ORCID Profile
0000-0002-9546-0960
Current Organisations
E O Lawrence Berkeley National Laboratory
,
National University of Singapore
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Publisher: Springer Science and Business Media LLC
Date: 15-06-2023
DOI: 10.1038/S41559-023-02093-X
Abstract: The temperature sensitivity of ecosystem respiration regulates how the terrestrial carbon sink responds to a warming climate but has been difficult to constrain observationally beyond the plot scale. Here we use observations of atmospheric CO 2 concentrations from a network of towers together with carbon flux estimates from state-of-the-art terrestrial biosphere models to characterize the temperature sensitivity of ecosystem respiration, as represented by the Arrhenius activation energy, over various North American biomes. We infer activation energies of 0.43 eV for North America and 0.38 eV to 0.53 eV for major biomes therein, which are substantially below those reported for plot-scale studies (approximately 0.65 eV). This discrepancy suggests that sparse plot-scale observations do not capture the spatial-scale dependence and biome specificity of the temperature sensitivity. We further show that adjusting the apparent temperature sensitivity in model estimates markedly improves their ability to represent observed atmospheric CO 2 variability. This study provides observationally constrained estimates of the temperature sensitivity of ecosystem respiration directly at the biome scale and reveals that temperature sensitivities at this scale are lower than those based on earlier plot-scale studies. These findings call for additional work to assess the resilience of large-scale carbon sinks to warming.
Publisher: Springer Science and Business Media LLC
Date: 30-05-2022
Publisher: Springer Science and Business Media LLC
Date: 07-03-2022
DOI: 10.1038/S41467-022-28824-5
Abstract: The terrestrial carbon sink slows the accumulation of carbon dioxide (CO 2 ) in the atmosphere by absorbing roughly 30% of anthropogenic CO 2 emissions, but varies greatly from year to year. The resulting variations in the atmospheric CO 2 growth rate (CGR) have been related to tropical temperature and water availability. The apparent sensitivity of CGR to tropical temperature ( $${{{{{{\\rm{\\gamma }}}}}}}_{{{{{{\\rm{CGR}}}}}}}^{{{{{{\\rm{T}}}}}}}$$ γ CGR T ) has changed markedly over the past six decades, however, the drivers of the observation to date remains unidentified. Here, we use atmospheric observations, multiple global vegetation models and machine learning products to analyze the cause of the sensitivity change. We found that a threefold increase in $${{{{{{\\rm{\\gamma }}}}}}}_{{{{{{\\rm{CGR}}}}}}}^{{{{{{\\rm{T}}}}}}}$$ γ CGR T emerged due to the long-term changes in the magnitude of CGR variability (i.e., indicated by one standard deviation of CGR STD CGR ), which increased 34.7% from 1960-1979 to 1985-2004 and subsequently decreased 14.4% in 1997-2016. We found a close relationship (r 2 = 0.75, p 0.01) between STD CGR and the tropical vegetated area (23°S – 23°N) affected by extreme droughts, which influenced 6-9% of the tropical vegetated surface. A 1% increase in the tropical area affected by extreme droughts led to about 0.14 Pg C yr −1 increase in STD CGR . The historical changes in STD CGR were dominated by extreme drought-affected areas in tropical Africa and Asia, and semi-arid ecosystems. The outsized influence of extreme droughts over a small fraction of vegetated surface lified the interannual variability in CGR and explained the observed long-term dynamics of $${{{{{{\\rm{\\gamma }}}}}}}_{{{{{{\\rm{CGR}}}}}}}^{{{{{{\\rm{T}}}}}}}$$ γ CGR T .
Publisher: Wiley
Date: 04-09-2022
DOI: 10.1111/GCB.16404
Abstract: Large‐scale reforestation can potentially bring both benefits and risks to the water cycle, which needs to be better quantified under future climates to inform reforestation decisions. We identified 477 water‐insecure basins worldwide accounting for 44.6% (380.2 Mha) of the global reforestation potential. As many of these basins are in the Asia‐Pacific, we used regional coupled land‐climate modeling for the period 2041–2070 to reveal that reforestation increases evapotranspiration and precipitation for most water‐insecure regions over the Asia‐Pacific. This resulted in a statistically significant increase in water yield ( p .05) for the Loess Plateau–North China Plain, Yangtze Plain, Southeast China, and Irrawaddy regions. Precipitation feedback was influenced by the degree of initial moisture limitation affecting soil moisture response and thus evapotranspiration, as well as precipitation advection from other reforested regions and moisture transport away from the local region. Reforestation also reduces the probability of extremely dry months in most of the water‐insecure regions. However, some regions experience nonsignificant declines in net water yield due to heightened evapotranspiration outstripping increases in precipitation, or declines in soil moisture and advected precipitation.
