The BOREAS Information System
1.1 Model Identification
BIOME-BGC (BioGeoChemical cycles)
1.2 Model Introduction
BIOME-BGC simulates biogeochemical and hydrologic processes across
multiple biomes based on the logic that differences in process rates between
biomes are primarily a function of climate and general life-form
characteristics. The carbon balance portion of BIOME-BGC utilizes daily
meteorological data in conjunction with general stand and soil information to
predict net photosynthesis, growth, maintenance and heterotrophic respiration
at a daily time-step. BIOME-BGC is general in the sense that the surface is
represented by singular, homogeneous canopy and soil layers. Detailed
descriptions of BIOME-BGC logic are given by Running and Coughlan (1988) and
Running and Hunt (1993). A description of the components of the model
relating to the prediction of hydrologic characteristics within different
boreal forest stands is given by Kimball and Running (submitted). A summary
of the important components of BIOME-BGC relating to the prediction of daily
carbon allocation and exchange is given below.
1.3 Objective/Purpose
In this investigation we used BIOME-BGC to estimate daily and annual
hydrologic and carbon budgets for different boreal forest stands associated
with the boreas tower flux sites and compared net carbon flux estimates with
results derived from tower flux and biomass measurement data. These results
were used to assess the important climate and stand characteristics that
control stand hydrologic characteristics, estimated productivity respiration
and surface-atmosphere carbon exchange. These results are intended to provide
a framework for evaluating the sensitivity of the boreal forest regional
carbon balance to global warming.
1.4 Summary of Parameters
Model daily input requirements:
Maximum and minimum daily air temperature (C), precipitation (cm), total daily
solar radiation (kJ) and daylength (s).
There is also a site initialization file that describes stand morphology
and soil characteristics. Parameters included in this file are discussed in
section 1.5. Site initialization files that were used to generate model
results for the sites in this investigation are included in this data
directory.
Model daily carbon outputs:
Net photosynthesis (GPP); maintenance (Rm), growth (Rg), heterotrophic (Rh)
and total respiration (Rtot); net ecosystem C exchange (NEE). Rm represents
the daily sum of estimated maintenance respiration rates from coarse and fine
root, sapwood and foliar carbon pools. foliar respiration is computed as the
sum of estimated day and night foliar respiration rates. GPP is computed as
the difference between gross photosynthesis and day leaf respiration. NPP is
determined as the difference between GPP and Rm. Rg was estimated as 32% of
the daily estimated NPP. Rh is estimated as a proportion of prescribed soil
and litter carbon pools; this proportion is regulated by estimated soil water
potential and soil temperature conditions. Rtot is estimated as the sum of Rm,
Rg, and Rh. NEE is estimated as the difference between GPP and Rtot.
Model daily hydrologic outputs:
Evaporation, transpiration, evapotranspiration, soil moisture, snow water
equivalent.
1.5 Discussion
BIOME-BGC simulates biogeochemical and hydrologic processes across
multiple biomes based on the logic that differences in process rates between
biomes are primarily a function of climate and general life-form
characteristics. The carbon balance portion of BIOME-BGC utilizes daily
meteorological data in conjunction with general stand and soil information to
predict net photosynthesis, growth, maintenance and heterotrophic respiration
at a daily time-step. BIOME-BGC is general in the sense that the surface is
represented by singular, homogeneous canopy and soil layers. Detailed
descriptions of BIOME-BGC logic are given by Running and Coughlan (1988) and
Running and Hunt (1993). A description of the components of the model
relating to the prediction of hydrologic characteristics within different
boreal forest stands is given by Kimball and Running (submitted). A summary
of the important components of BIOME-BGC relating to the prediction of daily
carbon allocation and exchange is given below.
The sole input to the carbon budget in BIOME-BGC is the photosynthetic
fixation of CO2 by the vegetation canopy. Outputs are all in the form of
respired CO2, coming either from plant tissues due to growth or maintenance
respiration, or from the litter and soil carbon pools as the result of
heterotrophic respiration.
Gross primary production (GPP) represents the total gain of carbon to the
system by net photosynthesis and is defined as the daily sum of gross
photosynthesis and daily foliar respiration. The current representation of
photosynthesis differs significantly from previously published descriptions of
the BGC family of models (Running and Hunt 1993, Hunt and Running 1992,
Running and Coughlan 1988). The original FOREST-BGC representation of
photosynthesis relies primarily on the parameterization of a mesophyll
conductance to CO2, estimating the rate of fixation as a diffusion process,
driven by a prescribed internal CO2 concentration. FOREST-BGC also does not
implement an explicit treatment of the photosynthetic biochemical pathways.
