%0 Journal Article
%A Lupi, C.
%A Larocque, G.
%A DesRochers, A.
%A Labrecque, M.
%A Mosseler, A.
%A Major, J.
%A Beaulieu, J.
%A Tremblay, M.F.
%A Gordon, A.M.
%A Thomas, B.R.
%A Vezina, A.
%A Bouafif, H.
%A Cormier, D.
%A Sidders, D.
%A Krygier, R.
%A Thevathasan, N.
%A Riopel, M.
%A Ferland-Raymond, B.
%T Evaluating sampling designs and deriving biomass equations for young plantations of poplar and willow clones
%B Biomass and Bioenergy
%D 2015
%V 83
%P 196-205
%Z cited By 0; doi=(10.1016/j.biombioe.2015.09.019)
%X Short-rotation intensive culture (SRIC) for bioenergy production is
at its pre-commercial stage in Canada. To be economically viable,
these types of plantations need an accurate examination of actual
yields, which requires precise and efficient estimation methods (i.e.,
specific allometric equations and sampling methods). At six SRIC
plantations from three Canadian provinces (Quebec, Ontario and Alberta),
6 willow and 10 poplar clones were sampled and clone allometric equations
were developed to estimate plant biomass. A stem selection approach
was successfully used to develop plant allometric equations, reducing
the number of stems to be measured by up to 81% in coppiced plantations
relative to traditional stem equations. Clone-specific equations
were more accurate than equations for groups of clones, but the difference
in terms of RMSE% was generally small (less than 5%). Using extensive
measurements of all the plants inside a plantation and a simulation
approach, we also compared five sampling methods (simple random sampling,
stratified sampling, systematic sampling, random and systematic cluster
sampling) to estimate total biomass inside the plantation. Simple
random sampling and stratified random sampling were the most efficient
methods (i.e., increased precision for equal sample size) for the
estimation of average plant biomass, survival and total plantation
biomass. Stratified random sampling (based on the position inside
the plantation) made it possible to reduce the sample size as compared
to simple random sampling, but only at higher levels of precision
(e.g., 25 less plants at 5% precision). Applications of sampling
using remote sensing techniques and GIS are briefly discussed. ©
2015 Published by Elsevier Ltd.
Scopus
%K Cloning; Forestry; Remote sensing, Allometric equations; Coppice SRIC;
Multi-stemmed plants; Random sampling; Stratified sampling, Biomass,
Salix
%U http://www.scopus.com/inward/record.url?eid=2-s2.0-84943655143&partnerID=40&md5=f7c740c1d89a9f5901a6f0946de8f775
%F LupiLarocqueDesRochersEtAl2015
%3 BibTeX type = ARTICLE