fitaci: Fit the Farquhar-Berry-von Caemmerer model of leaf...

Description Usage Arguments Details Value References Examples

View source: R/fitaci.R

Description

Fits the Farquhar-Berry-von Caemmerer model of photosynthesis to measurements of photosynthesis and intercellular CO2 concentration (Ci). Estimates Jmax, Vcmax, Rd and their standard errors. A simple plotting method is also included, as well as the function fitacis which quickly fits multiple A-Ci curves (see its help page). Temperature dependencies of the parameters are taken into account following Medlyn et al. (2002), see Photosyn for more details.

Usage

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fitaci(data, varnames = list(ALEAF = "Photo", Tleaf = "Tleaf", Ci = "Ci", PPFD
  = "PARi", Rd = "Rd"), Tcorrect = TRUE, Patm = 100, citransition = NULL,
  quiet = FALSE, startValgrid = TRUE, fitmethod = c("default", "bilinear",
  "onepoint"), algorithm = "default", fitTPU = FALSE, alphag = 0,
  useRd = FALSE, PPFD = NULL, Tleaf = NULL, alpha = 0.24,
  theta = 0.85, gmeso = NULL, EaV = 82620.87, EdVC = 0,
  delsC = 645.1013, EaJ = 39676.89, EdVJ = 2e+05, delsJ = 641.3615,
  GammaStar = NULL, Km = NULL, id = NULL, ...)

## S3 method for class 'acifit'
plot(x, what = c("data", "model", "none"), xlim = NULL,
  ylim = NULL, whichA = c("Ac", "Aj", "Amin", "Ap"), add = FALSE,
  pch = 19, addzeroline = TRUE, addlegend = !add, legendbty = "o",
  transitionpoint = TRUE, linecols = c("black", "blue", "red"), lwd = c(1,
  2), ...)

Arguments

data

Dataframe with Ci, Photo, Tleaf, PPFD (the last two are optional). For fitacis, also requires a grouping variable.

varnames

List of names of variables in the dataset (see Details).

Tcorrect

If TRUE, Vcmax and Jmax are corrected to 25C. Otherwise, Vcmax and Jmax are estimated at measurement temperature.

Patm

Atmospheric pressure (kPa)

citransition

If provided, fits the Vcmax and Jmax limited regions separately (see Details).

quiet

If TRUE, no messages are written to the screen.

startValgrid

If TRUE (the default), uses a fine grid of starting values to increase the chance of finding a solution.

fitmethod

Method to fit the A-Ci curve. Either 'default' (Duursma 2015), 'bilinear' (See Details), or 'onepoint' (De Kauwe et al. 2016).

algorithm

Passed to nls, sets the algorithm for finding parameter values.

fitTPU

Logical (default FALSE). Attempt to fit TPU limitation (fitmethod set to 'bilinear' automatically if used). See Details.

alphag

When estimating TPU limitation (with fitTPU), an additional parameter (see Details).

useRd

If Rd provided in data, and useRd=TRUE (default is FALSE), uses measured Rd in fit. Otherwise it is estimated from the fit to the A-Ci curve.

PPFD

Photosynthetic photon flux density ('PAR') (mu mol m-2 s-1)

Tleaf

Leaf temperature (degrees C)

alpha

Quantum yield of electron transport (mol mol-1)

theta

Shape of light response curve.

gmeso

Mesophyll conductance (mol m-2 s-1 bar-1). If not NULL (the default), Vcmax and Jmax are chloroplastic rates.

EaV, EdVC, delsC

Vcmax temperature response parameters

EaJ, EdVJ, delsJ

Jmax temperature response parameters

Km, GammaStar

Optionally, provide Michaelis-Menten coefficient for Farquhar model, and Gammastar. If not provided, they are calculated with a built-in function of leaf temperature.

id

Names of variables (quoted, can be a vector) in the original dataset to be stored in the result. Most useful when using fitacis, see there for examples of its use.

...

