Veg Structure Stats and Graphs
Jonathan Spiess
April 1, 2021
Overview
Mostly showing graphs and yearly Tukey's for now
Consistent patch contrast across variables except for 2019
No differences between grazer treatments
VOR Graphs
VOR Stats
## boundary (singular) fit: see ?isSingular## Data: HRECVeg
## Models:
## VORnull: log(VOR_Mean + 1) ~ 1 + (1 | Transect/Pasture/Year)
## VORm: log(VOR_Mean + 1) ~ Management + (1 | Transect/Pasture/Year)
## VORt: log(VOR_Mean + 1) ~ TSF + (1 | Transect/Pasture/Year)
## VORtm: log(VOR_Mean + 1) ~ Management + TSF + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## VORnull 5 2653.8 2687.5 -1321.9 2643.8
## VORm 6 2654.8 2695.3 -1321.4 2642.8 0.9878 1 0.3203
## VORt 9 2588.7 2649.4 -1285.3 2570.7 72.1065 3 1.51e-15 ***
## VORtm 10 2589.8 2657.3 -1284.9 2569.8 0.9044 1 0.3416
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVeg
## Models:
## VORnull: log(VOR_Mean + 1) ~ 1 + (1 | Transect/Pasture/Year)
## VORt: log(VOR_Mean + 1) ~ TSF + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## VORnull 5 2653.8 2687.5 -1321.9 2643.8
## VORt 9 2588.7 2649.4 -1285.3 2570.7 73.094 4 5.039e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVeg
## Models:
## VORnull: log(VOR_Mean + 1) ~ 1 + (1 | Transect/Pasture/Year)
## VORm: log(VOR_Mean + 1) ~ Management + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## VORnull 5 2653.8 2687.5 -1321.9 2643.8
## VORm 6 2654.8 2695.3 -1321.4 2642.8 0.9878 1 0.3203## boundary (singular) fit: see ?isSingular##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = VOR_Mean ~ TSF + (1 | Transect/Pasture/Year),
## data = HRECVeg, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.7865 0.1834 4.288 < 0.001 ***
## 2yr3yr - RB == 0 1.4127 0.2100 6.726 < 0.001 ***
## 3yr4yr - RB == 0 1.1935 0.2788 4.281 < 0.001 ***
## Unburned - RB == 0 0.5252 0.1586 3.312 0.00762 **
## 2yr3yr - 1yr2yr == 0 0.6262 0.2148 2.915 0.02767 *
## 3yr4yr - 1yr2yr == 0 0.4070 0.2844 1.431 0.59656
## Unburned - 1yr2yr == 0 -0.2613 0.1766 -1.480 0.56481
## 3yr4yr - 2yr3yr == 0 -0.2192 0.2984 -0.735 0.94610
## Unburned - 2yr3yr == 0 -0.8875 0.2070 -4.288 < 0.001 ***
## Unburned - 3yr4yr == 0 -0.6683 0.2790 -2.396 0.11089
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)Overall, TSF significantly influenced VOR and Management did not. Recently burned patches had lower VOR than all other patches (Yay!)
VORt17a <- lmer(log(VOR_Mean+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2017"), REML = FALSE)
Mult_VOR17a <- glht(VORt17a, linfct=mcp(TSF = "Tukey"))
summary(Mult_VOR17a) #Unburned higher than RB##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(VOR_Mean + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 0.32499 0.05217 6.23 4.68e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)VORt18a <- lmer(log(VOR_Mean+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2018"), REML = FALSE)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## unable to evaluate scaled gradient## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge: degenerate Hessian with 1 negative eigenvaluesMult_VOR18a <- glht(VORt18a, linfct=mcp(TSF = "Tukey"))
summary(Mult_VOR18a) #unburned higher than RB and 1-2##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(VOR_Mean + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.16341 0.08616 1.897 0.1386
## Unburned - RB == 0 0.34437 0.07465 4.613 <0.001 ***
## Unburned - 1yr2yr == 0 0.18096 0.07463 2.425 0.0403 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)VORt19a <- lmer(log(VOR_Mean+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2019"), REML = FALSE)## boundary (singular) fit: see ?isSingularMult_VOR19a <- glht(VORt19a, linfct=mcp(TSF = "Tukey"))
summary(Mult_VOR19a) #no differences##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(VOR_Mean + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.012112 0.092308 0.131 0.999
## 2yr3yr - RB == 0 0.149551 0.093007 1.608 0.374
## Unburned - RB == 0 0.153959 0.094069 1.637 0.358
## 2yr3yr - 1yr2yr == 0 0.137438 0.088969 1.545 0.410
## Unburned - 1yr2yr == 0 0.141847 0.092301 1.537 0.415
## Unburned - 2yr3yr == 0 0.004409 0.093000 0.047 1.000
## (Adjusted p values reported -- single-step method)VORt20a <- lmer(log(VOR_Mean+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2020"), REML = FALSE)
Mult_VOR20a <- glht(VORt20a, linfct=mcp(TSF = "Tukey"))
summary(Mult_VOR20a) #RB lower than everyone##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(VOR_Mean + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.61590 0.08051 7.650 <0.001 ***
## 2yr3yr - RB == 0 0.56275 0.08050 6.990 <0.001 ***
## 3yr4yr - RB == 0 0.72058 0.08052 8.949 <0.001 ***
## 2yr3yr - 1yr2yr == 0 -0.05315 0.08051 -0.660 0.912
## 3yr4yr - 1yr2yr == 0 0.10468 0.08052 1.300 0.563
## 3yr4yr - 2yr3yr == 0 0.15784 0.08052 1.960 0.203
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)Max Live Height Graphs
Max Live Height Stats
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Data: HRECVeg
## Models:
## MLnull: MaxLive ~ 1 + (1 | Transect/Pasture/Year)
## MLm: MaxLive ~ Management + (1 | Transect/Pasture/Year)
## MLt: MaxLive ~ TSF + (1 | Transect/Pasture/Year)
## MLtm: MaxLive ~ Management + TSF + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## MLnull 5 23425 23458 -11707 23415
## MLm 6 23425 23466 -11707 23413 1.4438 1 0.2295
## MLt 9 23400 23461 -11691 23382 30.9618 3 8.659e-07 ***
## MLtm 10 23401 23468 -11690 23381 1.3581 1 0.2439
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVeg
## Models:
## MLnull: MaxLive ~ 1 + (1 | Transect/Pasture/Year)
## MLt: MaxLive ~ TSF + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## MLnull 5 23425 23458 -11707 23415
## MLt 9 23400 23461 -11691 23382 32.406 4 1.581e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVeg
## Models:
## MLnull: MaxLive ~ 1 + (1 | Transect/Pasture/Year)
## MLm: MaxLive ~ Management + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## MLnull 5 23425 23458 -11707 23415
## MLm 6 23425 23466 -11707 23413 1.4438 1 0.2295##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = MaxLive ~ TSF + (1 | Transect/Pasture/Year), data = HRECVeg,
## REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 1.4030 0.3233 4.340 < 0.001 ***
## 2yr3yr - RB == 0 1.9750 0.3686 5.358 < 0.001 ***
## 3yr4yr - RB == 0 1.0565 0.4876 2.167 0.18424
## Unburned - RB == 0 0.5974 0.2786 2.145 0.19295
## 2yr3yr - 1yr2yr == 0 0.5720 0.3773 1.516 0.54078
## 3yr4yr - 1yr2yr == 0 -0.3465 0.4986 -0.695 0.95566
## Unburned - 1yr2yr == 0 -0.8056 0.3072 -2.622 0.06274 .
## 3yr4yr - 2yr3yr == 0 -0.9185 0.5246 -1.751 0.39128
## Unburned - 2yr3yr == 0 -1.3776 0.3580 -3.848 0.00109 **
## Unburned - 3yr4yr == 0 -0.4591 0.4826 -0.951 0.87157
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2017
MLt17a <- lmer(MaxLive ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2017"), REML = FALSE)## boundary (singular) fit: see ?isSingularMult_ML17a <- glht(MLt17a, linfct=mcp(TSF = "Tukey"))
summary(Mult_ML17a) #Unburned > RB##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = MaxLive ~ TSF + (1 | Transect/Pasture), data = subset(HRECVeg,
## Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 0.7381 0.2643 2.793 0.00522 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2018
MLt18a <- lmer(MaxLive ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2018"), REML = FALSE)
Mult_ML18a <- glht(MLt18a, linfct=mcp(TSF = "Tukey"))
summary(Mult_ML18a) #RB lower than other two patches##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = MaxLive ~ TSF + (1 | Transect/Pasture), data = subset(HRECVeg,
## Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.8906 0.3573 2.493 0.0336 *
## Unburned - RB == 0 1.4396 0.3095 4.651 <0.001 ***
## Unburned - 1yr2yr == 0 0.5491 0.3095 1.774 0.1771
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2019
MLt19a <- lmer(MaxLive ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2019"), REML = FALSE)
Mult_ML19a <- glht(MLt19a, linfct=mcp(TSF = "Tukey"))
summary(Mult_ML19a) #no difference##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = MaxLive ~ TSF + (1 | Transect/Pasture), data = subset(HRECVeg,
## Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -0.578809 0.532381 -1.087 0.697
## 2yr3yr - RB == 0 -0.041031 0.536257 -0.077 1.000
## Unburned - RB == 0 -0.039175 0.542622 -0.072 1.000
## 2yr3yr - 1yr2yr == 0 0.537778 0.510630 1.053 0.718
## Unburned - 1yr2yr == 0 0.539634 0.532340 1.014 0.741
## Unburned - 2yr3yr == 0 0.001856 0.536217 0.003 1.000
## (Adjusted p values reported -- single-step method)#2020
MLt20a <- lmer(MaxLive ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2020"), REML = FALSE)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00604857 (tol = 0.002, component 1)Mult_ML20a <- glht(MLt20a, linfct=mcp(TSF = "Tukey"))
summary(Mult_ML20a) #RB lower than other patches##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = MaxLive ~ TSF + (1 | Transect/Pasture), data = subset(HRECVeg,
## Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 2.70805 0.36941 7.331 <1e-04 ***
## 2yr3yr - RB == 0 2.09720 0.36939 5.678 <1e-04 ***
## 3yr4yr - RB == 0 2.65104 0.36951 7.174 <1e-04 ***
## 2yr3yr - 1yr2yr == 0 -0.61084 0.36939 -1.654 0.349
## 3yr4yr - 1yr2yr == 0 -0.05701 0.36951 -0.154 0.999
## 3yr4yr - 2yr3yr == 0 0.55384 0.36950 1.499 0.438
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)Max Dead Height Graphs
Max Dead Height Stats
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Data: HRECVeg
## Models:
## MDnull: log(MaxDead + 1) ~ 1 + (1 | Transect/Pasture/Year)
## MDm: log(MaxDead + 1) ~ Management + (1 | Transect/Pasture/Year)
## MDt: log(MaxDead + 1) ~ TSF + (1 | Transect/Pasture/Year)
## MDtm: log(MaxDead + 1) ~ Management + TSF + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## MDnull 5 5914.0 5947.8 -2952.0 5904.0
## MDm 6 5915.1 5955.7 -2951.6 5903.1 0.8664 1 0.3519
## MDt 9 5672.2 5732.9 -2827.1 5654.2 248.9628 3 <2e-16 ***
## MDtm 10 5673.1 5740.6 -2826.6 5653.1 1.0698 1 0.3010
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVeg
## Models:
## MDnull: log(MaxDead + 1) ~ 1 + (1 | Transect/Pasture/Year)
## MDt: log(MaxDead + 1) ~ TSF + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## MDnull 5 5914.0 5947.8 -2952.0 5904.0
## MDt 9 5672.2 5732.9 -2827.1 5654.2 249.83 4 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVeg
## Models:
## MDnull: log(MaxDead + 1) ~ 1 + (1 | Transect/Pasture/Year)
## MDm: log(MaxDead + 1) ~ Management + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## MDnull 5 5914.0 5947.8 -2952.0 5904.0
## MDm 6 5915.1 5955.7 -2951.6 5903.1 0.8664 1 0.3519##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(MaxDead + 1) ~ TSF + (1 | Transect/Pasture/Year),
## data = HRECVeg, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.51740 0.04476 11.559 <1e-04 ***
## 2yr3yr - RB == 0 0.85433 0.05164 16.545 <1e-04 ***
## 3yr4yr - RB == 0 1.21928 0.06838 17.830 <1e-04 ***
## Unburned - RB == 0 0.46460 0.03869 12.009 <1e-04 ***
## 2yr3yr - 1yr2yr == 0 0.33693 0.05332 6.318 <1e-04 ***
## 3yr4yr - 1yr2yr == 0 0.70188 0.06971 10.069 <1e-04 ***
## Unburned - 1yr2yr == 0 -0.05280 0.04374 -1.207 0.739
## 3yr4yr - 2yr3yr == 0 0.36495 0.07293 5.004 <1e-04 ***
## Unburned - 2yr3yr == 0 -0.38973 0.05176 -7.529 <1e-04 ***
## Unburned - 3yr4yr == 0 -0.75468 0.06930 -10.890 <1e-04 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2017
MDt17a <- lmer(log(MaxDead+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2017"), REML = FALSE)
