diff --git a/articles/evaluation/RegionalLevelEvaluation.html b/articles/evaluation/RegionalLevelEvaluation.html index a9fdee1eb..e89c978a2 100644 --- a/articles/evaluation/RegionalLevelEvaluation.html +++ b/articles/evaluation/RegionalLevelEvaluation.html @@ -75,7 +75,7 @@

Evaluation of regional-level forest dynamics

Miquel De Cáceres

-

2024-02-16

+

2024-02-18

Source: vignettes/evaluation/RegionalLevelEvaluation.Rmd diff --git a/articles/evaluation/StandLevelEvaluation.html b/articles/evaluation/StandLevelEvaluation.html index cf88267fc..f0995be66 100644 --- a/articles/evaluation/StandLevelEvaluation.html +++ b/articles/evaluation/StandLevelEvaluation.html @@ -73,7 +73,7 @@

Stand-level evaluation

Miquel De Cáceres

-

2024-02-16

+

2024-02-18

Source: vignettes/evaluation/StandLevelEvaluation.Rmd @@ -83,25 +83,27 @@

2024-02-16

-

Evaluation summaries +

PRADES

Soil moisture

- +
--+++--++ - + + @@ -114,81 +116,65 @@

Soil moisture

+ - - - - - - - + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + - - - - - - - - - + + + + + + + + + +
SiteMode n Bias Bias.relPRADESgranier 363-0.0161740-2.5343440.172762127.070480.73955540.47164690.26683740.185402629.0511460.223595835.035720.82633290.25123930.0511112
FRAPUE10120.097652313.4254260.143608519.743580.65965540.06158710.1804707
FONBLA0NaNNaNNaNNaNNANaNNaN
ESPALTARM10130.249711447.3654440.299261456.764130.75969150.11317050.0494851PRADESsperry363-0.0332228-5.2057540.148784423.313360.79995890.56011360.3685932
CANBALASC6760.140955220.0659160.287884240.982250.4564628-1.4991092-0.8602195PRADEScochard3630.106323416.6600490.136883521.448580.91240630.66832080.4190980
+

Plant transpiration

--+++----++++ - - + + + @@ -201,183 +187,108 @@

Plant transpiration

+ - - - - - - - + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + - - - - - - - - - - + + + + + + + + + + + - - - - - - - - - - + + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + +
plotcohortSiteModeCohort n Bias Bias.relPRADESgranier T1_153 3624.970070e-0223.946051.263509e-0160.876580.71708300.46400030.30186310.195883494.377690.2189727105.502260.5941152-1.4280751-0.2099073
PRADESgranier T2_168 253-7.239790e-02-37.763541.280982e-0166.817390.72630490.20931760.2134702
FRAPUET1_1681087-7.775850e-02-22.659602.252976e-0165.653990.6795413-0.7490764-0.2428823
FRAPUES1_280NaNNaNNaNNaNNANaNNaN
FONBLAT2_1480NaNNaNNaNNaNNANaNNaN
FONBLAT3_1680NaNNaNNaNNaNNANaNNaN-0.0312491-16.299860.089023246.435460.79676870.58806490.4533928
ESPALTARMT1_149924-5.060310e+04-99.999235.060310e+0499.999230.5869532-1.0085165-0.2119491
ESPALTARMT2_166805-3.539346e+04-99.998123.539346e+0499.998120.8208423-2.1428579-0.7402761
ESPALTARMT3_168943-5.504353e+04-99.998365.504353e+0499.998360.7399129-1.4866486-0.4947086PRADESsperryT1_153362-0.1124989-54.202580.130289362.774130.70663690.23599290.2801019
CANBALASCT1_19644-2.738551e-01-92.132272.738551e-0192.132270.4720402-2.3981351-0.9427867PRADESsperryT2_1682530.045097123.523120.166930487.072660.7018740-0.6430119-0.0249612
CANBALASCT2_1486112.018411e-0177.672953.756301e-01144.55082-0.2513688-9.4982076-1.8064229PRADEScochardT1_1533620.025071412.079550.141518468.184330.8039801-0.32315490.2180572
CANBALASCT3_171644-1.970242e-01-68.052622.243218e-0177.481270.5893409-0.5650410-0.2256941
CANBALASCT4_168679-2.396049e-01-56.461473.389610e-0179.874140.4795248-2.2547397-0.8259434PRADEScochardT2_1682530.054267328.306390.092764548.386940.86110900.50970860.4304212
+

-

Leaf water potentials +

Water potentials

- +
------+++++++ - - + + + @@ -391,332 +302,142 @@

Leaf water potentials

+ - - - - - - - - - - - - - - + - - - - + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + - - + + + - - - - - - - + + + + + + + + - + + + + + + + + + + + + + + + - - - - + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + - - - - - - - - - - - - - - - + + - - - - - - - - - - - + + + + + + + + + + + + - - - - - - - - - - - + + + + + + + + + + + +
plotcohortSiteModeCohort WP n Bias
PRADESsperry T1_153Midday potentials4-0.1977309-10.6446020.363684219.57850-0.4154639-1.6858419-0.7962793
PRADEST2_168Midday potentialsPredawn 1-1.2463547-59.7567321.246354759.75673-1.2864859-145.984211.2864859145.98421 NA -Inf -Inf
FRAPUET1_168Midday potentials16-0.3411775-12.1449260.546076019.438710.8099563-0.6259606-0.0993666
FONBLAT2_148Midday potentials0NaNNaNNaNNaNNANaNNaN
FONBLAT3_168Midday potentials0NaNNaNNaNNaNPRADESsperryT1_153Midday1-0.7990959-47.283780.799095947.28378 NANaNNaN
ESPALTARMT1_149Midday potentials60.370129221.0002360.370129221.000240.9779558-0.3769978-0.2441316
ESPALTARMT2_166Midday potentials60.723711229.6299380.723711229.629940.2306132-4.5976796-1.3728237
ESPALTARMT3_168Midday potentials6-0.3930286-16.8380690.509099721.810770.8408983-0.0908776-0.4557260-Inf-Inf
PRADEST1_153Predawn potentialssperryT2_168Predawn 40.164266610.8943640.425190928.19919-0.1142425-0.3534272-0.1017092-2.3900625-81.449242.390062581.449240.7033769-3.5116805-1.1753443
PRADESsperry T2_168Predawn potentialsMidday4-2.0987690-59.049712.098769059.049710.6297046-2.6532171-1.0644385
PRADEScochardT1_153Predawn 1-0.9537104-67.0952030.953710467.095200.665977175.571860.665977175.57186 NA -Inf -Inf
FRAPUET1_168Predawn potentials16-0.7877337-69.5618590.838845774.075370.8762916-0.5740040-0.3138908
FONBLAT2_148Predawn potentials0NaNNaNNaNNaNNANaNNaN
FONBLAT3_168Predawn potentials0NaNNaNNaNNaNPRADEScochardT1_153Midday10.909897853.840100.909897853.84010 NANaNNaN
ESPALTARMT1_149Predawn potentials60.491487843.5909330.491487843.590930.98748010.0966259-0.0438678-Inf-Inf
ESPALTARMT2_166Predawn potentials60.02437803.8165220.265760341.606310.81447050.56899130.1629597PRADEScochardT2_168Predawn40.497692616.960510.912135331.084010.98141550.47847530.1698090
ESPALTARMT3_168Predawn potentials60.322522632.6192280.418117942.287530.83201220.51897820.3534259PRADEScochardT2_168Midday40.892388725.107721.031561629.023400.99681470.2212831-0.0146879
-

Evaluation results by site +

FRAPUE

-

PRADES +

Soil moisture

-
-

Soil moisture -

- ---------- - - - - - - - - - - - - - - - - - - - - -
nBiasBias.relMAEMAE.relrNSENSE.abs
363-0.016174-2.5343440.172762127.070480.73955540.47164690.2668374
-

-

-
-
-

Plant transpiration -

- +
+----+---- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
nBiasBias.relMAEMAE.relrNSENSE.abs
T1_1533620.049700723.946050.126350960.876580.71708300.46400030.3018631
T2_168253-0.0723979-37.763540.128098266.817390.72630490.20931760.2134702
-

-
-
-

Leaf water potentials -

- --------+++ - - + + @@ -728,116 +449,66 @@

Leaf water potentials

- - - - - - - - - - + + + + + + + + + + - - - - - - - - - - + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + +
cohortWPSiteMode n Bias Bias.rel
T1_153Midday potentials4-0.1977309-10.644600.363684219.57850-0.4154639-1.6858419-0.7962793FRAPUEgranier10210.175957424.1637330.200536327.539070.5843796-0.4112639-0.1436430
T2_168Midday potentials1-1.2463547-59.756731.246354759.75673NA-Inf-InfFRAPUEsperry1021-0.0701551-9.6341950.115584415.872880.85952700.53964240.3408309
T1_153Predawn potentials40.164266610.894360.425190928.19919-0.1142425-0.3534272-0.1017092
T2_168Predawn potentials1-0.9537104-67.095200.953710467.09520NA-Inf-InfFRAPUEcochard10210.05942258.1603290.112175015.404680.79646130.46344290.3602744
-

-
+

-

FRAPUE +

Plant transpiration

-
-

Soil moisture -

--------- - - - - - - - - - - - - - - - - - - - - -
nBiasBias.relMAEMAE.relrNSENSE.abs
10120.097652313.425430.143608519.743580.65965540.06158710.1804707
-

-

-
-
-

Plant transpiration -

- -+--++++-+---++ - + + + @@ -849,49 +520,70 @@

Plant transpiration +

+ - - - - - - - - + + + + + + + + - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + +
SiteModeCohort n Bias Bias.relFRAPUEgranier T1_1681087-0.0777585-22.65960.225297665.653990.6795413-0.7490764-0.24288231096-0.0875796-25.5311300.149748043.654440.64859270.23610460.1727263
S1_280NaNNaNNaNNaNNANaNNaNFRAPUEsperryT1_16810960.070732520.6198770.225090465.618180.6074291-0.9363408-0.2434978
FRAPUEcochardT1_16810960.00405031.1807530.144134942.018110.82407010.22101250.2037356
-

+

-
-

Leaf water potentials -

- +
+

Water potentials +

+
-++++- - + + + @@ -904,126 +596,87 @@

Leaf water potentials

+ + - - - - - - - - - + + + + + + + + + + + - - - - - - - - - + + + + + + + + + - -
cohortSiteModeCohort WP n Bias
PRADESsperry T1_168Midday potentials16-0.3411775-12.144930.546076019.438710.8099563-0.6259606-0.0993666Predawn28-1.8940040-129.48478751.8940040129.484790.8497064-2.5444295-0.9918387
PRADESsperry T1_168Predawn potentials16-0.7877337-69.561860.838845774.075370.8762916-0.5740040-0.3138908Midday28-1.4801197-47.43633921.490167447.758360.7403975-4.2629157-1.4960554
-

-
-
-
-

FONBLA -

-
-

Soil moisture -

- - - - - - - - - - - - - - - - - - - - - -
nBiasBias.relMAEMAE.relrNSENSE.abs
0NaNNaNNaNNaNNANaNNaN
-

-

-
-
-

Plant transpiration -

- - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + - - - - - - - - - + + + + + + + + + + + +
nBiasBias.relMAEMAE.relrNSENSE.abs
T2_1480NaNNaNNaNNaNNANaNNaNPRADEScochardT1_168Predawn280.00623960.42657580.505768634.577190.88873290.65148910.4681059
T3_1680NaNNaNNaNNaNNANaNNaNPRADEScochardT1_168Midday281.110858935.60190381.238371739.688560.8498476-2.1182867-1.0742934
-

-
-

Leaf water potentials -

- + +
+

FONBLA +

+
+

Soil moisture +

+
--++-----+++++ - - + + @@ -1035,116 +688,66 @@

Leaf water potentials

- - - - - - - - - - + + + + + + + + + + - - - - - - - - - - + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + +
cohortWPSiteMode n Bias Bias.rel
T2_148Midday potentials0NaNNaNNaNNaNNANaNNaNFONBLAgranier3640.150563121.468440.182343425.999920.70810030.08702440.1262574
T3_168Midday potentials0NaNNaNNaNNaNNANaNNaNFONBLAsperry3640.074603510.637540.137019119.537230.79803420.51754090.3434400
T2_148Predawn potentials0NaNNaNNaNNaNNANaNNaN
T3_168Predawn potentials0NaNNaNNaNNaNNANaNNaNFONBLAcochard3640.085109612.135580.135563519.329690.81417880.52446550.3504145
-

-
+

-

ESPALTARM +

Plant transpiration

-
-

Soil moisture -

--------- - - - - - - - - - - - - - - - - - - - - -
nBiasBias.relMAEMAE.relrNSENSE.abs
10130.249711447.365440.299261456.764130.75969150.11317050.0494851
-

-

-
-
-

Plant transpiration -

- -+----++++++--+ - + + + @@ -1156,60 +759,109 @@

Plant transpiration -

- - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + - - - - - - - - + + + + + + + +
SiteModeCohort n Bias Bias.relT1_149924-50603.10-99.9992350603.1099.999230.5869532-1.008517-0.2119491FONBLAgranierT2_1483000.195468795.039200.2163145105.174660.3725291-6.5937035-1.1859690
FONBLAgranierT3_168309-0.0815908-28.187370.103120435.625270.81667840.43097760.2974624
FONBLAsperryT2_1483000.055751327.106950.107217052.130180.6029784-0.9195415-0.0834830
T2_166805-35393.46-99.9981235393.4699.998120.8208423-2.142858-0.7402761FONBLAsperryT3_1683090.093467132.290320.109326437.769270.89158450.28301950.2551822
FONBLAcochardT2_1483000.079328838.570620.2531704123.094440.3292795-10.2856625-1.5584169
FONBLAcochard T3_168943-55043.53-99.9983655043.5399.998360.7399129-1.486649-0.49470863090.046367516.018690.109096537.689830.80625430.23436400.2567487
-

+

-
-

Leaf water potentials -

+
+

Water potentials +

-+++---+++ - + + + @@ -1222,202 +874,120 @@

Leaf water potentials

- - - - - - - - - - + + + + + + + + + + + + - - - - - - - - - - + + + + + + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + - - - - - - - - - + + + + + + + + + - -
cohortSiteModeCohort WP n Bias
T1_149Midday potentials60.370129221.0002360.370129221.000240.9779558-0.3769978-0.2441316PRADESsperryT2_148Predawn30.861178344.276520.861178344.276520.9965277-3.0409566-1.4220641
T2_166Midday potentials60.723711229.6299380.723711229.629940.2306132-4.5976796-1.3728237PRADESsperryT2_148Midday30.964398936.149900.964398936.149900.9888488-17.7492845-4.1561923
PRADESsperry T3_168Midday potentials6-0.3930286-16.8380690.509099721.810770.8408983-0.0908776-0.4557260
T1_149Predawn potentials60.491487843.5909330.491487843.590930.98748010.0966259-0.0438678
T2_166Predawn potentials60.02437803.8165220.265760341.606310.81447050.56899130.1629597Predawn30.423627227.911020.423627227.911020.99952590.33912600.0428507
PRADESsperry T3_168Predawn potentials60.322522632.6192280.418117942.287530.83201220.51897820.3534259Midday30.619060922.685460.619060922.685460.9718487-1.6514397-0.9124306
-

-
-
-
-

CAN BALASC -

-
-

Soil moisture -

- ---------- - - - - - - - - - - - - - - - - - - - - -
nBiasBias.relMAEMAE.relrNSENSE.abs
6760.140955220.065920.287884240.982250.4564628-1.499109-0.8602195
-

-

-
-
-

Plant transpiration -

- ----------- - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + + + + - - - - - - - - - + + + + + + + + + + + +
nBiasBias.relMAEMAE.relrNSENSE.abs
T1_19644-0.2738551-92.132270.273855192.132270.4720402-2.398135-0.9427867PRADEScochardT2_148Predawn10.901377863.852030.901377863.85203NA-Inf-Inf
PRADEScochard T2_1486110.201841177.672950.3756301144.55082-0.2513688-9.498208-1.8064229Midday11.190340449.701061.190340449.70106NA-Inf-Inf
T3_171644-0.1970242-68.052620.224321877.481270.5893409-0.565041-0.2256941PRADEScochardT3_168Predawn30.442774929.172580.442774929.172580.99614930.2638482-0.0004119
T4_168679-0.2396049-56.461470.338961079.874140.4795248-2.254740-0.8259434PRADEScochardT3_168Midday31.180491243.259041.180491243.259040.9878493-8.5425367-2.6468263
-

-
-
-

Leaf water potentials -

-
+
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a/articles/evaluation/StandLevelEvaluation_files/figure-html/unnamed-chunk-96-6.png and /dev/null differ diff --git a/articles/intro/PackageOverview.html b/articles/intro/PackageOverview.html index 04b143eb8..2abea0003 100644 --- a/articles/intro/PackageOverview.html +++ b/articles/intro/PackageOverview.html @@ -73,7 +73,7 @@

