New developments in museum-based informatics and applications in biodiversity analysis.

By Catherine H. Graham, Simon Ferrier, Falk Huettman, C. Moritz, A. Townsend Peterson. Trends in Ecology & Evolution, 2004

1,126 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology

View Paper: https://www.semanticscholar.org/paper/3cc75884f7034515a9b8ed0f32d6ad711838422c

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Citations in the corpus

Life-history strategies predict fish invasions and extirpations in the colorado river basin (2006, background): “While we recognize the potential limitations associated with analyzing compiled data that was not systematically collected, such as museum-based specimen data (Graham et al. 2004), this database was constructed with a high level of quality control.”
The influence of spatial errors in species occurrence data used in distribution models (2007, background): “While species occurrence data provide the basis for much research, their use can be problematic because absence data are generally unavailable, sample sizes are often small and geographical bias and spatial error in the data are generally unexplored or unknown (Hijmans et al . 2000; Graham et al . ”
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 fact, most taxa have rarely been collected and their full distribution areas are highly hypothetical, which makes them prime targets for conservation biology and ecological modelling (Graham et al. 2004).”
Species Distribution Models: Ecological Explanation and Prediction Across Space and Time (2009, neutral): “SDMs are still regularly used for such purposes, particularly in quantitative ecological studies (Leathwick & Austin 2001) and evolutionary biology (Graham et al. 2004b).”
Evidence of climatic niche shift during biological invasion. (2007, methodology): “As only occurrences were available, pseudo-absences were generated (Graham et al. 2004) to fill the absence component of the models.”
The importance of biotic interactions in species distribution models: a test of the Eltonian noise hypothesis using parrots (2014, background): “Despite the initial good performance of the models, the inclusion of biotic variables increased AUC for all SDMs generated with one of the resolutions modelled (Fig.”
Assessing the Relevance of Herbarium Collections as Tools for Conservation Biology (2017, positive): “org), these are increasingly used as inputs in distribution models (Graham et al., 2004; Enquist et al., 2009).”
Accounting for spatially biased sampling effort in presence‐only species distribution modelling (2015, background): “Global Biodiversity Information Facility (GBIF)] are also becoming increasingly accessible (Graham et al., 2004; Peterson et al., 2011).”
WHAT MATTERS FOR PREDICTING THE OCCURRENCES OF TREES: TECHNIQUES, DATA, OR SPECIES' CHARACTERISTICS? (2007, methodology): “Models were trained with a set of presence-only records from natural-history collections (NHC; Graham et al. 2004) and tested with an independent, generally more accurate, set of observations that include both presence and absence data, thus providing a measure of the predictive power of each…”
Selecting thresholds for the prediction of species occurrence with presence‐only data (2013, background): “Information concerning the distributions of species is fundamental to many ecological, evolutionary and conservation problems (Graham et al., 2004; Guisan & Thuiller, 2005; Franklin, 2009).”
Measuring the relative effect of factors affecting species distribution model predictions (2014, background): “…random (or uniform) design (Albert et al. 2010), for which every pixel has the same probability of being sampled, and a design under which locations that are close to roads are more likely to be sampled, as occurs frequently in practice (also called sampling bias, see Graham et al. 2004) ; see Fig.”
Predicting the distribution of Sasquatch in western North America: anything goes with ecological niche modelling (2009, background): “Finally, as museums begin to develop databases of collections, all effort should be made to ensure taxonomic accuracy prior to releasing information to the public and to update these databases as new research accumulates for difficult species groups (Graham et al., 2004; Soberón & Peterson, 2004; Ch”