Mult_MDt17a <- glht(MDt17a, linfct=mcp(TSF = "Tukey"))
summary(Mult_MDt17a) #different##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(MaxDead + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 0.59683 0.04404 13.55 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2018
MDt18a <- lmer(log(MaxDead+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2018"), REML = FALSE)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## unable to evaluate scaled gradient## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge: degenerate Hessian with 1 negative eigenvaluesMult_MDt18a <- glht(MDt18a, linfct=mcp(TSF = "Tukey"))
summary(Mult_MDt18a) #Unburned > 1-2 > RB ##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(MaxDead + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.22277 0.05079 4.386 3.22e-05 ***
## Unburned - RB == 0 0.44043 0.04404 10.000 < 1e-05 ***
## Unburned - 1yr2yr == 0 0.21766 0.04401 4.946 < 1e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2019
MDt19a <- lmer(log(MaxDead+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2019"), REML = FALSE)
Mult_MDt19a <- glht(MDt19a, linfct=mcp(TSF = "Tukey"))
summary(Mult_MDt19a) #RB lower than everybody, others equal##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(MaxDead + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.29476 0.06878 4.285 0.000107 ***
## 2yr3yr - RB == 0 0.39428 0.06913 5.703 < 1e-04 ***
## Unburned - RB == 0 0.33128 0.06943 4.771 < 1e-04 ***
## 2yr3yr - 1yr2yr == 0 0.09951 0.06780 1.468 0.457077
## Unburned - 1yr2yr == 0 0.03652 0.06877 0.531 0.951563
## Unburned - 2yr3yr == 0 -0.06300 0.06912 -0.911 0.798755
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2020
MDt20a <- lmer(log(MaxDead+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2020"), REML = FALSE)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## unable to evaluate scaled gradient
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge: degenerate Hessian with 1 negative eigenvaluesMult_MDt20a <- glht(MDt20a, linfct=mcp(TSF = "Tukey"))
summary(Mult_MDt20a) #RB lower than everybody, others equal##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(MaxDead + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 1.01550 0.10018 10.137 <0.001 ***
## 2yr3yr - RB == 0 1.12683 0.10017 11.249 <0.001 ***
## 3yr4yr - RB == 0 1.20602 0.10021 12.035 <0.001 ***
## 2yr3yr - 1yr2yr == 0 0.11133 0.10017 1.111 0.683
## 3yr4yr - 1yr2yr == 0 0.19052 0.10021 1.901 0.228
## 3yr4yr - 2yr3yr == 0 0.07919 0.10020 0.790 0.859
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)Mean Litter Depth Graphs
Mean Litter Depth Stats
#Transect/Pasture/Year
LMnull <- lmer(log(LitMean+1) ~ 1 + (1|Transect/Pasture/Year), data=HRECVeg, REML = FALSE)## boundary (singular) fit: see ?isSingularLMt <- lmer(log(LitMean+1) ~ TSF + (1|Transect/Pasture/Year), data=HRECVeg, REML = FALSE)## boundary (singular) fit: see ?isSingularLMm <- lmer(log(LitMean+1) ~ Management + (1|Transect/Pasture/Year), data=HRECVeg, REML = FALSE)## boundary (singular) fit: see ?isSingularLMtm <- lmer(log(LitMean+1) ~ Management + TSF +(1|Transect/Pasture/Year), data=HRECVeg, REML = FALSE)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00636183 (tol = 0.002, component 1)anova(LMnull, LMt, LMm, LMtm) #no difference between sheep and cattle## Data: HRECVeg
## Models:
## LMnull: log(LitMean + 1) ~ 1 + (1 | Transect/Pasture/Year)
## LMm: log(LitMean + 1) ~ Management + (1 | Transect/Pasture/Year)
## LMt: log(LitMean + 1) ~ TSF + (1 | Transect/Pasture/Year)
## LMtm: log(LitMean + 1) ~ Management + TSF + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## LMnull 5 3785.4 3819.2 -1887.7 3775.4
## LMm 6 3786.7 3827.3 -1887.4 3774.7 0.6632 1 0.4154
## LMt 9 3687.2 3748.0 -1834.6 3669.2 105.5049 3 <2e-16 ***
## LMtm 10 3688.3 3755.8 -1834.2 3668.3 0.9288 1 0.3352
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1anova(LMnull, LMt) #no difference between sheep and cattle## Data: HRECVeg
