PBG Management and Patch

Everything summarized to the transect instead of including transect

I then summarized the sdcor values by Year, variable, and random effect grouping for graphing purposes.

Setup

VOR VP Calc

knitr::kable(VORvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C VOR20C VOR 2020 Management:Patch (Intercept) NA 0.1481627 0.3849191
C VOR20C VOR 2020 Management (Intercept) NA 0.0000000 0.0000035
C VOR20C VOR 2020 Residual NA NA 0.0206359 0.1436519
FN VOR20FN VOR 2020 Management:Patch (Intercept) NA 0.0599680 0.2448837
FN VOR20FN VOR 2020 Management (Intercept) NA 0.0000000 0.0000000
FN VOR20FN VOR 2020 Residual NA NA 0.0719818 0.2682942
FS VOR20FS VOR 2020 Management:Patch (Intercept) NA 0.0947099 0.3077497
FS VOR20FS VOR 2020 Management (Intercept) NA 0.0000000 0.0000192
FS VOR20FS VOR 2020 Residual NA NA 0.0162531 0.1274875
C VOR19C VOR 2019 Management:Patch (Intercept) NA 0.0081859 0.0904758
C VOR19C VOR 2019 Management (Intercept) NA 0.0000000 0.0000000
C VOR19C VOR 2019 Residual NA NA 0.0185316 0.1361306
FN VOR19FN VOR 2019 Management:Patch (Intercept) NA 0.0283447 0.1683588
FN VOR19FN VOR 2019 Management (Intercept) NA 0.0000000 0.0000000
FN VOR19FN VOR 2019 Residual NA NA 0.0478532 0.2187537
FS VOR19FS VOR 2019 Management:Patch (Intercept) NA 0.1100174 0.3316887
FS VOR19FS VOR 2019 Management (Intercept) NA 0.0000000 0.0000218
FS VOR19FS VOR 2019 Residual NA NA 0.0967367 0.3110252
C VOR18C VOR 2018 Management:Patch (Intercept) NA 0.0213475 0.1461079
C VOR18C VOR 2018 Management (Intercept) NA 0.0005668 0.0238074
C VOR18C VOR 2018 Residual NA NA 0.0282575 0.1680998
FN VOR18FN VOR 2018 Management:Patch (Intercept) NA 0.0108403 0.1041167
FN VOR18FN VOR 2018 Management (Intercept) NA 0.0000000 0.0000000
FN VOR18FN VOR 2018 Residual NA NA 0.0275516 0.1659866
FS VOR18FS VOR 2018 Management:Patch (Intercept) NA 0.1141322 0.3378346
FS VOR18FS VOR 2018 Management (Intercept) NA 0.0000000 0.0000000
FS VOR18FS VOR 2018 Residual NA NA 0.0448179 0.2117023
C VOR17C VOR 2017 Management:Patch (Intercept) NA 0.0242202 0.1556286
C VOR17C VOR 2017 Management (Intercept) NA 0.0000000 0.0000000
C VOR17C VOR 2017 Residual NA NA 0.0316985 0.1780407
FN VOR17FN VOR 2017 Management:Patch (Intercept) NA 0.0136430 0.1168032
FN VOR17FN VOR 2017 Management (Intercept) NA 0.0000000 0.0000000
FN VOR17FN VOR 2017 Residual NA NA 0.0237377 0.1540705
FS VOR17FS VOR 2017 Management:Patch (Intercept) NA 0.0409691 0.2024082
FS VOR17FS VOR 2017 Management (Intercept) NA 0.0000000 0.0000022
FS VOR17FS VOR 2017 Residual NA NA 0.0312325 0.1767273

