Use of personal sporetraps to complement continuous aerobiological monitoring

We analysed pollen and spore data obtained from one continuous and two personal Burkard sporetraps during the spring months of three years (2007–2009). For the statistical analysis, the data was normalised with a log transformation, and then subjected to an ANOVA and a Pearson correlation analysis. The best time to use the personal samplers was determined from 15 years of continuous aerobiological monitoring pollen data to be between 11:00–16:00, when highest concentration was found and in a steady way. Height of sampling was compared at floor level and at 1.1 m with personal samplers; both of them were on a terrace at 6 m above the ground, but no statistically significant differences were found. The results revealed that there were apparently no differences between continuous and personal Burkard samplers for total pollen and spores. Nevertheless, distinguishing the main pollen types (i.e., Poaceae, Quercus, Olea, Cupressaceae, Plantago, and Platanus) revealed that there are some differences for Poaceae pollen only. In conclusion, personal samplers could be used to anticipate continuous monitoring data because their sampling is shorter and the results may be obtained quicker than with a continuous sampler, although they must never be considered as a replacement.     

Forecasting airborne Platanus pollen in the Madrid region

This study analyses the atmospheric concentration of Platanus pollen in four stations in the Madrid region over a period of 10 years (1994–2003). Various statistical analyses (regression analysis and decision tree) were used to prepare a forecasting model for possible application as a preventive measure in pollinosis. The data comes from the PALINOCAM network and the samplers used were Hirst type (Burkard pollen trap). Platanus pollen is present in the atmosphere during a short period of time in spring, and the maximum concentrations are detected during the last two weeks of March and the first week of April. Regression analysis shows that the pollen concentration of the two previous days is the best predictive variable. The models obtained for the four stations analysed account for between 37 and 61% of the variation in pollen levels in the air. The decision trees show how the introduction of meteorological variables improves prediction for this pollen type.     

Foraging trip duration of honeybee increases during a poor air quality episode and the increase persists thereafter

Increased concentration of airborne particulate matter (PM) in the atmosphere alters the degree of polarization of skylight which is used by honeybees for navigation during their foraging trips. However, little has empirically shown whether poor air quality indeed affects foraging performance (foraging trip duration) of honeybee. Here, we show apparent increases in the average duration of honeybee foraging during and after a heavy air pollution event compared with that of the pre‐event period. The average foraging duration of honeybees during the event increased by 32 min compared with the pre‐event conditions, indicating that 71% more time was spent on foraging. Moreover, the average foraging duration measured after the event did not recover to its pre‐event level. We further investigated whether an optical property (Depolarization Ratio, DR) of dominant PM in the atmosphere and level of air pollution (fine PM mass concentration) affect foraging trip duration. The result demonstrates the DR and fine PM mass concentration have significant effects on honeybee foraging trip duration. Foraging trip duration increases with decreasing DR while it increases with increasing fine PM mass concentration. In addition, the effects of fine PM mass concentration are synergistic with overcast skies. Our study implies that poor air quality could pose a new threat to bee foraging.     

Bacterial type III effector–induced plant C8 volatiles elicit antibacterial immunity in heterospecific neighbouring plants via airborne signalling

Upon sensing attack by pathogens and insect herbivores, plants release complex mixtures of volatile compounds. Here, we show that the infection of lima bean (Phaseolus lunatus L.) plants with the non-host bacterial pathogen Pseudomonas syringae pv. tomato led to the production of microbe-induced plant volatiles (MIPVs). Surprisingly, the bacterial type III secretion system, which injects effector proteins directly into the plant cytosol to subvert host functions, was found to prime both intra- and inter-specific defense responses in neighbouring wild tobacco (Nicotiana benthamiana) plants. Screening of each of 16 effectors using the Pseudomonas fluorescens effector-to-host analyser revealed that an effector, HopP1, was responsible for immune activation in receiver tobacco plants. Further study demonstrated that 1-octen-3-ol, 3-octanone and 3-octanol are novel MIPVs emitted by the lima bean plant in a HopP1-dependent manner. Exposure to synthetic 1-octen-3-ol activated immunity in tobacco plants against a virulent pathogen Pseudomonas syringae pv. tabaci. Our results show for the first time that a bacterial type III effector can trigger the emission of C8 plant volatiles that mediate defense priming via plant–plant interactions. These results provide novel insights into the role of airborne chemicals in bacterial pathogen-induced inter-specific plant–plant interactions.     

Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City,Northwest China

Crop biomass is an important ecological indicator of growth, light use efficiency, and carbon stocks in agro-ecosystems. Light detection and ranging (LiDAR) or laser scanning has been widely used to estimate forest structural parameters and biomass. However, LiDAR is rarely used to estimate crop parameters because the short, dense canopies of crops limit the accuracy of the results. The objective of this study is to explore the potential of airborne LiDAR data in estimating biomass components of maize, namely aboveground biomass (AGB) and belowground biomass (BGB). Five biomass-related factors were measured during the entire growing season of maize. The field-measured canopy height and leaf area index (LAI) were identified as the factors that most directly affect biomass components through Pearson's correlation analysis and structural equation modeling (SEM). Field-based estimation models were proposed to estimate maize biomass components during the tasseling stage. Subsequently, the maize height and LAI over the entire study area were derived from LiDAR data and were used as input for the estimation models to map the spatial pattern of the biomass components. The results showed that the LiDAR-estimated biomass was comparable to the field-measured biomass, with root mean squared errors (RMSE) of 288.51 g/m² (AGB), and 75.81 g/m² (BGB). In conclusion, airborne LiDAR has great potential for estimating canopy height, LAI, and biomass components of maize during the peak growing season.     