## Models:
## LMnull: log(LitMean + 1) ~ 1 + (1 | Transect/Pasture/Year)
## LMt: log(LitMean + 1) ~ TSF + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## LMnull 5 3785.4 3819.2 -1887.7 3775.4
## LMt 9 3687.2 3748.0 -1834.6 3669.2 106.17 4 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1anova(LMnull, LMm) #no difference between sheep and cattle## Data: HRECVeg
## Models:
## LMnull: log(LitMean + 1) ~ 1 + (1 | Transect/Pasture/Year)
## LMm: log(LitMean + 1) ~ Management + (1 | Transect/Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## LMnull 5 3785.4 3819.2 -1887.7 3775.4
## LMm 6 3786.7 3827.3 -1887.4 3774.7 0.6632 1 0.4154Mult_LMta <- glht(LMt, linfct=mcp(TSF = "Tukey"))
summary(Mult_LMta) #3-4 > 2-3 = Unburned > 1-2 > RB##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(LitMean + 1) ~ TSF + (1 | Transect/Pasture/Year),
## data = HRECVeg, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.21904 0.05795 3.780 0.00144 **
## 2yr3yr - RB == 0 0.44864 0.06573 6.826 < 0.001 ***
## 3yr4yr - RB == 0 0.82587 0.08578 9.628 < 0.001 ***
## Unburned - RB == 0 0.39446 0.04945 7.977 < 0.001 ***
## 2yr3yr - 1yr2yr == 0 0.22960 0.06808 3.373 0.00642 **
## 3yr4yr - 1yr2yr == 0 0.60683 0.08821 6.879 < 0.001 ***
## Unburned - 1yr2yr == 0 0.17541 0.05375 3.263 0.00914 **
## 3yr4yr - 2yr3yr == 0 0.37723 0.09341 4.039 < 0.001 ***
## Unburned - 2yr3yr == 0 -0.05419 0.06213 -0.872 0.90292
## Unburned - 3yr4yr == 0 -0.43141 0.08311 -5.191 < 0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2017
LMt17a <- lmer(log(LitMean+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2017"), REML = FALSE)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## unable to evaluate scaled gradient## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge: degenerate Hessian with 1 negative eigenvaluesMult_LMt17a <- glht(LMt17a, linfct=mcp(TSF = "Tukey"))
summary(Mult_LMt17a)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(LitMean + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 0.18805 0.04495 4.184 2.86e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2018
LMt18a <- lmer(log(LitMean+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2018"), REML = FALSE)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## unable to evaluate scaled gradient
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge: degenerate Hessian with 1 negative eigenvaluesMult_LMt18a <- glht(LMt18a, linfct=mcp(TSF = "Tukey"))
summary(Mult_LMt18a)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(LitMean + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.05945 0.05935 1.002 0.574
## Unburned - RB == 0 0.42198 0.05144 8.204 <1e-04 ***
## Unburned - 1yr2yr == 0 0.36253 0.05142 7.051 <1e-04 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2019
LMt19a <- lmer(log(LitMean+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2019"), REML = FALSE)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## unable to evaluate scaled gradient
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge: degenerate Hessian with 1 negative eigenvaluesMult_LMt19a <- glht(LMt19a, linfct=mcp(TSF = "Tukey"))
summary(Mult_LMt19a)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(LitMean + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.15448 0.06087 2.538 0.05407 .
## 2yr3yr - RB == 0 0.18467 0.06125 3.015 0.01376 *
## Unburned - RB == 0 0.37744 0.06168 6.119 < 0.001 ***
## 2yr3yr - 1yr2yr == 0 0.03019 0.05949 0.508 0.95732
## Unburned - 1yr2yr == 0 0.22296 0.06086 3.664 0.00133 **
## Unburned - 2yr3yr == 0 0.19277 0.06124 3.148 0.00899 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2020
LMt20a <- lmer(log(LitMean+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2020"), REML = FALSE)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## unable to evaluate scaled gradient
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge: degenerate Hessian with 1 negative eigenvaluesMult_LMt20a <- glht(LMt20a, linfct=mcp(TSF = "Tukey"))
summary(Mult_LMt20a)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(LitMean + 1) ~ TSF + (1 | Transect/Pasture),
## data = subset(HRECVeg, Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.76204 0.10733 7.100 <1e-04 ***
## 2yr3yr - RB == 0 0.91733 0.10733 8.547 <1e-04 ***
## 3yr4yr - RB == 0 0.88177 0.10735 8.214 <1e-04 ***
## 2yr3yr - 1yr2yr == 0 0.15528 0.10733 1.447 0.470
## 3yr4yr - 1yr2yr == 0 0.11972 0.10735 1.115 0.680
## 3yr4yr - 2yr3yr == 0 -0.03556 0.10735 -0.331 0.987
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)Bare Ground Cover Graphs
Bare Ground Stats
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Data: HRECVegT