Max Live VP Calc

knitr::kable(MLvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C ML20C ML 2020 Management:Patch:Transect (Intercept) NA 0.1995043 0.4466591
C ML20C ML 2020 Management:Patch (Intercept) NA 2.3367542 1.5286446
C ML20C ML 2020 Management (Intercept) NA 0.0000000 0.0000000
C ML20C ML 2020 Residual NA NA 1.2624451 1.1235858
FN ML20FN ML 2020 Management:Patch (Intercept) NA 0.6841989 0.8271632
FN ML20FN ML 2020 Management (Intercept) NA 0.0000000 0.0000000
FN ML20FN ML 2020 Residual NA NA 0.8821963 0.9392531
FS ML20FS ML 2020 Management:Patch (Intercept) NA 1.8225202 1.3500075
FS ML20FS ML 2020 Management (Intercept) NA 0.0000000 0.0000000
FS ML20FS ML 2020 Residual NA NA 0.7505467 0.8663410
C ML19C ML 2019 Management:Patch (Intercept) NA 0.2390481 0.4889254
C ML19C ML 2019 Management (Intercept) NA 0.0000000 0.0000000
C ML19C ML 2019 Residual NA NA 0.6803046 0.8248058
FN ML19FN ML 2019 Management:Patch (Intercept) NA 0.2370616 0.4868897
FN ML19FN ML 2019 Management (Intercept) NA 0.0177959 0.1334015
FN ML19FN ML 2019 Residual NA NA 1.2123915 1.1010865
FS ML19FS ML 2019 Management:Patch (Intercept) NA 3.2388413 1.7996781
FS ML19FS ML 2019 Management (Intercept) NA 0.0000000 0.0000000
FS ML19FS ML 2019 Residual NA NA 0.4672384 0.6835484
C ML18C ML 2018 Management:Patch (Intercept) NA 0.4301067 0.6558252
C ML18C ML 2018 Management (Intercept) NA 0.1109648 0.3331139
C ML18C ML 2018 Residual NA NA 0.2139652 0.4625637
FN ML18FN ML 2018 Management:Patch (Intercept) NA 0.2902148 0.5387159
FN ML18FN ML 2018 Management (Intercept) NA 0.0000000 0.0000000
FN ML18FN ML 2018 Residual NA NA 0.6884618 0.8297360
FS ML18FS ML 2018 Management:Patch (Intercept) NA 1.2028827 1.0967601
FS ML18FS ML 2018 Management (Intercept) NA 0.0268962 0.1640006
FS ML18FS ML 2018 Residual NA NA 0.4943728 0.7031165
C ML17C ML 2017 Management:Patch (Intercept) NA 0.0180346 0.1342928
C ML17C ML 2017 Management (Intercept) NA 0.0000000 0.0000091
C ML17C ML 2017 Residual NA NA 0.3795064 0.6160409
FN ML17FN ML 2017 Management:Patch (Intercept) NA 0.0712925 0.2670066
FN ML17FN ML 2017 Management (Intercept) NA 0.0000000 0.0000000
FN ML17FN ML 2017 Residual NA NA 0.6654469 0.8157493
FS ML17FS ML 2017 Management:Patch (Intercept) NA 0.1348204 0.3671789
FS ML17FS ML 2017 Management (Intercept) NA 0.1207734 0.3475247
FS ML17FS ML 2017 Residual NA NA 1.0511102 1.0252367

Max Dead VP Calc

knitr::kable(MDvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C MD20C MD 2020 Management:Patch (Intercept) NA 0.2700584 0.5196715
C MD20C MD 2020 Management (Intercept) NA 0.0000000 0.0000000
C MD20C MD 2020 Residual NA NA 0.0384487 0.1960834
FN MD20FN MD 2020 Management:Patch:Transect (Intercept) NA 0.0975663 0.3123560
FN MD20FN MD 2020 Management:Patch (Intercept) NA 0.2438033 0.4937645
FN MD20FN MD 2020 Management (Intercept) NA 0.0000000 0.0000000
FN MD20FN MD 2020 Residual NA NA 0.1235568 0.3515065
FS MD20FS MD 2020 Management:Patch (Intercept) NA 0.2223255 0.4715141
FS MD20FS MD 2020 Management (Intercept) NA 0.0000000 0.0000000
FS MD20FS MD 2020 Residual NA NA 0.0588960 0.2426851
C MD19C MD 2019 Management:Patch (Intercept) NA 0.0125325 0.1119489
C MD19C MD 2019 Management (Intercept) NA 0.0000000 0.0000000
C MD19C MD 2019 Residual NA NA 0.0361748 0.1901968
FN MD19FN MD 2019 Management:Patch (Intercept) NA 0.0435045 0.2085773
FN MD19FN MD 2019 Management (Intercept) NA 0.0000000 0.0000000
FN MD19FN MD 2019 Residual NA NA 0.0520197 0.2280783
FS MD19FS MD 2019 Management:Patch (Intercept) NA 0.0489946 0.2213473
FS MD19FS MD 2019 Management (Intercept) NA 0.0007179 0.0267944
FS MD19FS MD 2019 Residual NA NA 0.0419173 0.2047372
C MD18C MD 2018 Management:Patch (Intercept) NA 0.0169735 0.1302824
C MD18C MD 2018 Management (Intercept) NA 0.0000000 0.0000064
C MD18C MD 2018 Residual NA NA 0.0093846 0.0968743
FN MD18FN MD 2018 Management:Patch (Intercept) NA 0.0286219 0.1691801
FN MD18FN MD 2018 Management (Intercept) NA 0.0000000 0.0000028
FN MD18FN MD 2018 Residual NA NA 0.0153025 0.1237033
FS MD18FS MD 2018 Management:Patch (Intercept) NA 0.0786325 0.2804148
FS MD18FS MD 2018 Management (Intercept) NA 0.0000000 0.0000012
FS MD18FS MD 2018 Residual NA NA 0.0090663 0.0952173
C MD17C MD 2017 Management:Patch (Intercept) NA 0.0756879 0.2751143
C MD17C MD 2017 Management (Intercept) NA 0.0000000 0.0000032
C MD17C MD 2017 Residual NA NA 0.0101952 0.1009711
FN MD17FN MD 2017 Management:Patch (Intercept) NA 0.0634879 0.2519681
FN MD17FN MD 2017 Management (Intercept) NA 0.0000000 0.0000050
FN MD17FN MD 2017 Residual NA NA 0.0093776 0.0968378
FS MD17FS MD 2017 Management:Patch (Intercept) NA 0.0811059 0.2847910
FS MD17FS MD 2017 Management (Intercept) NA 0.0000000 0.0000000
FS MD17FS MD 2017 Residual NA NA 0.0288937 0.1699815

