GLOBAL BIODIVERSITY INFORMATICS: SETTING THE SCENE FOR A "NEW WORLD" OF ECOLOGICAL MODELING

Recent developments in information and communication technology are allowing new experiences in the integration, analysis and visualization of biodiversity information, and are leading to development of a new field of research, biodiversity informatics. Although this field has great potential in diverse realms, including basic biology, human economics, and public health, much of this potential remains to be explored. The success of several concerted international efforts depends largely on broad deployment of biodiversity informatics information and products. Several global and regional efforts are organizing and providing data for conservation and sustainable development research, including the Global Biodiversity Information Facility, the European Biodiversity Information Network, and the Inter-American Biodiversity Information Network. Critical to development of this field is building a biodiversity information infrastructure, making primary biodiversity data freely and openly available over the Internet. In addition to specimen and taxonomic data, access to non-biological environmental data is critical to spatial analysis and modeling of biodiversity. Adoption of standards and protocols and development of tools for collection management, data- cleaning, georeferencing, and modeling tools, are allowing a quantum leap in the area. Open access to research data and open-source tools are leading to a new era of web services and computational frameworks for spatial biodiversity analysis, bringing new opportunities and dimensions to novel approaches in ecological analysis, predictive modeling, and synthesis and visualization of biodiversity information.

[1]  P. Wouters,et al.  Promise and practice in data sharing , 2003 .

[2]  A. Peterson,et al.  Predicting Species Invasions Using Ecological Niche Modeling: New Approaches from Bioinformatics Attack a Pressing Problem , 2001 .

[3]  Julian D. Olden,et al.  Illuminating the “black box”: a randomization approach for understanding variable contributions in artificial neural networks , 2002 .

[4]  David R. B. Stockwell,et al.  Future projections for Mexican faunas under global climate change scenarios , 2002, Nature.

[5]  David R. B. Stockwell,et al.  The GARP modelling system: problems and solutions to automated spatial prediction , 1999, Int. J. Geogr. Inf. Sci..

[6]  David R. B. Stockwell,et al.  Induction of sets of rules from animal distribution data: a robust and informative method of data analysis , 1992 .

[7]  S. B. McDowell,et al.  Atlas of elapid snakes of Australia , 1987 .

[8]  S. Manel,et al.  Comparing discriminant analysis, neural networks and logistic regression for predicting species distributions: a case study with a Himalayan river bird , 1999 .

[9]  A. Peterson,et al.  Predicting distributions of known and unknown reptile species in Madagascar , 2003, Nature.

[10]  Walter V Reid.  Bridging the Science–Policy Divide , 2004, PLoS biology.

[11]  Gail Hodge,et al.  Digital Preservation and Permanent Access to Scientific Information: The State of the Practice , 2004 .

[12]  Marinez Ferreira de Siqueira,et al.  Consequences of global climate change for geographic distributions of cerrado tree species , 2003 .

[13]  T. Yee,et al.  Generalized additive models in plant ecology , 1991 .

[14]  W. Thuiller.  BIOMOD – optimizing predictions of species distributions and projecting potential future shifts under global change , 2003 .

[15]  A. Peterson,et al.  Ecologic Niche Modeling and Potential Reservoirs for Chagas Disease, Mexico. , 2002, Emerging infectious diseases.

[16]  V. Chavan,et al.  Natural history collections: A call for national information infrastructure , 2003 .

[17]  V. Sánchez‐Cordero,et al.  Museum specimen data predict crop damage by tropical rodents. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[18]  A. Peterson,et al.  Lutzomyia vectors for cutaneous leishmaniasis in Southern Brazil: ecological niche models, predicted geographic distributions, and climate change effects. , 2003, International journal for parasitology.

[19]  L. Krishtalka,et al.  Can Natural History Museums Capture the Future? , 2000 .

[20]  A. Peterson,et al.  Chagas Disease in a Domestic Transmission Cycle in Southern Texas, USA , 2003, Emerging infectious diseases.

[21]  Arthur D. Chapman.  Sistema de Informação Distribuído para Coleções Biológicas: A Integração do Species Analyst e SinBiota , 2004 .

[22]  A. Peterson,et al.  Sensitivity of distributional prediction algorithms to geographic data completeness , 1999 .

[23]  A. Peterson,et al.  Ecologic niche modeling and differentiation of populations of Triatoma brasiliensis neiva, 1911, the most important Chagas' disease vector in northeastern Brazil (hemiptera, reduviidae, triatominae). , 2002, The American journal of tropical medicine and hygiene.

[24]  O. Phillips,et al.  Extinction risk from climate change , 2004, Nature.

[25]  A. Peterson.  Predicting the Geography of Species’ Invasions via Ecological Niche Modeling , 2003, The Quarterly Review of Biology.

[26]  Manuel Ruiz Muller.  An analysis of the implications of intellectual property rights (IPR) on the Global Biodiversity Information Facility (GBIF) , 2004 .

[27]  A. O. Nicholls,et al.  Determining species response functions to an environmental gradient by means of a β‐function , 1994 .

[28]  A. Peterson,et al.  Biodiversity informatics: managing and applying primary biodiversity data. , 2004, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[29]  F. Bisby.  The quiet revolution: biodiversity informatics and the internet. , 2000, Science.

[30]  V. Sánchez‐Cordero,et al.  Conservatism of ecological niches in evolutionary time , 1999, Science.

[31]  T. Dawson,et al.  SPECIES: A Spatial Evaluation of Climate Impact on the Envelope of Species , 2002 .

[32]  Matthew E. Watts,et al.  Effectiveness of the global protected area network in representing species diversity , 2004, Nature.