## Models:
## BGnull: log(BGCover + 1) ~ 1 + (1 | Pasture/Year)
## BGm: log(BGCover + 1) ~ Management + (1 | Pasture/Year)
## BGt: log(BGCover + 1) ~ TSF + (1 | Pasture/Year)
## BGtm: log(BGCover + 1) ~ Management + TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## BGnull 4 751.25 765.94 -371.62 743.25
## BGm 5 753.12 771.49 -371.56 743.12 0.1251 1 0.7236
## BGt 8 660.78 690.17 -322.39 644.78 98.3456 3 <2e-16 ***
## BGtm 9 662.65 695.71 -322.33 644.65 0.1279 1 0.7206
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## BGnull: log(BGCover + 1) ~ 1 + (1 | Pasture/Year)
## BGt: log(BGCover + 1) ~ TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## BGnull 4 751.25 765.94 -371.62 743.25
## BGt 8 660.78 690.17 -322.39 644.78 98.471 4 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## BGnull: log(BGCover + 1) ~ 1 + (1 | Pasture/Year)
## BGm: log(BGCover + 1) ~ Management + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## BGnull 4 751.25 765.94 -371.62 743.25
## BGm 5 753.12 771.49 -371.56 743.12 0.1251 1 0.7236##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(BGCover + 1) ~ TSF + (1 | Pasture/Year), data = HRECVegT,
## REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -0.5499 0.1253 -4.388 < 0.001 ***
## 2yr3yr - RB == 0 -0.8146 0.1473 -5.531 < 0.001 ***
## 3yr4yr - RB == 0 -1.5252 0.1961 -7.777 < 0.001 ***
## Unburned - RB == 0 -0.9874 0.1100 -8.978 < 0.001 ***
## 2yr3yr - 1yr2yr == 0 -0.2647 0.1509 -1.755 0.38845
## 3yr4yr - 1yr2yr == 0 -0.9753 0.1986 -4.911 < 0.001 ***
## Unburned - 1yr2yr == 0 -0.4375 0.1257 -3.481 0.00425 **
## 3yr4yr - 2yr3yr == 0 -0.7106 0.2065 -3.441 0.00481 **
## Unburned - 2yr3yr == 0 -0.1728 0.1520 -1.137 0.77901
## Unburned - 3yr4yr == 0 0.5379 0.2032 2.647 0.05862 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2017
BGt17a <- lmer(log(BGCover+1) ~ TSF + (1|Pasture), data=subset(HRECVegT, Year=="2017"), REML = FALSE)
Mult_BGt17a <- glht(BGt17a, linfct=mcp(TSF = "Tukey"))
summary(Mult_BGt17a)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(BGCover + 1) ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 -0.7563 0.1000 -7.563 3.95e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2018
BGt18a <- lmer(log(BGCover+1) ~ TSF + (1|Pasture), data=subset(HRECVegT, Year=="2018"), REML = FALSE)## boundary (singular) fit: see ?isSingularMult_BGt18a <- glht(BGt18a, linfct=mcp(TSF = "Tukey"))
summary(Mult_BGt18a) #RB = 1-2 > Unburned##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(BGCover + 1) ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -0.2905 0.1773 -1.638 0.228140
## Unburned - RB == 0 -0.9209 0.1536 -5.997 < 1e-04 ***
## Unburned - 1yr2yr == 0 -0.6304 0.1536 -4.105 0.000107 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2019
BGt19a <- lmer(log(BGCover+1) ~ TSF + (1|Pasture), data=subset(HRECVegT, Year=="2019"), REML = FALSE)
Mult_BGt19a <- glht(BGt19a, linfct=mcp(TSF = "Tukey"))
summary(Mult_BGt19a)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(BGCover + 1) ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -0.3883 0.2179 -1.782 0.2820
## 2yr3yr - RB == 0 -0.7571 0.2234 -3.389 0.0040 **
## Unburned - RB == 0 -1.2906 0.2234 -5.777 <0.001 ***
## 2yr3yr - 1yr2yr == 0 -0.3688 0.2179 -1.692 0.3276
## Unburned - 1yr2yr == 0 -0.9022 0.2179 -4.140 <0.001 ***
## Unburned - 2yr3yr == 0 -0.5334 0.2234 -2.388 0.0795 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)#2020
BGt20a <- lmer(log(BGCover+1) ~ TSF + (1|Pasture), data=subset(HRECVegT, Year=="2020"), REML = FALSE)
Mult_BGt20a <- glht(BGt20a, linfct=mcp(TSF = "Tukey"))
summary(Mult_BGt20a)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(BGCover + 1) ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -1.1296 0.3241 -3.485 0.00294 **
## 2yr3yr - RB == 0 -1.0188 0.3241 -3.143 0.00924 **
## 3yr4yr - RB == 0 -1.7572 0.3241 -5.421 < 0.001 ***
## 2yr3yr - 1yr2yr == 0 0.1108 0.3241 0.342 0.98626
## 3yr4yr - 1yr2yr == 0 -0.6276 0.3241 -1.936 0.21298
## 3yr4yr - 2yr3yr == 0 -0.7384 0.3241 -2.278 0.10337
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)Ground Litter Cover Graphs
Ground Litter Stats
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Data: HRECVegT
## Models:
## Gnull: GCover ~ 1 + (1 | Pasture/Year)
## Gm: GCover ~ Management + (1 | Pasture/Year)
## Gt: GCover ~ TSF + (1 | Pasture/Year)
## Gmt: GCover ~ TSF + Management + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Gnull 4 2194.0 2208.7 -1093.0 2186.0
## Gm 5 2192.6 2210.9 -1091.3 2182.6 3.398 1 0.06528 .
## Gt 8 2152.3 2181.7 -1068.2 2136.3 46.279 3 4.948e-10 ***
## Gmt 9 2151.1 2184.1 -1066.5 2133.1 3.222 1 0.07265 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Gnull: GCover ~ 1 + (1 | Pasture/Year)
## Gt: GCover ~ TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Gnull 4 2194.0 2208.7 -1093.0 2186.0
## Gt 8 2152.3 2181.7 -1068.2 2136.3 49.677 4 4.218e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Gnull: GCover ~ 1 + (1 | Pasture/Year)