The original version of BIOME-BGC presents a more detailed representation of
photosynthesis, relying on explicit models of photosynthetic biochemistry
(Leuning 1990, Farquhar et al. 1980). The original BIOME-BGC also includes an
iterative calculation of intracellular CO2 concentration (Ci), as well as an
explicit calculation of the CO2 compensation point. The current
implementation of photosynthetic biochemistry is closely related to the
original BIOME-BGC logic in that it is based on the Farquhar biochemical
model, but the resulting set of equations is somewhat different due to
differences in the logical constraints applied: we solve a quadratic system of
equations by elimination of Ci, instead of specifying a value as an initial
condition. Other differences include a more detailed dependence of the
kinetic parameters on temperature (Woodrow and Berry 1988), and a simplifying
assumption that empirically relates the maximum rate of electron transport to
the maximum carboxylation velocity (Wullschleger 1993).
Photosynthesis is regulated by the canopy conductance to CO2 (gc), leaf
maintenance respiration and daily meteorological conditions including air
pressure, air temperature and photosynthetically active photon flux density
(PPFD). The maximum canopy conductance to CO2 (gc,max) defines the upper
boundary of the photosynthetic rate and is determined by LAI and prescribed
leaf-scale boundary layer, cuticular and maximum stomatal conductances; gc is
reduced when air temperature, vapor pressure deficit, PPFD, or soil water
potential deviate from prescribed optimal conditions (Leuning 1990, Running
and Coughlan 1988, Jarvis and Morison 1981). BIOME-BGC represents the canopy
as a "big leaf" in that all units of leaf area in the canopy are represented
using a single, canopy averaged conductance. This assumption is generally not
valid at sub-daily (e.g. hourly) time-steps since the reduction of irradiance
at lower vertical layers of the canopy reduces conductances at the bottom of
the canopy. The big leaf assumption is strengthened, however, by the
integrative effects of a daily time-step, and by the implicit assumption that
the allocation of leaf nitrogen between light harvesting and carbon fixing
enzymes over depth in the canopy varies in response to the canopy light
environment, allowing an optimized use of intercepted radiation (Evans 1989).
Total respiration from the system (Rtot) is estimated on a daily basis as
the sum of the maintenance (Rm), heterotrophic (Rh) and growth (Rg)
respiration components. Rm represents the total loss of carbon due to day and
night leaf respiration (Rdl + Rnl), sapwood (Rsw), coarse root (Rcr) and fine
root (Rfr) respiration. Respiration is estimated as a daily proportion of
carbon in living tissue that is released as the result of cellular metabolic
processes, excluding any growth processes. Rm is calculated from mean daily
air temperatures and prescribed leaf, root and sapwood carbon pools using an
exponentially increasing function of respiration with temperature following
Amthor (1986). The magnitude of the respiration response to temperature is
governed by a prescribed rate defined at a reference temperature (i.e. 15 C)
and a proportional change in rate for a 10 C change in temperature (Q10). In
all cases except leaf maintenance respiration the daily average temperature is
used, and a single value is calculated for the mass lost to maintenance
respiration for the day. In the case of leaves, however, Rdl and Rnl rates
are calculated from estimated day and night air temperatures, respectively,
since Rdl is required to determine GPP. Daily growth respiration was not
determined explicitly by the model in this investigation; instead Rg was
computed as a proportion (32%) of the daily estimated total net primary
productivity, NPP (Penning de Vries et al. 1974).
The heterotrophic respiration term in BIOME-BGC represents the loss of
carbon from the system resulting from soil microbial respiration. Daily Rh is
estimated as a proportion of prescribed soil and litter carbon pools. The
proportion of litter carbon being respired on a daily basis is regulated by
soil water potential and soil temperature conditions following Orchard and
Cook (1983), Andren and Paustian (1987), and Running and Coughlan (1988). The
proportion of soil carbon respired on a daily basis was estimated as 1% of the
proportion of litter carbon respired based on data for boreal coniferous and
deciduous stands (Fox and Van Cleve 1983, Cole and Rapp 1981).
