of NDP-078A, along with Appendixes A, B, C, and D.
of NDP-078A, along with Appendixes A, B, C, and D.
Fortran and SASTM access codes are provided to read the ASCII data files. The data files and this documentation are available without charge on a variety of media and via the Internet from the Carbon Dioxide Information Analysis Center (CDIAC).
Keywords: forests, growth, leaf area index, litter, sapling, soil, soil
temperature, soil water content, soil water
potential, tree, weather
To provide data on the responses of forests to altered precipitation regimes, the Throughfall Displacement Experiment (TDE) was established in the Walker Branch Watershed (WBW) of East Tennessee (latitude 35o 58' N, longitude 84o 17' W). Funding for the TDE was provided by the Program for Ecosystem Research of the U.S. Department of Energy's Office of Biological and Environmental Research.
Remotely sensed imagery of the WBW is available from the National Aeronautics and Space Administration (http://modis- land.gsfc.nasa.gov/val/coresite.asp?SiteID=28 and http: //modis.gsfc.nasa.gov/MODIS/LAND/VAL/prove/forest/prove.html) and from the U.S. Geological Survey.
A detailed description of the TDE is provided by Hanson et al. (1998) and Hanson et al. (2001) (see Appendix A). Experimental manipulation of hydrologic inputs at the TDE is accomplished by intercepting throughfall in approximately 2000 subcanopy troughs (0.3 x 5 m) suspended above the forest floor on a "dry" treatment plot and transferring the throughfall across a control plot for distribution onto a "wet" treatment plot. Each plot is 80 x 80 m in size. The treatments result in a 33% decrease in precipitation reaching the forest floor on the dry plot and a corresponding increase in precipitation on the wet plot. Reductions in soil moisture on the dry plot are expected to be equivalent to the driest growing seasons of the 1980's drought, which resulted in reduced tree growth of some species.
The site was chosen because of its uniform slope, consistent soils, and a
reasonably uniform distribution of
vegetation. The physical and chemical characteristics of the typic Paleudult
soils (Fullerton cherty silt loam)
of the TDE site are summarized in Appendix B.
The forest community is dominated by white oak, chestnut oak, and
red maple, but it contains more than 25 tree species (Appendix C). The past 25 years of research on the
Walker
Branch Watershed provide an important reference database against which to
judge the outcomes of this large-scale
field experiment.
MEASUREMENT METHODS
Soil Water Content and Potential
Soil water content (%, v/v) was measured with a Soil Moisture Equipment Corp.® TRASE
SYSTEM time-domain
reflectometer (TDR) following the procedure of Topp and Davis (1985) as
documented for soils with high
coarse-fraction content (Drungil et al. 1989). Three hundred and ten sampling
locations were installed at
an 8 x 8-m spacing across the site, giving more than 100 soil water monitoring
locations per plot. At each
location two pairs of TDR waveguides were installed in a vertical orientation
(0 to 0.35 and 0 to 0.7 m).
The surface (0 to 0.35 m) TDR measurements coincide with the zone of maxium
root density in these soils.
TDR measurements were obtained biweekly during the growing season and
approximately monthly during the dormant
season. The TDR soil water content measurements were adjusted for the coarse
fraction of these soils and
converted to soil water potentials using laboratory-derived soil moisture
retention curves for the A, A/E,
and E/B horizons (Hanson et al. 1998).
Soil Rock Content
Soil was sampled from depths of 0 to 30 and 30 to 60 cm in ~10-cm-diameter
cylindrical cores with a total
volume of 2430.96 cm3. The soil coarse fraction was determined by
weighing the material retained by a 2-mm
sieve. To convert coarse-fraction mass to volume all rock (i.e., chert) was
assumed to have a mean density
of 2.3 g cm-3. This density was based on laboratory observations
for chert taken from the TDE samples.
Weather and Radiation
Weather data are collected as hourly means and logged on LiCor® LI-1000
data loggers housed in instrument
enclosures located at one upslope and one downslope location per treatment
plot and one enclosure in the nearby
clearing. Measurements of incoming rainfall, irradiance (LiCor® LI-200SA
pyranometer), and photosynthetic
photon flux density (LiCor® LI-191SA quantum sensor) were obtained in a
nearby clearing until 1998 when
above-canopy observations were added to the ambient plot tower. Clearing data
were used to represent
"above-canopy" conditions for the experimental site for the years 1993-1997.
Mean incident shortwave radiation
was measured with an Eppley® precision spectral pyranometer located 44 m
above the forest canopy (these data
are not available for 1993 and 1994). Two tipping bucket rain gauges with 3-m
extension troughs attached are
installed on each plot to evaluate the amount of throughfall reaching the
forest floor. Sub-canopy air temperatures
(2 stations per treatment plot) are measured with thermistors at approximately
1 m height in a location shielded
from direct solar radiation. Wind data for 1993 through 1997 are from a height
of 37 m on the the Oak Ridge Ameriflux
tower (10 m above the canopy). A value of 1.5 m s-1 is used to fill
in for missing hours for those years in the
hourly weather data. Wind data for 1998 through 2000 are from the ambient plot
tower on the TDE experimental site
and the anemometer is nearer to the canopy (4 m above the canopy).
