FIA_alternate_disturbance_analysis.Rmd

---
title: "FIA_alternate_tsd"
author: "Katie Nigro"
date: "`r Sys.Date()`"
output: html_document
editor_options: 
  chunk_output_type: console
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```


```{r}
dist_seeds_joined_alt <- dist_seeds_joined %>% 
  filter(!(Agent == "insect.disease" & !source=="tree_table" & dist_year == MEASYEAR)) %>%
  mutate(tsd=MEASYEAR - dist_year) %>% 
  filter(Agent %in% c("fire","insect.disease","none"))
  
ggplot(dist_seeds_joined_alt %>% filter(!source=="tree_table"))+
  geom_histogram(aes(x=tsd))+
  facet_wrap(~Agent, scales="free")
 
ggplot(dist_tsd %>% filter(tsd>0))+
  geom_boxplot(aes(x=Agent, y=tsd))
##time since disturbance for insect/disease was much shorter on average than for fire. 
 



```


```{r, echo=FALSE}
##create function that appends climate data to each species/lifestage/disturbance

#' merge_sp_dist_env
#'
#' @param joined_df dataframe with disturbance and species data joined. Either species.sum.long or dist_seeds_joined
#' @param sp_code code for desired species. Can be found in FIA user guide. 
#' @param agent_name name of the desired disturbance. Either fire, insect.disease, harvest, other or none. 
#' @param env_vars environmental variables dataframe. Called env_vars here. 
#'
#' @return dataframe with environmental variables associated with each plot for a desired species/lifestage/disturbance combination 
#' @export
#'
#' @examples
merge_sp_dist_env <- function(joined_df, sp_code, agent_name, env_vars) {  sp_dist_env <- joined_df %>% 
    filter(SPCD == sp_code &
             Agent == agent_name) %>% 
    dplyr::select(SPCD, PLT_CN, Agent, dist_year, source) %>% 
    left_join(env_vars, by = "PLT_CN")
  
  return(sp_dist_env)
}

   
#FIA codes for all desired species (n=16) and disturbances (n=3)
sp_codes <- as.character(unique(sample_seeds_over60$SPCD))
dist_names <- c("fire","insect.disease","none")

#put environmental data for each species/disturbance combination in a dataframe within a list for adults
adult_data <- list()
for(i in 1:length(sp_codes)){
  for(j in 1:length(dist_names)){
    df <- merge_sp_dist_env(species.sum.long, sp_codes[i], dist_names[j], env_vars)
    adult_data[[paste(sp_codes[i],"_",dist_names[j],"_cvars",sep="")]]<- df
  }
}
#list for seedlings 
seedling_data <- list()
for(i in 1:length(sp_codes)){
  for(j in 1:length(dist_names)){
    df <- merge_sp_dist_env(dist_seeds_joined, sp_codes[i], dist_names[j], env_vars)
    seedling_data[[paste(sp_codes[i],"_",dist_names[j],"_cvars",sep="")]]<- df
  }
}
```