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Data 2016, 1(3), 20; doi:10.3390/data1030020

Standardization and Quality Control in Data Collection and Assessment of Threatened Plant Species

1
National Park Service, Heartland Inventory and Monitoring Program, 6424 W. Farm Road 182, Republic, MO 65738, USA
2
Department of Biology, Missouri State University, Springfield, MO 65897, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Martin M. Gossner
Received: 10 May 2016 / Revised: 30 October 2016 / Accepted: 9 December 2016 / Published: 14 December 2016
(This article belongs to the Special Issue Biodiversity and Species Traits)
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Abstract

Informative data collection is important in the identification and conservation of rare plant species. Data sets generated by many small-scale studies may be integrated into large, distributed databases, and statistical tools are being developed to extract meaningful information from such databases. A diversity of field methodologies may be employed across smaller studies, however, resulting in a lack of standardization and quality control, which makes integration more difficult. Here, we present a case study of the population-level monitoring of two threatened plant species with contrasting life history traits that require different field sampling methodologies: the limestone glade bladderpod, Physaria filiformis, and the western prairie fringed orchid, Plantanthera praeclara. Although different data collection methodologies are necessary for these species based on population sizes and plant morphology, the resulting data allow for similar inferences. Different sample designs may frequently be necessary for rare plant sampling, yet still provide comparable data. Various sources of uncertainty may be associated with data collection (e.g., random sampling error, methodological imprecision, observer error), and should always be quantified if possible and included in data sets, and described in metadata. Ancillary data (e.g., abundance of other plants, physical environment, weather/climate) may be valuable and the most relevant variables may be determined by natural history or empirical studies. Once data are collected, standard operating procedures should be established to prevent errors in data entry. Best practices for data archiving should be followed, and data should be made available for other scientists to use. Efforts to standardize data collection and control data quality, particularly in small-scale field studies, are imperative to future cross-study comparisons, meta-analyses, and systematic reviews. View Full-Text
Keywords: data quality control; data standardization; observer error; Physaria filiformis; Plantanthera praeclara; rare plant sampling; sample design data quality control; data standardization; observer error; Physaria filiformis; Plantanthera praeclara; rare plant sampling; sample design
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Morrison, L.W.; Young, C.C. Standardization and Quality Control in Data Collection and Assessment of Threatened Plant Species. Data 2016, 1, 20.

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