An ED-based Protocol for Optimal Sampling of Biodiversity

By Joaquín Hortal, Jorge M. Lobo. Biodiversity and Conservation, 2005

177 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/99bfeff8b128ab3291392a25c5bc09db3106b034

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

The application of predictive modelling of species distribution to biodiversity conservation (2007, background): “…field data using environmentally stratified sampling designs assures that the range of environmental variation is covered, and improves these predictions (Austin & Heyligers, 1991; Margules & Austin, 1991; Hortal et al ., 2001; Hortal & Lobo, 2005; J.R. Ferrer-Paris & J.P. Rodríguez, unpubl. data).”
Five (or so) challenges for species distribution modelling (2006, background): “Others have regarded models as providing a spatial representation of the realized niche (e.g. Austin et al., 1990; Guisan & Zimmermann, 2000; Pearson & Dawson, 2003) on the grounds that the observed species’ spatial distributions that are utilized 1Department of Biodiversity and Evolutionary”
Predicting species distributions from museum and herbarium records using multiresponse models fitted with multivariate adaptive regression splines (2007, background): “…growing literature on the measurement of biases in presence-only data (Freitag et al., 1998; Griffiths et al., 1999; Reddy & Dávalos, 2003) and how to design surveys to provide better coverage when existing data are inadequate (Dennis & Hardy, 1999; Hortal & Lobo, 2005; Ferrier et al., in press).”
Uncertainty associated with survey design in Species Distribution Models (2014, background): “Many methods to design surveys have been proposed with the objective of maximizing the amount of biodiversity captured, while incorporating time and cost limitations (Austin & Heyligers, 1989; Pereira & Itami, 1991; Hirzel & Guisan, 2002; Funk et al., 2005; Hortal & Lobo, 2005; Medina et al., 2013).”
Exploring the effects of quantity and location of pseudo-absences and sampling biases on the performance of distribution models with limited point occurrence data (2011, background): “…presences and absences need to be well-distributed across the entire environmental and geographical gradient of the study area (Kadmon et al. 2004; Hortal & Lobo 2005; Reese et al. 2005; Soberón & Peterson 2005; Vaughan & Ormerod 2005; Hortal et al. 2007; Hortal et al. 2008; Lobo et al. 2010),…”
Bias in freshwater biodiversity sampling: the case of Iberian water beetles (2008, background): “As discussed above, well-sampled and undersampled cells differ significantly in a number of variables, and these differences should be borne in mind to diminish environmental bias in future surveys (Funk et al ., 2005; Hortal & Lobo, 2005).”
Seven Shortfalls that Beset Large-Scale Knowledge of Biodiversity (2015, background): “In the case of data on geographic distributions, maps of ignorance that provide information on which data are reliable or uncertain (Rocchini et al. 2011) can be used to inform the design and implementation of new surveys (Hortal & Lobo 2005).”
Unprotecting the rare species: a niche‐based gap analysis for odonates in a core Cerrado area (2011, background): “These results highlight the extent of the Wallacean shortfall (Bini et al., 2006; Brown & Lomolino, 2008) and support the plea for augmenting the quantity and quality of biogeographical data for conservation purposes (Gaston & Rodrigues, 2003; Hortal & Lobo, 2005; Romo et al., 2006; Lobo, 2008).”
Standardization and optimization of arthropod inventories—the case of Iberian spiders (2009, background): “In such case, a good option is to use an approach that maximizes the environmental diversity encompassed by a predetermined number of areas (e.g., Hortal and Lobo 2005).”
KnowBR: An application to map the geographical variation of survey effort and identify well-surveyed areas from biodiversity databases (2018, methodology): “This final slope can be considered a measure of the degree of completeness of the inventory in each spatial unit (the final rate of increase in the number of species attained with the survey effort developed so far; see Hortal and Lobo, 2005).”
Distribution and Endemism of Angiosperms in the Atlantic Forest (2011, methodology): “In every grid cell, the number of database records was used as a surrogate of sampling effort (Hortal & Lobo 2005).”
Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges (2010, methodology): “…heterogeneity is considered to be one of the main factors associated with a high degree of biological diversity given that areas with higher environmental heterogeneity can host more species due to the greater number of available niches within them (Gaston, 2000; Hortal and Lobo, 2005).”
Accounting for uncertainty when mapping species distributions: The need for maps of ignorance (2011, methodology): “…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; Chiarucci et al., 2008; Funk et al., 2005; Hortal and Lobo, 2005; Rocchini et al., 2005).”
Use of niche models in invasive species risk assessments (2011, background): “…to environmental dimensions will certainly exist (see, e.g., Hirzel et al. 2001; Zaniewski et al. 2002; Engler et al. 2004; Kadmon et al. 2004; Hortal and Lobo 2005; Reese et al. 2005), which may have profound consequences for estimation of species’ niches (Lobo et al. 2007; Hortal et al.…”
The uncertain nature of absences and their importance in species distribution modelling (2010, background): “The compilation of exhaustive databases and the study of survey completeness can also help to identify the location of these methodological absences to some extent (Hortal and Lobo 2005).”
Human perturbations reduce dung beetle diversity and dung removal ecosystem function (2021, methodology): “…entrance of the sampling units in the curve was randomized 100 times in EstimateS version 9.1.0 (Colwell, 2013), and inventory completeness was assessed from the final slope of this smoothed curve (i.e., the difference in observed richness between the last two sampling units; Hortal & Lobo, 2005).”