Alain Zuur & Elena N. Ieno 
Analyzing Ecological Data 

‚Which test should I apply?‘ During the many years of working with ecologists, biologists and other environmental scientists, this is probably the question that the authors of this book hear the most often. The answer is always the same and along the lines of ‚What are your underlying questions?‘, ‚What do you want to show?‘. The answers to these questions provide the starting point for a detailed discussion on the ecological background and purpose of the study. This then gives the basis for deciding on the most appropriate analytical approach. Therefore, a better start­ ing point for an ecologist is to avoid the phrase ‚test‘ and think in terms of ‚analy­ sis‘. A test refers to something simple and unified that gives a clear answer in the form of a p-value: something rarely appropriate for ecological data. In practice, one has to apply a data exploration, check assumptions, validate the models, per­ haps apply a series of methods, and most importantly, interpret the results in terms of the underlying ecology and the ecological questions being investigated. Ecology is a quantitative science trying to answer difficult questions about the complex world we live in. Most ecologists are aware of these complexities, but few are fully equipped with the statistical sophistication and understanding to deal with them.

Inhaltsverzeichnis

Data management and software.- Advice for teachers.- Exploration.- Linear regression.- Generalised linear modelling.- Additive and generalised additive modelling.- to mixed modelling.- Univariate tree models.- Measures of association.- Ordination — First encounter.- Principal component analysis and redundancy analysis.- Correspondence analysis and canonical correspondence analysis.- to discriminant analysis.- Principal coordinate analysis and non-metric multidimensional scaling.- Time series analysis — Introduction.- Common trends and sudden changes.- Analysis and modelling of lattice data.- Spatially continuous data analysis and modelling.- Univariate methods to analyse abundance of decapod larvae.- Analysing presence and absence data for flatfish distribution in the Tagus estuary, Portugal.- Crop pollination by honeybees in Argentina using additive mixed modelling.- Investigating the effects of rice farming on aquatic birds with mixed modelling.- Classification trees and radar detection of birds for North Sea wind farms.- Fish stock identification through neural network analysis of parasite fauna.- Monitoring for change: Using generalised least squares, non-metric multidimensional scaling, and the Mantel test on western Montana grasslands.- Univariate and multivariate analysis applied on a Dutch sandy beach community.- Multivariate analyses of South-American zoobenthic species — spoilt for choice.- Principal component analysis applied to harbour porpoise fatty acid data.- Multivariate analyses of morphometric turtle data — size and shape.- Redundancy analysis and additive modelling applied on savanna tree data.- Canonical correspondence analysis of lowland pasture vegetation in the humid tropics of Mexico.- Estimating common trends in Portuguese fisherieslandings.- Common trends in demersal communities on the Newfoundland-Labrador Shelf.- Sea level change and salt marshes in the Wadden Sea: A time series analysis.- Time series analysis of Hawaiian waterbirds.- Spatial modelling of forest community features in the Volzhsko-Kamsky reserve.

Über den Autor

Grad students, researchers