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Environmental niche modelling (alternatively known as ecological niche modelling, fundamental niche modelling, or simply niche modelling; also: species distribution models) 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 various factors such as barriers to dispersal, geological history, or biotic interactions, that increase the difference between the realized niche and the fundamental niche. 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.

Correlative models

Correlative models relate observed presences of a species to values of environmental variables at those sites. Some models use absences, as well, but the most commonly used models use presence-only data since one can generally be more sure of a species' presence than its absence and because most data sets do not include sites where a species was searched for but not found. Because they are based on actual distribution of the species, they model the realized niche (resulting of abiotic and biotic constraints) as opposed to the fundamental niche that is solely based on the species' abiotic requirements.

Mechanistic models

A mechanistic model (or process-based model) assess the bio-physiological aspects of a species to generate the conditions in which the species can ideally persist, based on observations made in controlled field or laboratory studies. As such it represents the fundamental niche of the species.

To date, most environmental niche modeling has not used mechanistic models because they require detailed parameterization and thus more precise knowledge of the species of interest. See ^[1] for a comparison between mechanistic and correlative models.

Niche modelling tools

Examples of niche modelling tools that have been developed include BIOCLIM,^[2]^[3] DOMAIN, the Genetic Algorithm for Rule-set Production (GARP),^[4] maximization of information entropy (MAXENT), generalized linear models (GLMs), generalized additive models (GAMs), classification and regression trees (CART), boosted regression trees (BRTs; also known as gradient boosting methods), random forests (RF), Bayesian methods, and relative environmental suitability (RES) modelling as described by Kaschner et al.^[5] 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.

References

^ Morin, X. (2009). "Comparing niche- and process-based models to reduce prediction uncertainty in species range shifts under climate change". Ecology. 90 (5): 1301–13. doi:10.1890/08-0134.1. PMID 19537550. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)
^ Nix HA (1986). "BIOCLIM — a Bioclimatic Analysis and Prediction System". Research report, CSIRO Division of Water and Land Resources. 1983–1985: 59–60.
^ Nix HA (1986). "A biogeographic analysis of Australian elapid snakes". In Longmore (ed.). Atlas of Elapid Snakes of Australia. Australian Flora and Fauna Series 7. Bureau of Flora and Fauna, Canberra. pp. 4–15.
^ Stockwell DRB & Peters DP (1999). "The GARP modelling system: Problems and solutions to automated spatial prediction". International Journal of Geographic Information Systems. 13 (2): 143–158. doi:10.1080/136588199241391.
^ Kaschner K, Watson R, Trites AW & Pauly D (2006). "Mapping world-wide distributions of marine mammal species using a relative environmental suitability (RES) model" (PDF). Marine ecology. Progress series. 316: 285–310. doi:10.3354/meps316285.{{cite journal}}: CS1 maint: multiple names: authors list (link)

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

[1] Morin, X. (2009). "Comparing niche- and process-based models to reduce prediction uncertainty in species range shifts under climate change". Ecology. 90 (5): 1301–13. doi:10.1890/08-0134.1. PMID 19537550. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)

[Nix1986a-2] Nix HA (1986). "BIOCLIM — a Bioclimatic Analysis and Prediction System". Research report, CSIRO Division of Water and Land Resources. 1983–1985: 59–60.

[Nix1986b-3] Nix HA (1986). "A biogeographic analysis of Australian elapid snakes". In Longmore (ed.). Atlas of Elapid Snakes of Australia. Australian Flora and Fauna Series 7. Bureau of Flora and Fauna, Canberra. pp. 4–15.

[Stockwell1999-4] Stockwell DRB & Peters DP (1999). "The GARP modelling system: Problems and solutions to automated spatial prediction". International Journal of Geographic Information Systems. 13 (2): 143–158. doi:10.1080/136588199241391.

[Kaschner2006-5] Kaschner K, Watson R, Trites AW & Pauly D (2006). "Mapping world-wide distributions of marine mammal species using a relative environmental suitability (RES) model" (PDF). Marine ecology. Progress series. 316: 285–310. doi:10.3354/meps316285.{{cite journal}}: CS1 maint: multiple names: authors list (link)

