Correlations between soil colour and geochemical properties and SSA and SOM
Author
Alex Koiter
Load Libraries
In [1]:
library(tidyverse)
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library(patchwork)library(scales)
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library(viridis)
Loading required package: viridisLite
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Joining with `by = join_by(sample_number, site, sampling_design)`
Joining with `by = join_by(sample_number, site, sampling_design)`
Warning: There were 2 warnings in `mutate()`.
The first warning was:
ℹ In argument: `ssa_test = map(data, ~cor.test(.$value,
.$specific_surface_area, method = "pearson"))`.
Caused by warning in `cor()`:
! the standard deviation is zero
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Warning: There were 2 warnings in `mutate()`.
The first warning was:
ℹ In argument: `d50_test = map(data, ~cor.test(.$value,
.$specific_surface_area, method = "pearson"))`.
Caused by warning in `cor()`:
! the standard deviation is zero
ℹ Run `dplyr::last_dplyr_warnings()` to see the 1 remaining warning.
Warning: There were 2 warnings in `mutate()`.
The first warning was:
ℹ In argument: `om_test = map(data, ~cor.test(.$value, .$OM, method =
"pearson"))`.
Caused by warning in `cor()`:
! the standard deviation is zero
ℹ Run `dplyr::last_dplyr_warnings()` to see the 1 remaining warning.
corr_geo
# A tibble: 264 × 10
site sampling_design Fingerprint p_value_ssa estimate_ssa p_value_d50
<chr> <chr> <chr> <dbl> <dbl> <dbl>
1 Forest Grid Ag 2.89e- 5 0.555 2.89e- 5
2 Forest Grid Al 5.39e-14 0.834 5.39e-14
3 Forest Grid As 9.84e- 7 -0.629 9.84e- 7
4 Forest Grid B 2.15e- 3 0.424 2.15e- 3
5 Forest Grid Ba 4.69e- 3 -0.394 4.69e- 3
6 Forest Grid Be 1.11e- 7 0.669 1.11e- 7
7 Forest Grid Bi 5.61e- 9 0.715 5.61e- 9
8 Forest Grid Ca 3.95e-11 -0.775 3.95e-11
9 Forest Grid Cd 2.20e- 1 0.177 2.20e- 1
10 Forest Grid Ce 2.95e- 7 -0.652 2.95e- 7
# ℹ 254 more rows
# ℹ 4 more variables: estimate_d50 <dbl>, p_value_om <dbl>, estimate_om <dbl>,
# type <chr>
`geom_smooth()` using formula = 'y ~ x'
`geom_smooth()` using formula = 'y ~ x'
`geom_smooth()` using formula = 'y ~ x'
`geom_smooth()` using formula = 'y ~ x'
Exploring the relation between select geochemical concentrations and specific surface area and soil organic matter content. Solid lines indicate linear relation for each site and sampling design independently and dashed lines indicate linear relation for each sampling design with data combined across both sites.
`geom_smooth()` using formula = 'y ~ x'
`geom_smooth()` using formula = 'y ~ x'
`geom_smooth()` using formula = 'y ~ x'
`geom_smooth()` using formula = 'y ~ x'
Exploring the relation between select colour coefficients and specific surface area and soil organic matter content. Solid lines indicate linear relation for each site and sampling design independently and dashed lines indicate linear relation for each sampling design with data combined across both sites.
