A high-performance web-based information system for publishing large-scale species range maps in support of biodiversity studies

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t a r t i c l e i n f o Keywords: High-performance Species range map Quadtree Web-based Spatial databases GIS Functionality, performance and scalability are critical to Web-based information systems for publishing and disseminating large-scale species distribution data. Existing systems do not support dynamic spatial window queries on large-scale species range maps that are important to compute alpha and beta diversities for biodiversity analysis and modeling. In this study, we have developed a main-memory based novel quadtree data structure to represent large-scale species range maps and support dynamic spatial window queries to retrieve a list of species and their area sizes within a query window efficiently. Using the NatureServe's 4000+ bird species range maps, experiment results have shown that the memory footprint of the proposed quadtree data structure representing the range maps of all the species is about 1/6 of the quadtree derived by combining individual quadtrees each representing a species range map. The experiment results have also demonstrated that the query response times of our main-memory spatial database are well below a fraction of a second for query windows as large as 10 × 10°, which are 2–3 orders better than using a typical disk-resident spatial database system. More than a million of species have been recorded in several repositories, such as the repositories provided by the " Catalogue of Life " project (COL, 2010) and the uBio project (uBio, 2010). The range maps of more and more species are also becoming available which allows researchers to explore the relationships among species distributions and the environments. Synergizing geoinformatics and bioinformatics technologies for species distributions and biodiver-sities research will contribute to our understanding of the ecological consequences of climate change and human impacts. Last decade saw massive developments of biodiversity related information systems on the Internet and the available species distribution data has been increased dramatically (Bisby, 2000). As an example, at the time of writing, the Global Biodiversity Facility (GBIF) data portal has hosted 322, 366, 001 species occurrence records (GBIF, 2012). While the point locations of species occurrences themselves are useful to model species distributions at individual species level …