Historical maps confirm the accuracy of zero-inflated model predictions of ancient tree abundance in English wood-pastures

摘要

1. Ancient trees have important ecological, historical and social connections, and are a key source of dead and decaying wood, a globally declining resource. Wood-pastures, which combine livestock grazing, open spaces and scattered trees, are significant reservoirs of ancient trees, yet information about their true abundance within wood-pastures is limited. England has extensive databases of both ancient trees and wood-pasture habitat, providing a unique opportunity for the first large-scale, national case study to address this knowledge gap. 2. We investigated the relationship between the abundance of ancient trees in a large sample of English wood-pastures (5,571) and various unique environmental, historical and anthropogenic predictors, to identify wood-pastures with high numbers of undiscovered ancient trees. A major challenge in many modelling studies is obtaining independent data for model verification: here we introduce a novel model verification step using series of historic maps with detailed records of trees to validate our model predictions. This desk-based method enables rapid verification of model predictions using completely independent data across a large geographical area, without the need for, or limitations associated with, extensive field surveys. 3. Historic map verification estimates correlated well with model predictions of tree abundance. Model predictions suggest there are ~101,400 undiscovered ancient trees in all wood-pastures in England, around 10 times the total current number of ancient tree records. Important predictors of ancient tree abundance included wood-pasture area, distance to several features including cities, commons, historic Royal forests and Tudor deer parks, and different types of soil and land classes. 4. Synthesis and applications. Historical maps and statistical models can be used in combination to produce accurate predictions of ancient tree abundance in wood-pastures, and inform future targeted surveys of wood-pasture