Tradeoffs of different types of species occurrence data for use in systematic conservation planning.

By C. Rondinini, K. Wilson, L. Boitani, H. Grantham, Hugh P. Possingham. Ecology Letters, 2006

554 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/2164949ef58637fb54aea40b98b98b2ab78c4784

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Citations in the corpus

Where to put things? Spatial land management to sustain biodiversity and economic returns (2008, background): “The geographic range can be defined by abiotic niche space and/or the outer envelope of a species' point locality data on the landscape (Rondinini et al., 2006).”
The sizes of species’ geographic ranges (2009, background): “In the main, distributions based on range-wide occurrences suffer from greater errors of omission than commission, with sampling effort seldom adequate except at coarse mapping resolutions and often inadequate at any resolution that is useful for many applied purposes (Graham & Hijmans 2006; Rondin”
Without quality presence–absence data, discrimination metrics such as TSS can be misleading measures of model performance (2018, background): “Here we will define species prevalence as the ratio between the species area of occupancy (AOO, i.e. the area that a species actually occupies) and the total study area (see Rondinini, Wilson, Boitani, Grantham, & Possingham, 2006 for definitions).”
Poor overlap between the distribution of Protected Areas and globally threatened birds in Africa (2011, background): “It develops and complements previous habitat suitability mapping efforts carried out on African amphibians and mammals (Rondinini et al., 2005, 2006b; Rondinini & Boitani, 2006).”
Conservation biogeography of the Antarctic (2012, background): “…schemes should be used, and how other activities, land uses or values should be included in any optimization approach have been much discussed (e.g. Rondinini et al., 2006; Seo et al., 2009; Wilson et al., 2010; Carvalho et al., 2011), but understanding the distribution of diversity at one or more…”
Estimating patterns of reptile biodiversity in remote regions (2013, background): “Systematic conservation planning requires more complete knowledge of biodiversity distribution and the identification of relationships between biodiversity and environmental features (Margules & Pressey, 2000; Rondinini et al., 2006; Mokany & Ferrier, 2011).”
The importance of correcting for sampling bias in MaxEnt species distribution models (2013, background): “These can be omission errors (false negatives; a species is mistakenly 2 Diversity and Distributions, 1–14, ª 2013 John Wiley & Sons Ltd thought to be absent) or commission errors (false positives: a species is mistakenly thought to be present) (Rondinini et al., 2006).”
The biodiversity of species and their rates of extinction, distribution, and protection (2014, background): “the coarse-resolution species maps with the high-resolution protected area boundaries (99).”
Global patterns of terrestrial vertebrate diversity and conservation (2013, background): “For instance, one can refine the broad range maps using forest cover or species’ elevation ranges to reduce their errors of commission, which are widely seen as their main drawback (37).”
Application of species distribution models and conservation planning software to the design of a reserve network for the riverine fishes of northeastern Mesoamerica (2011, unknown): “A strength of using SDMs in conservation planning is that they act as ‘filters on habitat from a species-specific viewpoint’ (Rondinini et al., 2006), offering potential improvements in the biological realism of conservation plans.”
Interactive Effects of Water Temperature and Salinity on Growth and Mortality of Eastern Oysters, Crassostrea virginica: A Meta-Analysis Using 40 Years of Monitoring Data (2017, background): “Environmental variation and change make predicting species growth and mortality rates challenging for ecologists and managers (Clark & Clark 2001, Rondinini et al. 2006, Petchey et al. 2015).”
Predicting species distributions for conservation decisions (2013, background): “…accounting for the respective consequences of each type of error (omissions, commissions) when choosing a threshold, or by using different thresholds for different decisions (e.g. when to monitor, when to eradicate, when to change categorisation of threat; Field et al. 2004; Royle & Link 2006).”