Evaluating alternative data sets for ecological niche models of birds in the Andes

By J. L. Parra, C. Graham, J. Freile. 2004

124 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/6758df4b691b15ab25d60bebd53eb4ed79bb62c7

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS) (2006, background): “The most popular measure for the accuracy of presence‐absence predictions is Cohen’s kappa (Shao & Halpin 1995; Manel, Williams & Ormerod 2001; Loiselle et al . 2003; Petit et al . 2003; Berg, Gardenfors & von Proschwitz 2004; Parra, Graham & Freile 2004; Pearson, Dawson & Liu 2004; Rouget et al .”
Model‐based uncertainty in species range prediction (2006, methodology): “The AUC and k have been widely applied to assess the predictive performance of species range models (e.g. Loiselle et al., 2003; Thuiller, 2003; Brotons et al., 2004; Huntley et al., 2004; Parra et al., 2004).”
Determinants of local spider (Araneidae and Thomisidae) species richness on a regional scale: climate and altitude vs. habitat structure (2007, methodology): “…et al. , 2005 ); thus, it is a widely used factor in studies of species-richness patterns and in predictive modelling (i.e. Egbert et al. , 2002; Suárez-Seoane et al. , 2002; Bailey et al. , 2004; Foody, 2004; Parra et al. , 2004; Roura-Pascual et al. , 2004; Ruggiero & Kitzberger, 2004 ).”
Climate Change and Biodiversity: Some Considerations in Forecasting Shifts in Species' Potential Distributions (2005, background): “In general, climatic variables (e.g., maximum and minimum temperatures, precipitation) are particularly useful, as they coincide with physiological tolerances (Parra et al. 2004; Peterson and Cohoon 1999).”
Species distribution modelling for the people: unclassified landsat TM imagery predicts bird occurrence at fine resolutions (2013, methodology): “Most studies that have used reflectance data have used derived vegetation indices (Baret & Guyot, 1991), NDVI (Gottschalk et al., 2005; Gillespie et al., 2008) or have been focused on a single species.”
Predicting the spatial distribution of an invasive plant species (Eupatorium adenophorum) in China (2007, background): “These models can then be projected onto other landscapes to predict the geographic distribution of species (Lim et al. 2002; Parra et al. 2004).”
Predicting species distributions from herbarium collections: does climate bias in collection sampling influence model outcomes? (2007, background): “Elith & Burgmann, 2002; Feria & Peterson, 2002; Joseph & Stockwell, 2002; Parra et al., 2004; Arau ´ jo & Guisan, 2006).”
Comparison of six correlative models in predictive vegetation mapping on a local scale (2012, methodology): “Profile techniques use only presence locality records; e.g., BIOCLIM (Nix 1986; Parra et al. 2004), Gower similarity or DOMAIN (Carpenter et al. 1993; Segurado and Araujo 2004), GARP (Peterson 2001; Anderson 2003), Ecological niche factor analysis or BIOMAPPER (Hirzel et al. 2002) and MAXENT…”
Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot (2010, background): “…Hernandez et al. 2006), spatial scale (Lassueur et al. 2006; Guisan et al. 2007a; Trivedi et al. 2008), the nature of the environmental data set (Parra et al. 2004; Peterson and Nakazawa 2008), species traits (Poyry et al. 2008), biotic interactions (Araújo and Luoto 2007; Heikkinen et al.…”
Predicting species distributions across the Amazonian and Andean regions using remote sensing data (2008, background): “NDVI, or similar vegetation indices, are among the few satellite variables that have been used extensively in ecological niche modelling (e.g. Fuentes et al., 2001; Osborne et al., 2001; Luoto et al., 2002; Zinner et al., 2002; Parra et al., 2004; Roura-Pascual et al., 2006).”
Exploring the effects of quantity and location of pseudo-absences and sampling biases on the performance of distribution models with limited point occurrence data (2011, background): “…in species distribution models results from the lack of relevant explanatory variables such as biotic interactions (Austin & Meyers 1996; Fielding & Bell 1997; Parra et al. 2004; Peterson et al. 1999; Raxworthy et al. 2003), or the role of spatial autocorrelation (Segurado et al. 2006).”
Habitat suitability modelling of an invasive plant with advanced remote sensing data (2009, unknown): “…et al., 2007; Prates-Clark et al., 2008), tree height (Greco et al., 2002), vegetation phenology (e.g. Cablk et al., 2002; McPherson et al., 2004; Parra et al., 2004; Roura-Pascual et al., 2006; Peterson & Nakazawa, 2008; Prates-Clark et al., 2008; Wiegand et al., 2008), biomass (Edwards et…”
The importance of biotic interactions in species distribution models: a test of the Eltonian noise hypothesis using parrots (2014, background): “…(Lassueur et al., 2006; Guisan et al., 2007; Trivedi et al., 2008) and the nature of the environmental data set Journal of Biogeography 41, 513–523 ª 2013 John Wiley & Sons Ltd 519 (Parra et al., 2004; Peterson & Nakazawa, 2008) have been identified as influences on the outcome of models produced.”