Boosting species evenness, productivity and weed control in a mixed meadow by promoting arbuscular mycorrhizas

Lowland meadows represent aboveground and belowground biodiversity reservoirs in intensive agricultural areas, improving water retention and filtration, ensuring forage production, contrasting erosion and contributing to soil fertility and carbon sequestration. Besides such major ecosystem services, the presence of functionally different plant species improves forage quality, nutritional value and productivity, also limiting the establishment of weeds and alien species. Here, we tested the effectiveness of a commercial seed mixture in restoring a lowland mixed meadow in the presence or absence of inoculation with arbuscular mycorrhizal (AM) fungi and biostimulation of symbiosis development with the addition of short chain chito-oligosaccharides (CO). Plant community composition, phenology and productivity were regularly monitored alongside AM colonization in control, inoculated and CO-treated inoculated plots. Our analyses revealed that the CO treatment accelerated symbiosis development significantly increasing root colonization by AM fungi. Moreover, the combination of AM fungal inoculation and CO treatment improved plant species evenness and productivity with more balanced composition in forage species. Altogether, our study presented a successful and scalable strategy for the reintroduction of mixed meadows as valuable sources of forage biomass; demonstrated the positive impact of CO treatment on AM development in an agronomic context, extending previous observations developed under controlled laboratory conditions and leading the way to the application in sustainable agricultural practices.

Plant invasion risk inside and outside protected areas: Propagule pressure, abiotic and biotic factors definitively matter

Invasive alien species are among the main global drivers of biodiversity loss posing major challenges to nature conservation and to managers of protected areas. The present study applied a methodological framework that combined invasive Species Distribution Models, based on propagule pressure, abiotic and biotic factors for 14 invasive alien plants of Union concern in Italy, with the local interpretable model-agnostic explanation analysis aiming to map, evaluate and analyse the risk of plant invasions across the country, inside and outside the network of protected areas. Using a hierarchical invasive Species Distribution Model, we explored the combined effect of propagule pressure, abiotic and biotic factors on shaping invasive alien plant occurrence across three biogeographic regions (Alpine, Continental, and Mediterranean) and realms (terrestrial and aquatic) in Italy. We disentangled the role of propagule pressure, abiotic and biotic factors on invasive alien plant distribution and projected invasion risk maps. We compared the risk posed by invasive alien plants inside and outside protected areas. Invasive alien plant distribution varied across biogeographic regions and realms and unevenly threatens protected areas. As an alien's occurrence and risk on a national scale are linked with abiotic factors followed by propagule pressure, their local distribution in protected areas is shaped by propagule pressure and biotic filters. The proposed modelling framework for the assessment of the risk posed by invasive alien plants across spatial scales and under different protection regimes represents an attempt to fill the gap between theory and practice in conservation planning helping to identify scale, site, and species-specific priorities of management, monitoring and control actions. Based on solid theory and on free geographic information, it has great potential for application to wider networks of protected areas in the world and to any invasive alien plant, aiding improved management strategies claimed by the environmental legislation and national and global strategies.

Air Pollution and Aeroallergens as Possible Triggers in Preterm Birth Delivery

Preterm birth (PTB) identifies infants prematurely born <37 weeks/gestation and is one of the main causes of infant mortality. PTB has been linked to air pollution exposure, but its timing is still unclear and neglects the acute nature of delivery and its association with short-term effects. We analyzed 3 years of birth data (2015−2017) in Turin (Italy) and the relationships with proinflammatory chemicals (PM2.5, O3, and NO2) and biological (aeroallergens) pollutants on PTB vs. at-term birth, in the narrow window of a week before delivery. A tailored non-stationary Poisson model correcting for seasonality and possible confounding variables was applied. Relative risk associated with each pollutant was assessed at any time lag between 0 and 7 days prior to delivery. PTB risk was significantly associated with increased levels of both chemical (PM2.5, RR = 1.023 (1.003−1.043), O3, 1.025 (1.001−1.048)) and biological (aeroallergens, RR ~ 1.01 (1.0002−1.016)) pollutants in the week prior to delivery. None of these, except for NO2 (RR = 1.01 (1.002−1.021)), appeared to play any role on at-term delivery. Pollutant-induced acute inflammation eliciting delivery in at-risk pregnancies may represent the pathophysiological link between air pollution and PTB, as testified by the different effects played on PTB revealed. Further studies are needed to better elucidate a possible exposure threshold to prevent PTB.