## Gm: GCover ~ Management + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Gnull 4 2194.0 2208.7 -1093.0 2186.0
## Gm 5 2192.6 2210.9 -1091.3 2182.6 3.398 1 0.06528 .
## ---
## 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 = GCover ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 -11.848 1.533 -7.729 1.09e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = GCover ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -3.7323 2.0576 -1.814 0.164
## Unburned - RB == 0 -3.5931 1.7820 -2.016 0.107
## Unburned - 1yr2yr == 0 0.1392 1.7820 0.078 0.997
## (Adjusted p values reported -- single-step method)## boundary (singular) fit: see ?isSingular##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = GCover ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -12.369 3.193 -3.874 0.000619 ***
## 2yr3yr - RB == 0 -13.943 3.276 -4.257 < 1e-04 ***
## Unburned - RB == 0 -14.960 3.276 -4.567 < 1e-04 ***
## 2yr3yr - 1yr2yr == 0 -1.575 3.193 -0.493 0.960618
## Unburned - 1yr2yr == 0 -2.591 3.193 -0.812 0.848994
## Unburned - 2yr3yr == 0 -1.017 3.276 -0.310 0.989644
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)## boundary (singular) fit: see ?isSingular##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = GCover ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -6.026 4.148 -1.453 0.4663
## 2yr3yr - RB == 0 -1.172 4.148 -0.282 0.9921
## 3yr4yr - RB == 0 -12.180 4.148 -2.936 0.0173 *
## 2yr3yr - 1yr2yr == 0 4.854 4.148 1.170 0.6456
## 3yr4yr - 1yr2yr == 0 -6.154 4.148 -1.484 0.4474
## 3yr4yr - 2yr3yr == 0 -11.008 4.148 -2.654 0.0397 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)Vertical Litter Cover Graphs
vertical Litter Stats
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Data: HRECVegT
## Models:
## LCnull: LitCover ~ 1 + (1 | Pasture/Year)
## LCm: LitCover ~ Management + (1 | Pasture/Year)
## LCt: LitCover ~ TSF + (1 | Pasture/Year)
## LCtm: LitCover ~ Management + TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## LCnull 4 2187.2 2201.8 -1089.6 2179.2
## LCm 5 2188.7 2207.1 -1089.4 2178.7 0.4279 1 0.5130
## LCt 8 2069.1 2098.5 -1026.6 2053.1 125.6062 3 <2e-16 ***
## LCtm 9 2070.6 2103.6 -1026.3 2052.6 0.5340 1 0.4649
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## LCnull: LitCover ~ 1 + (1 | Pasture/Year)
## LCt: LitCover ~ TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## LCnull 4 2187.2 2201.8 -1089.6 2179.2
## LCt 8 2069.1 2098.5 -1026.6 2053.1 126.03 4 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## LCnull: LitCover ~ 1 + (1 | Pasture/Year)
## LCm: LitCover ~ Management + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## LCnull 4 2187.2 2201.8 -1089.6 2179.2
## LCm 5 2188.7 2207.1 -1089.4 2178.7 0.4279 1 0.513##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = LitCover ~ TSF + (1 | Pasture/Year), data = HRECVegT,
## REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 9.6379 1.4115 6.828 <1e-04 ***
## 2yr3yr - RB == 0 11.3174 1.6576 6.828 <1e-04 ***
## 3yr4yr - RB == 0 22.2778 2.2061 10.098 <1e-04 ***
## Unburned - RB == 0 11.5044 1.2377 9.295 <1e-04 ***
## 2yr3yr - 1yr2yr == 0 1.6795 1.6989 0.989 0.855
## 3yr4yr - 1yr2yr == 0 12.6398 2.2350 5.655 <1e-04 ***
## Unburned - 1yr2yr == 0 1.8664 1.4128 1.321 0.668
## 3yr4yr - 2yr3yr == 0 10.9604 2.3249 4.714 <1e-04 ***
## Unburned - 2yr3yr == 0 0.1869 1.7074 0.109 1.000
## Unburned - 3yr4yr == 0 -10.7734 2.2822 -4.721 <1e-04 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = LitCover ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 12.444 1.229 10.13 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = LitCover ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 2.3410 1.1013 2.126 0.084 .
## Unburned - RB == 0 8.5832 0.9538 8.999 <0.001 ***
## Unburned - 1yr2yr == 0 6.2422 0.9538 6.545 <0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)## boundary (singular) fit: see ?isSingular##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = LitCover ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 11.847 3.366 3.520 0.00222 **
## 2yr3yr - RB == 0 9.393 3.453 2.720 0.03295 *
## Unburned - RB == 0 10.742 3.453 3.111 0.01019 *
## 2yr3yr - 1yr2yr == 0 -2.454 3.366 -0.729 0.88546
## Unburned - 1yr2yr == 0 -1.105 3.366 -0.328 0.98779
## Unburned - 2yr3yr == 0 1.349 3.453 0.391 0.97977
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = LitCover ~ TSF + (1 | Pasture), data = subset(HRECVegT,
## Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 14.4480 3.0841 4.685 < 0.001 ***
## 2yr3yr - RB == 0 14.8246 3.0841 4.807 < 0.001 ***
## 3yr4yr - RB == 0 24.6234 3.0841 7.984 < 0.001 ***
## 2yr3yr - 1yr2yr == 0 0.3766 3.0841 0.122 0.99935
## 3yr4yr - 1yr2yr == 0 10.1754 3.0841 3.299 0.00518 **
## 3yr4yr - 2yr3yr == 0 9.7988 3.0841 3.177 0.00833 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)Forb Stats
## Data: HRECVegT
## Models:
## Forbnull: log(Forb + 1) ~ 1 + (1 | Pasture/Year)
## Forbm: log(Forb + 1) ~ Management + (1 | Pasture/Year)
## Forbt: log(Forb + 1) ~ TSF + (1 | Pasture/Year)
## Forbtm: log(Forb + 1) ~ Management + TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Forbnull 4 597.62 612.31 -294.81 589.62
## Forbm 5 595.21 613.58 -292.61 585.21 4.4024 1 0.03589 *
## Forbt 8 595.99 625.38 -290.00 579.99 5.2188 3 0.15646
## Forbtm 9 593.60 626.66 -287.80 575.60 4.3989 1 0.03596 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Forbnull: log(Forb + 1) ~ 1 + (1 | Pasture/Year)
## Forbt: log(Forb + 1) ~ TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Forbnull 4 597.62 612.31 -294.81 589.62
## Forbt 8 595.99 625.38 -290.00 579.99 9.6212 4 0.04731 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Forbnull: log(Forb + 1) ~ 1 + (1 | Pasture/Year)
## Forbm: log(Forb + 1) ~ Management + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Forbnull 4 597.62 612.31 -294.81 589.62
## Forbm 5 595.21 613.58 -292.61 585.21 4.4024 1 0.03589 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Forbnull: log(Forb + 1) ~ 1 + (1 | Pasture/Year)
## Forbtm: log(Forb + 1) ~ Management + TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Forbnull 4 597.62 612.31 -294.81 589.62
## Forbtm 9 593.60 626.66 -287.80 575.60 14.02 5 0.01548 *
## ---
## 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 = log(Forb + 1) ~ Management + TSF + (1 | Pasture/Year),
## data = HRECVegT, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -0.7351 0.2886 -2.547 0.0109 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Forb + 1) ~ Management + TSF + (1 | Pasture/Year),
