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https://github.com/iiasa/ibis.iSDM
Modelling framework for creating Integrated SDMS
https://github.com/iiasa/ibis.iSDM
bayesian biodiversity integrated-framework poisson-process scenarios sdm spatial-grain spatial-predictions species-distribution-modelling
Last synced: 3 months ago
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Modelling framework for creating Integrated SDMS
- Host: GitHub
- URL: https://github.com/iiasa/ibis.iSDM
- Owner: iiasa
- License: cc-by-4.0
- Created: 2021-01-21T20:27:17.000Z (almost 4 years ago)
- Default Branch: master
- Last Pushed: 2024-06-08T15:41:58.000Z (5 months ago)
- Last Synced: 2024-06-11T17:14:38.770Z (5 months ago)
- Topics: bayesian, biodiversity, integrated-framework, poisson-process, scenarios, sdm, spatial-grain, spatial-predictions, species-distribution-modelling
- Language: R
- Homepage: https://iiasa.github.io/ibis.iSDM/
- Size: 408 MB
- Stars: 20
- Watchers: 8
- Forks: 1
- Open Issues: 16
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE.md
- Citation: CITATION.cff
Awesome Lists containing this project
- open-sustainable-technology - ibis.iSDM - Provides a series of convenience functions to fit integrated Species Distribution Models. (Biosphere / Species Distribution Modeling)
README
---
output:
rmarkdown::github_document:
html_preview: no
---
```{r, echo = FALSE, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
# The ibis framework - An **I**ntegrated model for **B**iod**I**versity distribution projection**S**
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[](https://github.com/iiasa/ibis.iSDM/actions/workflows/R-CMD-check.yaml)
[](https://creativecommons.org/licenses/by/4.0/)
[](https://app.codecov.io/gh/iiasa/ibis.iSDM?branch=master)
[](https://doi.org/10.1016/j.ecoinf.2023.102127)
[](https://iiasa.r-universe.dev/ibis.iSDM)
[](https://CRAN.R-project.org/package=ibis.iSDM)
The **ibis.iSDM** package provides a series of convenience functions to fit integrated Species Distribution Models (iSDMs). With integrated models we generally refer to SDMs that incorporate information from different biodiversity datasets, external parameters such as priors or offsets with respect to certain variables and regions. See [Fletcher et al. (2019)](https://doi.org/10.1002/ecy.2710) and [Isaac et al. (2020)](https://linkinghub.elsevier.com/retrieve/pii/S0169534719302551) for an introduction to iSDMs.
## Installation
The latest version can be installed from GitHub. A CRAN release is planned, but
in the meantime the package can be found on R-universe as well.
```{r gh-installation, eval = FALSE, message=FALSE}
# For installation (Not yet done)
install.packages("ibis.iSDM", repos = "https://iiasa.r-universe.dev")
# For Installation directly from github
install.packages("remotes")
remotes::install_github("IIASA/ibis.iSDM")
```
## Basic usage
See relevant [reference site](https://iiasa.github.io/ibis.iSDM/) and [articles](https://iiasa.github.io/ibis.iSDM/articles/01_train_simple_model.html).
Note that the package is in active development and parameters of some functions might change.
**Citation:**
Jung, Martin. 2023. “An Integrated Species Distribution Modelling Framework for Heterogeneous Biodiversity Data.” Ecological Informatics, 102127, [DOI](https://doi.org/10.1016/j.ecoinf.2023.102127)
## Acknowledgement 
**ibis.iSDM** is developed and maintained by the Biodiversity, Ecology and Conservation group at the International Institute for Applied Systems Analysis (IIASA), Austria.
## Contributors
All contributions to this project are gratefully acknowledged using the [`allcontributors` package](https://github.com/ropenscilabs/allcontributors) following the [all-contributors](https://allcontributors.org) specification. Contributions of any kind are welcome!
