Biophsyical constraints on gross primary production by the terrestrial biosphere

Wang, Han; Prentice, Iain Colin; Davis, T. W.

doi:10.5194/bg-11-5987-2014

Cited by 69 publications

(36 citation statements)

References 81 publications

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“…The coordination hypothesis is also invoked by the new "first-principles" global primary production model developed by Wang et al (2014) and further elaborated and tested by Wang et al (2017). However, there are several steps between these models and the potentially wider application of the coordination hypothesis in physical land surface and Earth System modelling.…”

Section: Implications For Modellingmentioning

confidence: 99%

“…The LPJ model requires daily or monthly inputs and assumes complete acclimation on monthly timescales. Wang et al (2014Wang et al ( , 2017 implemented their model on monthly time steps. Modelling diurnal cycles would require a separation of timescales, such that photosynthetic capacities would be near-constant over a diurnal cycle but would vary gradually in response to the seasonal cycle.…”

Section: Implications For Modellingmentioning

confidence: 99%

“…Modelling diurnal cycles would require a separation of timescales, such that photosynthetic capacities would be near-constant over a diurnal cycle but would vary gradually in response to the seasonal cycle. Thus, whereas Wang et al (2014Wang et al ( , 2017 could make V cmax and J max "disappear" from equations describing monthly primary production (because on this timescale they were considered to depend only on the environment), multitemporal applications will have to explicitly predict time-varying values of V cmax and J max depending on antecedent environmental conditions. Field measurements of photosynthetic parameters in different seasons are required to test these predictions .…”

Section: Implications For Modellingmentioning

confidence: 99%

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Thermal acclimation of leaf photosynthetic traits in an evergreen woodland, consistent with the coordination hypothesis

et al. 2018

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Abstract. Ecosystem models commonly assume that key photosynthetic traits, such as carboxylation capacity measured at a standard temperature, are constant in time. The temperature responses of modelled photosynthetic or respiratory rates then depend entirely on enzyme kinetics. Optimality considerations, however, suggest this assumption may be incorrect. The "coordination hypothesis" (that Rubisco-and electron-transport-limited rates of photosynthesis are co-limiting under typical daytime conditions) predicts, instead, that carboxylation (V cmax ) capacity should acclimate so that it increases somewhat with growth temperature but less steeply than its instantaneous response, implying that V cmax when normalized to a standard temperature (e.g. 25 • C) should decline with growth temperature. With additional assumptions, similar predictions can be made for electron-transport capacity (J max ) and mitochondrial respiration in the dark (R dark ). To explore these hypotheses, photosynthetic measurements were carried out on woody species during the warm and the cool seasons in the semi-arid Great Western Woodlands, Australia, under broadly similar light environments. A consistent proportionality between V cmax and J max was found across species. V cmax , J max and R dark increased with temperature in most species, but their values standardized to 25 • C declined. The c i : c a ratio increased slightly with temperature. The leaf N : P ratio was lower in the warm season. The slopes of the relationships between log-transformed V cmax and J max and temperature were close to values predicted by the coordination hypothesis but shallower than those predicted by enzyme kinetics.

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Section: Implications For Modellingmentioning

confidence: 99%

Section: Implications For Modellingmentioning

confidence: 99%

Section: Implications For Modellingmentioning

confidence: 99%

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Thermal acclimation of leaf photosynthetic traits in an evergreen woodland, consistent with the coordination hypothesis

et al. 2018

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“…For example, Wang et al (2014) have shown that a model explicitly derived from optimality considerations -the least-cost hypothesis of Wright et al (2003) and Prentice et al (2014), and the co-limitation or coordination hypothesis (e.g. Maire et al, 2012) -can predict global patterns of forest GPP without the need for PFT-specific parameters.…”