## data = HRECVegT, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.08805 0.11015 0.799 0.9277
## 2yr3yr - RB == 0 0.17163 0.12915 1.329 0.6628
## 3yr4yr - RB == 0 0.07117 0.17159 0.415 0.9935
## Unburned - RB == 0 -0.18800 0.09640 -1.950 0.2805
## 2yr3yr - 1yr2yr == 0 0.08358 0.13255 0.631 0.9687
## 3yr4yr - 1yr2yr == 0 -0.01688 0.17404 -0.097 1.0000
## Unburned - 1yr2yr == 0 -0.27605 0.10973 -2.516 0.0825 .
## 3yr4yr - 2yr3yr == 0 -0.10046 0.18130 -0.554 0.9805
## Unburned - 2yr3yr == 0 -0.35963 0.13237 -2.717 0.0486 *
## Unburned - 3yr4yr == 0 -0.25917 0.17685 -1.465 0.5736
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Forb + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -0.7056 0.3072 -2.297 0.0216 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Forb + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 -0.1073 0.2096 -0.512 0.609
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Forb + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -0.7258 0.2328 -3.118 0.00182 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Forb + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.07782 0.18052 0.431 0.902
## Unburned - RB == 0 -0.10621 0.15634 -0.679 0.774
## Unburned - 1yr2yr == 0 -0.18402 0.15634 -1.177 0.465
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Forb + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -0.5757 0.3822 -1.506 0.132
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Forb + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.1486 0.1569 0.947 0.77951
## 2yr3yr - RB == 0 -0.1108 0.1608 -0.689 0.90127
## Unburned - RB == 0 -0.3991 0.1608 -2.482 0.06301 .
## 2yr3yr - 1yr2yr == 0 -0.2594 0.1569 -1.653 0.34887
## Unburned - 1yr2yr == 0 -0.5477 0.1569 -3.490 0.00265 **
## Unburned - 2yr3yr == 0 -0.2883 0.1608 -1.793 0.27662
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Forb + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -0.9172 0.3082 -2.976 0.00292 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Forb + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -0.08766 0.18793 -0.466 0.966
## 2yr3yr - RB == 0 0.29431 0.18793 1.566 0.398
## 3yr4yr - RB == 0 0.12973 0.18793 0.690 0.901
## 2yr3yr - 1yr2yr == 0 0.38197 0.18793 2.033 0.176
## 3yr4yr - 1yr2yr == 0 0.21739 0.18793 1.157 0.654
## 3yr4yr - 2yr3yr == 0 -0.16458 0.18793 -0.876 0.817
## (Adjusted p values reported -- single-step method)Legume Stats
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Data: HRECVegT
## Models:
## Legumenull: log(Legume + 1) ~ 1 + (1 | Pasture/Year)
## Legumem: log(Legume + 1) ~ Management + (1 | Pasture/Year)
## Legumet: log(Legume + 1) ~ TSF + (1 | Pasture/Year)
## Legumetm: log(Legume + 1) ~ Management + TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Legumenull 4 706.91 721.60 -349.45 698.91
## Legumem 5 700.94 719.30 -345.47 690.94 7.9722 1 0.00475 **
## Legumet 8 700.83 730.22 -342.42 684.83 6.1035 3 0.10668
## Legumetm 9 693.49 726.55 -337.75 675.49 9.3416 1 0.00224 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Legumenull: log(Legume + 1) ~ 1 + (1 | Pasture/Year)
## Legumet: log(Legume + 1) ~ TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Legumenull 4 706.91 721.60 -349.45 698.91
## Legumet 8 700.83 730.22 -342.42 684.83 14.076 4 0.007057 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Legumenull: log(Legume + 1) ~ 1 + (1 | Pasture/Year)
## Legumem: log(Legume + 1) ~ Management + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Legumenull 4 706.91 721.6 -349.45 698.91
## Legumem 5 700.94 719.3 -345.47 690.94 7.9722 1 0.00475 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Legumenull: log(Legume + 1) ~ 1 + (1 | Pasture/Year)
## Legumetm: log(Legume + 1) ~ Management + TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Legumenull 4 706.91 721.60 -349.45 698.91
## Legumetm 9 693.49 726.55 -337.75 675.49 23.417 5 0.0002809 ***
## ---
## 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 = log(Legume + 1) ~ Management + TSF + (1 | Pasture/Year),
## data = HRECVegT, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -0.7242 0.2005 -3.612 0.000303 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Legume + 1) ~ Management + TSF + (1 | Pasture/Year),
## data = HRECVegT, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -0.23047 0.13070 -1.763 0.38305
## 2yr3yr - RB == 0 -0.31486 0.15410 -2.043 0.23546
## 3yr4yr - RB == 0 -0.38164 0.20592 -1.853 0.33159
## Unburned - RB == 0 0.20767 0.11517 1.803 0.35978
## 2yr3yr - 1yr2yr == 0 -0.08439 0.15738 -0.536 0.98271
## 3yr4yr - 1yr2yr == 0 -0.15117 0.20803 -0.727 0.94791
## Unburned - 1yr2yr == 0 0.43813 0.13236 3.310 0.00777 **
## 3yr4yr - 2yr3yr == 0 -0.06678 0.21563 -0.310 0.99789
## Unburned - 2yr3yr == 0 0.52252 0.16070 3.252 0.00941 **
## Unburned - 3yr4yr == 0 0.58930 0.21502 2.741 0.04530 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Legume + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 0.2652 0.3528 0.752 0.452
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Legume + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 -0.1921 0.2190 -0.877 0.38
## (Adjusted p values reported -- single-step method)## boundary (singular) fit: see ?isSingular##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Legume + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -0.7258 0.1516 -4.788 1.68e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Legume + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -0.0009758 0.2143703 -0.005 1.0000
## Unburned - RB == 0 0.5179389 0.1856501 2.790 0.0144 *
## Unburned - 1yr2yr == 0 0.5189147 0.1856501 2.795 0.0143 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)## boundary (singular) fit: see ?isSingular##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Legume + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -1.175 0.161 -7.296 2.96e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Legume + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -0.38741 0.22485 -1.723 0.3116
