Identification of a purC gene from Streptococcus pneumoniae.

A gene encoding 5'-phosphoribosyl-5-aminoimidazole-4-N-succinocarboxamide synthetase was identified in Streptococcus pneumoniae as a 708-bp segment of the genome encoding a 27,001-Da protein with strong similarity to known PurC proteins. The S. pneumoniae purC gene, found immediately adjacent to the competence induction genes, comAB, was cloned and sequenced. The predicted protein product of purC displayed substantial (> 40%) identity to the entire sequence of the PurC proteins of Bacillus subtilis and Escherichia coli. Function of the S. pneumoniae gene product was demonstrated by complementation of E. coli purC mutations.     

Condition for the appearance of the metastable P beta' phase in fully hydrated phosphatidylcholines as studied by small-angle x-ray diffraction.

In the ripple phase of fully hydrated multilamellar vesicles of dipalmitoylphosphatidylcholine (DPPC), two kinds of small-angle x-ray diffraction profiles are observed on cooling through the main transition. One is a seemingly normal profile similar to that observed on heating and the other is the superposition of the diffraction profiles for the primary (normal) and the secondary ripple structures. We found that the profile obtained depended on the cooling rate. Increasing the cooling rate from 0.1 degrees C/min to 1 degrees C/min caused the peaks originating from the secondary ripple structure to diminish. After a cooling scan at 43 degrees C/min, the profile became similar to that of the normal ripple structure, although a trace of the secondary ripple structure remains. The results are interpreted in terms of the rise and fall of three-dimensional correlated domains composed of both primary and secondary ripple structures. At slow cooling rates, correlated domains of both kinds of ripple structures develop. As the cooling rate is increased, the domain of the primary ripple structure remains correlated, while that of the secondary ripple structure becomes less correlated. In addition, the multipeak profile appears even at rapid cooling rates, if the final low temperature lies just below the Tm for the main transition. This results suggests that formation of the correlated domains of the secondary ripple structure requires a certain time interval during which the DPPC vesicles experience the temperature just below the main transition. The secondary ripple structure takes place in phosphatidylcholines having more than 15 carbons in each hydrocarbon chain upon cooling through the main transition.     

How drought events during the last century have impacted biomass carbon in Amazonian rainforests

During the last two decades, inventory data show that droughts have reduced biomass carbon sink of the Amazon forest by causing mortality to exceed growth. However, process-based models have struggled to include drought-induced responses of growth and mortality and have not been evaluated against plot data. A process-based model, ORCHIDEE-CAN-NHA, including forest demography with tree cohorts, plant hydraulic architecture and drought-induced tree mortality, was applied over Amazonia rainforests forced by gridded climate fields and rising CO₂ from 1901 to 2019. The model reproduced the decelerating signal of net carbon sink and drought sensitivity of aboveground biomass (AGB) growth and mortality observed at forest plots across selected Amazon intact forests for 2005 and 2010. We predicted a larger mortality rate and a more negative sensitivity of the net carbon sink during the 2015/16 El Niño compared with the former droughts. 2015/16 was indeed the most severe drought since 1901 regarding both AGB loss and area experiencing a severe carbon loss. We found that even if climate change did increase mortality, elevated CO₂ contributed to balance the biomass mortality, since CO₂-induced stomatal closure reduces transpiration, thus, offsets increased transpiration from CO₂-induced higher foliage area.     

Damage to living trees contributes to almost half of the biomass losses in tropical forests

Accurate estimates of forest biomass stocks and fluxes are needed to quantify global carbon budgets and assess the response of forests to climate change. However, most forest inventories consider tree mortality as the only aboveground biomass (AGB) loss without accounting for losses via damage to living trees: branchfall, trunk breakage, and wood decay. Here, we use ~151,000 annual records of tree survival and structural completeness to compare AGB loss via damage to living trees to total AGB loss (mortality + damage) in seven tropical forests widely distributed across environmental conditions. We find that 42% (3.62 Mg ha⁻¹ year⁻¹; 95% confidence interval [CI] 2.36–5.25) of total AGB loss (8.72 Mg ha⁻¹ year⁻¹; CI 5.57–12.86) is due to damage to living trees. Total AGB loss was highly variable among forests, but these differences were mainly caused by site variability in damage-related AGB losses rather than by mortality-related AGB losses. We show that conventional forest inventories overestimate stand-level AGB stocks by 4% (1%–17% range across forests) because assume structurally complete trees, underestimate total AGB loss by 29% (6%–57% range across forests) due to overlooked damage-related AGB losses, and overestimate AGB loss via mortality by 22% (7%–80% range across forests) because of the assumption that trees are undamaged before dying. Our results indicate that forest carbon fluxes are higher than previously thought. Damage on living trees is an underappreciated component of the forest carbon cycle that is likely to become even more important as the frequency and severity of forest disturbances increase.     