Litter Depth VP Calc

knitr::kable(LMvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C LM20C LM 2020 Management:Patch (Intercept) NA 0.2449952 0.4949699
C LM20C LM 2020 Management (Intercept) NA 0.0000000 0.0000000
C LM20C LM 2020 Residual NA NA 0.0355606 0.1885753
FN LM20FN LM 2020 Management:Patch (Intercept) NA 0.2298360 0.4794121
FN LM20FN LM 2020 Management (Intercept) NA 0.0152696 0.1235702
FN LM20FN LM 2020 Residual NA NA 0.0550970 0.2347274
FS LM20FS LM 2020 Management:Patch (Intercept) NA 0.1635568 0.4044215
FS LM20FS LM 2020 Management (Intercept) NA 0.0000000 0.0000091
FS LM20FS LM 2020 Residual NA NA 0.0207371 0.1440039
C LM19C LM 2019 Management:Patch (Intercept) NA 0.0290041 0.1703060
C LM19C LM 2019 Management (Intercept) NA 0.0000000 0.0000000
C LM19C LM 2019 Residual NA NA 0.0503381 0.2243615
FN LM19FN LM 2019 Management:Patch (Intercept) NA 0.0249583 0.1579819
FN LM19FN LM 2019 Management (Intercept) NA 0.0000000 0.0000194
FN LM19FN LM 2019 Residual NA NA 0.0210385 0.1450466
FS LM19FS LM 2019 Management:Patch (Intercept) NA 0.0000000 0.0000057
FS LM19FS LM 2019 Management (Intercept) NA 0.0234543 0.1531479
FS LM19FS LM 2019 Residual NA NA 0.0577042 0.2402171
C LM18C LM 2018 Management:Patch (Intercept) NA 0.0176034 0.1326777
C LM18C LM 2018 Management (Intercept) NA 0.0000000 0.0000000
C LM18C LM 2018 Residual NA NA 0.0116913 0.1081264
FN LM18FN LM 2018 Management:Patch (Intercept) NA 0.0929951 0.3049510
FN LM18FN LM 2018 Management (Intercept) NA 0.0000000 0.0000017
FN LM18FN LM 2018 Residual NA NA 0.0188149 0.1371675
FS LM18FS LM 2018 Management:Patch (Intercept) NA 0.0501537 0.2239502
FS LM18FS LM 2018 Management (Intercept) NA 0.0000000 0.0000000
FS LM18FS LM 2018 Residual NA NA 0.0123054 0.1109297
C LM17C LM 2017 Management:Patch (Intercept) NA 0.0022009 0.0469139
C LM17C LM 2017 Management (Intercept) NA 0.0011800 0.0343514
C LM17C LM 2017 Residual NA NA 0.0162886 0.1276267
FN LM17FN LM 2017 Management:Patch (Intercept) NA 0.0299329 0.1730112
FN LM17FN LM 2017 Management (Intercept) NA 0.0000000 0.0000000
FN LM17FN LM 2017 Residual NA NA 0.0265149 0.1628340
FS LM17FS LM 2017 Management:Patch (Intercept) NA 0.0068828 0.0829628
FS LM17FS LM 2017 Management (Intercept) NA 0.0010465 0.0323494
FS LM17FS LM 2017 Residual NA NA 0.0147075 0.1212743

Bare Ground VP Calc

knitr::kable(BGvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C BG20C BG 2020 Management:Patch (Intercept) NA 0.6498017 0.8061028
C BG20C BG 2020 Management (Intercept) NA 0.0000000 0.0000271
C BG20C BG 2020 Residual NA NA 0.7922892 0.8901063
FN BG20FN BG 2020 Management:Patch (Intercept) NA 0.4549221 0.6744791
FN BG20FN BG 2020 Management (Intercept) NA 0.0000000 0.0000000
FN BG20FN BG 2020 Residual NA NA 0.5500202 0.7416335
FS BG20FS BG 2020 Management:Patch (Intercept) NA 1.1044676 1.0509365
FS BG20FS BG 2020 Management (Intercept) NA 0.0000000 0.0000636
FS BG20FS BG 2020 Residual NA NA 0.2979886 0.5458834
C BG19C BG 2019 Management:Patch (Intercept) NA 0.2235449 0.4728054
C BG19C BG 2019 Management (Intercept) NA 0.0000000 0.0000000
C BG19C BG 2019 Residual NA NA 0.4856411 0.6968795
FN BG19FN BG 2019 Management:Patch (Intercept) NA 0.2518438 0.5018404
FN BG19FN BG 2019 Management (Intercept) NA 0.0000009 0.0009512
FN BG19FN BG 2019 Residual NA NA 0.3135550 0.5599598
FS BG19FS BG 2019 Management:Patch (Intercept) NA 0.1501359 0.3874737
FS BG19FS BG 2019 Management (Intercept) NA 0.1273263 0.3568281
FS BG19FS BG 2019 Residual NA NA 0.5774392 0.7598942
C BG18C BG 2018 Management:Patch (Intercept) NA 0.1429281 0.3780583
C BG18C BG 2018 Management (Intercept) NA 0.0000000 0.0000341
C BG18C BG 2018 Residual NA NA 0.1985592 0.4455998
FN BG18FN BG 2018 Management:Patch (Intercept) NA 0.2610453 0.5109259
FN BG18FN BG 2018 Management (Intercept) NA 0.0000000 0.0000000
FN BG18FN BG 2018 Residual NA NA 0.2006610 0.4479520
FS BG18FS BG 2018 Management:Patch (Intercept) NA 0.1109963 0.3331611
FS BG18FS BG 2018 Management (Intercept) NA 0.0000000 0.0000000
FS BG18FS BG 2018 Residual NA NA 0.3791242 0.6157306
C BG17C BG 2017 Management:Patch (Intercept) NA 0.0879845 0.2966219
C BG17C BG 2017 Management (Intercept) NA 0.0000000 0.0000000
C BG17C BG 2017 Residual NA NA 0.1771098 0.4208442
FN BG17FN BG 2017 Management:Patch (Intercept) NA 0.1794255 0.4235864
FN BG17FN BG 2017 Management (Intercept) NA 0.0000000 0.0000000
FN BG17FN BG 2017 Residual NA NA 0.0995663 0.3155413
FS BG17FS BG 2017 Management:Patch (Intercept) NA 0.1418271 0.3765994
FS BG17FS BG 2017 Management (Intercept) NA 0.0000000 0.0000000
FS BG17FS BG 2017 Residual NA NA 0.0950053 0.3082293

