bruna_etal_fig2.Rmd

---
title: "Bruna et al. Ecology Data Paper Figure 2"
author: "Emilio M. Bruna"
date: "2023-06-14"
# output: html_document
output: pdf_document
# knit: (function(inputFile, encoding) {
#   rmarkdown::render(inputFile,
#   encoding = encoding,
#   output_dir = "./docs/maps/images")
#   })

mainfont: Times New Roman
fontsize: 12pt
# bibliography: ["./references.bib"] 
# #.// indicates it is in the parent directory (used for both ms and appendix)
# csl: "./ecology.csl"
fig_caption: yes #yes will automatically add "Figure X" to the start 
always_allow_html: yes
header-includes:
  - \usepackage{float} #to keep figure in the location placed instead of end
  - \floatplacement{figure}{H}
  - \usepackage{booktabs}
  - \raggedbottom
 # - \usepackage{endfloat} #[nomarkers] excludes the {insert figure x around here] from main text. The others exclude the list of tables and figures. https://cs.brown.edu/about/system/managed/latex/doc/endfloat.pdf
  - \usepackage{tabu}
  - \usepackage{makecell}
  - \usepackage{pdflscape}
  - \usepackage{longtable}
  - \newcommand{\blandscape}{\begin{landscape}}
  - \newcommand{\elandscape}{\end{landscape}}
  - \setlength\parindent{22pt}
editor_options: 
  markdown: 
    wrap: 72
---

```{r GlobalOptions, include=FALSE}
options(knitr.duplicate.label = 'allow')
knitr::opts_chunk$set(fig.pos = 'h')

library(tidyverse)
library(here)
library(cowplot)
library(ggplot2)
knitr::opts_chunk$set(echo = FALSE,message=FALSE,warning=FALSE)
```

```{r data, cached=TRUE, echo = FALSE, warning=FALSE,message = FALSE}
ha_plants<-read_csv(here("data", "survey_archive", "HDP_survey.csv"))
```

```{r repro, fig.cap='The abundance and reproduction of \\textit{Heliconia acuminata} in Continuous Forest. In each of survey year (gray lines) the data from the six demographic plots in Continuous Forest were pooled to give (A) the total number of post-seedling \\textit{H. acuminata} in size classes based on shoot number, and (B) the percentage of plants in each size class that produced at least 1 inflorescence. The green line is the average of the annual values for each size category.'}
# fig.cap='', fig.height = 10, fig.width = 7, fig.align = "center"

hacf<-ha_plants %>%
  filter(str_detect(plot_id,"CF")==TRUE) %>%
  filter(recorded_sdlg==FALSE) %>%
  filter(shts>0) %>%
  filter(is.na(shts)==FALSE)

size<-hacf %>%
  group_by(year,shts) %>%
  summarize(n=n_distinct((plant_id)))

repro<-hacf %>%
  group_by(year,shts) %>%
  filter(is.na(infl)==FALSE) %>%
  summarize(n_rep=n_distinct((plant_id)))


max_shts<-max(size$shts,na.rm = TRUE)
cf_rep<-full_join(size,repro) %>%
  mutate(n_rep = replace_na(n_rep, 0)) %>%
  mutate(shts_bin = cut(shts, breaks=c(0,1,2, 3, 4, 5,6,7,max_shts),
                      labels = c("1", "2", "3", "4","5","6","7","8")),
       .after=shts) %>%
  group_by(year,shts_bin) %>%
  mutate(n_bin=sum(n),.after=shts_bin) %>%
  group_by(year,shts_bin) %>%
  mutate(n_rep_bin=sum(n_rep),.after=n_bin) %>%
  relocate(n,.after=shts) %>%
  relocate(n_rep,.after=n) %>%
  mutate(perc_n=n_rep/n*100) %>%
  mutate(perc_bin=n_rep_bin/n_bin*100) %>%
  arrange(year,shts_bin)
# cf_rep

cf_rep_summary<-cf_rep %>%
    group_by(shts_bin) %>%
    summarize(perc_bin=mean(perc_bin),sd=sd(perc_bin)) %>%
    mutate(year="mean\n(1998-2012)")

cf_rep<- cf_rep %>%
