Comparing induction at an early and late step in signal transduction mediating indirect defence in Brassica oleracea

The induction of plant defences involves a sequence of steps along a signal transduction pathway, varying in time course. In this study, the effects of induction of an early and a later step in plant defence signal transduction on plant volatile emission and parasitoid attraction are compared. Ion channel-forming peptides represent a class of inducers that induce an early step in signal transduction. Alamethicin (ALA) is an ion channel-forming peptide mixture from the fungus Trichoderma viride that can induce volatile emission and increase endogenous levels of jasmonic acid (JA) and salicylic acid in plants. ALA was used to induce an early step in the defence response in Brussels sprouts plants, Brassica oleracea var. gemmifera, and to study the effect on volatile emission and on the behavioural response of parasitoids to volatile emission. The parasitoid Cotesia glomerata was attracted to ALA-treated plants in a dose-dependent manner. JA, produced through the octadecanoid pathway, activates a later step in induced plant defence signal transduction, and JA also induces volatiles that are attractive to parasitoids. Treatment with ALA and JA resulted in distinct volatile blends, and both blends differed from the volatile blends emitted by control plants. Even though JA treatment of Brussels sprouts plants resulted in higher levels of volatile emission, ALA-treated plants were as attractive to C. glomerata as JA-treated plants. This demonstrates that on a molar basis, ALA is a 20 times more potent inducer of indirect plant defence than JA, although this hormone has more commonly been used as a chemical inducer of plant defence

Volatile Constituents, Inorganic Elements and Primary Screening of Bioactivity of Black Coral Cigarette Holders

Black corals (BC) have been used for a long time in Chinese medicine, and may have some pharmaceutical functions when used as material for cigarette holders in southeast China. This study is aimed to investigate the bioactivities of volatile constituents in BC and to explore the folklore behind the use of BC cigarette holders (BCCHs). We extracted the volatile constituents of BC by supercritical fluid extraction (SFE) with carbon dioxide (CO2-SFE), then identified and analyzed the constituents by gas chromatography-mass spectrometry (GC-MS). In total, 15 components were reliably identified in BC and found to be biologically active. These included triethyl phosphate, butylated hydroxytoluene, cedrol, n-hexadecanoic acid, squalene, and cholesterol. Meanwhile 13 inorganic elements (P, Ca, Mg, S, B, Si, Fe, Cu, Zn, Ba, etc.) were determined by inductively coupled plasma spectrometer (ICPS). In the bioactivity tests, the BC extract (BCE) showed a scavenging activity of 2,2-diphenyl-1-picrylhydrazyl free radicals and hydroxyl radicals by phenanthroline-Fe (II) oxidation and moderate inhibition of Gram-positive microorganisms. The antioxidant and antimicrobial activities of BC, which are related to the active chemical composition, may explain the perceived benefit for cigarette smokers who use BCCHs

The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

The recent US National Academies report "Assessment of Intraseasonal to Interannual Climate Prediction and Predictability" was unequivocal in recommending the need for the development of a North American Multi-Model Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users. The multi-model ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation, and has proven to produce better prediction quality (on average) then any single model ensemble. This multi-model approach is the basis for several international collaborative prediction research efforts, an operational European system and there are numerous examples of how this multi-model ensemble approach yields superior forecasts compared to any single model. Based on two NOAA Climate Test Bed (CTB) NMME workshops (February 18, and April 8, 2011) a collaborative and coordinated implementation strategy for a NMME prediction system has been developed and is currently delivering real-time seasonal-to-interannual predictions on the NOAA Climate Prediction Center (CPC) operational schedule. The hindcast and real-time prediction data is readily available (e.g., http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/) and in graphical format from CPC (http://origin.cpc.ncep.noaa.gov/products/people/wd51yf/NMME/index.html). Moreover, the NMME forecast are already currently being used as guidance for operational forecasters. This paper describes the new NMME effort, presents an overview of the multi-model forecast quality, and the complementary skill associated with individual models

Observational Evidence that Soil Moisture Variations Affect Precipitation

Land-atmosphere feedback, by which precipitation-induced soil moisture anomalies affect subsequent precipitation, may be an important element of Earth's climate system, but its very existence has never been demonstrated conclusively at regional to continental scales. Evidence for the feedback is sought in a 50-year observational precipitation dataset covering the United States. The precipitation variance and autocorrelation fields are characterized by features that agree (in structure, though not in magnitude) with those produced by an atmospheric general circulation model (AGCM). Because the model-generated features are known to result from land-atmosphere feedback alone, the observed features are highly suggestive of the existence of feedback in nature

New components of the honey bee (Apis mellifera L.) queen retinue pheromone

The honey bee queen produces pheromones that function in both releaser and primer roles such as attracting a retinue of workers around her, attracting drones on mating flights, preventing workers from reproducing at the individual (worker egg-laying) and colony (swarming) level, and regulating several other aspects of colony functioning. The queen mandibular pheromone (QMP), consisting of five synergistic components, is the only pheromone chemically identified in the honey bee (Apis mellifera L.) queen, but this pheromone does not fully duplicate the pheromonal activity of a full queen extract. To identify the remaining unknown compounds for retinue attraction, honey bee colonies were selectively bred to have low response to synthetic QMP and high response to a queen extract in a laboratory retinue bioassay. Workers from these colonies were then used in the bioassay to guide the isolation and identification of the remaining active components. Four new compounds were identified from several glandular sources that account for the majority of the difference in retinue attraction between synthetic QMP and queen extract: methyl (Z)-octadec-9-enoate (methyl oleate), (E)-3-(4-hydroxy-3-methoxyphenyl)-prop-2-en-1-ol (coniferyl alcohol), hexadecan-1-ol, and (Z9,Z12,Z15)-octadeca-9,12,15-trienoic acid (linolenic acid). These compounds were inactive alone or in combination, and they only elicited attraction in the presence of QMP. There was still unidentified activity remaining in the queen extract. The queen therefore produces a synergistic, multiglandular pheromone blend of at least nine compounds for retinue attraction, the most complex pheromone blend known for inducing a single behavior in any organism