Direct and indirect estimation of leaf area index, f(APAR), and net primary production of terrestrial ecosystems

A primary objective of the Earth Observing System (EOS) is to develop and v alidate algorithms to estimate leaf area index (L), fraction of absorbed ph otosynthetically active radiation (f(APAR)) and net primary production (NPP ) from remotely sensed products. These three products are important because they relate to or are components of the metabolism of the biosphere and ca n be determined for terrestrial ecosystems from satellite-borne sensors. Th e importance of these products in the EOS program necessitates the need to use standard methods to obtain accurate ground truth estimates of L, f(APAR ), and NPP that are correlated to satellite-derived estimates. The objectiv e of this article is to review; direct and indirect methods used to estimat e L, f(APAR) and NPP in terrestrial ecosystems. Direct estimates of L, biom ass, and NPP can be obtained by harvesting individual plants, developing al lometric equations, and applying these equations to all individuals in the stand. Using non-site-specific allometric equations to estimate L and folia ge production can cause large errors because carbon allocation to foliage i s influenced by numerous environmental and ecological factors. All of the o ptical instruments that indirectly estimate L actually estimate "effective" leaf area index (L-E) and underestimate L when foliage in the canopy is no n-randomly distributed (i.e., clumped). We discuss several methods, ranging from simple to complex in terms of data needs, that can be used to correct estimates of L when foliage is clumped. Direct estimates of above ground a nd below-ground net primary production (NPPA and NPPB, respectively) are la borious, expensive and can only be carried out for small plots, yet there i s a great need to obtain global estimates of NPP. Process models, driven by remotely sensed input parameters, are useful tools to examine the influenc e of global change on the metabolism of terrestrial ecosystems, but an inco mplete understanding of carbon allocation continues to hamper development o f more accurate NPP models. We summarize cal-bon allocation patterns for ma jor terrestrial biomes and discuss emerging allocation patterns that can be incorporated into global NPP models. One common process model, light use e fficiency or epsilon model, uses remotely sensed f(APAR), light use efficie ncy (LUE) and carbon allocation coefficients, and other meteorological data to estimates NPP. Such models require reliable estimates of LUE. We summar ize the literature and provide LUE coefficients for the major biomes, being careful to correct for inconsistencies in radiation dry matter and carbon allocation tl nits. (C) Elsevier Science Inc., 1999.