
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Models for predicting wood density of British-grown Sitka spruce

Models for predicting wood density of British-grown Sitka spruce
This paper describes the development of models to predict wood density in Sitka spruce (Picea sitchensis (Bong.) Carr.) growing in Britain. The models were designed to be practical and widely applicable and useful for large-scale resource mapping and investigating the impact of silvicultural treatments. Two models (and a variant of the second) were developed using data obtained from a 52-year-old spacing trial in Clocaenog Forest, North Wales, and a 32-year-old re-spacing experiment in Kershope Forest, Northern England. The model equations were based on models used to describe the within-tree variation in the wood density of Norway spruce (Picea abies L. Karst.) in France and are functions of ring width and ring number from the pith. The models were able to explain up to 48 per cent of the variability in density from Clocaenog but only 27 per cent of the variability in the density from Kershope, although they were able to accurately represent the radial trends in wood density. Some of the difficulties in explaining the variation in density may be due to the differences in the site conditions, silviculture and age of the trees at the two sites, but it is clear there is significant inter-tree variation in the data.
- Bangor University United Kingdom
- Bangor University United Kingdom
- Département Sciences sociales, agriculture et alimentation, espace et environnement France
- National Research Institute for Agriculture, Food and Environment France
- University of Aberdeen United Kingdom
BRITAIN, [SDV]Life Sciences [q-bio], STEMS, NORWAY SPRUCE, STIFFNESS, 333, [SDV] Life Sciences [q-bio], TOMOGRAPHY, TIMBER, QUALITY, UK, TREE
BRITAIN, [SDV]Life Sciences [q-bio], STEMS, NORWAY SPRUCE, STIFFNESS, 333, [SDV] Life Sciences [q-bio], TOMOGRAPHY, TIMBER, QUALITY, UK, TREE
2 Research products, page 1 of 1
- 2020IsAmongTopNSimilarDocuments
- 2017IsAmongTopNSimilarDocuments
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).64 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
