OOS 31-10 - Roots are weapons: Game theory of fine-root investment from a whole-plant perspective; theoretical predictions and empirical challenges

Wednesday, August 10, 2011: 4:40 PM
15, Austin Convention Center
Ray Dybzinski1, Caroline E. Farrior2 and Stephen W. Pacala2, (1)Princeton University, Princeton, NJ, (2)Ecology and Evolutionary Biology, Princeton University, Princeton, NJ
Background/Question/Methods

Most of the theory that has been developed to understand allocation of photosynthate to fine roots has taken an “optimality” framework, asking what fine root allocation strategy will maximize a plant’s growth rate in isolation. But winning strategies are not necessarily “optimal” in this sense because fine roots also affect the resource availability experienced by other individuals. Moreover, treatment of aboveground processes or population-level demography is often absent, potentially skewing our understanding of what are ultimately coordinated whole-plant, whole-lifecycle strategies. 

Results/Conclusions

We review recent and breaking theoretical results from models that take a whole-plant, full-demography, game-theoretic framework, with explicit consideration of the effects of fine root allocation on resource availability. Plants tend to invest more in fine roots in this framework than they are expected to in the “optimality” framework described above in order to create resource availabilities that prevent individuals with any alternative strategy from prevailing. We demonstrate that runaway investment in fine roots is only prevented by factors that would seem to have little direct effect on fine root allocation, such as light limitation or periodic release from water limitation. In general, we suggest that, unlike leaves for which an “optimality” framework is often appropriate, fine roots will almost always employ game theoretic strategies that are strictly competitive in nature and thus will appear non-adaptive when viewed in isolation. In the coda, we highlight the critical trade-offs in fine root function and construction that are necessary for the next generation of whole-plant models and for which empirical information is lacking or conflicting.

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