Analysis of determinants of mammalian species richness in South America using spatial autoregressive models

By M. Tognelli, D. Kelt. 2004

173 citations recorded by the source corpus.

Subfields: Ecological Modeling, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/1edb139e5bcf55a5b7711fe60773dbbfcbade188

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In Ecological Modeling

In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

Red herrings revisited: spatial autocorrelation and parameter estimation in geographical ecology (2007, methodology): “1), we also modelled the relationship between species richness and the environmental predictors using a spatially explicit simultaneous autoregressive (SAR) model (Cressie 1993, Schabenberg and Gotway 2005, Tognelli and Kelt 2004, Kissling and Carl 2007).”
Basin-wide variations in foliar properties of Amazonian forest: phylogeny, soils and climate. (2009, background): “Previous spatial analyses of ecological datasets have revealed that in some cases small neighbourhood distances (first-order) SAR models are able to remove the spatial autocorrelation signal (Jetz and Rahbek, 2002), while other studies suggest that larger neighbourhood (higher-order) SARs should be ”
Effects of incorporating spatial autocorrelation into the analysis of species distribution data (2007, background): “(1996); 19, Tognelli and Kelt (2004); 20, Zhang et al .”
The riverscape of Western Amazonia – a quantitative approach to the fluvial biogeography of the region (2007, methodology): “The same 1-degree grid system is often used in species-level studies of the region (e.g. Nelson et al., 1990; Rahbek & Graves, 2001; Tognelli & Kelt, 2004).”
Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression (2009, methodology): “The dominant practice is to use multiple regression and rank the standardized partial regression coefficients (hereafter standardized coefficients; Sokal and Rohlf 1995) or associated t-values of coefficients of explanatory variables (Hawkins et al. 2003, Tognelli and Kelt 2004, Kissling et al. 20”
The significance of geographic range size for spatial diversity patterns in Neotropical palms (2006, methodology): “…for vertebrate groups like birds and mammals (Kaufman and Willig 1998, Rahbek and Graves 2001, Willig et al. 2003, Ruggiero and Kitzberger 2004, Tognelli and Kelt 2004), or use other data from plots (ter Steege et al. 2003) or other floristic inventories (Barthlott et al. 1996, Kier et al.…”
Bird species richness patterns of northern Taiwan: primary productivity, human population density, and habitat heterogeneity (2006, background): “Several recent studies have demonstrated the importance of using statistical techniques that account for spatial autocorrelation on some level when assessing species distributions (Lichstein et al ., 2002; Dark, 2004; Tognelli & Kelt, 2004).”
Spatial autocorrelation and the selection of simultaneous autoregressive models (2007, background): “The interpretation of parameter estimates and model coefficients from spatial models is now among the most important issues in geographical ecology (Lennon, 2000; Diniz-Filho et al., 2003; Tognelli & Kelt, 2004; Dormann, 2007; Kühn, 2007).”
Accounting for multi‐scale spatial autocorrelation improves performance of invasive species distribution modelling (iSDM) (2012, result): “…Bini et al. (2009) were unable to identify reliable predictors of coefficient shifts in spatial regression, our results corroborate the findings of other studies (e.g. Lichstein et al., 2002; Tognelli & Kelt, 2004), suggesting that ignoring SAC leads to overestimation of environmental effects.”
Promising the future? Global change projections of species distributions (2007, unknown): “There are some brilliant and insightful studies on species distributions (e.g. Bonn & Schröder, 2001; Graf, Bollmann, Suter, & Bugmann, 2005; Lichstein, Simons, Shriner, & Franzreb, 2002; Özesmi & Özesmi, 1999; Schadt et al., 2002; Tognelli & Kelt, 2004).”
Macro‐scale bird species richness patterns of the East Asian mainland and islands: energy, area and isolation (2006, background): “The CAR models assume that the response at each quadrat is a function not only of the explanatory variables but also of the values of the response variable in neighbouring quadrats (Lichstein et al., 2002; Tognelli & Kelt, 2004).”