Model of strategies of tree carbon allocation to roots, foliage and defense in relation to environmental conditions.

摘要

Study of the effects of changing nutrient input on plant-soil nutrient interactions led us to consider three general questions regarding the relationship between carbon, or energy, flow, nutrients, and plant carbon allocation strategies. (1) We addressed the question of whether a plant energy (or carbon) allocation strategy that minimizes the available limiting nutrient in soil solution is also the strategy that maximizes of energy flow through the plant, as conjectured by Lotka (1922) in his Maximum Energy Flux (Power) Principle. (2) We addressed whether such patterns can be explained, despite their apparent inconsistency with what would be expected from the R* Rule; that is, a asked whether optimal plant defense allocation strategies could be found under a range of conditions of nutrient availability, shading, and herbivory. . We minimization of limiting nutrient. (3) We asked whether optimal plant defense allocation strategies could be found under a range of conditions of nutrient availability, shading, and herbivory.;To answer the first question, I used a 'basic' model, revised from a literature model, G'DAY (Comins and McMurtrie 1993) to study how a tree should allocate its energy (or carbon) resources between foliage, roots, and wood in a way that maximizes its growth rate and maximizes its competitive fitness. In our model, primary productivity, G, corresponded to energy flow, and steady state soil porewater limiting nutrient concentration, N*pore, corresponded to R*. I found that the allocation strategy, SMinR*, that leads to Min(N*pore), is the same as the strategy, SMaxG_root, for which energy flux to roots is maximized. That allocation strategy, however, is different from the strategy, SMaxG, that produces maximum power, or maximum photosynthetic rate, for the whole plant system, Max(G). Hence, we conclude that Min(N*pore) and Max(G) should not necessarily co-occur in an ecological system, although they will be related.;To answer the second question, I then extended the approach of my first research to the landscape level, using the Everglades pattern of tree islands in an oligotrophic marsh as an example. Nutrient cycling in the Everglades involves not only the vertical recycling of nutrients at specific locations in space, but also biologically driven horizontal fluxes between different areas of the landscape. This latter process can result in net accumulation of nutrients in some places, such as tree islands, and net losses in others, the surrounding marsh. We examined the effects of such nutrient-concentrating fluxes on the relationship between limiting nutrient concentration and energy flow in tree islands. To study this system, we again used the G'DAY model of plant growth and nutrient cycling in which both nutrients and light may limit growth, with plants allocating carbon and nutrients between foliage and roots according to different strategies. We incorporated in the model the assumption that biological processes may transport nutrients horizontally on the landscape. We assumed, in particular, that these processes can draw nutrients from outside the zone of local recycling in a high biomass zone at a rate proportional to the local biomass density. Analysis showed that at sites where there is a sufficient rate of biomass-dependent input of nutrients, the plant species with the highest biomass production rates (roughly corresponding to the best competitors) do not reduce locally available nutrients to a minimum concentration level (that is, minimum R*), as expected from the R* rule, but instead maximize local nutrient concentration.;To test the last question, I extended the same model further to include both herbivory and the allocation to carbon-based chemical defenses and I studied the tradeoff between carbon invested in biomass growth (foliage, roots and structural wood) and plant defense. I assumed that the plant could expend some fraction of its net intake of carbon to produce secondary chemicals and that defense chemicals are purely carbon based and do not involve nutrients such as nitrogen in any significant amount. We simplified the problem by not assuming any ontogenetic effects of toxin production, or induction of defense, but rather a continuous rate of toxin production as a proportion of the photosynthetic rate that the plant could control. We also assumed that the effect of the defense chemicals was simply to slow down feeding by the herbivore. The model does not explicitly include the effect of the toxin on herbivore mortality. Our results are preliminary, but are able to corroborate some of the predictions of Coley et al. (1985), including that under low nutrient input condition, a high level of allocation to plant defenses may be needed for plant survival. Although there are many limitations in this study, our research still proved that modeling may provide a way of testing how environmental factors influence the investment of carbon into defense. (Abstract shortened by UMI.)