Section: C Prentice Et Al: Next-generation Land-surface Modellinmentioning

confidence: 99%

Reliable, robust and realistic: the three R's of next-generation land-surface modelling

et al. 2015

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Abstract. Land-surface models (LSMs) are increasingly called upon to represent not only the exchanges of energy, water and momentum across the land-atmosphere interface (their original purpose in climate models), but also how ecosystems and water resources respond to climate, atmospheric environment, land-use and land-use change, and how these responses in turn influence land-atmosphere fluxes of carbon dioxide (CO 2 ), trace gases and other species that affect the composition and chemistry of the atmosphere. However, the LSMs embedded in state-of-the-art climate models differ in how they represent fundamental aspects of the hydrological and carbon cycles, resulting in large inter-model differences and sometimes faulty predictions. These "thirdgeneration" LSMs respect the close coupling of the carbon and water cycles through plants, but otherwise tend to be under-constrained, and have not taken full advantage of robust hydrological parameterizations that were independently developed in offline models. Benchmarking, combining multiple sources of atmospheric, biospheric and hydrological data, should be a required component of LSM development, but this field has been relatively poorly supported and intermittently pursued. Moreover, benchmarking alone is not sufficient to ensure that models improve. Increasing complexity may increase realism but decrease reliability and robustness, by increasing the number of poorly known model parameters. In contrast, simplifying the representation of complex processes by stochastic parameterization (the representation of unresolved processes by statistical distributions of values) has been shown to improve model reliability and realism in both atmospheric and land-surface modelling contexts. We provide examples for important processes in hydrology (the generation of runoff and flow routing in heterogeneous catchments) and biology (carbon uptake by speciesdiverse ecosystems). We propose that the way forward for next-generation complex LSMs will include: (a) representations of biological and hydrological processes based on the implementation of multiple internal constraints; (b) systematic application of benchmarking and data assimilation techniques to optimize parameter values and thereby test the structural adequacy of models; and (c) stochastic parameterization of unresolved variability, applied in both the hydrological and the biological domains.

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“…However, the primary biochemical effect of CO 2 , which both these models ignore, is an increase in photosynthesis with rising CO 2 due to increased LUE 8 (although alternative LUE models account for this effect 9,10 The third remote-sensing based proxy for global NPP used in S15 was based on VOD, which is closely related to above-ground biomass. However, above-ground biomass (a state) is not the same thing as NPP (a flux).…”

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confidence: 99%

Satellite based estimates underestimate the effect of CO2 fertilization on net primary productivity

et al. 2016

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Smith et al.1 (hereafter S15) compared global estimates of net primary production (NPP) derived from satellites and earth system models (ESMs). They concluded thatESMs over-estimate the effect of CO 2 fertilisation on NPP. An overestimation by ESMs is possible 2 , but here we draw attention to the fact that the satellite-derived NPP estimates used in S15 are likely to underestimate the CO 2 fertilisation effect because they do not account for the primary effect of CO 2 on the biochemistry of photosynthesis. We also show that the calculation in S15 of the sensitivity of NPP to atmospheric CO 2 is misleading, invalidating the comparison with Free Air CO 2 Enrichment (FACE) data.Global NPP cannot be measured; however, by exploiting the observed linear relationship between NPP and absorbed photosynthetically active radiation (APAR) 3 , light use efficiency (LUE) models use satellite data to estimate NPP on a pixel basis.Although satellite-derived NPP estimates have often been treated as observations 4 , they are not 5 . S15 used three independent satellite-based proxies for NPP: a LUE model, a model tree ensemble (MTE 6 ) constrained by ecosystem carbon flux measurements, and remotely sensed vegetation optical depth (VOD 7 ). The LUE and MTE models assume that CO 2 affects NPP solely through changes in the observed fraction of absorbed radiation (fAPAR), which is closely related to leaf area.However, the primary biochemical effect of CO 2 , which both these models ignore, is an increase in photosynthesis with rising CO 2 due to increased LUE 8 (although alternative LUE models account for this effect 9,10 ). At the two longest-running forest

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Biophsyical constraints on gross primary production by the terrestrial biosphere

Cited by 69 publications

References 81 publications

Thermal acclimation of leaf photosynthetic traits in an evergreen woodland, consistent with the coordination hypothesis

Thermal acclimation of leaf photosynthetic traits in an evergreen woodland, consistent with the coordination hypothesis

Reliable, robust and realistic: the three R's of next-generation land-surface modelling

Satellite based estimates underestimate the effect of CO2 fertilization on net primary productivity

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