scholarly journals Pollen Production of Quercus in the North-Western Iberian Peninsula and Airborne Pollen Concentration Trends during the Last 27 Years

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 702
Author(s):  
María Fernández-González ◽  
Estefanía González-Fernández ◽  
Helena Ribeiro ◽  
Ilda Abreu ◽  
F. Javier Rodríguez-Rajo
Keyword(s):  
Climate Change ◽  
Airborne Pollen ◽  
Pollen Grains ◽  
Maximum Temperature ◽  
Pollen Production ◽  
Pollen Monitoring ◽  
Main Pollen Season ◽  
Pollen Concentrations ◽  
Oak Pollen ◽  
The Impact

Natural forests are considered a reservoir of great biological diversity constituting one of the most important ecosystems in Europe. Quercus study is essential to assess ecological conservation of forests, and also of economic importance for different industries. In addition, oak pollen can cause high sensitization rates of respiratory allergies in pollen-allergy sufferers. This study sought to know the pollen production of six oak species in the transitional area between the Eurosiberian and Mediterranean Bioclimatic Regions, and to assess the impact of climate change on airborne oak pollen concentrations. The study was conducted in Ourense (NW Spain) over the 1993–2019 period. A Lanzoni VPPS 2000 volumetric trap monitored airborne pollen. A pollen production study was carried out in ten trees randomly selected in several Quercus forest around the Ourense city. Oak pollen represented around 14% of annual total pollen registered in the atmosphere of Ourense, showing an increasing trend during the last decade. Pollen production of the six studied oak species follow the proportions 1:1:2:5:90:276 for Q. ilex, Q. faginea, Q. rubra, Q. suber, Q. pyrenaica, and Q. robur respectively. We detected a significant trend to the increase of the annual maximum temperature, whereas a decrease of the maximum and mean temperatures during three previous months to oak flowering. This could be related with the detected trend to a delay of the oak Main Pollen Season onset of 0.47 days per year. We also found significant trends to an increase of the annual pollen integral of 7.9% pollen grains per year, and the pollen peak concentration of 7.5% pollen grains per year. Quercus airborne pollen monitoring as well as the knowledge of the reproductive behavior of the main oak species, bring us an important support tool offering a promising bio-indicator to detect ecological variations induced by climate change.

scholarly journals Neural networks for increased accuracy of allergenic pollen monitoring

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marcel Polling ◽  
Chen Li ◽  
Lu Cao ◽  
Fons Verbeek ◽  
Letty A. de Weger ◽  
...  
Keyword(s):  
Neural Networks ◽  
Airborne Pollen ◽  
Pollen Grains ◽  
Allergenic Pollen ◽  
Herbarium Specimens ◽  
Pollen Monitoring ◽  
Pollen Concentrations ◽  
Source Of Information ◽  
Urticaceae Pollen

AbstractMonitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of Convolutional Neural Networks (CNNs) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species has very low allergenic relevance, pollen from several species of Parietaria is severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these without the often used acetolysis step to train the CNN model. The models show that unacetolyzed Urticaceae pollen grains can be distinguished with > 98% accuracy. We then apply our model on before unseen Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.

scholarly journals The course of birch pollen seasons in Sosnowiec (Southern Poland) in 1997–2020 in relation to meteorological conditions

Aerobiologia ◽  
2021 ◽  
Author(s):  
Katarzyna Dąbrowska-Zapart ◽  
Tadeusz Niedźwiedź
Keyword(s):  
Wind Speed ◽  
Pollen Season ◽  
Birch Pollen ◽  
Pollen Grains ◽  
Meteorological Conditions ◽  
Maximum Temperature ◽  
Synoptic Situation ◽  
Pollen Concentrations ◽  
Pollen Seasons ◽  
The Impact

AbstractThe study's main objective was to specify the extent to which weather conditions were related to the course of birch pollen seasons in the years 1997–2020. The impact of atmospheric conditions on the daily concentrations of birch pollen grains, the Annual pollen integral (APIn), and the length of pollen seasons were studied. The dependency between each meteorological condition and various features of the birch pollen season was determined using Spearman’s rho correlation, the Kruskal–Wallis test, and cluster analysis with the k-means method. It has been shown that the duration of sunshine and average air temperature occurring within 14 days preceding the season has the most significant influence on the beginning of a birch pollen season. The value of daily birch pollen concentrations in Sosnowiec showed a statistically significant positive correlation with the duration of sunlight and the average and maximum wind speed. The daily concentration also depended on the synoptic situation: the mass airflow direction, the type of air mass inflow, and the type of weather front. The near-ground temperature influenced the APIn of birch pollen grains during the period of 14 days before the beginning of the season and the meteorological conditions occurring in the summer of the preceding year such as the maximum temperature, duration of sunlight, the maximum and average wind speed, and the relative air humidity. It was concluded that the length of birch pollen seasons decreased year by year.

scholarly journals How will climate change alter the dynamics of airborne pollen and pollen load of allergenic plants?

