By Alain F. Zuur, Elena N. Ieno, Graham M. Smith
This booklet offers a pragmatic creation to analysing ecological info utilizing genuine information units accumulated as a part of postgraduate ecological stories or study projects.
The first a part of the ebook supplies a mostly non-mathematical creation to facts exploration, univariate equipment (including GAM and combined modelling techniques), multivariate research, time sequence research (e.g. universal developments) and spatial statistics. the second one half presents 17 case stories, mostly written including biologists who attended classes given by means of the 1st authors. The case experiences comprise subject matters starting from terrestrial ecology to marine biology. The case reports can be utilized as a template in your personal information research; simply try and discover a case research that fits your individual ecological questions and knowledge constitution, and use this as start line for you personal research. information from all case experiences can be found from www.highstat.com. counsel on software program is supplied in bankruptcy 2.
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Additional resources for Analysing Ecological Data (Statistics for Biology and Health)
Data exploration Linear regression Partial linear regression GLM GAM Mixed modelling GLS Tree models Neural networks Measures of association PCA RDA Partial RDA CA CCA Partial CCA Discriminant analysis NMDS Geometric morphometric analysis De-seasonalising Repeated lowess smoothing MAFA DFA Chronological clustering Spatial statistics SAR SMA Variograms Surface variogram K ^ S Brodgar NR R R Genstat X X R R R R R R NR X X X X X p X N N N N N N N N X * simple X X X * compl N R N N N R R R R CANOCO PRIMER X X R X X PC-Ord X X "simple X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X "compl X X *compl * compl *compl *compl "compl * compl *compl *compl X X X X X X X X X X X X X X X 18 • • • • 3 Advice for teachers able.
In the last multivariate chapter, Mexican plant data are analysed using canonical correspondence analysis. The role of an invasive species is investigated. Time series case study chapters In the first time series case study, Portuguese fisheries landing trends are analysed. The main aim of this chapter is to estimate common trends using DFA and MAFA. In another time series case study chapter, groundfish research survey data from the northwest Atlantic are analysed and the effects of time lags are explored using MAFA and DFA.
We suggest starting the students on an exercise with only one explanatory variable so that they can see the model fit in the form of a logistic curve. Generalised additive modelling (1 day). The second part of the GAM chapter is slightly more technical than the first part. If the audience consists of biologists, we suggest explaining only the underlying concepts of splines, degrees of freedom and cross-validation. We chose to present the more technical aspects of GAM in this book simply because it is difficult to find it in textbooks for biologists.