Package overview

Miquel De Caceres

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2024-02-16

+

2024-02-18

Source: vignettes/intro/PackageOverview.Rmd diff --git a/articles/intro/PreparingInputs.html b/articles/intro/PreparingInputs.html index e8e30d84a..9fa30a536 100644 --- a/articles/intro/PreparingInputs.html +++ b/articles/intro/PreparingInputs.html @@ -73,7 +73,7 @@

Preparing model inputs

Miquel De Cáceres

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2024-02-16

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2024-02-18

Source: vignettes/intro/PreparingInputs.Rmd diff --git a/articles/intro/UnderstandingInputs.html b/articles/intro/UnderstandingInputs.html index c3336e014..0f56b6655 100644 --- a/articles/intro/UnderstandingInputs.html +++ b/articles/intro/UnderstandingInputs.html @@ -73,7 +73,7 @@

Understanding model inputs

Miquel De Caceres

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2024-02-16

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2024-02-18

Source: vignettes/intro/UnderstandingInputs.Rmd diff --git a/articles/modelanalysis/SensitivityCalibration.html b/articles/modelanalysis/SensitivityCalibration.html index ba977c105..086319763 100644 --- a/articles/modelanalysis/SensitivityCalibration.html +++ b/articles/modelanalysis/SensitivityCalibration.html @@ -73,7 +73,7 @@

Sensitivity analysis and calibration

Miquel De Caceres

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2024-02-16

+

2024-02-18

Source: vignettes/modelanalysis/SensitivityCalibration.Rmd @@ -358,20 +358,20 @@

Model output functions
 data(exampleobs)
 head(exampleobs)
-
##                  SWC       ETR  E_T1_148   E_T2_168 FMC_T1_148 FMC_T2_168
-## 2001-01-01 0.3045751 2.3411471 0.1339854 0.07607795   125.9175   93.06831
-## 2001-01-02 0.3102597 2.1269664 0.2337255 0.13067831   125.8440   93.09309
-## 2001-01-03 0.2910761 0.4372701 0.2044522 0.13490555   125.8258   93.08122
-## 2001-01-04 0.3044012 2.4051967 0.1821502 0.10833830   125.9498   93.05980
-## 2001-01-05 0.2943755 2.1179359 0.1741763 0.17682843   125.8625   93.04084
-## 2001-01-06 0.2983762 2.7841214 0.2050965 0.16383047   125.8570   93.07484
-##              BAI_T1_148 BAI_T2_168    DI_T1_148 DI_T2_168
-## 2001-01-01 2.523957e-05          0 1.145092e-07         0
-## 2001-01-02 9.827612e-10          0 4.195872e-11         0
-## 2001-01-03 2.558302e-13          0 0.000000e+00         0
-## 2001-01-04 2.583888e-11          0 1.439640e-12         0
-## 2001-01-05 2.939784e-03          0 8.218013e-05         0
-## 2001-01-06 3.163390e-03          0 4.238446e-05         0
+
##        dates       SWC       ETR   E_T1_148   E_T2_168 FMC_T1_148 FMC_T2_168
+## 1 2001-01-01 0.3069977 1.9590280 0.07897391 0.05401519   125.8873   93.07011
+## 2 2001-01-02 0.3224390 1.8063483 0.25711073 0.14870784   125.9162   93.07620
+## 3 2001-01-03 0.3083034 0.2818827 0.20327929 0.08146374   125.9254   93.07423
+## 4 2001-01-04 0.3235625 1.5629178 0.09251115 0.06161691   125.8833   93.08324
+## 5 2001-01-05 0.3146014 1.2766893 0.15464108 0.13231872   125.9490   93.09398
+## 6 2001-01-06 0.3409924 1.7082599 0.14587030 0.07959577   125.9485   93.08401
+##     BAI_T1_148 BAI_T2_168    DI_T1_148 DI_T2_168
+## 1 2.318246e-05          0 2.614144e-07         0
+## 2 2.266946e-09          0 3.828287e-11         0
+## 3 1.815648e-13          0 0.000000e+00         0
+## 4 2.421352e-11          0 1.005387e-12         0
+## 5 2.924564e-03          0 9.304292e-05         0
+## 6 2.833330e-03          0 5.142938e-05         0

where soil water content dynamics is in column SWC. The model fit to observed data can be measured using the Nash-Sutcliffe coefficient, which we calculate for the initial run using function @@ -379,7 +379,7 @@

Model output functions
 evaluation_metric(S1, measuredData = exampleobs, type = "SWC", 
                   metric = "NSE")
-
## [1] -2.501692
+
## [1] 0.9364947

A call to evaluation_metric() provides the coefficient given a model simulation result, but is not a model output function as we defined above. Analogously to the measures of total transpiration and @@ -398,10 +398,10 @@

Model output functions 
 of_eval(parMin)
-
## [1] -5.133859
+
## [1] 0.7608044
 of_eval(parMax)
-
## [1] -9.523272
+
## [1] -6.398158

Global sensitivity analyses diff --git a/articles/parametrization/GrowthCalibration.html b/articles/parametrization/GrowthCalibration.html index 2e1f2810f..16eb29113 100644 --- a/articles/parametrization/GrowthCalibration.html +++ b/articles/parametrization/GrowthCalibration.html @@ -75,7 +75,7 @@

Calibration of growth and senescence

Miquel De Cáceres

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2024-02-16

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2024-02-18

Source: vignettes/parametrization/GrowthCalibration.Rmd diff --git a/articles/parametrization/Metamodelling.html b/articles/parametrization/Metamodelling.html index bea20b048..629374d0e 100644 --- a/articles/parametrization/Metamodelling.html +++ b/articles/parametrization/Metamodelling.html @@ -74,7 +74,7 @@

Meta-modelling exercise

Miquel De Cáceres

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2024-02-16

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2024-02-18

Source: vignettes/parametrization/Metamodelling.Rmd diff --git a/articles/runmodels/AdvancedWaterEnergyBalance.html b/articles/runmodels/AdvancedWaterEnergyBalance.html index 3ae1cc022..4f25fad1f 100644 --- a/articles/runmodels/AdvancedWaterEnergyBalance.html +++ b/articles/runmodels/AdvancedWaterEnergyBalance.html @@ -73,7 +73,7 @@

Advanced water and energy balance

Miquel De Caceres

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2024-02-16

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2024-02-18

Source: vignettes/runmodels/AdvancedWaterEnergyBalance.Rmd @@ -273,10 +273,10 @@

Water balance input object## S1_165 1085.030 1380.808 2170.587 4146.637 ## ## $VGrhizo_kmax -## 1 2 3 4 -## T1_148 296483.4 41158.65 5206.196 1703.629 -## T2_168 46380598.9 41722941.01 3763846.755 728011.313 -## S1_165 10941458.6 4405482.18 574055.729 169670.901 +## 1 2 3 4 +## T1_148 176772045 24539986 3104085 1015753 +## T2_168 82682357 74379184 6709782 1297820 +## S1_165 1116059122 449371399 58555276 17306902 ## ## $VCroot_kmax ## 1 2 3 4 @@ -317,13 +317,13 @@

Water balance input object## T2_168 0.004473333 0.2007222 68.51600 118.7863 0.40 1.60 ## S1_165 0.010455247 0.2830167 62.78100 118.4486 0.29 1.16 ## VCleaf_kmax VCleafapo_kmax VCleaf_c VCleaf_d kleaf_symp VCstem_kmax -## T1_148 4.000000 8.00000 1.456324 -1.536975 8.00000 1.339563 -## T2_168 4.000000 8.00000 2.254991 -3.133381 8.00000 1.620936 -## S1_165 9.579077 19.15815 2.254991 -3.133381 19.15815 4.599269 -## VCstem_c VCstem_d VCroot_kmax VCroot_c VCroot_d VGrhizo_kmax -## T1_148 5.030852 -4.797531 2.916127 3.193056 -0.9870357 344551.9 -## T2_168 2.731881 -4.278250 2.896748 1.182310 -2.5041509 92595397.9 -## S1_165 3.095442 -7.857378 3.242501 1.402489 -1.5233241 16090667.4 +## T1_148 4.000000 8.00000 5.030852 -4.797531 8.00000 1.339563 +## T2_168 4.000000 8.00000 2.731881 -4.278250 8.00000 1.620936 +## S1_165 9.579077 19.15815 3.095442 -7.857378 19.15815 4.599269 +## VCstem_c VCstem_d VCroot_kmax VCroot_c VCroot_d VGrhizo_kmax +## T1_148 5.030852 -4.797531 2.916127 5.030852 -4.797531 205431869 +## T2_168 2.731881 -4.278250 2.896748 2.731881 -4.278250 165069144 +## S1_165 3.095442 -7.857378 3.242501 3.095442 -7.857378 1641292700 ## Plant_kmax FR_leaf FR_stem FR_root ## T1_148 0.7465846 0.1866462 0.5573346 0.2560193 ## T2_168 0.8249857 0.2062464 0.5089563 0.2847972 @@ -510,21 +510,21 @@

Water balance output## NetRain Snowmelt Runon ## 0.000000000 0.000000000 0.000000000 ## Infiltration Runoff DeepDrainage -## 0.000000000 0.000000000 0.008444669 +## 0.000000000 0.000000000 0.008442749 ## SoilEvaporation HerbTranspiration PlantExtraction -## 0.500000000 0.048725420 0.441008334 +## 0.500000000 0.048725420 0.879355298 ## Transpiration HydraulicRedistribution -## 0.441008334 0.000000000 +## 0.879355298 0.000000000

And Soil contains water evaporated from each soil layer, water transpired from each soil layer and the final soil water potential:

 sd1$Soil
##   HerbTranspiration HydraulicInput HydraulicOutput PlantExtraction         psi
-## 1       0.008571001              0     0.288628120     0.288628120 -0.03513262
-## 2       0.012000080              0     0.139710283     0.139710283 -0.03315439
-## 3       0.013576976              0     0.011267299     0.011267299 -0.03296476
-## 4       0.014577363              0     0.001402631     0.001402631 -0.03299518
+## 1 0.008571001 0 0.624931278 0.624931278 -0.03595813 +## 2 0.012000080 0 0.232685935 0.232685935 -0.03328231 +## 3 0.013576976 0 0.019134296 0.019134296 -0.03298146 +## 4 0.014577363 0 0.002603789 0.002603789 -0.03300144

Soil and canopy energy balance @@ -560,21 +560,21 @@

Plant output
 sd1$Plants

##               LAI    LAIlive     FPAR Extraction Transpiration
-## T1_148 0.84874773 0.84874773 92.18285 0.17145075    0.17145075
-## T2_168 0.70557382 0.70557382 72.36365 0.25707171    0.25707171
-## S1_165 0.03062604 0.03062604 44.32407 0.01248587    0.01248587
-##        GrossPhotosynthesis NetPhotosynthesis    RootPsi    StemPsi     LeafPLC
-## T1_148          1.91266768        1.79911299 -0.2180120 -0.6186918 0.105673867
-## T2_168          1.75124703        1.64531791 -0.3785782 -0.9685505 0.030530559
-## S1_165          0.06688913        0.06294377 -0.3759137 -0.6029081 0.009637998
-##             StemPLC LeafPsiMin  LeafPsiMax      dEdP        DDS   StemRWC
-## T1_148 1.553358e-05 -0.8045533 -0.03995231 0.4790119 0.05005867 0.9987769
-## T2_168 9.496613e-03 -1.2294457 -0.04019149 0.5400064 0.03087011 0.9912581
-## S1_165 1.971280e-04 -0.7151737 -0.04188680 1.0414421 0.02823879 0.9879970
+## T1_148 0.84874773 0.84874773 92.18285 0.51972663    0.51972663
+## T2_168 0.70557382 0.70557382 72.36365 0.33237115    0.33237115
+## S1_165 0.03062604 0.03062604 44.32407 0.02725753    0.02725753
+##        GrossPhotosynthesis NetPhotosynthesis    RootPsi   StemPsi     LeafPLC
+## T1_148          2.12426850        2.01339458 -0.5335429 -1.624335 0.002722852
+## T2_168          1.81702456        1.71356630 -0.4379319 -1.169929 0.014501424
+## S1_165          0.07014613        0.06637218 -0.7888535 -1.322764 0.001529193
+##            StemPLC LeafPsiMin  LeafPsiMax      dEdP         DDS   StemRWC
+## T1_148 0.002195517  -1.992041 -0.03994095 0.5028769 0.002731251 0.9946726
+## T2_168 0.016295506  -1.475232 -0.04017868 0.5491158 0.014521628 0.9863067
+## S1_165 0.002013280  -1.579954 -0.04186438 1.0700642 0.001531708 0.9756540
 ##          LeafRWC      LFMC  WaterBalance
-## T1_148 0.9442717 122.37927 -2.710505e-18
-## T2_168 0.9763045  91.56735  7.752046e-18
-## S1_165 0.9867170  95.32174  1.162129e-18
+## T1_148 0.9496856 122.47272 -1.729302e-17 +## T2_168 0.9743809 91.26229 -8.592302e-18 +## S1_165 0.9778179 94.27543 4.031877e-19

While Plants contains one value per cohort and variable that summarizes the whole simulated day, information by disaggregated by time step can be accessed in PlantsInst. Moreover, we can @@ -604,16 +604,16 @@

Output for sunlit and shade leaves 
 sd1$SunlitLeaves
-
##        LeafPsiMin  LeafPsiMax      GSWMin     GSWMax  TempMin  TempMax
-## T1_148 -0.9592402 -0.03995231 0.002242885 0.07233002 1.273603 12.05125
-## T2_168 -1.6359558 -0.04198952 0.003269166 0.09304960 1.271446 17.66165
-## S1_165 -1.1220604 -0.04703362 0.007561899 0.09615895 1.266836 17.45753
+
##        LeafPsiMin  LeafPsiMax      GSWMin    GSWMax  TempMin  TempMax
+## T1_148  -2.242720 -0.03994095 0.002242884 0.2741563 1.273603 11.69716
+## T2_168  -1.980099 -0.04197336 0.003269165 0.1199765 1.271446 17.29191
+## S1_165  -2.289301 -0.04699638 0.007561891 0.1997103 1.266836 16.55885
 sd1$ShadeLeaves
-
##        LeafPsiMin  LeafPsiMax      GSWMin     GSWMax   TempMin  TempMax
-## T1_148 -0.7018481 -0.03995231 0.002250627 0.06647826 0.9887835 10.52722
-## T2_168 -0.9260605 -0.04019149 0.003263123 0.11869066 0.5311464 10.52028
-## S1_165 -0.5152537 -0.04188680 0.007632281 0.10589943 0.6698708 10.32592
+
##        LeafPsiMin  LeafPsiMax      GSWMin    GSWMax   TempMin   TempMax
+## T1_148  -1.791699 -0.03994095 0.002250626 0.2803527 0.9555411 10.158239
+## T2_168  -1.123196 -0.04017868 0.003263121 0.1807394 0.5311464 10.181732
+## S1_165  -1.251721 -0.04186438 0.007632274 0.2310791 0.5914201  9.625732

Instantaneous values are also stored for sunlit and shade leaves. We can also use the plot function for objects of class spwb_day to draw instantaneous variations in temperature @@ -664,43 +664,43 @@

Running the model
 x$soil$W
-
## [1] 0.9867803 0.9990148 1.0002255 1.0000308
+
## [1] 0.9818782 0.9982019 1.0001186 0.9999908

And the temperature of soil layers:

 x$soil$Temp
-
## [1] 8.150905 3.143876 2.380323 2.434077
+
## [1] 8.016705 3.132713 2.380127 2.434077