Further arguments (ignored at the moment).

x

For plot.acifit, an object returned by fitaci

what

The default is to plot both the data and the model fit, or specify 'data' or 'model' to plot one of them, or 'none' for neither (only the plot region is set up)

xlim

Limits for the X axis, if left blank estimated from data

ylim

Limits for the Y axis, if left blank estimated from data

whichA

By default all photosynthetic rates are plotted (Aj=Jmax-limited (blue), Ac=Vcmax-limited (red), Hyperbolic minimum (black)), TPU-limited rate (Ap, if estimated in the fit). Or, specify one or two of them.

add

If TRUE, adds to the current plot

pch

The plotting symbol for the data

addzeroline

If TRUE, the default, adds a dashed line at y=0

addlegend

If TRUE, adds a legend (by default does not add a legend if add=TRUE)

legendbty

Box type for the legend, passed to argument bty in legend.

transitionpoint

For plot.acifit, whether to plot a symbol at the transition point.

linecols

Vector of three colours for the lines (limiting rate, Ac, Aj), if one value provided it is used for all three.

lwd

Line widths, can be a vector of length 2 (first element for Ac and Aj, second one for the limiting rate).

Details

Fitting method

The default method to fit A-Ci curves (set by fitmethod="default") uses non-linear regression to fit the A-Ci curve. No assumptions are made on which part of the curve is Vcmax or Jmax limited. Normally, all three parameters are estimated: Jmax, Vcmax and Rd, unless Rd is provided as measured (when useRd=TRUE, and Rd is contained in the data). This is the method as described by Duursma (2015, Plos One).

The 'bilinear' method to fit A-Ci curves (set by fitmethod="bilinear") linearizes the Vcmax and Jmax-limited regions, and applies linear regression twice to estimate first Vcmax and Rd, and then Jmax (using Rd estimated from the Vcmax-limited region). The transition point is found as the one which gives the best overall fit to the data (i.e. all possible transitions are tried out, similar to Gu et al. 2010, PCE). The advantage of this method is that it always returns parameter estimates, so it should be used in cases where the default method fails. Be aware, though, that the default method fails mostly when the curve contains bad data (so check your data before believing the fitted parameters).

When citransition is set, it splits the data into a Vcmax-limited (where Ci < citransition), and Jmax-limited region (Ci > citransition). Both parameters are then estimated separately for each region (Rd is estimated only for the Vcmax-limited region). Note that the actual transition point as shown in the standard plot of the fitted A-Ci curve may be quite different from that provided, since the fitting method simply decides which part of the dataset to use for which limitation, it does not constrain the actual estimated transition point directly. See the example below. If fitmethod="default", it applies non-linear regression to both parts of the data, and when fitmethod="bilinear", it uses linear regression on the linearized photosynthesis rate. Results will differ between the two methods (slightly).

The 'onepoint' fitting method is a very simple estimation of Vcmax and Jmax for every point in the dataset, simply by inverting the photosynthesis equation. See De Kauwe et al. (2016) for details. The output will give the original data with Vcmax and Jmax added (note you can set Tcorrect as usual!). For increased reliability, this method only works if dark respiration (Rd) is included in the data (useRd is set automatically when setting fitmethod='one-point'). This method is not recommended for full A-Ci curves, but rather for spot gas exchange measurements, when a simple estimate of Vcmax or Jmax is needed, for example when separating stomatal and non-stomatal drought effects on photosynthesis (Zhou et al. 2013, AgForMet). The user will have to decide whether the Vcmax or Jmax rates are used in further analyses. This fitting method can not be used in fitacis, because Vcmax and Jmax are already estimated for each point in the dataset.

TPU limitation

Optionally, the fitaci function estimates the triose-phosphate utilization (TPU) rate. The TPU can act as another limitation on photosynthesis, and can be recognized by a 'flattening out' of the A-Ci curve at high Ci. When fitTPU=TRUE, the fitting method used will always be 'bilinear'. The TPU is estimated by trying out whether the fit improves when the last n points of the curve are TPU-limited (where n=1,2,...). When TPU is estimated, it is possible (though rare) that no points are Jmax-limited (in which case estimated Jmax will be NA). A minimum of two points is always reserved for the estimate of Vcmax and Rd. An additional parameter (alphag) can be set that affects the behaviour at high Ci (see Ellsworth et al. 2015 for details, and also Photosyn). See examples.

