Predicting species distributions from herbarium collections: does climate bias in collection sampling influence model outcomes?

By Bette A. Loiselle, P. M. Jørgensen, T. Consiglio, Iván Jiménez, J. Blake, Lúcia G. Lohmann, O. M. Montiel. 2007

320 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/4f55f3f08e6da5d9bfe615373695b70783461bae

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias (2014, background): “Several studies questioned the effect of sampling design [38], or the biased nature of museum and herbarium datasets [39] on the predictive performance of SDMs.”
Effects of the number of presences on reliability and stability of MARS species distribution models: the importance of regional niche variation and ecological heterogeneity (2010, background): “In natural history collections, the number of presences for many species is usually less than 20 (Stockwell & Peterson 2002; Loiselle et al. 2008; Mateo 2008), and our results show that collecting more than around this number will have hardly any effect on the reliability of SDMs generated with…”
Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot (2010, background): “On a larger spatial scale, Loiselle et al. (2008) found that although localities based on herbarium collections did not represent well the entire climatic gradient in which most species occur, this existing climatic bias did not greatly affect distribution predictions when compared with an unbiased…”
Uncertainty associated with survey design in Species Distribution Models (2014, methodology): “dom and non-stratified designs are often expected to be spatially and environmentally biased (Hortal et al., 2007; Loiselle et al., 2008), but this is not always the case.”
Profile or group discriminative techniques? Generating reliable species distribution models using pseudo‐absences and target‐group absences from natural history collections (2010, result): “On the contrary, other authors have claimed that the environmental bias in collections does not greatly affect distribution predictions (Kadmon et al., 2004; Loiselle et al., 2008).”
Global mapping of Jatropha curcas yield based on response of fitness to present and future climate (2010, methodology): “Loiselle et al. (2008) found that the effects of biases in specimen sampling were limited if a minimum of 100 specimen locations were available.”
The data void in modeling current and future distributions of tropical species (2011, methodology): “Using these ‘presence-only’ data, a minimum of 20–50 collections per taxa are generally required to produce accurate species distribution models (e.g., Hernandez et al., 2006; Loiselle et al., 2008; Wisz et al., 2008).”
A strict maximum likelihood explanation of MaxEnt, and some implications for distribution modelling (2013, methodology): “The tendency for PO-data to be burdened with strong sampling bias (Araújo & Guisan 2006, Hortal et al. 2008, Loiselle et al. 2008, Robertson et al. 2010, Wolmarans et al. 2010, McCarthy et al. 2011) makes model evaluation by use of a set of P/A data collected independently of the data used to…”
Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia (2010, background): “All rights reserved. doi:10.1016/j.ecolmodel.2010.01.004 with environmental variables (Araújo and Guisan, 2006; Loiselle et al., 2008).”
Keep collecting: accurate species distribution modelling requires more collections than previously thought (2011, background): “…at random but rather collections tend to be clumped around specific areas because of the nature of collecting campaigns and ease of access to sites within a particular habitat (Kadmon et al., 2004; Moerman & Estabrook, 2006; Schulman et al., 2007; Tobler et al., 2007; Loiselle et al., 2008).”
Partial versus Full Species Distribution Models (2012, unknown): “political boundaries) compared to SDMs fitted on the total range of occurrence (sensu Maiorano et al.(2012) for time slices).”