Spatial autocorrelation and autoregressive models in ecology

By Jeremy W. Lichstein, Theodore Simons, S. Shriner, K. Franzreb. 2002

947 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/edbb2e4590713b1f452c417306783fd1ce9c2d18

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Conservation of newt guilds in an agricultural landscape of Belgium: the importance of aquatic and terrestrial habitats (2008, methodology): “Moran I was used to evaluate the spatial autocorrelation of residuals of GLMs following the Monte Carlo procedure described by Lichstein et al. (2002).”
The flora of German cities is naturally species rich (2004, background): “Rosenzweig, 1995) and the influence of spatial autocorrelation on statistical analyses (e.g. Fortin et al., 1989; Lichstein et al., 2002).”
Landscape-scale spatial distribution of spruce budworm defoliation in relation to bioclimatic conditions (2005, methodology): “The statistical significance of the coefficient of spatial autocorrelation was calculated by using a permutation test (Lichstein et al. 2002) with 999 permutations.”
Can niche-based distribution models outperform spatial interpolation? (2007, background): “…been explored [e.g. spatially explicit presence/absence models (Pereira & Itami, 1991; Augustin et al. , 1996), spatially explicit abundance models (Lichstein et al. , 2002) and community-based models (Elith et al. , 2006)], presence/absence-based habitat models still dominate current practice.”
Factors and mechanisms explaining spatial heterogeneity: a review of methods for insect populations (2011, background): “They are well suited for modelling the abundance of species whose distributions are controlled by a combination of exogenous factors and biological properties (Lichstein et al. 2002).”
Incorporating spatial autocorrelation may invert observed patterns (2006, background): “Lennon (2000) raised this topic again and pointed out that spatial autocorrelation can alter parameter estimates of linear models by influencing the variance–covariance matrix (Anselin, 1988; Anselin & Bera, 1998).”
Using presence‐only modelling to predict Asian elephant habitat use in a tropical forest landscape: implications for conservation (2010, background): “Spatial autocorrelation, resulting from spatial dependence between elephant presence observations, could potentially increase the risk of type I errors (i.e. falsely rejecting a null hypothesis; Lichstein et al., 2002; Dormann et al., 2007).”
Species richness and community composition of songbirds in a tropical forest‐agricultural landscape (2004, methodology): “The landscape context of avian sampling sites may be an important influence on local community structure (Lichstein et al., 2002; Pearman, 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…”
On the relationship between conditional (CAR) and simultaneous (SAR) autoregressive models (2017, background): “, Clayton and Kaldor, 1987; Lawson, 2013), agriculture (Cullis and Gleeson, 1991; Besag and Higdon, 1999), econometrics (Anselin, 1988; LeSage and Pace, 2009), ecology (Lichstein et al., 2002; Kissling and Carl, 2008), and image analysis (Besag, 1986; Li, 2009).”