NPP represents the net accumulation of carbon by the stand and is
determined as the difference between GPP and the sum of Rm and Rg. The net
ecosystem exchange of carbon (NEE) represents the net accumulation or loss of
carbon by the entire soil-stand system and is determined as the difference
between GPP and Rtot. Positive fluxes in this investigation denote a net
uptake of carbon by the system while negative fluxes denote a net loss.
Standards for denoting positive and negative fluxes generally vary between
different disciplines, however, and net carbon uptake is often denoted as a
negative flux in the literature.
BIOME-BGC uses daily maximum and minimum air temperatures, humidity,
incident solar radiation and precipitation to determine daily carbon and water
fluxes. Average daily incident shortwave radiation (Qi) was simulated using
MT-CLIM logic described by Running et al. (1987). Average daily net solar
radiation (Qn) was estimated using a prescribed, constant albedo for
vegetation. Qn was attenuated through the vegetation canopy using Beer's
formulation and a prescribed extinction coefficient modulated by LAI to derive
the amount of solar radiation transmitted through the canopy (Qt). The amount
of solar radiation absorbed by the canopy (Qa) was estimated as the difference
between Qi and Qt. PPFD was estimated based on the assumption that
photosynthetically active radiation represents approximately 50% of Qa
(Running and Coughlan 1988).
Mean daily air temperature (Ta) was estimated as the average of the
measured daily maximum and minimum air temperatures. Minimum daily air
temperature was assumed equal to the mean daily dew point and was used to
estimate the mean daily vapor pressure deficit (VPD). Daily soil temperatures
at a 30 cm soil depth (Tsoil) were estimated using an 11 day running average
of Ta (Zheng et al. 1993). Soil water potential (PSI) was estimated from soil
water content, soil depth and texture information following Cosby et al.
(1984). Ta, VPD, PPFD and PSI were used to estimate gc and GPP following
Jarvis and Morison (1981) and Farquhar and von Caemmerer (1982), respectively.
Ta and Tsoil were used to estimate Rm while Tsoil and PSI were used to
estimate Rh (Running and Coughlan 1988).
1.6 Related Models
These results represent site specific model runs using BIOME-BGC.
BIOME-BGC will also be used within the context of a regional hydro-ecological
simulation system (RHESSys) to generate landscape level estimates of 1994
daily hydrologic and carbon fluxes within the 1x10^6 km^2 boreas study region.
A detailed description of the RHESSys model is given by Band et al. (1991
a,b, 1993)
2.1 Investigator(s) Name and Title
Steven W. Running and John S. Kimball (TE-21 and RSS-8)
NTSG School of Forestry, University of Montana
Missoula, MT 59812
2.2 Title of Investigation
BIOME-BGC simulations of stand hydrology, productivity, surface-atmosphere
carbon and water exchange at selected boreas tower flux sites for 1994
2.3 Contact Information
John S. Kimball NTSG School of Forestry, University of Montana Missoula, MT 59812 Tel: (406)243-5616 FAX: (406)243-4510 Email: johnk@ntsg.umt.edu
BIOME-BGC requires general information about stand morphology and soil
characteristics in order to simulate the water and carbon balance at a site.
Information required by the model to define initial hydrologic characteristics
of the study sites is given by Kimball et al. (submitted). A list of critical
parameters used to define soil and stand carbon characteristics at the 8 study
sites are presented in Table 1. These parameters were held constant
throughout the model runs. Soil parameters were derived from measurements
collected at the sites during 1994 by Cuenca et al. (submitted) and values
reported in the literature for representative soil types (Hillel 1980). The
soil depth was set at 0.5 m and assumed homogeneous in regard to soil
mineralized carbon, structure and soil moisture characteristics. Mean daily
stand solar albedos for snow-free conditions were estimated from site
observations (Sellers et al. 1995).
