data <- read.csv("/Users/justincarter/Downloads/CPF_DSP_clean_v5.csv")
data$PM <- as.factor(data$PM)
data$Sample_depth_cm <- as.factor(data$Sample_depth_cm)
data$FSDMP <- as.factor(data$FSDMP)
data$Age_year <- as.factor(data$Age_year)
lm_P <- lm(P.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4, data = data)
summary(lm_P)
##
## Call:
## lm(formula = P.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP +
## Age_year)^4, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -237.43 -20.75 -3.51 11.03 338.14
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 9.42403 19.65049 0.480
## PMTill -0.68232 27.79000 -0.025
## Sample_depth_cm10-20 92.68543 27.79000 3.335
## Sample_depth_cm20-40 151.26620 27.79000 5.443
## Sample_depth_cm5-10 13.65230 27.79000 0.491
## FSDMP1 6.77351 27.79000 0.244
## FSDMP2 19.76937 27.08634 0.730
## Age_year15-20 0.76732 27.79000 0.028
## PMTill:Sample_depth_cm10-20 -73.69430 39.30099 -1.875
## PMTill:Sample_depth_cm20-40 -103.39192 39.30099 -2.631
## PMTill:Sample_depth_cm5-10 -12.49674 39.30099 -0.318
## PMTill:FSDMP1 -6.04724 39.30099 -0.154
## PMTill:FSDMP2 -18.27380 38.80662 -0.471
## PMTill:Age_year15-20 0.07537 39.30099 0.002
## Sample_depth_cm10-20:FSDMP1 5.13356 39.30099 0.131
## Sample_depth_cm20-40:FSDMP1 55.56454 39.30099 1.414
## Sample_depth_cm5-10:FSDMP1 -2.21729 39.30099 -0.056
## Sample_depth_cm10-20:FSDMP2 -12.81314 38.30586 -0.334
## Sample_depth_cm20-40:FSDMP2 -28.30659 38.30586 -0.739
## Sample_depth_cm5-10:FSDMP2 -2.46662 38.30586 -0.064
## Sample_depth_cm10-20:Age_year15-20 9.05974 39.30099 0.231
## Sample_depth_cm20-40:Age_year15-20 63.56481 39.30099 1.617
## Sample_depth_cm5-10:Age_year15-20 -8.20829 39.30099 -0.209
## FSDMP1:Age_year15-20 -7.40612 39.30099 -0.188
## FSDMP2:Age_year15-20 -18.49507 38.30586 -0.483
## PMTill:Sample_depth_cm10-20:FSDMP1 10.64077 55.57999 0.191
## PMTill:Sample_depth_cm20-40:FSDMP1 -55.20903 55.57999 -0.993
## PMTill:Sample_depth_cm5-10:FSDMP1 6.10143 55.57999 0.110
## PMTill:Sample_depth_cm10-20:FSDMP2 13.45542 54.88084 0.245
## PMTill:Sample_depth_cm20-40:FSDMP2 52.49148 54.88084 0.956
## PMTill:Sample_depth_cm5-10:FSDMP2 3.10926 54.88084 0.057
## PMTill:Sample_depth_cm10-20:Age_year15-20 23.61938 56.01253 0.422
## PMTill:Sample_depth_cm20-40:Age_year15-20 -28.03740 55.57999 -0.504
## PMTill:Sample_depth_cm5-10:Age_year15-20 13.46118 55.57999 0.242
## PMTill:FSDMP1:Age_year15-20 6.52463 55.57999 0.117
## PMTill:FSDMP2:Age_year15-20 17.64409 54.88084 0.321
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 8.15742 55.57999 0.147
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 -85.26380 55.57999 -1.534
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 4.39730 55.57999 0.079
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 65.86634 54.17267 1.216
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 64.35218 54.17267 1.188
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 11.11584 54.17267 0.205
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 -41.95698 78.90842 -0.532
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 68.49761 78.60198 0.871
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 -7.90538 78.60198 -0.101
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 -78.65122 77.92356 -1.009
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 -99.64612 77.61323 -1.284
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 -11.29154 77.61323 -0.145
## Pr(>|t|)
## (Intercept) 0.631793
## PMTill 0.980424
## Sample_depth_cm10-20 0.000934 ***
## Sample_depth_cm20-40 9.26e-08 ***
## Sample_depth_cm5-10 0.623514
## FSDMP1 0.807561
## FSDMP2 0.465910
## Age_year15-20 0.977986
## PMTill:Sample_depth_cm10-20 0.061521 .
## PMTill:Sample_depth_cm20-40 0.008856 **
## PMTill:Sample_depth_cm5-10 0.750674
## PMTill:FSDMP1 0.877792
## PMTill:FSDMP2 0.637979
## PMTill:Age_year15-20 0.998471
## Sample_depth_cm10-20:FSDMP1 0.896142
## Sample_depth_cm20-40:FSDMP1 0.158210
## Sample_depth_cm5-10:FSDMP1 0.955038
## Sample_depth_cm10-20:FSDMP2 0.738185
## Sample_depth_cm20-40:FSDMP2 0.460373
## Sample_depth_cm5-10:FSDMP2 0.948690
## Sample_depth_cm10-20:Age_year15-20 0.817807
## Sample_depth_cm20-40:Age_year15-20 0.106602
## Sample_depth_cm5-10:Age_year15-20 0.834669
## FSDMP1:Age_year15-20 0.850625
## FSDMP2:Age_year15-20 0.629489
## PMTill:Sample_depth_cm10-20:FSDMP1 0.848273
## PMTill:Sample_depth_cm20-40:FSDMP1 0.321166
## PMTill:Sample_depth_cm5-10:FSDMP1 0.912642
## PMTill:Sample_depth_cm10-20:FSDMP2 0.806450
## PMTill:Sample_depth_cm20-40:FSDMP2 0.339429
## PMTill:Sample_depth_cm5-10:FSDMP2 0.954849
## PMTill:Sample_depth_cm10-20:Age_year15-20 0.673490
## PMTill:Sample_depth_cm20-40:Age_year15-20 0.614228
## PMTill:Sample_depth_cm5-10:Age_year15-20 0.808756
## PMTill:FSDMP1:Age_year15-20 0.906610
## PMTill:FSDMP2:Age_year15-20 0.748005
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.883390
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.125820
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.936980
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.224772
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.235591
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.837528
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.595224
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.384044
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.919940
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.313437
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.199944
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.884403
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 58.95 on 391 degrees of freedom
## Multiple R-squared: 0.5897, Adjusted R-squared: 0.5404
## F-statistic: 11.96 on 47 and 391 DF, p-value: < 2.2e-16
new_P <- step(lm_P, direction = "both")
## Start: AIC=3624.52
## P.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP:Age_year 6 24900 1383734 3620.5
## <none> 1358833 3624.5
##
## Step: AIC=3620.49
## P.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:FSDMP + PM:Sample_depth_cm:Age_year +
## PM:FSDMP:Age_year + Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP 6 5073.2 1388807 3610.1
## - Sample_depth_cm:FSDMP:Age_year 6 16086.9 1399821 3613.6
## - PM:Sample_depth_cm:Age_year 3 9028.1 1392762 3617.3
## - PM:FSDMP:Age_year 2 8290.4 1392024 3619.1
## <none> 1383734 3620.5
## + PM:Sample_depth_cm:FSDMP:Age_year 6 24900.4 1358833 3624.5
##
## Step: AIC=3610.1
## P.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year +
## Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP:Age_year 6 16112.3 1404919 3603.2
