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pdi

Phenotypic Index Measures for Oak Decline Severity

v0.4.2 · Feb 9, 2021 · GPL-3

Description

Oak declines are complex disease syndromes and consist of many visual indicators that include aspects of tree size, crown condition and trunk condition. This can cause difficulty in the manual classification of symptomatic and non-symptomatic trees from what is in reality a broad spectrum of oak tree health condition. Two phenotypic oak decline indexes have been developed to quantitatively describe and differentiate oak decline syndromes in Quercus robur. This package provides a toolkit to generate these decline indexes from phenotypic descriptors using the machine learning algorithm random forest. The methodology for generating these indexes is outlined in Finch et al. (2121) <doi:10.1016/j.foreco.2021.118948>.

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NOTE 11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

LazyData

  'LazyData' is specified without a 'data' directory
NOTE r-oldrel-macos-x86_64

LazyData

  'LazyData' is specified without a 'data' directory
NOTE r-oldrel-windows-x86_64

LazyData

  'LazyData' is specified without a 'data' directory

Dependency Network

Dependencies Reverse dependencies dplyr magrittr purrr randomForest readxl stringr tibble tidyr tidyselect pdi

Version History

new 0.4.2 Mar 10, 2026