留茬免耕播种对河西绿洲灌区春小麦出苗和产量的影响

本研究通过田间定位试验,探讨了河西绿洲灌区单作小麦、小麦/玉米间作、小麦/大豆间作3种典型春小麦生产模式下,长期留茬免耕播种对春小麦出苗和产量的影响,为该区域春小麦高效可持续生产提供理论依据.结果 表明:与传统翻耕相比,留茬免耕播种小麦/玉米和小麦/大豆间作的小麦出苗率、出苗均匀度下降明显,降幅分别为3.3％～8.6％...     

日粮水平对鲇鱼日总代谢,特殊动力作用和活动代谢的影响

在２５℃不同日粮水平（饥饿─４％体重／ｄ）条件下,采用封闭式呼吸仪测定了３１尾鲇鱼（体重７２．９─１３３．３ｇ）的日总代谢率,然后,将鱼限制在呼吸室中的限动笼内测定了其中２０尾鲇鱼的静止日总代谢率,并计算出了鲇鱼的特殊动力作用（ＳＤＡ）和活动代谢率。日总代谢率和活动代谢率都随日粮水平的升高呈“Ｖ”形变化,分别在约１％和２％体重／ｄ的日粮水平时最低,ＳＤＡ的能量支出占摄入能量的２２．１４％。     

整治区植烟土壤养分空间变异及肥力适宜性等级评价

采用地理信息系统(GIS)技术和地统计学方法,研究了湖北省恩施市“清江源”现代烟草农业科技园区、恩施城郊和利川柏杨基地单元新整治区域的土壤属性和速效养分空间变异特征,并采用模糊数学法对其土壤肥力适宜性指数(SFI)进行评价.结果表明: 土地整治对土壤速效磷含量的变异和空间分布的影响较大,这种影响程度可能与地形地貌特征和整治程度有关;土地整治对土壤pH值的影响较小,但是柏杨土壤酸化严重(pH<5.5).77.6%的城郊土壤具有较低的SFI,而柏杨和清江源分别仅有17.1%和31.4%的土壤具有较低的SFI.柏杨需要重点解决土壤酸化问题,城郊需要重点解决整个区域土壤培肥和肥力均衡化问题,而清江源则需解决SFI较低区域的培肥问题.     

Sowing different mixtures in dry acidic grassland produced priority effects of varying strength

Several longer-term assembly studies on ex-arable land have found that species that arrive first at a disturbed site can play a key role in the further development of the community and that this priority effect influences aboveground productivity, species diversity and stability of the grassland communities that develop. Restoration of nutrient poor, species rich grasslands is often limited by seed dispersal as well as the accessibility of suitable microsites for establishment. Sowing species (i.e. creating priority effects for further assembly) may help overcome such dispersal barriers, but the potential of using priority effects for restoration has not been tested in this type of dry grassland. We tested the hypothesis that sowing two different seed mixtures used for dry acidic grassland restoration onto a sandy substrate (which formed an equivalent to a primary succession) would create priority effects, and that these priority effects would be sustained over a number of years. We followed community assembly and measured aboveground productivity for four years after sowing. We found that priority effects caused by sowing of differently diverse mixtures did also occur in dry acidic grassland habitat, but that how persistent they were over time depended on the response variable considered. Priority effects on species number were not as strong as found in previous ex-arable land studies, whereas priority effects for aboveground productivity were still visible after 4 years. In addition, functional composition of the community still reflected the composition of the seed mixtures 4 years later. Our results suggest that priority effects can occur in nutrient-poor dry acidic grassland but in contrast to more nutrient-rich sites the breadth of responses affected may not be as wide.     