Ground Litter VP Calc

knitr::kable(GCvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C GC20C GC 2020 Management:Patch (Intercept) NA 84.4115879 9.1875779
C GC20C GC 2020 Management (Intercept) NA 0.0000000 0.0000000
C GC20C GC 2020 Residual NA NA 93.8377592 9.6869892
FN GC20FN GC 2020 Management:Patch (Intercept) NA 61.0230143 7.8117229
FN GC20FN GC 2020 Management (Intercept) NA 0.0000006 0.0007659
FN GC20FN GC 2020 Residual NA NA 135.2870014 11.6312941
FS GC20FS GC 2020 Management:Patch (Intercept) NA 94.8298892 9.7380639
FS GC20FS GC 2020 Management (Intercept) NA 0.0000000 0.0000000
FS GC20FS GC 2020 Residual NA NA 48.9362284 6.9954434
C GC19C GC 2019 Management:Patch (Intercept) NA 102.4065333 10.1196113
C GC19C GC 2019 Management (Intercept) NA 0.0000000 0.0000000
C GC19C GC 2019 Residual NA NA 37.2261206 6.1013212
FN GC19FN GC 2019 Management:Patch (Intercept) NA 0.0000000 0.0000000
FN GC19FN GC 2019 Management (Intercept) NA 0.0000000 0.0000000
FN GC19FN GC 2019 Residual NA NA 128.2534952 11.3249060
FS GC19FS GC 2019 Management:Patch (Intercept) NA 85.6490285 9.2546760
FS GC19FS GC 2019 Management (Intercept) NA 0.0000000 0.0001538
FS GC19FS GC 2019 Residual NA NA 48.2188207 6.9439773
C GC18C GC 2018 Management:Patch (Intercept) NA 1.9344274 1.3908370
C GC18C GC 2018 Management (Intercept) NA 6.9532279 2.6368974
C GC18C GC 2018 Residual NA NA 27.3800594 5.2325959
FN GC18FN GC 2018 Management:Patch (Intercept) NA 8.3758109 2.8940993
FN GC18FN GC 2018 Management (Intercept) NA 0.0000000 0.0000000
FN GC18FN GC 2018 Residual NA NA 39.7808097 6.3072030
FS GC18FS GC 2018 Management:Patch (Intercept) NA 18.3903128 4.2883928
FS GC18FS GC 2018 Management (Intercept) NA 0.0000000 0.0000000
FS GC18FS GC 2018 Residual NA NA 27.0159740 5.1976893
C GC17C GC 2017 Management:Patch (Intercept) NA 26.5051386 5.1483142
C GC17C GC 2017 Management (Intercept) NA 0.0000000 0.0000845
C GC17C GC 2017 Residual NA NA 47.4981910 6.8918931
FN GC17FN GC 2017 Management:Patch (Intercept) NA 10.8598449 3.2954279
FN GC17FN GC 2017 Management (Intercept) NA 0.0000000 0.0001350
FN GC17FN GC 2017 Residual NA NA 29.6317429 5.4435047
FS GC17FS GC 2017 Management:Patch (Intercept) NA 33.9652757 5.8279736
FS GC17FS GC 2017 Management (Intercept) NA 0.0000000 0.0000000
FS GC17FS GC 2017 Residual NA NA 20.4868257 4.5262375

