1. Brian J. Enquist Dept. Ecology and Evolutionary Biology University of Arizona, Tucson, A.Z. and The Santa Fe Institute, Santa Fe, N.M. Brian J. Enquist Dept. Ecology and Evolutionary Biology University of Arizona, Tucson, A.Z. and The Santa Fe Institute, Santa Fe, N.M. Botanical Information and Ecology Network

2. Botanical Information and Ecology Network (BIEN) Brian J. Enquist, University of Arizona, Richard Condit, STRI, Panama and CTFS Robert K. Peet, University of North Carolina at Chapel Hill, Brad Boyle, University of Arizona, Steven Dolins, Bradley University, Mark Schildhauer, NCEAS Organizers

3. CTFS Meeting, Panama December 2006 Advisory meeting for CTFS plot database A unique opportunity to do something larger....

4. (1) Specific science questions – Compile the primary sources of biodversity data at the nexus of merging herbarium, plot (abundance), and trait data for plants in the Americas. (2) Technology development goals associated with answering these questions effectively – as well as to establish an informatics methodology for continuing to assemble and integrate relevant observation data for this and other projects. BIEN Goals (3) Longer-term program development – seek support to develop a permanent technical solution to the integration of vegetation/botanical data

5. - Generate a standardized species list for the Americas - Ask basic science questions at the nexus between abundance, distribution, traits, and diversity across broad gradients - Generate geographic range maps for all species within the BIEN database Science Goals

6. The lack of standardized and integrated botanical information across world’s major biomes is an impediment to advancing basic ecological understanding. In order to do biodiversity science need to document and develop workflows to integrate and ‘scrub’ botanical data Need to clarify how the abundance, distribution, and diversity of plants vary across broad gradients and respond to global change Justification for Working Group

7. Exchange schema Confederated resource Plot and Trait Data Science ! Data Standardization Tools TAXONOMIC PHYLOGENETIC INTELLIGENCE Database BIEN 2.0 BIEN 3.0 Deliverables Cyberinfrastructure Data Sources Data Discovery DATA SCRUBBING CORRECTING, Specimen Data

8. The lack of integrated botanical information across world’s major biomes is an impediment to advancing basic ecological understanding. This is especially true in the tropics where biodiversity is uniquely quite high and patchy. Need to clarify exactly how tropical and temperate floras and communities might differ and how they vary across gradients and respond to global change Justification for Working Group

9. - Jan 2008 - NCEAS BIEN Working Group Proposal - Feb 2009 - iPlant BIEN Working Group Proposal - Aug. 2010 - iPlant BIEN GeoSpatial Proposal BIEN Proposals Provided support for - Meetings - Graduate student support - Post-doctoral funding (Brad Boyle) - Technician support (John Donoghue, Aaron Marcuse-Kubitza)

10. 2008 2009 2010 BIEN NCEAS Meetings

11. Spring 2010 Development of a Taxonomic Name Resolution Service Meeting Missouri Botanical Garden Additional sub-meetings Spring 2011 Development of Geospatial Initiative Meeting at iPlant, Tucson

12. A large fraction of biodiversity data available is crap! - Mangled coordinates - Mis-spelled names, taxa - Data corruption from cultivated species - Heterogeneous sampling - Bad taxonomy Integrating and using biodiversity data is fraught with numerous technical issues Not trivial issues – major impediments to use of biodiversity data The past three years..... What have we learned? Developed tools and workflows to correct, scrub data, and remove ‘bad data’

13. Summary – Major Steps BIEN Data Workflow - Geovalidation of observations - Taxonomic corrections and synonymy (TNRS!) - Identifying and removing cultivated specimens, plantation data etc. - Formalization of BIEN database 2.0 Hurtles surpassed in order to integrate and standardize botanical data - Compilation of herbarium, trait, and ecological plot data - Computational challenge – Scaling up geographic range calculations

14. http://tnrs.iplantcollaborative.org/

15. Science anticipation Now, we are ready..... Botanical data have enormous problems Developed a workflow, tools, and scripts to standardize, clean, and scrub botanical data in order to do science The past three years.....

16. BIEN 2.0 Data Sources (post scrubbing) Herbarium and Observation Data - GBIF - MOBOT - CRIA (Brazil collections) - Arizona - NYBG - UNC, NCS etc. - REMIB (Mexico) - Utrecht - CTFS - FIA - Madidi plots - Vegbank - TEAM - SALVIAS Plot Data Plant Traits Specimen# = 9,345,197 Plot# = 329,741 Total Number of Species = 204,929 Total number of observations = 12,171,014 - GLOPNET - Numerous literature sources - BIEN researcher data Traits = 27 Trait observations = 140,285

17. What we now have available - Summary data for all species in BIEN - mean abundance, max abundnce, total #plots observed in - latitudinal range - mean trait values and trait variation - mean dbh, max dbh - habit information (tree, shrub, liana, etc.)? - Summary data for all species in BIEN ? - Conservation Status (IUCN Red List) -Geographic Range maps (Convex Hull, MaxEnt etc.) Recent output from High Performance Computing - A scrubbed species list of all plants in the Americas - A website (data soon to be accessible) -A species-level phylogeny for BIEN species (?)

18. http://bien.nceas.ucsb.edu/bien/

19. What is unique about BIEN2.0? These are the primary data used for asking questions about botanical diversity, distribution, and ecology Computation demands... – No one has modeled ranges for this number of species - We have a work flow established for large scale calculation of ranges We have documented a repeatable work flow that any researcher must use to take species observations and combine them with traits, ecology, and to put them ‘on a map’. - this is the most basic work flow that is required in biodiversity science

20. (1) Do science and write papers (2) Detail BIEN3.0 database and geospatial tools (3) Future funding Write a major requirements document for NCEAS Meeting goals Break into subgroups (4) iPlant/BIEN GeoSpatial planning

21. NCEAS deliverables -Species list for new word checklist -Range maps for all species - Traits and habit values for a large fraction of BIEN species -The ability to download and calculate basic stats for taxa and clades -Data accessible (at least summary data)

22. BIEN Plant Distributions Climate layers GeoSpatial Data Discovery Environment User Interface User Science User Applied User Outreach and Education iPlantNCEAS (other?) User contributing data? - data standardization tools? What type of science? What kind of applied And education demand? Integrate data GeoSpatial Discovery Proposal to iPlant

24. iPlant NCEAS BIEN iPlant cyberinfrastructure development team Plant Adaptation Group Plant Nutrition iPlant Tree of Life (iPToL) Tree Biology iPlant GeoSpatial Seed Projects Tree Biology GeoSpatial Tools Data Discovery GeoSpatial Tools Data Discovery McGill et al. NCEAS Group iPlant Data Discovery Environment

25. Proposed GeoSpatial Tools Merge BIEN 3.0 with climate and geography layers (1) Click on a map and get a species list (2) Click on a plant clade and map out its distribution (3) Click on a plant observation (taxa) and obtain climate/environmental data Tools to Geoscrub and Correct Botanical Observation Data Tools for Botanical GeoSpatial Discovery