---
authors:
  - givenNames:
      - Norman 
    familyNames:
      - Gentsch
    type: Person
  - givenNames:
      - Jens
    familyNames:
      - Boy
    type: Person
  - givenNames:
      - Juan Daniel 
    familyNames:
      - Kennedy Batalla
    type: Person
  - givenNames:
      - Diana
    familyNames:
      - Heuermann
    type: Person
  - givenNames:
      - Nicolaus
    familyNames:
      - von Wirén
    type: Person
  - givenNames:
      - Dörte 
    familyNames:
      - Schweneker
    type: Person
  - givenNames:
      - Ulf 
    familyNames:
      - Feuerstein
    type: Person
  - givenNames:
      - Jonas
    familyNames:
      - Groß
    type: Person
  - givenNames:
      - Bernahrd 
    familyNames:
      - Bauer
    type: Person
  - givenNames:
      - Barbara
    familyNames:
      - Reinhold-Hurek
    type: Person
  - givenNames:
      - Thomas
    familyNames:
      - Hurek
    type: Person
  - givenNames:
      - Fabricio 
    familyNames:
      - Camacho Céspedes 
    type: Person 
  - givenNames:
      - Georg 
    familyNames:
      - Guggenberger
    type: Person
datePublished:
  value: '2020-05-23'
  type: Date
dateReceived:
  value: '2020-02-05'
  type: Date
dateAccepted:
  value: '2020-05-03'
  type: Date
title: >-
  Catch crop diversity increases rhizosphere carbon input and soil microbial biomass
isPartOf:
  volumeNumber: '56'
  isPartOf:
    title: Biology and Fertility of Soils
    identifiers:
      - name: doi
        propertyID: 'https://registry.identifiers.org/registry/doi'
        value: https://doi.org/10.1007/s00374-020-01475-8
        type: PropertyValue
    publisher:
      name: 'Springer Science and Business Media {LLC}'
      type: Organization
    type: Periodical
  type: PublicationVolume
---

## Abstract
Catch crops increase plant species richness in crop rotations, but are most often grown as pure stands. Here, we investigate...

## Results

### Plant biomass and net ecosystem exchange
The NEE decreased significantly with increasing catch crop diversity ([Fig. 1](#fig1)), suggesting increasing $$CO_2$$-C uptake from the atmosphere.

chunk: Figure 1
:::
## Net ecosystem exchange (NEE) of C between catch crop treatments. Bars represent means ± SE; lowercase letters denote significant differences (p < `r p`) between treatments

```r
# 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)


# 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 = 7, 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$cc_variant <- factor(data$cc_variant, levels = c("Fallow", "Mustard", "Mix4", "Mix12"))
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)

#Compute Position
Pos <- aggregate(NEE~cc_variant,data,min)

# 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= merge(df_NEE,Pos) ,
            aes(y=NEE-10,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)

```
:::
{#fig1}


## 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](#fig1)), which suggested higher photosynthetic $$CO_2$$-C fixation rates with increasing catch crop diversity.