Standing Litter VP Calc

knitr::kable(LCvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C LC20C LC 2020 Management:Patch (Intercept) NA 123.086686 11.0944439
C LC20C LC 2020 Management (Intercept) NA 0.000000 0.0000003
C LC20C LC 2020 Residual NA NA 83.247246 9.1239929
FN LC20FN LC 2020 Management:Patch (Intercept) NA 80.626420 8.9792216
FN LC20FN LC 2020 Management (Intercept) NA 0.000000 0.0000000
FN LC20FN LC 2020 Residual NA NA 51.796896 7.1970061
FS LC20FS LC 2020 Management:Patch (Intercept) NA 122.106779 11.0501936
FS LC20FS LC 2020 Management (Intercept) NA 0.000000 0.0000000
FS LC20FS LC 2020 Residual NA NA 34.080600 5.8378592
C LC19C LC 2019 Management:Patch (Intercept) NA 11.816117 3.4374580
C LC19C LC 2019 Management (Intercept) NA 0.000000 0.0000000
C LC19C LC 2019 Residual NA NA 86.592395 9.3055035
FN LC19FN LC 2019 Management:Patch (Intercept) NA 11.724179 3.4240589
FN LC19FN LC 2019 Management (Intercept) NA 0.000000 0.0000000
FN LC19FN LC 2019 Residual NA NA 96.987776 9.8482372
FS LC19FS LC 2019 Management:Patch (Intercept) NA 26.813543 5.1781795
FS LC19FS LC 2019 Management (Intercept) NA 0.000000 0.0000000
FS LC19FS LC 2019 Residual NA NA 146.141957 12.0889188
C LC18C LC 2018 Management:Patch (Intercept) NA 3.792175 1.9473508
C LC18C LC 2018 Management (Intercept) NA 0.000000 0.0001000
C LC18C LC 2018 Residual NA NA 7.639562 2.7639757
FN LC18FN LC 2018 Management:Patch (Intercept) NA 30.422366 5.5156474
FN LC18FN LC 2018 Management (Intercept) NA 0.000000 0.0001407
FN LC18FN LC 2018 Residual NA NA 6.327295 2.5154114
FS LC18FS LC 2018 Management:Patch (Intercept) NA 24.850053 4.9849827
FS LC18FS LC 2018 Management (Intercept) NA 0.000000 0.0000004
FS LC18FS LC 2018 Residual NA NA 7.160305 2.6758747
C LC17C LC 2017 Management:Patch (Intercept) NA 31.491344 5.6117149
C LC17C LC 2017 Management (Intercept) NA 0.000000 0.0000000
C LC17C LC 2017 Residual NA NA 17.156284 4.1420145
FN LC17FN LC 2017 Management:Patch (Intercept) NA 33.473312 5.7856125
FN LC17FN LC 2017 Management (Intercept) NA 0.000000 0.0000000
FN LC17FN LC 2017 Residual NA NA 12.227271 3.4967515
FS LC17FS LC 2017 Management:Patch (Intercept) NA 38.859229 6.2337171
FS LC17FS LC 2017 Management (Intercept) NA 0.000000 0.0000000
FS LC17FS LC 2017 Residual NA NA 12.724601 3.5671559

Forb VP Calc

knitr::kable(FBvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C FB20C FB 2020 Management:Patch (Intercept) NA 0.0000000 0.0000000
C FB20C FB 2020 Management (Intercept) NA 0.2049431 0.4527064
C FB20C FB 2020 Residual NA NA 0.2210517 0.4701613
FN FB20FN FB 2020 Management:Patch (Intercept) NA 0.1258889 0.3548082
FN FB20FN FB 2020 Management (Intercept) NA 0.0481590 0.2194516
FN FB20FN FB 2020 Residual NA NA 0.2169068 0.4657325
FS FB20FS FB 2020 Management:Patch (Intercept) NA 0.1667261 0.4083211
FS FB20FS FB 2020 Management (Intercept) NA 0.2785203 0.5277502
FS FB20FS FB 2020 Residual NA NA 0.3440085 0.5865223
C FB19C FB 2019 Management:Patch (Intercept) NA 0.0000000 0.0000000
C FB19C FB 2019 Management (Intercept) NA 0.0345680 0.1859248
C FB19C FB 2019 Residual NA NA 0.3370934 0.5805975
FN FB19FN FB 2019 Management:Patch (Intercept) NA 0.1510442 0.3886441
FN FB19FN FB 2019 Management (Intercept) NA 0.0628155 0.2506302
FN FB19FN FB 2019 Residual NA NA 0.1471419 0.3835908
FS FB19FS FB 2019 Management:Patch (Intercept) NA 0.1374496 0.3707419
FS FB19FS FB 2019 Management (Intercept) NA 0.0359296 0.1895511
FS FB19FS FB 2019 Residual NA NA 0.1067561 0.3267355
C FB18C FB 2018 Management:Patch (Intercept) NA 0.0000000 0.0000000
C FB18C FB 2018 Management (Intercept) NA 0.1721765 0.4149416
C FB18C FB 2018 Residual NA NA 0.0755734 0.2749061
FN FB18FN FB 2018 Management:Patch (Intercept) NA 0.1775705 0.4213911
FN FB18FN FB 2018 Management (Intercept) NA 0.2179791 0.4668824
FN FB18FN FB 2018 Residual NA NA 0.2308343 0.4804522
FS FB18FS FB 2018 Management:Patch (Intercept) NA 0.2026420 0.4501578
FS FB18FS FB 2018 Management (Intercept) NA 0.0000000 0.0000000
FS FB18FS FB 2018 Residual NA NA 0.2263539 0.4757666
C FB17C FB 2017 Management:Patch (Intercept) NA 0.0240994 0.1552398
C FB17C FB 2017 Management (Intercept) NA 0.1559343 0.3948852
C FB17C FB 2017 Residual NA NA 0.1914661 0.4375684
FN FB17FN FB 2017 Management:Patch (Intercept) NA 0.3277632 0.5725060
FN FB17FN FB 2017 Management (Intercept) NA 0.0746095 0.2731474
FN FB17FN FB 2017 Residual NA NA 0.2493165 0.4993160
FS FB17FS FB 2017 Management:Patch (Intercept) NA 0.5304270 0.7283042
FS FB17FS FB 2017 Management (Intercept) NA 0.0000000 0.0000000
FS FB17FS FB 2017 Residual NA NA 0.5125316 0.7159131