Covid-19 pandemic in north-west Italy: the potential role of meteorology, air pollution and pollens

Background

Italy was the first western country severely affected by the Covid-19 pandemic attesting more than 16 million cases since the outbreak began. Po Valley regions have been most afflicted, with Piedmont ranking sixth at 25,899 cases/100,000 inhabitants. Within this area, air dispersion is hampered making Po Valley a recognised air pollution hotspot. We aimed to explore the potential association between the environment and Covid-19 incidence.

Methods

Daily key air pollutants (NO2, NO, CO, O3, PM10, and PM2.5), meteorological parameters (temperature, %humidity, wind speed and solar radiation), pollens and Covid-19 cases were collected from 01/01 to 31/12/2021 in Turin, Italy. This ecological study preliminarily tested correlations (Spearman) between air pollutants and Covid-19 cases.

Results

The Covid-19 pandemic followed a seasonal trend with the highest number of cases (/100,000 inhabitants) in winter and spring (3.1) followed by autumn (1.3) and summer (0.5) (KW test p < 0.0001). Likewise, all air pollutants showed peaks in winter and autumn and sensibly decreased during spring and summer apart from pollens and O3. O3 follows the photochemical processes reaching its peak in the sunniest periods, while pollens undergo their natural vegetative process. Daily Covid-19 cases were positively correlated with daily-averaged NO2 (0.50, p < 0.0001), NO (0.48, p < 0.0001), CO (0.81, p < 0.0001), PM10 (0.36, p < 0.0001), PM2.5 (0.39, p < 0.0001), pollens (0.15, p = 0.073) and inversely with O3 (-0.44, p < 0.0001). We plan future analyses to test the hypothesized association by enhanced models with lagged air pollution variables, with demographic characteristics and meteorological data as potential confounders.

Conclusions

Results from ecological studies may support researchers’ preliminary understanding of the interplay between environment and Public Health issues, including pandemics. A multidisciplinary approach is mandatory to deepen the complexity of this topic across European regions

Key messages

• The Covid-19 pandemic may be associated with environmental conditions and air pollution but further research is needed.

• Atmospheric particulate matter, including aeroallergens, can favour many airborne-related diseases by acting as immune suppressor and/or carrier, but these hypotheses deserve future research.

Radial stem growth dynamics and phenology of a multi-stemmed species (Corylus avellana L.) across orchards in the Northern and Southern hemispheres

Climate change and the global economy impose new challenges in the management of food-producing trees and require studying how to model plant physiological responses, namely growth dynamics and phenology. Hazelnut (Corylus avellana L.) is a multi-stemmed forest species domesticated for nut production and now widely spread across different continents. However, information on stem growth and its synchronization with leaf and reproductive phenology is extremely limited. This study aimed at (i) defining the sequencing of radial growth phases in hazelnut (onset, maximum growth and cessation) and the specific temperature triggering stem growth; and (ii) combining the stem growth phases with leaf and fruit phenology. Point dendrometers were installed on 20 hazelnut trees across eight orchards distributed in the Northern and Southern hemisphere during a period of three growing seasons between 2015 and 2018. The radial growth variations and climatic parameters were averaged and recorded every 15 min. Leaf and reproductive phenology were collected weekly at each site. Results showed that stem radial growth started from day of year 84 to 134 in relation to site and year but within a relatively narrow range of temperature (from 13 to 16.5 °C). However, we observed a temperature-related acclimation in the cultivar Tonda di Giffoni. Maximum growth always occurred well before the summer solstice (on average 35 days) and before the maximum annual air temperatures. Xylogenesis developed rapidly since the time interval between onset and maximum growth rate was about 3 weeks. Importantly, the species showed an evident delay of stem growth onset with respect to leaf emergence (on average 4-6 weeks) rarely observed in tree species. These findings represent the first global analysis of radial growth dynamics in hazelnut, which is an essential step for developing models on orchard functioning and management on different continents.

