A Primer of Ecological Statistics

By Nicholas Gotelli. 2005

154 citations recorded by the source corpus.

Subfields: Environmental Chemistry, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8d8201d8ab184d5e17a847faf276f300cfcc2ae9

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In Environmental Chemistry

In Statistics and Probability

Citations in the corpus

Behavioral evolution in the major worker subcaste of twig-nesting Pheidole (Hymenoptera: Formicidae): does morphological specialization influence task plasticity? (2009, unknown): “Measurements were standardized by conversion to Z scores prior to PCA analysis of the unrotated correlation matrix (Gotelli and Ellison 2004).”
Preventing horticultural introductions of invasive plants: potential efficacy of voluntary initiatives (2007, unknown): “…hypothesis that respondents assigned a different responsibility level to horticultural groups (retailers, wholesalers, and growers) than to non-horticultural groups (policy makers, scientists, government agencies, and consumers) we performed an a priori contrast (Gotelli and Ellison 2004, p 339).”
Abundance‐Based Similarity Indices and Their Estimation When There Are Unseen Species in Samples (2006, methodology): “The Bray–Curtis similarity index is widely used to generate distance matrices in vegetation ordination studies (Gotelli and Ellison, 2004).”
Climate change, genetic markers and species distribution modelling (2015, unknown): “Because SDMs are inherently a regression-based approach, there is, in theory, no advantage to replicate sampling at a single location, particularly as there is an inevitable trade-off with sampling among locations (Gotelli & Ellison, 2012).”
Introduced deer reduce native plant cover and facilitate invasion of non-native tree species: evidence for invasional meltdown (2010, unknown): “NMDS is a robust ordination procedure that produces a plot in which different replicates are placed far apart in the ordination space, while similar replicates are placed close together (Gotelli and Ellison 2004).”
mvabund– an R package for model‐based analysis of multivariate abundance data (2012, background): “Independence of sites, as always, is an important assumption in multivariate analysis which can only be ensured through an appropriate study design (Gotelli & Ellison 2004).”