Overview..
The measurement of absorbed photosynthetically active radiation (APAR) using remotely sensed reflectance in the red and near infrared has been the subject of a great deal of research in the past decade. The ratio of NPP to APAR (often called the production "efficiency", units g MJ-1, here called PAR Utilization) has become a research focus because of its implications for the use of remote sensing to estimate NPP. If the values of PAR utilization are similar for all plant types and biomes, then the task of NPP estimation with remote sensing is simplified because NPP would be directly proportional to light harvesting. If, however, values vary widely, then representative values may have to be determined for each vegetation type or biome on a case by case basis. Assigning values of PAR utilization assumes between-biome variability is greater than within-biome variability, which may not be realistic (it even varies substantially between types of plants). Alternatively ecophysiological simulation models, requiring explicit parameterizations, for which a number of nontrivial assumptions are required, may be used in conjunction with the remote sensing observations to derive values of PAR utilization (see the results of another paper that took this approach).
Objectives and Approach..
It has been suggested that limited resource availability in the natural environment and high resource acquisition costs result in an optimization of resource allocation by plants through evolutionary selection, which results in a narrow range of PAR Utilization and maximization of carbon gain. If true, this "functional convergence" hypothesis (summarized below) would provide strong theoretical support for an interpretation of the observed correlation between remotely sensed APAR and NPP in terms of evolutionary optimization. This paper explores the evidence for such convergence and the implications for global estimation of NPP using remote sensing. We have examined the hypothesis in the context of remote sensing of NPP through an integration of inter-disciplinary research on resource-based growth constraints (stresses) and associated resource trade-offs, the costs versus benefits of various allocation strategies (particularly growth versus defense allocation), the evidence for optimization of resource-use efficiency and the associated evidence for maximization of carbon gain and fitness.
The Functional Convergence Hypothesis
The functional convergence hypothesis states that plant canopy light harvesting is scaled to the availability of all others resources such that "biochemical capacity for CO2 fixation is curtailed whenever a limitation in the availability of any resource prevents the efficient exploitation of additional capacity" (Field 1991). In other words, plants do not have unusable excess photosynthetic capacity because selection favors investment in acquisition of the most limiting resource and not in additional photosynthetic machinery. Because different plant adaptive strategies, or plant functional types, have adapted to different environmental conditions, this implies that the scaling of light harvesting to resource availability is independent of the nature of the limiting resource. In essence, the functional convergence hypothesis states that resource shortages of any sort will lead to adjustments of light capture, hence light capture serves as an integrator of resource status and biochemical capacity for CO2 assimilation.
Summary and Implications
The journal publication discusses these conclusions in some detail - a brief summary is provided here. A great deal of evidence suggests that natural selection results in closely related suites of traits which, acting together, confer fitness through optimized resource use. Several traits have been identified as "ecological integrators" that characterize functional types and their associated allocation of resources. Remotely sensed spectral vegetation indices, which are linked to foliage display and light absorption by vegetation, are thus linked with many other plant traits. These traits reflect trade-offs in costs versus benefits of resource acquisition, allocation and utilization. Resource-use optimization was most evident on a leaf mass basis, rather than on a leaf area or volume basis, and thus provides an index of the costs of resource acquisition.
The evidence for optimization of resource use suggests that a maximization of carbon gain can be equated with a maximization of fitness. The allocation of assimilated carbon, however, varies by growth strategy such that differences in respiratory costs relative to carbon gain do not result in a convergence on a narrow range in en among plant species. For example, proportionately more resources are allocated to non-photosynthetic components in long-lived plant functional types adapted to resource-poor environments, which in turn results in greater respiratory costs relative to carbon gain. Thus decoupling of light harvesting and utilization may occur via biochemical channels, which affects the linkages between maximized carbon assimilation, en, and production models driven by light absorption. Short-term decoupling may also be introduced by a combination of stomatal, canopy and boundary layer resistances.
Two important factors which may act to decouple light harvesting and carbon assimilation from NPP and en have thus been confirmed: short-term stomatal control and canopy coupling with the atmosphere, and longer-term respiratory carbon costs in relation to assimilatory carbon gains (respiration efficiency). Limitations of the functional convergence hypothesis with respect to short-term decoupling of carbon assimilation and light harvesting has been noted by Field (1991), but the longer-term decoupling associated with respiration efficiency has not previously been discussed. We have shown that en varies among functional types primarily as a result of differences in respiration efficiency associated with different resource allocation strategies. This finding limits the direct applicability of the functional convergence hypothesis with respect to net primary production modeling with net PAR utilization. We have instead presented evidence for convergence in the amount of carbon assimilation per unit APAR (gross PAR utilization), and noted links between this term and the quantum yield of photosynthesis, a measure of maximum biochemical capacity for CO2 assimilation. We therefore reject the functional convergence hypothesis with respect to convergence in net PAR utilization and accept it in relation to gross PAR utilization. This is in accordance with Field's initial theory and does not diminish its utility with respect to NPP modeling. Rather, it focuses the application of the hypothesis on that aspect of NPP modeling where it most benefits the accurate determination of global primary production - the determination of gross PAR utilization.
These conclusions are based on a survey of the existing literature of plant ecophysiology, biophysics and evolutionary biology, all of which are rapidly expanding fields contributing to Earth system science and global change biology. They should be tested further with additional measurements of light absorption and whole-ecosystem production, as such data become available. It is particularly important to examine respiratory costs in relation to carbon gains for a range of resource allocation strategies if accurate monitoring of global NPP with satellite remote sensing is to be realized.
The research discussed here has been published in the following publications:
S.J.Goetz and S.D.Prince, 1999, Modeling terrestrial carbon exchange and storage: the evidence for and implications of functional convergence in light use efficiency, Advances in Ecological Research, 28 : 57-92.
Goetz, S. J. and S. D. Prince. 1996. Remote sensing of net primary production in boreal forest stands, Agricultural and Forest Meteorology 78 (3): 149-179.
Goetz, S. J. and S. D. Prince. 1998. Variability in carbon exchange and light utilization among boreal forest stands: implications for remote sensing of net primary production,, Canadian Journal of Forest Research 28(3):375-389.