California Pitcher Plant - Cobra Lily (Darlingtonia californica)

Spring is in full swing in the higher elevations around Mount Shasta and the surrounding ranges. I am always struck by the large patches of Cobra Lilies that grow along nutrient poor seeps in alpine meadows. I nearly always stop to take some photos and take in all the cool colors and shapes when out on training runs or hikes. I have made many observations of these over the past few years, but here is a quick post to pull out observations from GBIF.

Load the libraries.

library(tidyverse)
library(rgbif)
library(gpx)

Make the large Northern California polygon to look for observations in GBIF.

norcal_geometry <- paste('POLYGON((-124.4323 42.0021, -121.5045 42.0021, -121.5045 40.194, -124.4323 40.194, -124.4323 42.0021))')

cobra_lily <- occ_data(scientificName = "darlingtonia californica", hasCoordinate = TRUE, limit = 1000,
                   geometry = norcal_geometry)
# length(cobra_lily)
head(cobra_lily)

## $meta
## $meta$offset
## [1] 900
## 
## $meta$limit
## [1] 100
## 
## $meta$endOfRecords
## [1] FALSE
## 
## $meta$count
## [1] 1129
## 
## 
## $data
## # A tibble: 1,000 × 125
##    key        scientificName  decimalLatitude decimalLongitude issues datasetKey
##    <chr>      <chr>                     <dbl>            <dbl> <chr>  <chr>     
##  1 3499352919 Darlingtonia c…            41.9            -124. cdrou… 50c9509d-…
##  2 3499475143 Darlingtonia c…            41.9            -124. cdrou… 50c9509d-…
##  3 3499606799 Darlingtonia c…            41.8            -124. cdrou… 50c9509d-…
##  4 3499614932 Darlingtonia c…            41.9            -124. cdrou… 50c9509d-…
##  5 3499614940 Darlingtonia c…            42.0            -124. cdrou… 50c9509d-…
##  6 3499647846 Darlingtonia c…            41.9            -124. cdrou… 50c9509d-…
##  7 3698398122 Darlingtonia c…            41.9            -124. cdrou… 50c9509d-…
##  8 3743185922 Darlingtonia c…            41.9            -124. cdrou… 50c9509d-…
##  9 3746965657 Darlingtonia c…            41.9            -124. cdrou… 50c9509d-…
## 10 3747115575 Darlingtonia c…            42.0            -124. cdrou… 50c9509d-…
## # … with 990 more rows, and 119 more variables: publishingOrgKey <chr>,
## #   installationKey <chr>, publishingCountry <chr>, protocol <chr>,
## #   lastCrawled <chr>, lastParsed <chr>, crawlId <int>,
## #   hostingOrganizationKey <chr>, basisOfRecord <chr>, occurrenceStatus <chr>,
## #   taxonKey <int>, kingdomKey <int>, phylumKey <int>, classKey <int>,
## #   orderKey <int>, familyKey <int>, genusKey <int>, speciesKey <int>,
## #   acceptedTaxonKey <int>, acceptedScientificName <chr>, kingdom <chr>, …

Quick map of observations.

cobra_lily_coords <- cobra_lily$data[ , c("decimalLongitude", "decimalLatitude", "occurrenceStatus", "coordinateUncertaintyInMeters", "institutionCode", "references")]

maps::map(database = "state", region = "california")
points(cobra_lily_coords[ , c("decimalLongitude", "decimalLatitude")], pch = ".", col = "red", cex = 3)

Pull in my run data using the gpx R library and subset the route to make plotting easier.

run <-  read_gpx('../../../static/data/cobra_lily_run.gpx')
TrailRun1 <- as.data.frame(run$routes)

Make a quick run plot.

TrailRun_plot <- ggplot() +
          geom_point(data = TrailRun1, aes(x = Longitude, y = Latitude), color = 'black') +
          xlab("Longitude") + ylab("Latitude")
TrailRun_plot

Subset the larger California dataset to only include a zoomed in portion where I ran based on the maximum and minimum coordinates from the run plot above.

cobra_lily_coords_sub <- subset(cobra_lily_coords, decimalLatitude > 41.3 & decimalLatitude < 41.365 & decimalLongitude > -122.6 & decimalLongitude < -122.5 )

Overlay the plots and add a triangle for the seep where I observed some Cobra Lilies next to the trail.

TrailRun_plot2 <- ggplot() +
          coord_quickmap() +
          geom_point(data = TrailRun1, aes(x = Longitude, y = Latitude), color = 'black') +
          geom_point(data=cobra_lily_coords_sub, aes(x = decimalLongitude, y = decimalLatitude), color = 'red') +
          geom_point(aes(x = -122.55, y = 41.325), pch=25, size= 12, colour="purple") +
          xlab("Longitude") + ylab("Latitude")
TrailRun_plot2

In a follow-up post we will import some additional environmental data to make a multi-layered map.