Temperature correction

When Tcorrect=TRUE (the default), Jmax and Vcmax are re-scaled to 25C, using the temperature response parameters provided (but Rd is always at measurement temperature). When Tcorrect=FALSE, estimates of all parameters are at measurement temperature. If TPU is fit, it is never corrected for temperature. Important parameters to the fit are GammaStar and Km, both of which are calculated from leaf temperature using standard formulations. Alternatively, they can be provided as known inputs.

Mesophyll conductance

It is possible to provide an estimate of the mesophyll conductance as input (gmeso), in which case the fitted Vcmax and Jmax are to be interpreted as chloroplastic rates. When using gmeso, it is recommended to use the 'default' fitting method (which will use the Ethier&Livingston equations inside Photosyn). It is also implemented with the 'bilinear' method but it requires more testing (and seems to give some strange results). When gmeso is set to a relatively low value, the resulting fit may be quite strange.

Other parameters

The A-Ci curve parameters depend on the values of a number of other parameters. For Jmax, PPFD is needed in order to express it as the asymptote. If PPFD is not provided in the dataset, it is assumed to equal 1800 mu mol m-2 s-1 (in which case a warning is printed). It is possible to either provide PPFD as a variable in the dataset (with the default name 'PARi', which can be changed), or as an argument to the fitaci directly.

Plotting and summarizing

The default plot of the fit is constructed with plot.acifit, see Examples below. When plotting the fit, the A-Ci curve is simulated using the Aci function, with leaf temperature (Tleaf) and PPFD set to the mean value for the dataset. The coefficients estimated in the fit (Vcmax, Jmax, and usually Rd) are extracted with coef. The summary of the fit is the same as the 'print' method, that is myfit will give the same output as summary(myfit) (where myfit is an object returned by fitaci).

Because fitaci returns the fitted nls object, more details on statistics of the fit can be extracted with standard tools. The Examples below shows the use of the nlstools to extract many details of the fit at once. The fit also includes the root mean squared error (RMSE), which can be extracted as myfit$RMSE. This is a useful metric to compare the different fitting methods.

Atmospheric pressure correction

Note that atmospheric pressure (Patm) is taken into account, assuming the original data are in molar units (Ci in mu mol mol-1, or ppm). During the fit, Ci is converted to mu bar, and Km and Gammastar are recalculated accounting for the effects of Patm on the partial pressure of oxygen. When plotting the fit, though, molar units are shown on the X-axis. Thus, you should get (nearly) the same fitted curve when Patm was set to a value lower than 100kPa, but the fitted Vcmax and Jmax will be higher. This is because at low Patm, photosynthetic capacity has to be higher to achieve the same measured photosynthesis rate.

Value

A list of class 'acifit', with the following components:

df

A dataframe with the original data, including the measured photosynthetic rate (Ameas), the fitted photosynthetic rate (Amodel), Jmax and Vcmax-limited gross rates (Aj, Ac), TPU-limited rate (Ap), dark respiration (Rd), leaf temperature (Tleaf), chloroplastic CO2 (Cc), PPFD, atmospheric pressure (Patm), and 'original Ci, i.e. the Ci used as input (which is different from the Ci used in fitting if Patm was not set to 100kPa)

pars

Contains the parameter estimates and their approximate standard errors

nlsfit

The object returned by nls, and contains more detail on the quality of the fit

Tcorrect

whether the temperature correction was applied (logical)

Photosyn

A copy of the Photosyn function with the arguments adjusted for the current fit. That is, Vcmax, Jmax and Rd are set to those estimated in the fit, and Tleaf and PPFD are set to the mean value in the dataset. All other parameters that were set in fitaci are also used (e.g. temperature dependency parameters, TPU, etc.).

