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Imputing missing data in plant traits: A guide to improve gap‐filling.

Authors :
Joswig, Julia S.
Kattge, Jens
Kraemer, Guido
Mahecha, Miguel D.
Rüger, Nadja
Schaepman, Michael E.
Schrodt, Franziska
Schuman, Meredith C.
Source :
Global Ecology & Biogeography. Aug2023, Vol. 32 Issue 8, p1395-1408. 14p.
Publication Year :
2023

Abstract

Aim: Globally distributed plant trait data are increasingly used to understand relationships between biodiversity and ecosystem processes. However, global trait databases are sparse because they are compiled from many, mostly small databases. This sparsity in both trait space completeness and geographical distribution limits the potential for both multivariate and global analyses. Thus, 'gap‐filling' approaches are often used to impute missing trait data. Recent methods, like Bayesian hierarchical probabilistic matrix factorization (BHPMF), can impute large and sparse data sets using side information. We investigate whether BHPMF imputation leads to biases in trait space and identify aspects influencing bias to provide guidance for its usage. Innovation: We use a fully observed trait data set from which entries are randomly removed, along with extensive but sparse additional data. We use BHPMF for imputation and evaluate bias by: (1) accuracy (residuals, RMSE, trait means), (2) correlations (bi‐ and multivariate) and (3) taxonomic and functional clustering (valuewise, uni‐ and multivariate). BHPMF preserves general patterns of trait distributions but induces taxonomic clustering. Data set–external trait data had little effect on induced taxonomic clustering and stabilized trait–trait correlations. Main Conclusions: Our study extends the criteria for the evaluation of gap‐filling beyond RMSE, providing insight into statistical data structure and allowing better informed use of imputed trait data, with improved practice for imputation. We expect our findings to be valuable beyond applications in plant ecology, for any study using hierarchical side information for imputation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1466822X
Volume :
32
Issue :
8
Database :
Academic Search Index
Journal :
Global Ecology & Biogeography
Publication Type :
Academic Journal
Accession number :
164936866
Full Text :
https://doi.org/10.1111/geb.13695