  mutate(year=as.character(year))

  plot_data<- full_join(cf_rep,cf_rep_summary,
                        by=c("perc_bin","shts_bin","year")) %>%
    mutate(year=as.factor(year)) %>%
    mutate(shts_bin=as.factor(shts_bin)) %>%
    mutate(highlight=ifelse(year=="mean\n(1998-2012)","mean\n(1998-2012)","other")) %>%
    mutate(year=as.character(year))
# library(hrbrthemes)
  perc_plot<-plot_data %>%
    ggplot(aes(x=shts_bin,
               y=perc_bin,
               group=year, size=highlight,color=highlight)) +
    scale_y_continuous(breaks=c(0,10,20,30,40,50,60))+
    labs(x="shoots",y="% flowering")+
    geom_line() +
    expand_limits(x= c(-0, 9))+
    geom_text(data=plot_data %>% filter(shts_bin=="8") %>% filter(year=="mean\n(1998-2012)"),
              aes(label = year,
                  x = shts_bin,
                  y = perc_bin,
                  color = highlight),
              size=2,
              hjust = 0.6,
              nudge_x=0.5,
              # position = position_dodge(0.0)
              )+
    scale_x_discrete(labels = c(seq(1,7),expression("">=8)))+
    # geom_text(aes(label = year))+
    scale_color_manual(values = c("darkgreen","lightgrey")) +
    scale_size_manual(values=c(1.0,0.5)) +
    theme(legend.position="none") +
    # ggtitle("title") +
    theme_classic() +
    theme(
      legend.position="none",
      plot.title = element_text(size=14)
    )
  # perc_plot
# n plot ------------------------------------------------------------------
  cf_n_summary<-cf_rep %>%
    group_by(shts_bin) %>%
    summarize(n_bin=mean(n_bin)) %>%
    mutate(year="mean\n(1998-2012)")

  cf_rep<- cf_rep %>%
    mutate(year=as.character(year))

  plot_n_data<- full_join(cf_rep,cf_n_summary,
                        by=c("n_bin","shts_bin","year")) %>%
    mutate(year=as.factor(year)) %>%
    mutate(shts_bin=as.factor(shts_bin)) %>%
    mutate(highlight=ifelse(year=="mean\n(1998-2012)","mean\n(1998-2012)","other")) %>%
    mutate(year=as.character(year))

  n_plot<-plot_n_data %>%
    ggplot(aes(x=shts_bin,
               y=n_bin,
               group=year, size=highlight,color=highlight)) +
    # scale_y_continuous(breaks=c(0,10,20,30,40,50,60))+
    labs(x="shoots",y="number of plants")+
    geom_line() +
    expand_limits(x= c(-0, 9))+
    geom_text(data=plot_n_data %>% filter(shts_bin=="8") %>% filter(year=="mean\n(1998-2012)"),
              aes(label = year,
                  x = shts_bin,
                  y = n_bin,
                  color = highlight),
              size=2,
              hjust = 0.6,
              nudge_x=0.5,
              # position = position_dodge(0.0)
    )+
    scale_x_discrete(labels = c(seq(1,7),expression("">=8)))+
    # geom_text(aes(label = year))+
    scale_color_manual(values = c("darkgreen","lightgrey")) +
    scale_size_manual(values=c(1.0,0.5)) +
    theme(legend.position="none") +
    # ggtitle("title") +
    theme_classic() +
    theme(
      legend.position="none",
      plot.title = element_text(size=14)
    )
  # n_plot

# join plots --------------------------------------------------------------

library(gridExtra)
figure_rep<-grid.arrange(n_plot, perc_plot, ncol = 1)
# figure_rep
# grid.arrange(n_plot, perc_plot, ncol = 1)
#
# figure_rep <- ggdraw() +
#   draw_image('./MetadataS1/figures/repro_figure.jpeg',x = -0.26, y = 0.3, scale = .5)

```