Modeling at the Arctic LTER
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Modeling has
played a major part in
research at the Arctic
LTER in studies of
individual processes to
studies of the
biogeochemical linkages
among carbon, nitrogen
and water cycles on
arctic landscapes.
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Soil-Plant-Atmosphere
model (SPA)
Soil-Plant-Atmosphere
model (SPA) is a
detailed sub-diurnal
model of
canopy-atmosphere
interactions,
linking a radiative
transfer scheme, a
biochemical model of
photosynthesis, CO2
diffusion, and a
hydraulic model of
stomatal opening
The Aggregated
Canopy Model (ACM)
is directly derived
from SPA, but
operates on a daily,
rather than 30
minute, time-step
and at the whole
canopy, rather than
leaf, level. ACM has
been used to access
the patterns of
gross primary
production in the
Kuparuk River basin.
Below is a comparison of the
soil-plant-atmosphere (SPA) model to
data collected from eddy flux towers at
several location on the North Slope of
Alaska (Williams et al. 2000).
That same
model was used to explain the relationship
between leaf area and canopy nitrogen across the
North Slope (Williams and Rastetter 1999). The
GPP isopleths on the graph were generated with
the SPA model. The clustering of data suggests a
strong optimization of leaf display and N
allocation to maximize productivity.
Productivity cannot increase substantially by
increasing either leaf are or canopy nitrogen
alone. To increase GPP, both must increase
in tandem. The data are from 7 distinct
vegetation types, suggesting that all 7 use a
similar optimization strategy. The gray
line is the relationship expected if N is
distributed exponentially down through the
canopy.
Williams et
al. (2001) Used an aggregated for of the SPA
model (the Aggregated Canopy Model)
to
predict the spatial distribution of
photosynthesis for the Kuparuk River Basin.
Arctic Net
Ecosystem Exchange
Shaver et al
(in press) developed a simple model of Arctic
Net Ecosystem Exchange (ANEE) of CO2
based of several hundred chamber-based
measurements made for seven vegetation types (Betula,
Heath, Mesic, Salix, Snowbed, Tussock, Wet
Sedge) in Alaska and Sweden:
(1)
where R0
(µmol m-2 leaf s-1)
and Rx (µmol m-2
ground s-1) are respiration
parameters, L is the leaf area
index (m2 leaf m-2
ground), β is a temperature-response
parameter (ºC-1), T is
air temperature (ºC), Pm
is the leaf-level, light-saturated
photosynthetic rate per unit leaf area (µmol m-2
leaf s-1), k is the
Beer’s extinction coefficient (m2
ground m-2 leaf), E0
is the initial slope of the leaf-level light
response curve (µmol C µmol-1
photons), and I0 is the
photosynthetically active photon flux density (PPFD)
above the canopy (μmol m-2 s-1).
The model has
two remarkable characteristics:
- It
requires only three measured variables to
apply (L, T, and I0)
- The
same parameter values apply to all
vegetation types in all locations
Indeed, the
parameters estimated for one type of vegetation
work to simulate NEE in the other six vegetation
types and parameters estimated for Sweden are
indistinguishable from those estimated for
Alaska (Fig. 1). We have since tested the
model with data from Western Greenland and from
Svalbard and again the same three measurements
and the same parameter values work well to
predict NEE for these new sites.
MBL General
Ecosystem Model
The
Marine
Biological
Laboratory General
Ecosystem Model
(MBL-GEM) is
a linked-process model describing
the interactions between carbon and
nitrogen
in terrestrial
ecosystems. The
model is intended to
be generally
applicable to most
terrestrial
ecosystems and, in
its original form,
has been used to
analyze the
responses of
temperate deciduous
forests, tropical
evergreen forests,
and arctic tundra to
changes in CO2
concentration,
temperature, N
inputs, irradiance,
and soil moisture.
In the arctic
MBL-GEM has been used
to synthesize and analyze long-term experiments
on tundra responses to fertilizer and warming. McKane et al. (1997a) calibrated of the General
Ecosystem Model (GEM) to plot scale experiments
of tussock tundra and the calibrated model was
used in various analyses of long-term responses
to changes in climate (McKane et al. 1997b,
Rastetter et al 1997, 2004).
Rastetter et
al. (2004) linked several GEM models along a
transect to examine the effects of down-slope
movement of water and nutrients on the responses
of tussock tundra to changes in climate.
The simulations indicate that over the next 100
years, the movement of nutrient down hill will
result in a 30% higher net carbon storage at the
base of the 100 m transect than at the top.
TOPMODEL
Stieglitz et
al. (2003) analyzed how the hydrological
connectivity changes as arctic hill slope wet up
and dry out. Connectivity does not simply
expand upward from the valley floor and then
contract back down slope. Patterns of
connectivity also depend on the topography,
depth of thaw, and soil characteristics.
It is this connectivity that determines the
down-slope transport of nutrients on hill
slopes.
We are
currently trying to link the hill-slope
hydrology models with our plot scale
biogeochemical models to predict the complex
biogeochemical interactions on hill slopes and
ultimately the delivery of nutrients and organic
matter to streams and lakes at the base of these
hill slopes.
References
McKane, R. B., E. B. Rastetter, G. R.
Shaver, K. J. Nadelhoffer, A. E. Giblin,
J. A. Laundre, and F. S. Chapin, III.
1997. Reconstruction and analysis of
historical changes in carbon storage in
arctic tundra. Ecology 78:1188-1198.
McKane, R. B., E. B. Rastetter, G. R.
Shaver, K. J. Nadelhoffer, A. E. Giblin,
J. A. Laundre, and F. S. Chapin, III.
1997. Climatic effects on tundra carbon
storage inferred from experimental data
and a model. Ecology 78:1170-1187.
Rastetter, E. B., G. I. Aagren, and
G. R. Shaver. 1997. Responses of
N-limited ecosystems to increased CO2: A
balanced-nutrition,
coupled-element-cycles model. Ecological
Applications [Ecol. Appl.] 7:444-460.
Rastetter, E. B., B. L. Kwiatkowski,
S. Le Dizes, and J. E. Hobbie. 2004. The
role of down-slope water and nutrient
fluxes in the response of arctic hill
slopes to climate change.
Biogeochemistry 69:37-62.
Stieglitz, M., J. Shaman, J.
McNamara, G. W. Kling, V. Engel, and J.
Shanley. 2003. An Approach to
Understanding Hydrologic Connectivity on
the Hillslope and the Implications for
Nutrient Transport. Global
Biogeochemical Cycles 17:1105,
doi:1110.1029/2003GB002041
Williams, M., W.
Eugster, E. B. Rastetter, J. P.
McFadden, and F. S. Chapin, III. 2000.
The controls on net ecosystem
productivity along an Arctic transect: a
model comparison with flux measurements.
Global Change Biology 6:116-126.
Williams, M., and E.
B. Rastetter. 1999. Vegetation
characteristics and primary productivity
along an arctic transect: implications
for scaling-up. Journal of Ecology [J.
Ecol.] 87:885-898.
Williams, M., E. B.
Rastetter, E. Carpino, J. E. Hobbie, G.
R. Shaver, and B. L. Kwiatkowski. 2001.
Primary production of an arctic
watershed: An uncertainty analysis.
Ecological Applications 11:1800-1816.
