Index measures for oak decline severity using phenotypic descriptors

Oak decline syndromes such as Acute Decline (AOD) and Chronic (COD) are becoming increasingly prevalent with this comes the need for more quantitative, sensitive standardised visual oak health monitoring. Phenotyping protocols were developed to specifically measure severity based on a comprehensive set of simple phenotypic descriptors. A total 36 measurements describing status included aspects tree size, crown condition, presence biotic agents number derived composite Phenotypic collected from 174 Quercus robur, surveyed 9 sites across England healthy, AOD, COD AOD trees in remission. Using these data, Index (PDI) Acuteness (DAI) quantitatively describe differentiate acute chronic spectrum. These indexes unsupervised random forest machine learning models, trained using data. The suitability type assessed by comparing index scores manual classifications along an assessment descriptor importance contribution models. Crown condition size descriptors ‘composite volume’ contributed positively PDI. Trees smaller crowns poor had greater PDI values. Tree stature stem bleeding highly DAI, allowing differentiation between syndromes. relatively larger where small was absent. but measures allow easy comparisons both spatially temporally. have potential provide useful tools monitoring management well application remote sensing omics research.