Legume VP Calc

knitr::kable(LGvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C LG20C LG 2020 Management:Patch (Intercept) NA 0.0896640 0.2994395
C LG20C LG 2020 Management (Intercept) NA 0.5473469 0.7398290
C LG20C LG 2020 Residual NA NA 0.1115472 0.3339868
FN LG20FN LG 2020 Management:Patch (Intercept) NA 0.2435651 0.4935231
FN LG20FN LG 2020 Management (Intercept) NA 0.1985049 0.4455389
FN LG20FN LG 2020 Residual NA NA 0.1910943 0.4371434
FS LG20FS LG 2020 Management:Patch (Intercept) NA 0.3490884 0.5908370
FS LG20FS LG 2020 Management (Intercept) NA 0.2700613 0.5196742
FS LG20FS LG 2020 Residual NA NA 0.4325011 0.6576482
C LG19C LG 2019 Management:Patch (Intercept) NA 0.1201504 0.3466271
C LG19C LG 2019 Management (Intercept) NA 0.2963793 0.5444073
C LG19C LG 2019 Residual NA NA 0.4913028 0.7009300
FN LG19FN LG 2019 Management:Patch (Intercept) NA 0.1522882 0.3902412
FN LG19FN LG 2019 Management (Intercept) NA 0.3172925 0.5632872
FN LG19FN LG 2019 Residual NA NA 0.1755500 0.4189868
FS LG19FS LG 2019 Management:Patch (Intercept) NA 0.4517018 0.6720876
FS LG19FS LG 2019 Management (Intercept) NA 0.1887855 0.4344945
FS LG19FS LG 2019 Residual NA NA 0.2880272 0.5366817
C LG18C LG 2018 Management:Patch (Intercept) NA 0.0458588 0.2141466
C LG18C LG 2018 Management (Intercept) NA 0.1081119 0.3288037
C LG18C LG 2018 Residual NA NA 0.0882594 0.2970848
FN LG18FN LG 2018 Management:Patch (Intercept) NA 0.1426832 0.3777344
FN LG18FN LG 2018 Management (Intercept) NA 0.0849588 0.2914769
FN LG18FN LG 2018 Residual NA NA 0.4153167 0.6444507
FS LG18FS LG 2018 Management:Patch (Intercept) NA 0.6895172 0.8303717
FS LG18FS LG 2018 Management (Intercept) NA 0.0000000 0.0000000
FS LG18FS LG 2018 Residual NA NA 0.2429381 0.4928875
C LG17C LG 2017 Management:Patch (Intercept) NA 0.0000000 0.0000000
C LG17C LG 2017 Management (Intercept) NA 0.0000000 0.0000000
C LG17C LG 2017 Residual NA NA 0.6785709 0.8237541
FN LG17FN LG 2017 Management:Patch (Intercept) NA 0.0000000 0.0000000
FN LG17FN LG 2017 Management (Intercept) NA 0.0000000 0.0000000
FN LG17FN LG 2017 Residual NA NA 0.2957973 0.5438725
FS LG17FS LG 2017 Management:Patch (Intercept) NA 1.0972655 1.0475044
FS LG17FS LG 2017 Management (Intercept) NA 0.1011238 0.3179997
FS LG17FS LG 2017 Residual NA NA 0.0624569 0.2499137

