Building statistical models to analyze species distributions.

By Andrew M. Latimer, Shanshan Wu, Alan E. Gelfand, John A. Silander. Ecological Applications, 2006

385 citations recorded by the source corpus.

Subfields: Ecological Modeling, Genetics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/27116e61b3286e149712d7932c5bc08cab03c6af

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Citations in the corpus

Predicting species distributions from checklist data using site‐occupancy models (2010, background): “Site-occupancy models also form the basis for the recently developed models for inference about communities, both static (Dorazio & Royle, 2005; Gelfand et al., 2005; Dorazio et al., 2006; Latimer et al., 2006; Kéry & Royle, 2008a,b) and dynamic (Kéry et al., 2009; Dorazio et al., in press).”
Joint Species Distribution Modeling: Dimension Reduction Using Dirichlet Processes (2017, methodology): “Customarily, SDMs are fitted independently across a collection of species (Thuiller, 2003; Latimer et al., 2006; Elith and Leathwick, 2009; Chakraborty et al., 2011).”
Uses and requirements of ecological niche models and related distributional models (2006, background): “, distributions of other species in the region) and that bring in spatial considerations that may be relevant to dispersal ability and accessibility (Leathwick 1998; Latimer et al. 2006).”
Estimating patterns of reptile biodiversity in remote regions (2013, background): “Simulations have shown that BCA is one of the spatial techniques with the best performance under a variety of conditions (Latimer et al., 2006; Beale et al., 2010).”
Accounting for spatially biased sampling effort in presence‐only species distribution modelling (2015, background): “…spatially explicit details such as the complexity of irregular sampling intensity (termed ‘spatial coverage bias’ by Royle et al., 2007) (see also Gelfand et al., 2003; Arg aez et al., 2005; Latimer et al., 2006; Ward et al., 2009; Di Lorenzo et al., 2011; Hui et al., 2011; Golini, 2012).”
Predicting species distributions: a critical comparison of the most common statistical models using artificial species (2007, methodology): “, 2006), we restricted ourselves to comparing four commonly used methods (Guisan & Thuiller, 2005; Latimer et al., 2006).”
A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels (2019, background): “…to provide increased predictive performance for interpolation (predictions made for similar environmental conditions and same region as data used for model fitting), by borrowing information about species occurrences from nearby sites, which are likely linked by dispersal (Latimer et al. 2006).”
A comparison between Ensemble and MaxEnt species distribution modelling approaches for conservation: A case study with Egyptian medicinal plants (2020, neutral): “…2006), random forests ( rf ) (Evans et al., 2011; Svetnik et al., 2003), boosted regression trees ( brt ) (De'ath, 2002), and other machine learning methods such as artificial neural networks ( ANN ) (Zurada, 1992) or Bayesian heirarchical modelling (Hefley and Hooten, 2016; Latimer et al., 2006).”
Promising the future? Global change projections of species distributions (2007, background): “Guisan & Thuiller, 2005; Guisan & Zimmermann, 2000; Latimer, Wu, Gelfand, & Silander, 2006 ), nor do I wish to cover all types of organisms addressed with species distribution models (for a glimpse at the wide range of approaches, contexts and problems see Scott, Heglund, Morrison, Haufler, & Wall,”
Estimating demographic models for the range dynamics of plant species (2010, background): “…phenomenological models can vary substantially (e.g. Pearson et al., 2006), the usefulness of summarizing such alternative predictions is debated (Araújo & New, 2007), and most phenomenological models ignore errors in the observation of species distributions and abundances (Latimer et al., 2006).”
Spatial factor analysis: a new tool for estimating joint species distributions and correlations in species range (2015, methodology): “Latent spatial variables have been used previously in a several species distribution models (Latimer et al. 2006), sometimes in conjunction with measured environmental variables (Latimer et al. 2009; Shelton et al. 2014; Harris 2015) or phylogenetic relationships (Kaldhusdal et al. 2015), and are…”
Protected areas network is not adequate to protect a critically endangered East Africa Chelonian: Modelling distribution of pancake tortoise, Malacochersus tornieri under current and future climates (2020, methodology): “For modeling, we used a set of 24 environmental variables (Supplementary material Appendix 2) suggested by Latimer et al. (2006) for the Proteaceae that includes both climatic (Schulze 1997) and edaphic variables.”