Litter Temperature
Self-contained Onset Computer® data loggers were deployed within the Oi
litter layer during extensive periods
in 1997 1998 and 2000. In 1997 1998, StowAway XTI08 sensors in the dry (x4)
and ambient (x4) plots were used.
The XTI08 sensors employed an external thermistor positioned inside litter
decomposition bags that were located
in the Oi horizon leaf litter from March 15, 1997, through February 6, 1998.
StowAway TidbiT sensors were placed
directly in the Oi layer of the dry (x4) and wet (x4) plots from January 27,
2000, to December 14, 2000.
Soil Temperature
From 1993 through 1997 hourly soil temperatures were measured at two depths
(10 and 35 cm) at 2 locations in each
treatment plot. LiCor® LI-1000-15 soil temperature thermistors were
installed vertically from the surface
to the specified depth. Data were automatically logged on six independent
LiCor LI-1000 data loggers housed
in instrument enclosures located at one upslope and one downslope location per
treatment plot. No differences
among treatment plots or slope positions were observed for temperatures at
these depths, and the data were pooled
as hourly site averages. Starting in 1998, soil temperature observations were
obtained from Campbell Scientific®
Model 107 soil temperature thermistors installed horizontally into the walls
of an excavated and subsequently
refilled soil pit. The probes were distributed at four depths in each pit (~10
cm, ~30 cm, ~45 cm, and one deep
probe in the 60 to 100-cm range). Data were logged as hourly means of 5-second
(for 1993-1997 data) or 1-minute
(1998 and thereafter) observations on a Campbell Scientific® CR10X data
logger.
Tree Mortality and Growth
Prior to the experiment and at approximately annual intervals thereafter, all trees greater than 0.1 m in diameter at 1.3 m height (diameter at breast height, dbh) were identified to species (762 trees). Presence/mortality was recorded annually. Annual diameter measurements were conducted with diameter tapes at tagged locations on all trees.
Tree heights and crown widths were measured directly on approximately one- third of the trees or derived from allometric relationships from a subset of the measured data. Quercus spp. and Acer spp. were the major canopy dominants; Liriodendron tulipifera L. was a canopy dominant on the lower slope positions; and Nyssa sylvatica Marsh. and Oxydendrum arboreum [L. ] D. C. were the predominant species occupying mid-canopy locations. In March of 1994, stand basal area averaged 21 m2 ha-1 with nearly identical basal area on each plot. By December 1999, mean basal area across all plots had increased to 22.8 m2 ha-1.
Quercus alba L., Q. prinus L., Acer rubrum L., L.
tulipifera L., and N. sylvatica Marsh. trees greater than 0.2 m dbh
were fitted with dendrometer bands (170 trees) for biweekly measurements of
stem circumference during each growing
season. A single dendrometer measurement consists of duplicate digital caliper
measurements (0.01 mm resolution)
of the distance between two reference holes in stainless steel dendrometer
bands (25.4 mm wide x 0.2 mm thick)
installed around the circumference of each tree (McLaughlin and Downing 1996).
Measured changes in the circumference
of each tree were combined with information on its initial stem diameter to
obtain the change in stem basal area over
time (mm2 day-1 or mm2 year-1).
Dendrometer bands were installed on the Q. alba, Q. prinus, and
A. rubrum trees
prior to the 1993 growing season, and bands for L. tulipifera and N.
sylvatica were added in February of 1994. All
dendrometer bands were installed during the dormant season, ahead of the
initial growth measurements, to eliminate
potential first-year bias in the dendrometer band measurements (Keeland and
Sharitz 1993).
Sapling Growth and Mortality
Starting in 1996 all saplings in 27 plots (8 x 8 m) distributed across the TDE experimental area (9 plots per treatment) were observed for survival and diameter (measured with a caliper) at marked locations on the stems. The preferred target height for diameter measurements was 1.3 m unless the sapling was too small, in which case 1 m was used instead. Figure 1 shows the distribution (random within rows). Each small block is an 8 x 8-m plot. The 27 plots, each 8 x 8 m, yielded a total of 1728 m2 of monitored area, which was 9% of the total TDE experimental area. The number of saplings (trees < 0.1 m dbh) across the TDE area averaged 3073 ha-1 in 1994 and 2112 ha-1 in 1999. Saplings contributed an additional 3 and 2.6 m2 ha-1 to total stand basal area in 1994 and 1999, respectively. Acer rubrum L. and Cornus florida L. combined to make up 59 percent of all saplings and 53 percent of the sapling basal area.
In February and March of 1994, 10 transects for observations of sapling growth
and mortality were established
across the three plots from lower- to upper-slope positions. Although other
species were considered for these
measurements, only A. rubrum and C. florida were distributed
across the TDE in sufficient numbers for inclusion.
Saplings ranged from 10 to 60 mm dbh with the majority from 10 to 40 mm.
Height measurements were not included
because the crowns were broad without predominant main shoots and because
height growth was minimal in the
low-light understory environment of our closed canopy stand. Starting at the
time of spring leafout each year,
biweekly measurements of stem diameter at a permanently marked location on
each sapling's main stem (typically
between 1 and 1.5 m above the ground) were conducted until sapling growth had
ceased for that year. Each stem
caliper measurement was the mean of three replicate diameter measurements made
with a digital caliper (0.01 mm
resolution) from three different angles around the marked point of
measurement. The mean of replicate measures
from different angles was required to minimize the impact of noncircular stem
cross sections. Sapling stem
diameters were converted to basal area to express mean daily sapling growth
rates per plant in mm2 day-1, or
integrated annual sapling growth in mm2 year-1.
