Natural History Specimen Digitization: Challenges and Concerns

Vollmar, Ana; Macklin, James; Ford, Linda

doi:10.17161/bi.v7i2.3992

Cited by 92 publications

(78 citation statements)

References 8 publications

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“…Such issues lead to spatial and temporal biases in data collection resulting in incomplete information or data deficiency on ecology and distribution of the threatened species. Such spatial and temporal biases are visible in the plant sample collections stored in most herbaria or natural history museums 8 . The biased and incomplete surveys eventually reduce the accuracy of the threat assessment 9 .…”

Section: Introductionmentioning

confidence: 99%

Inventory and Characterization of New Populations through Ecological Niche Modelling Improve Threat Assessment

et al. 2018

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Categorization of species under different threat classes is a pre-requisite for planning, management and monitoring of any species conservation programme. However, data availability, particularly at the population level, has been a major bottleneck in the correct categorization of threatened species. Till date, threat assessments have been mostly based on expert opinion and/or herbarium records. The availability of primary data on distribution of species and their population attributes is limited in India because of inadequate field survey, which has been ascribed to resource constraints and inaccessibility. In this study, we demonstrate that ecological niche modelling (ENM) can be an economical and effective tool to guide surveys overcoming the above two constraints leading to the discovery of new populations of threatened species. Such data lead to improved threat assessment and more accurate categorization. We selected 14 threatened plants comprising 5 trees (Acer hookeri Miq., Bhesa robusta (Roxb.) Ding Hou, Gynocardia odorata Roxb., Ilex venulosa Hook. f. and Lagerstroemia minu-

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Section: Introductionmentioning

confidence: 99%

Inventory and Characterization of New Populations through Ecological Niche Modelling Improve Threat Assessment

et al. 2018

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“…These are thought to represent a large proportion of the specimen data existing in digital form. Effectively, the "low hanging fruit" have been picked and although the amount of specimen data increases steadily, the present growth rate is minimal when considering that estimates of the total numbers run in the range of 1.2 to 2.1 billion specimens (Ariño, 2010) or even higher (see reference in Vollmar & al., 2010).…”

Section: Introductionmentioning

confidence: 86%

“…The Task Group conducted a global survey to identify the barriers and challenges to digitization (Vollmar et al, 2010) and undertook a prototype study to estimate the universe of the natural history collections data (Ariño, 2010). It further held consultations with the natural history collections community and professional societies such as the Society for Preservation of Natural History Collections , and the Consortium of European Taxonomic Facilities (CETAF).…”

Section: Introductionmentioning

confidence: 99%

Summary of Recommendations of the GBIF Task Group on the Global Strategy and Action Plan for the Digitisation of Natural History Collections

Berendsohn¹,

Chavan²,

Macklin³

2010

Biodiv. Inf.

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Abstract. -A Task Group to envision a Global Strategy and Action Plan for the Mobilization of Natural History Collections Data established by the Global Biodiversity Information Facility (GBIF) has formulated three basic recommendations in order to increase the rate of mobilization of natural history collections data and improve the usage of this information resource: (i) GBIF must facilitate access to information about non-digitized collection resources by publicizing the research potential of collections through metadata and assessing the number of non-digitized specimens; (ii) GBIF must work with collections to continue to increase the efficiency of specimen data capture and to enhance data quality by means of technical measures, by means of ensuring attribution and professional credit and influencing institutional priorities, and by engaging with funding agencies; (iii) GBIF must continue to improve and promote the global infrastructure used to mobilize digitized collection data through technical measures, outreach activities and political measures.

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“…Meeting GSPC targets on plant conservation seems unlikely without substantial increases in funding and personnel allocated to data collection, curation and mobilization. Given difficulties in securing adequate and sustained financing for such activities (Vollmar et al 2010;Bradley et al 2014;Costello et al 2014), efforts to improve DAI should be globally coordinated and prioritized (Meyer et al 2015).…”

Section: Prospects For Using Dai In Global Plant Research Conservatimentioning

confidence: 99%

Multidimensional biases, gaps and uncertainties in global plant occurrence information

Meyer

Weigelt

Kreft

2015

Preprint

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Plants are a hyperdiverse clade that plays a key role in maintaining ecological and evolutionary processes as well as human livelihoods. Glaring biases, gaps, and uncertainties in plant occurrence information remain a central problem in ecology and conservation, but these limitations have never been assessed globally. In this synthesis, we propose a conceptual framework for analyzing information biases, gaps and uncertainties along taxonomic, geographical, and temporal dimensions and apply it to all c. 370,000 species of land plants. To this end, we integrated 120 million point-occurrence records with independent databases on plant taxonomy, distributions, and conservation status. We find that different data limitations are prevalent in each dimension. Different information metrics are largely uncorrelated, and filtering out specific limitations would usually lead to extreme trade-offs for other information metrics. In light of these multidimensional data limitations, we critically discuss prospects for global plant ecological and biogeographical research, monitoring and conservation, and outline critical next steps towards more effective information usage and mobilization. We provide an empirical baseline for evaluating and improving global floristic knowledge and our conceptual framework can be applied to the study of other hyperdiverse clades. AbstractPlants are a hyperdiverse clade that plays a key role in maintaining ecological and evolutionary processes as well as human livelihoods. Glaring biases, gaps, and uncertainties in plant occurrence information remain a central problem in ecology and conservation, but these limitations have never been assessed globally. In this synthesis, we propose a conceptual framework for analyzing information biases, gaps and uncertainties along taxonomic, geographical, and temporal dimensions and apply it to all c. 370,000 species of land plants. To this end, we integrated 120 million point-occurrence records with independent databases on plant taxonomy, distributions, and conservation status. We find that different data limitations are prevalent in each dimension. Different information metrics are largely uncorrelated, and filtering out specific limitations would usually lead to extreme trade-offs for other information metrics. In light of these multidimensional data limitations, we critically discuss prospects for global plant ecological and biogeographical research, monitoring and conservation, and outline critical next steps towards more effective information usage and mobilization. We provide an empirical baseline for evaluating and improving global floristic knowledge and our conceptual framework can be applied to the study of other hyperdiverse clades.PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1326v2 | CC-BY 4.0 Open Access |

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Natural History Specimen Digitization: Challenges and Concerns

Cited by 92 publications

References 8 publications

Inventory and Characterization of New Populations through Ecological Niche Modelling Improve Threat Assessment

Inventory and Characterization of New Populations through Ecological Niche Modelling Improve Threat Assessment

Summary of Recommendations of the GBIF Task Group on the Global Strategy and Action Plan for the Digitisation of Natural History Collections

Multidimensional biases, gaps and uncertainties in global plant occurrence information

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