Lifemapper is a collection of computational services, software modules, web services and project collaborations centered on the computation of maps and models of species geographic ranges. Species distribution modeling is an active field of biological and informatics research because of its ability to predict how species could respond geographically to climate and other types of anthropogenic environmental change.
At its start in 2000, Lifemapper harvested specimen locality information from internet-accessible museum databases, then combined those species distribution points with data describing climate at those locations (particularly rainfall and temperature) to generate distribution models of where species should occur based on where they were known to exist. Data for Lifemapper was obtained from museum databases using a distributed network query protocol “DiGIR” developed at KU in collaboration with UC Berkeley. DiGIR mobilized specimen data on the Internet and enabled the aggregation of specimen records from multiple museums into large databases. DiGIR ultimately contributed to the vision and implementation of the global database of biological specimen information maintained by the Global Biodiversity Information Facility in Copenhagen, Denmark. Lifemapper distribution models were created for each species with a graphical Windows screen-saver based on the SETI@Home distributed computing architecture. The Lifemapper screen saver engaged thousands of desktop users around the world. In addition to the distributed data acquisition and computation architecture, we created a geospatial archive in Postgres to store and serve the resulting species distribution models through a web portal.
Ten years later, Lifemapper has blossomed into a multifaceted geospatial database, visual modeling environment, and analytical web services and computation provider as part of several related research and education initiatives. Lifemapper is at the core of a collaboration among four universities in two states, Kansas and Oklahoma, to create a “cyberCommons”, an integrated science and computation environment for knowledge discovery and education across complex environmental phenomena. Lifemapper provides computational power, data pipelines, end-user workflow authoring environment (Vistrails), enabling researchers to easily construct species distribution modeling experiments with high performance computational and analytical services. Lifemapper will support automatic archiving and description of niche modeling runs, along with a gesture-based user interface for efficient browsing and filtering of massive quantities of model outputs. As part of the cyberCommons, Lifemapper will facilitate the research of biogeographers to understand patterns, evolutionary influences, ecological interactions and climate impacts on regional patterns of biological diversity.
Lifemapper is the core technology for an education research collaboration with the University of Michigan “The ChangeThinking Project” to develop learning progression-driven visualization technologies and associated curriculum materials to assess how middle and high school students’ thinking evolves about ecological impacts of global climate change. This joint effort will deliver dynamic, age-appropriate visualization and Lifemapper species distribution modeling tools to serve as an information source for teaching and learning about the impacts of global climate change. The research will also provide an empirical and theoretical basis for content and inquiry reasoning progressions that articulate critical concept development in science and that explain how learning development is consistent with theories of learning. Among the education/informatics research questions ChangeThinking seeks to answer is: What kinds of dynamic visualization and modeling interactions support the development of deep thinking (in junior and senior high students) about the ecological impacts of climate change?
Lifemapper is also at the core of a cyberinfrastructure collaboration with the University of Connecticut to generate multi-species occurrence data sets (matrices) as input data for macroecological research. By broadening geographical, taxonomic, and temporal scales of species distribution analysis, macroecologists attempt to document and explain statistical patterns of species distribution, abundance, and diversity.
Macroecologists require species occurrence and distribution data as inputs to their multispecies, biome, continental, or global scale methods for analyzing biogeographic patterns and their correlates. For macroecological analysis, however, the biodiversity/ecological niche community protocols are inadequate pipelines – the biodiversity data streams do not filter, aggregate, build, and validate the multispecies grid data sets required for ME research. In order to use the vast amounts of occurrence data, macroecologists struggle with manual, ad hoc data manipulations to assemble ME data sets for analysis. In this collaboration we have an extraordinary opportunity to make vital connections with macroecology and to catalyze macroecological studies by making the creation of multispecies data grids easy with Lifemapper data pipeline, modeling and analytical web services.
Lifemapper is supported by U.S. National Science Foundation grants: EHR/DRL 0918590, BIO/DBI 0815290, EPSCoR 0919443.