow depth has
implications for climate change.
 Snow depth and the maintenance of the ribbon forest to
determine the relative impacts of physical damage,
shorter growing seasons, and infection by snow molds on
trees
 How much snow mold damage is too much for a conifer
to survive?
Conclusion
 Ribbon forest structure controlled by several factors,
including snow molds
 Fungi that infect plants underneath the snow; limits
growth
 Deeper snow makes snow mold infection more likely
 Insulation
 Abundant moisture
 Not enough data to determine pattern of snow mold
damage extent in ribbon forest
Acknowledgements
Thanks to Tim Kittel for support and analysis help, and to
Sebastian Baily, Jake Delfin, and Atty Phleger for data
collection help.
Literature Cited
 Cunningham, C., N.E. Zimmermann, V. Stoeckli, and H. Bugmann.
2006. Growth response of Norway spruce saplings in two forest gaps
in the Swiss Alps to artificial browsing, infection with black snow mold,
and competition by ground vegetation. Canadian Journal of Forest
Research. 36(11): 2782-2793.

DOI: 10.1139/x06-156
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
DOI: 10.1007/s10267-008-0452-2
 Kittel, Timothy. 2013. Historical Climate Change on Niwot Ridge.
http://culter.colorado.edu/~kittel/WEcol_GuestLec/
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February 2013.
 Knight, D.H. 1994. Mountains and Plains: the Ecology of
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 Matsumoto, N. 2009. Snow molds: a group of fungi that
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
DOI: 10.1264/jsme2.ME09101
 Pokorny, J.D. 2012. Snow Molds of Conifers. http://
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Accessed 5 February 2013.
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