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| 1 | Lignin characteristics in soil profiles in different plant communities in a subtropical mixed forest显示文摘Aims Lignin is generally considered as an important indicator of soil organic carbon(SOC)storage and dynamics.to evaluate the effects of plant communities and soil depth on soil lignin is critical to better understand forest carbon cycling.Methods We compared lignin content and chemical signature in three soil depths of four major plant communities in a subtropical forest,which located in the north part of Wuling Mountains,China.Lignin was measured using CuO oxidation method.Important Findings Both lignin content and its biochemical signature in plant litter varied among communities.However,these differences were mostly no longer exist in the upper soil layers.Lignin chemistry in soils inherited some of the biochemical signature of lignin in litter,but in a diminished magnitude.these results suggest that different plant communities had similar decomposition process with vary-ing rates,caused diminished differences in lignin content and its biochemical signature.Lignin content decreased with soil depth,but the biochemical signature of lignin was not significantly dif-ferent among soil layers for all communities,which suggests that vertical movement of lignin within the soil profile is very likely a key process causing this similar biochemical signature.these results emphasized the important roles of lignin inputs and soil eluviation in shaping lignin characteristics and distribution in forest soils,which pinpoint the urgent need to consider hydrological processes in studying forest soil carbon cycling. | Xinggang Wang Qiuxiang Tian Qianxi Li Chang Liao Mei He Feng Liu | 2018 | Journal of Plant Ecology2018，11，4： | 2 |
| 2 | Screening of lactobacilli with antagonistic activity against enteroinvasive Escherichia coli显示文摘 | Xiaoming Liu Wenyu Liu Qiuxiang Zhang Fengwei Tian Gang Wang Hao Zhang Wei Chen | 2013 | Food Control2013，，2： | 1 |
| 3 | Nitrogen availability regulates deep soil priming effect by changing microbial metabolic efficiency in a subtropical forest显示文摘In terrestrial ecosystems,deep soils(below 30 cm)are major organic carbon(C)pools.The labile carbon input could alter soil organic carbon(SOC)mineralization,resulting in priming effect(PE),which could be modified by nitrogen(N)availability,however,the underlying mechanism is unclear for deep soils,which complicates the prediction of deep soil C cycling in response to N deposition.A series of N applications with ^(13)C labeled glucose was set to investigate the effect of labile C and N on deep SOC mineralization.Microbial biomass,functional community,metabolic efficiency and enzyme activities were examined for their effects on SOC mineralization and PE.During incubation,glucose addition promoted SOC mineralization,resulting in positive PE.The magnitude of PE decreased significantly with increasing N.The N-regulated PE was not dependent on extracellular enzyme activities but was positively correlated with carbon use efficiency and negatively with metabolic quotient.Higher N levels resulted in higher microbial biomass and SOC-derived microbial biomass than lower N levels.These results suggest that the decline in the PE under high N availability was mainly controlled by higher microbial metabolic efficiency which allocated more C for growth.Structural equation modelling also revealed that microbial metabolic efficiency rather than enzyme activities was the main factor regulating the PE.The negative effect of additional N suggests that future N deposition could promote soil C sequestration. | Chang Liao Qiuxiang Tian Feng Liu | 2021 | Journal of Forestry Research2021，32，2： | 1 |
| 4 | Coordination and order risk assessment of water and land resource system based on periphery and synergetics theories显示文摘Coordinated and orderly water and land resource system is vital to ensure the economic and social development of a region.Grain production in Heilongjiang Province has increased consecutively every year since 2003,and numerous water and land resource-related problems have become increasingly prominent and have had significant adverse effects on social and economic development and stability in the region.In this study,Heilongjiang Province and its 13 prefecture-level cities were selected as the study area,and the degrees of coordination of the social,economic and ecological subsystems were evaluated using periphery theory and the theory of synergetics.To ensure that the assessment was objective and accurate,weights were calculated using the projection pursuit technique,and similarity degrees were calculated using a modified(by introducing the chi-square distance)order of preference by similarity to ideal solution(TOPSIS)technique.Moreover,to reflect the variations in the overall degree of coordination in Heilongjiang Province,the risk level of the coordination of the water and land resource system was predicted through the year 2020 using a dynamic neural network.This study provides a reference for establishing effective and balanced coordination between society and water and land resources. | Qiuxiang Jiang Zhimei Zhou Zilong Wang Qiang Fu Youzhu Zhao Tian Wang | 2018 | International Journal of Agricultural and Biological Engineering2018，11，3： | 0 |
| 5 | Eff ects of stand condition and root density on fi ne-root dynamics across root functional groups in a subtropical montane forest显示文摘Fine roots play key roles in belowground C cycling in terrestrial ecosystems.Based on their distinct functions,fi ne roots are either absorptive fi ne roots(AFRs)or transport fi ne roots(TFRs).However,the function-based fi ne root dynamics of trees and their responses to forest stand properties remain unclear.Here,we studied the dynamics of AFRs and TFRs and their responses to stand conditions and root density in a subtropical montane mixed forest based on a 2-a root window experiment.Mean(±SE)annual production,mortality,and turnover rate of AFRs were 7.87±0.17 m m^(−2)a^(−1),8.13±0.20 m m^(−2)a^(−1)and 2.96±0.24 a^(−1),respectively,compared with 7.09±0.17 m m^(−2)a^(−1),4.59±0.17 m m^(−2)a^(−1),and 2.01±0.22 a^(−1),respectively,for TFRs.The production and mortality of fi ne roots were signifi cantly higher in high root-density sites than in low-root density sites,whereas the turnover of fi ne roots was faster in the low root-density sites.Furthermore,root density had a larger positive eff ect than other environmental factors on TFR production but had no obvious impact on AFR production.Tree species diversity had an apparent positive eff ect on AFR production and was the crucial driver of AFR production,probably due to a complementary eff ect,but had no evident impact on TFR.Both tree density and tree species diversity were positively correlated with the mortality of AFRs and negatively related to the turnover of TFRs,suggesting that higher root density caused stronger competition for rooting space and that plants tend to reduce maintenance costs by decreasing TFR turnover.These fi ndings illustrated the importance of root functional groups in understanding root dynamics and their responses to changes in environmental conditions. | Lin Huang Rudong Zhao Xiaoxiang Zhao Qiuxiang Tian Pengyun Yue Feng Liu | 2023 | Journal of Forestry Research2023，34，3： | 0 |
| 6 | Associative learning of a three-terminal memristor network for digits recognition显示文摘Imitating the associative intelligence of the biological brain is attractive but is poorly achieved in hardware because the complex tunable connection in neural networks is difficult to reproduce. We develop a circuit composed of a three-terminal memristor network to reproduce the biological conditioning process artificially. The synaptic weight between co-firing neurons is strengthened simultaneously by generating a feedback signal from the integrate-and-fire neuron to the gate of the synaptic memristor. The network allows the multi-associative capacity of recalling more than one digit in one circuit. Both single and multi-associative learning for recalling digital images are achieved. Furthermore, all 10 digital images from “0” to “9” are successfully recalled in an associative network with such paralleling circuits. Assisted by this associative layer, a typical classification network effectively improves the recognition rate for fragmentary digital images.Our work sheds light on brain-inspired artificial associative memory and provides a strategy for applications,such as object recognition with partial features and similar scenes. | Yiming REN Bobo TIAN Mengge YAN Guangdi FENG Bin GAO Fangyu YUE Hui PENG Xiaodong TANG Qiuxiang ZHU Junhao CHU Chungang DUAN | 2023 | Science China(Information Sciences)2023，66，2： | 0 |
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