## 2yr3yr - RB == 0 -0.05474 0.23055 -0.237 0.9953
## Unburned - RB == 0 0.16432 0.23055 0.713 0.8921
## 2yr3yr - 1yr2yr == 0 0.33267 0.22485 1.480 0.4499
## Unburned - 1yr2yr == 0 0.55172 0.22485 2.454 0.0676 .
## Unburned - 2yr3yr == 0 0.21905 0.23055 0.950 0.7776
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Legume + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -1.2752 0.1763 -7.232 4.75e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = log(Legume + 1) ~ TSF + Management + (1 | Pasture),
## data = subset(HRECVegT, Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 0.1050 0.2054 0.511 0.9564
## 2yr3yr - RB == 0 -0.4453 0.2054 -2.168 0.1322
## 3yr4yr - RB == 0 -0.2693 0.2054 -1.311 0.5556
## 2yr3yr - 1yr2yr == 0 -0.5503 0.2054 -2.679 0.0368 *
## 3yr4yr - 1yr2yr == 0 -0.3743 0.2054 -1.823 0.2626
## 3yr4yr - 2yr3yr == 0 0.1760 0.2054 0.857 0.8270
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)Grass Stats
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular
## boundary (singular) fit: see ?isSingular## Data: HRECVegT
## Models:
## Grassnull: Grass ~ 1 + (1 | Pasture/Year)
## Grassm: Grass ~ Management + (1 | Pasture/Year)
## Grasst: Grass ~ TSF + (1 | Pasture/Year)
## Grasstm: Grass ~ Management + TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Grassnull 4 2300.6 2315.3 -1146.3 2292.6
## Grassm 5 2302.4 2320.7 -1146.2 2292.4 0.2605 1 0.6098
## Grasst 8 2285.8 2315.2 -1134.9 2269.8 22.5992 3 4.894e-05 ***
## Grasstm 9 2287.5 2320.6 -1134.8 2269.5 0.2705 1 0.6030
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Grassnull: Grass ~ 1 + (1 | Pasture/Year)
## Grasst: Grass ~ TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Grassnull 4 2300.6 2315.3 -1146.3 2292.6
## Grasst 8 2285.8 2315.2 -1134.9 2269.8 22.86 4 0.0001351 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Data: HRECVegT
## Models:
## Grassnull: Grass ~ 1 + (1 | Pasture/Year)
## Grassm: Grass ~ Management + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Grassnull 4 2300.6 2315.3 -1146.3 2292.6
## Grassm 5 2302.4 2320.7 -1146.2 2292.4 0.2605 1 0.6098## Data: HRECVegT
## Models:
## Grassnull: Grass ~ 1 + (1 | Pasture/Year)
## Grasstm: Grass ~ Management + TSF + (1 | Pasture/Year)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## Grassnull 4 2300.6 2315.3 -1146.3 2292.6
## Grasstm 9 2287.5 2320.6 -1134.8 2269.5 23.13 5 0.0003187 ***
## ---
## 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 = Grass ~ Management + TSF + (1 | Pasture/Year),
## data = HRECVegT, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 1.409 2.702 0.522 0.602
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = Grass ~ Management + TSF + (1 | Pasture/Year),
## data = HRECVegT, REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 5.632 2.043 2.757 0.04359 *
## 2yr3yr - RB == 0 3.627 2.401 1.511 0.54355
## 3yr4yr - RB == 0 11.075 3.198 3.463 0.00452 **
## Unburned - RB == 0 7.202 1.793 4.016 < 0.001 ***
## 2yr3yr - 1yr2yr == 0 -2.005 2.459 -0.815 0.92259
## 3yr4yr - 1yr2yr == 0 5.442 3.238 1.681 0.43394
## Unburned - 1yr2yr == 0 1.569 2.049 0.766 0.93757
## 3yr4yr - 2yr3yr == 0 7.447 3.366 2.212 0.16733
## Unburned - 2yr3yr == 0 3.574 2.479 1.442 0.58898
## Unburned - 3yr4yr == 0 -3.873 3.314 -1.169 0.76082
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = Grass ~ TSF + Management + (1 | Pasture), data = subset(HRECVegT,
## Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 -2.496 5.186 -0.481 0.63
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = Grass ~ TSF + Management + (1 | Pasture), data = subset(HRECVegT,
## Year == "2017"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Unburned - RB == 0 10.498 3.476 3.02 0.00253 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = Grass ~ TSF + Management + (1 | Pasture), data = subset(HRECVegT,
## Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 1.601 3.019 0.53 0.596
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = Grass ~ TSF + Management + (1 | Pasture), data = subset(HRECVegT,
## Year == "2018"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 3.3617 2.9834 1.127 0.496
## Unburned - RB == 0 2.9781 2.5837 1.153 0.480
## Unburned - 1yr2yr == 0 -0.3836 2.5837 -0.148 0.988
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = Grass ~ TSF + Management + (1 | Pasture), data = subset(HRECVegT,
## Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 1.567 2.948 0.532 0.595
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = Grass ~ TSF + Management + (1 | Pasture), data = subset(HRECVegT,
## Year == "2019"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 -0.84249 3.89301 -0.216 0.996
## 2yr3yr - RB == 0 0.66617 3.99133 0.167 0.998
## Unburned - RB == 0 0.69390 3.99133 0.174 0.998
## 2yr3yr - 1yr2yr == 0 1.50866 3.89301 0.388 0.980
## Unburned - 1yr2yr == 0 1.53639 3.89301 0.395 0.979
## Unburned - 2yr3yr == 0 0.02772 3.99133 0.007 1.000
## (Adjusted p values reported -- single-step method)## boundary (singular) fit: see ?isSingular##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = Grass ~ TSF + Management + (1 | Pasture), data = subset(HRECVegT,
## Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## Sheep - Cattle == 0 4.907 2.241 2.19 0.0285 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)##
## Simultaneous Tests for General Linear Hypotheses
##
## Multiple Comparisons of Means: Tukey Contrasts
##
##
## Fit: lmer(formula = Grass ~ TSF + Management + (1 | Pasture), data = subset(HRECVegT,
## Year == "2020"), REML = FALSE)
##
## Linear Hypotheses:
## Estimate Std. Error z value Pr(>|z|)
## 1yr2yr - RB == 0 13.578 3.169 4.285 <0.001 ***
## 2yr3yr - RB == 0 7.090 3.169 2.238 0.1133
## 3yr4yr - RB == 0 16.553 3.169 5.224 <0.001 ***
## 2yr3yr - 1yr2yr == 0 -6.488 3.169 -2.048 0.1708
## 3yr4yr - 1yr2yr == 0 2.975 3.169 0.939 0.7839
## 3yr4yr - 2yr3yr == 0 9.463 3.169 2.987 0.0152 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## (Adjusted p values reported -- single-step method)