Hazelnut Pollen Phenotyping Using Label-Free Impedance Flow Cytometry

Impedance flow cytometry (IFC) is a versatile lab-on-chip technology which enables fast and label-free analysis of pollen grains in various plant species, promising new research possibilities in agriculture and plant breeding. Hazelnut is a monoecious, anemophilous species, exhibiting sporophytic self-incompatibility. Its pollen is dispersed by wind in midwinter when temperatures are still low and relative humidity is usually high. Previous research found that hazelnut can be characterized by high degrees of pollen sterility following a reciprocal chromosome translocation occurring in some cultivated genotypes. In this study, IFC was used for the first time to characterize hazelnut pollen biology. IFC was validated via dye exclusion in microscopy and employed to (i) follow pollen hydration over time to define the best pre-hydration treatment for pollen viability evaluation; (ii) test hazelnut pollen viability and sterility on 33 cultivars grown in a collection field located in central Italy, and two wild hazelnuts. The accessions were also characterized by their amount and distribution of catkins in the tree canopy. Pollen sterility rate greatly varied among hazelnut accessions, with one main group of highly sterile cultivars and a second group, comprising wild genotypes and the remaining cultivars, producing good quality pollen. The results support the hypothesis of recurring reciprocal translocation events in Corylus avellana cultivars, leading to the observed gametic semi-sterility. The measured hazelnut pollen viability was also strongly influenced by pollen hydration (R adj 2 = 0.83, P ≤ 0.0001) and reached its maximum at around 6 h of pre-hydration in humid chambers. Viable and dead pollen were best discriminated at around the same time of pollen pre-hydration, suggesting that high humidity levels are required for hazelnut pollen to maintain its functionality. Altogether, our results detail the value of impedance flow cytometry for high throughput phenotyping of hazelnut pollen. Further research is required to clarify the causes of pollen sterility in hazelnut, to confirm the role of reciprocal chromosome translocations and to investigate its effects on plant productivity.

Quantitative methods in microscopy to assess pollen viability in different plant taxa

High-quality pollen is a prerequisite for plant reproductive success. Pollen viability and sterility can be routinely assessed using common stains and manual microscope examination, but with low overall statistical power. Current automated methods are primarily directed towards the analysis of pollen sterility, and high throughput solutions for both pollen viability and sterility evaluation are needed that will be consistent with emerging biotechnological strategies for crop improvement. Our goal is to refine established labelling procedures for pollen, based on the combination of fluorescein (FDA) and propidium iodide (PI), and to develop automated solutions for accurately assessing pollen grain images and classifying them for quality. We used open-source software programs (CellProfiler, CellProfiler Analyst, Fiji and R) for analysis of images collected from 10 pollen taxa labelled using FDA/PI. After correcting for image background noise, pollen grain images were examined for quality employing thresholding and segmentation. Supervised and unsupervised classification of per-object features was employed for the identification of viable, dead and sterile pollen. The combination of FDA and PI dyes was able to differentiate between viable, dead and sterile pollen in all the analysed taxa. Automated image analysis and classification significantly increased the statistical power of the pollen viability assay, identifying more than 75,000 pollen grains with high accuracy (R² = 0.99) when compared to classical manual counting. Overall, we provide a comprehensive set of methodologies as baseline for the automated assessment of pollen viability using fluorescence microscopy, which can be combined with manual and mechanized imaging systems in fundamental and applied research on plant biology. We also supply the complete set of pollen images (the FDA/PI pollen dataset) to the scientific community for future research.

Pollen concentrations and prevalence of asthma and allergic rhinitis in Italy: Evidence from the GEIRD study

BACKGROUND

Pollen exposure has acute adverse effects on sensitized individuals. Information on the prevalence of respiratory diseases in areas with different pollen concentrations is scanty.

