Daniel S. W. Katz, Elizabeth Vogt, Arie Manangan, Claudia L. Brown, Dan Dalan, Kai Zhu, Yiluan Song, Theresa M. Crimmins
{"title":"美国国家表型网络的观测结果可以用来模拟空气中的花粉","authors":"Daniel S. W. Katz, Elizabeth Vogt, Arie Manangan, Claudia L. Brown, Dan Dalan, Kai Zhu, Yiluan Song, Theresa M. Crimmins","doi":"10.1007/s10453-022-09774-3","DOIUrl":null,"url":null,"abstract":"<div><p>The USA National Phenology Network (USA-NPN) hosts the largest volunteer-contributed collection of plant phenology observations in the USA. The potential contributions of these spatially and temporally explicit observations of flowers and pollen cones to the field of aerobiology remain largely unexplored. Here, we introduce this freely available dataset and demonstrate its prospective applications for modeling airborne pollen in a case study. Specifically, we compare the timing of 4265 observations of flowering for oak (<i>Quercus</i>) trees in the eastern USA to winter–spring temperatures. We then use this relationship to predict the day of peak flowering at 15 pollen monitoring stations in 15 years and compare the predicted day of peak flowering to the peak day of measured pollen (<i>n</i> = 111 station-years). There was a strong association between winter–spring temperature and the presence of open flowers (<i>r</i><sup>2</sup> = 0.66, <i>p</i> < 0.0001) and the predicted peak flowering was strongly correlated with peak airborne pollen concentrations (<i>r</i><sup>2</sup> = 0.81, <i>p</i> < 0.0001). These results demonstrate the potential for the USA-NPN’s phenological observations to underpin source-based models of airborne pollen. We also highlight opportunities for leveraging and enhancing this near real-time dataset for aerobiological applications.\n</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"39 1","pages":"169 - 174"},"PeriodicalIF":2.2000,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Observations from the USA National Phenology Network can be leveraged to model airborne pollen\",\"authors\":\"Daniel S. W. Katz, Elizabeth Vogt, Arie Manangan, Claudia L. Brown, Dan Dalan, Kai Zhu, Yiluan Song, Theresa M. Crimmins\",\"doi\":\"10.1007/s10453-022-09774-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The USA National Phenology Network (USA-NPN) hosts the largest volunteer-contributed collection of plant phenology observations in the USA. The potential contributions of these spatially and temporally explicit observations of flowers and pollen cones to the field of aerobiology remain largely unexplored. Here, we introduce this freely available dataset and demonstrate its prospective applications for modeling airborne pollen in a case study. Specifically, we compare the timing of 4265 observations of flowering for oak (<i>Quercus</i>) trees in the eastern USA to winter–spring temperatures. We then use this relationship to predict the day of peak flowering at 15 pollen monitoring stations in 15 years and compare the predicted day of peak flowering to the peak day of measured pollen (<i>n</i> = 111 station-years). There was a strong association between winter–spring temperature and the presence of open flowers (<i>r</i><sup>2</sup> = 0.66, <i>p</i> < 0.0001) and the predicted peak flowering was strongly correlated with peak airborne pollen concentrations (<i>r</i><sup>2</sup> = 0.81, <i>p</i> < 0.0001). These results demonstrate the potential for the USA-NPN’s phenological observations to underpin source-based models of airborne pollen. We also highlight opportunities for leveraging and enhancing this near real-time dataset for aerobiological applications.\\n</p></div>\",\"PeriodicalId\":7718,\"journal\":{\"name\":\"Aerobiologia\",\"volume\":\"39 1\",\"pages\":\"169 - 174\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2022-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aerobiologia\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10453-022-09774-3\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerobiologia","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s10453-022-09774-3","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
Observations from the USA National Phenology Network can be leveraged to model airborne pollen
The USA National Phenology Network (USA-NPN) hosts the largest volunteer-contributed collection of plant phenology observations in the USA. The potential contributions of these spatially and temporally explicit observations of flowers and pollen cones to the field of aerobiology remain largely unexplored. Here, we introduce this freely available dataset and demonstrate its prospective applications for modeling airborne pollen in a case study. Specifically, we compare the timing of 4265 observations of flowering for oak (Quercus) trees in the eastern USA to winter–spring temperatures. We then use this relationship to predict the day of peak flowering at 15 pollen monitoring stations in 15 years and compare the predicted day of peak flowering to the peak day of measured pollen (n = 111 station-years). There was a strong association between winter–spring temperature and the presence of open flowers (r2 = 0.66, p < 0.0001) and the predicted peak flowering was strongly correlated with peak airborne pollen concentrations (r2 = 0.81, p < 0.0001). These results demonstrate the potential for the USA-NPN’s phenological observations to underpin source-based models of airborne pollen. We also highlight opportunities for leveraging and enhancing this near real-time dataset for aerobiological applications.
期刊介绍:
Associated with the International Association for Aerobiology, Aerobiologia is an international medium for original research and review articles in the interdisciplinary fields of aerobiology and interaction of human, plant and animal systems on the biosphere. Coverage includes bioaerosols, transport mechanisms, biometeorology, climatology, air-sea interaction, land-surface/atmosphere interaction, biological pollution, biological input to global change, microbiology, aeromycology, aeropalynology, arthropod dispersal and environmental policy. Emphasis is placed on respiratory allergology, plant pathology, pest management, biological weathering and biodeterioration, indoor air quality, air-conditioning technology, industrial aerobiology and more.
Aerobiologia serves aerobiologists, and other professionals in medicine, public health, industrial and environmental hygiene, biological sciences, agriculture, atmospheric physics, botany, environmental science and cultural heritage.