The detection and attribution of extreme reductions in vegetation growth across the global land surface

Negative extreme anomalies in vegetation growth (NEGs) usually indicate severely impaired ecosystem services. These NEGs can result from diverse natural and anthropogenic causes, especially climate extremes (CEs). However, the relationship between NEGs and many types of CEs remains largely unknown at regional and global scales. Here, with satellite-derived vegetation index data and supporting tree-ring chronologies, we identify periods of NEGs from 1981 to 2015 across the global land surface. We find 70% of these NEGs are attributable to five types of CEs and their combinations, with compound CEs generally more detrimental than individual ones. More importantly, we find that dominant CEs for NEGs vary by biome and region. Specifically, cold and/or wet extremes dominate NEGs in temperate mountains and high latitudes, whereas soil drought and related compound extremes are primarily responsible for NEGs in wet tropical, arid and semi-arid regions. Key characteristics (e.g., the frequency, intensity and duration of CEs, and the vulnerability of vegetation) that determine the dominance of CEs are also region- and biome-dependent. For example, in the wet tropics, dominant individual CEs have both higher intensity and longer duration than non-dominant ones. However, in the dry tropics and some temperate regions, a longer CE duration is more important than higher intensity. Our work provides the first global accounting of the attribution of NEGs to diverse climatic extremes. Our analysis has important implications for developing climate-specific disaster prevention and mitigation plans among different regions of the globe in a changing climate.     

Climate–ecosystem modelling made easy: The Land Sites Platform

Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single-site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version-controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site-level simulations. We provide input data for 20 established geo-ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.     

Long-term changes in Noctiluca scintillans blooms along the Chinese coast from 1933 to 2020

Noctiluca scintillans is one of the most common harmful algal species and widely known due to its bioluminescence. In this study, the spatial distribution, seasonal variations, and long-term trends of N. scintillans blooms in China and the related drivers were analyzed and discussed. From 1933 to 2020, a total of 265 events of N. scintillans blooms were recorded in Chinese coastal waters, with a total duration of 1052 days. The first N. scintillans bloom occurred in Zhejiang in 1933, and only three events were recorded before 1980. From 1981 to 2020, N. scintillans caused harmful algal blooms (HABs) almost every year, both the average duration and the proportion of multiphase HABs showed an increasing trend. 1986–1992, 2002–2004, and 2009–2016 were the three peak periods with a frequency of no less than five events of N. scintillans blooms per year. In terms of spatial distribution, N. scintillans blooms spread from the Southeast China Sea to the Bohai Sea after 2000, Guangdong, Fujian, and Hebei were the three provinces with the highest numbers of recorded events of N. scintillans blooms. Moreover, 86.8% of the events of N. scintillans blooms occurred in spring (March, April, and May) and summer (June, July, and August). Among environmental factors, the dissolved inorganic phosphate, dissolved silicate and chemical oxygen demand were significantly correlated with the cell density of N. scintillans during N. scintillans blooms, and most of N. scintillans blooms were recorded in the temperature range of 18.0–25.0°C. Precipitation, hydrodynamics, water temperature, and food availability might be the main factors affecting the spatial–temporal distribution of N. scintillans blooms along the Chinese coast.     

Extinction risk of Chinese angiosperms varies between woody and herbaceous species

Aim

Understanding how species' traits and environmental contexts relate to extinction risk is a critical priority for ecology and conservation biology. This study aims to identify and explore factors related to extinction risk between herbaceous and woody angiosperms to facilitate more effective conservation and management strategies and understand the interactions between environmental threats and species' traits.

Location

China.

Taxon

Angiosperms.

Methods

We obtained a large dataset including five traits, six extrinsic variables, and 796,118 occurrence records for 14,888 Chinese angiosperms. We assessed the phylogenetic signal and used phylogenetic generalized least squares regressions to explore relationships between extinction risk, plant traits, and extrinsic variables in woody and herbaceous angiosperms. We also used phylogenetic path analysis to evaluate causal relationships among traits, climate variables, and extinction risk of different growth forms.

Results

The phylogenetic signal of extinction risk differed among woody and herbaceous species. Angiosperm extinction risk was mainly affected by growth form, altitude, mean annual temperature, normalized difference vegetation index, and precipitation change from 1901 to 2020. Woody species' extinction risk was strongly affected by height and precipitation, whereas extinction risk for herbaceous species was mainly affected by mean annual temperature rather than plant traits.

Main conclusions

Woody species were more likely to have higher extinction risks than herbaceous species under climate change and extinction threat levels varied with both plant traits and extrinsic variables. The relationships we uncovered may help identify and protect threatened plant species and the ecosystems that rely on them.     

崖椒茎的化学成分

从崖椒（Zanthoxglum schinifolutm Sieb.et Zucc.)茎的石油醚、二氯甲烷提取物中分离得到8个化合物。经物理常数测定及光谱（UV,IR,MS,NMR)分析鉴定其为（1）白鲜碱（dictamning),（2）茵芋碱（skimmianine),(3)滨蒿内酯（scoparone),(4)崖椒内酯（schinifolin),(5)莨菪亭（scopoletin),（6）7-羟基-8-甲氧基香豆素（7-hydroxy-8-methoxycoumarin),（7）N-甲基弗林辛（N-methylflindersine),（8）β-谷甾醇（β-sitosterol),其中化合物（5）、（6）和（7）为首次从该植物中分离。     

药用寄生植物菟丝子属,列当属和无根藤属氨基酸的分析

本文测定了菟丝子属、列当属和无根藤属某些种的种子和植株氨基酸的种类组成和含量。结果表明,3个属种子和植株氨基酸均在15种以上,且含量丰富,特别是必需氨基酸的含量较高。文中讨论了氨基酸的药用和在种子鉴定与化学分类上的作用,探讨了开发应用的前景。