Remote sensing of forest gas exchange: Considerations derived from a tomographic perspective

The global exchange of gas (CO₂, H₂O) and energy (sensible and latent heat) between forest ecosystems and the atmosphere is often assessed using remote sensing (RS) products. Although these products are essential in quantifying the spatial variability of forest–atmosphere exchanges, large uncertainties remain from a measurement bias towards top of canopy fluxes since optical RS data are not sensitive for the vertically integrated forest canopy. We hypothesize that a tomographic perspective opens new pathways to advance upscaling gas exchange processes from leaf to forest stands and larger scales. We suggest a 3D modelling environment comprising principles of ecohydrology and radiative transfer modelling with measurements of micrometeorological variables, leaf optical properties and forest structure, and assess 3D fields of net CO₂ assimilation (A_n) and transpiration (T) in a Swiss temperate forest canopy. 3D simulations were used to quantify uncertainties in gas exchange estimates inherent to RS approaches and model assumptions (i.e. a big‐leaf approximation in modelling approaches). Our results reveal substantial 3D heterogeneity of forest gas exchange with top of canopy A_n and T being reduced by up to 98% at the bottom of the canopy. We show that a simplified use of RS causes uncertainties in estimated vertical gas exchange of up to 300% and that the spatial variation of gas exchange in the footprint of flux towers can exceed diurnal dynamics. We also demonstrate that big‐leaf assumptions can cause uncertainties up to a factor of 10 for estimates of A_n and T. Concluding, we acknowledge the large potential of 3D assessments of gas exchange to unravelling the role of vertical variability and canopy structure in regulating forest–atmosphere gas and energy exchange. Such information allows to systematically link canopy with global scale controls on forest functioning and eventually enables advanced understanding of forest responses to environmental change.     

Low-frequency airborne vibrations generated by crickets during singing and aggression

When crickets (Gryllus bimaculatus) produce their calling, courtship and rivalry songs, they generate, in addition to the audible stridulatory sound, low-frequency air oscillations associated with the inward and outward movements of the forewings. The frequencies of these oscillations are below ca 70 Hz, with a major component at 30 Hz, the syllable repetition rate. In the courtship song, single oscillations are also produced. Jerking movements of the whole body, which often occur in the presence of rivals, cause considerable air currents. In all these cases the air vibrations are sufficient to be perceived both by the individual generating them and by conspecifics (and perhaps by other insects) via air-flow receptors, in crickets the cercal filiform hairs.     

First volumetric airborne pollen sampling in Montevideo City,Uruguay

A volumetric aeropalynological sampling was carried out for the first time in MontevideoUruguay, from October 2000 to September 2001, using a Rotorod sampler Model 40. During the year 76 pollen types were identified. Airborne pollen was recorded over the year but a maximum pollen period was observed from August to April. For the rest of the months, pollen concentration was below 1% of the total annual pollen (TP). The pollen spectrum was characterized by the dominance of herbaceous pollen (NAP), which represented 68% of the TP and dominates the spectrum from November to March. Poaceae was the most frequent and abundant pollen type accounting for 45% of TP. The pollen spectrum reflected the floristic diversity of the city and most of the sources of airborne pollen are present in local and regional flora. Fourteen pollen types reach more than 1% of the TP and most of them are cited as allergenic pollen in other regions. These results may prove important for future medical research.     

A method for the direct detection of airborne dispersal in lichens

This study sets out a novel method to determine dispersal distances in lichens. Direct measurement of dispersal often remains difficult for lichens and other small inconspicuous species because of the need to track microscopic reproductive propagules, which even if they can be captured, cannot be identified using traditional morphological approaches. A low‐cost device (<£200) was developed to trap the reproductive propagules of lichens, capable of sampling around 0.1 m³ of air per minute. In parallel, molecular techniques were developed to enable species‐specific detection of propagules caught by the devices, with identification using novel species‐specific primers and optimization of a standard DNA extraction and nested PCR protocol. The methods were tested for both their sensitivity and specificity against a suite of lichen epiphytes, differing in their reproductive mechanisms, dispersal structures and rarity. Sensitivity tests showed that the molecular techniques could detect a single asexual propagule (soredium or isidium), or as few as 10 sexual spores. As proof of concept, propagule traps were deployed into a wooded landscape where the target epiphytes were present. Extractions from deployed propagule traps were sequenced, showing that the method was able to detect the presence of the target species in the atmosphere. As far as we are aware, this is the first attempt to use mechanized propagule traps in combination with DNA diagnostics to detect dispersal of lichens. The tests carried out here point the way for future dispersal studies of lichen epiphytes and other passively dispersed microscopic organisms including fungi or bryophytes.