Embedding and extending GIS for exploratory analysis of large-scale species distribution data

ABSTRACT

Exploratory analysis of large-scale species distribution data is essential to gain information and knowledge, stimulating hypotheses and seeking possible explanations of species distribution patterns. Geographical Information System (GIS) has played an important role in modeling and visualizing species distribution patterns for a single or a limited number of species. However, traditional GIS models do not take taxonomic components of species distribution data into consideration and are neither effective nor efficient in managing large-scale species distribution data.

In this study, we propose to embed and extend GIS for large scale species distribution data analysis. We provide an integrated data model that seamlessly links geographical, taxonomic and environmental data related to species distribution data analysis. We then present LEEASP (a Linked Environment for Exploratory Analysis of large-scale Species Distribution data), a prototype that has been developed based on the integrated data model. LEEASP utilizes the state-of-the-art advanced visualization techniques and multiple view coordination techniques to visualize different data sources that are relevant to species distribution data analysis. The North America tree species distribution data and other related data are used as an example to demonstrate the feasibility of the realization of the proposed integrated data model and how LEEASP can help users explore the geographical-taxonomic-environmental relationships

REFERENCES

• 1: Bisby, F. A., 2000. The quiet revolution: biodiversity informatics and the Internet, Science, 289(5488), pp. 2309--12.
• 2: Bongshin Lee , Cynthia Sims Parr , Dana Campbell , Benjamin B. Bederson, How users interact with biodiversity information using TaxonTree, Proceedings of the working conference on Advanced visual interfaces, May 25-28, 2004, Gallipoli, Italy [doi>10.1145/989863.989918]
• 3: COL (Catalogue of Life), 2007. http://www.catalogueoflife.org/
• 4: Robert M. Edsall, The parallel coordinate plot in action: design and use for geographic visualization, Computational Statistics & Data Analysis, v.43 n.4, p.605-619, 28 August 2003 [doi>10.1016/S0167-9473(02)00295-5]
• 5: Thomas Erl, Service-Oriented Architecture: Concepts, Technology, and Design, Prentice Hall PTR, Upper Saddle River, NJ, 2005
• 6: Frehner, M., Brandli, M., 2006. Virtual database: Spatial analysis in a Web-based data management system for distributed ecological data. Environmental Modelling & Software, 21(11), 1544--1554.
• 7: Godefroid, S., Rucquoij, S., et al., 2006. Spatial variability of summer microclimates and plant species response along transects within clearcuts in a beech forest. Plant Ecology 185(1), pp. 107--121.
• 8: Martin Graham , Jessie Kennedy, Extending taxonomic visualisation to incorporate synonymy and structural markers, Information Visualization, v.4 n.3, p.206-223, September 2005 [doi>10.1057/palgrave.ivs.9500096]
• 9: Graham, J., Simpson, A., Crall, A., Jarnevich, C., Newman, G., Stohlgren, T. J., 2008. Vision of a cyberinfrastructure for nonnative, invasive species management. Bioscience, 58(3), 263--268.
• 10: Guisan, A., Zimmermann, N. E., 2000. Predictive habitat distribution models in ecology. Ecological Modelling 135(2--3), pp. 147--186.
• 11: Guisan A., Thuiller, W., 2005. Predicting species distribution: offering more than simple habitat models. Ecology Letters 8(9), pp. 993--1009.
• 12: Guralnick, R. P., Hill, A. W., Lane, M., 2007. Towards a collaborative, global infrastructure for biodiversity assessment. Ecology Letters, 10(8), 663--672.
• 13: Haining, R. Wise, S., Ma, J. S. 1998. Exploratory spatial data analysis in a geographic information system environment. Journal of the Royal Statistical Society Series D-the Statistician, 47, 457--469.
• 14: Hargrove, W. W., Hoffman, F. M., 2004. Potential of multivariate quantitative methods for delineation and visualization of ecoregions. Environmental Management, 34, S39--S60.
• 15: Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15), pp. 1965--1978. Also see http://www.worldclim.org/
• 16: Hillis, D. M., Heath, T. A., et al., 2005. Analysis and visualization of tree space. Systematic Biology 54(3), pp. 471--482.
