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More efficient estimation of plant biomass

Brathen, K A and Hagberg, Oskar LU (2004) In Journal of Vegetation Science 15(5). p.653-660
Abstract
Question: The optimal use of the point intercept method (PIM) for efficient estimation of plant biomass has not been addressed although PIM is a commonly used method in vegetation analysis. In this study we compare results achieved using PIM at a range of efforts, we assess a method for calculating these results that are new with PIM and we provide a formula for planning the optimal use of PIM. Location: Northern Norway. Methods: We collected intercept data at a range of efforts, i.e. from one to 100 pins per 0.25 m(2) plots, on three plant growth forms in a mountain meadow. After collection of intercept data we clipped and weighed the plant biomass. The relationship between intercept frequency and weighed biomass (b) was estimated using... (More)
Question: The optimal use of the point intercept method (PIM) for efficient estimation of plant biomass has not been addressed although PIM is a commonly used method in vegetation analysis. In this study we compare results achieved using PIM at a range of efforts, we assess a method for calculating these results that are new with PIM and we provide a formula for planning the optimal use of PIM. Location: Northern Norway. Methods: We collected intercept data at a range of efforts, i.e. from one to 100 pins per 0.25 m(2) plots, on three plant growth forms in a mountain meadow. After collection of intercept data we clipped and weighed the plant biomass. The relationship between intercept frequency and weighed biomass (b) was estimated using both a weighted linear regression model (WLR) and an ordinary linear regression model (OLR). The accuracy of the estimate of biomass achieved by PIM at different efforts was assessed by running computer simulations at different pin densities. Results: The relationship between intercept frequency and weighed biomass (b) was far better estimated using WLR compared to the normally used OLR. Efforts above 10 pins per 0.25 m(2) lot had a negligible effect on the accuracy of the estimate of biomass achieved by PIM whereas the number of plots had a strong effect. Moreover, for a given level of accuracy, the required number of plots varied depending on plant growth form. We achieved similar results to that of the computer simulations when applying our WLR based formula. Conclusion: This study shows that PIM can be applied more efficiently than was done in previous studies for the purpose of plant biomass estimation, where several plots should be analysed but at considerably less effort per plot. Moreover, WLR rather than OLR should be applied when estimating biomass from intercept frequency. The formula we have deduced is a useful tool for planning plant biomass analysis with PIM. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Rhinanthus minor, point intercept method, graminoid, Bistorta vivipara, ericoid, weighted linear regression
in
Journal of Vegetation Science
volume
15
issue
5
pages
653 - 660
publisher
International Association of Vegetation Science
external identifiers
  • wos:000224638600008
  • scopus:6344294939
ISSN
1654-1103
DOI
10.1658/1100-9233(2004)015[0653:MEEOPB]2.0.CO;2
language
English
LU publication?
yes
id
33549d7a-8c48-432b-8eea-b7029d01931a (old id 262725)
date added to LUP
2007-10-17 11:49:54
date last changed
2017-10-01 03:47:31
@article{33549d7a-8c48-432b-8eea-b7029d01931a,
  abstract     = {Question: The optimal use of the point intercept method (PIM) for efficient estimation of plant biomass has not been addressed although PIM is a commonly used method in vegetation analysis. In this study we compare results achieved using PIM at a range of efforts, we assess a method for calculating these results that are new with PIM and we provide a formula for planning the optimal use of PIM. Location: Northern Norway. Methods: We collected intercept data at a range of efforts, i.e. from one to 100 pins per 0.25 m(2) plots, on three plant growth forms in a mountain meadow. After collection of intercept data we clipped and weighed the plant biomass. The relationship between intercept frequency and weighed biomass (b) was estimated using both a weighted linear regression model (WLR) and an ordinary linear regression model (OLR). The accuracy of the estimate of biomass achieved by PIM at different efforts was assessed by running computer simulations at different pin densities. Results: The relationship between intercept frequency and weighed biomass (b) was far better estimated using WLR compared to the normally used OLR. Efforts above 10 pins per 0.25 m(2) lot had a negligible effect on the accuracy of the estimate of biomass achieved by PIM whereas the number of plots had a strong effect. Moreover, for a given level of accuracy, the required number of plots varied depending on plant growth form. We achieved similar results to that of the computer simulations when applying our WLR based formula. Conclusion: This study shows that PIM can be applied more efficiently than was done in previous studies for the purpose of plant biomass estimation, where several plots should be analysed but at considerably less effort per plot. Moreover, WLR rather than OLR should be applied when estimating biomass from intercept frequency. The formula we have deduced is a useful tool for planning plant biomass analysis with PIM.},
  author       = {Brathen, K A and Hagberg, Oskar},
  issn         = {1654-1103},
  keyword      = {Rhinanthus minor,point intercept method,graminoid,Bistorta vivipara,ericoid,weighted linear regression},
  language     = {eng},
  number       = {5},
  pages        = {653--660},
  publisher    = {International Association of Vegetation Science},
  series       = {Journal of Vegetation Science},
  title        = {More efficient estimation of plant biomass},
  url          = {http://dx.doi.org/10.1658/1100-9233(2004)015[0653:MEEOPB]2.0.CO;2},
  volume       = {15},
  year         = {2004},
}