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Amélie Marie Beucher

Mapping tree species ecograms based on soil pH and soil water availability across Denmark

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DOI

A prerequisite for successful afforestation and reforestation is understanding the quality of a site before establishing
a specific tree species. Ecograms have been widely applied to determine the suitability of different sites
for different species by a simple assessment of nutrient and water availability. Their graphical representation
of suitability into classes allows ecograms to be easily understood. However, ecograms have generally been
mapped for small areas only and their validity has rarely been documented. The aim of this study is to map
ecograms for five tree species across Denmark and validate the maps using forest stand production data.
For this purpose, we classified the landscape into six nutrient classes and nine water classes based on four
variables to generate the ecogram maps. Based on these classes, the generated maps depict if a tree species is
unsuitable, suitable or optimal for a specific site. The absolute average misclassification for nutrient and water
supply was 1 and 2 classes, respectively. Stepwise linear regression was implemented to determine if the four
variables used to create the ecograms were able to predict production as observed from forest experiment
and management planning data obtained from across the country. All five species used the full model to
explain variation in production. However, the average production values per ecogram growing condition were
not significantly different for all species. The range of R2 for the five species was 0.05–0.32, indicating that
one ecogram template might not work for all species. The high-resolution national ecogram maps incorporate
large-scale variables important for tree growth and will be beneficial when selecting new land for afforestation.
The simplicity of ecograms allows for easy interpretation, meaning that foresters can quickly determine which
regions of a landscape are suitable, saving time and resources.
Original languageEnglish
JournalForestry
Volume95
Issue2
Pages (from-to)287-299
Number of pages13
ISSN0015-752X
DOIs
Publication statusPublished - Apr 2022

    Research areas

  • ABIES, DISTRIBUTION MODELS, DOUGLAS-FIR PLANTATIONS, ENVIRONMENTAL-FACTORS, FOREST MANAGEMENT, SITE INDEX, SPRUCE, TEXTURE

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