ebirdst_predictors

A data frame of the predictors used in the eBird Status and Trends models.
These include effort variables (e.g. distance traveled, number of observers,
etc.) in addition to land and water cover variables. These landcover
variables are derived from the MODIS MCD12Q1 500 m landcover product, and for
each land cover class two FRAGSTATS metrics are calculated within a 1.5 km
buffer around each checklist: % landcover (PLAND) and edge density (ED).

datasets

Tools to download, load, plot, and analyze eBird Status and
Trends Data Products
(<https://science.ebird.org/en/status-and-trends>). eBird
(<https://ebird.org/home>) is a global database of bird observations
collected by member of the public. eBird Status and Trends uses these
data to model global bird abundances, range boundaries, and habitat
associations at a high spatial and temporal resolution.

Matthew Strimas-Mackey

ebirdst

Access and Analyze eBird Status and Trends Data

Shawn Ligocki

Tom Auer

Daniel Fink

Cornell Lab of Ornithology 

ebirdst_predictors function

A data frame with 74 rows and 5 columns:<dl>
<dt>predictor</dt>
<dd>Predictor variable name.</dd><dt>predictor_label</dt>
<dd>Descriptive labels for predictors for plotting and
translating the cryptic variables names (e.g. <code>umd_fs_c1</code> is
Evergreen Needleleaf Forest.</dd><dt>lc_class</dt>
<dd>For the land and water cover FRAGSTATS variables, this
gives the associated landcover class. It can be used for grouping
and summarizing the four FRAGSTATS metrics to the level of the
landcover class.</dd><dt>lc_class_label</dt>
<dd>Similar to <code>predictor_label</code>; however, this variable
gives the FRAGSTATS metrics a single name for the landcover
class.</dd>
</dl>

Format

eBird Status and Trends predictors — ebirdst_predictors

A data frame with 74 rows and 5 columns:<dl>
<dt>predictor</dt>
<dd>Predictor variable name.</dd>

<dt>predictor_label</dt>
<dd>Descriptive labels for predictors for plotting and
translating the cryptic variables names (e.g. <code>umd_fs_c1</code> is
Evergreen Needleleaf Forest.</dd>

<dt>lc_class</dt>
<dd>For the land and water cover FRAGSTATS variables, this
gives the associated landcover class. It can be used for grouping
and summarizing the four FRAGSTATS metrics to the level of the
landcover class.</dd>

<dt>lc_class_label</dt>
<dd>Similar to <code>predictor_label</code>; however, this variable
gives the FRAGSTATS metrics a single name for the landcover
class.</dd>


</dl>

ebirdst_predictors: eBird Status and Trends predictors

Description

Usage

Arguments

Format