Photosynthesis is a critical parameter in ecological research. Not only does it drive productivity at the eco- system scale, but at the level of species and the individual plant it is functionally related to growth and a suite of co-evolved traits that are critical to plant function, including hydraulic conductance, leaf lifespan, specific leaf area, and leaf nitrogen content. Chlorophyll (Chl) fluorescence provides a useful, direct, and integrated measure of photosynthetic function and plant stress making it a valuable tool for plant ecologists for use at the leaf level to the ecosystem level. At the leaf and whole plant level, the most useful parameters for ecologi- cal use in tracking photosynthetic performance and stress in plants are the potential quantum efficiency of photosynthesis, calculated from the ratio of two fluorescence parameters Fv (variable Chl fluorescence) /Fm (maximum Chl fluorescence) in a dark adapted leaf, and the quantum yield, ΔF/Fm ́, where ΔF is variable Chl fluorescence and Fm ́ is maximum Chl fluorescence in an illuminated leaf. The ratio of electron transport rates (ETR) to carbon assimilation rate, A (ETR/A) may also be an increasingly useful and easily measured parameter. Other parameters, including the ratio of UV excited blue fluorescence (BF) to Chl fluorescence, (BF/ChlF),are also becoming more widely used for the detection of plant stresses in response to various environmental factors. At the ecosystem level, reflectance indices of vegetation and carbon flux data from eddy correlation towers are currently used in large-scale productivity models. Chl fluorescence from vegetation can provide a direct measure of radiation use efficiency (RUE), making it promising for use in ecosystem level models, given continued development of technology for remote measurements. The role of individual species, which respond in contrasting ways to environmental disturbance, is critical to ecosystem dynamics. Remote measure- ment of fluorescence parameters may eventually be able to distinguish different species or functional groups within an ecosystem allowing species composition to be taken into account in large-scale models. This would allow a mechanistic understanding of ecosystem processes and provide a greater ability to predict changes in ecosystem function from perturbations that differentially affect species.
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