Identification of a general light use efficiency model for gross primary production

Horn, Judith; Schulz, Karsten

doi:10.5194/bg-8-999-2011

Cited by 38 publications

(34 citation statements)

References 141 publications

(152 reference statements)

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“…EF and AET/PET, as integrated moisture index at ecosystem scale, had the greatest explanation capability for LUE (50–70%) at both sites. Similar results were found by Yuan et al [7], Garbulsky et al [11], and Horn and Schulz [15]. LUE was linearly and positively correlated with EF and AET/PET at both sites; however, slopes of these relationships differed significantly between sites (ANCOVA; for EF, F 1,76 = 25.304, P<0.001; for AET/PET, F 1,76 = 37.979, P<0.001) (Fig.…”

Section: Resultssupporting

confidence: 87%

Light Use Efficiency over Two Temperate Steppes in Inner Mongolia, China

Wang

Zhou

2012

PLoS ONE

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Vegetation light use efficiency (LUE) is a key parameter of Production Efficiency Models (PEMs) for simulating gross primary production (GPP) of vegetation, from regional to global scales. Previous studies suggest that grasslands have the largest inter-site variation of LUE and controlling factors of grassland LUE differ from those of other biomes, since grasslands are usually water-limited ecosystems. Combining eddy covariance flux data with the fraction of photosynthetically active radiation absorbed by the plant canopy from MODIS, we report LUE on a typical steppe and a desert steppe in Inner Mongolia, northern China. Results show that both annual average LUE and maximum LUE were higher on the desert steppe (0.51 and 1.13 g C MJ−1) than on the typical steppe (0.34 and 0.88 g C MJ−1), despite the higher GPP of the latter. Water availability was the primary limiting factor of LUE at both sites. Evaporative fraction (EF) or the ratio of actual evapotranspiration to potential evapotranspiration (AET/PET) can explain 50–70% of seasonal LUE variations at both sites. However, the slope of linear regression between LUE and EF (or AET/PET) differed significantly between the two sites. LUE increased with the diffuse radiation ratio on the typical steppe; however, such a trend was not found for the desert steppe. Our results suggest that a biome-dependent LUEmax is inappropriate, because of the large inter-site difference of LUEmax within the biome. EF could be a promising down-regulator on grassland LUE for PEMs, but there may be a site-specific relationship between LUE and EF.

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Section: Resultssupporting

confidence: 87%

Light Use Efficiency over Two Temperate Steppes in Inner Mongolia, China

Wang

Zhou

2012

PLoS ONE

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“…Models based on the LUE principle continue to be developed and compared, now most commonly in terms of their ability to reproduce GPP as derived from CO 2 flux measurements (see e.g. Cheng et al, 2014;McCallum et al, 2009McCallum et al, , 2013Verma et al, 2014;Horn and Schulz, 2011;Yuan et al, 2007Yuan et al, , 2013. Their popularity depends on the fact that green-vegetation cover in LUE models is directly provided from satellite observations, thus sidestepping one of the most serious limitations of current dynamic global vegetation models (DGVMs), namely their (in)ability to realistically predict spatial and temporal patterns of green-vegetation cover (Kelley et al, 2013).…”

Section: Implications For Modelling Strategymentioning

confidence: 99%

Biophsyical constraints on gross primary production by the terrestrial biosphere

2014

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Abstract. Persistent divergences among the predictions of complex carbon-cycle models include differences in the sign as well as the magnitude of the response of global terrestrial primary production to climate change. Such problems with current models indicate an urgent need to reassess the principles underlying the environmental controls of primary production. The global patterns of annual and maximum monthly terrestrial gross primary production (GPP) by C 3 plants are explored here using a simple first-principles model based on the light-use efficiency formalism and the Farquhar model for C 3 photosynthesis. The model is driven by incident photosynthetically active radiation (PAR) and remotely sensed green-vegetation cover, with additional constraints imposed by low-temperature inhibition and CO 2 limitation. The ratio of leaf-internal to ambient CO 2 concentration in the model responds to growing-season mean temperature, atmospheric dryness (indexed by the cumulative water deficit, E) and elevation, based on an optimality theory. The greatest annual GPP is predicted for tropical moist forests, but the maximum (summer) monthly GPP can be as high, or higher, in boreal or temperate forests. These findings are supported by a new analysis of CO 2 flux measurements. The explanation is simply based on the seasonal and latitudinal distribution of PAR combined with the physiology of photosynthesis. By successively imposing biophysical constraints, it is shown that partial vegetation cover -driven primarily by water shortage -represents the largest constraint on global GPP.

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“…It is based on the principle, derived from theoretical expectations and syntheses of canopy-scale measurements (Healey et al, 1998;Hollinger et al, 1994;Kanniah et al, 2012;Niyogi et al, 2005;Norman, 1993;Roderick et al, 2001;Urban et al, 2007), that the efficiency of carbon uptake is usually higher under diffuse light conditions that accompany cloudy and/or hazy skies than it is under clear sky conditions. The underlying mechanism for this increase in efficiency is the increased penetration of light into deeper layers in the canopy under diffuse light conditions such that substantially more leaves operate in partial light conditions -under which photosynthesis is inherently more efficient -rather than in deep shade or saturated light (Campbell & Norman, 2000;Farquhar & Roderick, 2003;Gu et al, 2002;Horn & Schulz, 2011;Kanniah et al, 2013;Kanniah et al, 2012;Mercado et al, 2009;Roderick et al, 2001;Spitters, 1986;Williams et al, 2014). This phenomenon has been widely incorporated into bio-physical canopy models (Alton et al, 2007;Anderson et al, 2000;Choudhury, 2000Choudhury, , 2001ade Pury & Farquhar, 1997;Hammer & Wright, 1994;Jenkins et al, 2007;Norman, 1980;Norman & Arkebauer, 1991;Sinclair et al, 1992;Wang & Leuning, 1998).…”

mentioning

confidence: 95%