## - PM:Sample_depth_cm:Age_year 3 9038.2 1397845 3606.9
## - PM:FSDMP:Age_year 2 8277.4 1397084 3608.7
## <none> 1388807 3610.1
## + PM:Sample_depth_cm:FSDMP 6 5073.2 1383734 3620.5
##
## Step: AIC=3603.17
## P.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP 6 645.1 1405564 3591.4
## - PM:Sample_depth_cm:Age_year 3 9439.4 1414359 3600.1
## - PM:FSDMP:Age_year 2 8288.3 1413208 3601.7
## <none> 1404919 3603.2
## + Sample_depth_cm:FSDMP:Age_year 6 16112.3 1388807 3610.1
## + PM:Sample_depth_cm:FSDMP 6 5098.6 1399821 3613.6
##
## Step: AIC=3591.37
## P.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:Age_year 3 9433.5 1414998 3588.3
## - PM:FSDMP:Age_year 2 8295.6 1413860 3589.9
## <none> 1405564 3591.4
## + Sample_depth_cm:FSDMP 6 645.1 1404919 3603.2
##
## Step: AIC=3588.3
## P.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:FSDMP:Age_year 2 8300 1423298 3586.9
## <none> 1414998 3588.3
## + PM:Sample_depth_cm:Age_year 3 9433 1405564 3591.4
## - Sample_depth_cm:Age_year 3 31050 1446048 3591.8
## + Sample_depth_cm:FSDMP 6 639 1414359 3600.1
## - PM:Sample_depth_cm 3 286440 1701438 3663.2
##
## Step: AIC=3586.87
## P.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:FSDMP 2 4677 1427975 3584.3
## - PM:Age_year 1 510 1423808 3585.0
## - FSDMP:Age_year 2 11077 1434375 3586.3
## <none> 1423298 3586.9
## + PM:FSDMP:Age_year 2 8300 1414998 3588.3
## + PM:Sample_depth_cm:Age_year 3 9438 1413860 3589.9
## - Sample_depth_cm:Age_year 3 31034 1454332 3590.3
## + Sample_depth_cm:FSDMP 6 646 1422652 3598.7
## - PM:Sample_depth_cm 3 286481 1709779 3661.4
##
## Step: AIC=3584.31
## P.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Age_year 1 520 1428495 3582.5
## - FSDMP:Age_year 2 11051 1439026 3583.7
## <none> 1427975 3584.3
## + PM:FSDMP 2 4677 1423298 3586.9
## + PM:Sample_depth_cm:Age_year 3 9450 1418525 3587.4
## - Sample_depth_cm:Age_year 3 30990 1458965 3587.7
## + Sample_depth_cm:FSDMP 6 666 1427309 3596.1
## - PM:Sample_depth_cm 3 286590 1714565 3658.6
##
## Step: AIC=3582.47
## P.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## Sample_depth_cm:Age_year + FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - FSDMP:Age_year 2 11133 1439628 3581.9
## <none> 1428495 3582.5
## + PM:Age_year 1 520 1427975 3584.3
## + PM:FSDMP 2 4687 1423808 3585.0
## - Sample_depth_cm:Age_year 3 31001 1459496 3585.9
## + Sample_depth_cm:FSDMP 6 661 1427834 3594.3
## - PM:Sample_depth_cm 3 286563 1715058 3656.7
##
## Step: AIC=3581.88
## P.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## Sample_depth_cm:Age_year
##
## Df Sum of Sq RSS AIC
## - FSDMP 2 6979 1446607 3580.0
## <none> 1439628 3581.9
## + FSDMP:Age_year 2 11133 1428495 3582.5
## + PM:Age_year 1 602 1439026 3583.7
## + PM:FSDMP 2 4662 1434966 3584.5
## - Sample_depth_cm:Age_year 3 30973 1470601 3585.2
## + Sample_depth_cm:FSDMP 6 674 1438954 3593.7
## - PM:Sample_depth_cm 3 286632 1726259 3655.6
##
## Step: AIC=3580
## P.mass..kg.ha. ~ PM + Sample_depth_cm + Age_year + PM:Sample_depth_cm +
## Sample_depth_cm:Age_year
##
## Df Sum of Sq RSS AIC
## <none> 1446607 3580.0
## + PM:Age_year 1 591 1446016 3581.8
## + FSDMP 2 6979 1439628 3581.9
## - Sample_depth_cm:Age_year 3 31017 1477624 3583.3
## - PM:Sample_depth_cm 3 286524 1733131 3653.3
lm_SOC <- lm(SOC..Mg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4, data = data)
summary(lm_SOC)
##
## Call:
## lm(formula = SOC..Mg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP +
## Age_year)^4, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -17.851 -3.771 -0.613 2.813 41.963
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 16.4944 2.0180 8.174
## PMTill 3.0156 2.8539 1.057
## Sample_depth_cm10-20 -4.1156 2.8539 -1.442
## Sample_depth_cm20-40 -6.4422 2.8539 -2.257
## Sample_depth_cm5-10 -3.4267 2.8539 -1.201
## FSDMP1 -2.0300 2.8539 -0.711
## FSDMP2 -4.4714 2.7816 -1.608
## Age_year15-20 -2.2800 2.8539 -0.799
## PMTill:Sample_depth_cm10-20 -5.2178 4.0360 -1.293
## PMTill:Sample_depth_cm20-40 -6.0311 4.0360 -1.494
## PMTill:Sample_depth_cm5-10 -3.6144 4.0360 -0.896
## PMTill:FSDMP1 1.8978 4.0360 0.470
## PMTill:FSDMP2 5.0192 3.9852 1.259
## PMTill:Age_year15-20 0.6211 4.0360 0.154
## Sample_depth_cm10-20:FSDMP1 -0.7811 4.0360 -0.194
## Sample_depth_cm20-40:FSDMP1 2.6244 4.0360 0.650
## Sample_depth_cm5-10:FSDMP1 -1.3978 4.0360 -0.346
## Sample_depth_cm10-20:FSDMP2 0.4676 3.9338 0.119
## Sample_depth_cm20-40:FSDMP2 1.0452 3.9338 0.266
## Sample_depth_cm5-10:FSDMP2 0.7377 3.9338 0.188
## Sample_depth_cm10-20:Age_year15-20 0.9700 4.0360 0.240
## Sample_depth_cm20-40:Age_year15-20 4.5544 4.0360 1.128
## Sample_depth_cm5-10:Age_year15-20 4.5844 4.0360 1.136
## FSDMP1:Age_year15-20 5.1111 4.0360 1.266
## FSDMP2:Age_year15-20 6.4600 3.9338 1.642
## PMTill:Sample_depth_cm10-20:FSDMP1 1.9533 5.7077 0.342
## PMTill:Sample_depth_cm20-40:FSDMP1 -1.5889 5.7077 -0.278
## PMTill:Sample_depth_cm5-10:FSDMP1 5.2522 5.7077 0.920
## PMTill:Sample_depth_cm10-20:FSDMP2 -4.1276 5.6359 -0.732
## PMTill:Sample_depth_cm20-40:FSDMP2 -0.8841 5.6359 -0.157
## PMTill:Sample_depth_cm5-10:FSDMP2 0.4312 5.6359 0.077
## PMTill:Sample_depth_cm10-20:Age_year15-20 3.2422 5.7522 0.564
## PMTill:Sample_depth_cm20-40:Age_year15-20 3.5644 5.7077 0.624
## PMTill:Sample_depth_cm5-10:Age_year15-20 -1.6867 5.7077 -0.296
## PMTill:FSDMP1:Age_year15-20 -5.8178 5.7077 -1.019
## PMTill:FSDMP2:Age_year15-20 -8.4800 5.6359 -1.505
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 -2.3511 5.7077 -0.412
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 -8.7811 5.7077 -1.538
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 -6.3133 5.7077 -1.106
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 -1.4780 5.5632 -0.266
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 -6.0904 5.5632 -1.095
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 -4.4844 5.5632 -0.806
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 2.8300 8.1034 0.349
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 3.6300 8.0720 0.450
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 3.8533 8.0720 0.477
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 3.6980 8.0023 0.462
