岩溶区和非岩溶区两种优势植物凋落叶分解的比较研究

应用野外分解网袋法对岩溶地区和非岩溶地区两种优势树种桂花和青冈栎凋落叶的分解速率和养分释放规律进行研究。结果表明:分解1年后,凋落叶失重率桂花大于青冈栎,同一物种岩溶区大于非岩溶区。凋落叶各元素浓度随分解时间变化也有一定差异,C含量均表现为初期上升,后下降,最后上升的趋势;N含量前半年呈波动状态,后半年逐渐上升;P含量处波动状态,总体呈上升趋势。N、P含量和凋落叶失重率均表现为极显著正相关,而C:N、C:P、N:P与凋落叶失重率呈极显著负相关(P<0.01),说明凋落叶分解过程中失重率与N、P含量及C:N、C:P、N:P关系密切。凋落叶桂花N、P含量比青冈栎高,分解速率也比较快。     

A time for every season: soil aggregate turnover stimulates decomposition and reduces carbon loss in grasslands managed for bioenergy

A primary goal of many next‐generation bioenergy systems is to increase ecosystem services such as soil carbon (C) storage and nutrient retention. Evaluating whether bioenergy management systems are achieving these goals is challenging in part because these processes occur over long periods of time at varying spatial scales. Investigation of microbially mediated soil processes at the microbe scale may provide early insights into the mechanisms driving these long‐term ecosystem services. Furthermore, seasonal fluctuations in microbial activity are rarely considered when estimating whole ecosystem functioning, but are central to decomposition, soil structure, and realized C storage. Some studies have characterized extracellular enzyme activity within soil structures (aggregates); however, seasonal variation in decomposition at the microscale remains virtually unknown, particularly in managed ecosystems. As such, we hypothesize that temporal variation in aggregate turnover is a strong regulator of microbial activity, with important implications for decomposition and C and nitrogen (N) storage in bioenergy systems. We address variation in soil microbial extracellular enzyme activity spatially across soil aggregates and temporally across two growing seasons in three ecosystems managed for bioenergy feedstock production: Zea mays L. (corn) agroecosystem, fertilized and unfertilized reconstructed tallgrass prairie. We measured potential N‐acetyl‐glucosaminidase (NAG), β‐glucosidase (BG), β‐xylosidase (BX), and cellobiohydrolase (CB) enzyme activity. Aggregate turnover in prairie systems was driven by precipitation events and seasonal spikes in enzyme activity corresponded with aggregate turnover events. In corn monocultures, soil aggregates turned over early in the growing season, followed by increasing, albeit low, enzyme activity throughout the growing season. Independent of management system or sampling date, NAG activity was greatest in large macroaggregates (>2000 μm) and CB activity was greatest in microaggregates (<250 μm). High microbial activity coupled with greater aggregation in prairie bioenergy systems may reduce loss of soil organic matter through decomposition and increase soil C storage.     

Identification of the active site of human mitochondrial malonyl‐coenzyme a decarboxylase: A combined computational study

Malonyl‐CoA decarboxylase (MCD) can control the level of malonyl‐CoA in cell through the decarboxylation of malonyl‐CoA to acetyl‐CoA, and plays an essential role in regulating fatty acid metabolism, thus it is a potential target for drug discovery. However, the interactions of MCD with CoA derivatives are not well understood owing to unavailable crystal structure with a complete occupancy in the active site. To identify the active site of MCD, molecular docking and molecular dynamics simulations were performed to explore the interactions of human mitochondrial MCD (HmMCD) and CoA derivatives. The findings reveal that the active site of HmMCD indeed resides in the prominent groove which resembles that of CurA. However, the binding modes are slightly different from the one observed in CurA due to the occupancy of the side chain of Lys183 from the N‐terminal helical domain instead of the adenine ring of CoA. The residues 300 ? 305 play an essential role in maintaining the stability of complex mainly through hydrogen bond interactions with the pyrophosphate moiety of acetyl‐CoA. Principle component analysis elucidates the conformational distribution and dominant concerted motions of HmMCD. MM_PBSA calculations present the crucial residues and the major driving force responsible for the binding of acetyl‐CoA. These results provide useful information for understanding the interactions of HmMCD with CoA derivatives. Proteins 2016; 84:792–802. © 2016 Wiley Periodicals, Inc.     

