Analyzing Ecological Data

Couverture
Springer, 29 août 2007 - 672 pages
'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.
 

Table des matières

Introduction
1
Data management and software
7
Advice for teachers
17
Exploration
23
Linear regression
49
Generalised linear modelling 79
78
Additive and generalised additive modelling
97
Introduction to mixed modelling
125
Crop pollination by honeybees in Argentina using additive mixed
403
Investigating the effects of rice farming on aquatic birds with mixed
416
Classification trees and radar detection of birds for North Sea wind
435
Fish stock identification through neural network analysis of parasite
449
Using generalised least squares nonmetric
463
Univariate and multivariate analysis applied on a Dutch sandy beach
485
Multivariate analyses of SouthAmerican zoobenthic species spoilt
503
Multivariate analyses of morphometric turtle data size and shape
529

Univariate tree models
143
Measures of association
163
Ordination First encounter 189
188
Correspondence analysis and canonical correspondence analysis
225
Introduction to discriminant analysis
245
Principal coordinate analysis and nonmetric multidimensional scaling
259
Time series analysis Introduction
265
Common trends and sudden changes
289
Analysis and modelling of lattice data
321
Spatially continuous data analysis and modelling
341
Univariate methods to analyse abundance of decapod larvae
373
Analysing presence and absence data for flatfish distribution in the Tagus
389
Redundancy analysis and additive modelling applied on savanna tree
547
Canonical correspondence analysis of lowland pasture vegetation in
561
Estimating common trends in Portuguese fisheries landings
575
Common trends in demersal communities on the NewfoundlandLabrador
589
A time series
600
Time series analysis of Hawaiian waterbirds
615
Spatial modelling of forest community features in the VolzhskoKamsky
633
References
649
CABRAL
651
Index
667
Droits d'auteur

Autres éditions - Tout afficher

Expressions et termes fréquents

Fréquemment cités

Page 650 - Beukema, JJ 1979. Biomass and species richness of the macrobenthic animals living on a tidal flat area in the Dutch Wadden Sea: Effects of a severe winter. Neth. J. Sea Res.
Page 651 - Bowering, WR, MJ Morgan, and WB Brodie. 1997. Changes in the population of American plaice (Hippoglossoides platessoides) off Labrador and northeastern Newfoundland: A collapsing stock with low exploitation. Fish. Res.
Page 650 - Zwanenburg, K. (2000) Impact of fishing on size composition and diversity of demersal fish communities.
Page 650 - Bray-Curtis ordination: an effective strategy for analysis of multivariate ecological data. Adv. Ecol Res., 14:1-55.

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