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 1.2382 7.9704 0.155
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 7.6733 7.9704 0.963
## Pr(>|t|)
## (Intercept) 4.21e-15 ***
## PMTill 0.2913
## Sample_depth_cm10-20 0.1501
## Sample_depth_cm20-40 0.0245 *
## Sample_depth_cm5-10 0.2306
## FSDMP1 0.4773
## FSDMP2 0.1088
## Age_year15-20 0.4248
## PMTill:Sample_depth_cm10-20 0.1968
## PMTill:Sample_depth_cm20-40 0.1359
## PMTill:Sample_depth_cm5-10 0.3710
## PMTill:FSDMP1 0.6385
## PMTill:FSDMP2 0.2086
## PMTill:Age_year15-20 0.8778
## Sample_depth_cm10-20:FSDMP1 0.8466
## Sample_depth_cm20-40:FSDMP1 0.5159
## Sample_depth_cm5-10:FSDMP1 0.7293
## Sample_depth_cm10-20:FSDMP2 0.9055
## Sample_depth_cm20-40:FSDMP2 0.7906
## Sample_depth_cm5-10:FSDMP2 0.8513
## Sample_depth_cm10-20:Age_year15-20 0.8102
## Sample_depth_cm20-40:Age_year15-20 0.2598
## Sample_depth_cm5-10:Age_year15-20 0.2567
## FSDMP1:Age_year15-20 0.2061
## FSDMP2:Age_year15-20 0.1014
## PMTill:Sample_depth_cm10-20:FSDMP1 0.7324
## PMTill:Sample_depth_cm20-40:FSDMP1 0.7809
## PMTill:Sample_depth_cm5-10:FSDMP1 0.3580
## PMTill:Sample_depth_cm10-20:FSDMP2 0.4644
## PMTill:Sample_depth_cm20-40:FSDMP2 0.8754
## PMTill:Sample_depth_cm5-10:FSDMP2 0.9391
## PMTill:Sample_depth_cm10-20:Age_year15-20 0.5733
## PMTill:Sample_depth_cm20-40:Age_year15-20 0.5327
## PMTill:Sample_depth_cm5-10:Age_year15-20 0.7678
## PMTill:FSDMP1:Age_year15-20 0.3087
## PMTill:FSDMP2:Age_year15-20 0.1332
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.6806
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.1247
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.2694
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.7906
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.2743
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.4207
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.7271
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.6532
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.6334
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.6443
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.8766
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.3363
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.054 on 391 degrees of freedom
## Multiple R-squared: 0.2778, Adjusted R-squared: 0.1909
## F-statistic: 3.199 on 47 and 391 DF, p-value: 2.465e-10
new_SOC <- step(lm_SOC, direction = "both")
## Start: AIC=1626.19
## SOC..Mg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP:Age_year 6 48.919 14379 1615.7
## <none> 14330 1626.2
##
## Step: AIC=1615.69
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:FSDMP + PM:Sample_depth_cm:Age_year +
## PM:FSDMP:Age_year + Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP:Age_year 6 179.632 14559 1609.1
## - PM:Sample_depth_cm:FSDMP 6 232.940 14612 1610.7
## - PM:Sample_depth_cm:Age_year 3 138.187 14517 1613.9
## <none> 14379 1615.7
## - PM:FSDMP:Age_year 2 132.088 14511 1615.7
## + PM:Sample_depth_cm:FSDMP:Age_year 6 48.919 14330 1626.2
##
## Step: AIC=1609.14
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:FSDMP + PM:Sample_depth_cm:Age_year +
## PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP 6 233.45 14792 1604.1
## - PM:Sample_depth_cm:Age_year 3 140.26 14699 1607.3
## - PM:FSDMP:Age_year 2 133.13 14692 1609.1
## <none> 14559 1609.1
## + Sample_depth_cm:FSDMP:Age_year 6 179.63 14379 1615.7
##
## Step: AIC=1604.12
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP 6 125.68 14918 1595.8
## - PM:Sample_depth_cm:Age_year 3 139.82 14932 1602.2
## - PM:FSDMP:Age_year 2 132.57 14925 1604.0
## <none> 14792 1604.1
## + PM:Sample_depth_cm:FSDMP 6 233.45 14559 1609.1
## + Sample_depth_cm:FSDMP:Age_year 6 180.15 14612 1610.7
##
## Step: AIC=1595.84
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:Age_year 3 139.75 15058 1593.9
## - PM:FSDMP:Age_year 2 132.47 15050 1595.7
## <none> 14918 1595.8
## + Sample_depth_cm:FSDMP 6 125.68 14792 1604.1
##
## Step: AIC=1593.93
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:Age_year 3 98.01 15156 1590.8
## - PM:FSDMP:Age_year 2 131.62 15189 1593.8
## <none> 15058 1593.9
## + PM:Sample_depth_cm:Age_year 3 139.75 14918 1595.8
## - PM:Sample_depth_cm 3 339.40 15397 1597.7
## + Sample_depth_cm:FSDMP 6 125.61 14932 1602.2
##
## Step: AIC=1590.78
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + FSDMP:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:FSDMP:Age_year 2 131.08 15287 1590.6
## <none> 15156 1590.8
## + Sample_depth_cm:Age_year 3 98.01 15058 1593.9
## - PM:Sample_depth_cm 3 339.86 15496 1594.5
## + Sample_depth_cm:FSDMP 6 125.57 15030 1599.1
##
## Step: AIC=1590.56
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - FSDMP:Age_year 2 54.47 15341 1588.1
## - PM:FSDMP 2 55.43 15342 1588.2
## - PM:Age_year 1 27.95 15315 1589.4
## <none> 15287 1590.6
## + PM:FSDMP:Age_year 2 131.08 15156 1590.8
## + Sample_depth_cm:Age_year 3 97.47 15189 1593.8
## - PM:Sample_depth_cm 3 340.79 15628 1594.2
## + Sample_depth_cm:FSDMP 6 125.50 15161 1598.9
##
## Step: AIC=1588.12
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:FSDMP 2 55.43 15397 1585.7
## - PM:Age_year 1 29.70 15371 1587.0
## <none> 15341 1588.1
## + FSDMP:Age_year 2 54.47 15287 1590.6
## + Sample_depth_cm:Age_year 3 97.47 15244 1591.3
## - PM:Sample_depth_cm 3 340.79 15682 1591.8
## + Sample_depth_cm:FSDMP 6 125.50 15216 1596.5
##
## Step: AIC=1585.7
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Age_year 1 29.43 15426 1584.5
## <none> 15397 1585.7
## - FSDMP 2 185.34 15582 1587.0
## + PM:FSDMP 2 55.43 15341 1588.1
## + FSDMP:Age_year 2 54.47 15342 1588.2
## + Sample_depth_cm:Age_year 3 97.83 15299 1588.9
## - PM:Sample_depth_cm 3 340.17 15737 1589.3
## + Sample_depth_cm:FSDMP 6 125.54 15271 1594.1
##
## Step: AIC=1584.54
## SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm
##
## Df Sum of Sq RSS AIC
## <none> 15426 1584.5
## + PM:Age_year 1 29.43 15397 1585.7
## - FSDMP 2 185.75 15612 1585.8
## + FSDMP:Age_year 2 56.20 15370 1586.9
## + PM:FSDMP 2 55.17 15371 1587.0
## - Age_year 1 161.17 15587 1587.1
## + Sample_depth_cm:Age_year 3 98.03 15328 1587.7
## - PM:Sample_depth_cm 3 339.83 15766 1588.1
## + Sample_depth_cm:FSDMP 6 125.57 15301 1593.0
lm_SON <- lm(SON..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4, data = data)
summary(lm_SON)
