PARENT SESSION
Thursday, August 10, 8:00-11:30 am
OOS 11 - The devil is in the detail: theory for empirical model systems
Ballroom C, Ballroom Level, Cook Convention Center
Organized by: ON Bjornstad (onb1@psu.edu) and P Amarasekare
This session explores how many recent advances in theoretical ecology have come through modifications of classical models to be applicable to detailed experimental or observational data.
Building a mechanistic theory of forest biogeography.
Purves, Drew*,1, Lichstein, Jeremy 1, Ogle, Kiona1, 2, Strigul, Nikolay1, Bohlman, Stephanie1, Pacala, Stephen1, 1 Princeton University, Princeton, NJ2 University of Wyoming, Laramie, WY
ABSTRACT- We aim to build a quantitative understanding of spatiotemporal variation in the species composition of US forests. We adopt a new approach, fitting species-specific, mechanistic, individual-based models of the whole life-cycle -- dispersal, recruitment, growth, mortality -- to every tree species on the continent. We then use the models to make predictions for community dynamics over larger temporal and spatial scales, and thereby ask whether our current understanding of individual-scale processes is sufficient to explain the observed spatiotemporal variation in forest composition. This approach depends on very large, recently-released forest inventory data sets, together with Bayesian statistics, and rapid computation, which may help to explain why the approach as not been attempted before. In addition, we have found it necessary to develop two new theoretical frameworks. The first is a new forest canopy model, which we generated from previous models by adding an increased level of growth plasticity. Curiously, this more realistic model turns out to be much simpler than previous formulations, and allows forest gap models to be implemented extremely rapidly over century timescales. The second is a new statistical technique that forces species' parameters to lie within a low-dimensional manifold, defined by a small number of key life-history strategy axes; with the axes themselves defined entirely by the data, rather than from theoretical expectation. Thus, we aim to build a theory from the ground up. We present recent results yield by this approach, including new trade-off axes, and ask whether, and how, they relate to existing ideas in theoretical ecology.
Key words: Modeling, Forests, Trees