AIM

We performed an ecologic analysis to assess whether the prevalence of allergic rhinitis and asthma in young adults varied across areas with different pollen concentrations in Italy.

METHODS

A questionnaire on respiratory diseases was delivered to random samples of 20-44year-old subjects from six centers in 2005-2010. Data on the daily air concentrations of 7 major allergologic pollens (Poaceae, Urticaceae, Oleaceae, Cupressaceae, Coryloideae, Betula and Ambrosia) were collected for 2007-2008. Center-specific pollen exposure indicators were calculated, including the average number of days per year with pollens above the low or high concentration thresholds defined by the Italian Association of Aerobiology. Associations between pollen exposure and disease prevalence, adjusted for potential confounders, were estimated using logistic regression models with center as a random-intercept.

RESULTS

Overall, 8834 subjects (56.8%) filled in the questionnaire. Allergic rhinitis was significantly less frequent in the centers with longer periods with high concentrations of at least one (OR per 10days=0.989, 95%CI: 0.979-0.999) or at least two pollens (OR=0.974, 95%CI: 0.951-0.998); associations with the number of days with at least one (OR=0.988, 95%CI: 0.972-1.004) or at least two (OR=0.985, 95%CI: 0.970-1.001) pollens above the low thresholds were borderline significant. Asthma prevalence was not associated with pollen concentrations.

CONCLUSIONS

Our study does not support that the prevalence of allergic rhinitis and asthma is greater in centers with higher pollen concentrations. It is not clear whether the observed ecologic associations hold at the individual level.

Air pollution, aeroallergens and admissions to pediatric emergency room for respiratory reasons in Turin, northwestern Italy

Background

Air pollution can cause respiratory symptoms or exacerbate pre-existing respiratory diseases, especially in children. This study looked at the short-term association of air pollution concentrations with Emergency Room (ER) admissions for respiratory reasons in pediatric age (0–18 years).

Methods

Daily number of ER admissions in a children’s Hospital, concentrations of urban-background PM_2.5, NO₂, O₃ and total aeroallergens (Corylaceae, Cupressaceae, Gramineae, Urticaceae, Ambrosia, Betula) were collected in Turin, northwestern Italy, for the period 1/08/2008 to 31/12/2010 (883 days). The associations between exposures and ER admissions were estimated, at time lags between 0 and 5 days, using generalized linear Poisson regression models, adjusted for non-meteorological potential confounders.

Results

In the study period, 21,793 ER admissions were observed, mainly (81 %) for upper respiratory tract infections. Median air pollution concentrations were 22.0, 42.5, 34.1 μg/m³ for urban-background PM_2.5, NO₂, and O₃, respectively, and 2.9 grains/m³ for aeroallergens. We found that ER admissions increased by 1.3 % (95 % CI: 0.3-2.2 %) five days after a 10 μg/m³ increase in NO₂, and by 0.7 % (95 % CI: 0.1-1.2 %) one day after a 10 grains/m³ increase in aeroallergens, while they were not associated with PM_2.5 concentrations. ER admissions were negatively associated with O₃ and aeroallergen concentrations at some time lags, but these association shifted to the null when meteorological confounders were adjusted for in the models.

Conclusions

Overall, these findings confirm adverse short-term health effects of air pollution on the risk of ER admission in children and encourage a careful management of the urban environment to health protection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-016-3376-3) contains supplementary material, which is available to authorized users.

Five years of phenological monitoring in a mountain grassland: inter-annual patterns and evaluation of the sampling protocol