##
## Call:
## lm(formula = SON..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP +
## Age_year)^4, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1675.5 -302.8 -74.9 180.7 10793.7
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 888.05 274.81 3.232
## PMTill 225.73 388.63 0.581
## Sample_depth_cm10-20 24.25 388.63 0.062
## Sample_depth_cm20-40 -105.26 388.63 -0.271
## Sample_depth_cm5-10 1159.81 388.63 2.984
## FSDMP1 -120.37 388.63 -0.310
## FSDMP2 -262.43 378.79 -0.693
## Age_year15-20 -132.15 388.63 -0.340
## PMTill:Sample_depth_cm10-20 -506.98 549.61 -0.922
## PMTill:Sample_depth_cm20-40 -465.07 549.61 -0.846
## PMTill:Sample_depth_cm5-10 -1525.10 549.61 -2.775
## PMTill:FSDMP1 168.27 549.61 0.306
## PMTill:FSDMP2 458.10 542.70 0.844
## PMTill:Age_year15-20 143.00 549.61 0.260
## Sample_depth_cm10-20:FSDMP1 -163.86 549.61 -0.298
## Sample_depth_cm20-40:FSDMP1 -26.22 549.61 -0.048
## Sample_depth_cm5-10:FSDMP1 -1349.84 549.61 -2.456
## Sample_depth_cm10-20:FSDMP2 -73.06 535.69 -0.136
## Sample_depth_cm20-40:FSDMP2 128.59 535.69 0.240
## Sample_depth_cm5-10:FSDMP2 -1290.34 535.69 -2.409
## Sample_depth_cm10-20:Age_year15-20 180.69 549.61 0.329
## Sample_depth_cm20-40:Age_year15-20 1114.27 549.61 2.027
## Sample_depth_cm5-10:Age_year15-20 -1074.73 549.61 -1.955
## FSDMP1:Age_year15-20 207.57 549.61 0.378
## FSDMP2:Age_year15-20 316.94 535.69 0.592
## PMTill:Sample_depth_cm10-20:FSDMP1 234.02 777.27 0.301
## PMTill:Sample_depth_cm20-40:FSDMP1 -43.80 777.27 -0.056
## PMTill:Sample_depth_cm5-10:FSDMP1 1587.32 777.27 2.042
## PMTill:Sample_depth_cm10-20:FSDMP2 203.25 767.49 0.265
## PMTill:Sample_depth_cm20-40:FSDMP2 434.09 767.49 0.566
## PMTill:Sample_depth_cm5-10:FSDMP2 1401.34 767.49 1.826
## PMTill:Sample_depth_cm10-20:Age_year15-20 -43.86 783.32 -0.056
## PMTill:Sample_depth_cm20-40:Age_year15-20 -871.03 777.27 -1.121
## PMTill:Sample_depth_cm5-10:Age_year15-20 1132.63 777.27 1.457
## PMTill:FSDMP1:Age_year15-20 -388.35 777.27 -0.500
## PMTill:FSDMP2:Age_year15-20 -749.01 767.49 -0.976
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 -219.86 777.27 -0.283
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 -824.36 777.27 -1.061
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 919.02 777.27 1.182
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 -115.42 757.59 -0.152
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 -1051.93 757.59 -1.389
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 1141.64 757.59 1.507
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 496.74 1103.51 0.450
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 913.01 1099.22 0.831
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 -991.71 1099.22 -0.902
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 102.62 1089.73 0.094
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 691.49 1085.39 0.637
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 -901.95 1085.39 -0.831
## Pr(>|t|)
## (Intercept) 0.00134 **
## PMTill 0.56170
## Sample_depth_cm10-20 0.95028
## Sample_depth_cm20-40 0.78665
## Sample_depth_cm5-10 0.00302 **
## FSDMP1 0.75694
## FSDMP2 0.48885
## Age_year15-20 0.73401
## PMTill:Sample_depth_cm10-20 0.35687
## PMTill:Sample_depth_cm20-40 0.39797
## PMTill:Sample_depth_cm5-10 0.00579 **
## PMTill:FSDMP1 0.75965
## PMTill:FSDMP2 0.39912
## PMTill:Age_year15-20 0.79486
## Sample_depth_cm10-20:FSDMP1 0.76576
## Sample_depth_cm20-40:FSDMP1 0.96198
## Sample_depth_cm5-10:FSDMP1 0.01448 *
## Sample_depth_cm10-20:FSDMP2 0.89159
## Sample_depth_cm20-40:FSDMP2 0.81042
## Sample_depth_cm5-10:FSDMP2 0.01647 *
## Sample_depth_cm10-20:Age_year15-20 0.74252
## Sample_depth_cm20-40:Age_year15-20 0.04330 *
## Sample_depth_cm5-10:Age_year15-20 0.05124 .
## FSDMP1:Age_year15-20 0.70589
## FSDMP2:Age_year15-20 0.55444
## PMTill:Sample_depth_cm10-20:FSDMP1 0.76351
## PMTill:Sample_depth_cm20-40:FSDMP1 0.95509
## PMTill:Sample_depth_cm5-10:FSDMP1 0.04180 *
## PMTill:Sample_depth_cm10-20:FSDMP2 0.79129
## PMTill:Sample_depth_cm20-40:FSDMP2 0.57199
## PMTill:Sample_depth_cm5-10:FSDMP2 0.06863 .
## PMTill:Sample_depth_cm10-20:Age_year15-20 0.95537
## PMTill:Sample_depth_cm20-40:Age_year15-20 0.26313
## PMTill:Sample_depth_cm5-10:Age_year15-20 0.14587
## PMTill:FSDMP1:Age_year15-20 0.61761
## PMTill:FSDMP2:Age_year15-20 0.32971
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.77743
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.28953
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.23777
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.87899
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.16576
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.13263
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.65285
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.40671
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.36751
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.92502
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.52444
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.40649
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 824.4 on 391 degrees of freedom
## Multiple R-squared: 0.1228, Adjusted R-squared: 0.0174
## F-statistic: 1.165 on 47 and 391 DF, p-value: 0.2208
new_SON <- step(lm_SON, direction = "both")
## Start: AIC=5940.65
## SON..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP:Age_year 6 2606172 268353559 5932.9
## <none> 265747387 5940.7
##
## Step: AIC=5932.94
## SON..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:FSDMP + PM:Sample_depth_cm:Age_year +
## PM:FSDMP:Age_year + Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP 6 4270115 272623674 5927.9
## - Sample_depth_cm:FSDMP:Age_year 6 4615530 272969089 5928.4
## - PM:Sample_depth_cm:Age_year 3 2450406 270803965 5930.9
## <none> 268353559 5932.9
## - PM:FSDMP:Age_year 2 2857454 271211013 5933.6
## + PM:Sample_depth_cm:FSDMP:Age_year 6 2606172 265747387 5940.7
##
## Step: AIC=5927.87
## SON..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year +
## Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP:Age_year 6 4614932 277238606 5923.2
## - PM:Sample_depth_cm:Age_year 3 2448586 275072260 5925.8
## <none> 272623674 5927.9
## - PM:FSDMP:Age_year 2 2848842 275472516 5928.4
## + PM:Sample_depth_cm:FSDMP 6 4270115 268353559 5932.9
##
## Step: AIC=5923.24
## SON..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP 6 1847106 279085711 5914.2
## - PM:Sample_depth_cm:Age_year 3 2316215 279554821 5920.9
## <none> 277238606 5923.2
## - PM:FSDMP:Age_year 2 2847834 280086440 5923.7
## + Sample_depth_cm:FSDMP:Age_year 6 4614932 272623674 5927.9
## + PM:Sample_depth_cm:FSDMP 6 4269516 272969089 5928.4
##
## Step: AIC=5914.15
## SON..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:Age_year 3 2318743 281404454 5911.8
## <none> 279085711 5914.2
## - PM:FSDMP:Age_year 2 2859650 281945361 5914.6
## + Sample_depth_cm:FSDMP 6 1847106 277238606 5923.2
##
## Step: AIC=5911.78
## SON..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:Age_year 3 3079361 284483815 5910.6
## - PM:Sample_depth_cm 3 3442951 284847406 5911.1
## <none> 281404454 5911.8
## - PM:FSDMP:Age_year 2 2855980 284260434 5912.2
## + PM:Sample_depth_cm:Age_year 3 2318743 279085711 5914.2
## + Sample_depth_cm:FSDMP 6 1849633 279554821 5920.9
##
## Step: AIC=5910.56
## SON..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + FSDMP:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm 3 3443615 287927430 5909.8
## <none> 284483815 5910.6
## - PM:FSDMP:Age_year 2 2850052 287333867 5910.9
## + Sample_depth_cm:Age_year 3 3079361 281404454 5911.8
## + Sample_depth_cm:FSDMP 6 1853738 282630078 5919.7
##
## Step: AIC=5909.84
## SON..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:FSDMP +
## PM:Age_year + FSDMP:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm 3 1434247 289361677 5906.0
## <none> 287927430 5909.8
## - PM:FSDMP:Age_year 2 2851996 290779426 5910.2
## + PM:Sample_depth_cm 3 3443615 284483815 5910.6
## + Sample_depth_cm:Age_year 3 3080024 284847406 5911.1
## + Sample_depth_cm:FSDMP 6 1884206 286043224 5919.0
##
## Step: AIC=5906.02
## SON..kg.ha. ~ PM + FSDMP + Age_year + PM:FSDMP + PM:Age_year +
## FSDMP:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## <none> 289361677 5906.0
## - PM:FSDMP:Age_year 2 2868134 292229811 5906.4
## + Sample_depth_cm 3 1434247 287927430 5909.8
lm_Ca <- lm(Ca.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4, data = data)