Ci_transition

The Ci at which photosynthesis transitions from Vcmax to Jmax limited photosynthesis.

Rd_measured

Logical - was Rd provided as measured input?

GammaStar

The value for GammaStar, either calculated or provided to the fit.

Km

he value for Km, either calculated or provided to the fit.

kminput

Was Km provided as input? (If FALSE, it was calculated from Tleaf)

gstarinput

Was GammaStar provided as input? (If FALSE, it was calculated from Tleaf)

fitmethod

The fitmethod uses, either default or bilinear

citransition

The input citransition (NA if it was not provided as input)

gmeso

The mesophyll conductance used in the fit (NA if it was not set)

fitTPU

Was TPU fit?

alphag

The value of alphag used in estimating TPU.

RMSE

The Root-mean squared error, calculated as sqrt(sum((Ameas-Amodel)^2)).

runorder

The data returned in the 'df' slot are ordered by Ci, but in rare cases the original order of the data contains information; 'runorder' is the order in which the data were provided.

References

Duursma, R.A., 2015. Plantecophys - An R Package for Analysing and Modelling Leaf Gas Exchange Data. PLoS ONE 10, e0143346. doi:10.1371/journal.pone.0143346

De Kauwe, M. G. et al. 2016. A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis. New Phytol 210, 1130-1144.

Examples

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## Not run: 
# Fit an A-Ci curve on a dataframe that contains Ci, Photo and optionally Tleaf and PPFD. 
# Here, we use the built-in example dataset 'acidata1'.
f <- fitaci(acidata1)

# Note that the default behaviour is to correct Vcmax and Jmax for temperature, 
# so the estimated values are at 25C. To turn this off:
f2 <- fitaci(acidata1, Tcorrect=FALSE)

# To use different T response parameters (see ?Photosyn),
f3 <- fitaci(acidata1, Tcorrect=TRUE, EaV=25000)

# Make a standard plot
plot(f)

# Look at a summary of the fit
summary(f)

# Extract coefficients only
coef(f)

# The object 'f' also contains the original data with predictions.
# Here, Amodel are the modelled (fitted) values, Ameas are the measured values.
with(f$df, plot(Amodel, Ameas))
abline(0,1)

# The fitted values can also be extracted with the fitted() function:
fitted(f)

# The non-linear regression (nls) fit is stored as well,
summary(f$nlsfit)

# Many more details can be extracted with the nlstools package
library(nlstools)
overview(f$nlsfit)
 
# The curve generator is stored as f$Photosyn:
# Calculate photosynthesis at some value for Ci, using estimated 
# parameters and mean Tleaf, PPFD for the dataset.
f$Photosyn(Ci=820)

# Photosynthetic rate at the transition point:
f$Photosyn(Ci=f$Ci_transition)$ALEAF

# Set the transition point; this will fit Vcmax and Jmax separately. Note that the *actual* 
# transition is quite different from that provided, this is perfectly fine : 
# in this case Jmax is estimated from the latter 3 points only (Ci>800), but the actual 
# transition point is at ca. 400ppm.
g <- fitaci(acidata1, citransition=800)
plot(g)
g$Ci_transition

# Use measured Rd instead of estimating it from the A-Ci curve. 
# The Rd measurement must be added to the dataset used in fitting, 
# and you must set useRd=TRUE.
acidata1$Rd <- 2
f2 <- fitaci(acidata1, useRd=TRUE)
f2

# Fit TPU limitation
ftpu <- fitaci(acidata1, fitTPU=TRUE, PPFD=1800, Tcorrect=TRUE)
plot(ftpu)

## End(Not run)

Example output

Result of fitaci.