We can also see the current state of canopy variables:

 x$canopy
##    zlow zmid  zup     Tair Cair     VPair
-## 1     0   50  100 5.748649  386 0.5170718
-## 2   100  150  200 5.748649  386 0.5170718
-## 3   200  250  300 5.748649  386 0.5170718
-## 4   300  350  400 5.748649  386 0.5170718
-## 5   400  450  500 5.748649  386 0.5170718
-## 6   500  550  600 5.748649  386 0.5170718
-## 7   600  650  700 5.748649  386 0.5170718
-## 8   700  750  800 5.748649  386 0.5170718
-## 9   800  850  900 5.748649  386 0.5170718
-## 10  900  950 1000 5.748649  386 0.5170718
-## 11 1000 1050 1100 5.748649  386 0.5170718
-## 12 1100 1150 1200 5.748649  386 0.5170718
-## 13 1200 1250 1300 5.748649  386 0.5170718
-## 14 1300 1350 1400 5.748649  386 0.5170718
-## 15 1400 1450 1500 5.748649  386 0.5170718
-## 16 1500 1550 1600 5.748649  386 0.5170718
-## 17 1600 1650 1700 5.748649  386 0.5170718
-## 18 1700 1750 1800 5.748649  386 0.5170718
-## 19 1800 1850 1900 5.748649  386 0.5170718
-## 20 1900 1950 2000 5.748649  386 0.5170718
-## 21 2000 2050 2100 5.748649  386 0.5170718
-## 22 2100 2150 2200 5.748649  386 0.5170718
-## 23 2200 2250 2300 5.748649  386 0.5170718
-## 24 2300 2350 2400 5.748649  386 0.5170718
-## 25 2400 2450 2500 5.748649  386 0.5170718
-## 26 2500 2550 2600 5.748649  386 0.5170718
-## 27 2600 2650 2700 5.748649  386 0.5170718
-## 28 2700 2750 2800 5.748649  386 0.5170718
+## 1 0 50 100 5.644686 386 0.5170718 +## 2 100 150 200 5.644686 386 0.5170718 +## 3 200 250 300 5.644686 386 0.5170718 +## 4 300 350 400 5.644686 386 0.5170718 +## 5 400 450 500 5.644686 386 0.5170718 +## 6 500 550 600 5.644686 386 0.5170718 +## 7 600 650 700 5.644686 386 0.5170718 +## 8 700 750 800 5.644686 386 0.5170718 +## 9 800 850 900 5.644686 386 0.5170718 +## 10 900 950 1000 5.644686 386 0.5170718 +## 11 1000 1050 1100 5.644686 386 0.5170718 +## 12 1100 1150 1200 5.644686 386 0.5170718 +## 13 1200 1250 1300 5.644686 386 0.5170718 +## 14 1300 1350 1400 5.644686 386 0.5170718 +## 15 1400 1450 1500 5.644686 386 0.5170718 +## 16 1500 1550 1600 5.644686 386 0.5170718 +## 17 1600 1650 1700 5.644686 386 0.5170718 +## 18 1700 1750 1800 5.644686 386 0.5170718 +## 19 1800 1850 1900 5.644686 386 0.5170718 +## 20 1900 1950 2000 5.644686 386 0.5170718 +## 21 2000 2050 2100 5.644686 386 0.5170718 +## 22 2100 2150 2200 5.644686 386 0.5170718 +## 23 2200 2250 2300 5.644686 386 0.5170718 +## 24 2300 2350 2400 5.644686 386 0.5170718 +## 25 2400 2450 2500 5.644686 386 0.5170718 +## 26 2500 2550 2600 5.644686 386 0.5170718 +## 27 2600 2650 2700 5.644686 386 0.5170718 +## 28 2700 2750 2800 5.644686 386 0.5170718

We simply use function resetInputs() to reset state variables to their default values, so that the new simulation is not affected by the end state of the previous simulation:

@@ -745,29 +745,29 @@

Running the modelspwb():

 S <- spwb(x, examplemeteo, latitude = 41.82592, elevation = 100)
-
## Initial plant water content (mm): 6.78513
+
## Initial plant water content (mm): 6.78662
 ## Initial soil water content (mm): 290.875
 ## Initial snowpack content (mm): 0
 ## Performing daily simulations
 ## 
 ##  [Year 2001]:....................................
 ## 
-## Final plant water content (mm): 6.75219
-## Final soil water content (mm): 321.501
+## Final plant water content (mm): 6.41269
+## Final soil water content (mm): 246.858
 ## Final snowpack content (mm): 0
-## Change in plant water content (mm): -0.0329405
-## Plant water balance result (mm): -2.95258e-16
-## Change in soil water content (mm): 30.6257
-## Soil water balance result (mm): 30.5229
+## Change in plant water content (mm): -0.37393
+## Plant water balance result (mm): -9.37334e-16
+## Change in soil water content (mm): -44.0172
+## Soil water balance result (mm): -44.0435
 ## Change in snowpack water content (mm): 0
 ## Snowpack water balance result (mm): -7.10543e-15
 ## Water balance components:
 ##   Precipitation (mm) 513
 ##   Rain (mm) 462 Snow (mm) 51
 ##   Interception (mm) 92 Net rainfall (mm) 370
-##   Infiltration (mm) 328 Runoff (mm) 42 Deep drainage (mm) 135
-##   Soil evaporation (mm) 15  Herbaceous transpiration (mm) 14 Woody plant transpiration (mm) 184
-##   Plant extraction from soil (mm) 184  Plant water balance (mm) -0 Hydraulic redistribution (mm) 1

+##   Infiltration (mm) 346 Runoff (mm) 24 Deep drainage (mm) 56
+##   Soil evaporation (mm) 8  Herbaceous transpiration (mm) 13 Woody plant transpiration (mm) 363
+##   Plant extraction from soil (mm) 363  Plant water balance (mm) -0 Hydraulic redistribution (mm) 14

Function spwb() returns an object of class spwb. If we inspect its elements, we realize that the output is arranged differently than in spwb_day():

@@ -800,38 +800,38 @@

Running the model## 2001-01-05 1.6760567 1.884401 1.884401 0 0.7539027 0 ## 2001-01-06 1.2077028 13.359801 13.359801 0 11.7240275 0 ## Infiltration Runoff DeepDrainage Evapotranspiration Interception -## 2001-01-01 3.4241795 0 0.008465071 2.0715031 1.444929 -## 2001-01-02 1.0717469 0 0.008504341 1.6900511 1.426545 -## 2001-01-03 0.0000000 0 0.008540795 0.2651084 0.000000 -## 2001-01-04 4.3625616 0 0.008585333 1.6592513 1.434411 -## 2001-01-05 0.7539027 0 0.008629148 1.3602822 1.130499 -## 2001-01-06 11.7240275 0 0.008672633 1.8297480 1.635773 +## 2001-01-01 3.4241795 0 0.008464267 2.255715 1.444929 +## 2001-01-02 1.0717469 0 0.008501580 1.947740 1.426545 +## 2001-01-03 0.0000000 0 0.008535573 0.551716 0.000000 +## 2001-01-04 4.3625616 0 0.008577728 1.896419 1.434411 +## 2001-01-05 0.7539027 0 0.008619290 1.590887 1.130499 +## 2001-01-06 11.7240275 0 0.008660502 2.028699 1.635773 ## SoilEvaporation HerbTranspiration PlantExtraction Transpiration -## 2001-01-01 0.44789475 0.011023432 0.1676556 0.1676556 -## 2001-01-02 0.06807917 0.020448135 0.1749791 0.1749791 -## 2001-01-03 0.05486714 0.016254819 0.1939865 0.1939865 -## 2001-01-04 0.06392529 0.007106208 0.1538085 0.1538085 -## 2001-01-05 0.02622930 0.020931035 0.1826231 0.1826231 -## 2001-01-06 0.02521112 0.015082180 0.1536816 0.1536816 +## 2001-01-01 0.44789475 0.011023432 0.3518677 0.3518677 +## 2001-01-02 0.07362662 0.020448029 0.4271203 0.4271203 +## 2001-01-03 0.06419196 0.016254627 0.4712694 0.4712694 +## 2001-01-04 0.08811282 0.007106063 0.3667885 0.3667885 +## 2001-01-05 0.03090352 0.020930645 0.4085543 0.4085543 +## 2001-01-06 0.03064445 0.015081842 0.3471994 0.3471994 ## HydraulicRedistribution ## 2001-01-01 0.000000e+00 -## 2001-01-02 1.461249e-05 -## 2001-01-03 6.450671e-06 -## 2001-01-04 3.122947e-05 -## 2001-01-05 2.427505e-03 -## 2001-01-06 2.930023e-03 +## 2001-01-02 9.966818e-06 +## 2001-01-03 1.024336e-07 +## 2001-01-04 6.221948e-06 +## 2001-01-05 1.692829e-03 +## 2001-01-06 1.902109e-03

Elements Plants is itself a list with several elements that contain daily output results by plant cohorts, for example leaf minimum (midday) water potentials are:

 head(S$Plants$LeafPsiMin)
-
##                T1_148     T2_168     S1_165
-## 2001-01-01 -0.4112408 -0.7382799 -0.3902716
-## 2001-01-02 -0.4713257 -0.7470919 -0.3928797
-## 2001-01-03 -0.4838920 -0.8590447 -0.4992473
-## 2001-01-04 -0.3730945 -0.6497506 -0.3438892
-## 2001-01-05 -0.4971942 -0.8263250 -0.4244027
-## 2001-01-06 -0.4464305 -0.7257777 -0.3746801
+
##               T1_148     T2_168     S1_165
+## 2001-01-01 -1.356475 -0.9361828 -0.6881288
+## 2001-01-02 -1.565760 -0.9954821 -0.8409771
+## 2001-01-03 -1.528220 -1.1073103 -0.8965962
+## 2001-01-04 -1.269772 -0.8492362 -0.5930441
+## 2001-01-05 -1.642458 -1.0753026 -0.9518200
+## 2001-01-06 -1.542817 -0.9753797 -0.8080354

Plotting and summarizing results @@ -865,89 +865,89 @@

Plotting and summarizing results 
 summary(S, freq="months",FUN=mean, output="Soil")
-
##                  W.1       W.2      W.3      W.4     ML.1     ML.2     ML.3
-## 2001-01-01 1.1857453 1.1330134 1.036473 1.009202 80.83678 132.1694 78.51150
-## 2001-02-01 0.9932351 1.2242828 1.238226 1.128213 67.71262 142.8162 93.79401
-## 2001-03-01 1.1112514 1.2026977 1.297851 1.382486 75.75825 140.2983 98.31051
-## 2001-04-01 0.9572397 1.1322086 1.249407 1.367151 65.25868 132.0755 94.64094
-## 2001-05-01 1.0113716 1.0933617 1.200711 1.335943 68.94906 127.5439 90.95225
-## 2001-06-01 0.7556657 0.9874473 1.153115 1.301929 51.51661 115.1887 87.34694
-## 2001-07-01 1.0035522 0.9884829 1.114971 1.265945 68.41598 115.3095 84.45759
-## 2001-08-01 1.0672689 1.0348317 1.101480 1.242769 72.75979 120.7162 83.43569
-## 2001-09-01 1.0727786 1.0894163 1.112318 1.233790 73.13541 127.0837 84.25664
-## 2001-10-01 1.0651216 1.1171961 1.141528 1.247333 72.61340 130.3242 86.46921
-## 2001-11-01 1.1172744 1.1870446 1.204591 1.291977 76.16886 138.4723 91.24619
-## 2001-12-01 0.9215663 1.1837060 1.290325 1.383622 62.82669 138.0828 97.74039
-##                ML.4    MLTot       WTD        SWE PlantExt.1 PlantExt.2
-## 2001-01-01 30.57828 322.0959 3456.8367 1.65619239  0.1166855 0.05227876
-## 2001-02-01 34.18427 338.5071 2276.7098 0.27608905  0.1637527 0.10911893
-## 2001-03-01 41.88860 356.2556  877.8681 0.01762496  0.2269428 0.12189916
-## 2001-04-01 41.42395 333.3991 1312.5326 0.58072652  0.2429992 0.14800099
-## 2001-05-01 40.47836 327.9236 1624.0735 0.00000000  0.3817760 0.20466619
-## 2001-06-01 39.44777 293.5000 2097.7182 0.00000000  0.4534040 0.36997652
-## 2001-07-01 38.35745 306.5405 2305.6406 0.00000000  0.5401126 0.28425762
-## 2001-08-01 37.65524 314.5669 2410.1505 0.00000000  0.6078771 0.28650480
-## 2001-09-01 37.38319 321.8589 2327.6327 0.00000000  0.3799801 0.18704734
-## 2001-10-01 37.79353 327.2004 2138.5488 0.00000000  0.3189253 0.16291001
-## 2001-11-01 39.14621 345.0335 1561.8554 2.60802857  0.1590945 0.08714046
-## 2001-12-01 41.92300 340.5729 1035.2846 0.00000000  0.1237340 0.10073438
-##             PlantExt.3   PlantExt.4 HydraulicInput.1 HydraulicInput.2
-## 2001-01-01 0.003318498 0.0006445663     0.0000000000     1.070587e-03
-## 2001-02-01 0.008866559 0.0011646391     0.0037775385     0.000000e+00
-## 2001-03-01 0.010422957 0.0017435202     0.0015261763     1.090571e-05
-## 2001-04-01 0.012874974 0.0017654349     0.0037697361     0.000000e+00
-## 2001-05-01 0.017664368 0.0023722688     0.0006762318     0.000000e+00
-## 2001-06-01 0.032888968 0.0044232795     0.0189968477     0.000000e+00
-## 2001-07-01 0.025300696 0.0034249568     0.0054275170     2.637453e-04
-## 2001-08-01 0.024270052 0.0032856350     0.0000000000     4.832867e-06
-## 2001-09-01 0.015378095 0.0021015471     0.0001289239     5.010046e-06
-## 2001-10-01 0.013439680 0.0018416860     0.0001883006     0.000000e+00
-## 2001-11-01 0.007193905 0.0017047964     0.0007416097     5.608201e-05
-## 2001-12-01 0.008775717 0.0013232033     0.0074874395     0.000000e+00
+
##                  W.1       W.2       W.3      W.4     ML.1      ML.2     ML.3
+## 2001-01-01 1.1734876 1.1145136 1.0290997 1.008304 80.00113 130.01132 77.95294
+## 2001-02-01 0.9807509 1.1918303 1.1620297 1.062746 66.86153 139.03055 88.02222
+## 2001-03-01 1.0474359 1.1894876 1.2796245 1.284929 71.40770 138.75726 96.92987
+## 2001-04-01 0.8496587 1.0706844 1.2277734 1.357160 57.92447 124.89851 93.00222
+## 2001-05-01 0.8364800 0.9966322 1.1616575 1.313385 57.02603 116.26010 87.99402
+## 2001-06-01 0.5133378 0.8030990 1.0961887 1.264994 34.99619  93.68388 83.03485
+## 2001-07-01 0.7656414 0.6823754 1.0390494 1.215078 52.19670  79.60112 78.70662
+## 2001-08-01 0.6925900 0.6693732 1.0031511 1.175504 47.21650  78.08437 75.98738
+## 2001-09-01 0.6613701 0.6591303 0.9738572 1.142503 45.08812  76.88950 73.76840
+## 2001-10-01 0.6764769 0.6491615 0.9499872 1.118483 46.11801  75.72662 71.96028
+## 2001-11-01 0.8738718 0.6831155 0.9343324 1.100280 59.57517  79.68745 70.77445
+## 2001-12-01 0.9705633 0.7379771 0.9247269 1.088244 66.16701  86.08722 70.04685
+##                ML.4    MLTot      WTD        SWE PlantExt.1 PlantExt.2
+## 2001-01-01 30.55108 318.5165 3527.671 1.65619239  0.3107699 0.10584971
+## 2001-02-01 32.20065 326.1149 2892.994 0.27608905  0.4257649 0.18302904
+## 2001-03-01 38.93267 346.0275 1442.375 0.01762496  0.5274848 0.21372334
+## 2001-04-01 41.12122 316.9464 1533.997 0.58072652  0.5738724 0.26555735
+## 2001-05-01 39.79487 301.0750 2009.791 0.00000000  0.7849142 0.37369599
+## 2001-06-01 38.32865 250.0436 2443.470 0.00000000  0.4314077 1.02453452
+## 2001-07-01 36.81622 247.3207 2831.893 0.00000000  1.0912392 0.44196116
+## 2001-08-01 35.61715 236.9054 3112.869 0.00000000  1.2415305 0.44584250
+## 2001-09-01 34.61723 230.3633 3289.235 0.00000000  0.7475436 0.29678978
+## 2001-10-01 33.88946 227.6944 3408.751 0.00000000  0.6654072 0.23899722
+## 2001-11-01 33.33790 243.3750 3453.192 2.60802857  0.4350331 0.08506037
+## 2001-12-01 32.97322 255.2743 3547.373 0.00000000  0.4344285 0.07183331
+##            PlantExt.3  PlantExt.4 HydraulicInput.1 HydraulicInput.2
+## 2001-01-01 0.00790211 0.001323566     0.0000000000     0.0009078394
+## 2001-02-01 0.01482812 0.001974889     0.0040863678     0.0000000000
+## 2001-03-01 0.01817062 0.002651147     0.0025557012     0.0000000000
+## 2001-04-01 0.02330108 0.003303651     0.0114274356     0.0000000000
+## 2001-05-01 0.03309791 0.004654345     0.0161047209     0.0000000000
+## 2001-06-01 0.09540695 0.013279718     0.2361219106     0.0000000000
+## 2001-07-01 0.05721903 0.007986390     0.0364320601     0.0237801570
+## 2001-08-01 0.05944333 0.008343092     0.0064505831     0.0095601568
+## 2001-09-01 0.04482460 0.006351775     0.0130937990     0.0067742414
+## 2001-10-01 0.04149792 0.005944168     0.0146298999     0.0176237997
+## 2001-11-01 0.02014496 0.003044898     0.0005410576     0.0300372853
+## 2001-12-01 0.01308325 0.002071392     0.0000000000     0.0343363641
 ##            HydraulicInput.3 HydraulicInput.4       psi.1       psi.2
-## 2001-01-01     4.858801e-04     7.298495e-05 -0.01350062 -0.01770650
-## 2001-02-01     0.000000e+00     7.437831e-06 -0.03835089 -0.01058083
-## 2001-03-01     0.000000e+00     0.000000e+00 -0.02029229 -0.01171529
-## 2001-04-01     0.000000e+00     0.000000e+00 -0.04191358 -0.01777842
-## 2001-05-01     0.000000e+00     0.000000e+00 -0.03458531 -0.02132726
-## 2001-06-01     0.000000e+00     0.000000e+00 -0.12284758 -0.03616198
-## 2001-07-01     0.000000e+00     0.000000e+00 -0.04277097 -0.03489515
-## 2001-08-01     0.000000e+00     0.000000e+00 -0.02500247 -0.02795119
-## 2001-09-01     3.560886e-08     0.000000e+00 -0.02396631 -0.02136741
-## 2001-10-01     0.000000e+00     0.000000e+00 -0.02513340 -0.01868332
-## 2001-11-01     2.376462e-06     0.000000e+00 -0.02109237 -0.01302985
-## 2001-12-01     0.000000e+00     0.000000e+00 -0.05280406 -0.01380221
+## 2001-01-01     4.462574e-04     6.133280e-05 -0.01443443 -0.01922915
+## 2001-02-01     1.807143e-06     9.403664e-06 -0.04186638 -0.01269843
+## 2001-03-01     0.000000e+00     0.000000e+00 -0.02805572 -0.01280121
+## 2001-04-01     0.000000e+00     0.000000e+00 -0.07239036 -0.02432175
+## 2001-05-01     0.000000e+00     0.000000e+00 -0.09439304 -0.03454779
+## 2001-06-01     0.000000e+00     0.000000e+00 -0.67400660 -0.10306132
+## 2001-07-01     0.000000e+00     0.000000e+00 -0.16732646 -0.17428597
+## 2001-08-01     0.000000e+00     0.000000e+00 -0.17818094 -0.18848524
+## 2001-09-01     0.000000e+00     0.000000e+00 -0.21330640 -0.20113357
+## 2001-10-01     0.000000e+00     0.000000e+00 -0.20698836 -0.21447867
+## 2001-11-01     0.000000e+00     0.000000e+00 -0.10516637 -0.17395267
+## 2001-12-01     0.000000e+00     0.000000e+00 -0.04150006 -0.12408594
 ##                   psi.3        psi.4
-## 2001-01-01 -0.027583402 -0.031478545
-## 2001-02-01 -0.009213776 -0.018000430
-## 2001-03-01 -0.005909402 -0.001120134
-## 2001-04-01 -0.008829631 -0.002166710
-## 2001-05-01 -0.011963043 -0.003842137
-## 2001-06-01 -0.015690758 -0.005700142
-## 2001-07-01 -0.018967921 -0.007721204
-## 2001-08-01 -0.020246074 -0.009109250
-## 2001-09-01 -0.019095982 -0.009633958
-## 2001-10-01 -0.016400216 -0.008740117
-## 2001-11-01 -0.011429746 -0.005998350
-## 2001-12-01 -0.006447549 -0.001135959