summary(lm_Ca)
##
## Call:
## lm(formula = Ca.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP +
## Age_year)^4, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2236.2 -253.4 -47.2 166.8 3329.4
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 484.369 232.457 2.084
## PMTill 282.221 328.743 0.858
## Sample_depth_cm10-20 -12.804 328.743 -0.039
## Sample_depth_cm20-40 36.179 328.743 0.110
## Sample_depth_cm5-10 -115.730 328.743 -0.352
## FSDMP1 -65.730 328.743 -0.200
## FSDMP2 -137.282 320.419 -0.428
## Age_year15-20 -161.819 328.743 -0.492
## PMTill:Sample_depth_cm10-20 -76.609 464.913 -0.165
## PMTill:Sample_depth_cm20-40 676.334 464.913 1.455
## PMTill:Sample_depth_cm5-10 -84.330 464.913 -0.181
## PMTill:FSDMP1 118.270 464.913 0.254
## PMTill:FSDMP2 197.975 459.065 0.431
## PMTill:Age_year15-20 150.788 464.913 0.324
## Sample_depth_cm10-20:FSDMP1 -129.336 464.913 -0.278
## Sample_depth_cm20-40:FSDMP1 91.154 464.913 0.196
## Sample_depth_cm5-10:FSDMP1 -36.892 464.913 -0.079
## Sample_depth_cm10-20:FSDMP2 261.170 453.141 0.576
## Sample_depth_cm20-40:FSDMP2 127.958 453.141 0.282
## Sample_depth_cm5-10:FSDMP2 -3.687 453.141 -0.008
## Sample_depth_cm10-20:Age_year15-20 62.774 464.913 0.135
## Sample_depth_cm20-40:Age_year15-20 130.145 464.913 0.280
## Sample_depth_cm5-10:Age_year15-20 176.187 464.913 0.379
## FSDMP1:Age_year15-20 170.618 464.913 0.367
## FSDMP2:Age_year15-20 265.008 453.141 0.585
## PMTill:Sample_depth_cm10-20:FSDMP1 378.510 657.486 0.576
## PMTill:Sample_depth_cm20-40:FSDMP1 960.289 657.486 1.461
## PMTill:Sample_depth_cm5-10:FSDMP1 240.948 657.486 0.366
## PMTill:Sample_depth_cm10-20:FSDMP2 343.490 649.216 0.529
## PMTill:Sample_depth_cm20-40:FSDMP2 1440.720 649.216 2.219
## PMTill:Sample_depth_cm5-10:FSDMP2 162.284 649.216 0.250
## PMTill:Sample_depth_cm10-20:Age_year15-20 148.630 662.603 0.224
## PMTill:Sample_depth_cm20-40:Age_year15-20 776.735 657.486 1.181
## PMTill:Sample_depth_cm5-10:Age_year15-20 -55.207 657.486 -0.084
## PMTill:FSDMP1:Age_year15-20 -319.911 657.486 -0.487
## PMTill:FSDMP2:Age_year15-20 -500.799 649.216 -0.771
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 130.269 657.486 0.198
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 -211.751 657.486 -0.322
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 -137.313 657.486 -0.209
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 -251.947 640.838 -0.393
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 -164.455 640.838 -0.257
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 101.866 640.838 0.159
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 -56.477 933.451 -0.061
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 -718.062 929.826 -0.772
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 38.386 929.826 0.041
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 -206.283 921.801 -0.224
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 -1402.963 918.130 -1.528
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 -68.016 918.130 -0.074
## Pr(>|t|)
## (Intercept) 0.0378 *
## PMTill 0.3912
## Sample_depth_cm10-20 0.9690
## Sample_depth_cm20-40 0.9124
## Sample_depth_cm5-10 0.7250
## FSDMP1 0.8416
## FSDMP2 0.6686
## Age_year15-20 0.6228
## PMTill:Sample_depth_cm10-20 0.8692
## PMTill:Sample_depth_cm20-40 0.1465
## PMTill:Sample_depth_cm5-10 0.8562
## PMTill:FSDMP1 0.7993
## PMTill:FSDMP2 0.6665
## PMTill:Age_year15-20 0.7459
## Sample_depth_cm10-20:FSDMP1 0.7810
## Sample_depth_cm20-40:FSDMP1 0.8447
## Sample_depth_cm5-10:FSDMP1 0.9368
## Sample_depth_cm10-20:FSDMP2 0.5647
## Sample_depth_cm20-40:FSDMP2 0.7778
## Sample_depth_cm5-10:FSDMP2 0.9935
## Sample_depth_cm10-20:Age_year15-20 0.8927
## Sample_depth_cm20-40:Age_year15-20 0.7797
## Sample_depth_cm5-10:Age_year15-20 0.7049
## FSDMP1:Age_year15-20 0.7138
## FSDMP2:Age_year15-20 0.5590
## PMTill:Sample_depth_cm10-20:FSDMP1 0.5652
## PMTill:Sample_depth_cm20-40:FSDMP1 0.1449
## PMTill:Sample_depth_cm5-10:FSDMP1 0.7142
## PMTill:Sample_depth_cm10-20:FSDMP2 0.5970
## PMTill:Sample_depth_cm20-40:FSDMP2 0.0270 *
## PMTill:Sample_depth_cm5-10:FSDMP2 0.8027
## PMTill:Sample_depth_cm10-20:Age_year15-20 0.8226
## PMTill:Sample_depth_cm20-40:Age_year15-20 0.2382
## PMTill:Sample_depth_cm5-10:Age_year15-20 0.9331
## PMTill:FSDMP1:Age_year15-20 0.6268
## PMTill:FSDMP2:Age_year15-20 0.4409
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.8430
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.7476
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.8347
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.6944
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.7976
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.8738
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.9518
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.4404
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.9671
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.8230
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.1273
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.9410
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 697.4 on 391 degrees of freedom
## Multiple R-squared: 0.488, Adjusted R-squared: 0.4265
## F-statistic: 7.931 on 47 and 391 DF, p-value: < 2.2e-16
new_Ca <- step(lm_Ca, direction = "both")
## Start: AIC=5793.71
## Ca.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP:Age_year 6 1519126 191671985 5785.2
## <none> 190152859 5793.7
##
## Step: AIC=5785.2
## Ca.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:FSDMP + PM:Sample_depth_cm:Age_year +
## PM:FSDMP:Age_year + Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP 6 1661100 193333084 5777.0
## - PM:Sample_depth_cm:Age_year 3 72983 191744968 5779.4
## - Sample_depth_cm:FSDMP:Age_year 6 3175065 194847049 5780.4
## <none> 191671985 5785.2
## - PM:FSDMP:Age_year 2 3905304 195577288 5790.1
## + PM:Sample_depth_cm:FSDMP:Age_year 6 1519126 190152859 5793.7
##
## Step: AIC=5776.99
## Ca.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year +
## Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:Age_year 3 73011 193406095 5771.2
## - Sample_depth_cm:FSDMP:Age_year 6 3175016 196508100 5772.1
## <none> 193333084 5777.0
## - PM:FSDMP:Age_year 2 3905809 197238893 5781.8
## + PM:Sample_depth_cm:FSDMP 6 1661100 191671985 5785.2
##
## Step: AIC=5771.16
## Ca.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:FSDMP:Age_year + Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP:Age_year 6 3194921 196601016 5766.4
## <none> 193406095 5771.2
## - PM:FSDMP:Age_year 2 3902854 197308949 5775.9
## + PM:Sample_depth_cm:Age_year 3 73011 193333084 5777.0
## + PM:Sample_depth_cm:FSDMP 6 1661128 191744968 5779.4
## - PM:Sample_depth_cm 3 43683546 237089641 5854.6
##
## Step: AIC=5766.35
## Ca.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP 6 1903944 198504959 5758.6
## - Sample_depth_cm:Age_year 3 265514 196866530 5760.9
## <none> 196601016 5766.4
## - PM:FSDMP:Age_year 2 3910322 200511337 5771.0
## + Sample_depth_cm:FSDMP:Age_year 6 3194921 193406095 5771.2
## + PM:Sample_depth_cm:Age_year 3 92915 196508100 5772.1
## + PM:Sample_depth_cm:FSDMP 6 1661070 194939946 5774.6
## - PM:Sample_depth_cm 3 43676700 240277716 5848.4
##
## Step: AIC=5758.58
## Ca.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:Age_year 3 265378 198770337 5753.2
## <none> 198504959 5758.6
## - PM:FSDMP:Age_year 2 3915972 202420932 5763.2
## + PM:Sample_depth_cm:Age_year 3 93522 198411437 5764.4
## + Sample_depth_cm:FSDMP 6 1903944 196601016 5766.4
## - PM:Sample_depth_cm 3 43438166 241943125 5839.5
##
## Step: AIC=5753.17
## Ca.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + FSDMP:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## <none> 198770337 5753.2
## - PM:FSDMP:Age_year 2 3916826 202687164 5757.7
## + Sample_depth_cm:Age_year 3 265378 198504959 5758.6
## + Sample_depth_cm:FSDMP 6 1903807 196866530 5760.9
## - PM:Sample_depth_cm 3 43437530 242207867 5833.9
lm_Mg <- lm(Mg.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4, data = data)
summary(lm_Mg)