2020 ◽  
Author(s):  
Herwig A. E. Schinko ◽  
Bernd Lamprecht ◽  
Roland Schmidt
Keyword(s):  
Climate Change ◽  
Meteorological Parameters ◽  
Pollen Load ◽  
Pollen Allergens ◽  
Pollen Monitoring ◽  
Allergenic Plants ◽  
Pollen Concentrations ◽  
Pollen Seasons ◽  
The Impact ◽  
Seasonal Pollen

Summary Background Globally, climate change is being observed. Pollen allergies have been increasing since the middle of the last century. Outdoors, sensitization against pollen allergens is responsible for the highest prevalence of allergies of eyes and airways. Hence, the following two questions arose: (1) How does climate change become manifest locally–regionally, and do temperatures and precipitation have to be considered exceptional in 2018? (2) How do changing meteorological conditions impact on pollination and pollen load? Methods Pollen data of the main allergenic plants—collected at the pollen monitoring station Linz, Upper Austria—were analysed; 2018 was compared to the years 1993–2017. By means of statistical methods, the impact of meteorological parameters on pollen seasons and pollen load were examined. Results Climate change was confirmed for the region. The regional climate has shifted from moderate to warmer and drier (semi-arid) conditions. Preseasonal cumulated meteorological parameters determined flowering and pollen seasons (PS). Start and duration of the pollination of hazel, alder, birch, and grass followed other rules than the seasonal pollen production, termed seasonal pollen integral (SPIn). By its hybrid character, the model-year 2018 offered the unique chance to generate and explain different scenarios of pollen emission and transmission. For the start of flowering of hazel (Corylus), alder (Alnus) and birch (Betula), the coincidence of cumulated mean daily warmth (MDWcumul) and a distinct threshold for the highest temperature of a day (HTD) is necessary and species-specific. In 2018, the earliest begin of the pollen season (PSB) was observed. Frost delayed the PSB. Preseasonal frost as well as cool temperatures caused SPIn of alder and birch to rise, whereas SPIn of hazel were increased by warmer temperatures. Warm weather prolonged pollen seasons of early flowering plants. Heat combined with drought shortened PS of birch in 2018. Cumulated relative humidity (RHcumul) correlated highly significant with the PSB of grasses. Warm and dry conditions in 2018 caused the earliest PSB of grass since 1993. Over the years, SPI and major pollen peaks of grasses have decreased, primarily due to dryness. Conclusion The assumption that climate warming in Linz over 26 years should have increased pollen concentrations of allergenic plants was not confirmed. On the contrary, trend analyses showed that the pollen load has decreased. Hence, the increase in sensitization to pollen allergens and of the prevalence of pollen allergies ask for other explanations.

scholarly journals Automatic Image Classification Using Neural Networks Increases Accuracy for Allergenic Pollen Monitoring

2020 ◽  
Author(s):  
Marcel Polling ◽  
Chen Li ◽  
Lu Cao ◽  
Fons Verbeek ◽  
Letty de Weger ◽  
...  
Keyword(s):  
Airborne Pollen ◽  
Pollen Grains ◽  
Allergenic Pollen ◽  
Herbarium Specimens ◽  
Pollen Monitoring ◽  
Pollen Concentrations ◽  
Family Level ◽  
Source Of Information ◽  
Urticaceae Pollen

Abstract Monitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen are traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of a Convolutional Neural Network (CNN) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species have very low allergenic relevance, those from several species of Parietaria are severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these to train the CNN model VGG16. The model shows that Urticaceae pollen can be distinguished with 98.3% accuracy. We then apply our model on Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.

scholarly journals The impact of climate change in wheat and barley yields in the Iberian Peninsula

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Virgílio A. Bento ◽  
Andreia F. S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Rita M. Cardoso ◽  
...  
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Model ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Historical Period ◽  
Early Winter ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Spring Maximum