Grass VP Calc

knitr::kable(GRvar)
Block Model Variable Year grp var1 var2 vcov sdcor
C GR20C GR 2020 Management:Patch (Intercept) NA 46.6191997 6.8278254
C GR20C GR 2020 Management (Intercept) NA 0.0000000 0.0000000
C GR20C GR 2020 Residual NA NA 94.8057014 9.7368219
FN GR20FN GR 2020 Management:Patch (Intercept) NA 55.4396928 7.4457836
FN GR20FN GR 2020 Management (Intercept) NA 0.0000000 0.0000000
FN GR20FN GR 2020 Residual NA NA 128.8993982 11.3533871
FS GR20FS GR 2020 Management:Patch (Intercept) NA 51.5870237 7.1824107
FS GR20FS GR 2020 Management (Intercept) NA 0.0000000 0.0000000
FS GR20FS GR 2020 Residual NA NA 31.8759037 5.6458749
C GR19C GR 2019 Management:Patch (Intercept) NA 27.4416664 5.2384794
C GR19C GR 2019 Management (Intercept) NA 0.0000000 0.0000000
C GR19C GR 2019 Residual NA NA 57.3791375 7.5749018
FN GR19FN GR 2019 Management:Patch (Intercept) NA 24.6520161 4.9650797
FN GR19FN GR 2019 Management (Intercept) NA 0.0000000 0.0002211
FN GR19FN GR 2019 Residual NA NA 165.5308567 12.8658796
FS GR19FS GR 2019 Management:Patch (Intercept) NA 29.2551350 5.4088016
FS GR19FS GR 2019 Management (Intercept) NA 0.0000000 0.0000000
FS GR19FS GR 2019 Residual NA NA 129.8414564 11.3947995
C GR18C GR 2018 Management:Patch (Intercept) NA 31.1710260 5.5831018
C GR18C GR 2018 Management (Intercept) NA 7.4495331 2.7293833
C GR18C GR 2018 Residual NA NA 38.3914480 6.1960833
FN GR18FN GR 2018 Management:Patch (Intercept) NA 30.4156366 5.5150373
FN GR18FN GR 2018 Management (Intercept) NA 0.0000006 0.0007508
FN GR18FN GR 2018 Residual NA NA 96.8667721 9.8420919
FS GR18FS GR 2018 Management:Patch (Intercept) NA 0.0000000 0.0000000
FS GR18FS GR 2018 Management (Intercept) NA 0.0000000 0.0000000
FS GR18FS GR 2018 Residual NA NA 43.3508108 6.5841333
C GR17C GR 2017 Management:Patch (Intercept) NA 33.9086429 5.8231128
C GR17C GR 2017 Management (Intercept) NA 0.0000000 0.0000000
C GR17C GR 2017 Residual NA NA 93.9771152 9.6941795
FN GR17FN GR 2017 Management:Patch (Intercept) NA 0.0000000 0.0000000
FN GR17FN GR 2017 Management (Intercept) NA 0.0000000 0.0000000
FN GR17FN GR 2017 Residual NA NA 95.7207316 9.7836972
FS GR17FS GR 2017 Management:Patch (Intercept) NA 278.3758535 16.6845993
FS GR17FS GR 2017 Management (Intercept) NA 0.0000993 0.0099626
FS GR17FS GR 2017 Residual NA NA 102.2629328 10.1125137
## `summarise()` has grouped output by 'Year', 'Variable'. You can override using the `.groups` argument.

2017 vs 2020 PBG Tests

VOR Year Test

##             Df  Sum Sq Mean Sq F value Pr(>F)  
## Year         1 0.03568 0.03568   10.56 0.0314 *
## Residuals    4 0.01351 0.00338                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "VOR"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)  
## 2020 - 2017 == 0  0.15424    0.04746    3.25   0.0314 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)
##             Df    Sum Sq   Mean Sq F value Pr(>F)
## Year         1 7.017e-11 7.017e-11   1.326  0.314
## Residuals    4 2.117e-10 5.293e-11
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "VOR"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0 6.84e-06   5.94e-06   1.151    0.314
## (Adjusted p values reported -- single-step method)

Max Live Year Test

##             Df Sum Sq Mean Sq F value Pr(>F)  
## Year         1 1.4380  1.4380   19.63 0.0114 *
## Residuals    4 0.2931  0.0733                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "ML"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)  
## 2020 - 2017 == 0   0.9791     0.2210    4.43   0.0114 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)
##             Df  Sum Sq Mean Sq F value Pr(>F)
## Year         1 0.02013 0.02013       1  0.374
## Residuals    4 0.08051 0.02013
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "ML"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0  -0.1158     0.1158      -1    0.374
## (Adjusted p values reported -- single-step method)

Max Dead Year Test

##             Df  Sum Sq Mean Sq F value  Pr(>F)    
## Year         1 0.07551 0.07551   174.5 0.00019 ***
## Residuals    4 0.00173 0.00043                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "MD"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)    
## 2020 - 2017 == 0  0.22436    0.01698   13.21  0.00019 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)
##             Df    Sum Sq   Mean Sq F value Pr(>F)
## Year         1 1.098e-11 1.098e-11   3.488  0.135
## Residuals    4 1.259e-11 3.148e-12
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "MD"))
## 
## Linear Hypotheses:
##                    Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0 -2.706e-06  1.449e-06  -1.868    0.135
## (Adjusted p values reported -- single-step method)

Litter Depth Year Test

##             Df  Sum Sq Mean Sq F value  Pr(>F)   
## Year         1 0.19293 0.19293    58.8 0.00155 **
## Residuals    4 0.01312 0.00328                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "LM"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)   
## 2020 - 2017 == 0  0.35864    0.04677   7.668  0.00155 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)
##             Df   Sum Sq   Mean Sq F value Pr(>F)
## Year         1 0.000539 0.0005392   0.197   0.68
## Residuals    4 0.010922 0.0027306
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "LM"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0  0.01896    0.04267   0.444     0.68
## (Adjusted p values reported -- single-step method)

Bare Ground Year Test

##             Df Sum Sq Mean Sq F value Pr(>F)  
## Year         1 0.3431  0.3431   16.89 0.0147 *
## Residuals    4 0.0812  0.0203                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "BG"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)  
## 2020 - 2017 == 0   0.4782     0.1164    4.11   0.0147 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)
##             Df    Sum Sq   Mean Sq F value Pr(>F)
## Year         1 1.373e-09 1.373e-09   2.692  0.176
## Residuals    4 2.040e-09 5.101e-10
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "BG"))
## 
## Linear Hypotheses:
##                   Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0 3.026e-05  1.844e-05   1.641    0.176
## (Adjusted p values reported -- single-step method)