##
## Call:
## lm(formula = Mg.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP +
## Age_year)^4, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -771.20 -29.88 -6.16 19.77 1004.42
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 50.3375 63.5332 0.792
## PMTill 50.6485 89.8495 0.564
## Sample_depth_cm10-20 10.7221 89.8495 0.119
## Sample_depth_cm20-40 31.5950 89.8495 0.352
## Sample_depth_cm5-10 -9.1747 89.8495 -0.102
## FSDMP1 -8.1277 89.8495 -0.090
## FSDMP2 -6.9135 87.5745 -0.079
## Age_year15-20 -13.4751 89.8495 -0.150
## PMTill:Sample_depth_cm10-20 11.8176 127.0664 0.093
## PMTill:Sample_depth_cm20-40 253.4119 127.0664 1.994
## PMTill:Sample_depth_cm5-10 -16.7715 127.0664 -0.132
## PMTill:FSDMP1 16.7501 127.0664 0.132
## PMTill:FSDMP2 50.2803 125.4681 0.401
## PMTill:Age_year15-20 -2.9602 127.0664 -0.023
## Sample_depth_cm10-20:FSDMP1 -17.1393 127.0664 -0.135
## Sample_depth_cm20-40:FSDMP1 -14.1272 127.0664 -0.111
## Sample_depth_cm5-10:FSDMP1 -5.6876 127.0664 -0.045
## Sample_depth_cm10-20:FSDMP2 20.9355 123.8490 0.169
## Sample_depth_cm20-40:FSDMP2 -0.7660 123.8490 -0.006
## Sample_depth_cm5-10:FSDMP2 -8.7248 123.8490 -0.070
## Sample_depth_cm10-20:Age_year15-20 -3.4173 127.0664 -0.027
## Sample_depth_cm20-40:Age_year15-20 -1.3108 127.0664 -0.010
## Sample_depth_cm5-10:Age_year15-20 6.7928 127.0664 0.053
## FSDMP1:Age_year15-20 8.7750 127.0664 0.069
## FSDMP2:Age_year15-20 16.2050 123.8490 0.131
## PMTill:Sample_depth_cm10-20:FSDMP1 60.7202 179.6991 0.338
## PMTill:Sample_depth_cm20-40:FSDMP1 338.9710 179.6991 1.886
## PMTill:Sample_depth_cm5-10:FSDMP1 35.7718 179.6991 0.199
## PMTill:Sample_depth_cm10-20:FSDMP2 176.5598 177.4386 0.995
## PMTill:Sample_depth_cm20-40:FSDMP2 457.1233 177.4386 2.576
## PMTill:Sample_depth_cm5-10:FSDMP2 37.7370 177.4386 0.213
## PMTill:Sample_depth_cm10-20:Age_year15-20 31.2058 181.0975 0.172
## PMTill:Sample_depth_cm20-40:Age_year15-20 199.7348 179.6991 1.111
## PMTill:Sample_depth_cm5-10:Age_year15-20 15.5541 179.6991 0.087
## PMTill:FSDMP1:Age_year15-20 -17.3593 179.6991 -0.097
## PMTill:FSDMP2:Age_year15-20 -80.3270 177.4386 -0.453
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 15.9275 179.6991 0.089
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.4999 179.6991 0.003
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 -2.5846 179.6991 -0.014
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 -34.0737 175.1490 -0.195
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 -2.5627 175.1490 -0.015
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 -2.2841 175.1490 -0.013
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 -1.5172 255.1237 -0.006
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 -292.0413 254.1329 -1.149
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 -23.3287 254.1329 -0.092
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 -153.2354 251.9395 -0.608
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 -497.2556 250.9361 -1.982
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 -14.4368 250.9361 -0.058
## Pr(>|t|)
## (Intercept) 0.4287
## PMTill 0.5733
## Sample_depth_cm10-20 0.9051
## Sample_depth_cm20-40 0.7253
## Sample_depth_cm5-10 0.9187
## FSDMP1 0.9280
## FSDMP2 0.9371
## Age_year15-20 0.8809
## PMTill:Sample_depth_cm10-20 0.9259
## PMTill:Sample_depth_cm20-40 0.0468 *
## PMTill:Sample_depth_cm5-10 0.8951
## PMTill:FSDMP1 0.8952
## PMTill:FSDMP2 0.6888
## PMTill:Age_year15-20 0.9814
## Sample_depth_cm10-20:FSDMP1 0.8928
## Sample_depth_cm20-40:FSDMP1 0.9115
## Sample_depth_cm5-10:FSDMP1 0.9643
## Sample_depth_cm10-20:FSDMP2 0.8659
## Sample_depth_cm20-40:FSDMP2 0.9951
## Sample_depth_cm5-10:FSDMP2 0.9439
## Sample_depth_cm10-20:Age_year15-20 0.9786
## Sample_depth_cm20-40:Age_year15-20 0.9918
## Sample_depth_cm5-10:Age_year15-20 0.9574
## FSDMP1:Age_year15-20 0.9450
## FSDMP2:Age_year15-20 0.8960
## PMTill:Sample_depth_cm10-20:FSDMP1 0.7356
## PMTill:Sample_depth_cm20-40:FSDMP1 0.0600 .
## PMTill:Sample_depth_cm5-10:FSDMP1 0.8423
## PMTill:Sample_depth_cm10-20:FSDMP2 0.3203
## PMTill:Sample_depth_cm20-40:FSDMP2 0.0104 *
## PMTill:Sample_depth_cm5-10:FSDMP2 0.8317
## PMTill:Sample_depth_cm10-20:Age_year15-20 0.8633
## PMTill:Sample_depth_cm20-40:Age_year15-20 0.2670
## PMTill:Sample_depth_cm5-10:Age_year15-20 0.9311
## PMTill:FSDMP1:Age_year15-20 0.9231
## PMTill:FSDMP2:Age_year15-20 0.6510
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.9294
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.9978
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.9885
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.8459
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.9883
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.9896
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.9953
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.2512
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.9269
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.5434
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.0482 *
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.9542
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 190.6 on 391 degrees of freedom
## Multiple R-squared: 0.5301, Adjusted R-squared: 0.4736
## F-statistic: 9.385 on 47 and 391 DF, p-value: < 2.2e-16
new_Mg <- step(lm_Mg, direction = "both")
## Start: AIC=4654.82
## Mg.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP:Age_year 6 196263 14400602 4648.8
## <none> 14204338 4654.8
##
## Step: AIC=4648.85
## Mg.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:FSDMP + PM:Sample_depth_cm:Age_year +
## PM:FSDMP:Age_year + Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP 6 148016 14548617 4641.3
## - Sample_depth_cm:FSDMP:Age_year 6 210410 14611012 4643.2
## - PM:Sample_depth_cm:Age_year 3 21747 14422349 4643.5
## <none> 14400602 4648.8
## - PM:FSDMP:Age_year 2 285515 14686117 4653.5
## + PM:Sample_depth_cm:FSDMP:Age_year 6 196263 14204338 4654.8
##
## Step: AIC=4641.33
## Mg.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year +
## Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP:Age_year 6 210399 14759017 4635.6
## - PM:Sample_depth_cm:Age_year 3 21747 14570365 4636.0
## <none> 14548617 4641.3
## - PM:FSDMP:Age_year 2 285592 14834209 4645.9
## + PM:Sample_depth_cm:FSDMP 6 148016 14400602 4648.8
##
## Step: AIC=4635.64
## Mg.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP 6 142114 14901131 4627.8
## - PM:Sample_depth_cm:Age_year 3 19274 14778290 4630.2
## <none> 14759017 4635.6
## - PM:FSDMP:Age_year 2 285950 15044967 4640.1
## + Sample_depth_cm:FSDMP:Age_year 6 210399 14548617 4641.3
## + PM:Sample_depth_cm:FSDMP 6 148005 14611012 4643.2
##
## Step: AIC=4627.84
## Mg.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:Age_year 3 19275 14920406 4622.4
## <none> 14901131 4627.8
## - PM:FSDMP:Age_year 2 286091 15187222 4632.2
## + Sample_depth_cm:FSDMP 6 142114 14759017 4635.6
##
## Step: AIC=4622.41
## Mg.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:Age_year 3 27353 14947758 4617.2
## <none> 14920406 4622.4
## - PM:FSDMP:Age_year 2 286082 15206488 4626.7
## + PM:Sample_depth_cm:Age_year 3 19275 14901131 4627.8
## + Sample_depth_cm:FSDMP 6 142115 14778290 4630.2
## - PM:Sample_depth_cm 3 4410798 19331204 4730.1
##
## Step: AIC=4617.22
## Mg.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + FSDMP:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## <none> 14947758 4617.2
## - PM:FSDMP:Age_year 2 286335 15234093 4621.5
## + Sample_depth_cm:Age_year 3 27353 14920406 4622.4
## + Sample_depth_cm:FSDMP 6 142098 14805660 4625.0
## - PM:Sample_depth_cm 3 4410534 19358293 4724.7
lm_K <- lm(K.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4, data = data)
summary(lm_K)
