000 02258nam a22003498i 4500
001 CR9780511615146
003 UkCbUP
005 20200124160252.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 090914s2003||||enk o ||1 0|eng|d
020 _a9780511615146 (ebook)
020 _z9780521814096 (hardback)
020 _z9780521891080 (paperback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aQH541.15.S72
_bL47 2003
082 0 0 _a577/.07/27
_221
100 1 _aLepš, Jan,
_d1953-
_eauthor.
245 1 0 _aMultivariate analysis of ecological data using CANOCO /
_cJan Leps̆ & Petr S̆milauer.
264 1 _aCambridge :
_bCambridge University Press,
_c2003.
300 _a1 online resource (xi, 269 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520 _aThis book is primarily written for ecologists needing to analyse data resulting from field observations and experiments. It will be particularly useful for students and researchers dealing with complex ecological problems, such as the variation of biotic communities with environmental conditions or the response of biotic communities to experimental manipulation. Following a simple introduction to ordination methods, the text focuses on constrained ordination methods (RDA, CCA) and the use of permutation tests on statistical hypotheses of multivariate data. An overview of classification methods, or modern regression methods (GLM, GAM, loess), is provided and guidance on the correct interpretation of ordination diagrams is given. Seven case studies of varying difficulty help to illustrate the suggested analytical methods, using the Canoco for Windows software. The case studies utilise both the descriptive and manipulative approaches, and they are supported by data sets and project files available from the book website.
650 0 _aEcology
_xStatistical methods.
650 0 _aMultivariate analysis.
700 1 _aŠmilauer, Petr,
_d1967-
_eauthor.
776 0 8 _iPrint version:
_z9780521814096
856 4 0 _uhttps://doi.org/10.1017/CBO9780511615146
999 _c519633
_d519631