Catch crop diversity increases rhizosphere carbon input and soil microbial biomass

Abstract

Introduction

Material and methods

Results

Plant biomass and net ecosystem exchange

The NEE decreased significantly with increasing catch crop diversity (Fig. 1), suggesting increasing -C uptake from the atmosphere.

# written with R version 4.0.2 (2020-06-22) -- "Taking Off Again"
##------ Tue Oct 13 11:53:48 2020 ------##
# by Norman Gentsch

library(tidyverse)
library(lme4)
library(emmeans)
library(multcomp)
library(knitr)
library(DT)

# set theme for ggplot
theme_set(theme_bw())
theme_myBW <- theme(axis.title.x = element_text(size = 10, color = "black"), 
                    axis.title.y = element_text(angle = 90, vjust = 1.5, size = 10, color = "black"),
                    axis.text.x = element_text(size = 10, color = "black"), 
                    axis.text.y = element_text(size = 10, color = "black"), 
                    axis.ticks =element_line(colour="black"),
                    strip.text.x = element_text(size = 10, color = "black"),
                    strip.background = element_blank(),
                    panel.border =element_rect(colour="black", fill=NA), 
                    panel.grid.major = element_blank(),
                    panel.grid.minor = element_blank(),
                    plot.title = element_text(size = 12, hjust=0.5),
                    #legend.position=c(0.0,1.0), 
                    #legend.justification=c(0,1), 
                    legend.text = element_text(size = 10),
                    legend.text.align=0,
                    legend.title =  element_text(size = 10), 
                    legend.key = element_rect(colour="white", fill = "white"),
                    legend.key.size = unit(5, "mm"),
                    legend.background = element_blank())


# set vector with colors and label
COL <- c("Fallow" = "slategray", "Mustard" = "red3" , "Mix4" = "orchid3", "Mix12"= "orange4")
SHP <- c("Fallow"=21,"Mustard"=22,"Mix4"=23, "Mix12"=24)


data <- read.csv2("data.csv", as.is=T)
data$NEE <- as.numeric(data$NEE)


lm_NEE <- lmer(NEE ~ cc_variant + (1|Date), data=data)
df_NEE <- cld(emmeans(lm_NEE, specs ="cc_variant"), Letters=letters, sort=FALSE)

# summary table for 
sum.lm <- glht(lm_NEE, linfct = mcp(cc_variant = "Tukey"))
#summary(sum.lm)$test$pvalue


glht.table <- function(x) {
  pq <- summary(x)$test
  mtests <- cbind(pq$coefficients, pq$sigma, pq$tstat, pq$pvalues)
  colnames(mtests) <- c("Estimate", "Std Error", "z value", "p value")
  return(mtests)
  }

df.summary <- data.frame(glht.table(sum.lm))
#df.summary
abc <- subset (df.summary, p.value<0.01)
maxValue <- max(abc$p.value)
p <- round(maxValue + 5*10^(-3), 2)

colMax <- function(data) sapply(data, max, na.rm = TRUE)

# Plot for BFS
  ggplot(data, aes(x= cc_variant, y=NEE, fill= cc_variant))+
  geom_boxplot()+
  scale_fill_manual(values = COL, guide=FALSE)+
  geom_text(data= df_NEE ,aes(y=-600,x=cc_variant, label=.group))+
  labs(x="Catch crop variant",  y=expression("NEE (mg CO"[2]~"- C"~m^{-2}~h^{-1}~")"), fill="")+
  theme_myBW+scale_x_discrete(limits=c("Fallow", "Mustard", "Mix4", "Mix12"))

#ggsave("Fig1.png", width = 84, height = 70, units = "mm", dpi = 600)



#summary(lm_NEE)

Net ecosystem exchange (NEE) of C between catch crop treatments. Bars represent means ± SE; lowercase letters denote significant differences (p < p) between treatments

Discussion

NEE is linked to plant diversity

... The NEE in our study showed a remarkably strong negative gradient from mustard to mix 4 to mix 12 (Fig. 1), which suggested higher photosynthetic -C fixation rates with increasing catch crop diversity.

Conclusion

References

Table 1. Representation of the p-values

datatable(df.summary)