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Terrestrial modeling group Benoit Courbaud (visiting faculty) Jim Crooks (Samsi postdoc) Mike Dietze (Harvard) Cari Kauffman (Samsi postdoc) Sean McMahon.

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Presentation on theme: "Terrestrial modeling group Benoit Courbaud (visiting faculty) Jim Crooks (Samsi postdoc) Mike Dietze (Harvard) Cari Kauffman (Samsi postdoc) Sean McMahon."— Presentation transcript:

1 Terrestrial modeling group Benoit Courbaud (visiting faculty) Jim Crooks (Samsi postdoc) Mike Dietze (Harvard) Cari Kauffman (Samsi postdoc) Sean McMahon (Duke postdoc) Jonty Rougier (Samsi visitor) Wei Wu (Duke postdoc) Jim Clark (Duke)

2 Challenges Infer forest diversity response to climate change Demographic rates of all species depend on interactions with other species, resources, and climate Inference: –Hidden variables –Data at many scales Prediction: large number of interactions –Regional climate affects diversity at tree scales –Climate drivers: GCMs need down-scaling

3 Beginnings Stand simulator parameterized to long- term data sets A SAMSI “terrestrial modeling group” Goals: –Downscale climate to local soil moisture (Cauffman, Rugier, Wu) –Model emulation (Crooks)

4 TDR Maturity obs Data Processes Parameters Hyperparameters CO2 treatment Seed traps ClimateDiameter data Survival Dispersal Maturation Fecundity Diameter growth Mortality risk Observation errors Process uncertainty Heterogeneity Light Canopy data Soil moisture Diameter Climate through soil moisture Hierarchical Bayes model

5 Many types of data and models

6 Clark, LaDeau, Ibanez Ecol Monogr (2004) Inference at the individual tree level ‘mean response’ year effect random individual effect error

7 Demographic rates depend on soil moisture Cari to discuss soil moisture modeling

8 Stochastic Emulation ● The forest simulator has properties that make emulation both important and difficult: – Slow speed limits the physical area that can be simulated in reasonable time. – Its output is – stochastic – non-gaussian – varies over the input space. ● Need for a nonparametric statistical method to emulate the entire output distribution across in the input space.

9 Stochastic Emulation Use the Kernel Stick-Breaking Processes idea of Dunson and Park (2006) to build such an emulator. No final results yet, but the methods and preliminary work will be presented tonight in Jim Crooks' poster.

10 Our ‘transition workshop’ April 2007 Climate scientists and ecologists discussed applications to a range of temperate and tropical sites Discussion of Research Coordination Network proposal Using data from a range of sites, can we more fully explore implications of climate change for forest biodiversity?


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