Leaf decomposition and nutrient release of dominant species in the forest and lake in the Jiuzhaigou National Nature Reserve,China

AimsLitter decomposition is an important ecological process in nutrient cycling and productivity of ecosystems. Our objective is to quantify the differences of litter decomposition and nutrient release (N and P) under the forest and in an alpine lake among the dominant tree species in the Jiuzhaigou National Nature Reserve.
Methods Fresh leaf litters of Abies ernestii, Pinus tabulaeformis, Betula albo-sinensis, and Salix cupularis were collected and placed in bags under the forest and in an alpine lake for a year.
Important findings The mass remaining ratio (MR) of the leaf litters was well predicted with Olson’s decay model (r > 0.93, p < 0.01). The time for 99% decomposition was the shortest for S. cupularis (6.80 a), followed by B. albo-sinensis (10.34 a), A. ernestii (18.88 a), and P. tabulaeformis (27.21 a). These values were 1.48-, 1.55-, 1.80-, and 1.65-folds of the corresponding values in the lake, respectively. Both MR and nitrogen remaining ratio (NR) had significantly negative correlations with the leaf initial N concentration, but significantly positive correlations with the initial C:N. The nutrient release was significantly different among the four species and between the two sites (i.e., forest and alpine lake). The N release of S. cupularis was consistent between forest and the lake (i.e. directly released in the beginning of decomposition), while other species had an obvious N enrichment process before it released. The release of P among was similar among the four species and between the two sites, with a release—enrichment—release pattern. Overall, the leaf litter decomposition appeared as an intricate process that was affected by the litter chemistry and and the environment. The fast litter decomposition in the lake may have a profound influence on the water quanlity in the Jiuzhaigou National Nature Reserve.     

Anthropogenic nitrogen enrichment enhances soil carbon accumulation by impacting saprotrophs rather than ectomycorrhizal fungal activity

There is evidence that anthropogenic nitrogen (N) deposition enhances carbon (C) sequestration in boreal forest soils. However, it is unclear how free‐living saprotrophs (bacteria and fungi, SAP) and ectomycorrhizal (EM) fungi responses to N addition impact soil C dynamics. Our aim was to investigate how SAP and EM communities are impacted by N enrichment and to estimate whether these changes influence decay of litter and humus. We conducted a long‐term experiment in northern Sweden, maintained since 2004, consisting of ambient, low N additions (0, 3, 6, and 12 kg N ha^?1 year^?1) simulating current N deposition rates in the boreal region, as well as a high N addition (50 kg N ha^?1 year^?1). Our data showed that long‐term N enrichment impeded mass loss of litter, but not of humus, and only in response to the highest N addition treatment. Furthermore, our data showed that EM fungi reduced the mass of N and P in both substrates during the incubation period compared to when only SAP organisms were present. Low N additions had no effect on microbial community structure, while the high N addition decreased fungal and bacterial biomasses and altered EM fungi and SAP community composition. Actinomycetes were the only bacterial SAP to show increased biomass in response to the highest N addition. These results provide a mechanistic understanding of how anthropogenic N enrichment can influence soil C accumulation rates and suggest that current N deposition rates in the boreal region (≤12 kg N ha^?1 year^?1) are likely to have a minor impact on the soil microbial community and the decomposition of humus and litter.     