Incremental growth of saplings that died in a given year
were included in the calculation of that year's mean growth rate but excluded
in all subsequent estimates
of annual growth. Additional randomly chosen saplings were added to the
measurement pool after the 1994, 1995,
and 1996 growing seasons (to make up for mortality losses), but no additional
plants were added to this
observation set after that time.
Leaf Area Index
Seasonal patterns of stand leaf area development were determined from the ratio of understory to overstory light penetration. This canopy light ratio (CLR; Equation 1) was calculated as 1 minus the ratio of the daily sum of understory photosynthetically active radiation (PARu; PAR at 1.5 m) to the daily sum of overstory incident PAR (PARo):
CLR = 1-(PARu/PARo) Eq. 1
Because of the presence of tree boles and branches, pre-leaf out and post- senescence baselines for the CLR were not zero. Therefore, to express the CLR on a 0-1 scale it was necessary to adjust the ratio for the light penetration during leafless periods as shown in Equation 2:
RelLAI = (Observed CLR-baseline)/(Maximum CLR-baseline) Eq. 2
where RelLAI is the relative leaf area index on the 0-1 scale for a given
date. However, because the baseline
ratio resulting from the presence of boles and branches changed with solar
elevation, we found it necessary
to use more than one baseline for the calculation of the seasonal pattern of
RelLAI. Although the baseline CLR
in the absence of leaves would vary continuously with solar elevation, we
found that use of the pre-leafout
baseline for days 80 through 180 and the post-senescence baseline for days 181
through 350 yielded an acceptable
RelLAI pattern. It is important to note that the RelLAI values are
representative of the development of leaf area,
not leaf mass (i.e., they may overpredict the rate of annual leaf mass
accumulation). Approximations of leaf
mass development or a direct estimate of leaf are index (LAI) could also be
made from the same data using a
light extinction approach as described by Hutchinson and Baldocchi (1989).
Data Logging
Environmental data for the TDE were logged on Campbell Scientific® CR10X data loggers located on each of the treatment plots. All loggers were interfaced with a Campbell Scientific MD9 coaxial multidrop interface, and data from all loggers were remotely accessed weekly via Campbell Scientific® COM200 modem and cellular telephone. As a backup to remote data downloads, the logged data were also stored in Campbell Scientific® SM192 nonvolatile circular memory with the capacity to hold approximately one month's data for the configuration used here. The loggers and associated instrumentation operated off three 12-volt, deep-cycle marine batteries wired in parallel. The batteries were trickle-charged from solar panels (Solarex® 55 watts @ 17.4 volts; with a metered Morningstar® PS30M photovoltaic controller, 30-amp PV current @ 12 volts) installed on towers above the forest canopy. Sensors were connected to the CR10X data logger via a standard wiring panel and two Campbell Scientific® AN416 multiplexer modules.
An example data program for the CR10X data logger editor and the data logger download file for the TDE ambient plot and its instruments are included in this numeric data package (NDP) as files tdeambi.csi and tdeambi.dld, respectively. The example program includes two sampling tables. The majority of the instrumentation is queried once per minute and logged as hourly means or sums as a part of the first sampling table, and a second samling table is included to query heat dissipation matric potential sensors (Campbell Scientific® Model 229) twice a day (noon and midnight). Table 1 lists the measurement interval, logging interval, and type of sensors being logged on the TDE ambient plot as of December 2000.
This NDP provides datasets, and accompanying documentation, on site
characterization, system performance,
weather, species composition, and growth. Related NDPs are planned on
physiology, decomposition, and nutrient cycling.
2. APPLICATIONS OF THE DATA
These data are useful for quantifying certain responses of temperate forest
ecosystems (litter and soil water
content, growth, mortality) to changes in precipitation patterns. Other
datasets from the TDE will be useful
for quantifying other aspects of ecosystem response (e.g., physiology,
decomposition, nutrient cycling).
Data from the TDE have been used in published studies of the effects of
altered water regimes on forest root
systems (Joslin et al. 2000) and sapling and
large-tree growth and mortality (Hanson et al.
2001), and a wide
variety of process-based studies (see Appendix
D for TDE publications).
3. DATA LIMITATIONS AND RESTRICTIONS
Users should be aware of limitations to the data as a result of suspect
values. The quality-assurance checks
performed by CDIAC, and the results of those checks, are described in Section 4.
In the weather files, some reported values of relative humidity (in files mweather.dat, dweather.dat, hw9399.dat, and hw00.dat) exceed 100%; this is physically impossible. However, it is not yet known how these values arose nor how to adjust the data.
Some values of relative leaf area (in file rellai.dat) were suspiciously low, such as the value of 0.44 on day 289 in 1998. Most such values occur in the fall; a lower sun angle may contribute to these low values. A curve-fitting approach may be appropriate to analyze the patterns of leaf senescence.
Hourly weather data were checked by the data contributors for errors and missing data. If bad or missing data were found, approximate replacement data were obtained from other weather data sources in the area, if possible, to provide the most complete data set.
