TURC: A diagnostic model of continental gross primary productivity and net primary productivity

Abstract

TURC, a diagnostic model for the estimation of continental gross primary productivity (GPP) and net primary productivity (NPP), is presented. This model uses a remotely sensed vegetation index to estimate the fraction of solar radiation absorbed by canopies, and an original parameterization of the relationship between absorbed solar radiation and GPP, based on measurements of CO2 fluxes above plant canopies. An independent, uncalibrated model of autotrophic maintenance and growth respiration is parameterized from literature data, and uses databases on temperature, biomass, and remotely sensed vegetation index. This model results in global estimates of GPP and NPP of 133.1 and 62.3 Gt(C) per year, respectively, which is consistent with commonly admitted values. The ratio of autotrophic respiration to GPP is about 70% for equatorial rain forests and 50% for temperate forests, as a result the highest predicted NPP are in tropical savannas of Africa and South America, and in temperate, highly cultivated zones of North America, not in equatorial rain forest zones. Conversion efficiencies defined as the ratio of yearly integrated NPP to absorbed photosynthetically active radiation (PAR) compare relatively well with a previous compilation of literature values, except for ecosystems with probable reduction of conversion efficiency due to water stress. Several sensitivity studies are performed on some input data sets, model assumptions, and model parameters.

A dynamic global vegetation model for studies of the coupled atmosphere‐biosphere system

“…The maintenance respiration coefficient (i.e., the fraction of biomass that is lost during a given time interval) increases linearly with temperature (air temperature for aboveground plant tissues; root-zone temperature for belowground tissues). Observations indicate that respiration of tropical plants is less sensitive to temperature than that of temperate or boreal plants [Ruimy et al, 1996]. This is a problem for grasses in ORCHIDEE, as tropical, temperate, and boreal C 3 grasses are represented by only one generic PFT (see list of PFTs in Table 1).…”

“…[128] Autotrophic respiration is calculated following Ruimy et al [1996]. The maintenance respiration R m for living plant compartments (except leaves) is calculated as…”

“…[46] The formulation of autotrophic respiration is based on work by Ruimy et al [1996]. The maintenance respiration R m for living plant compartments is basically calculated as a function of temperature and biomass, and as a function of the (prescribed) nitrogen/carbon ratio of each tissue.…”

The potential of the MERIS Terrestrial Chlorophyll Index for carbon flux estimation

“…Whilst such models show great promise, their applicability at regional and global scales is challenging due to their complexity and requirements for data that are often scarce or unavailable at the appropriate spatial and temporal scales. Carbon flux models that are driven by remotely sensed observations can be used to estimate gross primary productivity (GPP) frequently and over large areas; for example the NASA Carnegie-Ames-Stanford (NASA-CASA) model (Potter et al 1993), the Terrestrial Uptake and Release of Carbon (TURC) model (Ruimy et al 1996) and the Moderate Resolution Imaging Spectrometer Global Primary Productivity (MODIS-MOD17 GPP) model (Running et al 2004)). The vast majority of satellite-based models are 'Production Efficiency Models' (PEMs) based on the light use (LUE) efficiency concept for conversion of absorbed photosynthetically active radiation (APAR) into biomass (Monteith 1977).…”

Towards harmonizing competing models: Russian forests' net primary production case study

“…constitute the only tool for capturing the drivers of the ecosystems functioning. Cramer et al (1999) presented cross-comparison of the NPP estimates provided by 17 DGVMs combined in three groups: (a) satellite-based models whose variables are derived from remote sensing data, including CASA (Potter et al, 1993), GLO-PEM (Prince, 1991), SDBM (Knorr and Heiman, 1995), TURC (Ruimy et al, 1996), SIB2 (Sellers et al, 1996a,b); (b) models for assessment of biogeochemical fluxes, including HRBM (Esser and Lautenschlager, 1994), CENTURY (Parton et al, 1993), TEM (McGuire et al, 1995), CARAIB (Warnant et al, 1994), FBM (Ludeke et al, 1994), PLAI (Plöchl and Cramer, 1995a,b), SILVAN (Kaduk and Heimann, 1996), BIOME-BGC (Running and Hunt, 1993), KGBM (Kergoat, 1998), and (c) models for assessment of seasonal biogeochemical fluxes and vegetation structures, including BIOME3 (Haxeltine and Prentice, 1996), DOLY (Woodward et al, 1995) and HYBRID (Friend et al, 1997). In the cross-comparison exercise, the models use standardized input data (climate, soil texture data and normalized difference vegetation index (NDVI) by 0.5º grid at a monthly temporal resolution scale), being substantially different in definitions of the underlying NPP production processes.…”