Tree demography on Mt. Rainier:
Forecasting range shifts under global warming
Janneke Hille Ris Lambers, Ailene Kane, Andrew Larson & Jessica Lundquist - University of Washington
Introduction
Humans are changing the weather – temperatures are rising and snowfall
amounts are decreasing at higher latitudes and on mountain tops. One of the
greatest challenges ecologists face is forecasting how such climatic changes
will affect species distributions. There is ample evidence that species’ ranges
are already shifting in response to warming, and models suggest that continued
migration poleward and uphill is needed for species to track areas climatically
similar to those they occur in now. Forecasting the rate of these range shifts
requires an understanding of how climate influences demography (growth,
survival, fecundity) across species’ ranges. With its 4400 meters in elevation
and a strong rainshadow, Mt. Rainier is a microcosm of climate zones and
forest types found in Oregon, Washington and British Columbia. It is thus an
ideal location for studies of how climate change will affect tree range shifts.
Here, we use data collected from Mt. Rainier National Park to understand the
relationship between elevation, climate parameters and tree performance for 4
conifers (Douglas fir, Western hemlock, Western red cedar, Pacific silver fir).
We ask:
1. Does abundance, growth and survival of these 4 tree species, measured at 18
permanent forest stands, correlate with temperature, precipitation or snowfall?
2. Do annual growth rates of adult trees and juvenile seedlings, measured at one
location, correlate with annually varying snow, temperature, and precipitation?
Conclusions
Results
1. Climate correlates with the abundance of 1 species.
Although the abundance of Douglas fir,
Western red cedar and Western hemlock
decline with elevation (Fig 2.), only
Western hemlock abundance correlates
with three climate variables (Fig. 3).
It is possible that these climate variables
drive the abundance of this species at Mt.
Rainier, but our analyses were limited by
small sample size (18 stands) and
correlations between the climate
variables (Table 1).
Figure 3. The relationship between mean annual temperature, total precipitation, and total
snowfall and the basal area of Western hemlock at 18 stands across Mt. Rainier.
Precipitation and snowfall are reported as mm of rain equivalent.
Table 1. Correlations between climate variables at 18 stands
Climate variable
Elevation
Precipitation
Snow
Temperature
Elevation
Precipitation
0.404
Snow
0.609
0.876
Temperature
-0.701
-0.484
-0.832
2. Snow influences Western hemlock
demography, and may affect other species
by increasing late-season soil moisture
while decreasing growing season length.
3. Tree rings show great promise for
assessing impacts of global warming on
population dynamics.
2. Stand-specific growth and survival rates of 1 species
was correlated with average annual snowfall.
Methods
We use three kinds of data:
1. Growth and mortality data were collected from 18 one hectare stands within the
park (Fig. 1). These stands were established in 1978, with the size and survival
of each tree censused every 5 years. The stands vary widely in climatic
variables and the abundance of the four focal tree species (Fig. 2).
2. Annual ring widths quantified from increment cores and seedling crosssections. Data were collected adjacent to Longmire, a climate monitoring
station (Fig. 2). We collected ten increment cores and 10 seedling crosssections for 2 species (Western hemlock, Pacific silver fir), and measured ringwidths using WinDENDRO.
3. Climate averages were estimated for each stand using the Parameter-elevation
Regressions on Independent Slopes Model (PRISM) climate mapping system
(PRISM Group 2007). Climate data for Longmire were acquired from Natural
Resource Conservation Service and the National Climate Data Center.
For all trees, growth and
survival depended on tree size.
Thus, we fit a relationship
between size and growth and
size and survival (power-law
and logistic, respectively) using
maximum likelihood, and asked
whether parameters describing
size-specific growth and survival
Figure 4. The relationship between snowfall and stand-specific growth parameters (from power law sizerates correlated with climate
growth relationships), and size-growth relationships of two stands spanning the extremes of snowfall.
variables. For all but one
species, size-specific growth and survival was not correlated with stand-specific climate variables.
For survival data, low sample size affected model fitting and interpretation (in many stands, fewer
than 5 trees died over the 30 year sampling period). However, Western hemlock growth was
correlated with snow parameters, with lower growth in plots where snowfall is higher (Fig. 4).
3. Tree ring data indicates that the annual growth of two
species will be sensitive to climate change.
Annual growth rates of Western hemlock and Pacific silver fir seedlings and adults at 1000 meters,
where both these species are abundant, correlate with annual fluctuations in precipitation, snowfall
and/or temperature (Table 2). Climate variables do not explain much of the annual variation in
growth, presumably due to the low sample size (5 individuals per size class and species).
Decreased snow with warming will
Table 2. Coefficients and model R2’s from a linear regressions between
likely positively affect Western hemlock annual growth chronologies and climate variables.
Western hemlock
Pacific silver fir
recruitment and growth, although the
Climate variable
Seedling
Adult
Seedling
Adult
negative effect of increased temp0.0037
0.0001
0.0011
-0.0001
erature on adult growth may dampen
Precipitation (total)
-0.0014
-0.0008
0.0005
0.0052
this response. By contrast, increased
Snow
temperatures will positively affect
-0.0029
-0.0451
0.1041
-0.0022
Temperature
Pacific silver fir seedling growth.
Model fit (R squared)
0.308
0.100
0.135
0.050
Figure 1. Mt. Rainier National Park (solid line), roads (dashed lines), stand
locations (black dots), and site of long-term climate records (blue star).
1. Tree growth and survival of most species
did not vary with climatic variables,
suggesting that range shifts in response to
global warming may be difficult to predict.
Figure 2. Abundance of the four focal species
across an altitudinal gradient. Each dot represents
the species’ basal area at each of the 18 stands.
For more information, email jhrl@u.washington.edu
http://protist.biology.washington.edu/oikos/index.html
Future Work
1. Monitoring of microclimate.
To better understand how climate influences demography, we will measure
temperature, soil moisture, snow depth and snow duration at each stand (Fig. 1,
Fig. 5).
Figure 5. Temperature sensors in trees (a) deployed using a slingshot (b) by Jessica Lundquist
(c). Combining measurements of air temperature and soil temperature over time allows for
quantification of snow duration (d) and and snow depth (Lundquist 2008, in press).
2. Seedling demography.
The growth and survival of conifer seedlings in the Pacific Northwest may be far more sensitive to climate than are adult trees,
because of shallow roots which make them sensitive to the late
summer droughts common to this region, and their short stature
that makes them susceptible to short growing seasons when
buried by snow. Thus, we will census seedling growth and
survival in each stand (Fig. 1), and compare these measures
to microclimate measures (Fig. 5).
3. Quantify seed dispersal, and estimate
migration rates.
Forecasting range shifts with climate change requires knowledge
of demographic sensitivity to altered climate AND dispersal rates.
We will quantify seed dispersal, and combine estimates with
demography data to forecast conifer migration rates on Mt. Rainier.
Acknowledgements
We thank Jerry Franklin, Steve Acker and other members of the Permanent Sample Network for graciously sharing their data,
Howard Bruner for data management, Jonathan Deschamps for analyzing ring widths, and HJ Andrews LTER for providing the
growth and mortality data. Funding for these data was in part provided by NSF LTER (DEB-02-18088)