The increasingly important effect of climate change and extremes on alpine phenology highlights the need to establish accurate monitoring methods to track inter-annual variation (IAV) and long-term trends in plant phenology. We evaluated four different indices of phenological development (two for plant productivity, i.e., green biomass and leaf area index; two for plant greenness, i.e., greenness from visual inspection and from digital images) from a 5-year monitoring of ecosystem phenology, here defined as the seasonal development of the grassland canopy, in a subalpine grassland site (NW Alps). Our aim was to establish an effective observation strategy that enables the detection of shifts in grassland phenology in response to climate trends and meteorological extremes. The seasonal development of the vegetation at this site appears strongly controlled by snowmelt mostly in its first stages and to a lesser extent in the overall development trajectory. All indices were able to detect an anomalous beginning of the growing season in 2011 due to an exceptionally early snowmelt, whereas only some of them revealed a later beginning of the growing season in 2013 due to a late snowmelt. A method is developed to derive the number of samples that maximise the trade-off between sampling effort and accuracy in IAV detection in the context of long-term phenology monitoring programmes. Results show that spring phenology requires a smaller number of samples than autumn phenology to track a given target of IAV. Additionally, productivity indices (leaf area index and green biomass) have a higher sampling requirement than greenness derived from visual estimation and from the analysis of digital images. Of the latter two, the analysis of digital images stands out as the more effective, rapid and objective method to detect IAV in vegetation development.

Models to predict the start of the airborne pollen season

Aerobiological data can be used as indirect but reliable measures of flowering phenology to analyze the response of plant species to ongoing climate changes. The aims of this study are to evaluate the performance of several phenological models for predicting the pollen start of season (PSS) in seven spring-flowering trees (Alnus glutinosa, Acer negundo, Carpinus betulus, Platanus occidentalis, Juglans nigra, Alnus viridis, and Castanea sativa) and in two summer-flowering herbaceous species (Artemisia vulgaris and Ambrosia artemisiifolia) by using a 26-year aerobiological data set collected in Turin (Northern Italy). Data showed a reduced interannual variability of the PSS in the summer-flowering species compared to the spring-flowering ones. Spring warming models with photoperiod limitation performed best for the greater majority of the studied species, while chilling class models were selected only for the early spring flowering species. For Ambrosia and Artemisia, spring warming models were also selected as the best models, indicating that temperature sums are positively related to flowering. However, the poor variance explained by the models suggests that further analyses have to be carried out in order to develop better models for predicting the PSS in these two species. Modeling the pollen season start on a very wide data set provided a new opportunity to highlight the limits of models in elucidating the environmental factors driving the pollen season start when some factors are always fulfilled, as chilling or photoperiod or when the variance is very poor and is not explained by the models.

European larch phenology in the Alps: can we grasp the role of ecological factors by combining field observations and inverse modelling?

Vegetation phenology is strongly influenced by climatic factors. Climate changes may cause phenological variations, especially in the Alps which are considered to be extremely vulnerable to global warming. The main goal of our study is to analyze European larch (Larix decidua Mill.) phenology in alpine environments and the role of the ecological factors involved, using an integrated approach based on accurate field observations and modelling techniques. We present 2 years of field-collected larch phenological data, obtained following a specifically designed observation protocol. We observed that both spring and autumn larch phenology is strongly influenced by altitude. We propose an approach for the optimization of a spring warming model (SW) and the growing season index model (GSI) consisting of a model inversion technique, based on simulated look-up tables (LUTs), that provides robust parameter estimates. The optimized models showed excellent agreement between modelled and observed data: the SW model predicts the beginning of the growing season (B(GS)) with a mean RMSE of 4 days, while GSI gives a prediction of the growing season length (L(GS)) with a RMSE of 5 days. Moreover, we showed that the original GSI parameters led to consistent errors, while the optimized ones significantly increased model accuracy. Finally, we used GSI to investigate interactions of ecological factors during springtime development and autumn senescence. We found that temperature is the most effective factor during spring recovery while photoperiod plays an important role during autumn senescence: photoperiod shows a contrasting effect with altitude decreasing its influence with increasing altitude.