• 17: Ivan Herman , Guy Melançon , M. Scott Marshall, Graph Visualization and Navigation in Information Visualization: A Survey, IEEE Transactions on Visualization and Computer Graphics, v.6 n.1, p.24-43, January 2000 [doi>10.1109/2945.841119]
• 18: ITIS, 2007. The Integrated Taxonomic Information System. http://www.itis.gov/
• 19: Jeffrey Heer , Stuart K. Card , James A. Landay, prefuse: a toolkit for interactive information visualization, Proceedings of the SIGCHI conference on Human factors in computing systems, April 02-07, 2005, Portland, Oregon, USA [doi>10.1145/1054972.1055031]
• 20: Laihonen, P., Kalliola, R., Salo, J., 2004. The biodiversity information clearing-house mechanism (CHM) as a global effort. Environmental Science & Policy, 7(2), 99--108.
• 21: Loveland, T. R., Merchant, J. M., 2004. Ecoregions and ecoregionalization: Geographical and ecological perspectives. Environmental Management, 34, pp. S1--S13.
• 22: Maceachren, A. M., Wachowicz, M., Edsall, R., Haug, D., Masters, R., 1999. Constructing knowledge from multivariate spatiotemporal data: integrating geographical visualization with knowledge discovery in database methods. International Journal of Geographical Information Science, 13(4), 311--334.
• 23: Myers, N., Mittermeier, R. A., Mittermeier, C. G., da Fonseca, G. A. B., Kent, J., 2000. Biodiversity hotspots for conservation priorities. Nature, 403(6772), 853--858.
• 24: NatureServe, 2007. http://www.natureserve.org/getData/animalData.jsp
• 25: Olson, D. M., Dinerstein, E., Wikramanayake, et al, 2001. Terrestrial ecoregions of the worlds: A new map of life on Earth. Bioscience, 51(11), 933--938.
• 26: Parr, C. S., Lee, B., et al, 2007. EcoLens: Integration and interactive visualization of ecological datasets. Ecological Informatics 2(1), pp. 61--69.
• 27: Pettorelli, N., Vik, J. O., et al, 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology & Evolution, 20(9), pp. 503--510.
• 28: Prasad, A. M., Iverson, L. R., 1999-ongoing. A Climate Change Atlas for 80 Forest Tree Species of the Eastern United States {database}. http://www.fs.fed.us/ne/delaware/atlas/index.html, Northeastern Research Station, USDA Forest Service, Delaware, Ohio.
• 29: Sarkar, I. N., 2007. Biodiversity informatics: organizing and linking information across the spectrum of life. Briefings in Bioinformatics, 8(5), 347--357.
• 30: uBio, 2007. Universal Biological Indexer and Organizer, http://www.ubio.org/
• 31: USGS, 1999. Atlas of Relations Between Climatic Parameters and Distributions of Important Trees and Shrubs in North America, http://pubs.usgs.gov/pp/p1650-a/
• 32: Vivid Solutions, 2004. Unified Mapping Platform (JUMP).http://www.vividsolutions.com/jump/.
• 33: Wieczorek, J., Guo, Q. G. Hijmans, R. J., 2004. The point-radius method for georeferencing locality descriptions and calculating associated uncertainty. International Journal of Geographical Information Science, 18(8), pp. 745--767.
• 34: Willig, M. R., Kaufman, D. M., et al, 2003. Latitudinal gradients of biodiversity: Pattern, process, scale, and synthesis, Annual Review of Ecology Evolution and Systematics 34: 273--309.
• 35: Willis, K. J., Gillson, L., Knapp, S., 2007. Biodiversity hotspots through time: an introduction. Philosophical Transactions of the Royal Society B-Biological Sciences, 362(1478), 169--174.
• 36: Jo Wood , Jason Dykes , Aidan Slingsby , Keith Clarke, Interactive Visual Exploration of a Large Spatio-temporal Dataset: Reflections on a Geovisualization Mashup., IEEE Transactions on Visualization and Computer Graphics, v.13 n.6, p.1176-1183, November 2007 [doi>10.1109/TVCG.2007.70570]
• 37: WWF, 2006. World Wildlife Fund WildFinder: Online database of species distributions, ver. Jan-06. From http://www.worldwildlife.org/WildFinder.
• 38: Zhang, J., Pennington. D., Liu, X., 2007, GBD-Explorer: Extending Open Source Java GIS for Exploring Ecoregion-Based Biodiversity Data, Ecological Informatics, 2(2), pp. 94--102.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Spatial databases and GIS

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: Graphical user interfaces (GUI)

General Terms:
Design

Keywords:
data modeling, exploratory analysis, species distribution, visualization