DESPOT, a process-based tree growth model that allocates carbon to maximize carbon gain.

We present a new model of tree growth, DESPOT (Deducing Emergent Structure and Physiology Of Trees), in which carbon (C) allocation is adjusted in each time step to maximize whole-tree net C gain in the next time step. Carbon gain, respiration and the acquisition and transport of substitutable photosynthetic resources (nitrogen, water and light) are modeled on a process basis. The current form of DESPOT simulates a uniform, monospecific, self-thinning stand. This paper describes DESPOT and its general behavior in comparison to published data, and presents an evaluation of the sensitivity of its qualitative predictions by Monte Carlo parameter sensitivity analysis. DESPOT predicts determinate height growth and steady stand-level net primary productivity (NPP), but slow declines in aboveground NPP and leaf area index. Monte Carlo analysis, wherein the model was run repeatedly with randomly different parameter sets, revealed that many parameter sets do not lead to sustainable NPP. Of those that do lead to sustainable growth, the ratios at maturity of net to gross primary productivity and of leaf area to sapwood area are highly conserved.