ENSO and NAO affect long‐term leaf litter dynamics and stoichiometry of Scots pine and European beech mixedwoods

Litterfall dynamics (production, seasonality and nutrient composition) are key factors influencing nutrient cycling. Leaf litter characteristics are modified by species composition, site conditions and water availability. However, significant evidence on how large‐scale, global circulation patterns affect ecophysiological processes at tree and ecosystem level remains scarce due to the difficulty in separating the combined influence of different factors on local climate and tree phenology. To fill this gap, we studied links between leaf litter dynamics with climate and other forest processes, such as tree‐ring width (TRW) and intrinsic water‐use efficiency (iWUE) in two mixtures of Scots pine (Pinus sylvestris L.) and European beech (Fagus sylvatica L.) in the south‐western Pyrenees. Temporal series (18 years) of litterfall production and elemental chemical composition were decomposed following the ensemble empirical mode decomposition method and relationships with local climate, large‐scale climatic indices, TRW and Scots pine's iWUE were assessed. Temporal trends in N:P ratios indicated increasing P limitation of soil microbes, thus affecting nutrient availability, as the ecological succession from a pine‐dominated to a beech‐dominated forest took place. A significant influence of large‐scale patterns on tree‐level ecophysiology was explained through the impact of the North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) on water availability. Positive NAO and negative ENSO were related to dry conditions and, consequently, to early needle shedding and increased N:P ratio of both species. Autumn storm activity appears to be related to premature leaf abscission of European beech. Significant cascading effects from large‐scale patterns on local weather influenced pine TRW and iWUE. These variables also responded to leaf stoichiometry fallen 3 years prior to tree‐ring formation. Our results provide evidence of the cascading effect that variability in global climate circulation patterns can have on ecophysiological processes and stand dynamics in mixed forests.     

Climate warming alters subsoil but not topsoil carbon dynamics in alpine grassland

Subsoil contains more than half of soil organic carbon (SOC) globally and is conventionally assumed to be relatively unresponsive to warming compared to the topsoil. Here, we show substantial changes in carbon allocation and dynamics of the subsoil but not topsoil in the Qinghai‐Tibetan alpine grasslands over 5 years of warming. Specifically, warming enhanced the accumulation of newly synthesized (¹⁴C‐enriched) carbon in the subsoil slow‐cycling pool (silt‐clay fraction) but promoted the decomposition of plant‐derived lignin in the fast‐cycling pool (macroaggregates). These changes mirrored an accumulation of lipids and sugars at the expense of lignin in the warmed bulk subsoil, likely associated with shortened soil freezing period and a deepening root system. As warming is accompanied by deepening roots in a wide range of ecosystems, root‐driven accrual of slow‐cycling pool may represent an important and overlooked mechanism for a potential long‐term carbon sink at depth. Moreover, given the contrasting sensitivity of SOC dynamics at varied depths, warming studies focusing only on surface soils may vastly misrepresent shifts in ecosystem carbon storage under climate change.     

Mapping Local Conformational Landscapes of Proteins in Solution

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Dynamic imaging and quantification of subcellular motion with eigen‐decomposition optical coherence tomography‐based variance analysis

The dynamic properties of subcellular organism are important biomarkers of the health. Imaging subcellular level dynamics provides effective solutions for evaluating cell metabolism and testing the responses of cells to pathogens and drugs in pharmaceutical engineering. In this paper, we demonstrate an innovative approach to contrast the subcellular motion by using eigen decomposition (ED)‐based variance analysis of time‐dependent complex optical coherence tomography signals. This method reveals a superior advantage of contrast to noise ratio when compared with the approach that employs intensity decorrelation. Furthermore, the eigen values derived from ED processing are calculated and applied to assess the power ratios of complex signal invariance that decreases exponentially along time dimension. The validation experiments are performed on the patterned samples of yeast powder mixed with gelatin/TiO2 water solution. Additionally, the proposed method is used to image mouse cerebral cortex in normal and pathological conditions, suggesting the practicality of variance power mapping in analyzing cortical neural activities. The technique promises efficient measurement of subcellular motions with high sensitivity and high throughput for in vivo and in situ applications.