2011 working group Fr Summary¶
BIEN science¶
Range size spectra¶
- a lot of similarities in Amazon and deciduous forest means and medians
- skewness similar
- sampling bias towards small range species in cell
- sample size dist in cell
- using range calculations to put patterns on map
- species in 1 deg grid cell
- species pool based on range overlap
- is observed trait range different from random?
- look at dataset over time
- in dry areas, triggered by availability of water
Functional traits vs range¶
- conservatism in traits for closely related species
- range not conserved at all
- absolute range size
- model of branch lengths
- auto-prune to BIEN species list
- factor in missing taxa at internal nodes
- commonness of rare species in BIEN
- not properly cutting data to new world
- species occurring along mountain areas and areas w/ high levels of animism
- macro-eco relationships
- patterns opposite those for birds and mammals
- tight relationships btw seed size and plant size
Science interface¶
- simclim: climates
- phylo: phylogeny
- env: temperature, pcpt
- valid: family, taxon name
- TNRS -> corrected species, family name, authority
- annotate data with species list, lat/long
- climate from lat/long server
- needs password protection
- list of points vs box
- ensure no data leaks
- geospatial meeting at 1:30pm
Database¶
- goal is to have something to walk away from in 1 year
- same validations but more data
- standard schema VegX/DwC to load data
- test VegX, VegBank to make sure they can accommodate use cases
- test load of sample data into VegBank
- reload data into core db
- FIA data in FTP site
- in place in Apr
- load full db in Apr/May
- use Nick Spencer's mapping tool to streamline the process of getting plot data into VegBIEN
- validation scripts will run on core db
- end access point to retrieve data
- CSV reps of db and range maps need to be accessible
- derived products
- at end of 1 year, have sustainable model
- how suitable BIEN 2 is w/ minor tweaks? vs. VegBank-based VegX-compliant model
- whenever can't get something out of BIEN 2, let us know
- need use cases that would break the system
- asking more from the initial analysis
- many manual processes before data is ready
- part of wiki w/ data problem statements: bug list
Data problems¶
- ability to separate different plot types: 10,000 Ha should be m^2: different units
- data cleaning, not just scrubbing
- engage TDWG (/Tadwig/)
- missing element, specimen, or occurrence record
- e.g. cultivated flag
Future plans¶
- another meeting next year?
- done after BIEN 3?
- funding for more meetings?
- NSF/RCN grant for 5 years support for meetings
- informatics proposal from NCEAS
- additional funding for tech devel
- compelling scientific question that can't be addressed because of tech challenges
- information plan complemented by what scientists working on
- educate NSF about what we're doing
- press release about what's being funded
- taxonomies, phylogenies, functional traits
- keep the BIEN server running
- will data be out of date in 3-4 years?
- BIEN vet
- addition of iPlant as collaborator
- bring GBIF in as partner
- move beyond botany to other organisms?
- map of life people focusing on vertebrates, but interested in what were doing
- going global would broaden the scope
- when does BIEN become accessible to the rest of the world? how to do it?
- objections from data providers who want data private
- new db will have tiered access control
- who will scrub data?
- a lot of work involved in going global?
- instead of scrubbing, we already have globally distributed data
- politics in going global
- start geoscrubbing
- internationalization in species names, place names
- touch base in conference call before Thanksgiving
- can put things together by Dec/Jan NSF deadline?
- iPlant proposal good starting point
- spring/summer deadlines more realistic
- convex hulls shapefiles, raster images
- requirements of what people need for their analyses
- 4 week lead time to work out sci's problems
- NSF site visit
- statistical strength of different models, sampling bias
- randomization too computationally intense?