R ggplot: How to make a graph showing the change of confidence interval over a continuous x variable?

[PeterChien]

I made a scatter plot by using ggplot2 to show the relationship between human footprint and soil carbon in different habitat types (natural, urban wild, and urban). The human footprint is a continuous variable which indicates human pressure on the nature. Higher footprint value means a land is more modified by humans.

Here is the code I used and the plot I have:

library(ggplot2)
SOC$Habitat <- factor(SOC$Habitat, levels = c("Natural", "Urban wild", "Urban")
#reorder the three habitat types

p <- ggplot(SOC, aes(x=Footprint, y=Stocks, shape=Habitat, color=Habitat) +
     geom_point() + 
     geomsmooth(method=lm, aes(fill=Habitat))

p + xlab("Human Footprint") + ylab("SOC Stocks (Mg ha-1)") + theme_classic()

p

Now I want to extract the confidence interval to see how it changes as the human footprint increases under different habitat types. The y variable in the new plot (I assume it can be a line graph) that I want now can be confidence interval range or confidence interval width, and x variable is the human footprint. The new line graph needs to contain three lines, representing each habitat type (natural, urban wild, and urban) with color.

However, I have no idea how to do it. Hope you can help me if you know how to do in ggplot2 or other packages. Thank you very much in advance.

[nirgrahamuk]

As a starting point, you used geomsmooth(method=lm, aes(fill=Habitat)) to fit an inline model while plotting.
Consider refactoring your code to create a proper lm object, that can be interrogated. Here is an example with R built in data.

library(tidyverse)
#example data
myiris <- iris
my_lm <- lm(Petal.Length ~ Sepal.Length + Species,data=iris)
myiris$lm_pred_val <- predict(my_lm,newdata = myiris,
                              interval =  "confidence"
                              ) %>% as.data.frame()
ggplot(data=myiris,
       aes(x=Sepal.Length,
           y=Petal.Length,
           color=Species,
           fill=Species)) + geom_point()+
  geom_line(aes(y=lm_pred_val$fit)) +
  geom_ribbon(aes(ymin=lm_pred_val$lwr,
                  ymax=lm_pred_val$upr), alpha=.3) +
  ggtitle("Petal Length predicted from Sepal Length over 3 species")

ggplot(data=myiris,
       aes(x=Sepal.Length,
           y=lm_pred_val$upr - lm_pred_val$lwr,
           color=Species,
           fill=Species)) + 
  geom_line() +
        ylab("Confidence Interval Width at .95") + 
  ylim(c(0,1)) +
  ggtitle("Change in Confidence Interval Width by Sepal.Length,\n when predicting Petal Length")

[PeterChien]

Hi there,

I successfully made it with your kind help! Thank you very much.