Incorporating measures of data quality into plant-pollinator databases.
OLLERTON, J. | TALIGA, C. | SALIM, J. A. | POELEN, J. H. | DRUCKER, D. P. | JEFF OLLERTON, UNIVERSITY OF NORTHAMPTON, NATIONAL SOIL SURVEY CENTER; CHRISTINE TALIGA, NATIONAL SOIL SURVEY CENTER; JOSÉ AUGUSTO SALIM, UNIVERSIDADE ESTADUAL DE CAMPINAS; JORRIT H. POELEN, RONIN INSTITUTE, UC SANTA BARBARA CHEADLE CENTER FOR BIODIVERSITY AND ECOLOGICAL RESTORATION; DEBORA PIGNATARI DRUCKER, CNPTIA.
The development of large databases of plant-pollinator relationships poses both great opportunities and a particular problem for scientists and practitioners interested in these interactions. A major issue is that it is rare for measures of data quality to be included, in the sense of stating the evidence by which animal X has been determined to be a pollinator of plant Y. Adding such information to databases is vital if we are to fully understand the plant-pollinator relationships that they describe and address information gaps. We present some examples of data quality schemas that have been used in the past and then adopted by the Pollinators of Apocynaceae Database and the Database of Pollinator Interactions (DoPI), and how the forthcoming USDA-NRCS PLANTS database has tackled this question. In addition, we discuss the use of controlled vocabularies developed by the Brazilian Network of Plant-Pollinator Interactions (REBIPP), allied to a vocabulary based on the Darwin Core standard. It is our hope that the pollination ecology community will see the importance of these or other evaluations of data quality and adopt them accordingly.
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