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- W1574407852 abstract "In the case of vegetation a decision is needed on what should be predicted, either individual plant species, species traits, or entire vegetation types, in analogy to the historic debate in plant ecology. Once various species distributions are modelled then these can be subjected to classification, resulting in vegetation types and ultimately in probabilities for the occurrence of vegetation types. In the reverse case, if vegetation types are modelled directly, relative species abundance within types is an estimate for occurrence probability. Technical constraints occurring in either of these approaches are assessed in this chapter. It presents methods for predicting species distribution based on environmental factors, including generalized linear models (GLMs), generalized additive models (GAMs), and classification and regression trees (CART). In conclusion, simulating vegetation types and extending the models to individual species offers more flexibility than the usual direct logistic regression approaches such as GLMs, GAMs and CART." @default.
- W1574407852 created "2016-06-24" @default.
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- W1574407852 date "2013-03-31" @default.
- W1574407852 modified "2023-09-23" @default.
- W1574407852 title "Static Predictive Modelling" @default.
- W1574407852 doi "https://doi.org/10.1002/9781118562543.ch8" @default.
- W1574407852 hasPublicationYear "2013" @default.
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