Estimates of average annual leaf area index (LAI) were derived from
effective LAI measurements conducted over approximately 3 periods during the
1994 growing season at each study site by Chen (submitted). Effective LAI was
measured using LI-COR LAI-2000 plant canopy analyzer and adjusted for foliage
clumping. Specific leaf area (SLA) and leaf nitrogen levels were determined
from plucked needle and leaf measurements at the spruce, jack pine and aspen
sites by Margolis et al. (1996 unpublished data). The amounts of leaf
nitrogen in RuBisCO were estimated from the literature for representative
cover types (Field and Mooney 1986). Leaf carbon was derived from LAI and SLA
information. Sapwood carbon was estimated from sapwood biomass measurements
collected by Gower et al. (1996 unpublished data) at the black spruce, aspen
and jack pine sites, and estimates of the relative proportions of sapwood live
cells (Waring and Schlesinger 1985). Coarse root carbon was estimated to be
approximately 25% of sapwood carbon (e.g. Grier et al. 1981, Grier and Logan
1977).
The amount of carbon attributed to fine root biomass is highly variable
depending on species type, stand age and nutrient availability. Processes
governing the partitioning of carbon between root and foliar biomass are
generally poorly understood and not well quantified in the literature.
Observations have shown, however, that fine root biomass is generally greater
than foliar biomass in nutrient limited systems which often occur in boreal
and cold temperate forests and may represent an adaptation to maximize
nutrient uptake (Nadelhoffer et al. 1985, Keyes and Grier 1981, Tetrealt et
al. 1978). Soil carbon attributed to fine roots was estimated from 1.5 (SOAS)
to 3.5 (SOJP) times the estimated leaf carbon based on observations from
boreal and cold temperate coniferous and deciduous stands on nutrient poor
sites (Gower et al. 1992, Comeau and Kimmins 1989, Nadelhoffer et al. 1985,
Linder and Axelson 1982, Perala and Alban 1982, Keyes and Grier 1981). Soil
litter and mineralized organic carbon pools within the prescribed 0.5 m soil
depths were estimated from soil layer depth, bulk density and percent organic
carbon measurements conducted at each of the study sites by Anderson et al.
(1995 unpublished data).
Leaf, stem, coarse and fine root maintenance respiration coefficients
were estimated from measured rates for coniferous and deciduous cover types
(Sprugel et al. 1995). All other ecophysiological parameters were obtained
from the literature for general cover types (e.g. Sprugel et al. 1995, Nobel
1991, Waring and Schlesinger 1985).
6.1 Data Notes
Not Applicable
BIOME-BGC was run over a 2 year period at each study site. The model was
initialized using 1989 AMS mesonet station meteorological data from the
Thompson airport (55.8 *N, 97.9 *W) for study sites in the NSA, and Prince
Albert airport (53.2 *N, 105.7 *W) and Waskesiu Lake (53.9 *N, 106.1 *W) for
study sites in the SSA (Shewchuk submitted). All analyses of model results
were done for the second year using the 1994 meteorological database described
above.
7.1 Spatial Characteristics
7.1.1 Spatial Coverage
These results constitute point simulations of the BOREAS NSA Old Black
Spruce (NSA-OBS), Young Jack Pine (NSA-YJP), SSA Old Aspen (SSA-OA), Old Black Spruce (SSA-OBS), and Old Jack Pine (SSA-OJP) tower flux sites.
7.1.2 Spatial Coverage Map
Not Applicable
7.1.3 Spatial Resolution
Not Applicable
7.1.4 Projection
Not Applicable
7.1.5 Grid Description
Not Applicable
7.2 Temporal Characteristics
The model generated daily results for 2 years. Results for the first year
were generated using 1989 meteorological data which were used to initialize
the model, while all analyses were done for the second year (1994).
7.2.1 Temporal Coverage
01-01-1994 to 12-31-1994
7.2.2 Temporal Coverage Map NA
Not Applicable
7.2.3 Temporal Resolution
daily
7.3 Data Characteristics
BIOME-BGC requires an input daily meteorological data file and an
initialization file to generate daily estimates of site hydrologic and carbon
balance characteristics. The meteorological data file variables are described
below. The initialization file provides site specific information about stand
morphology, soil type and condition. The initialization files used to generate
results for 1994 at the tower flux sites are included in this directory and
are described in section 5.
7.3.1 Input Parameter/Variables
Meteorological data input file: DOY PCP TMAX TMIN SOLIN DAYLEN
7.3.2 Variable Description/Definition
DOY = Julian day (1-365) PCP = daily precipitation (cm) TMAX = maximum 24-hour air temperature (C) TMIN = minimum 24-hour air temperature (C) SOLIN = total daily solar radiation (kJ) DAYLEN = daylength (s)
7.3.3 Unit of Measurement
See 7.3.2
7.3.4 Data Source
Daily meteorological data were derived from approximate 15 minute measurements
obtained from AMS mesonet and flux tower sites for 1994 (BOREAS Science Team
1995; Shewchuk submitted). The initialization data files were created using
information obtained from measurements by other boreas investigators and the
literature for similar stand types (See section 5).
