Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns

By A. Zaniewski, Anthony Lehmann, J. Overton. 2002

579 citations recorded by the source corpus.

Subfields: Ecological Modeling, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/bb6a8d106deec625a09d16a79ef3bdb3a846daec

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In Ecological Modeling

In Nature and Landscape Conservation

Citations in the corpus

WHAT MATTERS FOR PREDICTING THE OCCURRENCES OF TREES: TECHNIQUES, DATA, OR SPECIES' CHARACTERISTICS? (2007, methodology): “Alternatively, pseudo-absences can supplement presence-only records and then presence–absence techniques can be used (Manly et al. 1993, Stockwell and Peters 1999, Zaniewski et al. 2002, Engler et al. 2004).”
Bias in freshwater biodiversity sampling: the case of Iberian water beetles (2008, result): “Our results demonstrate that, as happens with other taxa and territories (Dennis et al ., 1999; Dennis & Thomas, 2000; Zaniewski et al ., 2002; Reutter et al ., 2003; Graham et al ., 2004; Soberón & Peterson, 2004; Mart’nez-Meyer, 2005; Romo et al ., 2006; Hortal et al ., 2007; Lobo et al ., 2007;…”
An evaluation of a GARP model as an approach to predicting the spatial distribution of non‐vagile invertebrate species (2006, methodology): “This approach, although not as accurate as using true presence/absence data, has been shown to provide significantly predictive models (Ferrier & Watson, 1997; Zaniewski et al ., 2002) with results that are easy to read and easy to interpret (Guisan & Thuiller, 2005).”
Predicted impact of climate change on European bats in relation to their biogeographic patterns (2010, methodology): “This derives from the characteristics of MAXENT: using pseudo-absences in the calculations implies that predictions are prone to overfit presence data, hence this technique is likely to reflect the natural distribution or the realized niche of taxa (Zaniewski et al., 2002).”
Modelling distribution and abundance with presence‐only data (2006, background): “These sites may be selected without replacement from within the study region either randomly (Stockwell & Peterson 2002), randomly with case-weighting to reduce the effective sample size of pseudo-absences (Ferrier & Watson 1996; Ferrier et al. 2002), or by using environmentally weighted random samp”
GIS-based modeling of Javan Hawk-Eagle distribution using logistic and autologistic regression models (2008, methodology): “…data are available, one approach is to generate ‘‘pseudo-absence’’ data from background areas from which species data are missing (Stockwell and Peterson, 2002a; Zaniewski et al., 2002; Engler et al., 2004; Pearce and Boyce, 2006) and use them in the model as absence data for the relevant species.”
Assessing habitat selection using multivariate statistics: Some refinements of the ecological-niche factor analysis (2008, background): “…in a large range of animal taxons (insects: e.g., Gallego et al., 2004; cetaceans: e.g., Compton, 2004; birds: e.g., Hirzel et al., 2004; mammals: e.g., Dettki et al., 2003; Zimmermann, 2004), in some plants (e.g., Zaniewski et al., 2002) and rare or endangered species (e.g., Reutter et al., 2003).”
Habitat suitability modelling to correlate gene flow with landscape connectivity (2008, methodology): “Presence-only data, however, are far easier to get from existing biodiversity databases, mainly because of the scarcity of reliable absence data (Boyce et al. 2002; Zaniewski et al. 2002; Graham et al. 2004).”
Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models (2010, background): “One solution is to draw randomly a set of absence records from cells that do not contain presence records (termed ‘pseudoabsence data’; Zaniewski et al., 2002).”
The Effects of Sampling Bias and Model Complexity on the Predictive Performance of MaxEnt Species Distribution Models (2013, background): “A number of other studies have shown the importance of the background data selection method through a variety of SDM techniques [19,20,21,22,23,52] and studies have begun to also evaluate MaxEnt [12,14,53,54,55].”
Mapping world-wide distributions of marine mammal species using a relative environmental suitability (RES) model (2006, background): “Habitat suitability models have been widely applied in terrestrial systems and for a wide range of landbased species (Peterson & Navarro-Sigüenza 1999, Zaniewski et al. 2002, Store & Jokimäki 2003).”
GRASP: generalized regression analysis and spatial prediction (2002, methodology): “The concept of GRASP has been used in numerous ecological applications (Table 1), including recent ones that have used the GRASP implementation demonstrated here, (e.g. Cawsey et al., 2002; Lehmann et al., 2002; Overton et al., 2002; Ray et al., 2002; Zaniewski et al., 2002).”
Species’ Distribution Modeling for Conservation Educators and Practitioners (2010, background): “, Stockwell and Peters, 1999) or according to a set of weighting criteria (e.g., Engler et al., 2004; Zaniewski et al., 2002).”
Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. (2009, methodology): “While some studies explore this idea (e.g., Zaniewski et al. 2002, Engler et al. 2004, Lütolf et al. 2006), the ecological literature lacks a coherent theoretical exploration, and the proposed solutions seem to represent different and probably incompatible reasoning.”