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Brainstorming for synthesis meeting

by Elsa Cleland last modified 2008-03-11 15:10

Individual university questions:

UCB - map of CA seedsize, fire effects information service database exploration
(FEIS http://www.fs.fed.us/database/feis/plants/index.html) DAVID
UH - Community similarity vs distance at 3 scales, using species functional
groups and phylo groups to look for differences
UCI - similarity across time in Fertsyn datasets, plant versus microbial
community change in response to fertilization
Columbia - Env versus biotic filtering at multiple scales, convex hulls

FIU-can functional traits predict the magnitude of plant responses to nutrient enrichment in estuarine and wetland ecosystems? meta analysis

List of ideas for synthesis:

-Note: just because a trait changes along a gradient, is it a response trait that

is predictive of response to environmental change?  patterns are integrated sum
of response and effect (UCI thoughts). use environmental manipulations to
obtain response traits, use those to predict what might happen along an
environmental gradient. 
-fire response traits - (resprouting, C storage belowground, seedbank capacity)

- effect traits (production, wood density - talk to jerome)
- water flow data (USGS streamguage, Jason's expertise)? GIS layers of fire history? JASON - has FRAP fire history from 1922 - 2007 for CA.

-effects traits important for ecosystem services. Different than the BEF argument, can the provision of certain ecosystem services be traced back to plant traits and the abundance weighted mean trait value? A few studies starting to show a link, or at least trying too. For example, see a general discussion by Diaz et al. (2007) and Mark and Dickinson (2008) for an example of a paired catchment study with two differing primary veg types.

-species distribution changes with shifts in precipitation - ask Scott for more watering
experiments?
- space for time subsitution in traits, maybe use abundance weighted traits means for
different years with different precipitation
- paleo literature - leaf size vs precipitation, % of flora with teeth vs temperature, SLA
versus nutrient availability

- traits predicting liklihood of fire, species responses to fire, effects of shifting
composition after fire, and ecosystem services

- controlled burn experiments? grasslands might be good here, as well as woody

some data sources:

-USGS Ecosystem map?
-Large scale range shifts
-Forest Inventory plots http://fia.fs.fed.us/tools-data/default.asp (UCI with fire history
maps)
- california fire perimeters map and GIS data: http://frap.cdf.ca.gov/data/frapgismaps/download.asp
- Berkeley's fire research center: http://firecenter.berkeley.edu/
- outbreaks (Elsa will talk to juliann aukema), large environmental gradients, would need
to collect the traits, probably only georeferenced at the level of the county

-the California Weislander vegetation plots: http://vtm.berkeley.edu
- VEGBANK (http://vegbank.org/vegbank/index.jsp idiosyncratic repository)
- USDA PLANTS - Dan et al. have downloaded and written R scripts
- TAXON scrubber (Brian Enquist's tool)
- note that Columbia is pulling seedsize out of Kew seedsize database - We are working on a simple script to harvest seed size data for a given species list. I agree with David that we might want to put together a master list and request data directly from John Dickie, the SID contact.

How to structure/group the questions:

-get students talking/interacting over the web before they come
-develop 2-3 questions before the meeting
-within university projects are independent, the folks at the synthesis won't bring
projects/tasks back
-California/Southeast/New England groups
- woody/herbaceous/wetland?
- fire/nutrients/precip/temp

Questions for Scott: are there good precip gradients across the interior of the US where we
could layer experimental responses along the gradient? (Mendy Smith/Alan Knapp synthesis -
does interannual variation in precipitation parralel the kinds of patterns you see along
spatial gradients in precipitation)

Here is information about fire maps in California:

The Fire Perimeters data consists of CDF fires 300 acres and greater in size and USFS fires 10 acres and greater throughout California from 1950 to 2002. Some fires before 1950, and some CDF fires smaller than 300 acres are also included. To ensure high quality fire perimeters data are avialable to the public and to cooperating agencies. This layer should not be used for statistical analysis. When compared to the Wildfire Activity Statistics Report it is only 90% complete. The Wildfire Activity Statistics Report is created annually by the California Department of Forestry and Fire Protection. You can download the entire GIS dataset http://gis.ca.gov/catalog/BrowseRecord.epl?id=21086


From the FIA library it looks like we are interested in phase 2 and potentially phase 3 data:

 Forest Monitoring. The forest monitoring component is the best known component of the FIA program. This component consists of a three stage systematic sample of sites across all forested lands of the US. Phase 1 consists of remote sensing for stratification, to identify where the forested land is. Phase 2 consists of one field sample site for very 6,000 acres of forest, where field crews collect data on forest type, site attributes, tree species, tree size, and overall tree condition. Phase 3 consists of a subset of Phase 2 sample plots which are measured for a broader suite of forest health attributes including tree crown conditions, lichen community composition, understory vegetation, down woody debris, and soil attributes. Soil samples are sent to a laboratory for chemical analysis. Finally, an associated sample scheme exists to detect cases of ozone damage occurring to adjacent forest vegetation. Collectively, the forest monitoring component of FIA provides a nationwide systematic sample of a wide array of measurements on forested ecosystems, which are used by a diverse set of customers for many purposes. For example, FIA data have been used to map habitat for endangered animal species, to identify areas of forest decline, and to track the effect of global change reflected in changing species distributions.

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