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.

library(tidyverse)
library(lme4)
library(emmeans)
library(multcomp)

# 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)


# generate data frame with original data
data <- read.csv2("data.csv")
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)

# Plot for BFS
  fig1 <- 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)
fig1

Net ecosystem exchange (NEE) of C between catch crop treatments. Bars represent means ± SE; lowercase letters denote significant differences (p < 0.01) 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