+## 2001-01-01 -0.028551693 -0.031631695
+## 2001-02-01 -0.014608972 -0.024255173
+## 2001-03-01 -0.006816287 -0.006510372
+## 2001-04-01 -0.010277381 -0.002736149
+## 2001-05-01 -0.014998735 -0.005079222
+## 2001-06-01 -0.021122407 -0.007843224
+## 2001-07-01 -0.027579521 -0.010974675
+## 2001-08-01 -0.032714627 -0.013829556
+## 2001-09-01 -0.037528227 -0.016495166
+## 2001-10-01 -0.041994892 -0.018646041
+## 2001-11-01 -0.045158813 -0.020401926
+## 2001-12-01 -0.047304584 -0.021645893

Parameter output is used to indicate the element of the spwb object for which we desire summaries. Similarly, it is possible to calculate the average stress of plant cohorts by months:

 summary(S, freq="months",FUN=mean, output="PlantStress")
-
##                T1_148     T2_168      S1_165
-## 2001-01-01 0.01589339 0.01222980 0.008408768
-## 2001-02-01 0.03265345 0.02529637 0.017755565
-## 2001-03-01 0.03681798 0.03090886 0.019149198
-## 2001-04-01 0.04583556 0.03832254 0.025656179
-## 2001-05-01 0.06563614 0.05140293 0.036679819
-## 2001-06-01 0.12929291 0.08278718 0.070671160
-## 2001-07-01 0.09793163 0.07972567 0.052841040
-## 2001-08-01 0.09376091 0.08059816 0.051858714
-## 2001-09-01 0.06250372 0.06220892 0.034202963
-## 2001-10-01 0.05103023 0.05442120 0.026799135
-## 2001-11-01 0.02621790 0.04109262 0.014779172
-## 2001-12-01 0.02908624 0.04201542 0.017735271
+
##                 T1_148      T2_168       S1_165
+## 2001-01-01 0.001350138 0.009387634 0.0006800756
+## 2001-02-01 0.004128992 0.021550111 0.0018234107
+## 2001-03-01 0.005790954 0.028230231 0.0027351640
+## 2001-04-01 0.007805622 0.035553090 0.0041181754
+## 2001-05-01 0.010935626 0.043618759 0.0060356291
+## 2001-06-01 0.036222284 0.089241676 0.0199718719
+## 2001-07-01 0.043980093 0.104076386 0.0237846496
+## 2001-08-01 0.044724909 0.105758381 0.0247523152
+## 2001-09-01 0.039466634 0.094940612 0.0223564421
+## 2001-10-01 0.038070203 0.090829313 0.0216198297
+## 2001-11-01 0.035482727 0.082963657 0.0203128920
+## 2001-12-01 0.035431447 0.082517986 0.0204097623

The summary function can be also used to aggregate the output by species. In this case, the values of plant cohorts belonging to the same species will be averaged using LAI values as weights. For @@ -957,29 +957,29 @@

Plotting and summarizing results
 head(summary(S, freq="day", output="PlantStress", bySpecies = TRUE))

##            Pinus halepensis Quercus coccifera Quercus ilex
-## 2001-01-01       0.01457523       0.009607435   0.01041011
-## 2001-01-02       0.01781953       0.009469159   0.01192640
-## 2001-01-03       0.01969738       0.013155253   0.01501557
-## 2001-01-04       0.01406559       0.008715060   0.01183315
-## 2001-01-05       0.01700067       0.009026958   0.01318169
-## 2001-01-06       0.01338657       0.007526559   0.01138333
+## 2001-01-01 0.0002331295 0.0001072831 0.002895831 +## 2001-01-02 0.0008041126 0.0002485790 0.006536424 +## 2001-01-03 0.0011929996 0.0003735271 0.008731344 +## 2001-01-04 0.0008679062 0.0002814782 0.008365780 +## 2001-01-05 0.0012413979 0.0004017631 0.009116606 +## 2001-01-06 0.0011967864 0.0003658900 0.008517169

Or we can combine the aggregation by species with a temporal aggregation (here monthly averages):

 summary(S, freq="month", FUN = mean, output="PlantStress", bySpecies = TRUE)
##            Pinus halepensis Quercus coccifera Quercus ilex
-## 2001-01-01       0.01589339       0.008408768   0.01222980
-## 2001-02-01       0.03265345       0.017755565   0.02529637
-## 2001-03-01       0.03681798       0.019149198   0.03090886
-## 2001-04-01       0.04583556       0.025656179   0.03832254
-## 2001-05-01       0.06563614       0.036679819   0.05140293
-## 2001-06-01       0.12929291       0.070671160   0.08278718
-## 2001-07-01       0.09793163       0.052841040   0.07972567
-## 2001-08-01       0.09376091       0.051858714   0.08059816
-## 2001-09-01       0.06250372       0.034202963   0.06220892
-## 2001-10-01       0.05103023       0.026799135   0.05442120
-## 2001-11-01       0.02621790       0.014779172   0.04109262
-## 2001-12-01       0.02908624       0.017735271   0.04201542
+## 2001-01-01 0.001350138 0.0006800756 0.009387634 +## 2001-02-01 0.004128992 0.0018234107 0.021550111 +## 2001-03-01 0.005790954 0.0027351640 0.028230231 +## 2001-04-01 0.007805622 0.0041181754 0.035553090 +## 2001-05-01 0.010935626 0.0060356291 0.043618759 +## 2001-06-01 0.036222284 0.0199718719 0.089241676 +## 2001-07-01 0.043980093 0.0237846496 0.104076386 +## 2001-08-01 0.044724909 0.0247523152 0.105758381 +## 2001-09-01 0.039466634 0.0223564421 0.094940612 +## 2001-10-01 0.038070203 0.0216198297 0.090829313 +## 2001-11-01 0.035482727 0.0203128920 0.082963657 +## 2001-12-01 0.035431447 0.0204097623 0.082517986
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Basic water balance

Miquel De Caceres

-

2024-02-16

+

2024-02-18

Source: vignettes/runmodels/BasicWaterBalance.Rmd diff --git a/articles/runmodels/ForestDynamics.html b/articles/runmodels/ForestDynamics.html index 8aa6866d2..53d947e0c 100644 --- a/articles/runmodels/ForestDynamics.html +++ b/articles/runmodels/ForestDynamics.html @@ -73,7 +73,7 @@

Forest dynamics

Miquel De Caceres

-

2024-02-16

+

2024-02-18

Source: vignettes/runmodels/ForestDynamics.Rmd @@ -218,14 +218,14 @@

Executing the forest dynamics model 
## Package 'meteoland' [ver. 2.2.1]
## , (b) Regeneration nT = 2 nS = 1
 ## Simulating year 2002 (2/10):  (a) Growth/mortality, (b) Regeneration nT = 2 nS = 1
-## Simulating year 2003 (3/10):  (a) Growth/mortality, (b) Regeneration nT = 2 nS = 1
-## Simulating year 2004 (4/10):  (a) Growth/mortality, (b) Regeneration nT = 2 nS = 1
-## Simulating year 2005 (5/10):  (a) Growth/mortality, (b) Regeneration nT = 2 nS = 1
-## Simulating year 2006 (6/10):  (a) Growth/mortality, (b) Regeneration nT = 2 nS = 1
-## Simulating year 2007 (7/10):  (a) Growth/mortality, (b) Regeneration nT = 2 nS = 1
-## Simulating year 2008 (8/10):  (a) Growth/mortality, (b) Regeneration nT = 2 nS = 1
-## Simulating year 2009 (9/10):  (a) Growth/mortality, (b) Regeneration nT = 2 nS = 1
-## Simulating year 2010 (10/10):  (a) Growth/mortality, (b) Regeneration nT = 2 nS = 1
+## Simulating year 2003 (3/10): (a) Growth/mortality, (b) Regeneration nT = 3 nS = 1 +## Simulating year 2004 (4/10): (a) Growth/mortality, (b) Regeneration nT = 3 nS = 1 +## Simulating year 2005 (5/10): (a) Growth/mortality, (b) Regeneration nT = 3 nS = 1 +## Simulating year 2006 (6/10): (a) Growth/mortality, (b) Regeneration nT = 3 nS = 1 +## Simulating year 2007 (7/10): (a) Growth/mortality, (b) Regeneration nT = 3 nS = 1 +## Simulating year 2008 (8/10): (a) Growth/mortality, (b) Regeneration nT = 3 nS = 1 +## Simulating year 2009 (9/10): (a) Growth/mortality, (b) Regeneration nT = 3 nS = 1 +## Simulating year 2010 (10/10): (a) Growth/mortality, (b) Regeneration nT = 3 nS = 1

It is worth noting that, while fordyn() calls function growth() internally for each simulated year, the verbose option of the control parameters only affects @@ -249,50 +249,50 @@

Stand, species and cohort ## 1 0 2 2 1 1 ## 2 1 2 2 1 1 ## 3 2 2 2 1 1 -## 4 3 2 2 1 1 -## 5 4 2 2 1 1 -## 6 5 2 2 1 1 -## 7 6 2 2 1 1 -## 8 7 2 2 1 1 -## 9 8 2 2 1 1 -## 10 9 2 2 1 1 -## 11 10 2 2 1 1 +## 4 3 2 3 1 1 +## 5 4 2 3 1 1 +## 6 5 2 3 1 1 +## 7 6 2 3 1 1 +## 8 7 2 3 1 1 +## 9 8 2 3 1 1 +## 10 9 2 3 1 1 +## 11 10 2 3 1 1 ## TreeDensityLive TreeBasalAreaLive DominantTreeHeight DominantTreeDiameter ## 1 552.0000 25.03330 800.0000 37.55000 ## 2 551.3644 25.32289 812.8313 37.78966 ## 3 550.7188 25.61469 825.5780 38.03032 -## 4 550.0629 25.90776 838.2220 38.27164 -## 5 549.3948 26.20164 850.7510 38.51338 -## 6 548.7180 26.49638 863.1607 38.75544 -## 7 548.0307 26.79170 875.4467 38.99771 -## 8 547.3327 27.08732 887.6069 39.24014 -## 9 546.6219 27.38320 899.6407 39.48269 -## 10 545.9022 27.67948 911.5480 39.72534 -## 11 545.1756 27.97622 923.3286 39.96807 +## 4 3679.0629 26.15351 838.2220 38.27164 +## 5 3251.4846 26.45837 850.7492 38.51318 +## 6 3005.2983 26.77410 863.1602 38.75509 +## 7 2798.7014 27.09006 875.4487 38.99723 +## 8 2622.9426 27.40621 887.6123 39.23953 +## 9 2471.6686 27.72232 899.6499 39.48197 +## 10 2340.1585 28.03854 911.5604 39.72448 +## 11 2224.8072 28.35500 923.3444 39.96707 ## QuadraticMeanTreeDiameter HartBeckingIndex ShrubCoverLive BasalAreaDead ## 1 24.02949 53.20353 3.750000 0.00000000 ## 2 24.18200 52.39384 3.114516 0.03951377 ## 3 24.33519 51.61512 3.185849 0.04069554 ## 4 24.48859 50.86684 3.258765 0.04190932 -## 5 24.64206 50.14819 3.333464 0.04327298 -## 6 24.79555 49.45768 3.409758 0.04443010 -## 7 24.94898 48.79416 3.487687 0.04573470 -## 8 25.10223 48.15636 3.567260 0.04706887 -## 9 25.25537 47.54309 3.649451 0.04856686 -## 10 25.40836 46.95296 3.731452 0.04982932 -## 11 25.56121 46.38478 3.815185 0.05097037 +## 5 24.64150 50.14873 3.417919 0.08474981 +## 6 24.79447 49.45861 3.501407 0.07323843 +## 7 24.94728 48.79544 3.586409 0.07430295 +## 8 25.09994 48.15798 3.672982 0.07543670 +## 9 25.25242 47.54507 3.762147 0.07676580 +## 10 25.40469 46.95537 3.851005 0.07787602 +## 11 25.55679 46.38763 3.941568 0.07888338 ## ShrubCoverDead BasalAreaCut ShrubCoverCut ## 1 0.000000000 0 0 ## 2 0.005321188 0 0 ## 3 0.004831917 0 0 ## 4 0.004942545 0 0 -## 5 0.005069738 0 0 -## 6 0.005171709 0 0 -## 7 0.005290002 0 0 -## 8 0.005410814 0 0 -## 9 0.005549886 0 0 -## 10 0.005661046 0 0 -## 11 0.005755980 0 0 +## 5 0.005127846 0 0 +## 6 0.005305999 0 0 +## 7 0.005435275 0 0 +## 8 0.005566915 0 0 +## 9 0.005717195 0 0 +## 10 0.005838546 0 0 +## 11 0.005942939 0 0

