Selecting areas for species persistence using occurrence data

By Miguel B. Araújo, Paul H. Williams. 2000

458 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/5e704942d3f2075a702228f0e6161268595022e0

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Citations in the corpus

Model‐based uncertainty in species range prediction (2006, background): “…2002; Midgley et al., 2003; Thomas et al., 2004; Hannah et al., 2005; Thuiller et al., 2005; Araújo et al., 2006), conservation prioritization (e.g. Araújo & Williams, 2000; Ferrier et al., 2002; Raxworthy et al., 2003; Williams et al., 2005), range filling (Svenning & Skov, 2004), niche…”
Predicting species distributions in poorly-studied landscapes (2008, background): “…al. 2005), (2) provide a baseline for predicting a species’ response to landscape alterations and/or climate change (Thuiller 2003; Araújo et al. 2006), and (3) identify high-priority sites for conservation (Araújo and Williams 2000; Ferrier et al. 2002; Loiselle et al. 2003; Wilson et al. 2005).”
Apples, Oranges, and Probabilities: Integrating Multiple Factors into Biodiversity Conservation with Consistency (2002, unknown): “Araújo and Williams [15] have described a framework for estimating probabilities of persistence for use in area selection .”
Updating bird species distribution at large spatial scales: applications of habitat modelling to data from long‐term monitoring programs (2007, background): “Knowing where a species occurs and recording changes in its distribution has major implications in ecology, species management, and conservation planning (Araújo & Williams, 2000; Bani et al ., 2002).”
The performance of state-of-the-art modelling techniques depends on geographical distribution of species. (2009, background): “…models is the fact that the performance of bioclimatic models is affected by geographical attributes of species, e.g. latitudinal range/marginality (Araújo and Williams, 2000; Segurado and Araújo, 2004), prevalence (Manel et al., 2001; Brotons et al., 2004; McPherson et al., 2004), spatial…”
Predicting species spatial distributions using presence-only data: a case study of native New Zealand ferns (2002, background): “Summation of species predictions used as a measure of species potential biodiversity ‘hotspots’ also shows ENFA models to give the highest and largest distribution of potential biodiversity.”
Challenging Wallacean and Linnean shortfalls: knowledge gradients and conservation planning in a biodiversity hotspot (2006, unknown): “After assuming range continuity (see Araújo & Williams, 2000 for similar reasoning), this HUS will occupy all the adjacent cells only if the level of knowledge in these cells (i.e. number of inventories) is within a given range of values, based on a randomly taken standard deviation (SD k ) of…”
Modelling distribution and abundance with presence‐only data (2006, background): “Examples include reserve design ( Araujo & Williams 2000 ), population viability analysis (Boyce et al. 1994; Akcakaya et al. 2004) and species or resource management (Johnson et al. 2004).”
How climate extremes—not means—define a species' geographic range boundary via a demographic tipping point (2014, background): “An extensive array of ‘‘atlas projects’’ (Araujo and Williams 2000, GBIF 2009) provide increasingly robust information on species’ geographic distributions, allowing researchers to generalize about the structure and dynamics of geographic ranges (Brown et al. 1996, Gaston 2003).”
Can vulnerability among British bumblebee (Bombus) species be explained by niche position and breadth (2007, methodology): “…measurement of the niche is very similar in all of these problems to the climatic suitability models and abundance models that are now routinely applied in ecological (e.g. Austin et al., 1990), evolutionary (e.g. Graham et al., 2004), and conservation studies (e.g. Araújo and Williams, 2000).”
An evaluation of methods for modelling species distributions (2004, methodology): “These distance values were rescaled from zero to one (value ) minimum/maximum ) minimum) to provide values comparable with that obtained with probability-based techniques.”
Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France (2006, background): “…2004; Araújo et al., 2006), to test biogeographical hypotheses (Huntley et al., 2004; McPherson et al., 2004) or to deal with conservation planning problems (Margules & Stein, 1989; Araújo & Williams, 2000; Polasky et al., 2000; Araújo et al., 2004; Cabeza et al., 2004; Williams et al., 2005).”
Profile or group discriminative techniques? Generating reliable species distribution models using pseudo‐absences and target‐group absences from natural history collections (2010, background): “In many cases, this distributional information is limited to that held by natural history collections (NHC) (Araújo & Williams, 2000; Barry & Elith, 2006).”
Sensitivity of Systematic Reserve Selection to Decisions about Scale, Biological Data, and Targets: Case Study from Southern British Columbia (2004, methodology): “Systematic reserve-selection procedures have been developed as a tool to aid in identifying priority conservation areas in light of limited knowledge and understanding of ecological systems (Pressey et al. 1993; Margules & Pressey 2000).”
Use of niche models in invasive species risk assessments (2011, background): “Put another way, overprediction (false positives), commonly cited as a problem with niche model results (Fielding and Haworth 1995; Araújo and Williams 2000; Stockwell and Peterson 2002; Brotons et al. 2004; Stockman et al. 2006) should be understood as a necessary part of the niche Use of niche mod”
A framework for species distribution modelling with improved pseudo-absence generation (2015, methodology): “…involved in true absence sampling, most of the14 available datasets for predictive modelling (generally natural history collec-15 tions, see. e.g. Araújo and Williams, 2000) are lacking explicit absence data.16 Thus, in most cases discrimination techniques are used, requiring the envi-17…”
Consequences of spatial autocorrelation for niche‐based models (2006, background): “…of spatial structure of species’ occurrences is to incorporate a term for SA into the analysis (Smith 1994; Augustin, Mugglestone & Buckland 1996; Araújo & Williams 2000; Keitt et al. 2002; Segurado & Araújo 2004), usually a measure of contagion that encompasses the effect of spatial…”