If TDE shortwave radiation data are needed for model input, the values for SWISIS should be used instead of the LiCor® pyranometer data. Both are in good agreement for most years, but the TDE pyranometer data for 1998 and 2000 do not agree very well with the SWISIS data (mean of 5 observations) distributed across the reservation.
The issue of pseudo-replication in the experimental design is addressed by Hanson et al. (1998) and Hanson et al. (2001).
In addition to the above considerations, users should be aware that there is
some evidence of minor effects
of the experimental infrastructure (specifically, the precipitation-collection
equipment) on the microclimate
of the "dry" treatment plot.
4. QUALITY-ASSURANCE CHECKS AND DATA-PROCESSING
ACTIVITIES PERFORMED BY
CDIAC
An important part of the data packaging process at CDIAC involves the quality
assurance (QA) of data before
distribution. To guarantee data of the highest possible quality, CDIAC
performs extensive QA checks, examining
the data for completeness, reasonableness, and accuracy.
Comma-delimited files provided by the data contributors were imported into Microsoft Excel® for QA checks (and, ultimately, converted to space-delimited ascii files for archiving). Files were renamed when necessary, for consistency. Variable names were made consistent across files, for simplicity of documentation and analysis.
The file soiltemp.txt provided by the data contributor was divided into two files, st9398.dat (data from 1993 through 1998) and st9900.dat (data from 1999 through 2000). Sixteen tdr*.txt files (one set for each of two depths, 35 and 70 cm, and for each year from 1993 through 2000) were combined into one tdr.dat file. For consistency with other files, in file tdr.dat integer values 1, 2, and 3 for the variable TREAT were replaced by character values W, A, and D, respectively; and values 1, 2, and 3 for the variable SLOPE were replaced by values B, M, and U, respectively. Eight monthly and eight daily weather files (one monthly and one daily file for each year from 1993 through 2000) were combined into a single mweather.dat file and a single dweather.dat file, respectively. Seven hourly weather files (for the years 1993 through 1999) were combined into a single hw9399.dat file.
The format of all values was checked for improper entries.
Several files (e.g., atree.dat) were reformatted by adding variables for year, depth, etc., but eliminating variables that were a combination of year, depth, etc., and another variable (e.g., growth), thereby reducing the total number of variables, resulting in a "narrower" but "longer" file.
For all variables in all files, the range of values was checked for impossible or suspiciously large or small values, such MONTH >12 or values of water potential (e.g., variable A35WP in file sw.dat) >0 MPa. Values of relative humidity apparently exceeding 100% are discussed in Section 3.
Comparisons and X-Y scattergrams were used to check for outliers and impossible or unlikely combinations. For example, file mweather.dat was inspected to ensure that, for air temperature, relative humidity, and soil temperature, the minimum did not exceed the mean, which in turn did not exceed the maximum; no observations failed this test. Scattergrams were plotted and visually examined to check the correlation between PYRAN and QUAN; and ATMIN and STMIN, ATMEAN and STMEAN, and ATMAX and STMAX (minimum, mean, and maximum air and soil temperatures) in file mweather.dat; no obvious outliers were detected.