Species-level analogous statistics are shown using:

 fd$SpeciesSummary
@@ -308,28 +308,28 @@

Stand, species and cohort ## 9 2 Quercus ilex 1 383.3275 6.600280 ## 10 3 Pinus halepensis 1 167.0792 19.220581 ## 11 3 Quercus coccifera 1 NA NA -## 12 3 Quercus ilex 1 382.9837 6.687179 -## 13 4 Pinus halepensis 1 166.7609 19.427080 +## 12 3 Quercus ilex 2 3511.9837 6.932931 +## 13 4 Pinus halepensis 1 166.7559 19.426297 ## 14 4 Quercus coccifera 1 NA NA -## 15 4 Quercus ilex 1 382.6339 6.774556 -## 16 5 Pinus halepensis 1 166.4381 19.633966 +## 15 4 Quercus ilex 2 3084.7286 7.032071 +## 16 5 Pinus halepensis 1 166.4277 19.632385 ## 17 5 Quercus coccifera 1 NA NA -## 18 5 Quercus ilex 1 382.2799 6.862410 -## 19 6 Pinus halepensis 1 166.1100 19.841010 +## 18 5 Quercus ilex 2 2838.8706 7.141718 +## 19 6 Pinus halepensis 1 166.0937 19.838571 ## 20 6 Quercus coccifera 1 NA NA -## 21 6 Quercus ilex 1 381.9207 6.950693 -## 22 7 Pinus halepensis 1 165.7763 20.048113 +## 21 6 Quercus ilex 2 2632.6078 7.251485 +## 22 7 Pinus halepensis 1 165.7536 20.044751 ## 23 7 Quercus coccifera 1 NA NA -## 24 7 Quercus ilex 1 381.5563 7.039204 -## 25 8 Pinus halepensis 1 165.4363 20.255089 +## 24 7 Quercus ilex 2 2457.1889 7.361457 +## 25 8 Pinus halepensis 1 165.4067 20.250723 ## 26 8 Quercus coccifera 1 NA NA -## 27 8 Quercus ilex 1 381.1856 7.128112 -## 28 9 Pinus halepensis 1 165.0916 20.462102 +## 27 8 Quercus ilex 2 2306.2619 7.471602 +## 28 9 Pinus halepensis 1 165.0546 20.456630 ## 29 9 Quercus coccifera 1 NA NA -## 30 9 Quercus ilex 1 380.8106 7.217375 -## 31 10 Pinus halepensis 1 164.7432 20.669212 +## 30 9 Quercus ilex 2 2175.1039 7.581911 +## 31 10 Pinus halepensis 1 164.6984 20.662556 ## 32 10 Quercus coccifera 1 NA NA -## 33 10 Quercus ilex 1 380.4324 7.307013 +## 33 10 Quercus ilex 2 2060.1088 7.692440 ## ShrubCoverLive BasalAreaDead ShrubCoverDead BasalAreaCut ShrubCoverCut ## 1 NA 0.000000000 NA 0 NA ## 2 3.750000 NA 0.000000000 NA 0 @@ -343,27 +343,27 @@

Stand, species and cohort ## 10 NA 0.035906911 NA 0 NA ## 11 3.258765 NA 0.004942545 NA 0 ## 12 NA 0.006002406 NA 0 NA -## 13 NA 0.037079647 NA 0 NA -## 14 3.333464 NA 0.005069738 NA 0 -## 15 NA 0.006193329 NA 0 NA -## 16 NA 0.038075601 NA 0 NA -## 17 3.409758 NA 0.005171709 NA 0 -## 18 NA 0.006354500 NA 0 NA -## 19 NA 0.039198091 NA 0 NA -## 20 3.487687 NA 0.005290002 NA 0 -## 21 NA 0.006536606 NA 0 NA -## 22 NA 0.040346233 NA 0 NA -## 23 3.567260 NA 0.005410814 NA 0 -## 24 NA 0.006722634 NA 0 NA -## 25 NA 0.041634961 NA 0 NA -## 26 3.649451 NA 0.005549886 NA 0 -## 27 NA 0.006931900 NA 0 NA -## 28 NA 0.042721946 NA 0 NA -## 29 3.731452 NA 0.005661046 NA 0 -## 30 NA 0.007107379 NA 0 NA -## 31 NA 0.043704887 NA 0 NA -## 32 3.815185 NA 0.005755980 NA 0 -## 33 NA 0.007265482 NA 0 NA +## 13 NA 0.037657616 NA 0 NA +## 14 3.417919 NA 0.005127846 NA 0 +## 15 NA 0.047092191 NA 0 NA +## 16 NA 0.038715279 NA 0 NA +## 17 3.501407 NA 0.005305999 NA 0 +## 18 NA 0.034523146 NA 0 NA +## 19 NA 0.039902965 NA 0 NA +## 20 3.586409 NA 0.005435275 NA 0 +## 21 NA 0.034399986 NA 0 NA +## 22 NA 0.041118276 NA 0 NA +## 23 3.672982 NA 0.005566915 NA 0 +## 24 NA 0.034318424 NA 0 NA +## 25 NA 0.042478586 NA 0 NA +## 26 3.762147 NA 0.005717195 NA 0 +## 27 NA 0.034287213 NA 0 NA +## 28 NA 0.043634249 NA 0 NA +## 29 3.851005 NA 0.005838546 NA 0 +## 30 NA 0.034241770 NA 0 NA +## 31 NA 0.044684338 NA 0 NA +## 32 3.941568 NA 0.005942939 NA 0 +## 33 NA 0.034199042 NA 0 NA

Package medfate provides a simple plot function for objects of class fordyn. For example, we can show the interannual variation in stand-level basal area using:

@@ -379,74 +379,96 @@

Tree/shrub tables 
 fd$TreeTable
-
##    Step Year Cohort          Species      DBH   Height        N Z50  Z95
-## 1     0   NA T1_148 Pinus halepensis 37.55000 800.0000 168.0000 100  600
-## 2     0   NA T2_168     Quercus ilex 14.60000 660.0000 384.0000 300 1000
-## 3     1 2001 T1_148 Pinus halepensis 37.78966 812.8313 167.6982 100  600
-## 4     1 2001 T2_168     Quercus ilex 14.70281 663.2086 383.6662 300 1000
-## 5     2 2002 T1_148 Pinus halepensis 38.03032 825.5780 167.3913 100  600
-## 6     2 2002 T2_168     Quercus ilex 14.80646 666.4497 383.3275 300 1000
-## 7     3 2003 T1_148 Pinus halepensis 38.27164 838.2220 167.0792 100  600
-## 8     3 2003 T2_168     Quercus ilex 14.91030 669.7017 382.9837 300 1000
-## 9     4 2004 T1_148 Pinus halepensis 38.51338 850.7510 166.7609 100  600
-## 10    4 2004 T2_168     Quercus ilex 15.01425 672.9614 382.6339 300 1000
-## 11    5 2005 T1_148 Pinus halepensis 38.75544 863.1607 166.4381 100  600
-## 12    5 2005 T2_168     Quercus ilex 15.11829 676.2270 382.2799 300 1000
-## 13    6 2006 T1_148 Pinus halepensis 38.99771 875.4467 166.1100 100  600
-## 14    6 2006 T2_168     Quercus ilex 15.22238 679.4963 381.9207 300 1000
-## 15    7 2007 T1_148 Pinus halepensis 39.24014 887.6069 165.7763 100  600
-## 16    7 2007 T2_168     Quercus ilex 15.32631 682.7619 381.5563 300 1000
-## 17    8 2008 T1_148 Pinus halepensis 39.48269 899.6407 165.4363 100  600
-## 18    8 2008 T2_168     Quercus ilex 15.43029 686.0295 381.1856 300 1000
-## 19    9 2009 T1_148 Pinus halepensis 39.72534 911.5480 165.0916 100  600
-## 20    9 2009 T2_168     Quercus ilex 15.53424 689.2958 380.8106 300 1000
-## 21   10 2010 T1_148 Pinus halepensis 39.96807 923.3286 164.7432 100  600
-## 22   10 2010 T2_168     Quercus ilex 15.63818 692.5602 380.4324 300 1000
+
##    Step Year Cohort          Species       DBH    Height         N Z50  Z95
+## 1     0   NA T1_148 Pinus halepensis 37.550000 800.00000  168.0000 100  600
+## 2     0   NA T2_168     Quercus ilex 14.600000 660.00000  384.0000 300 1000
+## 3     1 2001 T1_148 Pinus halepensis 37.789660 812.83132  167.6982 100  600
+## 4     1 2001 T2_168     Quercus ilex 14.702806 663.20859  383.6662 300 1000
+## 5     2 2002 T1_148 Pinus halepensis 38.030322 825.57799  167.3913 100  600
+## 6     2 2002 T2_168     Quercus ilex 14.806461 666.44970  383.3275 300 1000
+## 7     3 2003 T1_148 Pinus halepensis 38.271643 838.22196  167.0792 100  600
+## 8     3 2003 T2_168     Quercus ilex 14.910300 669.70171  382.9837 300 1000
+## 9     3 2003 T3_168     Quercus ilex  1.000000  47.23629 3129.0000 100 1000
+## 10    4 2004 T1_148 Pinus halepensis 38.513182 850.74915  166.7559 100  600
+## 11    4 2004 T2_168     Quercus ilex 15.013398 672.94123  382.6293 300 1000
+## 12    4 2004 T3_168     Quercus ilex  1.103375  54.92840 2702.0993 100 1000
+## 13    5 2005 T1_148 Pinus halepensis 38.755087 863.16018  166.4277 100  600
+## 14    5 2005 T2_168     Quercus ilex 15.116620 676.18825  382.2704 300 1000
+## 15    5 2005 T3_168     Quercus ilex  1.206802  62.62436 2456.6002 100 1000
+## 16    6 2006 T1_148 Pinus halepensis 38.997225 875.44867  166.0937 100  600
+## 17    6 2006 T2_168     Quercus ilex 15.219676 679.43251  381.9058 300 1000
+## 18    6 2006 T3_168     Quercus ilex  1.310379  70.33676 2250.7019 100 1000
+## 19    7 2007 T1_148 Pinus halepensis 39.239532 887.61228  165.7536 100  600
+## 20    7 2007 T2_168     Quercus ilex 15.322663 682.67612  381.5356 300 1000
+## 21    7 2007 T3_168     Quercus ilex  1.414080  78.06372 2075.6533 100 1000
+## 22    8 2008 T1_148 Pinus halepensis 39.481966 899.64989  165.4067 100  600
+## 23    8 2008 T2_168     Quercus ilex 15.425578 685.91808  381.1586 300 1000
+## 24    8 2008 T3_168     Quercus ilex  1.517867  85.80283 1925.1033 100 1000
+## 25    9 2009 T1_148 Pinus halepensis 39.724482 911.56037  165.0546 100  600
+## 26    9 2009 T2_168     Quercus ilex 15.528375 689.15612  380.7769 300 1000
+## 27    9 2009 T3_168     Quercus ilex  1.621711  93.55251 1794.3270 100 1000
+## 28   10 2010 T1_148 Pinus halepensis 39.967070 923.34440  164.6984 100  600
+## 29   10 2010 T2_168     Quercus ilex 15.631095 692.39075  380.3915 300 1000
+## 30   10 2010 T3_168     Quercus ilex  1.725601 101.31249 1679.7173 100 1000

The same can be shown for dead trees:

 fd$DeadTreeTable
-
##    Step Year Cohort          Species      DBH   Height         N N_starvation
-## 1     1 2001 T1_148 Pinus halepensis 37.78966 812.8313 0.3017709            0
-## 2     1 2001 T2_168     Quercus ilex 14.70281 663.2086 0.3338001            0
-## 3     2 2002 T1_148 Pinus halepensis 38.03032 825.5780 0.3069113            0
-## 4     2 2002 T2_168     Quercus ilex 14.80646 666.4497 0.3387482            0
-## 5     3 2003 T1_148 Pinus halepensis 38.27164 838.2220 0.3121288            0
-## 6     3 2003 T2_168     Quercus ilex 14.91030 669.7017 0.3437658            0
-## 7     4 2004 T1_148 Pinus halepensis 38.51338 850.7510 0.3182895            0
-## 8     4 2004 T2_168     Quercus ilex 15.01425 672.9614 0.3498056            0
-## 9     5 2005 T1_148 Pinus halepensis 38.75544 863.1607 0.3227688            0
-## 10    5 2005 T2_168     Quercus ilex 15.11829 676.2270 0.3539861            0
-## 11    6 2006 T1_148 Pinus halepensis 38.99771 875.4467 0.3281684            0
-## 12    6 2006 T2_168     Quercus ilex 15.22238 679.4963 0.3591678            0
-## 13    7 2007 T1_148 Pinus halepensis 39.24014 887.6069 0.3336200            0
-## 14    7 2007 T2_168     Quercus ilex 15.32631 682.7619 0.3643969            0
-## 15    8 2008 T1_148 Pinus halepensis 39.48269 899.6407 0.3400594            0
-## 16    8 2008 T2_168     Quercus ilex 15.43029 686.0295 0.3706929            0
-## 17    9 2009 T1_148 Pinus halepensis 39.72534 911.5480 0.3446877            0
-## 18    9 2009 T2_168     Quercus ilex 15.53424 689.2958 0.3750069            0
-## 19   10 2010 T1_148 Pinus halepensis 39.96807 923.3286 0.3483483            0
-## 20   10 2010 T2_168     Quercus ilex 15.63818 692.5602 0.3782701            0
-##    N_dessication N_burnt Z50  Z95
-## 1              0       0 100  600
-## 2              0       0 300 1000
-## 3              0       0 100  600
-## 4              0       0 300 1000
-## 5              0       0 100  600
-## 6              0       0 300 1000
-## 7              0       0 100  600
-## 8              0       0 300 1000
-## 9              0       0 100  600
-## 10             0       0 300 1000
-## 11             0       0 100  600
-## 12             0       0 300 1000
-## 13             0       0 100  600
-## 14             0       0 300 1000
-## 15             0       0 100  600
-## 16             0       0 300 1000
-## 17             0       0 100  600
-## 18             0       0 300 1000
-## 19             0       0 100  600
-## 20             0       0 300 1000
+
##    Step Year Cohort          Species       DBH    Height           N
+## 1     1 2001 T1_148 Pinus halepensis 37.789660 812.83132   0.3017709
+## 2     1 2001 T2_168     Quercus ilex 14.702806 663.20859   0.3338001
+## 3     2 2002 T1_148 Pinus halepensis 38.030322 825.57799   0.3069113
+## 4     2 2002 T2_168     Quercus ilex 14.806461 666.44970   0.3387482
+## 5     3 2003 T1_148 Pinus halepensis 38.271643 838.22196   0.3121288
+## 6     3 2003 T2_168     Quercus ilex 14.910300 669.70171   0.3437658
+## 7     4 2004 T1_148 Pinus halepensis 38.513182 850.74915   0.3232541
+## 8     4 2004 T2_168     Quercus ilex 15.013398 672.94123   0.3543510
+## 9     4 2004 T3_168     Quercus ilex  1.103375  54.92840 426.9007046
+## 10    5 2005 T1_148 Pinus halepensis 38.755087 863.16018   0.3281973
+## 11    5 2005 T2_168     Quercus ilex 15.116620 676.18825   0.3589506
+## 12    5 2005 T3_168     Quercus ilex  1.206802  62.62436 245.4991251
+## 13    6 2006 T1_148 Pinus halepensis 38.997225 875.44867   0.3340780
+## 14    6 2006 T2_168     Quercus ilex 15.219676 679.43251   0.3645662
+## 15    6 2006 T3_168     Quercus ilex  1.310379  70.33676 205.8982267
+## 16    7 2007 T1_148 Pinus halepensis 39.239532 887.61228   0.3400144
+## 17    7 2007 T2_168     Quercus ilex 15.322663 682.67612   0.3702317
+## 18    7 2007 T3_168     Quercus ilex  1.414080  78.06372 175.0486103
+## 19    8 2008 T1_148 Pinus halepensis 39.481966 899.64989   0.3469625
+## 20    8 2008 T2_168     Quercus ilex 15.425578 685.91808   0.3769852
+## 21    8 2008 T3_168     Quercus ilex  1.517867  85.80283 150.5500638
+## 22    9 2009 T1_148 Pinus halepensis 39.724482 911.56037   0.3520636
+## 23    9 2009 T2_168     Quercus ilex 15.528375 689.15612   0.3817231
+## 24    9 2009 T3_168     Quercus ilex  1.621711  93.55251 130.7762670
+## 25   10 2010 T1_148 Pinus halepensis 39.967070 923.34440   0.3561728
+## 26   10 2010 T2_168     Quercus ilex 15.631095 692.39075   0.3853878
+## 27   10 2010 T3_168     Quercus ilex  1.725601 101.31249 114.6097312
+##    N_starvation N_dessication N_burnt Z50  Z95
+## 1             0             0       0 100  600
+## 2             0             0       0 300 1000
+## 3             0             0       0 100  600
+## 4             0             0       0 300 1000
+## 5             0             0       0 100  600
+## 6             0             0       0 300 1000
+## 7             0             0       0 100  600
+## 8             0             0       0 300 1000
+## 9             0             0       0 100 1000
+## 10            0             0       0 100  600
+## 11            0             0       0 300 1000
+## 12            0             0       0 100 1000
+## 13            0             0       0 100  600
+## 14            0             0       0 300 1000
+## 15            0             0       0 100 1000
+## 16            0             0       0 100  600
+## 17            0             0       0 300 1000
+## 18            0             0       0 100 1000
+## 19            0             0       0 100  600
+## 20            0             0       0 300 1000
+## 21            0             0       0 100 1000
+## 22            0             0       0 100  600
+## 23            0             0       0 300 1000
+## 24            0             0       0 100 1000
+## 25            0             0       0 100  600
+## 26            0             0       0 300 1000
+## 27            0             0       0 100 1000

