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Fungi are among the most diverse and ecologically important kingdoms in life. However, the distributional ranges of fungi remain largely unknown as do the ecological mechanisms that shape their distributions1,2. To provide an integrated view of the spatial and seasonal dynamics of fungi, we implemented a globally distributed standardized aerial sampling of fungal spores3. The vast majority of operational taxonomic units were detected within only one climatic zone, and the spatiotemporal patterns of species richness and community composition were mostly explained by annual mean air temperature. Tropical regions hosted the highest fungal diversity except for lichenized, ericoid mycorrhizal and ectomycorrhizal fungi, which reached their peak diversity in temperate regions. The sensitivity in climatic responses was associated with phylogenetic relatedness, suggesting that large-scale distributions of some fungal groups are partially constrained by their ancestral niche. There was a strong phylogenetic signal in seasonal sensitivity, suggesting that some groups of fungi have retained their ancestral trait of sporulating for only a short period. Overall, our results show that the hyperdiverse kingdom of fungi follows globally highly predictable spatial and temporal dynamics, with seasonality in both species richness and community composition increasing with latitude. Our study reports patterns resembling those described for other major groups of organisms, thus making a major contribution to the long-standing debate on whether organisms with a microbial lifestyle follow the global biodiversity paradigms known for macroorganisms4,5.

Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m3 of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.

The article examines the complexities associated with effectively and comprehensively tackling the climate change crisis. Focusing on the need for education, the authors discuss a model of Education for Sustainable Development (ESD) that supports the development of competencies, coalition building and the capacity to support and maintain positive action. Drawing upon principles highlighted by the United Nations, the paper outlines the breadth and depth of knowledge required to support transformative ESD. Firstly enhancing comprehensive knowledge that develops cognitive, affective and axiological dimensions and proficiency. This enhances critical engagement with information and enables individuals to act responsibly and align with others in coalition building. The second element refers to collaborative partnership that is crucial for changes to be effective. This has been one of the most challenging barriers preventing positive action on the catastrophe pf climate change. Finally, the paper emphasizes the need to develop the competencies for supporting collective action, which will enable sustained action across transnational, transdisciplinary and transnational boundaries.

Background: There is evidence that global anthropogenic climate change may be impacting floral phenology and the temporal and spatial characteristics of aero‐allergenic pollen. Given the extent of current and future climate uncertainty, there is a need to strengthen predictive pollen forecasts. Methods: The study aims to use CatBoost (CB) and deep learning (DL) models for predicting the daily total pollen concentration up to 14 days in advance for 23 cities, covering all five continents. The model includes the projected environmental parameters, recent concentrations (1, 2 and 4 weeks), and the past environmental explanatory variables, and their future values. Results: The best pollen forecasts include Mexico City (R2(DL_7) ≈.7), and Santiago (R2(DL_7) ≈.8) for the 7th forecast day, respectively; while the weakest pollen forecasts are made for Brisbane (R2(DL_7) ≈.4) and Seoul (R2(DL_7) ≈.1) for the 7th forecast day. The global order of the five most important environmental variables in determining the daily total pollen concentrations is, in decreasing order: the past daily total pollen concentration, future 2 m temperature, past 2 m temperature, past soil temperature in 28–100 cm depth, and past soil temperature in 0–7 cm depth. City‐related clusters of the most similar distribution of feature importance values of the environmental variables only slightly change on consecutive forecast days for Caxias do Sul, Cape Town, Brisbane, and Mexico City, while they often change for Sydney, Santiago, and Busan. Conclusions: This new knowledge of the ecological relationships of the most remarkable variables importance for pollen forecast models according to clusters, cities and forecast days is important for developing and improving the accuracy of airborne pollen forecasts. [ABSTRACT FROM AUTHOR]

Active remote sensors equipped with the capability to detect polarization, a shape-relevant parameter, are essential to aerosol particle identification in the vertical domain. Most commonly, the linear particle depolarization ratio has been available at the shorter wavelengths of 355 and/or 532 nm. Recently, linear particle depolarization ratios at longer wavelengths (910, 1064, and 1565 nm) have emerged in lidar aerosol research. In this study, a synergy of three lidars, namely a PollyXT lidar, a Vaisala CL61 ceilometer, and a HALO Photonics StreamLine Pro Doppler lidar, as well as in situ aerosol and pollen observations have been utilized to investigate the spectral dependence of birch and pine pollen particles. We found that, regardless of the pollen type, the linear particle depolarization ratio was subject to the amount of pollen and its relative contribution to the aerosol mixture in the air. More specifically, during birch pollination, characteristic linear particle depolarization ratios of 5 ± 2 % (355 nm), 28 ± 6 % (532 nm), 23 ± 6 % (910 nm), and 33 ± 4 % (1565 nm) were retrieved at the pollen layer. Regarding the pine-dominant period, characteristic linear particle depolarization ratios of 6 ± 2 % , 43 ± 11 % , 22 ± 6 % , and 26 ± 3 % were determined at wavelengths of 355, 532, 910, and 1565 nm, respectively. For birch, the linear particle depolarization ratio at 1565 nm was the highest, followed by the 532 and 910 nm wavelengths, respectively. A sharp decrease at 355 nm was evident for birch pollen. For pine pollen, a maximum at the 532 nm wavelength was observed. There was no significant change in the linear particle depolarization ratio at 910 nm for the pollen types considered in this study. Given the low concentration of pollen in the air, the inclusion of the longer wavelengths (910 and 1565 nm) for the detection of birch and pine can be beneficial due to their sensitivity to trace large aerosol particles. [ABSTRACT FROM AUTHOR]

In order to document and study airborne pollen in the Mediterranean region, a pollen measurement campaign was performed during February-May 2018, at the Finokalia station in Crete. A ground-based multi-wavelength Raman polarization lidar PollyXT performed continuous measurements, together with a Hirst-type Burkard pollen sampler. The optical properties of pollen layers with presence of airborne pollen are retrieved and presented. Dust-free condition is applied for pollen study, using the dust models.

