Inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology

Abstract The collection and analysis of air samples for the study of microbial airborne communities or the detection of airborne pathogens is one of the few insights that we can grasp of a continuously moving flux of microorganisms from their sources to their sinks through the atmosphere. For large-...

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Autores principales:	Maria Choufany, Davide Martinetti, Samuel Soubeyrand, Cindy E. Morris
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4315198af92f49c197b63099a4c94621
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id	oai:doaj.org-article:4315198af92f49c197b63099a4c94621
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spelling	oai:doaj.org-article:4315198af92f49c197b63099a4c946212021-12-02T14:47:38ZInferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology10.1038/s41598-021-90733-22045-2322https://doaj.org/article/4315198af92f49c197b63099a4c946212021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-90733-2https://doaj.org/toc/2045-2322Abstract The collection and analysis of air samples for the study of microbial airborne communities or the detection of airborne pathogens is one of the few insights that we can grasp of a continuously moving flux of microorganisms from their sources to their sinks through the atmosphere. For large-scale studies, a comprehensive sampling of the atmosphere is beyond the scopes of any reasonable experimental setting, making the choice of the sampling locations and dates a key factor for the representativeness of the collected data. In this work we present a new method for revealing the main patterns of air-mass connectivity over a large geographical area using the formalism of spatio-temporal networks, that are particularly suitable for representing complex patterns of connection. We use the coastline of the Mediterranean basin as an example. We reveal a temporal pattern of connectivity over the study area with regions that act as strong sources or strong receptors according to the season of the year. The comparison of the two seasonal networks has also allowed us to propose a new methodology for comparing spatial weighted networks that is inspired from the small-world property of non-spatial networks.Maria ChoufanyDavide MartinettiSamuel SoubeyrandCindy E. MorrisNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Maria Choufany Davide Martinetti Samuel Soubeyrand Cindy E. Morris Inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology
description	Abstract The collection and analysis of air samples for the study of microbial airborne communities or the detection of airborne pathogens is one of the few insights that we can grasp of a continuously moving flux of microorganisms from their sources to their sinks through the atmosphere. For large-scale studies, a comprehensive sampling of the atmosphere is beyond the scopes of any reasonable experimental setting, making the choice of the sampling locations and dates a key factor for the representativeness of the collected data. In this work we present a new method for revealing the main patterns of air-mass connectivity over a large geographical area using the formalism of spatio-temporal networks, that are particularly suitable for representing complex patterns of connection. We use the coastline of the Mediterranean basin as an example. We reveal a temporal pattern of connectivity over the study area with regions that act as strong sources or strong receptors according to the season of the year. The comparison of the two seasonal networks has also allowed us to propose a new methodology for comparing spatial weighted networks that is inspired from the small-world property of non-spatial networks.
format	article
author	Maria Choufany Davide Martinetti Samuel Soubeyrand Cindy E. Morris
author_facet	Maria Choufany Davide Martinetti Samuel Soubeyrand Cindy E. Morris
author_sort	Maria Choufany
title	Inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology
title_short	Inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology
title_full	Inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology
title_fullStr	Inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology
title_full_unstemmed	Inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology
title_sort	inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/4315198af92f49c197b63099a4c94621
work_keys_str_mv	AT mariachoufany inferringlongdistanceconnectivityshapedbyairmassmovementforimprovedexperimentaldesigninaerobiology AT davidemartinetti inferringlongdistanceconnectivityshapedbyairmassmovementforimprovedexperimentaldesigninaerobiology AT samuelsoubeyrand inferringlongdistanceconnectivityshapedbyairmassmovementforimprovedexperimentaldesigninaerobiology AT cindyemorris inferringlongdistanceconnectivityshapedbyairmassmovementforimprovedexperimentaldesigninaerobiology
_version_	1718389505740767232

Inferring long-distance connectivity shaped by air-mass movement for improved experimental design in aerobiology

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