Metabolic distribution of radioactivity in Sprague-Dawley rats and B6C3F1 mice exposed to 1,3-[2,3-14C]-butadiene by whole body exposure

The uptake of 1,3-[2,3-(14)C]-butadiene and its disposition, measured as radioactivity in urine, faeces, exhaled volatiles and CO(2) during and following 6 h whole body exposure to 20 ppm butadiene has been investigated in male Sprague-Dawley rats and B6C3F1 mice. Whilst there were similarities between the two species, the uptake and metabolic distribution of butadiene were somewhat different for rats and mice. The major differences observed were in the urinary excretion of radioactivity and in the exhalation of 14C-CO(2). After 42 h from the start of exposure, 51.1% of radioactivity was eliminated in rat urine compared with 39.5% for mouse urine. 34.9% of the recovered radioactivity was exhaled by rats as 14C-CO(2), compared with 48.7% by mice. Excretion of radioactivity in faeces was similar for both species (3.8% for rats and 3.4% for mice). The tissue concentrations of 14C-butadiene equivalents measured in liver, testes, lung and blood of exposed mice were 0.493, 0460, 0.457, and 1.626 nmol/g tissue, respectively. The values for the corresponding rat tissues were 0.869, 0.329, 0.457, and 1.626 nmol butadiene equivalents/g tissue, respectively. For rats, 6.2% of recovered radioactivity (0.288 nmol butadiene equivalents/g tissue) was retained in carcasses whereas for mice the amount was 3.6% (0.334 nmol butadiene equivalents/g tissue). There were also some significant differences between the metabolic conversion of 1,3-[2,3-(14)C]-butadiene and excretion by mice following the 20 ppm whole body exposure compared to previously reported data for nose-only exposure to 200 ppm butadiene [Richardson et al., Toxicol. Sci. 49 (1999) 186]. The main difference between the high- and low-exposure studies was in the exhalation of 14C-CO(2). At the 200 ppm exposure, 40% of the radioactivity was exhaled as 14C-CO(2) by rats whereas 6% was measured by this route for mice. The proportional conversion of butadiene to CO(2) by mice was significantly greater at the low exposure concentration compared with that reported for the higher concentration. This shift was not observed for rats. The difference between species could be caused by a saturation of metabolism in mice between 20 and 200 ppm for the pathways leading to CO(2). Restraint or error in collection of CO(2) in the 200 ppm study could also be factors.     

Quantum biology at the cellular level—Elements of the research program

Quantum biology is emerging as a new field at the intersection between fundamental physics and biology, promising novel insights into the nature and origin of biological order. We discuss several elements of QBCL (quantum biology at cellular level) – a research program designed to extend the reach of quantum concepts to higher than molecular levels of biological organization. We propose a new general way to address the issue of environmentally induced decoherence and macroscopic superpositions in biological systems, emphasizing the ‘basis-dependent’ nature of these concepts. We introduce the notion of ‘formal superposition’ and distinguish it from that of Schroedinger's cat (i.e., a superposition of macroscopically distinct states). Whereas the latter notion presents a genuine foundational problem, the former one contradicts neither common sense nor observation, and may be used to describe cellular ‘decision-making’ and adaptation. We stress that the interpretation of the notion of ‘formal superposition’ should involve non-classical correlations between molecular events in a cell. Further, we describe how better understanding of the physics of Life can shed new light on the mechanism driving evolutionary adaptation (viz., ‘Basis-Dependent Selection’, BDS). Experimental tests of BDS and the potential role of synthetic biology in closing the ‘evolvability mechanism’ loophole are also discussed.     

Sea level and faunal changes during the latest Llandovery and earliest Ludlow (Silurian)

It is now recognized that the late Telychian and early Gorstian sea level changes are, like many others in the Silurian, of world‐wide extent. The 30–50 m deepening events at these times were between 1 and 2 Ma in duration, so melting continental ice caps appear to be the most probable cause. The faunal changes associated with the two events are respectively very close to the base and the top of the Wenlock Series and thus segregate many of the faunas diagnostic of the Llandovery, Wenlock, and Ludlow series. Permanent extinctions (often followed by radiations) are more prevalent in the graptolites, conodonts, and acritarchs, while benthic faunas are more affected by regional shifts in community distributions. This means that, in the benthos, slowly evolving lineages are the only reliable guides to time. Such phyletic evolution, however, appears to have been unaffected by sea‐level events.     

