Each of the eBird Status and Trends raster products is packaged as a GeoTIFF
file representing predictions on a regular grid. The core products are
occurrence, count, relative abundance, and percent of population. This
function loads one of the available data products into R as a RasterStack
object.
character; directory that the Status and Trends data for a given
species was downloaded to. This path is returned by ebirdst_download()
or get_species_path().
character; Status and Trends product to load: occurrence, count, relative abundance, or percent of population. See Details for a detailed explanation of each of these products.
character; temporal period of the estimation. The Status and Trends models make predictions for each week of the year; however, as a convenience, data are also provided summarized at the seasonal or annual ("full-year") level.
character; by default, the weekly products provide estimates of
the median value (metric = "median") and the summarized products are the
cell-wise mean across the weeks within the season (metric = "mean").
However, additional variants exist for some of the products. For the weekly
relative abundance, confidence intervals are provided: specify metric = "lower" to get the 10th quantile or metric = "upper" to get the 90th
quantile. For the seasonal and annual products, the cell-wise maximum
values across weeks can be obtained with metric = "max".
character; the resolution of the raster data to load. The
default is to load the native ~3 km resolution ("hr"); however, for some
applications 9 km ("mr") or 27 km ("lr") data may be suitable.
For the weekly cubes, a RasterStack with 52 layers for the given
product, labeled by week. Seasonal cubes will have up to four layers
labeled according to the seasons. The full-year products will have a single
layer.
The core Status and Trends data products provide weekly estimates across a regular spatial grid. They are packaged as rasters with 52 layers, each corresponding to estimates for a week of the year, and we refer to them as "cubes" (e.g. the "relative abundance cube"). All estimates are the median expected value for a standard 1km, 1 hour eBird Traveling Count by an expert eBird observer at the optimal time of day and for optimal weather conditions to observe the given species. These products are:
occurrence: the expected probability (0-1) of occurrence a species.
count: the expected count of a species, conditional on its occurrence at
the given location.
abundance: the expected relative abundance of a species, computed as the product of
the probability of occurrence and the count conditional on occurrence.
percent-population: the percent of the total relative abundance within
each cell. This is a derived product calculated by dividing each cell value
in the relative abundance raster with the total abundance summed across all
cells.
In addition to these weekly data cubes, this function provides access to data
summarized over different periods. Seasonal cubes are produced by taking the
cell-wise mean or max across the weeks within each season. The boundary dates
for each season are species specific and are available in ebirdst_runs, and
if a season failed review no associated layer will be included in the cube.
In addition, full-year summaries provide the mean or max across all weeks of
the year that fall within a season that passed review. Note that this is not
necessarily all 52 weeks of the year. For example, if the estimates for the
non-breeding season failed expert review for a given species, the full-year
summary for that species will not include the weeks that would fall within
the non-breeding season.
if (FALSE) {
# download example data
path <- ebirdst_download("example_data")
# or get the path if you already have the data downloaded
path <- get_species_path("example_data")
# weekly relative abundance
# note that only low resolution (lr) data are available for the example data
abd_weekly <- load_raster(path, "abundance", resolution = "lr")
# identify the weeks for each layer
parse_raster_dates(abd_weekly)
# max seasonal abundance
abd_seasonal <- load_raster(path, "abundance",
period = "seasonal", metric = "max",
resolution = "lr")
# available seasons in stack
names(abd_seasonal)
# subset to just breeding season abundance
abd_seasonal[["breeding"]]
}