0cf43cf8-ec14-4c37-85eb-23cccb5610b2 0.2.10 sdmpredictors R package 2016-09-26 2021-09-24 The goal of sdmpredictors is to make environmental data, commonly used for species distribution modelling (SDM), also called ecological niche modelling (ENM) or habitat suitability modelling, easy to use in R. sdmpredictors gives access to several environmental datasets, including the the Bio-ORACLE Marine Data Layers for Bioclimatic Modelling. LifeWatch hosts the website https://www.bio-oracle.org/ and supports the development of these layers. The package contains methods for getting downloading raster data for the current climate but also for future and paleo climatic conditions. These rasters and then loaded into R. Salvador Fernández Bejarano Flanders Marine Institute salvador.fernandez@vliz.be Samuel Bosch Institute for Agricultural and Fisheries Research (ILVO) samuel.bosch@ilvo.vlaanderen.be Salvador Fernández Bejarano Flanders Marine Institute salvador.fernandez@vliz.be https://metadatacatalogue.lifewatch.eu/srv/api/records/0cf43cf8-ec14-4c37-85eb-23cccb5610b2/attachments/sdmpredictors.jpg marine environmental modelling climate change terrestrial biogeography R https://github.com/lifewatch/sdmpredictors/blob/master/LICENSE.md Bio-Oracle dataset https://bio-oracle.org/ Bio-ORACLE is a set of GIS rasters providing geophysical, biotic and environmental data for surface and benthic marine realms. The Bio-ORACLE main purpose is to be used together with biological occurrence for fitting Species Distribution Models and predict future distribution of species. WorldClim http://www.worldclim.org/ WorldClim is a set of global climate layers (climate grids). WorldClim can be used together with biological occurrence for fitting Species Distribution Models and predict future distribution of species. MARSPEC http://marspec.org/ MARSPEC is a set of high resolution climatic and geophysical GIS data layers for the world ocean. MARSPEC can be used together with biological occurrence for fitting Species Distribution Models and predict future distribution of species. ENVIREM https://envirem.github.io/ The ENVIREM dataset is a set of 16 climatic and 2 topographic variables that can be used in modeling species' distributions. The strengths of this dataset include their close ties to ecological processes, and their availability at a global scale, at several spatial resolutions, and for several time periods. ENVIREM can be used together with biological occurrence for fitting Species Distribution Models and predict future distribution of species. Freshwater https://www.earthenv.org/streams The dataset consists of near-global, spatially continuous, and freshwater-specific environmental variables in a standardized 1km grid. Freshwater can be used together with biological occurrence for fitting Species Distribution Models and predict future distribution of species. data analysis data processing sdmpredictors is maintained and developed by a consortium of researchers, data managers and IT personnel from 4 institutions: Flanders Marine Institute, University of Algarve, Institute for Agricultural and Fisheries Research and University of Ghent. The maintenance and current developments of the package are carried out by the Flanders Marine Institute, currently with the funding of the LifeWatch Belgium project. https://github.com/lifewatch/sdmpredictors/issues https://lifewatch.github.io/sdmpredictors/articles/quickstart.html https://lifewatch.github.io/sdmpredictors/reference/index.html http://lifewatch.github.io/sdmpredictors/ WWW:LINK-1.0-http--link Package website https://cran.r-project.org/package=sdmpredictors WWW:LINK-1.0-http--link sdmpredictors on CRAN https://github.com/lifewatch/sdmpredictors WWW:LINK-1.0-http--link sdmpredictors on GitHub