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  "Title": "Phenotypic Index Measures for Oak Decline Severity",
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  "Description": "Oak declines are complex disease syndromes and consist of\nmany visual indicators that include aspects of tree size, crown\ncondition and trunk condition. This can cause difficulty in the\nmanual classification of symptomatic and non-symptomatic trees\nfrom what is in reality a broad spectrum of oak tree health\ncondition. Two phenotypic oak decline indexes have been\ndeveloped to quantitatively describe and differentiate oak\ndecline syndromes in Quercus robur. This package provides a\ntoolkit to generate these decline indexes from phenotypic\ndescriptors using the machine learning algorithm random forest.\nThe methodology for generating these indexes is outlined in\nFinch et al. (2021) <doi:10.1016/j.foreco.2021.118948>.",
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      "title": "Agrilus exit hole density (m^-2)",
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      "title": "Estimated bleed prevalence (%)",
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      "title": "Calculate Decline Indexes",
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