The following lists the specific data-quality checks by file:
January 14, 1993 14 14 25.5 25.4 24.8 -0.04 -0.04 -0.04 26.2 26.6 26.5 27.7 28.6 29.0 -0.02 -0.02 -0.02 February 24, 1993 55 55 26.6 25.6 25.1 -0.03 -0.04 -0.04 26.0 25.8 26.4 26.3 26.8 28.5 -0.03 -0.03 -0.02Last two data records:
November 1, 2000 2862 306 6.6 -9.9 5.6 -1.83 -9.99 -2.77 -9.9 -9.9 -9.9 -9.9 -9.9 -9.9 -9.99 -9.99 -9.99 December 15, 2000 2906 350 23.0 23.4 22.4 -0.05 -0.05 -0.06 23.8 22.4 21.9 24.6 21.4 21.4 -0.04 -0.06 -0.06
1993 14 14 26.5 25.9 24.4 26.2 24.6 25.4 24.2 25.5 24.7 -0.037 -0.039 -0.043 -0.037 -0.045 -0.036 -0.044 -0.038 -0.039 1993 55 55 27.1 26.7 26.5 26.7 24.5 25.4 24.9 25.6 25.1 -0.035 -0.035 -0.033 -0.035 -0.045 -0.036 -0.040 -0.037 -0.037Last two data records:
2000 306 2862 8.1 -9.9 5.0 -9.9 -9.9 -9.9 6.2 -9.9 4.9 -1.162 -9.999 -3.641 -9.999 -9.999 -9.999 -2.104 -9.999 -3.632 2000 350 2906 24.7 22.1 22.3 24.3 23.1 22.9 20.6 22.0 19.9 -0.046 -0.063 -0.058 -0.047 -0.054 -0.050 -0.073 -0.060 -0.077
1993 14 35W B 1 1 0 0 17.8 1993 14 35W B 1 2 0 8 26.6Last two data records:
2000 350 70D U 10 30 72 232 22.0 2000 350 70D U 10 31 72 240 22.7
W B 2 1 -999 -99.9 -9.9 -999 -99.9 -9.9 W B 2 2 475 206.5 8.5 697 303.0 12.5Last two data records:
D U 10 30 651 283.0 11.6 734 319.1 13.1 D U 10 31 -999 -99.9 -9.9 -999 -99.9 -9.9
1997 21 21.66 A 12.2 1997 21 21.70 A 9.9Last two data records:
2000 349 349.50 D 6.9 2000 349 349.54 D 7.4
1993 1 1 1.00 1 7.0 7.0 1993 1 1 1.04 2 7.0 7.0Last two data records: >pre> 1998 12 366 366.92 8783 -99.9 -99.9 1998 12 366 366.96 8784 -99.9 -99.9
1999 1 1 1.00 1 6.1571 7.4550 -9.99 -9.99 -9.99 -9.99 -9.99 -9.99 - 9.99 -9.99 -9.99 -9.99 -9.99 -9.99 1999 1 1 1.04 2 6.0109 7.3718 -9.99 -9.99 -9.99 -9.99 -9.99 -9.99 - 9.99 -9.99 -9.99 -9.99 -9.99 -9.99Last two data records:
2000 12 366 366.92 8783 -9.9999 -9.9999 3.10 5.50 6.90 7.40 4.20 7.00 8.20 9.70 3.90 5.80 6.80 7.60 2000 12 366 366.96 8784 -9.9999 -9.9999 3.00 5.50 6.90 7.40 4.10 7.00 8.20 9.70 3.80 5.80 6.80 7.60
1993 1 384 186 101 -3.3 5.5 16.5 21.5 76.8 101.5 5.0 6.1 7.5 -9.99 1993 2 488 241 50 -11.7 3.8 20.0 16.5 67.9 101.6 6.0 7.8 9.5 -9.99Last two data records:
2000 11 439 232 104 -6.5 8.0 25.1 15.0 68.4 100.0 6.7 12.2 17.8 1.40 2000 12 376 189 75 -12.4 -0.5 11.5 31.7 71.2 99.8 3.2 6.7 10.0 1.60
1993 1 8.04 3.61 66.8359 1.0 1.6 4.8 9.7 65.2 74.9 84.3 6.9 6.9 7.0 -9.9 1993 2 8.04 3.61 66.8359 0.0 1.6 4.9 9.7 65.2 75.0 84.3 6.7 6.8 6.9 -9.9Last two data records:
2000 365 8.90 4.70 57.0000 0.0 -10.5 -8.2 -6.3 63.0 71.1 83.3 3.7 4.0 4.7 2.1 2000 366 14.30 7.60 85.0000 0.0 -8.7 -6.3 -3.3 57.3 72.6 85.4 3.2 3.6 3.9 1.4
1993 1 1 1.00 0 0 0 -99 2.6 71.2 0.0 -9.9 7.0 0.213 -99 1993 1 1 1.04 1 0 0 -99 2.4 71.8 0.0 2.6 7.0 0.206 -99Last two data records in file hw9399.dat:
1999 12 365 365.96 8759 0 0 0 11.2 65.9 0.0 2.5 9.7 0.454 0 1999 12 365 366.00 8760 0 0 0 11.4 64.6 0.0 2.5 9.8 0.454 0
2000 1 1 1.04 1 0 0 0 11.1 66.1 0.0 2.3 9.4 0.449 0 2000 1 1 1.08 2 0 0 0 10.4 69.0 0.0 2.1 9.3 0.392 0Last two data records in file hw00.dat:
2000 12 366 366.96 8783 0 0 0 -5.6 70.3 0.0 1.6 3.6 0.120 0 2000 12 366 367.00 8784 0 0 0 -5.9 73.8 0.0 1.7 3.6 0.104 0
30.0AR W U 8 2 61.6 11.9 -99.9 -99.9 9.9 9.9 10.9 11.4 12.1 12.7 13.5 32.0AR A B 2 16 15.1 122.5 -99.9 -99.9 10.4 10.4 11.5 12.3 12.9 13.1 13.7Last two data records:
6019.0CF D B 1 24 2.5 189.6 -99.9 -99.9 -99.9 -99.9 9.8 10.1 11.3 10.3 10.4 6020.0OA D B 1 23 0.8 182.4 -99.9 -99.9 -99.9 -99.9 12.1 12.2 12.5 12.8 12.9
