Spatial nonstationarity and scale-dependency in the relationship between species richness and environmental determinants for the sub-Saharan endemic avifauna

By Giles M. Foody. 2004

196 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/df89bfdb6835634193687265d46e5954abff2080

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Citations in the corpus

Species distribution models and ecological theory: A critical assessment and some possible new approaches (2007, methodology): “…with their environment, or if the social behaviour of animals changes with location, then statistical models based on local regions may provide more information and better predictions than a global model based on data from the whole study area (Osborne and Suarez-Seoane, 2002; Foody, 2004).”
Eight (and a half) deadly sins of spatial analysis (2012, background): “Much like spatial autocorrelation itself, this fundamental property of geographical data was largely ignored until recently (Foody, 2004; Bickford & Laffan, 2006; Cassemiro et al., 2007; Beale et al., 2010; Landeiro & Magnusson, 2011), and it remains very uncommon for geographical ecology papers to ”
Non‐stationarity and local approaches to modelling the distributions of wildlife (2007, methodology): “The second study (Foody, 2005) looked at bird species richness in Great Britain, rather than the presence or absence of a single species. Here we extend Foody’s (2005) analysis to compare the performance of GWR and VCM for predicting species richness against his global regression model.”
Bird species richness patterns of northern Taiwan: primary productivity, human population density, and habitat heterogeneity (2006, background): “The relationships between species richness and climate-related variables were not only found to be scale-dependent, but were also declined at coarser scales (Foody, 2004; Rahbek, 2005).”
Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression (2009, methodology): “Even so, GWR has recently been used to investigate patterns of non-stationarity in macroecological data by examining spatial variation in the regression coefficients ( Foody 2004, Wang and Tenhunen 2005, Bickford and Laffan 2006, Cassemiro et al. 2007).”
Application of a geographically‐weighted regression analysis to estimate net primary production of Chinese forest ecosystems (2005, methodology): “When the kernels are smaller than needed, they may not estimate the parameters reliably where data are scarce (Fotheringham et al., 2002), thus spatially varying kernels have also been proposed. Parameter estimation in GWR is highly dependent on the weighting function of the bandwidth of the kernel ”
Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges (2010, background): “Multiple scales of analysis would therefore increase the probability of detecting a possible correlation between species diversity and spectral variability (Foody, 2004; Stickler and Southworth, 2008).”
Local Linear Estimation of Spatially Varying Coefficient Models: An Improvement on the Geographically Weighted Regression Technique (2008, background): “Foody (2003; 2004) explored, with GWR, the spatial relationships between the normalized-difference vegetation index and rainfall, as well as the spatial relationships between species richness and environmental determinants.”
Measuring and modelling biodiversity from space (2008, background): “The spatial resolution and scale dependence of relationships noted in the literature, however, indicate that the relationships assessed may be spatially non-stationary (Foody, 2004b).”
Hot, dry and different: Australian lizard richness is unlike that of mammals, amphibians and birds (2010, methodology): “We then used geographically weighted regressions (GWRs; see e.g. Fotheringham et al., 2002; Foody, 2004; Cassemiro et al., 2007) of lizard richness on the richness of the three other classes in turn to describe geographical variation in this relationship amongst taxa at local scales.”