Data and predictions:
           Ci      Ameas     Amodel         Ac        Aj   Ap       Rd VPD
1    72.81690 -0.6656991 -0.7314466  0.6051439  1.233113 1000 1.336532 1.5
2    89.33801  0.6089389  0.5060336  1.8427690  3.513935 1000 1.336532 1.5
3   119.73218  2.4030110  2.7087379  4.0458397  6.918011 1000 1.336532 1.5
4   163.84422  5.5908708  5.7507507  7.0887147 10.595421 1000 1.336532 1.5
5   219.61709  9.2532753  9.3634028 10.7035076 13.904585 1000 1.336532 1.5
6   259.24215 12.0213403 11.7820610 13.1252962 15.686054 1000 1.336532 1.5
7   416.48659 19.3715508 18.8005066 21.7607066 20.162013 3000 1.336532 1.5
8   861.70294 24.0843514 23.8113156 39.8882084 25.152138 3000 1.336532 1.5
9  1105.20222 24.7927750 25.0045538 47.2964660 26.344397 3000 1.336532 1.5
10 1356.10582 25.3376665 25.8021657 53.9109485 27.141449 3000 1.336532 1.5
      Tleaf         Cc PPFD Patm Ci_original
1  33.36515   72.81616 1800  100    72.81690
2  33.34065   89.33852 1800  100    89.33801
3  33.31123  119.73489 1800  100   119.73218
4  33.29358  163.84998 1800  100   163.84422
5  33.29326  219.62646 1800  100   219.61709
6  33.27833  259.25394 1800  100   259.24215
7  33.32764  416.50541 1800  100   416.48659
8  33.35583  861.72678 1800  100   861.70294
9  33.42005 1105.22725 1800  100  1105.20222
10 33.55434 1356.13165 1800  100  1356.10582

Root mean squared error:  0.9298254 

Estimated parameters:
        Estimate Std. Error
Vcmax  46.846621  1.4748353
Jmax  105.239159  1.3586480
Rd      1.336532  0.2413795
Note: Vcmax, Jmax are at 25C, Rd is at measurement T.

Curve was fit using method:  default 

Parameter settings:
Patm = 100
 alpha = 0.24
 theta = 0.85
 EaV = 82620.87
 EdVC = 0
 delsC = 645.1013
 EaJ = 39676.89
 EdVJ = 2e+05
 delsJ = 641.3615

Estimated from Tleaf (shown at mean Tleaf):
GammaStar =  64.80184 
Km =  1460.068 
     Vcmax       Jmax         Rd 
 46.846621 105.239159   1.336532 
 [1] -0.7314466  0.5060336  2.7087379  5.7507507  9.3634028 11.7820610
 [7] 18.8005066 23.8113156 25.0045538 25.8021657

Formula: ALEAF ~ acifun_wrap(Ci, PPFD = PPFD, Vcmax = Vcmax, Jmax = Jmax, 
    Rd = Rd, Tleaf = Tleaf, Patm = Patm, TcorrectVJ = Tcorrect, 
    alpha = alpha, theta = theta, gmeso = gmeso, EaV = EaV, EdVC = EdVC, 
    delsC = delsC, EaJ = EaJ, EdVJ = EdVJ, delsJ = delsJ, Km = Km, 
    GammaStar = GammaStar)

Parameters:
      Estimate Std. Error t value Pr(>|t|)    
Vcmax  46.8466     1.4748  31.764 7.92e-09 ***
Jmax  105.2392     1.3586  77.459 1.57e-11 ***
Rd      1.3365     0.2414   5.537 0.000872 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.3514 on 7 degrees of freedom

Number of iterations to convergence: 3 
Achieved convergence tolerance: 1.714e-06


'nlstools' has been loaded.

