Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes

By Mariya Shcheglovitova, R. P. Anderson. 2013

575 citations recorded by the source corpus.

Subfields: Ecological Modeling, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/89d15e9cb51c92c5047d449cb9d918135bc8b8ed

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

In Molecular Biology

Citations in the corpus

Optimizing ensembles of small models for predicting the distribution of species with few occurrences (2018, methodology): “P.s, we used a betamultiplier value of 2.5 to reduce the complexity of calibrated models, as recommended for modelling rare species (i.e., optimal values set between 1.5 and 4; Elith, Kearney, & Phillips, 2010; Moreno- Amat et al., 2015; Muscarella et al., 2014; Shcheglovitova & Anderson, 2013).”
Spatial filtering to reduce sampling bias can improve the performance of ecological niche models (2014, background): “In addition, overfit models have omision rates higher than theoretical expectations (Radosavljevic and nderson, 2013; Shcheglovitova and Anderson, 2013).”
ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models (2014, methodology): “ENMeval provides the mean and variance (corrected for the non-inde- pendence of the k iterations, Shcheglovitova & Anderson 2013) for each of these four metrics.”
SDMtoolbox: a python‐based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses (2014, methodology): “This tool also facilitates testing diﬀerent combinations of the ﬁve model feature class types and regularization multipliers to optimize model performance (Shcheglovitova & Anderson 2013; Radosavljevic & Anderson 2014).”
spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models (2015, background): “This is time consuming and prohibitive for species with more than a small number of records (Shcheglovitova and Anderson 2013).”
The challenge of modeling niches and distributions for data‐poor species: a comprehensive approach to model complexity (2018, methodology): “The jackknife (a method of withholding data) consists of n iterations; in each iteration n – 1 localities are used for calibration, and the model is evaluated on the withheld locality (Pearson 2007, Shcheglovitova and Anderson 2013).”
What is an optimal value of k in k-fold cross-validation in discrete Bayesian network analysis? (2020, methodology): “Such validation procedures can take various forms including bootstrapping, jackknifing, and cross-validation (e.g., Lillegard et al. 2005; Shcheglovitova and Anderson 2013; Arlot and Celisse 2010).”