Simulations from four process-based ecosystem models describing primary productivity in a tallgrass prairie long-term irrigation experiment
Data files
Sep 18, 2023 version files 3.33 KB
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anpp_simulation_output_2023_09_11.csv
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README.md
Abstract
To demonstrate current capabilities in modeling herbaceous ecosystems, we selected four different process-based models that vary in their representation of community change from no community representation to vegetation demographic models. These models were used to simulate a long-term irrigation experiment at a US tallgrass prairie (Konza Prairie Biological Station) following a standardized simulation protocol. Specifically, we were interested in how model output under a monotonic increase in water availability matched up to experimental findings of (1) herbaceous plant community change and (2) aboveground net primary productivity before and after the plant community change. The results of this simulation are included here.
README: Irrigation simulation output
https://doi.org/10.5061/dryad.m37pvmd80
The data here describe empirical observations and output from four model simulations of a long-term irrigation experiment at Konza Prairie Biological Station near Manhattan, KS, USA.
Description of the data and file structure
ANPP data: There are three columns contained in the file: year=calendar year; anpp_gm2=aboveground net primary productivity including leaf, stem, and seed productivity in grams per meter squared per year; source=model name or empirical observation indicator.
Sharing/Access information
Links to other publicly accessible locations of the data:
- Raw empirical data can be obtained from the doi: 10.6073/pasta/3037d44d496df3d12fbe9668c7d618a6
Code/Software
na
Methods
To simulate the Konza irrigation experiment, we used meteorological forcing data, environmental information (e.g., soil texture), and functional traits for Andropogon gerardii and Panicum virgatum (collated from author measurements and TRY) to calibrate and operate four models from 1991-2012. The goal was to evaluate the models’ ability to simulate the community shift and accompanying changes in ANPP. For these simulations, two PFTs were parameterized based on empirical information about functional traits for A. gerardii and P. virgatum and models were tuned to match observations from non-irrigated plots (i.e., controls). This led to slightly different starting PFT abundances among models when irrigated simulations began.
The following protocol was used to run all models for model simulation exercise.
Spin up:
Spin-up to equilibrium (1000-2000 years) using standard spin-up from model. Plant functional type (PFT) is C4 grassland or similar cover type. Starting C and biomass pools should stabilize near values in Table A1.
Industrial period:
Run models from 1860 to 1990 with random annual draws from met data. Site is burned every 3 years at the beginning of the growing season through 1990 (very low mortality of grass individuals). PFT throughout industrial period is C4 grassland, dominant species is Andropogon gerardii (Table A1)
Model calibration:
Calibrate model using ambient ANPP, forcing, LAI, species relative cover (see Collins et al. 2012 for control data), soil moisture data, and additional site-level biotic and abiotic information (Table A1).
Simulation of irrigation experiment:
Run models in “site-mode.” Perform two simulations from 1991-2012: one with ambient precipitation forcing data, and one with irrigation forcing data.
Use historical CO2 and N deposition data within model.
Site is burned every year in March starting in 1991.
Soil moisture observations - Volumetric soil moisture was measured hourly from 2007-2012 from 0-15 cm in soil (integrated across this range). Data to be used during model calibration
Interspecific competition – If the model allows for competition, parameterize two species: A. gerardii and Panicum virgatum. A. gerardii is a [relatively] drought-tolerant perennial C4 grass. Under low water and nutrient conditions, A. gerardii is an excellent competitor for light, but competitive ability becomes weaker under higher levels of water and/or nitrogen. P. virgatum undergoes water stress under lower soil moisture conditions but is a strong competitor for light when water and nutrients are abundant. See Table A1 for species characteristics (below).
Outputs:
Please output daily values of the following variables (finer temporal resolution is better):
● NPP (g C m-2 d-1) - site level observations include reproductive biomass so please report NPP or biomass increment+reproductive biomass
● Stem growth (g C m-2 d-1)
● Leaf growth (g C m-2 d-1)
● Root growth (g C m-2 d-1)
● PhenoGrass: LAI
● fAPAR
● If model includes sources of biomass not captured in NPP observations, output these components (g C m-2 d-1)
○ e.g., root exudates, root turnover, reproductive biomass
● Emissions from fire (g C m-2 d-1)
● GPP (g C m-2 d-1)
● NEE (g C m-2 d-1)
● Autotrophic respiration (g C m-2 d-1)
● Transpiration (mm H20 d-1)
● Runoff (mm H20 d-1)
● Deep and shallow soil moisture (%; 0-15 cm and >15 cm). Soil moisture observations integrated from 0-15 cm.
Table A1. Values used for parameterizing models.
