SDM-R – A reproducible and extensible R platform for species distribution modellings
sdm-R is an object-oriented, reproducible and extensible R platform for species distribution modelling. The sdm package is designed to create a comprehensive modelling and simulation framework that: 1) provides a standardised and unified structure for handling species distributions data and modelling techniques (e.g. a unified interface is used to fit different models offered by different packages); 2) is able to support markedly different modelling approaches; 3) enables scientists to modify the existing methods, extend the framework by developing new methods or procedures, and share them to be reproduced by the other scientists; 4) handles spatial as well as temporal data for single or multiple species; 5) employs high performance computing solutions to speed up modelling and simulations, and finally; 6) uses flexible and easy-to-use GUI interface. For more information, check the published paper by:
Naimi and Araujo 2016. A reproducible and extensible R platform for species distributions modelling. Ecography 39: 368-375.
Also Babak’s dedicated web page to get start with sdm-R.
BioGIS – Biogeographical Information System
BioGIS is a platform for visual inspection and analyses of large biodiversity data sets. It is a fully fledged geographical information system with functions that until recently were only available in WORLDMAP (a computer program developed by Paul Williams at the Natural History Museum and that was discontinued in the late 90s). Analytical functions include species richness and rarity analysis, spatial turnover (beta diversity), temporal turnover, spatiotemporal turnover, and overlays of 1-D, 2-D, and 3-D scores on maps. The program allows importing data in several formats, including shape files, raster files, and data matrices of several kinds (thus being able to smoothly communicate with BIOMOD, BIOENSEMBLES, and other modelling software). The program is being developed as part of a partnership involving Alejandro Rozenfeld, Carsten Rahbek, and Miguel B. Araújo.
Bioensembles is a computer-intensive platform for ensemble forecasting of species distributions that includes 13 different ecological niche modelling techniques and advanced consensus forecasting methodologies. Unlike BIOMOD it is a windows-based program written in Delphi that “speaks” with R and with the Java-based Maxent. BIOENSEMBLES is being developed as part of a partnership that started in 2007 with funding from the BBVA Foundation (BIOIMPACTO project) and later with funding from FCT (NICHE project). Development of BIOENSEMBLES involved Thiago Rangel and François Guilhaumon in the programming side (the latter mainly focusing on the interface with R and the parameterization of presence-absence methods) and Alexandre Diniz Filho and Miguel B. Araújo (conceptual development). The program is still unavailable for release but is being used for research within our labs.
No official release of BIOENSEMBLES has yet been made. Meanwhile, it should be cited by the first paper that used it:
Diniz-Filho, J. A. F., Bini, L.M., Rangel, T.F., Loyola, R.D., Hof, C., Nogués-Bravo, D. & Araújo, M.B. 2009. Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change. Ecography 32: 897-906.
BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling explicit treatment of a range of methodological uncertainties and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package.
BIOMOD is available for any platform (Unix, MacOS, Windows) on R-Forge:
It can be loaded directly from R using the following call:
BIOMOD should be cited as:
Thuiller, W., Lafourcade, B., Engler, R., & Araújo, M.B. 2009. BIOMOD – A platform for ensemble forecasting of species distributions. Ecography. 32: 369-373
demoniche – spatial population dynamics
demoniche is a computer software written in R that carries out spatially-explicit demographic modelling. The model simulates stochastic and gradual niche changes, to investigate population dynamics and persistence in space and time. demoniche offers the following features:
•Transition matrices that represent demographic responses to environmental or human impact scenarios
•Demographic and environmental stochasticity
•Temporal trends in environmental suitability of the species niche
•Long- and short-distance dispersal
demoniche is built in R and can be downloaded here. We encourage you to adapt demoniche to your and your species specific needs!
demoniche should be cited as:
Nenzén, H.K., Keith, D.A. & Araújo, M.B. 2011. demoniche – an R-package for simulating spatially-explicit population dynamics. Ecography. In review
MulTyLink is an open source application designed to identify connectivity linkages for distinct types of habitats, under a cost-efficient protocol. Since areas that can be used as linkages for one type of habitats may be barriers for other types, MulTyLink implements methods to optimize the selection of linkages free of barriers for every type of habitat. MulTyLink was conceived as a decision-support tool to be used in spatial conservation planning. The software provides users the flexibility to assign costs, friction values and habitat-specific barriers as input data. Based on these scores MulTyLink retrieves a network of linkages which may be visualized as a whole solution or independently for each habitat type.
MulTyLink is available as a stand alone programme here
MulTyLink should be cited as:
Brás, E., Cerdeira, J.O., Alagador, D. & Araújo, M.B. Linking habitats for multiple species. Environmental Modelling and Software. dx.doi.org/10.1016/j.envsoft.2012.08.001.
Alagador, D., Triviño, M., Cerdeira, J.O., Brás, R., Cabeza, M., Araújo, M.B. 2012. Linking like with like: optimising connectivity between environmentally-similar habitats. Landscape Ecology. 27: 291-301.
Taxonomic data are stored in specimen collections, museum records, and to a lesser extent in digitized databases. Too often, these sources contain incorrect taxonomic references and inaccurate geographical locations. Errors in taxonomic references usually arise because of changes in species nomenclatures. Geo-referencing of data my have errors because of inaccuracies in the characterization of the locations where specimens were captured, and because collectors reported locality names that later are changed. To solve these problems, we developed the IBIODAT software (Application for Normalizing Taxonomic Collections in the Iberian Peninsula). This application enables checking and correction of already digitized collections and also provides a tool for digitizing and geo-referencing old collections. All the outputs of the application follow the formats of the international agreements on taxonomic collections digitization (Darwin Core, GIBIF).
More information and downloads can be obtained here