CLASSIFICATION AND REGRESSION TREES: A POWERFUL YET SIMPLE TECHNIQUE FOR ECOLOGICAL DATA ANALYSIS

By G. De’ath, Katharina E. Fabricius. 2000

3,284 citations recorded by the source corpus.

Subfields: Ecology, Ecology, Evolution, Behavior and Systematics, Genetics

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Citations in the corpus

The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification (2014, neutral): “, [12, 32, 13, 23, 15]); and prototype- or case-based classifiers (e.”
Invasion success of alien plants: do habitat affinities in the native distribution range matter? (2009, methodology): “The data were analysed using classification trees (Breiman et al ., 1984; Steinberg & Colla, 1995; De’ath & Fabricius, 2000).”
Loss of functional diversity under land use intensification across multiple taxa. (2009, methodology): “We used the sum of squares around group means to establish splitting criteria, selected optimal tree size by K-fold crossvalidation, and evaluated model fit with Pearson correlation of predicted to observed disappearance (De"ath & Fabricius 2000).”
Stream Fragmentation Thresholds for a Reproductive Guild of Great Plains Fishes (2011, methodology): “Accordingly, we tested for minimum thresholds in fragment length associated with population status of each species using classification tree analysis (CTA; De’ath and Fabricius 2000).”
Predicting climate‐induced range shifts: model differences and model reliability (2006, methodology): “Because most trees tend to over-fit the data, we selected the optimal tree size using the modal size suggested by fifty 10-fold cross-validations applying a 1-SE rule ( De'ath & Fabricius, 2000 ).”
Whale distribution in relation to prey abundance and oceanographic processes in shelf waters of the Western Antarctic Peninsula (2006, background): “…response types, are invariant to monotonic transformations of the explanatory variables, are easy to construct and interpret, can interpret missing values in both response and explanatory variables, and are able to capture interaction effects among predictor variables (De’ath and Fabricius 2000).”
Scaling up keystone effects from simple to complex ecological networks (2005, methodology): “The Regression Trees contained 17–24 splits and explained on average 60% of the total variation in per capita keystone effect strength on any given Sn.”
Variation in depth of whitetip reef sharks: does provisioning ecotourism change their behaviour? (2011, methodology): “CARTS are a nonparametric method that provides statistically robust and ecologically meaningful interpretations of data (De’ath and Fabricius 2000).”