##
## Call:
## lm(formula = K.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP +
## Age_year)^4, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -205.49 -22.94 -3.45 15.81 452.28
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 34.46632 19.50508 1.767
## PMTill 29.62943 27.58435 1.074
## Sample_depth_cm10-20 47.84820 27.58435 1.735
## Sample_depth_cm20-40 89.19188 27.58435 3.233
## Sample_depth_cm5-10 3.76497 27.58435 0.136
## FSDMP1 0.02136 27.58435 0.001
## FSDMP2 7.13429 26.88590 0.265
## Age_year15-20 -3.57988 27.58435 -0.130
## PMTill:Sample_depth_cm10-20 -13.83368 39.01017 -0.355
## PMTill:Sample_depth_cm20-40 21.27825 39.01017 0.545
## PMTill:Sample_depth_cm5-10 -9.39071 39.01017 -0.241
## PMTill:FSDMP1 3.52705 39.01017 0.090
## PMTill:FSDMP2 1.96469 38.51945 0.051
## PMTill:Age_year15-20 -8.36790 39.01017 -0.215
## Sample_depth_cm10-20:FSDMP1 -24.81818 39.01017 -0.636
## Sample_depth_cm20-40:FSDMP1 -32.68241 39.01017 -0.838
## Sample_depth_cm5-10:FSDMP1 -5.46072 39.01017 -0.140
## Sample_depth_cm10-20:FSDMP2 16.64375 38.02241 0.438
## Sample_depth_cm20-40:FSDMP2 -26.80756 38.02241 -0.705
## Sample_depth_cm5-10:FSDMP2 -12.86170 38.02241 -0.338
## Sample_depth_cm10-20:Age_year15-20 -18.55583 39.01017 -0.476
## Sample_depth_cm20-40:Age_year15-20 6.02315 39.01017 0.154
## Sample_depth_cm5-10:Age_year15-20 -4.10353 39.01017 -0.105
## FSDMP1:Age_year15-20 3.64247 39.01017 0.093
## FSDMP2:Age_year15-20 -0.66362 38.02241 -0.017
## PMTill:Sample_depth_cm10-20:FSDMP1 41.71467 55.16871 0.756
## PMTill:Sample_depth_cm20-40:FSDMP1 66.98096 55.16871 1.214
## PMTill:Sample_depth_cm5-10:FSDMP1 33.49636 55.16871 0.607
## PMTill:Sample_depth_cm10-20:FSDMP2 4.00625 54.47473 0.074
## PMTill:Sample_depth_cm20-40:FSDMP2 55.43793 54.47473 1.018
## PMTill:Sample_depth_cm5-10:FSDMP2 12.93382 54.47473 0.237
## PMTill:Sample_depth_cm10-20:Age_year15-20 47.37713 55.59804 0.852
## PMTill:Sample_depth_cm20-40:Age_year15-20 59.36573 55.16871 1.076
## PMTill:Sample_depth_cm5-10:Age_year15-20 13.62472 55.16871 0.247
## PMTill:FSDMP1:Age_year15-20 -7.62672 55.16871 -0.138
## PMTill:FSDMP2:Age_year15-20 -15.31532 54.47473 -0.281
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 40.54301 55.16871 0.735
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 20.65087 55.16871 0.374
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 2.77303 55.16871 0.050
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 -22.30938 53.77180 -0.415
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 6.19571 53.77180 0.115
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 10.66845 53.77180 0.198
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 -66.19499 78.32451 -0.845
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 -75.83459 78.02033 -0.972
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 -29.67738 78.02033 -0.380
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 6.83721 77.34694 0.088
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 -5.30551 77.03891 -0.069
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 1.74461 77.03891 0.023
## Pr(>|t|)
## (Intercept) 0.07800 .
## PMTill 0.28342
## Sample_depth_cm10-20 0.08360 .
## Sample_depth_cm20-40 0.00133 **
## Sample_depth_cm5-10 0.89150
## FSDMP1 0.99938
## FSDMP2 0.79088
## Age_year15-20 0.89681
## PMTill:Sample_depth_cm10-20 0.72307
## PMTill:Sample_depth_cm20-40 0.58575
## PMTill:Sample_depth_cm5-10 0.80989
## PMTill:FSDMP1 0.92800
## PMTill:FSDMP2 0.95935
## PMTill:Age_year15-20 0.83026
## Sample_depth_cm10-20:FSDMP1 0.52502
## Sample_depth_cm20-40:FSDMP1 0.40266
## Sample_depth_cm5-10:FSDMP1 0.88875
## Sample_depth_cm10-20:FSDMP2 0.66182
## Sample_depth_cm20-40:FSDMP2 0.48120
## Sample_depth_cm5-10:FSDMP2 0.73534
## Sample_depth_cm10-20:Age_year15-20 0.63458
## Sample_depth_cm20-40:Age_year15-20 0.87737
## Sample_depth_cm5-10:Age_year15-20 0.91628
## FSDMP1:Age_year15-20 0.92566
## FSDMP2:Age_year15-20 0.98608
## PMTill:Sample_depth_cm10-20:FSDMP1 0.45003
## PMTill:Sample_depth_cm20-40:FSDMP1 0.22544
## PMTill:Sample_depth_cm5-10:FSDMP1 0.54410
## PMTill:Sample_depth_cm10-20:FSDMP2 0.94141
## PMTill:Sample_depth_cm20-40:FSDMP2 0.30946
## PMTill:Sample_depth_cm5-10:FSDMP2 0.81245
## PMTill:Sample_depth_cm10-20:Age_year15-20 0.39466
## PMTill:Sample_depth_cm20-40:Age_year15-20 0.28256
## PMTill:Sample_depth_cm5-10:Age_year15-20 0.80507
## PMTill:FSDMP1:Age_year15-20 0.89012
## PMTill:FSDMP2:Age_year15-20 0.77875
## Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.46285
## Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.70837
## Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.95994
## Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.67845
## Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.90833
## Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.84283
## PMTill:Sample_depth_cm10-20:FSDMP1:Age_year15-20 0.39855
## PMTill:Sample_depth_cm20-40:FSDMP1:Age_year15-20 0.33166
## PMTill:Sample_depth_cm5-10:FSDMP1:Age_year15-20 0.70387
## PMTill:Sample_depth_cm10-20:FSDMP2:Age_year15-20 0.92961
## PMTill:Sample_depth_cm20-40:FSDMP2:Age_year15-20 0.94513
## PMTill:Sample_depth_cm5-10:FSDMP2:Age_year15-20 0.98194
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 58.52 on 391 degrees of freedom
## Multiple R-squared: 0.5112, Adjusted R-squared: 0.4525
## F-statistic: 8.702 on 47 and 391 DF, p-value: < 2.2e-16
new_K <- step(lm_K, direction = "both")
## Start: AIC=3618
## K.mass..kg.ha. ~ (1 + PM + Sample_depth_cm + FSDMP + Age_year)^4
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP:Age_year 6 5565.7 1344363 3607.8
## <none> 1338797 3618.0
##
## Step: AIC=3607.82
## K.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:FSDMP + PM:Sample_depth_cm:Age_year +
## PM:FSDMP:Age_year + Sample_depth_cm:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP:Age_year 6 7724.7 1352088 3598.3
## - PM:Sample_depth_cm:FSDMP 6 8119.7 1352483 3598.5
## - PM:Sample_depth_cm:Age_year 3 5556.4 1349920 3603.6
## - PM:FSDMP:Age_year 2 12173.3 1356536 3607.8
## <none> 1344363 3607.8
## + PM:Sample_depth_cm:FSDMP:Age_year 6 5565.7 1338797 3618.0
##
## Step: AIC=3598.34
## K.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:FSDMP + PM:Sample_depth_cm:Age_year +
## PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:FSDMP 6 8114.6 1360203 3589.0
## - PM:Sample_depth_cm:Age_year 3 5650.0 1357738 3594.2
## - PM:FSDMP:Age_year 2 12163.7 1364252 3598.3
## <none> 1352088 3598.3
## + Sample_depth_cm:FSDMP:Age_year 6 7724.7 1344363 3607.8
##
## Step: AIC=3588.97
## K.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:FSDMP + Sample_depth_cm:Age_year +
## FSDMP:Age_year + PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:FSDMP 6 3994.2 1364197 3578.3
## - PM:Sample_depth_cm:Age_year 3 5631.8 1365834 3584.8
## - PM:FSDMP:Age_year 2 12132.3 1372335 3588.9
## <none> 1360203 3589.0
## + PM:Sample_depth_cm:FSDMP 6 8114.6 1352088 3598.3
## + Sample_depth_cm:FSDMP:Age_year 6 7719.7 1352483 3598.5
##
## Step: AIC=3578.25
## K.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:Sample_depth_cm:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Sample_depth_cm:Age_year 3 5647.7 1369844 3574.1
## - PM:FSDMP:Age_year 2 12160.0 1376357 3578.1
## <none> 1364197 3578.3
## + Sample_depth_cm:FSDMP 6 3994.2 1360203 3589.0
##
## Step: AIC=3574.07
## K.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + Sample_depth_cm:Age_year + FSDMP:Age_year +
## PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - Sample_depth_cm:Age_year 3 18372 1388217 3573.9
## - PM:FSDMP:Age_year 2 12125 1381970 3573.9
## <none> 1369844 3574.1
## + PM:Sample_depth_cm:Age_year 3 5648 1364197 3578.3
## + Sample_depth_cm:FSDMP 6 4010 1365834 3584.8
## - PM:Sample_depth_cm 3 106342 1476186 3600.9
##
## Step: AIC=3573.91
## K.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + FSDMP:Age_year + PM:FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:FSDMP:Age_year 2 12170 1400387 3573.7
## <none> 1388217 3573.9
## + Sample_depth_cm:Age_year 3 18372 1369844 3574.1
## + Sample_depth_cm:FSDMP 6 3990 1384227 3584.7
## - PM:Sample_depth_cm 3 106298 1494514 3600.3
##
## Step: AIC=3573.75
## K.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year + FSDMP:Age_year
##
## Df Sum of Sq RSS AIC
## - FSDMP:Age_year 2 1624 1402011 3570.3
## - PM:FSDMP 2 4342 1404729 3571.1
## - PM:Age_year 1 0 1400387 3571.7
## <none> 1400387 3573.7
## + PM:FSDMP:Age_year 2 12170 1388217 3573.9
## + Sample_depth_cm:Age_year 3 18417 1381970 3573.9
## + Sample_depth_cm:FSDMP 6 4017 1396370 3584.5
## - PM:Sample_depth_cm 3 106357 1506744 3599.9
##
## Step: AIC=3570.26
## K.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:FSDMP + PM:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:FSDMP 2 4365 1406376 3567.6
## - PM:Age_year 1 1 1402012 3568.3
## <none> 1402011 3570.3
## + Sample_depth_cm:Age_year 3 18438 1383573 3570.4
## + FSDMP:Age_year 2 1624 1400387 3573.7
## + Sample_depth_cm:FSDMP 6 4030 1397981 3581.0
## - PM:Sample_depth_cm 3 106385 1508396 3596.4
##
## Step: AIC=3567.62
## K.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year + PM:Sample_depth_cm +
## PM:Age_year
##
## Df Sum of Sq RSS AIC
## - FSDMP 2 3879 1410255 3564.8
## - PM:Age_year 1 2 1406378 3565.6
## <none> 1406376 3567.6
## + Sample_depth_cm:Age_year 3 18400 1387976 3567.8
## + PM:FSDMP 2 4365 1402011 3570.3
## + FSDMP:Age_year 2 1647 1404729 3571.1
## + Sample_depth_cm:FSDMP 6 4007 1402369 3578.4
## - PM:Sample_depth_cm 3 106335 1512711 3593.6
##
## Step: AIC=3564.83
## K.mass..kg.ha. ~ PM + Sample_depth_cm + Age_year + PM:Sample_depth_cm +
## PM:Age_year
##
## Df Sum of Sq RSS AIC
## - PM:Age_year 1 2 1410257 3562.8
## <none> 1410255 3564.8
## + Sample_depth_cm:Age_year 3 18379 1391876 3565.1
## + FSDMP 2 3879 1406376 3567.6
## - PM:Sample_depth_cm 3 106307 1516562 3590.7
##
## Step: AIC=3562.83
## K.mass..kg.ha. ~ PM + Sample_depth_cm + Age_year + PM:Sample_depth_cm
##
## Df Sum of Sq RSS AIC
## - Age_year 1 442 1410699 3561.0
## <none> 1410257 3562.8
## + Sample_depth_cm:Age_year 3 18380 1391878 3563.1
## + PM:Age_year 1 2 1410255 3564.8
## + FSDMP 2 3879 1406378 3565.6
## - PM:Sample_depth_cm 3 106308 1516565 3588.7
##
## Step: AIC=3560.97
## K.mass..kg.ha. ~ PM + Sample_depth_cm + PM:Sample_depth_cm
##
## Df Sum of Sq RSS AIC
## <none> 1410699 3561.0
## + Age_year 1 442 1410257 3562.8
## + FSDMP 2 3874 1406825 3563.8
## - PM:Sample_depth_cm 3 106297 1516996 3586.9
summary(new_P)
##
## Call:
## lm(formula = P.mass..kg.ha. ~ PM + Sample_depth_cm + Age_year +
## PM:Sample_depth_cm + Sample_depth_cm:Age_year, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -195.71 -20.40 -4.67 11.28 363.17
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16.5793 9.5549 1.735 0.0834 .