Publisher: Research Square Platform LLC
Date: 02-2023
DOI: 10.21203/RS.3.RS-2501133/V1
Abstract: Photosynthesis of C 4 plants responds to climate change differently than the more common C 3 plants, due to their unique anatomic and biochemical characteristics. The different response is expected to cause a change in global C 4 distribution, however, current C 4 distribution models are inadequate to predict that as they are based on a temperature-only hypothesis and lack observational constraints. Here, we used a global database of photosynthetic pathways, satellite observations and a photosynthetic optimality theory to produce a new observation-constrained estimate of C 4 distribution. We found that global C 4 coverage stabilized at 11.2% of the vegetated land surface during 1992 to 2016, as a net effect of C 4 grass decrease due to elevated CO 2 and C 4 crop increase, mainly from maize expansion. Using an emergent constraint approach, we estimated that C 4 contributed 12.5% of global photosynthetic carbon assimilation, a value much lower than previous estimates (~ 20%) but more in line with the mean of an ensemble of dynamic global vegetation models (14 ± 13%). By improving the understanding of recent global C 4 dynamics, our study sheds insight on the critical and previously underappreciated role of C 4 plants in modulating the global carbon cycle in recent history.
Publisher: Copernicus GmbH
Date: 29-04-2022
Abstract: Abstract. The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecological research. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to Vcmax, based on plants’ optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis. These two independent global Vcmax products agree well (r2 = 0.79, RMSE = 15.46 μmol m-2 s-1, P 0.001) and compare well with 3672 ground-based measurements (r2 = 0.68, RMSE = 13.55 μmol m-2 s-1 and P 0.001 for SIF r2 = 0.55, RMSE = 17.55 μmol m-2 s-1 and P 0.001 for LCC). Through a data assimilation technique, these two types of Vcmax products from remote sensing are combined to provide an optimized Vcmax product. The global distributions of these products are compatible with Vcmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play a major role in global ecosystem research. The three remote sensing Vcmax products are available at 0.5281/zenodo.6466968 (Chen et al., 2020) and the code for implementing the ecological optimality theory is available at github.com/SmithEcophysLab/optimal_vcmax_R (Smith, 2020).
Publisher: Springer Science and Business Media LLC
Date: 08-12-2021
DOI: 10.1038/S41586-021-04096-9
Abstract: The global terrestrial carbon sink is increasing
Publisher: Copernicus GmbH
Date: 07-09-2022
DOI: 10.5194/ESSD-14-4077-2022
Abstract: Abstract. The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecological research. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to Vcmax, based on plants' optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite (GOME-2) observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilation technique. These two independent global Vcmax products agree well (r2=0.79,RMSE=15.46µmol m−2 s−1, P .001) and compare well with 3672 ground-based measurements (r2=0.69,RMSE=13.8µmol m−2 s−1 and P .001 for SIF r2=0.55,RMSE=18.28µmol m−2 s−1 and P .001 for LCC). The LCC-derived Vcmax product is also used to constrain the retrieval of Vcmax from TROPical Ozone Mission (TROPOMI) SIF data to produce an optimized Vcmax product using both SIF and LCC information. The global distributions of these products are compatible with Vcmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH, and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play a major role in global ecosystem research. The three remote sensing Vcmax products based on SIF, LCC, and SIF+LCC are available at 0.5281/zenodo.6466968 (Chen et al., 2022), and the code for implementing the ecological optimality theory is available at github.com/SmithEcophysLab/optimal_vcmax_R and 0.5281/zenodo.5899564 (last access: 31 August 2022) (Smith et al., 2022).