Ground Litter Year Test

##             Df Sum Sq Mean Sq F value Pr(>F)  
## Year         1 25.899  25.899   19.17 0.0119 *
## Residuals    4  5.405   1.351                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "GC"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)  
## 2020 - 2017 == 0   4.1552     0.9491   4.378   0.0119 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)
##             Df    Sum Sq   Mean Sq F value Pr(>F)
## Year         1 4.980e-08 4.976e-08   0.497   0.52
## Residuals    4 4.004e-07 1.001e-07
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "GC"))
## 
## Linear Hypotheses:
##                   Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0 0.0001821  0.0002583   0.705     0.52
## (Adjusted p values reported -- single-step method)

Standing Litter Year Test

##             Df Sum Sq Mean Sq F value  Pr(>F)   
## Year         1 30.343  30.343   38.81 0.00338 **
## Residuals    4  3.128   0.782                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "LC"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)   
## 2020 - 2017 == 0    4.498      0.722   6.229  0.00338 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)
##             Df    Sum Sq   Mean Sq F value Pr(>F)
## Year         1 1.399e-14 1.399e-14       1  0.374
## Residuals    4 5.596e-14 1.399e-14
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "LC"))
## 
## Linear Hypotheses:
##                   Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0 9.658e-08  9.658e-08       1    0.374
## (Adjusted p values reported -- single-step method)

Forb Year Test

##             Df  Sum Sq Mean Sq F value Pr(>F)
## Year         1 0.08002 0.08002   1.168  0.341
## Residuals    4 0.27409 0.06852
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "FB"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0  -0.2310     0.2137  -1.081    0.341
## (Adjusted p values reported -- single-step method)
##             Df  Sum Sq Mean Sq F value Pr(>F)
## Year         1 0.04715 0.04715   1.413    0.3
## Residuals    4 0.13348 0.03337
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "FB"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0   0.1773     0.1492   1.189      0.3
## (Adjusted p values reported -- single-step method)

Legume Year Test

##             Df Sum Sq Mean Sq F value Pr(>F)
## Year         1 0.0188 0.01885   0.097  0.771
## Residuals    4 0.7755 0.19388
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "LG"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0   0.1121     0.3595   0.312    0.771
## (Adjusted p values reported -- single-step method)
##             Df Sum Sq Mean Sq F value Pr(>F)  
## Year         1 0.3206  0.3206   11.22 0.0286 *
## Residuals    4 0.1143  0.0286                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "LG"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)  
## 2020 - 2017 == 0   0.4623     0.1380    3.35   0.0286 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)

Grass Year Test

##             Df Sum Sq Mean Sq F value Pr(>F)
## Year         1   0.18    0.18   0.005  0.946
## Residuals    4 143.61   35.90
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonP, 
##     Variable == "GR"))
## 
## Linear Hypotheses:
##                  Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0  -0.3506     4.8924  -0.072    0.946
## (Adjusted p values reported -- single-step method)
##             Df    Sum Sq   Mean Sq F value Pr(>F)
## Year         1 1.654e-05 1.654e-05       1  0.374
## Residuals    4 6.617e-05 1.654e-05
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: aov(formula = sdcor ~ Year, data = subset(VPYearComparisonM, 
##     Variable == "GR"))
## 
## Linear Hypotheses:
##                   Estimate Std. Error t value Pr(>|t|)
## 2020 - 2017 == 0 -0.003321   0.003321      -1    0.374
## (Adjusted p values reported -- single-step method)

PBG VP Graphs

VOR

Max Live

Max Dead

Bare Ground

Ground Litter

Standing Litter

Forb

Legume

Grass

VP Use Comparison

## `summarise()` has grouped output by 'Year', 'Variable', 'Use'. You can override using the `.groups` argument.
## `summarise()` has grouped output by 'Variable', 'Use'. You can override using the `.groups` argument.

VOR Use Overall

## 
## Model selection based on AICc:
## 
##              K   AICc Delta_AICc AICcWt Cum.Wt    LL
## VOR_use_     4 -68.42       0.00      1      1 38.70
## VOR_use_null 3 -54.77      13.65      0      1 30.67
## Data: VPUseP
## Models:
## VOR_use_null: sdcor ~ 1 + (1 | Year)
## VOR_use_: sdcor ~ Use + (1 | Year)
##              npar     AIC     BIC logLik deviance  Chisq Df Pr(>Chisq)    
## VOR_use_null    3 -55.339 -49.853 30.669  -61.339                         
## VOR_use_        4 -69.392 -62.078 38.696  -77.392 16.053  1  6.158e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##   Simultaneous Tests for General Linear Hypotheses
## 
## Multiple Comparisons of Means: Tukey Contrasts
## 
## 
## Fit: lmer(formula = sdcor ~ Use + (1 | Year), data = VPUseP, REML = FALSE)
## 
## Linear Hypotheses:
##                                  Estimate Std. Error z value Pr(>|z|)    
## Homogeneous - Heterogeneous == 0 -0.13815    0.03152  -4.383 1.17e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)

Yearly Vor

Overall VOR