Accessing the output from function growth() diff --git a/articles/runmodels/ForestDynamics_files/figure-html/unnamed-chunk-11-1.png b/articles/runmodels/ForestDynamics_files/figure-html/unnamed-chunk-11-1.png index 20261614d..89ed23e3c 100644 Binary files a/articles/runmodels/ForestDynamics_files/figure-html/unnamed-chunk-11-1.png and b/articles/runmodels/ForestDynamics_files/figure-html/unnamed-chunk-11-1.png differ diff --git a/articles/runmodels/ForestDynamics_files/figure-html/unnamed-chunk-15-1.png b/articles/runmodels/ForestDynamics_files/figure-html/unnamed-chunk-15-1.png index c815dd6c1..17825f68a 100644 Binary files a/articles/runmodels/ForestDynamics_files/figure-html/unnamed-chunk-15-1.png and b/articles/runmodels/ForestDynamics_files/figure-html/unnamed-chunk-15-1.png differ diff --git a/articles/runmodels/ForestGrowth.html b/articles/runmodels/ForestGrowth.html index 08b4ee879..4c996ce0e 100644 --- a/articles/runmodels/ForestGrowth.html +++ b/articles/runmodels/ForestGrowth.html @@ -73,7 +73,7 @@

Forest growth

Miquel De Caceres

-

2024-02-16

+

2024-02-18

Source: vignettes/runmodels/ForestGrowth.Rmd @@ -506,9 +506,9 @@

Growth evaluationevaluation_stats(G1, exampleobs, "BAI", cohort = "T1_148", temporalResolution = "month")

##          n       Bias   Bias.rel        MAE    MAE.rel          r        NSE 
-## 12.0000000 -0.1139363 -8.7934517  0.1960732 15.1326723  0.9746096  0.9341656 
+## 12.0000000 -0.1300031 -9.9105778  0.1323675 10.0908246  0.9976550  0.9752268 
 ##    NSE.abs 
-##  0.8055017
+## 0.8648346

The observed data set is fake and the evaluation is unrealistically good. For illustrative purposes, we also compare diameter increment values, here drawing the observed and predicted time series diff --git a/articles/runmodels/ForestGrowth_files/figure-html/unnamed-chunk-27-1.png b/articles/runmodels/ForestGrowth_files/figure-html/unnamed-chunk-27-1.png index 9b3632644..1095e1fae 100644 Binary files a/articles/runmodels/ForestGrowth_files/figure-html/unnamed-chunk-27-1.png and b/articles/runmodels/ForestGrowth_files/figure-html/unnamed-chunk-27-1.png differ diff --git a/articles/runmodels/ForestGrowth_files/figure-html/unnamed-chunk-29-1.png b/articles/runmodels/ForestGrowth_files/figure-html/unnamed-chunk-29-1.png index f8ddd2fdb..56a2958df 100644 Binary files a/articles/runmodels/ForestGrowth_files/figure-html/unnamed-chunk-29-1.png and b/articles/runmodels/ForestGrowth_files/figure-html/unnamed-chunk-29-1.png differ diff --git a/articles/runmodels/Sureau.html b/articles/runmodels/Sureau.html index b6116d8fd..62724e0ad 100644 --- a/articles/runmodels/Sureau.html +++ b/articles/runmodels/Sureau.html @@ -73,7 +73,7 @@

Example_SurEau

Miquel De Caceres

-

2024-02-16

+

2024-02-18

Source: vignettes/runmodels/Sureau.Rmd @@ -135,12 +135,12 @@

Sureau network input## ..$ gsMax : num 285 ## ..$ gmin_S : num 3.09 ## ..$ gsNight : num 14.2 -## ..$ VCleaf_P50 : num -1.2 -## ..$ VCleaf_slope : num 115 +## ..$ VCleaf_P50 : num -4.46 +## ..$ VCleaf_slope : num 45.9 ## ..$ VCstem_P50 : num -4.46 ## ..$ VCstem_slope : num 45.9 -## ..$ VCroot_P50 : num -0.88 -## ..$ VCroot_slope : num 103 +## ..$ VCroot_P50 : num -4.46 +## ..$ VCroot_slope : num 45.9 ## ..$ PiFullTurgor_Leaf: num -1.59 ## ..$ epsilonSym_Leaf : num 8.92 ## ..$ PiFullTurgor_Stem: num -2.01 @@ -165,8 +165,8 @@

Sureau network input## $ k_SSym : num 0.26 ## $ k_LSym : num 8 ## $ k_RSApo : num [1:4] 0.8575 0.35519 0.04126 0.00738 -## $ k_SoilToStem : num [1:4] 0.85629 0.3537 0.0411 0.00736 -## $ k_Soil : num [1:4] 607.38 84.32 10.67 3.49 +## $ k_SoilToStem : num [1:4] 0.85749 0.35519 0.04126 0.00738 +## $ k_Soil : num [1:4] 362138 50273 6359 2081 ## $ k_Plant : num 0.747 ## $ Q_SApo_sat_mmol_perLeafArea: num 316823 ## $ Q_LApo_sat_mmol_perLeafArea: num 10298 diff --git a/articles/workedexamples/FontBlanche.html b/articles/workedexamples/FontBlanche.html index 72f0d4987..e9657fd1c 100644 --- a/articles/workedexamples/FontBlanche.html +++ b/articles/workedexamples/FontBlanche.html @@ -74,7 +74,7 @@

Soil and plant water balances at

Miquel De Caceres (CREAF), Nicolas Martin-StPaul (INRA)

-

2024-02-16

+

2024-02-18

Source: vignettes/workedexamples/FontBlanche.Rmd @@ -156,7 +156,7 @@

Soil 
##   widths clay sand om   bd rfc
 ## 1    300   39   26  6 1.45  50
 ## 2    700   39   26  3 1.45  65
-## 3   1000   39   26  1 1.45  85
+## 3   1000   39   26  1 1.45  90
 ## 4   2500   39   26  1 1.45  95

The soil input for function spwb() is actually an object of class soil that is created using a function with the @@ -186,9 +186,9 @@

Soil ## ## Layer 3 [ 1000 to 2000 mm ] ## clay (%): 39 silt (%): 34 sand (%): 26 organic matter (%): 1 [ Clay loam ] -## Rock fragment content (%): 85 Macroporosity (%): 7 +## Rock fragment content (%): 90 Macroporosity (%): 7 ## Theta WP (%): 24 Theta FC (%): 37 Theta SAT (%): 47 Theta current (%) 37 -## Vol. WP (mm): 35 Vol. FC (mm): 56 Vol. SAT (mm): 70 Vol. current (mm): 56 +## Vol. WP (mm): 24 Vol. FC (mm): 37 Vol. SAT (mm): 47 Vol. current (mm): 37 ## Temperature (Celsius): NA ## ## Layer 4 [ 2000 to 4500 mm ] @@ -198,10 +198,10 @@

Soil ## Vol. WP (mm): 29 Vol. FC (mm): 47 Vol. SAT (mm): 58 Vol. current (mm): 47 ## Temperature (Celsius): NA ## -## Total soil saturated capacity (mm): 330 -## Total soil water holding capacity (mm): 254 -## Total soil extractable water (mm): 115 -## Total soil current Volume (mm): 254 +## Total soil saturated capacity (mm): 306 +## Total soil water holding capacity (mm): 235 +## Total soil extractable water (mm): 106 +## Total soil current Volume (mm): 235 ## ## Snow pack water equivalent (mm): 0 ## Soil water table depth (mm): 4500 @@ -229,18 +229,22 @@

Species parameters
 fb$customParams
-
##   SpIndex Cohort VCstem_P12 VCstem_P50 VCstem_P88 VCstem_slope VCroot_P12
-## 1     142 T1_142  -1.971750      -6.50 -11.028250           11         NA
-## 2     148 T2_148  -3.707158      -4.79  -5.872842           46         -1
-## 3     168 T3_168  -4.739642      -6.40  -8.060358           30         NA
-##   VCroot_P50 VCroot_P88 VCroot_slope VCleaf_kmax LeafEPS LeafPI0 LeafAF StemEPS
-## 1         NA         NA           NA        3.00   12.38   -2.13    0.5   12.38
-## 2  -1.741565  -2.301482           NA        4.00    5.31   -1.50    0.6    5.00
-## 3         NA         NA           NA        2.63   15.00   -2.50    0.4   15.00
-##   StemPI0 StemAF Gswmin Gswmax    Gs_P50 Gs_slope    Al2As
-## 1   -2.13    0.4  0.002 0.2200 -2.207094 89.41176       NA
-## 2   -1.65    0.4  0.001 0.2175 -1.871216 97.43590  631.000
-## 3   -2.50    0.4  0.002 0.2200 -2.114188 44.70588 1540.671
+
##               Species VCleaf_P12 VCleaf_P50 VCleaf_P88 VCleaf_slope VCstem_P12
+## 1 Phillyrea latifolia         NA         NA         NA           NA  -1.971750
+## 2    Pinus halepensis         NA         NA         NA           NA  -3.707158
+## 3        Quercus ilex         NA         NA         NA           NA  -4.739642
+##   VCstem_P50 VCstem_P88 VCstem_slope VCroot_P12 VCroot_P50 VCroot_P88
+## 1      -6.50 -11.028250           11         NA         NA         NA
+## 2      -4.79  -5.872842           46         -1  -1.741565  -2.301482
+## 3      -6.40  -8.060358           30         NA         NA         NA
+##   VCroot_slope VCleaf_kmax LeafEPS LeafPI0 LeafAF StemEPS StemPI0 StemAF Gswmin
+## 1           NA        3.00   12.38   -2.13    0.5   12.38   -2.13    0.4  0.002
+## 2           NA        4.00    5.31   -1.50    0.6    5.00   -1.65    0.4  0.001
+## 3           NA        2.63   15.00   -2.50    0.4   15.00   -2.50    0.4  0.002
+##   Gswmax    Gs_P50 Gs_slope    Al2As
+## 1 0.2200 -2.207094 89.41176       NA
+## 2 0.2175 -1.871216 97.43590  631.000
+## 3 0.2200 -2.114188 44.70588 1540.671

We can use function modifySpParams() to replace the values of parameters for the desired traits, leaving the rest unaltered:

@@ -604,29 +608,29 @@

Running the model
 fb_SWB <- spwb(fb_x, fb_meteo, elevation = 420, latitude = 43.24083)
## Package 'meteoland' [ver. 2.2.1]
-
## Initial plant water content (mm): 31.8572
-## Initial soil water content (mm): 230.303
+
## Initial plant water content (mm): 31.8864
+## Initial soil water content (mm): 213.886
 ## Initial snowpack content (mm): 0
 ## Performing daily simulations
 ## 
 ##  [Year 2014]:....................................
 ## 
-## Final plant water content (mm): 31.8442
-## Final soil water content (mm): 222.538
+## Final plant water content (mm): 19.7795
+## Final soil water content (mm): 209.81
 ## Final snowpack content (mm): 0
-## Change in plant water content (mm): -0.0129855
-## Plant water balance result (mm): -6.31368e-17
-## Change in soil water content (mm): -7.76455
-## Soil water balance result (mm): 106.206
+## Change in plant water content (mm): -12.1068
+## Plant water balance result (mm): 1.03427e-15
+## Change in soil water content (mm): -4.07556
+## Soil water balance result (mm): 128.999
 ## Change in snowpack water content (mm): 0
 ## Snowpack water balance result (mm): 0
 ## Water balance components:
 ##   Precipitation (mm) 1066
 ##   Rain (mm) 1066 Snow (mm) 0
 ##   Interception (mm) 141 Net rainfall (mm) 925
-##   Infiltration (mm) 461 Runoff (mm) 464 Deep drainage (mm) 35
-##   Soil evaporation (mm) 11  Herbaceous transpiration (mm) 0 Woody plant transpiration (mm) 309
-##   Plant extraction from soil (mm) 309  Plant water balance (mm) -0 Hydraulic redistribution (mm) 52

+##   Infiltration (mm) 447 Runoff (mm) 478 Deep drainage (mm) 9
+##   Soil evaporation (mm) 9  Herbaceous transpiration (mm) 0 Woody plant transpiration (mm) 300
+##   Plant extraction from soil (mm) 300  Plant water balance (mm) 0 Hydraulic redistribution (mm) 50

Console output provides the water balance totals for the period considered, which may span several years. The output of function spwb() is an object of class with the same name, actually a @@ -654,26 +658,26 @@

Running the model## 2014-01-05 2.0447148 0.000000 0.000000 0 0.0000000 0 ## 2014-01-06 0.9330456 0.000000 0.000000 0 0.0000000 0 ## Infiltration Runoff DeepDrainage Evapotranspiration Interception -## 2014-01-01 0.0000000 0 0.004044955 0.2302227 0.00000 -## 2014-01-02 0.0000000 0 0.004049537 0.1959278 0.00000 -## 2014-01-03 0.0000000 0 0.004054056 0.1405035 0.00000 -## 2014-01-04 0.7213133 0 0.004058671 1.9682133 1.86936 -## 2014-01-05 0.0000000 0 0.004058257 0.4813200 0.00000 -## 2014-01-06 0.0000000 0 0.004052525 0.4341078 0.00000 +## 2014-01-01 0.0000000 0 0.004043731 0.2355285 0.00000 +## 2014-01-02 0.0000000 0 0.004045897 0.1959278 0.00000 +## 2014-01-03 0.0000000 0 0.004048036 0.1400658 0.00000 +## 2014-01-04 0.7213133 0 0.004050273 1.9680840 1.86936 +## 2014-01-05 0.0000000 0 0.004035678 1.3082763 0.00000 +## 2014-01-06 0.0000000 0 0.004010134 0.8389883 0.00000 ## SoilEvaporation HerbTranspiration PlantExtraction Transpiration -## 2014-01-01 0.21454034 0 1.568232e-02 0.01568232 -## 2014-01-02 0.19592778 0 4.065758e-19 0.00000000 -## 2014-01-03 0.13188014 0 8.623330e-03 0.00862333 -## 2014-01-04 0.09885303 0 1.431147e-17 0.00000000 -## 2014-01-05 0.11729664 0 3.640233e-01 0.36402332 -## 2014-01-06 0.08343541 0 3.506724e-01 0.35067242 +## 2014-01-01 0.21454034 0 2.098815e-02 0.020988148 +## 2014-01-02 0.19592778 0 -8.402567e-19 0.000000000 +## 2014-01-03 0.13158239 0 8.483367e-03 0.008483367 +## 2014-01-04 0.09872381 0 6.938894e-18 0.000000000 +## 2014-01-05 0.11716244 0 1.191114e+00 1.191113898 +## 2014-01-06 0.06883559 0 7.701527e-01 0.770152695 ## HydraulicRedistribution ## 2014-01-01 0.000000000 -## 2014-01-02 0.006037314 -## 2014-01-03 0.009166955 -## 2014-01-04 0.015757045 -## 2014-01-05 0.003833663 -## 2014-01-06 0.010103030 +## 2014-01-02 0.006148750 +## 2014-01-03 0.009327612 +## 2014-01-04 0.016023155 +## 2014-01-05 0.002212903 +## 2014-01-06 0.006349963

Comparing results with observations @@ -747,9 +751,9 @@

Stand evapotranspiration
 evaluation_stats(fb_SWB, fb_observed, type = "SE+TR")

##           n        Bias    Bias.rel         MAE     MAE.rel           r 
-## 365.0000000  -0.4567212 -34.2786501   0.6308529  47.3478872   0.5225861 
+## 365.0000000  -0.4858695 -36.4663375   0.8137626  61.0759530   0.5636700 
 ##         NSE     NSE.abs 
-##  -0.4631060  -0.2669829
+## -1.5106731 -0.6343325

Soil moisture @@ -776,9 +780,9 @@

Soil moisture
 evaluation_stats(fb_SWB, fb_observed, type = "REW")

##            n         Bias     Bias.rel          MAE      MAE.rel            r 
-## 364.00000000   0.08130738  11.59342887   0.13999188  19.96111529   0.79753335 
+## 364.00000000   0.01975867   2.81734292   0.08552408  12.19467790   0.91752414 
 ##          NSE      NSE.abs 
-##   0.50396283   0.32919501
+## 0.75550133 0.59019069

Plant transpiration @@ -804,15 +808,15 @@

Plant transpiration
 evaluation_stats(fb_SWB, fb_observed, cohort = "T2_148", type="E")

##            n         Bias     Bias.rel          MAE      MAE.rel            r 
-## 300.00000000   0.06899375  33.54558192   0.11515494  55.98970317   0.54018109 
+## 300.00000000   0.07791512  37.88325613   0.27619960 134.29152897   0.57659331 
 ##          NSE      NSE.abs 
-##  -1.33724099  -0.16369997
+## -9.64213859 -1.79113909 
 evaluation_stats(fb_SWB, fb_observed, cohort = "T3_168", type="E")
##            n         Bias     Bias.rel          MAE      MAE.rel            r 
-## 309.00000000   0.10956705  37.85240494   0.12412490  42.88174347   0.88132336 
+## 309.00000000   0.05170847  17.86385401   0.29006885 100.21081805   0.57392818 
 ##          NSE      NSE.abs 
-##   0.09417969   0.15436314
+## -3.60360469 -0.97617808

