BIOMOD – a platform for ensemble forecasting of species distributions

By Wilfried Thuiller, Bruno Lafourcade, Robin Engler, Miguel B. Araújo. 2009

2,605 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/aae8d49cb6f1bb0055849b5aaed7edfb92a61d3f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches (2011, methodology): “The BIOMOD library in R (Thuiller et al., 2009) was used to implement GLM, GAM, GBM and RF, assuming a binomial distribution and the same parameterizing options as for the MEM, but separately for each species (260 in the Diablerets and 42 in Belalp).”
The projection of species distribution models and the problem of non-analog climate (2009, methodology): “We projected a model of the entire Caspian Sea onto the Great Lakes using BIOMOD (Thuiller 2003; Thuiller et al. 2009) in R version 2.7.2 (R Development Core Team 2008).”
Applications of species distribution modeling to paleobiology (2011, background): “BIOMOD is an SDM platform specifically designed for ensemble forecasting (Thuiller et al., 2009).”
Species distribution modelling of marine benthos: a North Sea case study (2011, background): “This stepwise procedure removes redundancy in variables and reduces multicollinearity (Thuiller 2003, Thuiller et al. 2009).”
Present and future distribution of three aquatic plants taxa across the world: decrease in native and increase in invasive ranges (2017, methodology): “Once they are released into aquatic environments, their spread is facilitated by flows and flooding events that connect water bodies.”
Climate change threatens European conservation areas (2011, methodology): “All models were run using default options of the BIOMOD package (Thuiller et al. 2009).”
Where will conflicts between alien and rare species occur after climate and land-use change? A test with a novel combined modelling approach (2011, methodology): “Conceptual combined modelling framework We developed combined and non-combined ensemble forecasting models for current and future distributions of Acacia dealbata and Ruscus aculeatus using BIOMOD (Thuiller et al. 2009) in the R statistical software (R Development Core Team 2009).”
Selecting thresholds for the prediction of species occurrence with presence‐only data (2013, methodology): “Numerous modelling techniques have been used to predict species distributions (e.g. Segurado & Ara ujo, 2004; Elith et al., 2006; Thuiller et al., 2009).”
Ditch the niche – is the niche a useful concept in ecology or species distribution modelling? (2012, methodology): “Not according to the original papers (Thuiller, 2003; Thuiller et al., 2009), where neutral terminology is used.”
Forecasting the future of biodiversity: a test of single- and multi-species models for ants in North America (2011, methodology): “GDM tended to forecast greater amounts of compositional change and over a more contiguous area than did BIOMOD, including the south central United States (US), the Sierra Nevada of the western US, and most of Central America (Fig.”