Data: Improving the use of information from museum specimens: Using Google Earth© to georeference Guiana Shield specimens in the US National Herbarium

Abstract

ISSN 1948-6596 resources data Improving the use of information from museum specimens: Us- ing Google Earth © to georeference Guiana Shield specimens in the US National Herbarium Eduardo Garcia-Milagros and Vicki A. Funk US National Herbarium, Department of Botany, National Museum of Natural History, Smith- sonian Institution, Washington DC, 20013-7012 USA e-mail: eduadogarmi@gmail.com; http://botany.si.edu/bdg/index.html Abstract. Data found on labels of museum collections have been useful in a variety of biodiversity studies. However, the georeferenced data available are often hampered by poor interpretation of label informa- tion and as a result are not as accurate, and therefore useful, as they might be. We have used Google Earth© as a geographic information system to improve the georeferencing of the data. Its user interface allowed us to make use of all the label information and to represent the coordinates more accurately, thus producing a better quality and more reliable dataset to be used in our studies. The quality, defined as “fitness for use”, of the species-occurrence data generated, which is mostly affected by the values of accuracy and uncertainty associated to the coordinates, shows that uncertainly can be reduced. This method also allows us to show the power of examining georeferenced data from the stand point of ‘all collections from an expedition” rather than “all collections from a single area.” Type specimens housed at U.S. National Herbarium from the Guiana Shield were used in this work. Keywords. museum collections, georeferencing, data quality, Google Earth, type specimen Introduction The specimen collections housed in museums and herbaria are a permanent record of a species at a given location on a specific date. The locality of a collection is stored as text on a specimen label. Georeferencing is the process of converting these locality descriptions into latitude/longitude coor- dinates which can be easily analyzed with GIS ap- plications. These species-occurrence data, to- gether with environmental variables are often used in various modeling methods, i.e., to plot existing data and predict the geographic distribu- tion of species (e.g., Elith et al. 2006). These pre- dictive distribution models are becoming an im- portant tool in analytical biology, with applications in conservation and reserve planning, ecology, evolution, epidemiology, invasive-species man- agement and other fields (Phillips et al. 2005); however, they depend on accurate coordinates. Studies show that the data stored in the collec- tions are often geographically, temporally, and taxonomically biased (Funk et al. 1999, ter Steege et al. 2000, Funk and Richardson 2002, Reddy and Davalos 2003). Although these studies suggest that collecting more data is necessary, the infor- mation behind these collections is of a high value. Gathering such data in databases and georefer- encing them is a time-consuming and underappre- ciated task. However, once avaliable they are used, for instance, in establishing priorities for future expeditionary research and thus filling gaps in the data (Funk et al. 2005) and in regional con- servation planning (Ferrier 2002, Chefaoui et al. Recently there has been an increase in the availability of collections data (GBIF, TROPICOS, etc.) and an important consideration is how ‘good’ or reliable they are. Estimates of quality have been defined as “fitness for use” (Chrisman 1983) or “fitness for potential use” (English 1999) and Chapman (2005) describes how many factors may affect the quality of the data. In terms of geo- graphic position of location, precision and accu- racy are of concern and geographic data always frontiers of biogeography 2.3, 2010 — © 2010 the authors; journal compilation © 2010 The International Biogeography Society