Live pine pollen in rainwater: reconstructing its long-range transport

Williams, Claire G.; Barnéoud, Philippe

doi:10.1007/s10453-021-09697-5

Cited by 6 publications

(2 citation statements)

References 48 publications

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“…Concerning living organisms, windborne long distance dispersal (typically larger than 10 km) has been largely explored for bacteria and fungi (Aylor, 2003 , 2017 ; Barberán et al., 2015 ; Brown & Hovmøller, 2002 ; Morris et al., 2008 ; Soubeyrand et al., 2009 ), pollen and seeds (Nathan et al., 2011 ; Williams, 2010 ; Williams & Barneoud, 2021 ), aphids (M. Irwin & Thresh, 1988 ; Isard & Gage, 2001 ), lepidoptera (Westbrook et al., 2016 ; Wu et al., 2022 ), and midges (Aguilar‐Vega et al., 2019 ). Such small organisms, especially microscopic ones, are not easy to track individually all along their aerial trajectories.…”

Section: Introductionmentioning

confidence: 99%

Computing Geographical Networks Generated by Air‐Mass Movement

Richard,

Martinetti,

Lercier

et al. 2023

GeoHealth

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As air masses move within the troposphere, they transport a multitude of components including gases and particles such as pollen and microorganisms. These movements generate atmospheric highways that connect geographic areas at distant, local, and global scales that particles can ride depending on their aerodynamic properties and their reaction to environmental conditions. In this article we present an approach and an accompanying web application called tropolink for measuring the extent to which distant locations are potentially connected by air‐mass movement. This approach is based on the computation of trajectories of air masses with the HYSPLIT atmospheric transport and dispersion model, and on the computation of connection frequencies, called connectivities, in the purpose of building trajectory‐based geographical networks. It is illustrated for different spatial and temporal scales with three case studies related to plant epidemiology. The web application that we designed allows the user to easily perform intensive computation and mobilize massive archived gridded meteorological data to build weighted directed networks. The analysis of such networks allowed us for example, to describe the potential of invasion of a migratory pest beyond its actual distribution. Our approach could also be used to compute geographical networks generated by air‐mass movement for diverse application domains, for example, to assess long‐term risk of spread from persistent or recurrent sources of pollutants, including wildfire smoke.

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Section: Introductionmentioning

confidence: 99%

Computing Geographical Networks Generated by Air‐Mass Movement

Richard,

Martinetti,

Lercier

et al. 2023

GeoHealth

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“…Pollen released into the atmosphere can travel long distances, achieve great altitude and be in sufficient quantities to cause allergic reactions (Ziello et al 2012; Szczepanek et al 2017; Williams and Barnéoud 2021). Both Pinus and Poaceae pollen are ubiquitous in the atmosphere across Europe during their pollination season, including long-range transport of pollen to sampling stations when local plants are not releasing pollen (Kasprzyk 2006; Szczepanek et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Determining if honey bees (Apis mellifera) collect pollen from anemophilous plants in the UK

et al. 2022

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Whether insect pollinators use wind-pollinated plants have implications for insect monitoring and conservation strategies in a wide range of environments. Habitats, such as coniferous plantations and arable crops of the Poaceae family are not typically considered priority for the monitoring of insect pollinators or habitat enhancement. Further many pollinator monitoring techniques focus on flowers and do not count insect interactions with wind-pollinated plants. Using two honey bee colonies from distinct environments (urban and rural) in north east England, we investigate the use of wind-pollinated plants over the summer of 2021. We combine honey bee pollen pellet analysis with airborne pollen sampling to investigate whether honey bees use three common wind-pollinated plant groups (Pinus sp., Plantago sp. and Poaceae) that have previously been considered sources of forage. Our results show that honey bees do forage on Plantago and Poaceae pollen, in line with previous studies. However, we show statistically that Pinus pollen is contamination from the atmosphere and not actively collected. It is important to consider airborne contamination before making interpretations based on small amounts of pollen in samples of bee products. The use of members of the Poaceae has implications for insect pollinator monitoring in urban environments, which has not always been considered in past studies.

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