Taxonomist survey biases and the unveiling of biodiversity patterns

By P. Sastre, Jorge M. Lobo. 2009

127 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/f22b134b364f947ae8b2ea244e60c214beff7536

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Environmental filtering improves ecological niche models across multiple scales (2019, background): “Of particular interest to the ENM community is the issue of sampling bias (Sastre & Lobo, 2009).”
Distribution and Endemism of Angiosperms in the Atlantic Forest (2011, background): “Furthermore, the survey directed towards localities previously recognized as having higher species richness values, such as mountain ranges or particularly wet areas, is unpromising for discovering the true species richness distribution in an area (Sastre & Lobo 2009).”
The importance of correcting for sampling bias in MaxEnt species distribution models (2013, background): “Such errors can have severe consequences for conservation if SDMs are used to delineate areas of high conservation priority (Reddy & Davalos, 2003; Kremen et al., 2008; Sastre & Lobo, 2009).”
Seasonal drought limits tree species across the Neotropics (2017, background): “Fixed-area inventories of local communities from many locations, offer a particular advantage for this kind of study as they avoid the bias towards more charismatic or accessible taxa that affects ad hoc plant collection records (Nelson et al. 1990, Sastre and Lobo 2009).”
Uncertainty associated with survey design in Species Distribution Models (2014, background): “Sastre and Lobo (2009) found that biased survey designs were not efficient in covering the true geographic pattern of species richness within a region (see also Hortal & Lobo, 2011).”
Accounting for uncertainty when mapping species distributions: The need for maps of ignorance (2011, background): “…surveys have traditionally been influenced by the preconceived views and/or previous field experience of data collectors (Bacaro et al., 2009; Sastre and Lobo, 2009), although objective sampling schemes and cost-efficient survey protocols have long been available (Baffetta et al., 2007;…”
The strong influence of collection bias on biodiversity knowledge shortfalls of Brazilian terrestrial biodiversity (2016, methodology): “This is possibly explained by an inherent positive bias from taxonomists, who tend to sample more intensely the places they expect to be more diverse (Sastre & Lobo, 2009).”
Protected areas network is not adequate to protect a critically endangered East Africa Chelonian: Modelling distribution of pancake tortoise, Malacochersus tornieri under current and future climates (2020, background): “…is biased, one cannot differentiate whether species are observed in particular environments because those locations are preferable or because they receive the largest search effort (Phillips et al. 2009, Sastre and Lobo 2009, Wisz and Guisan 2009, Newbold et al. 2010, Chakraborty et al. 2011).”