We present a novel algorithm for characterizing the optical properties of pure pollen particles, based on the depolarization values obtained in lidar measurements. The algorithm was first tested and validated through a simulator, and then applied to the lidar observations during a four-month pollen campaign from May to August 2016 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio (62°44' N, 27°33' E), in Eastern Finland. Twenty types of pollen were observed and identified from concurrent measurements with Burkard sampler; Birch (Betula), pine (Pinus), spruce (Picea) and nettle (Urtica) pollen were most abundant, contributing more than 90% of total pollen load, regarding number concentrations. Mean values of lidar-derived optical properties in the pollen layer were retrieved for four intense pollination periods (IPPs). Lidar ratios at both 355 and 532 nm ranged from 55 to 70 sr for all pollen types, without significant wavelength-dependence. Enhanced depolarization ratio was found when there were pollen grains in the atmosphere, and even higher depolarization ratio (with mean values of 25% or 14%) was observed with presence of the more non-spherical spruce or pine pollen. The depolarization ratio at 532 nm of pure pollen particles was assessed, resulting to 24 ± 3% and 36 ± 5% for birch and pine pollen, respectively. Pollen optical properties at 1064 nm and 355 nm were also estimated. The backscatter-related Ångström exponent between 532 and 1064 nm was assessed as ~ 0.8 (~ 0.5) for pure birch (pine) pollen, thus the longer wavelength would be better choice to trace pollen in the air. The pollen depolarization ratio at 355 nm of 17% and 30% were found for birch and pine pollen, respectively. The depolarization values show a wavelength dependence for pollen. This can be the key parameter for pollen detection and characterization. [ABSTRACT FROM AUTHOR]

We present the results of birch pollen characterization using lidar measurements based on a 11-day period of birch pollination from 5 to 15 May 2016 at the European Aerosol Research Lidar Network (EARLINET) station in Vehmasmäki (Kuopio, 62°44′ N, 27°33′ E), Finland. The ground-based multi-wavelength Raman lidar PollyXT performed continuous measurements at this rural forest site and has been combined with a Hirst-type volumetric air sampler which measured the pollen type and concentration on roof level (4 m). The period was separated into two parts due to different atmospheric conditions and detected pollen types. During the first period, high concentrations of birch pollen were measured with a maximum two-hour average pollen concentration of 3700 grains/m³. Other pollen types represented less than 3 % of the total pollen count. In observed pollen layers, the mean particle depolarization ratio at 532 nm was 10 ± 6 % during the intense birch pollination period. Mean lidar ratios were found to be 45 ± 7 and 55 ± 16 sr at 355 and 532 nm, respectively. During the second period, birch pollen was still dominant but a significant contribution of spruce pollen was observed. Spruce pollen grains are highly non-spherical, leading to a larger mean depolarization ratio of 26 ± 7 % of the birch-spruce pollen mixture. Furthermore, higher lidar ratios were observed during this period with a mean value of 60 ± 3 and 62 ± 10 sr at 355 and 532 nm, respectively. The presented study shows the potential of the particle depolarization ratio to track pollen grains in the atmosphere. [ABSTRACT FROM AUTHOR]

Information about distribution of pollen sources, i.e. their presence and abundance in a specific region, is important especially when atmospheric transport models are applied to forecast pollen concentrations. The goal of this study is to evaluate three pollen source maps using an atmospheric transport model and study the effect on the model results by combining these source maps with pollen data. Here we evaluate three maps for the birch taxon: (1) a map derived by combining land cover data and forest inventory; (2) a map obtained from land cover data and calibrated using model simulations and pollen observations; (3) a statistical map resulting from analysis of forest inventory and forest plot data. The maps were introduced to the Enviro-HIRLAM (Environment - High Resolution Limited Area Model) as input data to simulate birch pollen concentrations over Europe for the birch pollen season 2006. 18 model runs were performed using each of the selected maps in turn with and without calibration with observed pollen data from 2006. The model results were compared with the pollen observation data at 12 measurement sites located in Finland, Denmark and Russia.We show that calibration of the maps using pollen observations significantly improved the model performance for all three maps. The findings also indicate the large sensitivity of the model results to the source maps and agree well with other studies on birch showing that pollen or hybrid-based source maps provide the best model performance. This study highlights the importance of including pollen data in the production of source maps for pollen dispersion modelling and for exposure studies. [ABSTRACT FROM AUTHOR]

We studied variation in concentrations of airborne pollen and other particles of biological origin in a boreal forest in Finland during 2003-2004. The highest concentrations of pollen were observed in late spring and early summer, whereas the peak concentrations of other particles of biological origin (including e.g. fungal spores) occurred in August-September. Although the patterns in concentrations in 2003 and 2004 were similar, the concentration levels were significantly different between the years. The contribution of pollen and other particles of biological origin led to an increase in the measured particulate matter (PM) mass during the pollen season (mass of pollen and other particles of biological origin 5.9 and 0.4 µg m-3, respectively, in respect to PMtotal mass of 9.9 µg m-3) but the effect on total particle number was negligible. The other particles of biological origin constituted the largest fraction of measured primary biological aerosol particle (PBAP) numbers (~99%), whereas pollen showed a higher relative mass fraction (~97%) of PBAP. These results underline the important contribution of PBAP to coarse atmospheric particle mass providing up to 65% of the total mass during the peak pollen season. [ABSTRACT FROM AUTHOR]