The consequences of spatial structure for the design and analysis of ecological field surveys

By P. Legendre, M. Dale, Marie-Josée Fortin, J. Gurevitch, Michael E. Hohn, Donald E. Myers. 2002

708 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/1cee7309cbc1f5353c41f4d77319e360b52809fb

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Citations in the corpus

Spatial fisheries ecology: Recent progress and future prospects (2008, background): “Statistical models that do not consider autocorrelation may result in rejections of a true null hypothesis (i.e., Type I error) more often than the nominal tolerance level (Legendre et al., 2002).”
Statistical solutions for error and bias in global citizen science datasets (2014, neutral): “to one another than those that are more distant (Legendre et al., 2002).”
Empirical estimate of the reliability of the use of the Point-Centred Quarter Method (PCQM) : solutions to ambiguous field situations and description of the PCQM+ protocol (2006, background): “reliability of the analysis of ecological field surveys (Legendre et al., 2002).”
Relationships between forest cover and fish diversity in the Amazon River floodplain (2018, methodology): “We used this approach to minimize spatial autocorrelation that might inflate type I error (false positive result; see Legendre et al., 2002).”
Integrating the statistical analysis of spatial data in ecology (2002, neutral): “Quantitative examination of spatially explicit data in ecology is broadly categorized as ‘‘spatial analysis’’ (e.g., Legendre and Fortin 1989 ).”
Consequences of spatial autocorrelation for niche‐based models (2006, methodology): “…1997; Legendre et al. 2002; Legendre et al. 2004), modifications at the level of model adjustment (Keitt et al. 2002; Lichstein et al. 2002) and a posteriori procedures, such as the use of correction factors, to improve statistical accuracy of models (Dutilleul 1993; Legendre et al. 2002).”
Beyond description: the active and effective way to infer processes from spatial patterns. (2009, background): “Ecological understanding of spatial structures Both physical and biological variables in nature display spatial patterns (Levin 1992, Legendre 1993, Dale 1999, Legendre et al. 2002, Tuda 2007).”
Extensive hydrochory uncouples spatiotemporal patterns of seedfall and seedling recruitment in a ‘bird‐dispersed’ riparian tree (2004, background): “Houle 1998; Nathan et al . 2000; Tomita et al . 2002) and statistical non-independence then needs to be taken into account ( Legendre et al . 2002 ).”
Application of a geographically‐weighted regression analysis to estimate net primary production of Chinese forest ecosystems (2005, background): “The importance of considering spatial autocorrelation in geographical ecology has been addressed by a number of recent papers (e.g. Diniz-Filho et al., 2003; Legendre et al., 2002; Lichstein et al., 2002).”
Spatial autocorrelation analysis in plant population: An overview (2015, background): “The second and third points are not always referred to as spatial autocorrelation, but rather spatial dependency (Legendre et al., 2002).”
Spatial autocorrelation and the selection of simultaneous autoregressive models (2007, background): “Our study complements previous studies on species distribution and spatial autocorrelation (e.g. Keitt et al., 2002; Legendre et al., 2002; Lichstein et al., 2002; Diniz-Filho et al., 2003; Tognelli & Kelt, 2004; Dormann, 2007; Kühn, 2007) and is thus a further step towards a better understanding of”
Water–energy balance and the geographic pattern of species richness of western Palearctic butterflies (2003, background): “Legendre et al. (2002) provide an explanation of the difference between spatial autocorrelation and spatial dependence and its relevance to interpreting ecological data.”