A specialist’s audit of aggregated occurrence records

Mesibov, Robert

doi:10.3897/zookeys.293.5111

Cited by 29 publications

(41 citation statements)

References 2 publications

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“…The new data sources can also introduce new uncertainties and errors, particularly regarding the consistency of taxonomic name usages (Mesibov 2013, Ferro and Flick 2015, Franz et al 2016, Mesibov 2018). Nevertheless, occurrence-based studies should strive to make high-quality, standard-compliant biodiversity data openly available (Sikes et al 2016).…”

Section: Checklist Generation Methodsmentioning

confidence: 99%

An updated checklist of the Tenebrionidae sec. Bousquet et al. 2018 of the Algodones Dunes of California, with comments on checklist data practices

Johnston

Aalbu²,

Franz

2018

BDJ

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Generating regional checklists for insects is frequently based on combining data sources ranging from literature and expert assertions that merely imply the existence of an occurrence to aggregated, standard-compliant data of uniquely identified specimens. The increasing diversity of data sources also means that checklist authors are faced with new responsibilities, effectively acting as filterers to select and utilize an expert-validated subset of all available data. Authors are also faced with the technical obstacle to bring more occurrences into Darwin Core-based data aggregation, even if the corresponding specimens belong to external institutions. We illustrate these issues based on a partial update of the Kimsey et al. 2017 checklist of darkling beetles - Tenebrionidae sec. Bousquet et al. 2018 - inhabiting the Algodones Dunes of California. Our update entails 54 species-level concepts for this group and region, of which 31 concepts were found to be represented in three specimen-data aggregator portals, based on our interpretations of the aggregators' data. We reassess the distributions and biogeographic affinities of these species, focusing on taxa that are precinctive (highly geographically restricted) to the Lower Colorado River Valley in the context of recent dune formation from the Colorado River. Throughout, we apply taxonomic concept labels (taxonomic name according to source) to contextualize preferred name usages, but also show that the identification data of aggregated occurrences are very rarely well-contextualized or annotated. Doing so is a pre-requisite for publishing open, dynamic checklist versions that finely accredit incremental expert efforts spent to improve the quality of checklists and aggregated occurrence data.

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Section: Checklist Generation Methodsmentioning

confidence: 99%

An updated checklist of the Tenebrionidae sec. Bousquet et al. 2018 of the Algodones Dunes of California, with comments on checklist data practices

Johnston

Aalbu²,

Franz

2018

BDJ

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“…For example, data with low spatial resolution may be faulty when constructing high-resolution species distribution model (Hefley et al, 2014;Maldonado et al, 2015;Velásquez-Tibatá et al, 2015). Several studies that assess the quality of biodiversity data exist (Ballesteros-Mejia et al, 2013;García-Roselló et al, 2014;Mesibov, 2013;Otegui et al, 2013b;Vandepitte et al, 2015). Yet, studies that actually quantify the effect of data cleaning are scarce (e.g.…”

Section: Introductionmentioning

confidence: 97%

“…formatting of date information), as well as errors during the central harvesting and indexing procedures (Otegui, 2012;Wieczorek et al, 2012). These problems have raised concerns that GBIF data cannot be reliably used for biodiversity research (Mesibov, 2013;Yesson et al, 2007). Data cleaning is a process used to determine inaccurate, incomplete, or unreasonable data, and improve the quality through correction of detected errors and omissions.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the value of user-level data cleaning for big data: A case study using mammal distribution models

Gueta

Carmel

2016

Ecological Informatics

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“…Assessments of country-endemicity relied solely upon IUCN-RL data that provides country-level distribution information for each assessed taxon. There have been many significant critiques of uncritical use of online species occurrence data (Yesson et al 2007;Beck et al 2013Beck et al , 2014Mesibov 2013;Otegui et al 2013), so we emphasize here that in this case we are only interested in accuracy to the country-level for the purpose of assessing endemicity. As opposed to species distribution modeling, a relatively coarse country-level analysis is justified here, since the implementation of CBD and GSPC are focused with respect to country boundaries.…”

Section: Geographic Occurrence and Endemicitymentioning

confidence: 99%

Comparing and contrasting threat assessments of plant species at the global and sub-global level

et al. 2017

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Evidence-based assessments of extinction risk are established tools used to inform the conservation of plant species, and form the basis of key targets within the framework of the Global Strategy for Plant Conservation (GSPC). An overall picture of plants threat assessments is challenging due to the use of a variety of methodologies and range in scope from global to subnational. In this study, we quantify the state of progress in assessing the extinction risk of all land plants, determine the key geographic and taxonomic gaps with respect to our understanding of plant extinction risk, and evaluate the impact of different sources and methodologies on the utility of plant assessments. To this end, we have analyzed a cleaned dataset compiled from IUCN Red List of Threatened Species and Regional Red Lists. We reveal that there are assessments available for 89,810 distinct species or 25% of all accepted land plant species. However unlike with other major organismal lineages the bulk of the plant species assessments are derived from Regional Red Lists, and not the Global IUCN Red List. We demonstrate that this bias towards regional assessments results in distinct taxonomic and geographic strengths and weaknesses, and we identify substantial taxonomic and geographic gaps in the assessment coverage. With species that have been assessed in common at both global and regional levels, we explore the implications of combining threat assessments from different sources. We find that half of global and regional assessments do not agree on the exact category of extinction risk for a species. Regional assessments assign a higher risk of extinction; or underestimate extinction risk with almost equal frequency. We conclude with recommended interventions, but support the suggestion that all threat assessments should be pooled to provide more data and broaden the scope of threat assessments for monitoring progress towards GSPC targets.

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A specialist’s audit of aggregated occurrence records

Cited by 29 publications

References 2 publications

An updated checklist of the Tenebrionidae sec. Bousquet et al. 2018 of the Algodones Dunes of California, with comments on checklist data practices

An updated checklist of the Tenebrionidae sec. Bousquet et al. 2018 of the Algodones Dunes of California, with comments on checklist data practices

Quantifying the value of user-level data cleaning for big data: A case study using mammal distribution models

Comparing and contrasting threat assessments of plant species at the global and sub-global level

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