Response by macrozoobenthos biomass to water level regulation in some Finnish lake littoral zones

The relationship of the macrozoobenthos biomass in the littoral area to the yearly fluctuation in water level and the characteristics of the area or lake are studied using data collected from sheltered bays in regulated and natural waters. Most of the lakes were clear and oligotrophic. The benthos biomass at all depths in the littoral decreased with increased water level fluctuation, provided that the transparency of the water was uniform.The macrozoobenthos biomass in the 0–3 m depth zone could be predicted fromlog macrozoobenthos biomass (mg ODW) m^-2=4.25-1.33 (log Biomass Index) in which the Biomass Index is calculated as% MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaaeOqaiaabM% gacaqGVbGaaeyBaiaabggacaqGZbGaae4CaiaabccacaqGjbGaaeOB% aiaabsgacaqGLbGaaeiEaiaab2dacaqGGaGaaeiiaiaabccacaqGGa% GaaeiiaiaabccacaqGGaGaaeiiaiaabccacaqGGaGaaeiiaiaabcca% caqGGaGaaeiiaiaabccacaqGGaGaaeiiaiaabccacaqGGaGaaeiiai% aabccadaWcaaabaeqabaGaae4DaiaabggacaqG0bGaaeyzaiaabkha% caqGGaGaaeiBaiaabwgacaqG2bGaaeyzaiaabYgacaqGGaGaaeOzai% aabYgacaqG1bGaae4yaiaabshacaqG1bGaaeyyaiaabshacaqGPbGa% ae4Baiaab6gacaqGGaGaaeyAaiaab6gacaqGGaGaaeiDaiaabIgaca% qGLbGaaeiiaiaabchacaqGYbGaaeyzaiaabAhacaqGPbGaae4Baiaa% bwhacaqGZbGaaeiiaiaabMhacaqGLbGaaeyyaiaabkhaaeaacaqGOa% GaaeyBaiaabUdacaqGGaGaae4yaiaabggacaqGSbGaae4yaiaabwha% caqGSbGaaeyyaiaabshacaqGLbGaaeizaiaabccacaqGMbGaaeOCai% aab+gacaqGTbGaaeiiaiaab2gacaqGVbGaaeOBaiaabshacaqGObGa% aeiBaiaabMhacaqGGaGaaeyBaiaabwgacaqGHbGaaeOBaiaabccaca% qG2bGaaeyyaiaabYgacaqG1bGaaeyzaiaabohacaqGPaaaaeaacaqG% tbGaaeyzaiaabogacaqGJbGaaeiAaiaabMgacaqGGaGaaeizaiaabM% gacaqGZbGaae4AaiaabccacaqG2bGaaeyyaiaabYgacaqG1bGaaeyz% aiaabccacaqGPbGaaeOBaiaabccacaqG0bGaaeiAaiaabwgacaqGGa% Gaae4CaiaabggacaqGTbGaaeyzaiaabccacaqGVbGaaeiCaiaabwga% caqGUbGaaeiiaiaabEhacaqGHbGaaeiDaiaabwgacaqGYbGaaeiiai% aabohacaqGLbGaaeyyaiaabohacaqGVbGaaeOBaiaabccacaqGOaGa% aeyBaiaabMcaaaaccaGae8hiaaIaaKiEaiab-bcaGiaaigdacaaIWa% GaaGimaiaac6caaaa!CBD8!\[{\text{Biomass Index = }}\frac{\begin{gathered} {\text{water level fluctuation in the previous year}} \hfill \\ {\text{(m; calculated from monthly mean values)}} \hfill \\ \end{gathered} }{{{\text{Secchi disk value in the same open water season (m)}}}} \user1{x} 100.\]The whole illuminated littoral shifts due to water level fluctuation, which disturbs the zonation of the benthos. Such an increase or decrease in benthic biomass has been observed after one year of disturbance due to water level fluctuation. It need, however, a study based on the carefully planned and collected data, in which it can be taken account by a multivariate statistical analysis also the interactions between the important factors affected the littoral benthos.