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;NPMR behaves like an organism
NPMR has been useful for modeling the response of an organism to its environment. Organismal response to environment tends to be nonlinear and have complex interactions among predictors. NPMR allows you to model automatically the complex interactions among predictors in much the same way that organisms integrate the numerous factors affecting their performance.<ref>{{Cite journal|last=McCune|first=B.|year=2006|title=Non-parametric habitat models with automatic interactions|journal=Journal of Vegetation Science|volume=17|pages=819–830|doi=10.1658/1100-9233(2006)17[819:NHMWAI]2.0.CO;2|issue=6|url=http://ir.library.oregonstate.edu/xmlui/bitstream/1957/3685/1/McCune2006JVS-NPMR.pdf}}</ref>
A key biological feature of an NPMR model is that failure of an organism to tolerate any single dimension of the predictor space results in overall failure of the organism. For example, assume that a plant needs a certain range of moisture in a particular temperature range. If either temperature or moisture fall outside the tolerance of the organism, then the organism dies. If it is too hot, then no amount of moisture can compensate to result in survival of the plant. Mathematically this works with NPMR because the product of the weights for the target point is zero or near zero if any of the weights for individual predictors (moisture or temperature) are zero or near zero. Note further that in this simple example, the second condition listed above is probably true: the response of the plant to moisture probably depends on temperature and vice versa.
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