AbstractThe impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies.

scholarly journals Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Negative Impact ◽  
Positive Impact ◽  
Information Criterion ◽  
Growing Season ◽  
Maximum Temperature ◽  
Linear Regression Models ◽  
The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

scholarly journals Spatial-temporal changes in river runoff and terrestrial ecosystem water retention under 1.5 °C and 2 °C warming scenarios across China

2017 ◽  
Author(s):  
Ran Zhai ◽  
Fulu Tao ◽  
Zhihui Xu
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
River Runoff ◽  
Water Retention ◽  
Terrestrial Ecosystem ◽  
Maximum Temperature ◽  
Climate Scenarios ◽  
Warming Scenario ◽  
Basin Scale ◽  
The Impact

Abstract. The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 ℃ above pre-industrial levels, and pursuing efforts to limit this to 1.5 ℃, it is therefore important to understand the impacts of climate change under 1.5 ℃ and 2.0 ℃ warming scenarios for climate adaptation and mitigation. Here, climate scenarios by four Global Circulation Models (GCMs) for the baseline (2006–2015), 1.5 ℃ and 2.0 ℃ warming scenarios (2106–2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on river runoff and Terrestrial Ecosystem Water Retention (TEWR) in China. The trends in annual mean temperature, precipitation, river runoff and TEWR were analysed at the grid and basin scale. Results showed that there were large uncertainties in climate scenarios from the different GCMs, which led to large uncertainties in the impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. The interannual variability of river runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from 1.5 ℃ warming scenario to 2.0 ℃ warming scenario. By contrast, TEWR would remain relatively stable. Both extreme low and high river runoff would increase under the two warming scenarios in most areas in China, with high river runoff increasing more. And the risk of extreme river runoff events would be higher under 2.0 ℃ warming scenario than under 1.5 ℃ warming scenario in term of both extent and intensity. River runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause river runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our findings highlight climate change mitigation and adaptation should be taken to reduce the risks of hydrological extreme events.

scholarly journals The late flowering of invasive species contributes to the increase of Artemisia allergenic pollen in autumn: an analysis of 25 years of aerobiological data (1995–2019) in Trentino-Alto Adige (Northern Italy)

Aerobiologia ◽  
2020 ◽  
Vol 36 (4) ◽  
pp. 669-682 ◽  
Author(s):  
Antonella Cristofori ◽  
Edith Bucher ◽  
Michele Rossi ◽  
Fabiana Cristofolini ◽  
Veronika Kofler ◽  
...  
Keyword(s):  
Invasive Species ◽  
Pollen Season ◽  
Airborne Pollen ◽  
Pollen Grains ◽  
Late Summer ◽  
Natura 2000 ◽  
Allergenic Pollen ◽  
Pollen Concentration ◽  
Pollen Concentrations ◽  
Negative Impacts

AbstractArtemisia pollen is an important aeroallergen in late summer, especially in central and eastern Europe where distinct anemophilous Artemisia spp. produce high amounts of pollen grains. The study aims at: (i) analyzing the temporal pattern of and changes in the Artemisia spp. pollen season; (ii) identifying the Artemisia species responsible for the local airborne pollen load.Daily pollen concentration of Artemisia spp. was analyzed at two sites (BZ and SM) in Trentino-Alto Adige, North Italy, from 1995 to 2019.The analysis of airborne Artemisia pollen concentrations evidences the presence of a bimodal curve, with two peaks, in August and September, respectively. The magnitude of peak concentrations varies across the studied time span for both sites: the maximum concentration at the September peak increases significantly for both the BZ (p < 0.05) and SM (p < 0.001) site. The first peak in the pollen calendar is attributable to native Artemisia species, with A. vulgaris as the most abundant; the second peak is mostly represented by the invasive species A. annua and A. verlotiorum (in constant proportion along the years), which are causing a considerable increase in pollen concentration in the late pollen season in recent years.. The spread of these species can affect human health, increasing the length and severity of allergenic pollen exposure in autumn, as well as plant biodiversity in both natural and cultivated areas, with negative impacts on, e.g., Natura 2000 protected sites and crops.

scholarly journals Integrating Phenological, Aerobiological and Weather Data to Study the Local and Regional Flowering Dynamics of Four Grapevine Cultivars