7.3.5 Data Range
Not Applicable
7.4 Sample Data Record
7.4.1 Output Parameter/Variables
Hydrologic output variables:
DOY SNOWW SOILW T ET E Q
Carbon output variables:
DOY GPP Rdl Rnl Rsw Rcr Rfr Rh Rm Rg NPP NEE Rtot
**NOTE: NEE denoted with a (-) sign indicates net C release from the stand to the atmosphere while a positive sign indicates net C uptake by the stand.
7.4.2 Variable Description/Definition
Return to top of documentDOY = julian day (Day Of Year)
SNOWW = Snow water equivalent of the snowcover (mm)
SOILW = Water held in the soil layer (mm)
T = Transpiration from the canopy (kg/m^2 day)
ET = Evapotranspiration (kg/m^2 day)
E = Evaporation from the canopy and surface (kg/m^2 day)
Q = outflow (mm/day)
GPP = Net daily photosynthesis (mg C/m^2 day)
Rdl = Day-time leaf respiration (mg C/m^2 day)
Rnl = Night leaf respiration (mg C/m^2 day)
Rsw = Sapwood respiration (mg C/m^2 day)
Rcr = Coarse root respiration (mg C/m^2 day)
Rfr = Fine root respiration (mg C/m^2 day)
Rh = Heterotrophic respiration (mg C/m^2 day)
Rm = Maintenance respiration (mg C/m^2 day)
Rg = Growth respiration (mg C/m^2 day)
NPP = Net primary production (mg C/m^2 day)
NEE = Net ecosystem carbon exchange (mg C/m^2 day); (-) sign indicates net C
release to the atmosphere while a positive sign indicates net C uptake
by the stand. Rtot=Total respiration (mg C/m^2 day)
7.4.3 Unit of Measurement
See section 7.4.2.
7.4.4 Data Source
BIOME-BGC model output
7.4.5 Data Range
Daily results for 1994
7.5 Sample Data Records
Meteorological data input file sample: 1 0.00 -28.50 -42.00 16.40 24467 2 0.00 -25.50 -42.40 28.70 24554 3 0.04 -15.70 -30.70 23.40 24649 Hydrologic output file: DOY SNOWW SOILW T ET E Q 1 55.39 190.00 0.00 0.01 0.01 0.00 2 55.78 190.00 0.00 0.01 0.01 0.00 3 55.77 190.00 0.00 0.01 0.00 0.00 Carbon output file: DOY GPP Rdl Rnl Rsw Rcr Rfr Rh Rm Rg NPP NEE Rtot 1 11 43 92 39 10 278 0 462 0.0 -451 -451 462 2 14 46 91 41 10 289 0 477 0.0 -463 -463 477 3 22 53 113 48 12 338 0 564 0.0 -542 -542 564
8.1 Data Granularity
Not Applicable
8.2 Data Format(s)
The model input and output files are in ascii format with space separated
columns.
9.1 Formulae
See section 9.
9.1.1 Derivation Techniques and Algorithms
See section 9.
9.2 Data Processing Sequence
See section 9.
9.2.1 Processing Steps
See section 9.
9.2.2 Processing Changes
See section 9.
9.3 Calculations
See section 9.
9.3.1 Special Corrections/Adjustments
Not Applicable
9.3.2 Calculated Variables
See section 7.4.1 and 7.4.2.
9.4 Graphs and Plots
Not Applicable
10.1 Sources of Error
BIOME-BGC is a process level model designed to be general enough to apply
at regional to global scales. The model uses several simplifying assumptions
regarding stand and meteorological conditions in order to facilitate
application at regional scales. A fundamental model assumption for this
investigation was that stand physiological conditions such as age, stand
structure, LAI and carbon storages were spatially and temporally uniform on an
annual basis. Soil conditions such as depth, density and moisture content were
also assumed spatially uniform with no lateral or subsurface drainage. Stand
conditions at the study sites were both spatially and temporally diverse and
were composed of different age types, biomass densities and species
compositions (BOREAS Science Team 1995). Some sites also had significant
vegetation understories that were not explicitly modeled in this
investigation. Evidence suggests that these vegetation types contributed
significantly to the daily carbon budget (e.g. Black et al. submitted).
