Multivariate Analysis of Ecological Data
By J. Lepš, P. Šmilauer. 2006
1,986 citations recorded by the source corpus.
Subfields: Environmental Chemistry, Nature and Landscape Conservation, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/0b5f2898d7d6dc83b7caabdc0ecfca40699691b2
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Environmental Chemistry
In Nature and Landscape Conservation
- J. Heino
- J. Soininen
- Kathrin Kiehl
- C. Murphy
- R. Pennington
- A. Oliveira-Filho
- J. Heilmann‐Clausen
- M. Christensen
In Statistics and Probability
- A. Oliveira-Filho
- J. Soininen
- L. Marini
- R. Pennington
- Kathrin Kiehl
- J. Heino
- D. R. Robertson
- Kane R. Keller
Citations in the corpus
- Beetle Responses to Habitat Fragmentation Depend on Ecological Traits, Habitat Condition, and Remnant Size (2005, methodology): “In PC-Ord (McCune & Mefford 1999), we produced a Bray and Curtis (1957) distance matrix that included all beetle species.”
- Species composition and structure of regenerated and remnant forest patches within an urban landscape (2002, methodology): “A Ward clustering technique, based on relative Euclidean distances (McCune and Mefford, 1999), used species importance values to identify community types.”
- Communities of wood‐inhabiting bryophytes and fungi on dead beech logs in Europe – reflecting substrate quality or shaped by climate and forest conditions? (2014, methodology): “The relative importance of the three groups of explanatory variables (substrate, climate and soil and forest condition; Table 2) on species composition in both organism groups were analysed by variation partitioning (Legendre & Legendre, 1998) using canonical correspondence analysis (CCA; Lep s & Sm”
- Dissecting a biodiversity hotspot: The importance of environmentally marginal habitats in the Atlantic Forest Domain of South America (2017, background): “…exclusion of 300 singletons (species found at a single site), as they commonly increase the noise in most analyses without contributing information (Lepš & Šmilauer, 2003); (2) the Hellinger transformation of the binary presence/absence data (Legendre & Gallagher, 2001), which reduces the effect…”