About SandflyMap

History

SandflyMap is authored by Desmond Foley, Pollie Rueda and Richard Wilkerson of the Walter Reed Biosystematics Unit (WRBU) based in the Smithsonian Institution, Washington DC. SandflyMap is currently under construction but is modeled after MosquitoMap, and, along with MosquitoMap and SandflyMap, is a part of the umbrella application VectorMap. See a published description of MosquitoMap in the International Journal of Health Geographics. SandflyMap was designed to be an online clearinghouse for global geo-referenced sand fly collection records and species distribution models derived from those records. This site is intended to increase our understanding of sand fly species and sand fly-borne disease distribution. We anticipate that it will also be useful for research on the impact of global warming and anthropogenic changes on emerging infectious diseases and biodiversity. Funding for the creation of SandflyMap was obtained from the Global Emerging Infections Surveillance and Response System (a Division of the Armed Forces Health Surveillance Center - AFHSC/Div of GEIS Ops) as part of a proposal to conduct ecological niche modelling of disease vectors. The web application was built by WorldView Solutions Inc. using ArcGIS Server 10 and Microsoft Silverlight.

Methods

SandflyMap is a unique global resource for researchers interested in sand fly-borne diseases and basic questions concerning sand fly distribution and ecology. More specifically, SandflyMap is an online database of species distribution models and georeferenced species collection events, for individual sand flies or pools of sand flies of the same species. Collection records and distribution maps come from museum specimens, the literature, and from submissions by other sand fly workers. Data for input to SandflyMap refers to preserved (vouchered) specimens and human observation data. We rescue sand fly observation data from the literature that does not have associated vouchered specimens so that they will be databased and served. These observations are given temporary Catalog numbers (SFMap 1, 2 etc), which comprise part of the datum's global unique identifier. A primary output of SandflyMap is ‘dots on maps’, or collection records to species for a particular time and place. These collection events may be observations only or may result in vouchered specimens that are stored in museums or other collections. Unlike Museum databases, SandflyMap is not primarily concerned with data that replicate the record of an individual’s collection, such as occur with exuviae, DNA material, progeny or genitalia preparations. These are considered derivatives and may (or may not) be recorded, unless they are the sole representative of an individual sand fly. Another primary output of SandflyMap are species distribution models. These may have been developed by a variety of procedures but are usually ecological niche models derived from presence-only data.

All records have basic information that accords with the Darwin Core schema including country and subordinate geographic units (using the GADM database), latitude and longitude, spatial accuracy , taxonomic data (including kingdom, family, genus, and species), an explicit statement of the basis of the record, the collector, collection date, and identification method and date. In all, over 60 data fields are present in SandflyMap, many with controlled vocabulary terms to assist data searches. Additional data fields include those for habitat, host, and any parasites identified in association with the sand fly (for a complete list of field, see Data Portal). The general description of the methodology for processing and data cleaning the databased georeferenced data is described in Foley et al. (2008. Ecological Entomology). Briefly, databases are divided into those records that have geographic coordinate data and those that do not. Entries are further divided into those of questionable taxonomy, apparent identification failures, and those with unequivocal species identification. Verbatim geographic coordinates are checked to ensure they have the correct sign (+ or -) for their hemisphere of origin, and converted to WGS84 and decimal degrees to 5 decimal places using Geotrans. Specimens with unequivocal identifications and geocodes will be filtered in Microsoft Excel for unique locations, and these point data converted to shape files and simple cleaning routines undertaken by the ‘check coordinates’ option of DIVA-GIS, a “point-in-polygon” method (Chapman, 2005, Principles and Methods of Data Cleaning – Primary Species and Species-Occurrence Data, version 1.0), which identifies points located outside all polygons (i.e. fall in the ocean), and points that do not match relations for the country names (i.e. fall in another country). We also use the GBIF Data Tester tool to further detect records likely to hold erroneous information. Anomalous locations are rechecked and corrected by consulting original collection cards and maps housed at the WRBU or through an online Gazetteer such as the ADL online Gazetteer and the Global Gazetteer. Spatial precision estimates were derived using BioGeoMancer or the Georeferencing calculator. Generic and species names are currently according to the list from the Catalogue of Life, June 2010 (care of Frederic Thompson).