## PMTill -4.9375 11.1011 -0.445 0.6567
## Sample_depth_cm10-20 94.2607 13.5233 6.970 1.21e-11 ***
## Sample_depth_cm20-40 169.0724 13.5126 12.512 < 2e-16 ***
## Sample_depth_cm5-10 10.3773 13.5126 0.768 0.4429
## Age_year15-20 -4.0538 11.0993 -0.365 0.7151
## PMTill:Sample_depth_cm10-20 -74.4653 15.7374 -4.732 3.03e-06 ***
## PMTill:Sample_depth_cm20-40 -123.4461 15.6994 -7.863 3.09e-14 ***
## PMTill:Sample_depth_cm5-10 -5.9692 15.6994 -0.380 0.7040
## Sample_depth_cm10-20:Age_year15-20 26.2029 15.7334 1.665 0.0966 .
## Sample_depth_cm20-40:Age_year15-20 39.0302 15.6968 2.487 0.0133 *
## Sample_depth_cm5-10:Age_year15-20 0.5377 15.6968 0.034 0.9727
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 58.21 on 427 degrees of freedom
## Multiple R-squared: 0.5632, Adjusted R-squared: 0.552
## F-statistic: 50.05 on 11 and 427 DF, p-value: < 2.2e-16
summary(new_SOC)
##
## Call:
## lm(formula = SOC..Mg.ha. ~ PM + Sample_depth_cm + FSDMP + Age_year +
## PM:Sample_depth_cm, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -19.731 -3.932 -0.968 3.062 45.411
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15.2637 0.9472 16.115 < 2e-16 ***
## PMTill 3.2553 1.1451 2.843 0.004687 **
## Sample_depth_cm10-20 -4.3564 1.1346 -3.840 0.000142 ***
## Sample_depth_cm20-40 -5.4470 1.1346 -4.801 2.19e-06 ***
## Sample_depth_cm5-10 -3.1357 1.1346 -2.764 0.005960 **
## FSDMP1 -0.6984 0.7088 -0.985 0.325042
## FSDMP2 -1.5824 0.6995 -2.262 0.024192 *
## Age_year15-20 1.2119 0.5731 2.115 0.035036 *
## PMTill:Sample_depth_cm10-20 -3.2617 1.6232 -2.009 0.045123 *
## PMTill:Sample_depth_cm20-40 -4.2353 1.6193 -2.615 0.009225 **
## PMTill:Sample_depth_cm5-10 -0.6606 1.6193 -0.408 0.683520
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.004 on 428 degrees of freedom
## Multiple R-squared: 0.2225, Adjusted R-squared: 0.2044
## F-statistic: 12.25 on 10 and 428 DF, p-value: < 2.2e-16
summary(new_SON)
##
## Call:
## lm(formula = SON..kg.ha. ~ PM + FSDMP + Age_year + PM:FSDMP +
## PM:Age_year + FSDMP:Age_year + PM:FSDMP:Age_year, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1157.7 -350.9 -106.6 184.2 11683.8
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1157.8 137.2 8.438 5.04e-16 ***
## PMTill -398.6 194.0 -2.054 0.040574 *
## FSDMP1 -505.4 194.0 -2.604 0.009522 **
## FSDMP2 -571.1 189.1 -3.020 0.002680 **
## Age_year15-20 -77.1 194.0 -0.397 0.691312
## PMTill:FSDMP1 612.6 274.4 2.233 0.026087 *
## PMTill:FSDMP2 967.8 270.9 3.572 0.000395 ***
## PMTill:Age_year15-20 200.3 275.4 0.727 0.467375
## FSDMP1:Age_year15-20 176.3 274.4 0.642 0.520979
## FSDMP2:Age_year15-20 310.5 267.4 1.161 0.246299
## PMTill:FSDMP1:Age_year15-20 -286.7 388.8 -0.738 0.461198
## PMTill:FSDMP2:Age_year15-20 -778.9 383.9 -2.029 0.043091 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 823.2 on 427 degrees of freedom
## Multiple R-squared: 0.0449, Adjusted R-squared: 0.02029
## F-statistic: 1.825 on 11 and 427 DF, p-value: 0.04787
summary(new_Ca)
##
## Call:
## lm(formula = Ca.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP +
## Age_year + PM:Sample_depth_cm + PM:FSDMP + PM:Age_year +
## FSDMP:Age_year + PM:FSDMP:Age_year, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1879.0 -252.4 -68.2 182.0 3756.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 432.68 139.42 3.103 0.00204 **
## PMTill -18.29 197.79 -0.092 0.92638
## Sample_depth_cm10-20 46.23 129.85 0.356 0.72200
## Sample_depth_cm20-40 112.85 129.85 0.869 0.38531
## Sample_depth_cm5-10 -44.69 129.85 -0.344 0.73090
## FSDMP1 -84.50 161.96 -0.522 0.60213
## FSDMP2 -40.92 157.86 -0.259 0.79558
## Age_year15-20 -69.54 161.96 -0.429 0.66786
## PMTill:Sample_depth_cm10-20 192.00 185.79 1.033 0.30199
## PMTill:Sample_depth_cm20-40 1510.27 185.33 8.149 4.23e-15 ***
## PMTill:Sample_depth_cm5-10 15.16 185.33 0.082 0.93486
## PMTill:FSDMP1 513.21 229.04 2.241 0.02557 *
## PMTill:FSDMP2 684.60 226.16 3.027 0.00262 **
## PMTill:Age_year15-20 370.44 229.87 1.612 0.10782
## FSDMP1:Age_year15-20 115.92 229.04 0.506 0.61305
## FSDMP2:Age_year15-20 186.37 223.24 0.835 0.40427
## PMTill:FSDMP1:Age_year15-20 -506.06 324.50 -1.560 0.11963
## PMTill:FSDMP2:Age_year15-20 -922.22 320.43 -2.878 0.00421 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 687.1 on 421 degrees of freedom
## Multiple R-squared: 0.4648, Adjusted R-squared: 0.4432
## F-statistic: 21.51 on 17 and 421 DF, p-value: < 2.2e-16
summary(new_Mg)
##
## Call:
## lm(formula = Mg.mass..kg.ha. ~ PM + Sample_depth_cm + FSDMP +
## Age_year + PM:Sample_depth_cm + PM:FSDMP + PM:Age_year +
## FSDMP:Age_year + PM:FSDMP:Age_year, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -633.94 -29.23 -3.90 22.35 1081.25
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 53.208 38.233 1.392 0.164754
## PMTill -31.552 54.240 -0.582 0.561068
## Sample_depth_cm10-20 7.457 35.610 0.209 0.834240
## Sample_depth_cm20-40 25.748 35.610 0.723 0.470046
## Sample_depth_cm5-10 -11.546 35.610 -0.324 0.745926
## FSDMP1 -17.366 44.413 -0.391 0.695984
## FSDMP2 -4.052 43.288 -0.094 0.925462
## Age_year15-20 -12.959 44.413 -0.292 0.770598
## PMTill:Sample_depth_cm10-20 80.917 50.949 1.588 0.112991
## PMTill:Sample_depth_cm20-40 486.978 50.824 9.582 < 2e-16 ***
## PMTill:Sample_depth_cm5-10 9.366 50.824 0.184 0.853879
## PMTill:FSDMP1 125.616 62.810 2.000 0.046148 *
## PMTill:FSDMP2 218.135 62.019 3.517 0.000484 ***
## PMTill:Age_year15-20 59.259 63.037 0.940 0.347718
## FSDMP1:Age_year15-20 12.236 62.810 0.195 0.845638
## FSDMP2:Age_year15-20 6.475 61.219 0.106 0.915820
## PMTill:FSDMP1:Age_year15-20 -97.177 88.987 -1.092 0.275441
## PMTill:FSDMP2:Age_year15-20 -247.155 87.872 -2.813 0.005143 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 188.4 on 421 degrees of freedom
## Multiple R-squared: 0.5055, Adjusted R-squared: 0.4855
## F-statistic: 25.32 on 17 and 421 DF, p-value: < 2.2e-16
summary(new_K)
##
## Call:
## lm(formula = K.mass..kg.ha. ~ PM + Sample_depth_cm + PM:Sample_depth_cm,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -181.26 -23.54 -4.82 13.66 483.61
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 35.698 7.645 4.669 4.04e-06 ***
## PMTill 23.312 10.911 2.136 0.033202 *
## Sample_depth_cm10-20 39.069 10.812 3.614 0.000338 ***
## Sample_depth_cm20-40 76.550 10.812 7.080 5.89e-12 ***
## Sample_depth_cm5-10 -2.285 10.812 -0.211 0.832738
## PMTill:Sample_depth_cm10-20 14.982 15.468 0.969 0.333310
## PMTill:Sample_depth_cm20-40 78.542 15.431 5.090 5.36e-07 ***
## PMTill:Sample_depth_cm5-10 8.374 15.431 0.543 0.587655
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 57.21 on 431 degrees of freedom
## Multiple R-squared: 0.485, Adjusted R-squared: 0.4766
## F-statistic: 57.98 on 7 and 431 DF, p-value: < 2.2e-16