Publisher: Wiley
Date: 22-04-2022
DOI: 10.1111/NPH.18076
Abstract: Nitrogen (N) limitation has been considered as a constraint on terrestrial carbon uptake in response to rising CO 2 and climate change. By extension, it has been suggested that declining carboxylation capacity ( V cmax ) and leaf N content in enhanced‐CO 2 experiments and satellite records signify increasing N limitation of primary production. We predicted V cmax using the coordination hypothesis and estimated changes in leaf‐level photosynthetic N for 1982–2016 assuming proportionality with leaf‐level V cmax at 25°C. The whole‐canopy photosynthetic N was derived using satellite‐based leaf area index (LAI) data and an empirical extinction coefficient for V cmax , and converted to annual N demand using estimated leaf turnover times. The predicted spatial pattern of V cmax shares key features with an independent reconstruction from remotely sensed leaf chlorophyll content. Predicted leaf photosynthetic N declined by 0.27% yr −1 , while observed leaf (total) N declined by 0.2–0.25% yr −1 . Predicted global canopy N (and N demand) declined from 1996 onwards, despite increasing LAI. Leaf‐level responses to rising CO 2 , and to a lesser extent temperature, may have reduced the canopy requirement for N by more than rising LAI has increased it. This finding provides an alternative explanation for declining leaf N that does not depend on increasing N limitation.
Publisher: Springer Science and Business Media LLC
Date: 22-08-2023
Publisher: Springer Science and Business Media LLC
Date: 19-08-2022
DOI: 10.1038/S41467-022-32631-3
Abstract: Water availability plays a critical role in shaping terrestrial ecosystems, particularly in low- and mid-latitude regions. The sensitivity of vegetation growth to precipitation strongly regulates global vegetation dynamics and their responses to drought, yet sensitivity changes in response to climate change remain poorly understood. Here we use long-term satellite observations combined with a dynamic statistical learning approach to examine changes in the sensitivity of vegetation greenness to precipitation over the past four decades. We observe a robust increase in precipitation sensitivity (0.624% yr −1 ) for drylands, and a decrease (−0.618% yr −1 ) for wet regions. Using model simulations, we show that the contrasting trends between dry and wet regions are caused by elevated atmospheric CO 2 (eCO 2 ). eCO 2 universally decreases the precipitation sensitivity by reducing leaf-level transpiration, particularly in wet regions. However, in drylands, this leaf-level transpiration reduction is overridden at the canopy scale by a large proportional increase in leaf area. The increased sensitivity for global drylands implies a potential decrease in ecosystem stability and greater impacts of droughts in these vulnerable ecosystems under continued global change.
Publisher: Springer Science and Business Media LLC
Date: 11-08-2021
DOI: 10.1038/S41467-021-25163-9
Abstract: Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We find global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential.
Publisher: Springer Science and Business Media LLC
Date: 03-08-2020
Publisher: American Geophysical Union (AGU)
Date: 20-05-2021
DOI: 10.1029/2020AV000310
Abstract: Large uncertainties in North American terrestrial carbon fluxes hinder regional climate projections. Terrestrial biosphere models (TBMs), the essential tools for understanding continental‐scale carbon cycle, erge on whether temperate forests or croplands dominate carbon uptake in North America. Evidence from novel photosynthetic proxies, such as those based on chlorophyll fluorescence, has cast doubt on the “weak cropland, strong forest” carbon uptake patterns simulated by most TBMs. However, no systematic evaluation of TBMs has yet been attempted to pin down space‐time patterns that are most consistent with regional CO 2 observational constraints. Here, we leverage atmospheric CO 2 observations and satellite‐observed photosynthetic proxies to understand emergent space‐time patterns in North American carbon fluxes from a large suite of TBMs and data‐driven models. To do so, we evaluate how well the atmospheric signals resulting from carbon flux estimates reproduce the space‐time variability in atmospheric CO 2 , as is observed by a network of continuous‐monitoring towers over North America. Models with gross or net carbon fluxes that are consistent with the observed CO 2 variability share a salient feature of growing‐season carbon uptake in Midwest US croplands. Conversely, the remaining models place most growing‐season uptake in boreal or temperate forests. Differences in model explanatory power depend mainly on the simulated annual cycles of cropland uptake—especially, the timing of peak uptake—rather than the distribution of annual mean fluxes across biomes. Our results suggest that improved model representation of cropland phenology is crucial to robust, policy‐relevant estimation of North American carbon exchange.
Location: United States of America
No related grants have been discovered for Xiangzhong Luo.