Showing 8 of total 8 results (show query)
ropensci
auk:eBird Data Extraction and Processing in R
Extract and process bird sightings records from eBird (<http://ebird.org>), an online tool for recording bird observations. Public access to the full eBird database is via the eBird Basic Dataset (EBD; see <http://ebird.org/ebird/data/download> for access), a downloadable text file. This package is an interface to AWK for extracting data from the EBD based on taxonomic, spatial, or temporal filters, to produce a manageable file size that can be imported into R.
Maintained by Matthew Strimas-Mackey. Last updated 2 months ago.
80.7 match 143 stars 9.04 score 254 scripts
ebird
ebirdst:Access and Analyze eBird Status and Trends Data Products
Tools for accessing and analyzing 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 distributions, abundances, and population trends at a high spatial and temporal resolution.
Maintained by Matthew Strimas-Mackey. Last updated 20 days ago.
77.3 match 26 stars 8.85 score 228 scriptsropensci
rebird:R Client for the eBird Database of Bird Observations
A programmatic client for the eBird database (<https://ebird.org/home>), including functions for searching for bird observations by geographic location (latitude, longitude), eBird hotspots, location identifiers, by notable sightings, by region, and by taxonomic name.
Maintained by Sebastian Pardo. Last updated 1 months ago.
birdsbirdingebirddatabasedatabiologyobservationssightingsornithologyebird-apiebird-webservicesspocc
43.4 match 90 stars 10.43 score 73 scripts 6 dependentsropensci
spocc:Interface to Species Occurrence Data Sources
A programmatic interface to many species occurrence data sources, including Global Biodiversity Information Facility ('GBIF'), 'iNaturalist', 'eBird', Integrated Digitized 'Biocollections' ('iDigBio'), 'VertNet', Ocean 'Biogeographic' Information System ('OBIS'), and Atlas of Living Australia ('ALA'). Includes functionality for retrieving species occurrence data, and combining those data.
Maintained by Hannah Owens. Last updated 1 months ago.
specimensapiweb-servicesoccurrencesspeciestaxonomygbifinatvertnetebirdidigbioobisalaantwebbisondataecoengineinaturalistoccurrencespecies-occurrencespocc
11.5 match 118 stars 10.09 score 552 scripts 5 dependents
mstrimas
colorist:Coloring Wildlife Distributions in Space-Time
Color and visualize wildlife distributions in space-time using raster data. In addition to enabling display of sequential change in distributions through the use of small multiples, 'colorist' provides functions for extracting several features of interest from a sequence of distributions and for visualizing those features using HCL (hue-chroma-luminance) color palettes. Resulting maps allow for "fair" visual comparison of intensity values (e.g., occurrence, abundance, or density) across space and time and can be used to address questions about where, when, and how consistently a species, group, or individual is likely to be found.
Maintained by Matthew Strimas-Mackey. Last updated 11 months ago.
3.4 match 14 stars 5.60 score 19 scripts
jcoliver
lifeR:Identify Sites for Your Bird List
A suite of tools to use the 'eBird' database (<https://ebird.org/home/>) and APIs to compare users' species lists to recent observations and create a report of the top sites to visit to see new species.
Maintained by Jeffrey Oliver. Last updated 1 months ago.
3.9 match 4 stars 4.78 score 6 scripts
philipmostert
PointedSDMs:Fit Models Derived from Point Processes to Species Distributions using 'inlabru'
Integrated species distribution modeling is a rising field in quantitative ecology thanks to significant rises in the quantity of data available, increases in computational speed and the proven benefits of using such models. Despite this, the general software to help ecologists construct such models in an easy-to-use framework is lacking. We therefore introduce the R package 'PointedSDMs': which provides the tools to help ecologists set up integrated models and perform inference on them. There are also functions within the package to help run spatial cross-validation for model selection, as well as generic plotting and predicting functions. An introduction to these methods is discussed in Issac, Jarzyna, Keil, Dambly, Boersch-Supan, Browning, Freeman, Golding, Guillera-Arroita, Henrys, Jarvis, Lahoz-Monfort, Pagel, Pescott, Schmucki, Simmonds and O’Hara (2020) <doi:10.1016/j.tree.2019.08.006>.
Maintained by Philip Mostert. Last updated 2 months ago.
1.7 match 25 stars 8.57 score 50 scripts 1 dependents
megatvini
MulvariateRandomForestVarImp:Variable Importance Measures for Multivariate Random Forests
Calculates two sets of post-hoc variable importance measures for multivariate random forests. The first set of variable importance measures are given by the sum of mean split improvements for splits defined by feature j measured on user-defined examples (i.e., training or testing samples). The second set of importance measures are calculated on a per-outcome variable basis as the sum of mean absolute difference of node values for each split defined by feature j measured on user-defined examples (i.e., training or testing samples). The user can optionally threshold both sets of importance measures to include only splits that are statistically significant as measured using an F-test.
Maintained by Dogonadze Nika. Last updated 6 months ago.
3.5 match 3.65 score 4 scripts