Further discussion of potential error sources for this investigation is given
by Kimball et al. (1996 a,b submitted).
10.2 Quality Assessment
See section 10.1.
10.2.1 Model Validation by Source
Model results were compared with daily carbon and water fluxes derived
from site tower flux measurements for 1994. Model estimates of annual NPP were
also compared with NPP estimates derived from site biomass measurements and
allometric equations for 1994 (BOREAS Science Team 1995). Model estimates of
SNOWW and SOILW were compared with measured data for 1994 (BOREAS Science Team
1995). Detailed discussion of these comparisons are given by Kimball et al.
(1996 a,b submitted).
10.2.2 Confidence Level/Accuracy Judgement
See section 10.2.1.
10.2.3 Measurement Error for Parameters
See section 10.1 and 10.2.1.
10.2.4 Additional Quality Assessments
See section 10.1 and 10.2.1.
10.2.5 Data Verification by Data Center
11.1 Limitations of the Model
See section 10.1 and 10.2.1.
11.2 Known Problems with the Model
See section 10.1 and 10.2.1.
11.3 Usage Guidance
Not Applicable
11.4 Other Relevant Information
Not Applicable
Carbon allocation, growth respiration and nitrogen cycle routines will be
activated (See Running and Hunt 1993) and model runs will be conducted over
longer time periods (50 to several hundred years) to investigate the effects
of inter-annual climate variations on site to regional water and carbon
budgets.
14.1 Software Description
See section 14.
14.2 Software Access
See section 14.
14.3 Platform Limitations
See section 14.
15.1 Contact Information
See section 2.3
15.2 Data Center Identification
15.3 Procedures for Obtaining Data
15.4 Data Center Status/Plans
Not Applicable
16.1 Tape Products
Not Applicable
16.2 Film Products
Not Applicable
16.3 Other Products
Not Applicable
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Malkonen, E. 1974. Annual primary production and nutrient cycle in some Scots pine stands. Commun. Inst. For. Fenn. (Helsinki), No. 84.
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Paavilainen, E. 1980. Effect of fertilization on plant biomass and nutrient cycle on a drained dwarf shrub pine swamp. Comm. Inst. For. Fenn. (Helsinki), No. 98.
Penning de Vries, F.W.T., A. Brunsting, H.H. Van Laar. 1974. Products, requirements and efficiency of biosynthesis: A quantitative approach. Journal of Theoretical Biology. 45:339-377.
Perala, D.A. and D.H. Alban. 1982. Biomass, nutrient distribution and litterfall in Populus, Pinus and Picea stands on two different soils in Minnesota. Plant and Soil. 64:177-192.
Rastetter, E.B., A.W. King, B.J. Cosby, G.M. Hornberger, R.V. O'Neill, and J.E. Hobbie. 1992. Aggregating fine-scale ecological knowledge to model coarser-scale attributes of ecosystems. Ecological Applications. 2:55-70.
Running, S.W. and J.C. Coughlan. 1988. A general model of forest ecosystem processes for regional applications, I. hydrologic balance, canopy gas exchange and primary production processes. Ecological Modelling. 42:125-154.
Running, S.W. and R.E. Hunt. 1993. Generalization of a forest ecosystem process model for other biomes, BIOME-BGC, and an application for global-scale models. In Scaling Physiologic Processes: Leaf to Globe. Eds. J.R. Ehleringer and C.B. Field. Academic Press, San Diego, CA, pp 141-158.
Running, S.W., R.R. Nemani, and R.D. Hungerford. 1987. Extrapolation of synoptic meteorological data in mountainous terrain and its use for simulating forest evapotranspiration and photosynthesis. Canadian Journal of Forest Research 17:472-483.
Sellers, P., F. Hall, H. Margolis, B. Kelly, D. Baldocchi, G. den Hartog, J. Cihlar, M.G. Ryan, B. Goodison, P. Crill, K.J. Ranson, D. Lettenmaier, and D.E. Wickland. 1995. The boreal ecosystem-atmosphere study (BOREAS): an overview and early results from the 1994 field year. Bulletin of the American Meteorological Society. 76(9):1549-1577.