Variable |
units |
value |
source comments |
latitude |
degrees N |
39.11 |
|
longitude |
degrees E |
-96.61 |
|
elevation |
m |
311 |
|
met var measurement height |
m |
3 |
|
experiment start |
year |
1991 |
|
experiment end |
year |
2012 |
|
|
|
|
|
Site history |
|
|
|
landuse history – plant cover |
na |
tallgrass prairie, burned annually starting in 1991 |
|
(additional rows for land use history – add as necessary) |
na |
na |
|
|
na |
na |
|
landuse history – fertiliser addition |
na |
none |
|
disturbance history – fire |
na |
Annual spring burns 1991-present |
|
|
na |
pre 1991, site burned every three years |
|
|
na |
|
|
disturbance history – hurricane/severe wind event |
na |
|
|
planting date |
na |
na |
|
grazing |
|
none |
|
|
|
|
|
Site initialisation |
|
|
|
PFT |
na |
C4 grassland |
|
PFT cover |
% |
100 |
|
tree age at beginning of experiment |
years |
0 |
|
vertical structure |
na |
Both Andropogon gerardii and Panicum virgatum are tall "canopy" species |
|
planting density |
Individuals m-2 |
na |
|
stand density at start of experiment |
Individuals m-2 |
51.5 |
# of dominant grass individuals per m2 in control plots in 1992 |
Mean (sd) dbh of each stem at start of experiment (m2 ha-1) |
cm |
no data |
|
Dates of harvesting during experiment |
na |
September |
|
Leaf (& non-woody shoot) biomass C |
g m-2 |
148 |
|
Wood biomass C (inc. coarse roots) |
g m-2 |
0 |
|
Fine root biomass C |
g m-2 |
419.3 |
from soil cores 0-30 cm, Wilcox et al. 2016 JGR |
Leaf (& non-woody shoot) biomass N |
g m-2 |
3.18936 |
0.97% N leaf biomass times aboveground biomass from Wilcox et al. 2016 JGR; 328.8 ANPP * 0.0097 |
Wood biomass N (inc. coarse roots) |
g m-2 |
0 |
|
Fine root biomass N |
g m-2 |
7.26882 |
0.78% N leaf biomass times fine root biomass from Wilcox et al. 2016 JGR; 931.9 ANPP * 0.0078 |
coarse woody debris C |
g m-2 |
0 |
|
soil C |
g m-2 |
9000 |
total C from 0-25 cm |
soil C |
g m-2 |
450 |
Active C - 5% of total |
soil C |
g m-2 |
5344 |
Slow C - 60% of total |
soil C |
g m-2 |
3206 |
Passive C - 35% of total |
soil N |
g m-2 |
625 |
Total N 0-25 cm |
soil N |
g m-2 |
155 |
Total N 0-5 cm |
|
g m-2 |
|
|
|
g m-2 |
|
|
Root mass in top 10 cm |
% |
52 |
Used exponential decay function for grass PFT. Jackson et al. 1996. |
Root mass in 10-20 cm |
% |
24 |
Used exponential decay function for grass PFT. Jackson et al. 1996. |
Root mass in 20-35 cm |
% |
11 |
Used exponential decay function for grass PFT. Jackson et al. 1996. |
Root mass in 35-50 cm |
% |
6 |
Used exponential decay function for grass PFT. Jackson et al. 1996. |
Root mass in 50-75 cm |
% |
4 |
Used exponential decay function for grass PFT. Jackson et al. 1996. |
Root mass in 75-100 cm |
% |
2 |
Used exponential decay function for grass PFT. Jackson et al. 1996. |
Root mass below 100 cm |
% |
1 |
Used exponential decay function for grass PFT. Jackson et al. 1996. |
root:shoot in control plots |
na |
1.1 |
From BNPP:ANPP measurements in Wilcox et al. 2016 JGR |
root:shoot in irrigated plots |
na |
0.91 |
From BNPP:ANPP measurements in Wilcox et al. 2016 JGR |
|
|
|
|
|
|
|
|
Soil properties |
|
|
|
Field capacity |
% volumetric |
35 |
Derived from soil moisture data within the experiment. Data can be found here: 10.6073/pasta/3037d44d496df3d12fbe9668c7d618a6 |
Wilting point |
% volumetric |
12 |
Derived from soil moisture data within the experiment. Data can be found here: 10.6073/pasta/3037d44d496df3d12fbe9668c7d618a6 |
Bulk Density |
g cm-1 |
1.01 |
|
Sand content |
% |
7.1 |
average of A1,2,3 horizons, 0-32 cm depth, Tuttle soils from Knapp et al. 1998 (grassland dynamics book) - |
Silt content |
% |
50.1 |
average of A1,2,3 horizons, 0-32 cm depth, Tuttle soils from Knapp et al. 1998 (grassland dynamics book) - |
Clay content |
% |
42.8 |
