Environmental data sets matter in ecological niche modelling: an example with Solenopsis invicta and Solenopsis richteri.

By A. Townsend Peterson, Y. Nakazawa. 2007

392 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Genetics

View Paper: https://www.semanticscholar.org/paper/aa1036ef650c60b8faa56e89e1f5f97532cc58ff

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

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Citations in the corpus

Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot (2010, background): “2008), the nature of the environmental data set (Parra et al. 2004; Peterson and Nakazawa 2008), species traits (Poyry et al.”
Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models (2010, background): “It has been shown that the choice of environmental variables can have a significant effect on model accuracy (Parolo et al., 2008; Peterson and Nakazawa, 2008).”
Invasive and flexible: niche shift in the drosophilid Zaprionus indianus (Insecta, Diptera) (2010, background): “…that the variables used in modeling processes usually reflect only particular components of a species’ niche (Soberon 2007) and that methodological issues and idiosyncratic characteristics of niche models must also be ruled out (Araujo and Guisan 2006; Peterson 2007; Peterson and Nakazawa 2008).”
Applications and future challenges in marine species distribution modeling (2011, background): “, 2008) and selection of appropriate predictors (Peterson and Nakazawa, 2008),”
The importance of biotic interactions in species distribution models: a test of the Eltonian noise hypothesis using parrots (2014, methodology): “them from the model based on their biological relevance. We then built another correlation matrix and repeated the procedure until all variables kept in the model presented correlations lower than 0.9; a similar procedure was described in Rissler & Apodaca (2007). We used a total of nine abiotic env”
Guidance on quantitative pest risk assessment (2018, background): “Such models take into account data from areas where the organism is present, including the native range (Fitzpatrick et al., 2007; Peterson and Nakazawa, 2008; Jarnevich et al., 2015; Kumar et al., 2015).”
Differences in spatial predictions among species distribution modeling methods vary with species traits and environmental predictors (2009, positive): “Peterson and Nakazawa (2008) showed that, when using one model type (GARP), spatial predictions of native and introduced distributions of fire ants were sensitive to the environmental data sets used to develop the models.”
Predicting distributions of invasive species (2013, background): “If you are unfamiliar with correlative models, reading the Boxes should give enough background for the following sections.”
ENVIREM: An expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling (2016, background): “Identifying better sets of predictor variables for certain species could, among other things, potentially alter projections of species’ invasiveness for particular regions (Peterson and Nakazawa 2008), alter our understanding of potentially suitable habitat for species introductions (Martínez-Meyer ”