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Title: Powerpoint template for scientific posters Swarthmore College


1
Piñon pine growth is associated with CO2 and
other climatic factors
C. S. Tysor1, A.V. Whipple1,2, G.W. Koch2
Department of Biological Sciences1,
Merriam-Powell Center for Environmental
Research2, Northern Arizona University,
Flagstaff, AZ 86011
Abstract
Results

Conclusions
MULTIPLE LINEAR REGRESSION MODEL RESULTS
Piñon growth trends at 10 sites across Arizona
(Fig.1) were compared to growth trends at Red
Mountain. All trees germinated between 1380 and
1898, except for at Red Mountain, where
germination occurred between 1906 and 1974.
Piñon pine, an important tree in the southwest,
has suffered extensive mortality in a recent
drought. In order to understand how climatic
variables may be affecting piñon growth, multiple
linear regression was used to model the response
of annual tree ring width to drought, atmospheric
CO2, and minimum and maximum temperatures.
Maximum temperature, CO2, and their interaction
are associated with growth. When drought
survivors were compared to trees that succumbed
to drought, the model showed that live trees were
more responsive to drought.
  • Lower partial pressure of CO2 at high
    elevations combined with drought conditions may
    cause piñon to be carbon limited. This model
    shows that as CO2 increases, piñon pine are
    growing more.
  • If increasing CO2 levels are causing an increase
    in growth, we would expect to see a similar
    pattern at other sites. Preliminary data from
    Sunset Crater in northern Arizona shows piñon
    exhibiting growth patterns similar to those at
    Red Mountain.
  • Warmer temperatures are associated with
    increased piñon growth.
  • Interactions between climatic variables,
    especially maximum temperatures and CO2 levels,
    influence piñon growth.
  • Piñon that have survived the drought grow more
    in wet conditions and less in dry conditions than
    piñon that have died.

Since the trees at Red Mountain were cored in
1998, 53 of them have died. Separate models
were constructed for surviving trees (Fig.4),
dead trees (Fig. 5), and surviving and dead trees
combined (Fig. 3). Significant climatic factors
and interactions are bolded.
The models fit the data reasonably well (Fig 6.,
Fig.7). Maximum temperature, CO2, and their
interaction increase growth in each model, and
there are important differences between each
model (Fig. 8).
Figure 1. Locations of all sites.
Figure 3. Model for all trees.
Figure 5. Model for dead trees.
Figure 4. Model for surviving trees.
Introduction and Questions
 Residual standard error 0.4797 on 1987 degrees
of freedom, Multiple R-squared 0.4282, Adjusted
R-squared 0.4268
Residual standard error 0.4553 on 4225 degrees
of freedom, Multiple R-squared 0.4133, Adjusted
R-squared 0.4123
Residual standard error 0.4288 on 2230 degrees
of freedom, Multiple R-squared 0.3968, Adjusted
R-squared 0.3944
  • Pinus edulis (piñon pine) is a dominant species
    in cool, arid woodlands across the Southwest. In
    the past decade, climate change induced drought
    has led to extensive piñon mortality across the
    region1. To better understand drought mortality,
    we must understand how piñon grow and how various
    climatic factors are affecting piñon growth
  • What is the pattern of tree ring width through
    time when CO2 is not changing dramatically?
  • What climate variables are influencing piñon
    growth?
  • Do the piñon that died in the drought differ
    from survivors in their responses to climate
    variables?

Significance codes p lt 0.0001 p lt 0.001 p
lt 0.01
Figure 6. Surviving annual tree ring width and
predicted ring width.
Figure 7. Dead annual tree ring width and
predicted ring width.
Literature cited
1Breshears D., N. Cobb, P. Rich, K. Price, C.
Allen, R. Balice, W. Romme, J. Kastens, M. L.
Floyd, J. Belnap, J. Anderson, O. Myers, and C.
Meyer. 2005. Regional vegetation die-off in
response to global-change-type drought.
Proceedings of the National Academy of Sciences
10215144-15148. 2D.M. Etheridge, L.P. Steele,
R.L. Langenfelds, R.J. Francey, J.-M. Barnola and
V.I. Morgan. 1998. Historical CO2 records from
the Law Dome DE08, DE08-2, and DSS ice cores. In
Trends A Compendium of Data on Global Change.
Carbon Dioxide Information Analysis Center, Oak
Ridge National Laboratory, U.S. Department of
Energy, Oak Ridge, Tenn., U.S.A. 3Keeling, C.D.
and T.P. Whorf. 2005. Atmospheric CO2 records
from sites in the SIO air sampling network. In
Trends A Compendium of Data on Global Change.
Carbon Dioxide Information Analysis Center, Oak
Ridge National Laboratory, U.S. Department of
Energy, Oak Ridge, Tenn., U.S.A 4PRISM Group,
Oregon State University, http//www.prismclimate.o
rg, created May 2008. 5Kempes C. P., O. B. Myers,
D. D. Breshears, and J. J. Ebersole. 2008.
Comparing response of Pinus edulis tree-ring
growth to five alternate moisture indices using
historic meteorological data. Journal of Arid
Environments 72350-357.
Piñon growth at all sites except Red Mountain
have a flat or decreasing trend in the first
century of growth (Fig. 2). Piñon at Red
Mountain, however, have an increasing growth
trend. Trees at Red Mountain grew more recently
than most trees at the other sites and could be
responding to increasing levels of atmospheric
CO2.
Methods
Ring widths are averaged for all trees in that
category.
  • To answer the first question, ring widths of
    piñon from 10 sites across Arizona were examined.
  • To answer the other questions, 111 piñon pine
    were cored at Red Mountain in 1998. Ring widths
    were measured, cores were crossdated, and a
    multiple linear regression including two-way
    interactions was used to model ring width.
    Insignificant interactions were removed one at a
    time and the new model was compared to previous
    models at each step.
  • Explanatory variables included
  • maximum and minimum temperatures
  • drought
  • CO2 concentration2,3
  • Monthly temperature data was obtained from PRISM4
    and averaged over each year. The Palmer Drought
    Severity Index (PDSI) was used as a measure of
    drought. Negative values indicate drier than
    normal conditions and positive values indicate
    wetter than normal conditions. PDSI is a better
    predictor of piñon growth than raw precipitation
    data5.

Figure 2. The first century of growth at Red
Mountain (red line) and other sites (black line).
Lines were created by averaging all trees in the
site(s) by age. Growth at Red Mountain occurs
between 1906 and 1995. Growth at other sites
occurs between 1380 and 1986
COMPARISON OF SURVIVING AND DEAD TREES
Figure 8. Different responses to climate
variables of surviving and dead trees. is a
positive response, - is a negative response,
and 0 is no significant response.
Trees that have survived the drought responded
differently to climate than trees that have died
(Fig. 8). Dead trees responded to the combination
of wetter conditions and higher CO2 levels by
increasing growth, but did not respond to wetter
or drier conditions alone. Unlike dead trees,
surviving trees were sensitive to drought. In dry
years, surviving trees decreased growth in wet
years, surviving trees increased growth.
Acknowledgments
Thanks to Colin Kremer for guidance, advice, and
encouragement, Douglas Pace and Melissa White for
programming and database assistance, and Michael
Peters for PRISM data. Funded by the
Undergraduate Mentoring in Environmental Biology
Program.
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