Agronomy ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 185
Author(s):  
María Fernández-González ◽  
Helena Ribeiro ◽  
Alba Piña-Rey ◽  
Ilda Abreu ◽  
F. Javier Rodríguez-Rajo
Keyword(s):  
Airborne Pollen ◽  
Weather Data ◽  
Vitis Vinifera L ◽  
Pollen Concentration ◽  
Peak Period ◽  
Hirst Sampler ◽  
Main Pollen Season ◽  
Pollen Concentrations ◽  
Integral Spin ◽  
Bioclimatic Conditions

Phenological, aerobiological, and weather data are useful tools to study local and regional flowering dynamics in crops with economic importance. The present study focuses on four autochthonous grapevine cultivars, namely, ‘Treixadura’, ‘Godello’, ‘Loureira’, and ‘Albariño’ (Vitis vinifera L.), which belong to the Designation of Origin Ribeiro area (located in northwestern Spain) from 2015–2019. The aims of the work were to (1) compare the airborne pollen concentration in the vineyard collected by two different traps, (2) analyze the influence of the main meteorological variables on cultivar phenology and pollen concentration, and (3) test the contribution of the air masses on pollen concentrations in the vineyard. Phenological development has been assessed twice weekly, according to the Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie (BBCH) scale. Airborne pollen concentrations were monitored by using two traps during stage 6 (flowering), namely, a Hirst volumetric sampler and a Cour passive trap. The bioclimatic conditions affected the duration of flowering, ranging from 11 and 24 days. The highest seasonal pollen integral (SPIn) was registered in 2016 for the Hirst sampler, with 302 pollen, and in 2019 for the Cour trap, with 1,797,765 pollen/m2/day. The main variables affecting pollen concentrations were average temperature during the main pollen season, as well as, temperatures and dew points during the pre-peak period. The relationship between pollen data registered by both traps and the obtained harvest indicate that the Hirst trap may be more suitable for predicting a local production and that the Cour sampler is more appropriate for forecasting regional productions.

Pollen, Allergens, and Human Health

2019 ◽  
Author(s):  
Rachel N. McInnes
Keyword(s):  
Management Practices ◽  
Dna Analysis ◽  
Pollen Grains ◽  
Health Impact ◽  
Meteorological Conditions ◽  
Day Length ◽  
Allergenic Pollen ◽  
Pollen Production ◽  
The Public ◽  
The Impact

Allergenic pollen is produced by the flowers of a number of trees, grasses, and weeds found throughout the world. Human exposure to such pollen grains can exacerbate pollen-related asthma and allergenic conditions such as allergic rhinitis (hay fever). While allergenic pollen comes from three main groups of plants—certain trees, grasses, and weeds—many people are sensitive to pollen from one or a few taxa only. Weather, climate, and environmental conditions have a significant impact on the levels and varieties of pollen grains present in the air. These allergenic conditions significantly reduce the quality of life of affected individuals and have been shown to have a major economic impact. Pollen production depends on both the current meteorological conditions (including day length, temperature, irradiation, precipitation, and wind speed/direction), and the water availability and other environmental and meteorological conditions experienced in the previous year. The climate affects the types of vegetation and taxa that can grow in a particular location through availability of different habitats. Land-use or land management is also crucial, and so this field of study has implications for vegetation management practices and policy. Given the influential effects of weather and climate on pollen, and the significant health impacts globally, the total effect of any future environmental and climatic changes on aeroallergen production and spread will be significant. The overall impact of climate change on pollen production and spread remains highly uncertain, and there is a need for further understanding of pollen-related health impact information. There are a number of ways air quality interacts with the impact of pollen. Further understanding of the risks of co-exposure to both pollen and air pollutants is needed to better inform public health policy. Furthermore, thunderstorms have been linked to asthma epidemics, especially during the grass pollen seasons. It is thought that allergenic pollen plays a role in this “thunderstorm asthma.” To reduce the exposure to, or impact from, pollen grains in the air, a number of adaptation and mitigation options may be adopted. Many of these would need to be done either through policy changes, or at a local or regional level, although some can be done by individuals to minimize their exposure to pollen they are sensitive to. Improved aeroallergen forecast models could be developed to provide detailed taxon-specific, localized information to the public. One challenge will be combining the many different sources of aeroallergen data that are likely to become available in future into numerical forecast systems. Examples of these potential inputs are automated observations of aeroallergens, real-time phenological observations and remote sensing of vegetation, social sensing, DNA analysis of specific aeroallergens, and data from symptom trackers or personal monitors. All of these have the potential to improve the forecasts and information available to the public.

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