Summary Seventeen global models of terrestrial biogeochemistry were compared with respect to annual and seasonal fluxes of net primary productivity (NPP) for the land biosphere. The comparison, sponsored by IGBP‐GAIM/DIS/GCTE, used standardized input variables wherever possible and was carried out through two international workshops and over the Internet. The models differed widely in complexity and original purpose, but could be grouped in three major categories: satellite‐based models that use data from the NOAA/AVHRR sensor as their major input stream (CASA, GLO‐PEM, SDBM, SIB2 and TURC), models that simulate carbon fluxes using a prescribed vegetation structure (BIOME‐BGC, CARAIB 2.1, CENTURY 4.0, FBM 2.2, HRBM 3.0, KGBM, PLAI 0.2, SILVAN 2.2 and TEM 4.0), and models that simulate both vegetation structure and carbon fluxes (BIOME3, DOLY and HYBRID 3.0). The simulations resulted in a range of total NPP values (44.4–66.3 Pg C year–1), after removal of two outliers (which produced extreme results as artefacts due to the comparison). The broad global pattern of NPP and the relationship of annual NPP to the major climatic variables coincided in most areas. Differences could not be attributed to the fundamental modelling strategies, with the exception that nutrient constraints generally produced lower NPP. Regional and global NPP were sensitive to the simulation method for the water balance. Seasonal variation among models was high, both globally and locally, providing several indications for specific deficiencies in some models.

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Kumar and Monteith's (1981) model for the remote sensing of crop growth has been used to estimate continental net primary productivity (NPP) as well as its seasonal and spatial variations. The model assumes a decomposition of NPP into independent parameters such as incident solar radiation (S0), radiation absorption efficiency by canopies (ƒ), and conversion efficiency of absorbed radiation into organic dry matter (e). The precision on some of the input parameters has been improved, compared to previous uses of this model at a global scale: remote sensing data used to derive ƒ have been calibrated, corrected of some atmospheric effects, and filtered; e has been considered as biome‐dependent and derived from literature data. The resulting global NPP (approximatively 60 GtC per year) is within the range of values given in the literature. However, mean NPP estimates per biome do not agree with the literature (in particular, the estimation for tropical rain forests NPP is much lower and for cultivations much higher than field estimates), which results in zonal and seasonal variations of continental NPP giving more weight to the temperate northern hemisphere than to the equatorial zone.

Summary Twelve global net primary productivity (NPP) models were compared: BIOME3, CASA, CARAIB, FBM, GLO‐PEM, HYBRID, KGBM, PLAI, SDBM, SIB2, SILVAN and TURC. These models all use solar radiation as an input, and compute either absorbed solar radiation directly, or the amount of leaves used to absorb solar radiation, represented by the leaf area index (LAI). For all models, we obtained or estimated photosynthetically active radiation absorbed by the canopy (APAR). We then computed the light use efficiency for NPP (LUE) on an annual basis as the ratio of NPP to APAR. We analysed the relative importance for NPP of APAR and LUE. The analyses consider the global values of these factors, their spatial patterns represented by latitudinal variations, and the overall grid cell by grid cell variability. Spatial variability in NPP within a model proved to be determined by APAR, and differences among models by LUE. There was a compensation between APAR and LUE, so that global NPP values fell within the range of ‘generally accepted values’. Overall, APAR was lower for satellite driven models than for the other models. Most computed values of LUE were within the range of published values, except for one model.

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.