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 * [http://www.aquamaps.org AquaMaps] - global predictive maps for marine species
 * [http://www.elsevier.com/wps/find/journaldescription.cws_home/503306/description Ecological Modelling] - International Journal on Ecological Modelling and Systems Ecology
-* [http://landshape.org/enm/ Niche Modeling] - online site/blog from David Stockwell, one of the early and current pioneers in ecological niche modelling
 {{modelling ecosystems|expanded=other}}

v t e Ecology: Modelling ecosystems: Trophic components
General	Abiotic component Abiotic stress Behaviour Biogeochemical cycle Biomass Biotic component Biotic stress Carrying capacity Competition Ecosystem Ecosystem ecology Ecosystem model Green world hypothesis Keystone species List of feeding behaviours Metabolic theory of ecology Productivity Resource Restoration
Producers	Autotrophs Chemosynthesis Chemotrophs Foundation species Kinetotrophs Mixotrophs Myco-heterotrophy Mycotroph Organotrophs Photoheterotrophs Photosynthesis Photosynthetic efficiency Phototrophs Primary nutritional groups Primary production
Consumers	Apex predator Bacterivore Carnivores Chemoorganotroph Foraging Generalist and specialist species Intraguild predation Herbivores Heterotroph Heterotrophic nutrition Insectivore Mesopredators Mesopredator release hypothesis Omnivores Optimal foraging theory Planktivore Predation Prey switching
Decomposers	Chemoorganoheterotrophy Decomposition Detritivores Detritus
Microorganisms	Archaea Bacteriophage Lithoautotroph Lithotrophy Marine Microbial cooperation Microbial ecology Microbial food web Microbial intelligence Microbial loop Microbial mat Microbial metabolism Phage ecology
Food webs	Biomagnification Ecological efficiency Ecological pyramid Energy flow Food chain Trophic level
Example webs	Lakes Rivers Soil Tritrophic interactions in plant defense Marine food webs cold seeps hydrothermal vents intertidal kelp forests North Pacific Gyre San Francisco Estuary tide pool
Processes	Ascendency Bioaccumulation Cascade effect Climax community Competitive exclusion principle Consumer–resource interactions Copiotrophs Dominance Ecological network Ecological succession Energy quality Energy systems language f-ratio Feed conversion ratio Feeding frenzy Mesotrophic soil Nutrient cycle Oligotroph Paradox of the plankton Trophic cascade Trophic mutualism Trophic state index
Defense, counter	Animal coloration Anti-predator adaptations Camouflage Deimatic behaviour Herbivore adaptations to plant defense Mimicry Plant defense against herbivory Predator avoidance in schooling fish

v t e Ecology: Modelling ecosystems: Other components
Population ecology	Abundance Allee effect Consumer-resource model Depensation Ecological yield Effective population size Intraspecific competition Logistic function Malthusian growth model Maximum sustainable yield Overpopulation Overexploitation Population cycle Population dynamics Population modeling Population size Predator–prey (Lotka–Volterra) equations Recruitment Small population size Stability Resilience Resistance Random generalized Lotka–Volterra model
Species	Biodiversity Density-dependent inhibition Ecological effects of biodiversity Ecological extinction Endemic species Flagship species Gradient analysis Indicator species Introduced species Invasive species / Native species Latitudinal gradients in species diversity Minimum viable population Neutral theory Occupancy–abundance relationship Population viability analysis Priority effect Rapoport's rule Relative abundance distribution Relative species abundance Species diversity Species homogeneity Species richness Species distribution Species–area curve Umbrella species
Species interaction	Antibiosis Biological interaction Commensalism Community ecology Ecological facilitation Interspecific competition Mutualism Parasitism Storage effect Symbiosis
Spatial ecology	Biogeography Cross-boundary subsidy Ecocline Ecotone Ecotype Disturbance Edge effects Foster's rule Habitat fragmentation Ideal free distribution Intermediate disturbance hypothesis Insular biogeography Land change modeling Landscape ecology Landscape epidemiology Landscape limnology Metapopulation Patch dynamics r/K selection theory Resource selection function Source–sink dynamics
Niche	Ecological niche Ecological trap Ecosystem engineer Environmental niche modelling Guild Habitat marine habitats Limiting similarity Niche apportionment models Niche construction Niche differentiation Ontogenetic niche shift
Other networks	Assembly rules Bateman's principle Bioluminescence Ecological collapse Ecological debt Ecological deficit Ecological energetics Ecological indicator Ecological threshold Ecosystem diversity Emergence Extinction debt Kleiber's law Liebig's law of the minimum Marginal value theorem Thorson's rule Xerosere
Other	Allometry Alternative stable state Balance of nature Biological data visualization Ecological economics Ecological footprint Ecological forecasting Ecological humanities Ecological stoichiometry Ecopath Ecosystem based fisheries Endolith Evolutionary ecology Functional ecology Industrial ecology Macroecology Microecosystem Natural environment Regime shift Sexecology Systems ecology Urban ecology Theoretical ecology
Outline of ecology