1.0AR W U 9 2 1 2.12 2.32 -9.99 -9.99 2.0AR W U 9 2 2 2.96 2.95 -9.99 -9.99Last two data records:
597.0QV D B 3 27 13 4.17 4.18 4.40 4.44 598.0Carya D B 3 27 14 1.52 1.50 1.60 1.61
1993 51AR A M 5 12 2673 1993 52AR A M 5 12 2462Last two data records:
2000 2992QA A M 6 13 1576 2000 2996QP W M 5 9 2157
1994 3001 AR W U 10 1 0.122 1994 3002 AR A U 10 11 0.090Last two data records:
2000 4027a CF A M 6 14 -9.999 2000 5015a CF W B 3 8 -9.999
1992 85 -9.99 1992 86 -9.99Last two data records:
2000 349 -9.99 2000 350 -9.99
/*** retrieval routine to read sw.dat ***/
data sw ;
infile '/home/cdp/ndp078a/sw.dat' ;
input DATE $ 1-18 RDOY 19-23 DOY 24-27 W35WC 28-32 A35WC 33-37 D35WC 38-42
W35WP 43-48 A35WP 49-54 D35WP 55-60 W70WC 61-65 A70WC 66-70 D70WC 71-75
W3570WC 76-80 A3570WC 81-85 D3570WC 86-90 W3570WP 91-96 A3570WP 97-102
D3570WP 103-108 ;
run ;
C *** Fortran program to read the NDP-078a file "sw.dat"
C
INTEGER RDOY, DOY
REAL W35WC, A35WC, D35WC, W35WP, A35WP, D35WP, W70WC,
+ A70WC, D70WC, W3570WC, A3570WC, D3570WC, W3570WP,
+ A3570WP, D3570WP
CHARACTER DATE*18
C
OPEN (UNIT=1, FILE='sw.dat')
C
10 READ (1,100,END=99) DATE, RDOY, DOY, W35WC, A35WC, D35WC,
+ W35WP, A35WP, D35WP, W70WD, A70WC, D70WC, W3570WC, A3570WC,
+ D3570WC, W3570WP, A3570WP, D3570WP
100 FORMAT (A18,I5,I4,3F5.1,3F6.2,6F5.1,3F6.2)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read nine.dat ***/
data nine ;
infile '/home/cdp/ndp078a/nine.dat' ;
input YEAR 1-5 DOY 6-9 RDOY 10-14 WBWC 15-19 WMWC 20-24 WUWC 25-29
ABWC 30-34 AMWC 35-39 AUWC 40-44 DBWC 45-49 DMWC 50-54 DUWC 55-59
WBWP 60-66 WMWP 67-73 WUWP 74-80 ABWP 81-87 AMWP 88-94
AUWP 95-101 DBWP 102-108 DMWP 109-115 DUWP 116-122 ;
run ;
C *** Fortran program to read the NDP-078a file "nine.dat"
C
INTEGER YEAR, DOY, RDOY
REAL WBWC, WMWC, WUWC, ABWC, AUWC, DBWC, DMWC, DUWC,
+ WBWP, WMWP, WUWP, ABWP, AMWP, AUWP, DBWP, EMWP,
+ DUWP
C
OPEN (UNIT=1, FILE='nine.dat')
C
10 READ (1,100,END=99) YEAR, DOY, RDOY, WBWC, WMWC, WUWC,
+ ABWC, AMWC, AUWC, DBWC, DMWC, DUWC, WBWP, WMWP, WUWP,
+ ABWP, AMWP, AUWP, DBWP, DMWP, DUWP
100 FORMAT (I5,I4,I5,9F5.1,9F7.3)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read tdr.dat ***/
data tdr ;
infile '/home/cdp/ndp078a/tdr.dat' ;
input YEAR 1-5 DOY 6-9 DEPTH 10-12 TREAT $ 13-14 SLOPE $ 15-16 Y 17-19
X 20-22 YM 23-25 XM 26-29 SWC 30-34 ;
run ;
C *** Fortran program to read the NDP-078a file "tdr.dat"
C
INTEGER YEAR, DOY, DEPTH, Y, X, YM, XM
REAL SWC
CHARACTER TREAT*2, SLOPE*2
C
OPEN (UNIT=1, FILE='tdr.test')
C
10 READ (1,100,END=99) YEAR, DOY, DEPTH, TREAT, SLOPE,
+ Y, X, YM, XM, SWC
100 FORMAT (I5,I4,I3,2A2,3I3,I4,F5.1)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read rocks.dat ***/
data rocks ;
infile '/home/cdp/ndp078a/rocks.dat' ;
input TREAT $ 1-2 SLOPE $ 3-4 Y 5-7 X 8-10
CFMASS30 11-15 CFVOL30 16-21 CFPCT30 22-26
CFMASS60 27-31 CFVOL60 32-37 CFPCT60 38-42 ;
run ;
C *** Fortran program to read the NDP-078a file "rocks.dat"
C
INTEGER Y, X, CFMASS30, CFMASS60
REAL CFVOL30, CFPCT30, CFVOL60, CFPCT60
CHARACTER TREAT*2, SLOPE*2
C
OPEN (UNIT=1, FILE='rocks.dat')
C
10 READ (1,100,END=99) TREAT, SLOPE, Y, X, CFMASS30,
+ CFVOL30, CFPCT30, CFMASS60, CFVOL60, CFPCT60
100 FORMAT (2A2,2I3,2(I5,F6.1,F5.1))
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read littert.dat ***/ data littert ; infile '/home/cdp/ndp078a/littert.dat' ; input YEAR 1-5 DOY 6-9 DFOY 10-16 TREAT $ 17-18 LITTERT 19-24 ; run ;
C *** Fortran program to read the NDP-078a file "littert.dat"
C
INTEGER YEAR, DOY
REAL DFOY
CHARACTER TREAT*2
