Energy Conversion and Use in Forests: An Analysis of Forest Production in Terms of Radiation Utilisation Efficiency (ɛ)

Abstract

The linear relationship between the photosynthetically active solar radiation (PAR) absorbed by forest canopies (APAR) and the production of dry mass by forests provides a simple, robust model with only one parameter for the estimation of forest production. The slope of the relationship is normally denoted E. The E model has been developed from plant production studies and is soundly based physiologically. It has also evolved from remote sensing studies. Although the relationship between APAR and canopy photosynthesis may be highly variable over short periods, it remains constant over longer periods, such as months or seasons.The effectiveness with which canopies convert energy into dry mass depends on environmental conditions such as temperature, water status and nutrition. Values of E derived experimentally, in terms of net primary production (NPP) and APAR, range from 2.8 g Mr 2 for agricultural crops to a low value of 0.2 g Mr 2 for tropical rainforests. Values for other forests tend to lie in the range of 1-2 g Mr 2 .Modifying factors with values between 0 and 1, dependent upon the availability of water in the soil, atmospheric vapour pressure deficits or nutrition, are used to account for the effects of these variables on E. If the modifiers are applied to E, the result is an estimate of potential E. Analysis of experimental results, therefore, should lead to the identification of optimum, unconstrained values of E, which may vary considerably less than the current experimental values.Since the proportion of incident energy absorbed by a plant canopy depends on the leaf area index (L*) of the canopy, good estimates of L* provide a sound basis for estimating APAR. Strong statistical relationships exist between reflectance ratios in the infrared, near-infrared and visible spectra, monitored from space, and L*, but these vary with vegetation type and surface conditions. More important are recent developments showing that the fraction of incoming energy absorbed by a canopy can be calculated directly from canopy reflectance properties measured from space. These allow direct application of the E model. As our knowledge of the factors causing variation in radiation utilisation by canopies improves, along with our capacity to The Use of Remote Sensing in the Modeling of Forest Productivityestimate environmental conditions and their modifying effects on radiation utilisation, it should be possible to use the £ model with remotely sensed data to estimate forest productivity over large areas.

Photosynthesis and reflectance indices for rainforest species in ecosystems undergoing progression and retrogression along a soil fertility chronosequence in New Zealand

“…The relationship between R aND-VI and Nm is attributable to the close association of foliage nitrogen and chlorophyll concentrations and thus absorption of red energy for photosynthesis by chlorophyll Merzlyak 1994, 1996). However, during periods of stress, R aNDVI is generally considered to be more closely associated with photosynthetic capacity than with actual photosynthesis rate because other processes limiting photosynthesis have little effect on the R aNDVI wavebands (Landsberg et al 1997). Although there is no mechanistic explanation for the strong relationship between R aNDVI and P m , it is most likely that the correlation is attributable to the effects of phosphorus deficiency resulting in reduced rates of electron transport, light-use efficiency and photosynthesis, as observed by Conroy et al (1986) with Pinus radiata D. Don.…”

Tower-Based Validation and Improvement of MODIS Gross Primary Production in an Alpine Swamp Meadow on the Tibetan Plateau

“…where ε is the PAR conversion efficiency (Kg C MJ´1) [47]. The two parameters for Tmin and the two parameters for VPD are used to calculate the scalars that attenuate ε max to produce the final ε (Equation (2)) [11].…”

The use of remote sensing in light use efficiency based models of gross primary production: A review of current status and future requirements

“…The use of a simple lookup table approach to determining from biome-specific parameters which do not vary in space and time (Running et al, 2000;Heinsch et al, 2002;Turner et al, 2003a), and distinguish only between 11 different vegetation types (Turner et al, 2003a;Heinsch et al, 2006) has been identified as the weak point of the GPP product as it greatly simplifies the existing spatial and temporal variability in . In addition, assigning values of on the basis of biome type assumes between-biome variability to be greater than within biome variability, which is often not realistic (Goetz and Prince, 1996;Landsberg et al, 1997). A further serious limitation is the degree to which the GCM derived inputs represent realistic estimates of climate variables because of the coarse scale of the GCM model outputs (~100 km) (Turner et al, 2003a,b).…”