IMPORTANT NOTICE: Most nonlinear regression models and data set examples
related to predictive microbiolgy have been moved to the package 'nlsMicrobio'


------
Formula: ALEAF ~ acifun_wrap(Ci, PPFD = PPFD, Vcmax = Vcmax, Jmax = Jmax, 
    Rd = Rd, Tleaf = Tleaf, Patm = Patm, TcorrectVJ = Tcorrect, 
    alpha = alpha, theta = theta, gmeso = gmeso, EaV = EaV, EdVC = EdVC, 
    delsC = delsC, EaJ = EaJ, EdVJ = EdVJ, delsJ = delsJ, Km = Km, 
    GammaStar = GammaStar)

Parameters:
      Estimate Std. Error t value Pr(>|t|)    
Vcmax  46.8466     1.4748  31.764 7.92e-09 ***
Jmax  105.2392     1.3586  77.459 1.57e-11 ***
Rd      1.3365     0.2414   5.537 0.000872 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.3514 on 7 degrees of freedom

Number of iterations to convergence: 3 
Achieved convergence tolerance: 1.714e-06

------
Residual sum of squares: 0.865 

------
t-based confidence interval:
             2.5%      97.5%
Vcmax  43.3591894  50.334052
Jmax  102.0264667 108.451851
Rd      0.7657604   1.907304

------
Correlation matrix:
          Vcmax      Jmax        Rd
Vcmax 1.0000000 0.6452788 0.8059230
Jmax  0.6452788 1.0000000 0.8043562
Rd    0.8059230 0.8043562 1.0000000

   Ci    ALEAF GS ELEAF       Ac       Aj   Ap       Rd VPD    Tleaf  Ca
1 820 23.54216  0     0 38.48885 24.88324 3000 1.336532 1.5 33.35401 400
        Cc PPFD Patm
1 820.0236 1800  100
[1] 17.35755
[1] 382.6943
Result of fitaci.

Data and predictions:
           Ci      Ameas      Amodel         Ac        Aj   Ap Rd VPD    Tleaf
1    72.81690 -0.6656991 -1.35292721  0.6471405  1.265786 1000  2 1.5 33.36515
2    89.33801  0.6089389 -0.02958141  1.9706558  3.607041 1000  2 1.5 33.34065
3   119.73218  2.4030110  2.32594382  4.3266181  7.101311 1000  2 1.5 33.31123
4   163.84422  5.5908708  5.57892434  7.5806664 10.876157 1000  2 1.5 33.29358
5   219.61709  9.2532753  9.44169960 11.4463234 14.273001 1000  2 1.5 33.29326
6   259.24215 12.0213403 12.02670039 14.0361824 16.101670 1000  2 1.5 33.27833
7   416.48659 19.3715508 18.67972602 23.2708841 20.696230 3000  2 1.5 33.32764
8   861.70294 24.0843514 23.81462284 42.6564214 25.818580 3000  2 1.5 33.35583
9  1105.20222 24.7927750 25.03933790 50.5788068 27.042444 3000  2 1.5 33.42005
10 1356.10582 25.3376665 25.85805505 57.6523296 27.860660 3000  2 1.5 33.55434
           Cc PPFD Patm Ci_original
1    72.81554 1800  100    72.81690
2    89.33798 1800  100    89.33801
3   119.73451 1800  100   119.73218
4   163.84981 1800  100   163.84422
5   219.62654 1800  100   219.61709
6   259.25419 1800  100   259.24215
7   416.50529 1800  100   416.48659
8   861.72678 1800  100   861.70294
9  1105.22728 1800  100  1105.20222
10 1356.13171 1800  100  1356.10582

Root mean squared error:  1.343346 

Estimated parameters:
       Estimate Std. Error
Vcmax  50.09774   1.181665
Jmax  108.26249   1.095321
Rd      2.00000         NA
Note: Vcmax, Jmax are at 25C, Rd is at measurement T.
Note: measured Rd was provided, only Vcmax and Jmax were fit.

Curve was fit using method:  default 

Parameter settings:
Patm = 100
 alpha = 0.24
 theta = 0.85
 EaV = 82620.87
 EdVC = 0
 delsC = 645.1013
 EaJ = 39676.89
 EdVJ = 2e+05
 delsJ = 641.3615

Estimated from Tleaf (shown at mean Tleaf):
GammaStar =  64.80184 
Km =  1460.068 
Rd found in dataset but useRd set to FALSE. Set to TRUE to use measured Rd.

plantecophys documentation built on Nov. 29, 2017, 1 a.m.