C
OPEN (UNIT=1, FILE='littert.dat')
C
10 READ (1,100,END=99) YEAR, DOY, DFOY, TREAT, LITTERT
100 FORMAT (I5,I4,F7.2,A2,F6.1)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
*** retrieval routine to read st9398.dat ***/
data st9398 ;
infile '/home/cdp/ndp078a/st9398.dat' ;
input YEAR 1-5 MOY 6-8 DOY 9-12 DFOY 13-19 HOY 20-24
ST10 25-30 ST35 31-36 ;
run ;
C *** Fortran program to read the NDP-078a file "st9398.dat"
C
INTEGER YEAR, MOY, DOY, HOY
REAL DFOY, ST10, ST35
C
OPEN (UNIT=1, FILE='st9398.dat')
C
10 READ (1,100,END=99) YEAR, MOY, DOY, DFOY, HOY, ST10, ST35
100 FORMAT (I5,I3,I4,F7.2,I5,2F6.1)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read st9900.dat ***/
data st9900 ;
infile '/home/cdp/ndp078a/st9900.dat' ;
input YEAR 1-5 MOY 6-8 DOY 9-12 DFOY 13-19 HOY 20-24
ST10 25-32 ST27 33-40 STW6 41-46 STW31 47-52
STW55 53-58 STW72 59-64 STA7 65-70 STA32 71-76
STA59 77-82 STA100 83-88 STD9 89-94 STD30 95-100
STD45 101-106 STD63 107-112 ;
run ;
C *** Fortran program to read the NDP-078a file "st9900.dat"
C
INTEGER YEAR, MOY, DOY, HOY
REAL DFOY, ST10, ST27, STW6, STW31, STW55, STW72,
+ STA7, STA32, STA59, STA100, STD9, STD30, STD45, STD63
C
OPEN (UNIT=1, FILE='st9900.dat')
C
10 READ (1,100,END=99) YEAR, MOY, DOY, DFOY, HOY, ST10, ST27,
+ STW6, STW31, STW55, STW72, STA7, STA32, STA59, STA100,
+ STD9, STD30, STD45, STD63
100 FORMAT (I5,I3,I4,F7.2,I5,2F8.4,12F6.2)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read mweather.dat ***/
data mweather ;
infile '/home/cdp/ndp078a/mweather.dat' ;
input YEAR 1-5 MONTH 6-8 QUAN 9-13 PYRAN 14-17 RAIN 18-21
ATMIN 22-27 ATMEAN 28-32 ATMAX 33-37 RHMIN 38-42
RHMEAN 43-47 RHMAX 48-53 STMIN 54-58 STMEAN 59-63
STMAX 64-68 WIND 69-74;
run ;
C *** Fortran program to read the NDP-078a file "mweather.dat"
C
INTEGER YEAR, MONTH, QUAN, PYRAN, RAIN
REAL ATMIN, ATMEAN, ATMAX, RHMIN, RHMEAN, RHMAX,
+ STMIN, STMEAN, STMAX, WIND
C
OPEN (UNIT=1, FILE='mweather.dat')
C
10 READ (1,100,END=99) YEAR, MONTH, QUAN, PYRAN, RAIN,
+ ATMIN, ATMEAN, ATMAX, RHMIN, RHMEAN, RHMAX, STMIN,
+ STMEAN, STMAX, WIND
100 FORMAT (I5,I3,I5,2I4,F6.1,4F5.1,F6.1,3F5.1,F6.2)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read dweather.dat ***/
data dweather ;
infile '/home/cdp/ndp078a/dweather.dat' ;
input YEAR 1-5 DOY 6-9 QUAN 10-15 PYRAN 16-21 RADMEAN 22-31
RAIN 32-37 ATMIN 38-43 ATMEAN 44-49 ATMAX 50-54 RHMIN 55-60
RHMEAN 61-66 RHMAX 67-72 STMIN 73-77 STMEAN 78-82
STMAX 83-87 WIND 88-92 ;
run ;
C *** Fortran program to read the NDP-078a file "dweather.dat"
C
INTEGER YEAR, DOY, RAIN
REAL QUAN, PYRAN, RADMEAN, ATMIN, ATMEAN, ATMAX, RHMIN,
+ RHMEAN, RHMAX, STMIN, STMEAN, STMAX, WIND
C
OPEN (UNIT=1, FILE='dweather.dat')
C
10 READ (1,100,END=99) YEAR, DOY, QUAN, PYRAN, RADMEAN,
+ RAIN, ATMIN, ATMEAN, ATMAX, RHMIN, RHMEAN, RHMAX, STMIN,
+ STMEAN, STMAX, WIND
100 FORMAT (I5,I4,2F6.2,F10.4,3F6.1,F5.1,3F6.1,4F5.1)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read hw9399.dat ***/
data hw9399 ;
infile '/home/cdp/ndp078a/hw9399.dat' ;
input YEAR 1-5 MOY 6-8 DOY 9-12 DFOY 13-19 HOY 20-24
QUAN 25-29 PYRAN 30-34 UQUAN 35-39 AT 40-45
RH 46-51 RAIN 52-56 WIND 57-61 ST 62-66
VPD 67-73 SWISIS 74-78;
run ;
C *** Fortran program to read the NDP-078a file "hw9399.dat"
C
INTEGER YEAR, MOY, DOY, HOY, QUAN, PYRAN, UQUAN, SWISIS
REAL DFOY, AT, RH, RAIN, WIND, ST, VPD
C
OPEN (UNIT=1, FILE='hw9399.dat')
C
10 READ (1,100,END=99) YEAR, MOY, DOY, DFOY, HOY, QUAN,
+ PYRAN, UQUAN, AT, RH, RAIN, WIND, ST, VPD, SWISIS