Occurrence of sialidase activity in two distinct and highly homogeneous populations of lysosomes prepared from the brain of developing mouse

Light and heavy lysosomes of mouse forebrain were separated from each other by centrifugation on a Percoll gradient. Light lysosomes were then freed from mitochondria and membranes by sucrose density gradient centrifugation and further purified by floatation-centrifugation on a sucrose gradient. The final preparations of light and heavy lysosomes, fairly homogenous, carried sialidase activity, assayed on MU-NeuAc. The optimal pH was 4.0 and 4.2, the apparent Km value 2.8 x 10(-5) M and 4.2 x 10(-5) M and the apparent Vmax value 0.11 and 0.47 mU.mg-1 protein, for the light and heavy lysosome sialidase, respectively. From 4 days to adulthood the specific activity of the light and heavy lysosome sialidase increased 3-fold and 1.7-fold, respectively.

Solubilization of the membrane-bound sialidase from pig brain by treatment with bacterial phosphatidylinositol phospholipase C

The total pellet from pig forebrain (from which the cytosolic sialidase was completely washed out) was treated with phosphatidylinositol phospholipase C (PIPLC) and centrifuged at high speed. The supernatant contained sialidase and 5'-nucleotidase activities. The greatest liberation of sialidase was obtained after incubation for 20 min with PIPLC at 37 degrees C using pH 6.0 and a ratio between PIPLC (as units) and protein of 1.6. Under these conditions, the release of sialidase, 5'-nucleotidase, and protein was 22, 50, and 18.5%, respectively. On treatment with PIPLC, a purified preparation of pig brain neuronal (synaptosomal) membranes released 28% of its sialidase whereas a purified preparation of pig brain lysosomes did not liberate any sialidase activity. The pH optimum of sialidase present in the supernatant obtained after PIPLC treatment of the total pellet was 4.2, the same as that of the enzyme embedded in the membrane. When this supernatant was subjected to ammonium sulfate fractionation, 88% of its sialidase, having a pH optimum of 4.2, was recovered in the fraction precipitated between 20 and 45% of salt saturation and subsequently dialyzed. Ammonium sulfate treatment caused the appearance of a second sialidase activity, having a pH optimum of 6.6 and behaving on fractionation similarly to the pH 4.2 sialidase. The Km and Vmax values of pH 4.2 and pH 6.6 sialidase were similar (1.48 x 10(-4) and 0.98 x 10(-4) M for Km and 1.6 and 1.4 mU/mg of protein for Vmax, respectively), whereas the stability on standing at 4 degrees C or exposure to freezing and thawing cycles was greater for pH 4.2 sialidase.(ABSTRACT TRUNCATED AT 250 WORDS)

Occurrence in brain lysosomes of a sialidase active on ganglioside

A lysosomal preparation, obtained from brain homogenate of 17-day-old C57BL mice by centrifugation on a self-generating Percoll linear density gradient, showed relative specific activity (RSA) values for typical lysosomal enzymes of 40-120 and for mitochondria, plasma membrane, and cytosol markers of much lower than 1, a result indicating a high degree of homogeneity. The lysosomal preparation contained a sialidase activity that was assayed radiometrically with ganglioside [3H]GD1a and fluorimetrically with 4-methylumbelliferyl-1-alpha-D-N-acetylneuraminic acid (MUB-NeuAc). The properties of the lysosomal enzyme were compared with those of the plasma membrane-bound sialidase contained in a purified synaptosomal plasma membrane fraction that was prepared from the same homogenate and assayed with the same substrates. The optimal pH was 4.2 for the lysosomal and 5.1 for the plasma membrane-bound enzyme. The apparent Km values for GD1a and MUB-NeuAc were 1.5 X 10(-5) and 4.2 X 10(-5) M, respectively, for the lysosomal enzyme and 2.7 X 10(-4) and 6.3 X 10(-5) M for the plasma membrane-bound one. Triton X-100 had a predominantly inhibitory effect on the lysosomal enzyme, whereas it strongly activated the plasma membrane-bound one. The lysosomal enzyme was highly unstable on storage and freezing and thawing cycles, whereas the plasma membrane-bound one was substantially stable. The RSA value of the lysosomal sialidase in the lysosomal fraction closely resembled that of authentic lysosomal enzymes, whereas the RSA value of plasma membrane-bound sialidase in the plasma membrane fraction was very similar to that of typical plasma membrane markers.(ABSTRACT TRUNCATED AT 250 WORDS)