EFFECTS OF SPATIAL STRUCTURES ON THE RESULTS OF FIELD EXPERIMENTS
By Pierre Legendre, M. Dale, Marie-Josée Fortin, P. Casgrain, J. Gurevitch. 2004
108 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/cfa094147d8abcadd1c4f4365f9ba26af3bc0b5a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
In Environmental Engineering
- A. Fajardo
- M. D. Schwartz
- Joshua J. Lawler
- Pedro Segurado
- W. Kunin
- Miguel B. Araújo
- Eliot J. B. McIntire
Citations in the corpus
- Consequences of spatial autocorrelation for niche‐based models (2006, background): “including a priori procedures at the level of sampling design (Harrison 1997; Legendre et al. 2002; Legendre et al. 2004), modifications at the level of model adjustment (Keitt et al.”
- Cross-scale Correlations and the Design and Analysis of Avian Habitat Selection Studies (2006, background): “It may also be possible to apply statistical approaches designed to measure and control for spatial autocorrelation (Legendre et al. 2004).”
- Why sampling scheme matters: the effect of sampling scheme on landscape genetic results (2009, background): “…other fields of the natural sciences (e.g., ecology, geology) have focused intensively on study design and the effect of spatial structure in biasing results (Sokal et al. 1998; Legendre et al. 2002, 2004); we believe the field of molecular ecology has paid less attention to these sampling issues.”
- Beyond description: the active and effective way to infer processes from spatial patterns. (2009, background): “…autocorrelated because of contagious biotic processes (e.g., dispersal, competition), historical factors (e.g., disturbance; Leduc et al. 1992), or spatially structured environmental predictors (e.g., soil carbon; Haining 1993, Legendre et al. 2004, Bellier et al. 2007; MacKenzie et al. 2008).”
- Restoration treatment effects on the understory of ponderosa pine/Douglas-fir forests in western Montana, USA (2006, methodology): “This experiment employed a randomized block design with nested sampling, a design shown to maximize statistical rigor (Legendre et al., 2004).”