Leaf water potentials @@ -1030,45 +1034,45 @@

Generating output summaries## 2014-10-01 63.53896 50.60000 50.60000 0 41.9066889 0 ## 2014-11-01 30.12083 222.60000 222.60000 0 198.0975096 0 ## 2014-12-01 26.01617 93.00000 93.00000 0 78.7534201 0 -## Infiltration Runoff DeepDrainage Evapotranspiration -## 2014-01-01 106.3075047 76.2692860 1.824623e-01 29.56393 -## 2014-02-01 82.0295477 73.2277525 1.063892e+01 37.76379 -## 2014-03-01 29.3392677 10.5524374 1.553201e+01 33.43340 -## 2014-04-01 7.2713589 0.0000000 5.635432e+00 44.72315 -## 2014-05-01 16.1038012 0.2243621 2.043486e+00 54.13042 -## 2014-06-01 25.5551985 0.3287505 6.056313e-01 69.00056 -## 2014-07-01 0.1428946 0.0000000 1.000713e-01 37.82908 -## 2014-08-01 17.2923364 35.5102204 1.748419e-03 34.85508 -## 2014-09-01 42.6486923 83.2470319 2.215849e-05 31.40472 -## 2014-10-01 17.3132699 24.5934191 3.534936e-05 30.70022 -## 2014-11-01 67.4784639 130.6190457 9.151247e-05 33.78054 -## 2014-12-01 49.0788900 29.6745300 3.071558e-04 23.37883 -## Interception SoilEvaporation HerbTranspiration PlantExtraction -## 2014-01-01 22.4713498 1.8266292 0 5.265954 -## 2014-02-01 25.8391081 1.7108734 0 10.213808 -## 2014-03-01 4.7207713 2.1718478 0 26.540785 -## 2014-04-01 7.7286411 0.5153570 0 36.479147 -## 2014-05-01 5.2718367 0.3208468 0 48.537740 -## 2014-06-01 7.7160510 0.2120841 0 61.072427 -## 2014-07-01 0.4571054 0.1472336 0 37.224740 -## 2014-08-01 7.5974432 0.1415725 0 27.116067 -## 2014-09-01 11.7042748 0.1253501 0 19.575096 -## 2014-10-01 8.6933111 0.2066293 0 21.800282 -## 2014-11-01 24.5024904 1.1452126 0 8.132835 -## 2014-12-01 14.2465799 2.0520483 0 7.080198 -## Transpiration HydraulicRedistribution -## 2014-01-01 5.265954 1.067117 -## 2014-02-01 10.213808 0.505925 -## 2014-03-01 26.540785 1.116502 -## 2014-04-01 36.479147 1.883272 -## 2014-05-01 48.537740 2.620689 -## 2014-06-01 61.072427 4.849620 -## 2014-07-01 37.224740 4.177675 -## 2014-08-01 27.116067 5.920486 -## 2014-09-01 19.575096 6.587488 -## 2014-10-01 21.800282 8.317284 -## 2014-11-01 8.132835 9.991313 -## 2014-12-01 7.080198 4.595628 +## Infiltration Runoff DeepDrainage Evapotranspiration Interception +## 2014-01-01 105.6926965 76.884094 1.489993e-01 37.842937 22.4713498 +## 2014-02-01 82.5533425 72.703958 2.157036e+00 50.431550 25.8391081 +## 2014-03-01 30.8785403 9.013165 5.210121e+00 72.738964 4.7207713 +## 2014-04-01 7.2713589 0.000000 1.352726e+00 91.055003 7.7286411 +## 2014-05-01 16.3281633 0.000000 6.342456e-02 64.532566 5.2718367 +## 2014-06-01 25.8839490 0.000000 6.932312e-07 39.430349 7.7160510 +## 2014-07-01 0.1428946 0.000000 1.219688e-07 8.926743 0.4571054 +## 2014-08-01 18.0726432 34.729914 8.281271e-08 12.124911 7.5974432 +## 2014-09-01 41.9593682 83.936356 2.327626e-07 16.557205 11.7042748 +## 2014-10-01 15.4607993 26.445890 9.145557e-07 13.203868 8.6933111 +## 2014-11-01 54.1792430 143.918267 2.270922e-06 26.920300 24.5024904 +## 2014-12-01 48.4837019 30.269718 4.338650e-06 16.160213 14.2465799 +## SoilEvaporation HerbTranspiration PlantExtraction Transpiration +## 2014-01-01 1.79496105 0 13.576626 13.576626 +## 2014-02-01 2.16884684 0 22.423595 22.423595 +## 2014-03-01 1.64202559 0 66.376168 66.376168 +## 2014-04-01 0.22242883 0 83.103933 83.103933 +## 2014-05-01 0.03567143 0 59.225058 59.225058 +## 2014-06-01 0.01424565 0 31.700052 31.700052 +## 2014-07-01 0.00000000 0 8.469637 8.469637 +## 2014-08-01 0.04548686 0 4.481981 4.481981 +## 2014-09-01 0.09045928 0 4.762471 4.762471 +## 2014-10-01 0.68995549 0 3.820601 3.820601 +## 2014-11-01 1.11267067 0 1.305139 1.305139 +## 2014-12-01 0.85803677 0 1.055597 1.055597 +## HydraulicRedistribution +## 2014-01-01 0.6722996 +## 2014-02-01 0.2313978 +## 2014-03-01 1.0975995 +## 2014-04-01 5.6907891 +## 2014-05-01 14.4989429 +## 2014-06-01 11.2760214 +## 2014-07-01 0.2218172 +## 2014-08-01 4.8755086 +## 2014-09-01 4.3544596 +## 2014-10-01 3.9836520 +## 2014-11-01 2.1810951 +## 2014-12-01 0.7433501

Parameter output is used to indicate the element of the spwb object for which we desire summaries. Similarly, it is possible to calculate the average stress of the three tree species by @@ -1076,18 +1080,18 @@

Generating output summaries
 summary(fb_SWB, freq="months",FUN=mean, output="PlantStress", bySpecies = TRUE)

##            Phillyrea latifolia Pinus halepensis Quercus ilex
-## 2014-01-01         0.001153786      0.009741856  0.003852492
-## 2014-02-01         0.002647338      0.018298538  0.006063052
-## 2014-03-01         0.009046174      0.050243872  0.017265760
-## 2014-04-01         0.016045402      0.076802710  0.029477695
-## 2014-05-01         0.029469726      0.119155735  0.051515501
-## 2014-06-01         0.072204852      0.223345672  0.103716881
-## 2014-07-01         0.329134848      0.580405266  0.285005116
-## 2014-08-01         0.472435783      0.715235269  0.391770370
-## 2014-09-01         0.421657889      0.647243655  0.357022997
-## 2014-10-01         0.062795227      0.170944203  0.081105276
-## 2014-11-01         0.025295614      0.059070843  0.032334175
-## 2014-12-01         0.006891936      0.014029414  0.006678394
+## 2014-01-01 0.0004433573 3.278079e-05 8.205441e-06 +## 2014-02-01 0.0010020336 6.922987e-05 2.002251e-05 +## 2014-03-01 0.0041604112 1.016083e-03 2.357837e-04 +## 2014-04-01 0.0154083646 8.558489e-03 3.084838e-03 +## 2014-05-01 0.2318173799 3.595759e-01 1.615418e-01 +## 2014-06-01 0.4844323573 9.176857e-01 5.598546e-01 +## 2014-07-01 0.7389237506 1.000000e+00 8.646694e-01 +## 2014-08-01 0.6116679612 1.000000e+00 1.000000e+00 +## 2014-09-01 0.4429184720 1.000000e+00 1.000000e+00 +## 2014-10-01 0.3700286698 1.000000e+00 1.000000e+00 +## 2014-11-01 0.3400187283 1.000000e+00 1.000000e+00 +## 2014-12-01 0.3119629065 1.000000e+00 1.000000e+00

In this case, the summary function aggregates the output by species using LAI values as weights.

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Water pools and species interactions

Miquel De Caceres (CREAF)

-

2024-02-16

+

2024-02-18

Source: vignettes/workedexamples/PlantWaterPools.Rmd diff --git a/pkgdown.yml b/pkgdown.yml index 3cf4a4c00..a86a98959 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -17,5 +17,5 @@ articles: Sureau: runmodels/Sureau.html FontBlanche: workedexamples/FontBlanche.html PlantWaterPools: workedexamples/PlantWaterPools.html -last_built: 2024-02-16T15:56Z +last_built: 2024-02-18T17:48Z diff --git a/reference/Rplot002.png b/reference/Rplot002.png index ffb0f6f84..2bb5e7668 100644 Binary files a/reference/Rplot002.png and b/reference/Rplot002.png differ diff --git a/reference/Rplot003.png b/reference/Rplot003.png index 48ba40c77..d3e2ea7e8 100644 Binary files a/reference/Rplot003.png and b/reference/Rplot003.png differ diff --git a/reference/Rplot004.png b/reference/Rplot004.png index 7bbd149c4..66abc18f8 100644 Binary files a/reference/Rplot004.png and b/reference/Rplot004.png differ diff --git a/reference/Rplot005.png b/reference/Rplot005.png index eee7835b0..4af17fec9 100644 Binary files a/reference/Rplot005.png and b/reference/Rplot005.png differ diff --git a/reference/aspwb.html b/reference/aspwb.html index 43d90c27c..6178e94b4 100644 --- a/reference/aspwb.html +++ b/reference/aspwb.html @@ -144,6 +144,7 @@

Examples

#Call simulation function S <- aspwb(x, examplemeteo, latitude = 41.82592, elevation = 100) +#> Package 'meteoland' [ver. 2.2.1] #> Initial soil water content (mm): 290.875 #> Initial snowpack content (mm): 0 #> Performing daily simulations diff --git a/reference/evaluation-1.png b/reference/evaluation-1.png index b9d6fd607..0318a5a28 100644 Binary files a/reference/evaluation-1.png and b/reference/evaluation-1.png differ diff --git a/reference/evaluation.html b/reference/evaluation.html index d65ce8459..1673e5c3c 100644 --- a/reference/evaluation.html +++ b/reference/evaluation.html @@ -159,7 +159,8 @@

Details

  • "DBH": For each plant cohort whose growth is to be evaluated, a column starting with "DBH_" and continuing with a cohort name (e.g. "DBH_T1_68") with DBH values in cm.

  • "Height": For each plant cohort whose growth is to be evaluated, a column starting with "Height_" and continuing with a cohort name (e.g. "Height_T1_68") with Height values in cm.

    • Additional columns may exist with the standard error of measured quantities. These should be named as the referred quantity, followed by "_err" (e.g. "PD_T1_68_err"), and are used to draw confidence intervals around observations.

    -

    Row names in measuredData indicate the date of measurement (in the case of days). If measurements refer to months or years, row names should also be in a "year-month-day" format, although with "01" for days and/or months (e.g. "2001-02-01" for february 2001, or "2001-01-01" for year 2001).

    +

    Row names in measuredData indicate the date of measurement (in the case of days). Alternatively, a column called "dates" can contain the measurement dates. +If measurements refer to months or years, row names should also be in a "year-month-day" format, although with "01" for days and/or months (e.g. "2001-02-01" for february 2001, or "2001-01-01" for year 2001).

    References

    @@ -225,14 +226,14 @@

    Examples

    #Evaluation statistics for soil water content evaluation_stats(S1, exampleobs) -#> n Bias Bias.rel MAE MAE.rel r -#> 365.00000000 0.03944408 14.25792968 0.03960729 14.31692719 0.82636503 -#> NSE NSE.abs -#> -2.50169230 -1.18830203 +#> n Bias Bias.rel MAE MAE.rel +#> 365.000000000 -0.002178275 -0.684413198 0.007515571 2.361389876 +#> r NSE NSE.abs +#> 0.969546409 0.936494713 0.748304328 #NSE only evaluation_metric(S1, exampleobs, metric="NSE") -#> [1] -2.501692 +#> [1] 0.9364947 #Comparison of temporal dynamics evaluation_plot(S1, exampleobs) @@ -240,7 +241,7 @@

    Examples

    #Loglikelihood value evaluation_metric(S1, exampleobs) -#> [1] 389.0348 +#> [1] 855.6326
    diff --git a/reference/exampleobs.html b/reference/exampleobs.html index 6dbf41906..4a79476c2 100644 --- a/reference/exampleobs.html +++ b/reference/exampleobs.html @@ -58,7 +58,10 @@

    Example observed data

    Format

    -

    A data frame containing daily 'observed' values for year 2001:

    SWC
    +

    A data frame containing daily 'observed' values for year 2001:

    dates
    +

    Measurement dates.

    + +
    SWC

    Soil moisture content (in m3/m3).

    ETR
    diff --git a/reference/growth.html b/reference/growth.html index 65accc4c1..3ba7e5668 100644 --- a/reference/growth.html +++ b/reference/growth.html @@ -234,7 +234,7 @@

    Examples

    #Call simulation function G2 <-growth(x2, examplemeteo, latitude = 41.82592, elevation = 100) -#> Initial plant cohort biomass (g/m2): 6248.36 +#> Initial plant cohort biomass (g/m2): 6793.08 #> Initial plant water content (mm): 6.78662 #> Initial soil water content (mm): 290.875 #> Initial snowpack content (mm): 0 @@ -242,28 +242,28 @@

    Examples

    #> #> Year 2001:.................................... #> -#> Final plant biomass (g/m2): 6429.52 -#> Change in plant biomass (g/m2): 181.155 -#> Plant biomass balance result (g/m2): 181.155 +#> Final plant biomass (g/m2): 6838.95 +#> Change in plant biomass (g/m2): 45.8692 +#> Plant biomass balance result (g/m2): 44.8656 #> Plant biomass balance components: -#> Structural balance (g/m2) 93 Labile balance (g/m2) 98 -#> Plant individual balance (g/m2) 191 Mortality loss (g/m2) 10 -#> Final plant water content (mm): 6.79576 -#> Final soil water content (mm): 322.25 +#> Structural balance (g/m2) 55 Labile balance (g/m2) 89 +#> Plant individual balance (g/m2) 144 Mortality loss (g/m2) 100 +#> Final plant water content (mm): 6.55211 +#> Final soil water content (mm): 270.352 #> Final snowpack content (mm): 0 -#> Change in plant water content (mm): 0.00913548 -#> Plant water balance result (mm): -1.23144e-17 -#> Change in soil water content (mm): 31.3748 -#> Soil water balance result (mm): 31.2803 +#> Change in plant water content (mm): -0.234506 +#> Plant water balance result (mm): 5.78995e-16 +#> Change in soil water content (mm): -20.5231 +#> Soil water balance result (mm): -20.4408 #> Change in snowpack water content (mm): 0 -#> Snowpack water balance result (mm): 7.10543e-15 +#> Snowpack water balance result (mm): 1.42109e-14 #> Water balance components: #> Precipitation (mm) 513 #> Rain (mm) 462 Snow (mm) 51 -#> Interception (mm) 91 Net rainfall (mm) 371 -#> Infiltration (mm) 329 Runoff (mm) 42 Deep drainage (mm) 142 -#> Soil evaporation (mm) 16 Herbaceous transpiration (mm) 14 Woody plant transpiration (mm) 176 -#> Plant extraction from soil (mm) 176 Plant water balance (mm) -0 Hydraulic redistribution (mm) 1 +#> Interception (mm) 88 Net rainfall (mm) 374 +#> Infiltration (mm) 346 Runoff (mm) 28 Deep drainage (mm) 59 +#> Soil evaporation (mm) 10 Herbaceous transpiration (mm) 14 Woody plant transpiration (mm) 335 +#> Plant extraction from soil (mm) 335 Plant water balance (mm) 0 Hydraulic redistribution (mm) 9 #Switch to 'Cochard' transpiration mode control <- defaultControl("Cochard") @@ -276,7 +276,7 @@

    Examples

    #Call simulation function G3 <-growth(x3, examplemeteo, latitude = 41.82592, elevation = 100) -#> Initial plant cohort biomass (g/m2): 6793.08 +#> Initial plant cohort biomass (g/m2): 6248.36 #> Initial plant water content (mm): 6.78662 #> Initial soil water content (mm): 290.875 #> Initial snowpack content (mm): 0 @@ -284,28 +284,28 @@

