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Environmental niche modelling (alternatively known as ecological niche modelling, or simply niche modelling) refers to the process of using computer algorithms to generate predictive maps of species distributions in geographic space on the basis of a mathematical representation of their known or inferred distributions in environmental space (= ecological niche), utilizing base data layers that summarize the spatial distribution of the environmental parameters considered in the model (such as temperature, altitude, wind stress, ocean depth, days of ice cover, water chemistry and so on). Such information may be of interest for a number of requirements, including interpolating between limited available data records; studying the divergence between actual and potential distributions (for example, the potential spread of invasive species once introduced to a new area, or the area once occupied by a species prior to exploitation by humans); as well as possible alterations to species ranges in the light of changing climatic or other factors. The extent to which such modelled data reflect real-world species distributions will depend on a number of factors, including the nature, complexity, and accuracy of the models used and the quality of the available environmental data layers; the availability of sufficient and reliable species distribution data as model input; and the influence of non-niche factors such as barriers to dispersal, geologic history, or competing species, that may prevent the present day occupation of all potential niches as identified by the model. Environmental niche modelling may be considered a part of the discipline of biodiversity informatics, or alternatively an end user of the species distribution data that is one output of biodiversity informatics activities.

Examples of niche modelling tools that have been developed include BIOCLIM[1][2], the Genetic Algorithm for Rule-set Production (GARP)[3], and relative environmental suitability (RES) modelling as described by Kaschner et al.[4]. Lifemapper and AquaMaps utilize implementations of GARP and RES, respectively, while a package of different software options for niche modelling is available online via the open source openModeller project.

Example of simple niche modelling using rainfall, altitude and current species observations to create a model of possible existence for a certain species.

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See also

References

  1. ^ Nix HA (1986). "BIOCLIM — a Bioclimatic Analysis and Prediction System". Research report, CSIRO Division of Water and Land Resources 1983–1985: 59–60. 
  2. ^ Nix HA (1986). "A biogeographic analysis of Australian elapid snakes". in Longmore. Atlas of Elapid Snakes of Australia. Australian Flora and Fauna Series 7. Bureau of Flora and Fauna, Canberra. pp. 4–15. 
  3. ^ Stockwell DRB & Peters DP (1999). "The GARP modelling system: Problems and solutions to automated spatial prediction". International Journal of Geographic Information Systems 13: 143-158. 
  4. ^ Kaschner K, Watson R, Trites AW & Pauly D (2006). "Mapping world-wide distributions of marine mammal species using a relative environmental suitability (RES) model". Marine ecology. Progress series 316: 285-310. http://www.int-res.com/articles/meps_oa/m316p285.pdf. 

Further reading

External links

  • openModeller - open source fundamental niche modelling library
  • lifemapper - niche modelling project from Kansas University
  • Lifemapper 2.0 - video of presentation by Aimee Stewart, Kansas University, at O'Reilly Where 2.0 Conference 2008
  • AquaMaps - global predictive maps for marine species
  • Ecological Modelling - International Journal on Ecological Modelling and Systems Ecology
  • Niche Modeling - online site/blog from David Stockwell, one of the early and current pioneers in ecological niche modelling
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