average of A1,2,3 horizons, 0-32 cm depth, Tuttle soils from Knapp et al. 1998 (grassland dynamics book) - |
|
|
|
|
sd – standard deviation |
|
|
|
Temp BlDc – temperate broadleaf deciduous |
|
|
|
|
|
|
|
Species level information |
|
|
|
Andropogon gerardii |
|
|
|
Vcmax,25 |
micromol CO2 m-2 s-1 |
34 |
|
Amax |
micromol CO2 m-2 s-1 |
21.6 |
|
Proportion roots in top 50 cm |
% |
93 |
based on exponential decay function |
Proportion individuals surviving fire |
% |
99 |
|
Water stress threshold for leaf abscission |
%AWC |
Operates better under low soil moisture than P. virgatum |
|
Stomatal conductance |
milli mol m-2 s-1 |
136 |
|
Specific leaf area |
mm2 mg-1 |
15.7 |
KW replaced the TRY number (19.6) with one calculated from data from Konza prairie (wilcox, unpublished) |
Rooting depth |
m |
0.508 |
|
Leaf nitrogen (N) content per leaf area |
g m-2 |
0.625 |
|
Leaf nitrogen (N) content per leaf dry mass |
mg/g |
10.86633 |
|
root:shoot (BNPP:ANPP) |
- |
1.1 |
BNPP:ANPP in A. gerardii dominated control plots. Data from Wilcox et al. 2016 JGR Biogeosciences |
Reproductive effort |
% of total plant biomass that is flowering stock |
10.7 |
From Knapp 1984; Also, A. gerardii typically reproduces clonally |
Root turnover |
% year-1 |
50 |
based on relationships between A. gerardii cover and root turnover - estimated root turnover at 100% A.gerardii cover from trendline. Data from Wilcox et al. 2016 JGR Biogeosciences |
Max leaf height |
cm |
74 |
Does not include flowering stalks; Wilcox unpublished data |
|
|
|
|
Panicum virgatum |
|
|
|
Vcmax,25 |
micromol CO2 m-2 s-1 |
34 |
|
Amax |
micromol CO2 m-2 s-1 |
31.7 |
|
Proportion roots in top 50 cm |
% |
93 |
|
Proportion individuals surviving fire |
% |
99 |
|
Water stress threshold for leaf abscission |
%AWC |
Operates worse under low soil moisture than A. gerardii |
|
Stomatal conductance |
milli mol m-2 s-1 |
304 |
|
Specific leaf area |
mm2 mg-1 |
22.90292 |
|
Rooting depth |
m |
0.3048 |
|
Leaf nitrogen (N) content per leaf area |
g m-2 |
0.88284 |
|
Leaf nitrogen (N) content per leaf dry mass |
mg/g |
17.22296 |
|
root:shoot (BNPP:ANPP) |
- |
0.72 |
based on relationships between P. virgatum cover and root:shoot - estimated root:shoot at 100% P.virgatum cover from trendline. Data from Wilcox et al. 2016 JGR Biogeosciences |
Reproductive effort |
% of total plant biomass that is flowering stock |
28.6 |
From Knapp 1984; Also, P. virgatum typically reproduces clonally |
Root turnover |
% year-1 |
30.9 |
based on relationships between P. virgatum cover and root turnover - estimated root turnover at 100% P.virgatum cover from trendline. Data from Wilcox et al. 2016 JGR Biogeosciences |
Max leaf height |
cm |
88 |
Does not include flowering stalks; Wilcox unpublished data |
Table A2. Forcing units used to drive models
Variable |
Unit and derivation |
Air temperature |
degC |
Soil temperature |
degC |
Relative humidity |
Percentage of the saturated vapor partial pressure |
VPD: VDEF, |
Pa (calculated from saturation vapor pressure (es): 0.6108* exp(17.27*T/(T+237.3)) and actual vapor pressure: RH/100*es. VPD=es-ea) |
Precipitation |
mm/hour |
Solar radiation |
W/m2
|
Wind speed
|
m/s |
References cited:
Knapp, A.K., Briggs, J.M., Hartnett, D.C. and Collins, S.L. eds., 1998. Grassland dynamics: long-term ecological research in tallgrass prairie. New York: Oxford University Press.
Jackson, R.B., Canadell, J., Ehleringer, J.R., Mooney, H.A., Sala, O.E. and Schulze, E.D., 1996. A global analysis of root distributions for terrestrial biomes. Oecologia, 108, pp.389-411.
Wilcox, K.R., Blair, J.M. and Knapp, A.K., 2016. Stability of grassland soil C and N pools despite 25 years of an extreme climatic and disturbance regime. Journal of Geophysical Research: Biogeosciences, 121(7), pp.1934-1945.