24 research outputs found

    Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: a perspective from long‐term data assimilation

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    It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model-data fusion framework and systematically analyzed the SSA-induced biases using time-series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83-fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA-induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young-aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long-term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C-climate feedback

    Highly flexible, light-weight and mechanically enhanced (Mo2C/PyC)f fabrics for efficient electromagnetic interference shielding

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    Highly flexible, light-weight, and mechanically enhanced Mo2C modified PyC fiber (Mo2C/PyC) f fabrics with excellent electromagnetic interference shielding effectiveness (EMI SE) and enhanced mechanical strength were prepared via precursor infiltration and pyrolysis (PIP) method. The introduction of Mo2C significantly improved the EMI SE and tensile strength of the resultant fabrics compared to the control test sample (PyCf fabrics) prepared under identical conditions. At the thickness of 0.5mm, the EMI SE of the resultant (Mo2C/PyC)(f) fabrics can reach 40.7 dB compared with 14.0 dB of PyCf fabrics while the tensile strength increased to 5.63 +/- 0.16 MPa compared to 0.73 +/- 0.10 MPa of pristine PyCf fabrics. When the thickness of the resultant sample increased to 1.5 mm, the EMI SE in the X band was analyzed up to 60.0 dB with a mean value of 51.2 dB

    Dinaphthobenzo[1,2:4,5]dicyclobutadiene: Antiaromatic and Orthogonally Tunable Electronics and Packing

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    Polycyclic conjugated hydrocarbons containing antiaromatic four-membered cyclobutadienoids (CDB) are of great fundamental and technical interest. However, their challenging synthesis has hampered the exploration and understanding of such systems. Reported herein is a modular and efficient synthesis of novel CBD-containing acene analogues, dinaphthobenzo[1,2:4,5]dicyclobutadiene (DNBDCs), with orthogonally tunable electronic properties and molecular packing. The design also features strong antiaromaticity of the CBD units, as revealed by nucleus-independent chemical shift and anisotropy of the induced current density calculations, as well as X-ray crystallography. Tuning the size of silyl substituents resulted in the most favorable brick-layer packing for triisobutylsilyl-DNBDC and a charge mobility of up to 0.52cm(2)V(-1)s(-1) in field-effect transistors

    Multi-proxy temperature reconstruction from the West Qinling Mountains, China for the past 500 years.

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    A total of 290 tree-ring samples, collected from six sites in the West Qinling Mountains of China, were used to develop six new standard tree-ring chronologies. In addition, 73 proxy records were assembled in collaboration with Chinese and international scholars, from 27 publically available proxy records and 40 tree-ring chronologies that are not available in public datasets. These records were used to reconstruct annual mean temperature variability in the West Qinling Mountains over the past 500 years (AD 1500-1995), using a modified point-by-point regression (hybrid PPR) method. The results demonstrate that the hybrid PPR method successfully integrates the temperature signals from different types of proxies, and that the method preserves a high degree of low-frequency variability. The reconstruction shows greater temperature variability in the West Qinling Mountains than has been found in previous studies. Our temperature reconstruction for this region shows: 1) five distinct cold periods, at approximately AD 1520-1535, AD 1560-1575, AD 1610-1620, AD 1850-1875 and AD 1965-1985, and four warm periods, at approximately AD 1645-1660, AD 1705-1725, AD 1785-1795 and AD 1920-1945; 2) that in this region, the 20(th) century was not the warmest period of the past 500 years; and 3) that a dominant and persistent oscillation of ca. 64 years is significantly identified in the 1640-1790 period
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