Multivariate Statistics for Wildlife and Ecology Research

By K. McGarigal, S. Stafford, Samuel A. Cushman. Springer: New York, 2000

1,365 citations recorded by the source corpus.

Subfields: Ecology

View Paper: https://www.semanticscholar.org/paper/83afcebe6cfcf0d8638655452f1fff7560c78282

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In Ecology

Citations in the corpus

A floristic analysis of the lowland dipterocarp forests of Borneo (2003, methodology): “The locations were clustered using the UPGMA algorithm as the two-dimensional representation of the locations produced by this analysis (dendrogram) retains the true distribution of the locations in multi-dimensional space in an acceptable manner, especially in comparison with other cluster algorith”
Factors affecting bee communities in forest openings and adjacent mature forest (2017, methodology): “To visualize differences in community composition between opening and forest habitats, we ordinated opening and forest samples using nonmetric multidimensional scaling (NMDS; McGarigal et al., 2000).”
Patterns of gammaridean amphipod abundance and species composition associated with dominant subtidal macroalgae from the western Antarctic Peninsula (2007, methodology): “The descriptive algal morphometrics data matrices collected for each target macroalgal species were log(x + 1) transformed to decrease the influence of outliers and then examined using cluster analysis (Romesburg 1984; McGarigal et al. 2000).”
Discriminant function analysis in marine ecology: some oversights and their solutions (2007, neutral): “This issue necessitates some sort of chance-corrected estimate of the null expectation for reclassification success (McGarigal et al. 2000).”
Prominent role of invasive species in avian biodiversity loss (2009, methodology): “PCA is an indirect ordination analysis that recombines the major linear patterns of covariation within a multivariate dataset (in this case, drivers of extinction) into a few axes, providing a dimensionally reduced summary of the original data (McGarigal et al., 2000).”
Crossing the line: migratory and homing behaviors of Atlantic bluefin tuna (2014, methodology): “…discriminant function analysis (QDFA) was used to evaluate the classification accuracy of yearlings to eastern and western nurseries because this analysis does not have the homogeneity of covariance matrices assumption and is robust to moderate deviations from normality (McGarigal et al. 2000).”
Hierarchical, Multi-scale decomposition of species-environment relationships (2002, methodology): “We used principal component analysis (PCA) and the latent root criterion to reduce the floristics data set to 10 uncorrelated components that accounted for most of the total floristics variance (McGarigal et al. 2000).”
Environmental and phylogenetic correlates of Eulemur behavior and ecology (Primates: Lemuridae) (2006, methodology): “First, we examined the overall similarity among the populations by performing hierarchical cluster analyses using the unweighted pair group method with arithmetic mean for the ENVIRONMENT, ECOLOGY, and SOC ORG datasets (McGarigal et al. 2000).”
Acoustic analysis of cattle ( Bos taurus ) mother–offspring contact calls from a source–filter theory perspective (2015, methodology): “The expected level of correct assignment was averaged from DFAs performed on 1000 randomised permutations of the data set (McGarigal et al., 2000).”
IMPACT OF NEST‐SITE SELECTION ON NEST SUCCESS AND NEST TEMPERATURE IN NATURAL AND DISTURBED HABITATS (2002, methodology): “We used the brokenstick model, which compares eigenvalues from the data to random ones, to determine the number of principal components to use in analyses (Jackson 1993, McGarigal et al. 2000).”
Timing of seasonal migration in mule deer: effects of climate, plant phenology, and life‐history characteristics (2011, methodology): “We used principal component analysis (PCA) of local weather data, based on the variance–covariance matrix (McGarigal et al. 2000), to reduce the dimensionality of those variables and derive independent composite variables that described daily weather.”
Invasive alien plants in China: diversity and ecological insights (2008, methodology): “Index of similarity (S) of these regions was calculated according to Sørensen (McGarigal 2000) using species richness in these regions as”
Physiology of individual late-run Fraser River sockeye salmon (Oncorhynchus nerka) sampled in the ocean correlates with fate during spawning migration (2006, methodology): “Statistical analysis Multivariate analysis of variance (MANOVA) on log10transformed data (McGarigal et al. 2000) revealed that stock-specific differences were only apparent for energetic and size information, so we pooled data from both W–H and Adams for all other biological characteristics.”
Using Surrogate Species and Groups for Conservation Planning and Management (2008, methodology): “Ever more sophisticated methods have been developed to meet this challenge (McGarigal et al. 2000).”
Individual dietary specialization and dive behaviour in the California sea otter: Using archival time–depth data to detect alternative foraging strategies (2007, methodology): “…for each pair of individuals, Ward’s minimum variance method was used to link similar points, and the number of significant clusters was determined by graphical examination of the resulting dendrogram and scree plot of inter-cluster distance vs. number of clusters (McGarigal et al., 2000).”