SDM (Species Distribution Models)

SDM (Species Distribution Models)

 

(Models that predict species' potential distributions by combining known occurrence records with digital layers of environmental variables)

 
  1. Maxent is based on the maximum-entropy approach for species habitat modeling.
    • finds the largest spread (maximum entropy) in a geographic dataset of species presences
    • maximizes the log likelihood of the data associated with the presence sites minus a penalty term, conceptually similar to information criteria like AIC
  2. DesktopGARP is a genetic algorithm that creates an ecological niche model for a species that represents the environmental conditions where that species would be able to maintain populations.
    • input a set of point localities where the species is known to occur
    • finds non-random correlations between the presence and absence of the species and the values of the environmental parameters
    • there are four types of rules that are implemented to build the models: atomic, logistic regression, bioclimatic envelope and negated bioclimatic envelope
  3. DIVA-GIS is particularly useful for mapping and analyzing biodiversity data, such as the distribution of species, or other 'point-distributions'.
    • supports SDMs for BIOCLIM or DOMAIN models
    • treats absence and background data as equivalent concepts. All non-presence points are considered to be absence data
  4. openModeller provides a flexible, robust, cross-platform environment to carry out ecological niche modeling experiments.
    • The framework includes facilities for sampling points, creating, testing, evaluating and projecting models into different environmental scenarios
    • More than 10 algorithms are available as plugins, including GARP, Maxent, ENFA and Support Vector Machines
  5. BioMapper is a A GIS-toolkit to model ecological niche and habitat suitability.
    • Preparing the ecogeographical maps in order to use them as input for the Ecological Niche Factor Analysis (ENFA) (e.g. computing frequency of occurrence map, standardization, masking, etc.)
    • Exploring and comparing maps by mean of descriptive statistics (distribution analysis, etc.)
    • Computing the Ecological Niche Factor Analysis and exploring its output
    • Computing a Habitat Suitability map

 

https://people.iut.ac.ir/en/fakheran/fakheran.iut.ac.ir/Species.distribution.model