    Examples

    #> #> Year 2001:.................................... #> -#> Final plant biomass (g/m2): 6825.28 -#> Change in plant biomass (g/m2): 32.1984 -#> Plant biomass balance result (g/m2): 30.6843 +#> Final plant biomass (g/m2): 6380.01 +#> Change in plant biomass (g/m2): 131.642 +#> Plant biomass balance result (g/m2): 131.642 #> Plant biomass balance components: -#> Structural balance (g/m2) 43 Labile balance (g/m2) 88 -#> Plant individual balance (g/m2) 131 Mortality loss (g/m2) 101 -#> Final plant water content (mm): 6.711 -#> Final soil water content (mm): 319.226 +#> Structural balance (g/m2) 47 Labile balance (g/m2) 94 +#> Plant individual balance (g/m2) 141 Mortality loss (g/m2) 10 +#> Final plant water content (mm): 6.75279 +#> Final soil water content (mm): 319.609 #> Final snowpack content (mm): 0 -#> Change in plant water content (mm): -0.0756219 -#> Plant water balance result (mm): -0.21971 -#> Change in soil water content (mm): 28.3506 -#> Soil water balance result (mm): 28.2811 +#> Change in plant water content (mm): -0.0338339 +#> Plant water balance result (mm): -3.17637 +#> Change in soil water content (mm): 28.7342 +#> Soil water balance result (mm): 28.6162 #> Change in snowpack water content (mm): 0 -#> Snowpack water balance result (mm): -7.10543e-15 +#> Snowpack water balance result (mm): 0 #> Water balance components: #> Precipitation (mm) 513 #> Rain (mm) 462 Snow (mm) 51 #> Interception (mm) 90 Net rainfall (mm) 372 #> Infiltration (mm) 329 Runoff (mm) 43 Deep drainage (mm) 136 -#> Soil evaporation (mm) 14 Herbaceous transpiration (mm) 14 Woody plant transpiration (mm) 188 -#> Plant extraction from soil (mm) 188 Plant water balance (mm) -0 Hydraulic redistribution (mm) 0 +#> Soil evaporation (mm) 15 Herbaceous transpiration (mm) 14 Woody plant transpiration (mm) 190 +#> Plant extraction from soil (mm) 187 Plant water balance (mm) -3 Hydraulic redistribution (mm) 0 # }
    diff --git a/reference/hydraulics_conductancefunctions-2.png b/reference/hydraulics_conductancefunctions-2.png index 6ed3a9b44..b72f9d4ba 100644 Binary files a/reference/hydraulics_conductancefunctions-2.png and b/reference/hydraulics_conductancefunctions-2.png differ diff --git a/reference/hydraulics_conductancefunctions-3.png b/reference/hydraulics_conductancefunctions-3.png index 8cbcb63ad..77ffea698 100644 Binary files a/reference/hydraulics_conductancefunctions-3.png and b/reference/hydraulics_conductancefunctions-3.png differ diff --git a/reference/hydrology_interception-1.png b/reference/hydrology_interception-1.png index fa6bbca1c..9269f3061 100644 Binary files a/reference/hydrology_interception-1.png and b/reference/hydrology_interception-1.png differ diff --git a/reference/modelInput.html b/reference/modelInput.html index 1b4409f66..3b316ad87 100644 --- a/reference/modelInput.html +++ b/reference/modelInput.html @@ -1299,10 +1299,10 @@

    Examples

    #> S1_165 1085.030 1380.808 2170.587 4146.637 #> #> $belowLayers$VGrhizo_kmax -#> 1 2 3 4 -#> T1_148 296483.4 41158.65 5206.196 1703.629 -#> T2_168 46380598.9 41722941.01 3763846.755 728011.313 -#> S1_165 10941458.6 4405482.18 574055.729 169670.901 +#> 1 2 3 4 +#> T1_148 176772045 24539986 3104085 1015753 +#> T2_168 82682357 74379184 6709782 1297820 +#> S1_165 1116059122 449371399 58555276 17306902 #> #> $belowLayers$VCroot_kmax #> 1 2 3 4 @@ -1359,13 +1359,13 @@

    Examples

    #> T2_168 0.004473333 0.2007222 68.51600 118.7863 0.40 1.60 #> S1_165 0.010455247 0.2830167 62.78100 118.4486 0.29 1.16 #> VCleaf_kmax VCleafapo_kmax VCleaf_c VCleaf_d kleaf_symp VCstem_kmax -#> T1_148 4.000000 8.00000 1.456324 -1.536975 8.00000 1.339563 -#> T2_168 4.000000 8.00000 2.254991 -3.133381 8.00000 1.620936 -#> S1_165 9.579077 19.15815 2.254991 -3.133381 19.15815 4.599269 -#> VCstem_c VCstem_d VCroot_kmax VCroot_c VCroot_d VGrhizo_kmax -#> T1_148 5.030852 -4.797531 2.916127 3.193056 -0.9870357 344551.9 -#> T2_168 2.731881 -4.278250 2.896748 1.182310 -2.5041509 92595397.9 -#> S1_165 3.095442 -7.857378 3.242501 1.402489 -1.5233241 16090667.4 +#> T1_148 4.000000 8.00000 5.030852 -4.797531 8.00000 1.339563 +#> T2_168 4.000000 8.00000 2.731881 -4.278250 8.00000 1.620936 +#> S1_165 9.579077 19.15815 3.095442 -7.857378 19.15815 4.599269 +#> VCstem_c VCstem_d VCroot_kmax VCroot_c VCroot_d VGrhizo_kmax +#> T1_148 5.030852 -4.797531 2.916127 5.030852 -4.797531 205431869 +#> T2_168 2.731881 -4.278250 2.896748 2.731881 -4.278250 165069144 +#> S1_165 3.095442 -7.857378 3.242501 3.095442 -7.857378 1641292700 #> Plant_kmax FR_leaf FR_stem FR_root #> T1_148 0.7465846 0.1866462 0.5573346 0.2560193 #> T2_168 0.8249857 0.2062464 0.5089563 0.2847972 @@ -1875,10 +1875,10 @@

    Examples

    #> S1_165 1085.030 1380.808 2170.587 4146.637 #> #> $belowLayers$VGrhizo_kmax -#> 1 2 3 4 -#> T1_148 296483.4 41158.65 5206.196 1703.629 -#> T2_168 46380598.9 41722941.01 3763846.755 728011.313 -#> S1_165 10941458.6 4405482.18 574055.729 169670.901 +#> 1 2 3 4 +#> T1_148 176772045 24539986 3104085 1015753 +#> T2_168 82682357 74379184 6709782 1297820 +#> S1_165 1116059122 449371399 58555276 17306902 #> #> $belowLayers$VCroot_kmax #> 1 2 3 4 @@ -1935,21 +1935,21 @@

    Examples

    #> T2_168 0.004473333 0.2007222 4.957957 -2.663333 30 68.51600 118.7863 #> S1_165 0.010455247 0.2830167 6.590920 -2.663333 30 62.78100 118.4486 #> Kmax_stemxylem Kmax_rootxylem VCleaf_kmax VCleafapo_kmax VCleaf_slope -#> T1_148 0.15 0.60 4.000000 8.00000 115.15152 -#> T2_168 0.40 1.60 4.000000 8.00000 25.47382 -#> S1_165 0.29 1.16 9.579077 19.15815 25.47382 +#> T1_148 0.15 0.60 4.000000 8.00000 45.86982 +#> T2_168 0.40 1.60 4.000000 8.00000 23.72029 +#> S1_165 0.29 1.16 9.579077 19.15815 12.52202 #> VCleaf_P50 VCleaf_c VCleaf_d kleaf_symp VCstem_kmax VCstem_slope -#> T1_148 -1.195000 1.456324 -1.536975 8.00000 1.339563 45.86982 -#> T2_168 -2.663333 2.254991 -3.133381 8.00000 1.620936 23.72029 -#> S1_165 -2.663333 2.254991 -3.133381 19.15815 4.599269 12.52202 +#> T1_148 -4.460444 5.030852 -4.797531 8.00000 1.339563 45.86982 +#> T2_168 -3.741111 2.731881 -4.278250 8.00000 1.620936 23.72029 +#> S1_165 -6.980000 3.095442 -7.857378 19.15815 4.599269 12.52202 #> VCstem_P50 VCstem_c VCstem_d kstem_symp VCroot_kmax VCroot_slope -#> T1_148 -4.460444 5.030852 -4.797531 0.26 2.916127 102.98981 -#> T2_168 -3.741111 2.731881 -4.278250 0.26 2.896748 22.56335 -#> S1_165 -6.980000 3.095442 -7.857378 0.26 3.242501 45.00056 -#> VCroot_P50 VCroot_c VCroot_d VGrhizo_kmax Plant_kmax FR_leaf -#> T1_148 -0.880000 3.193056 -0.9870357 344551.9 0.7465846 0.1866462 -#> T2_168 -1.836667 1.182310 -2.5041509 92595397.9 0.8249857 0.2062464 -#> S1_165 -1.173000 1.402489 -1.5233241 16090667.4 1.5867376 0.1656462 +#> T1_148 -4.460444 5.030852 -4.797531 0.26 2.916127 45.86982 +#> T2_168 -3.741111 2.731881 -4.278250 0.26 2.896748 23.72029 +#> S1_165 -6.980000 3.095442 -7.857378 0.26 3.242501 12.52202 +#> VCroot_P50 VCroot_c VCroot_d VGrhizo_kmax Plant_kmax FR_leaf +#> T1_148 -4.460444 5.030852 -4.797531 205431869 0.7465846 0.1866462 +#> T2_168 -3.741111 2.731881 -4.278250 165069144 0.8249857 0.2062464 +#> S1_165 -6.980000 3.095442 -7.857378 1641292700 1.5867376 0.1656462 #> FR_stem FR_root #> T1_148 0.5573346 0.2560193 #> T2_168 0.5089563 0.2847972 diff --git a/reference/optimization.html b/reference/optimization.html index ab7e14c28..69d95a81a 100644 --- a/reference/optimization.html +++ b/reference/optimization.html @@ -317,9 +317,9 @@

    Examples

    # Loglikelihood for the values of the parameter matrix oef(parMatrix[1, ]) -#> [1] 325.6906 +#> [1] 856.308 oef(parMatrix) -#> [1] 325.6906 115.3119 +#> [1] 856.3080 843.7411 # } diff --git a/reference/plot.forest-1.png b/reference/plot.forest-1.png index 18a472298..0938e86b0 100644 Binary files a/reference/plot.forest-1.png and b/reference/plot.forest-1.png differ diff --git a/reference/plot.spwb-1.png b/reference/plot.spwb-1.png index 74281e4aa..5af43576c 100644 Binary files a/reference/plot.spwb-1.png and b/reference/plot.spwb-1.png differ diff --git a/reference/plot.spwb_day-1.png b/reference/plot.spwb_day-1.png index 71229835f..c345dd02f 100644 Binary files a/reference/plot.spwb_day-1.png and b/reference/plot.spwb_day-1.png differ diff --git a/reference/soil_texture-1.png b/reference/soil_texture-1.png index f9c69fb54..530066f1a 100644 Binary files a/reference/soil_texture-1.png and b/reference/soil_texture-1.png differ diff --git a/reference/spwb.html b/reference/spwb.html index 9b8b3a760..0e58e479c 100644 --- a/reference/spwb.html +++ b/reference/spwb.html @@ -327,22 +327,22 @@

    Examples

    #> #> [Year 2001]:.................................... #> -#> Final plant water content (mm): 6.75219 -#> Final soil water content (mm): 321.501 +#> Final plant water content (mm): 6.41269 +#> Final soil water content (mm): 246.858 #> Final snowpack content (mm): 0 -#> Change in plant water content (mm): -0.0344323 -#> Plant water balance result (mm): -2.95258e-16 -#> Change in soil water content (mm): 30.6257 -#> Soil water balance result (mm): 30.5229 +#> Change in plant water content (mm): -0.37393 +#> Plant water balance result (mm): -9.37334e-16 +#> Change in soil water content (mm): -44.0172 +#> Soil water balance result (mm): -44.0435 #> Change in snowpack water content (mm): 0 #> Snowpack water balance result (mm): -7.10543e-15 #> Water balance components: #> Precipitation (mm) 513 #> Rain (mm) 462 Snow (mm) 51 #> Interception (mm) 92 Net rainfall (mm) 370 -#> Infiltration (mm) 328 Runoff (mm) 42 Deep drainage (mm) 135 -#> Soil evaporation (mm) 15 Herbaceous transpiration (mm) 14 Woody plant transpiration (mm) 184 -#> Plant extraction from soil (mm) 184 Plant water balance (mm) -0 Hydraulic redistribution (mm) 1 +#> Infiltration (mm) 346 Runoff (mm) 24 Deep drainage (mm) 56 +#> Soil evaporation (mm) 8 Herbaceous transpiration (mm) 13 Woody plant transpiration (mm) 363 +#> Plant extraction from soil (mm) 363 Plant water balance (mm) -0 Hydraulic redistribution (mm) 14 #Switch to 'Cochard' transpiration mode control <- defaultControl("Cochard") @@ -362,22 +362,22 @@

    Examples

    #> #> [Year 2001]:.................................... #> -#> Final plant water content (mm): 6.71843 -#> Final soil water content (mm): 318.295 +#> Final plant water content (mm): 6.71797 +#> Final soil water content (mm): 317.979 #> Final snowpack content (mm): 0 -#> Change in plant water content (mm): -0.0681907 -#> Plant water balance result (mm): -3.1186 -#> Change in soil water content (mm): 27.4203 -#> Soil water balance result (mm): 27.2839 +#> Change in plant water content (mm): -0.0686527 +#> Plant water balance result (mm): -0.154782 +#> Change in soil water content (mm): 27.1045 +#> Soil water balance result (mm): 26.9622 #> Change in snowpack water content (mm): 0 #> Snowpack water balance result (mm): -7.10543e-15 #> Water balance components: #> Precipitation (mm) 513 #> Rain (mm) 462 Snow (mm) 51 #> Interception (mm) 92 Net rainfall (mm) 370 -#> Infiltration (mm) 327 Runoff (mm) 42 Deep drainage (mm) 127 +#> Infiltration (mm) 328 Runoff (mm) 42 Deep drainage (mm) 125 #> Soil evaporation (mm) 13 Herbaceous transpiration (mm) 14 Woody plant transpiration (mm) 201 -#> Plant extraction from soil (mm) 198 Plant water balance (mm) -3 Hydraulic redistribution (mm) 0 +#> Plant extraction from soil (mm) 200 Plant water balance (mm) -0 Hydraulic redistribution (mm) 0 # } diff --git a/reference/spwb_day-1.png b/reference/spwb_day-1.png index ebdbbc070..35e264e5a 100644 Binary files a/reference/spwb_day-1.png and b/reference/spwb_day-1.png differ diff --git a/reference/transp_maximumTranspirationModel-1.png b/reference/transp_maximumTranspirationModel-1.png index ec7457898..41ad0aa93 100644 Binary files a/reference/transp_maximumTranspirationModel-1.png and b/reference/transp_maximumTranspirationModel-1.png differ diff --git a/reference/transp_maximumTranspirationModel.html b/reference/transp_maximumTranspirationModel.html index 4d3b9c9ca..f3b019b11 100644 --- a/reference/transp_maximumTranspirationModel.html +++ b/reference/transp_maximumTranspirationModel.html @@ -160,7 +160,7 @@

    Examples

    # Inspect the model for first cohort m[[1]] #> LAI I(LAI^2) -#> 0.075508868 -0.003636393 +#> 0.183385509 -0.008626493 # } diff --git a/reference/transp_stomatalregulation-1.png b/reference/transp_stomatalregulation-1.png index 30f271bce..48d526256 100644 Binary files a/reference/transp_stomatalregulation-1.png and b/reference/transp_stomatalregulation-1.png differ diff --git a/reference/vprofile_leafAreaDensity-1.png b/reference/vprofile_leafAreaDensity-1.png index 18a472298..0938e86b0 100644 Binary files a/reference/vprofile_leafAreaDensity-1.png and b/reference/vprofile_leafAreaDensity-1.png differ diff --git a/reference/vprofile_leafAreaDensity-2.png b/reference/vprofile_leafAreaDensity-2.png index 6f546651b..0076688fe 100644 Binary files a/reference/vprofile_leafAreaDensity-2.png and b/reference/vprofile_leafAreaDensity-2.png differ diff --git a/reference/vprofile_leafAreaDensity-3.png b/reference/vprofile_leafAreaDensity-3.png index 5b6040a2c..82d74f85d 100644 Binary files a/reference/vprofile_leafAreaDensity-3.png and b/reference/vprofile_leafAreaDensity-3.png differ diff --git a/reference/vprofile_leafAreaDensity-4.png b/reference/vprofile_leafAreaDensity-4.png index bf81a2464..c765a9628 100644 Binary files a/reference/vprofile_leafAreaDensity-4.png and b/reference/vprofile_leafAreaDensity-4.png differ diff --git a/reference/vprofile_leafAreaDensity-5.png b/reference/vprofile_leafAreaDensity-5.png index 92f82a870..93e4692e2 100644 Binary files a/reference/vprofile_leafAreaDensity-5.png and b/reference/vprofile_leafAreaDensity-5.png differ