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dynamicSDM

1.3.4Package record

Species Distribution and Abundance Modelling at High Spatio-Temporal Resolution

0packages depend
3.6Kdownloads / year
44.5%test coverage
13/13flavors OK

Overview

About

A collection of novel tools for generating species distribution and abundance models (SDM) that are dynamic through both space and time. These highly flexible functions incorporate spatial and temporal aspects across key SDM stages; including when cleaning and filtering species occurrence data, generating pseudo-absence records, assessing and correcting sampling biases and autocorrelation, extracting explanatory variables and projecting distribution patterns. Throughout, functions utilise Google Earth Engine and Google Drive to minimise the computing power and storage demands associated with species distribution modelling at high spatio-temporal resolution.

Install

Health

CRAN checks
13OK
Slowest check: 5.4 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.3.4
READMEYes · 759 wordsVignettesYes · 4 · dynamicNEWSYes · 67% structured · does not mention 1.3.4Citation fileYes · cites a publication
Help pages
30 (2 internal)includes a package overview page
Examples that run
73%16 run in a plain check (6 of them under a condition) · 6 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
96%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
70%

Downloads

3.6K
CRAN downloads in the past year
Rank #8,886 · ~10/day · ~302/mo
Daily download trend is not available in this view yet.
40530 days
1.1K90 days
3.6K1 year
Compare downloads with other packages →
Also on78 r2u

Repository

8Stars
2Forks
1Open issues
0Open PRs
2Releases
190Commits
1Commit identities
google-earth-enginegoogledrivesdmspatiotemporalspatiotemporal-data-analysisspatiotemporal-forecastingspecies-distribution-modellingspecies-distributions
190 commits · Last activity 2025-07-14 · 0% stars, 30d · Discussions: 7 posts
Responsiveness
How these are sampled
PRs merged (all time)
not measured
Median days to close, 50 most recently updated closed issues
1
Median days to close, 50 most recently updated closed PRs
not measured

Stars over time

2024-10-22 · 62026-07-07 · 8
PracticesBeta

5 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/r-a-dobson/dynamicsdm on 2026-10-18.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Docs source (2)
README.Rmd

GitHub Pages site last deployed 2023-03-16

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
24 external dependencies (excludes base and recommended)

Installing dynamicSDM adds 98 packages (58 with compiled code, 79 MB of source tarballs). Heaviest: stringi 11 MB, sf 9.3 MB, bslib 5.6 MB.

Depends (1)
R >= 3.5.0
Imports (15)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (6)
Author, Maintainer since 1.0 (2023), Contributor
Author, Contributor
Author, Contributor
Author, Contributor
Author, Contributor
Author, Contributor
Releases (8)

Pick two releases to compare their code metrics.

Package metadata

First published
2023-02-17
Total releases
8 / 3 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 3.5.0
Bundled data
49 KB / 6 files
Download size
1.0 MB

Cite

Cite this package

Run in R for the authors' entry:

citation("dynamicSDM")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1111/2041-210x.14101.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for dynamicSDM version 1.3.4 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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