Using functional traits to predict species growth trajectories, and cross-validation to evaluate these models for ecological prediction

Thomas, F, Yen, J and Vesk, P 2018, 'Using functional traits to predict species growth trajectories, and cross-validation to evaluate these models for ecological prediction', Ecology and Evolution, vol. 9, no. 4, pp. 1554-1566.


Document type: Journal Article
Collection: Journal Articles

Title Using functional traits to predict species growth trajectories, and cross-validation to evaluate these models for ecological prediction
Author(s) Thomas, F
Yen, J
Vesk, P
Year 2018
Journal name Ecology and Evolution
Volume number 9
Issue number 4
Start page 1554
End page 1566
Total pages 13
Publisher John Wiley & Sons Ltd
Abstract Modeling plant growth using functional traits is important for understanding the mechanisms that underpin growth and for predicting new situations. We use three data sets on plant height over time and two validation methods�in-sample model fit and leave-one-species-out cross-validation�to evaluate non-linear growth model predictive performance based on functional traits. In-sample measures of model fit differed substantially from out-of-sample model predictive performance; the best fitting models were rarely the best predictive models. Careful selection of predictor variables reduced the bias in parameter estimates, and there was no single best model across our three data sets. Testing and comparing multiple model forms is important. We developed an R package with a formula interface for straightforward fitting and validation of hierarchical, non-linear growth models. Our intent is to encourage thorough testing of multiple growth model forms and an increased emphasis on assessing model fit relative to a model's purpose.
Subject Ecology not elsewhere classified
Keyword(s) cross-validation
ecological predictions
functional traits
growth models
non-linear models
DOI - identifier 10.1002/ece3.4693
Copyright notice © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
ISSN 2045-7758
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