100 FORMAT (I5,I3,I4,F7.2,4I5,2F6.1,3F5.1,F7.3,I5)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read hw00.dat ***/
data hw00 ;
infile '/home/cdp/ndp078a/hw00.dat' ;
input YEAR 1-5 MOY 6-8 DOY 9-12 DFOY 13-19 HOY 20-24
QUAN 25-29 PYRAN 30-34 UQUAN 35-39 AT 40-45
RH 46-51 RAIN 52-56 WIND 57-61 ST 62-66
VPD 67-73 SWISIS 74-78;
run ;
C *** Fortran program to read the NDP-078a file "hw00.dat"
C
INTEGER YEAR, MOY, DOY, HOY, QUAN, PYRAN, UQUAN, SWISIS
REAL DFOY, AT, RH, RAIN, WIND, ST, VPD
C
OPEN (UNIT=1, FILE='hw00.dat')
C
10 READ (1,100,END=99) YEAR, MOY, DOY, DFOY, HOY, QUAN,
+ PYRAN, UQUAN, AT, RH, RAIN, WIND, ST, VPD, SWISIS
100 FORMAT (I5,I3,I4,F7.2,4I5,2F6.1,3F5.1,F7.3,I5)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read comptree.dat ***/
data comptree ;
infile '/home/cdp/ndp078a/comptree.dat' ;
input ID 1-7 SPC $ 8-15 TREAT $ 16-17 SLOPE $ 18-19 Y 20-22 X 23-25
YM 26-30 XM 31-36 D010693 37-42 D010694 43-48 D011294 49-54
D010695 55-60 D010796 61-66 D010797 67-72 D010998 73-78
D011299 79-84 D290101 85-90 ;
run ;
C *** Fortran program to read the NDP-078a file "comptree.dat"
C
INTEGER Y, X
REAL ID, YM, XM, D010693, D010694, D011294, D010695,
+ D010796, D010797, D010998, D011299, D290101
CHARACTER SPC*8, TREAT*2, SLOPE*2
C
OPEN (UNIT=1, FILE='comptree.dat')
C
10 READ (1,100,END=99) ID, SPC, TREAT, SLOPE, Y, X, YM,
+ XM, D010693, D010694, D011294, D010695, D010796,
+ D010797, D010998, D011299, D290101
100 FORMAT (F7.1,A8,2A2,2I3,F5.1,10F6.1)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read compsap.dat ***/
data compsap ;
infile '/home/cdp/ndp078a/compsap.dat' ;
input ORDER 1-6 SPC $ 7-15 TREAT $ 16-17 SLOPE $ 18-19 Y 20-21 X 22-24
PLOTID 25-27 D1996 28-33 D1997 34-39 D1998 40-45 D1999 46-51 ;
run ;
C *** Fortran program to read the NDP-078a file "compsap.dat"
C
INTEGER ORDER, Y, X, PLOTID
REAL D1996, D1997, D1998, D1999
CHARACTER SPC*9, TREAT*2, SLOPE*2
C
OPEN (UNIT=1, FILE='compsap.dat')
C
10 READ (1,100,END=99) ORDER, SPC, TREAT, SLOPE, Y, X,
+ PLOTID, D1996, D1997, D1998, D1999
100 FORMAT (F6.1,A9,2A2,I2,2I3,4F6.2)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read atree.dat ***/
data atree ;
infile '/home/cdp/ndp078a/atree.dat' ;
input YEAR 1-5 ID 6-10 SPC $ 11-13 TREAT $ 14-15 SLOPE $ 16-17 Y 18-20 X 21-23
GROWTH 24-29 ;
run ;
C *** Fortran program to read the NDP-078a file "atree.dat"
C
INTEGER YEAR, ID, Y, X, GROWTH
CHARACTER SPC*3, TREAT*2, SLOPE*2
C
OPEN (UNIT=1, FILE='atree.dat')
C
10 READ (1,100,END=99) YEAR, ID, SPC, TREAT, SLOPE,
+ Y, X, GROWTH
100 FORMAT (2I5,A3,2A2,2I3,I6)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read asapling.dat ***/
data asapling ;
infile '/home/cdp/ndp078a/asapling.dat' ;
input YEAR 1-4 ID $5-12 SPC $ 13-15 TREAT $ 16-17 SLOPE $ 18-19 Y 20-22
X 23-25 GROWTH 26-32 ;
run ;
C *** Fortran program to read the NDP-078a file "asapling.dat"
C
INTEGER YEAR, Y, X
REAL GROWTH
CHARACTER ID*7, SPC*3, TREAT*2, SLOPE*2
C
OPEN (UNIT=1, FILE='asapling.dat')
C
10 READ (1,100,END=99) YEAR, ID, SPC, TREAT, SLOPE,
+ Y, X, GROWTH
100 FORMAT (I4,A8,A3,2A2,2I3,F7.3)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
/*** retrieval routine to read rellai.dat ***/ data rellai ; infile '/home/cdp/ndp078a/rellai.dat' ; input YEAR 1-5 DOY 6-9 RELLAI 10-15 ; run ;
C *** Fortran program to read the NDP-078a file "rellai.dat"
C
INTEGER YEAR, DOY
REAL RELLAI
C
OPEN (UNIT=1, FILE='rellai.dat')
C
10 READ (1,100,END=99) YEAR, DOY, RELLAI
100 FORMAT (I5,I4,F6.2)
C
GO TO 10
99 CLOSE (UNIT=1)
STOP
END
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