Shewchuk, S.R. 1996. The surface atmospheric sciences mesonet for BOREAS. Journal of Geophysical Research. Submitted.
Sprugel, D.G., M.G. Ryan, J.R. Brooks, K.A. Vogt, and T.A. Martin. 1995. Respiration from the organ level to the stand. In Resource Physiology of Conifers, Acquisition, Allocation and Utilization. Eds. W.K. Smith and T.M. Hinckley. Academic Press, San Diego, pp 255-299.
Tetreault, J.P., B. Bernier, and J.A. Fortin. 1978. Nitrogen fertilization and mycorrhizae of balsam fir seedlings in natural stands. Naturaliste Canadien (Quebec). 105:461-466.
Waring, R.H. and W.H. Schlesinger. 1985. Forest Ecosystems Concepts and Management. Academic Press Inc., San Diego, 340 p.
Woodrow, I.E. and J.A. Berry. 1988. Enzymatic regulation of photosynthetic CO2 fixation in C3 plants. Annual Reviews of Plant Physiology and Plant Molecular Biology. 39:533-594.
Wullschleger, S.D. 1993. Biochemical limitations to carbon assimilation in C3 plants - a retrospective analysis of the A/Ci curves from 109 species. Journal of Experimental Botany. 44:907-920.
Zheng, D., E.R. Hunt and S.W. Running. 1993. A daily soil temperature model based on air temperature and precipitation for continental applications. Climate Research. 2:183-191.
17.1 Model Documentation
See Running and Coughlan (1988), Running and Hunt (1993), Hunt and
Running (1992) and Kimball et al. (1996).
17.2 Journal Articles and Study Reports
See section 17.1.
17.3 Archive/DBMS Usage Documentation
Not Applicable
BOREAS - BOReal Ecosystem-Atmosphere Study BORIS - BOREAS Information System DAAC - Distributed Active Archive Center EOS - Earth Observing System EOSDIS - EOS Data and Information System GSFC - Goddard Space Flight Center NASA - National Aeronautics and Space Administration ORNL - Oak Ridge National Laboratory NSA - BOREAS northern study area SSA - BOREAS southern study area NOBS - NSA old black spruce site NYJP - NSA young jack pine site SOBS - SSA old black spruce site SOJP - SSA old jack pine site SOAS - SSA old aspen site URL - Uniform Resource Locator DOY - julian day SNOWW - Snow water equivilent of the snowcover (mm) SOILW - Water held in the soil layer (mm) T - Transpiration from the canopy (kg/m^2 day) ET - Evapotranspiration (kg/m^2 day) E - Evaporation from the canopy and surface (kg/m^2 day) Q - outflow (mm/day) GPP - Net daily photosynthesis (mg C/m^2 day) Rdl - Day-time leaf respiration rate (mg C/m^2 day) Rnl - Night-time leaf respiration rate (mg C/m^2 day) Rsw - Sapwood respiration rate (mg C/m^2 day) Rcr - Coarse root respiration rate (mg C/m^2 day) Rfr - Fine root respiration rate (mg C/m^2 day) Rm - Maintenance respiration (mg C/m^2 day) Rh - Heterotrophic respiration (mg C/m^2 day) Rg - Growth respiration (mg C/m^2 day) NPP - Net primary production (mg C/m^2 day) NEE - Net ecosystem carbon exchange (mg C/m^2 day) Rtot - Total respiration (mg C/m^2 day) PCP - daily precipitation (cm) TMAX - maximum 24-hour air temperature (C) TMIN - minimum 24-hour air temperature (C) SOLIN - total daily solar radiation (kJ) DAYLEN - daylength (s) LAI - Leaf area index (m^2/m^2) SLA - Specific leaf area (m^2/kg C)
20.1 Document Revision Date
19-Sept-1996
20.2 Document Review Date(s)
BORIS Review:
Science Review:
20.3 Document
[BORIS and ORNL DAAC to fill in]
20.4 Citation
Use references in Section 17.1 when citing BIOME-BGC.
20.5 Document Curator
[BORIS and ORNL DAAC to fill in]
20.6 Document URL
[BORIS and ORNL DAAC to fill in]
Keywords: BIOME-BGC, carbon, water, hydrology, NPP, tower sites, modeling, productivity
