Commit 34b85f25 authored by Boulangeat Isabelle's avatar Boulangeat Isabelle

rebuild main analysis output document

parent a040a2b7
......@@ -3,9 +3,9 @@ title: "Main_analyse.Rmd"
author: "Isabelle Boulangeat"
date: "23/01/2020"
output:
md_document:
variant: markdown_github
html_document:
keep_md: yes
variant: markdown_github
editor_options:
chunk_output_type: console
always_allow_html: true
......@@ -97,7 +97,7 @@ res.tab.eval = as.data.frame(do.call(rbind, lapply(eval.models, function(x)unlis
res.tab.vars = as.data.frame(do.call(rbind, lapply(eval.models, function(x)unlist(x[5:6]))))
kable(res.tab.eval, caption = "model evaluation", digits = 2) %>% kable_styling(bootstrap_options = c("striped", "hover", "responsive"), full_width=FALSE)
kable(res.tab.vars, caption = "selected variables")%>% kable_styling(bootstrap_options = c("striped", "hover", "responsive"), font_size = 10)
# kable(res.tab.vars, caption = "selected variables")%>% kable_styling(bootstrap_options = c("striped", "hover", "responsive"), font_size = 10)
```
N.B. Some models do not fit well. The variables explain more or less depending on species but also on processes (extinction and colonisation).
......@@ -133,7 +133,7 @@ data.frame(unclass(table(coeffs.all$var, coeffs.all$process))) %>%
kable_styling("striped")
```
## Variables effect coefficients
## Variable effect coefficients
This gives a summary of selected variables with significant impact on colonisation or extinction and their estimated coefficients.
......@@ -153,18 +153,15 @@ coeffs.all[which(coeffs.all$process == "extinction" & coeffs.all$Pr...z..<0.1),]
## Lambda (1-ext/colo)
An overview of the performance of populations by site of by species
```{r lambda, fig-TRUE, fig.width=10}
```{r lambda, fig-TRUE, fig.width=10, warning=FALSE, fig.height=7}
all.sites = unique(DATA$cover[,c("SemiUniquePLOT", "YEAR", "SUBSITE", "SoilMoist", "TotalCover")])
pDATA = proj.dat.shape(all.sites, DATA$climato)
str(pDATA)
summary(pDATA)
selectVars = c("snowDays", "GSL", "GST", "SoilMoist", "TotalCover")
pDATA.all = na.omit(pDATA[,c(selectVars,"SemiUniquePLOT", "YEAR", "SUBSITE") ])
pred.all = lapply(spDATA.fit, predictions, pred.data = pDATA.all, selectVars=selectVars)
pred.tab = lapply(pred.all, function(x)data.frame(sp = x$sp, lambda = x$lambda, YEAR = x$YEAR, SUBSITE = x$SUBSITE))
pred.all.together = do.call(rbind, pred.tab)
head(pred.all.together)
pred.all.together[-which(pred.all.together$sp == "Rubus chamaemorus"), ] %>%
ggplot(aes(YEAR, lambda)) +
......@@ -180,7 +177,7 @@ pred.all.together[-which(pred.all.together$sp == "Rubus chamaemorus"), ] %>%
ggplot(aes(SITE, lambda, sp)) +
theme(axis.text.x = element_text(angle=90, hjust=1)) +
geom_boxplot() + geom_hline(yintercept = 0) +
facet_wrap( ~ sp,scales = "free_x", ncol = 4)
facet_wrap( ~ sp,scales = "free_x", ncol = 7)
pred.all.together[-which(pred.all.together$sp == "Rubus chamaemorus"), ] %>%
ggplot(aes(SITE, lambda, sp)) +
......@@ -190,7 +187,7 @@ pred.all.together[-which(pred.all.together$sp == "Rubus chamaemorus"), ] %>%
```
Simplified version focusing only on the sign of lambda
```{r lambda_sign, fig=TRUE, fig.width=10}
```{r lambda_sign, fig=TRUE, fig.width=10, warning=FALSE}
pred.all.together$lambdaSign = ifelse(pred.all.together$lambda>0, "+", "-")
pred.all.together[-which(pred.all.together$sp == "Rubus chamaemorus"), ] %>%
......
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