The use of individual tree statistics to quantify effects in an 'acid mist' experiment with mature trees

Cape, J.N.; Smith, R.I.; Crossley, A.; Harvey, F.J.; Sheppard, L.J.. 1995 The use of individual tree statistics to quantify effects in an 'acid mist' experiment with mature trees. Water, Air and Soil Pollution, 85 (3). 1367-1372. 10.1007/BF00477172

Full text not available from this repository.

Abstract/Summary

Mature trees of a single clone of Sitka spruce (Picea sitchensis (Bong.) Carr.) growing in the field were exposed to simulated acid mist at pH 2.5 over three successive years. The growth of each tree in the acid mist treatment, in terms of the stem area increment, was related to the pattern of growth of the untreated trees at the site during 1991 and 1992. In 1993, the effects of stopping the acid mist treatment on half of the treated trees was investigated by comparing the actual growth against that predicted relative to the untreated trees on the basis of the previous years'' data. The prediction of growth from one year to the next was consistently too small for the smallest acid-misted trees, suggesting that the growth rates relative to the untreated trees were increasing with time. Relative to the trees which continued to receive acid mist, however, the smaller trees which received no further acid mist in 1993 grew less than predicted, but there was a significantly greater growth than predicted for the largest recovering trees. Results from the individual tree modelling approach showed that a 10% change in relative stem area increment would be detectable at the 5% level, using a block of 4 trees as a treatment unit. The statistical techniques used are alternatives to conventional ANOVA calculations in determining statistically significant treatment effects where numbers of replicates are small.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1007/BF00477172
Programmes:	CEH Programmes pre-2009 publications > Biogeochemistry
UKCEH and CEH Sections/Science Areas:	_ Pre-2000 sections
ISSN:	0049-6979
Additional Keywords:	Statistics, Modelling
NORA Subject Terms:	Agriculture and Soil Science Atmospheric Sciences
Date made live:	26 May 2009 07:44 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/7257

Actions (login required)

View Item

Document Downloads

More statistics for this item...