{"title":"利用植物标本室数据增加在田间发现可育植物的可能性","authors":"J. S. Silva, E. Lenza, A. Moreira, C. Proença","doi":"10.24823/EJB.2021.355","DOIUrl":null,"url":null,"abstract":"The Phenological Predictability Index (PPI) is an algorithm incorporated into Brahms, one of the most widely used herbarium database management systems. PPI uses herbarium specimen data to calculate the probability of the occurrence of various phenological events in the field. Our hypothesis was that use of PPI to quantify the likelihood that a given species will be found in flower bud, flower or fruit in a particular area in a specific period makes field expeditions more successful in terms of finding fertile plants. PPI was applied to herbarium data for various angiosperm species locally abundant in Central Brazil to determine the month in which they were most likely to be found, in each of five areas of the Distrito Federal, with flower buds, flowers or fruits (i.e. the ‘maximum probability month’ for each of these phenophases). Plants of the selected species growing along randomised transects were tagged and their phenology was monitored over 12 months (method 1), and two one-day field excursions to each area were undertaken, by botanists with no prior knowledge of whether the species had previously been recorded at these sites, to record their phenological state (method 2). The results showed that field excursions in the PPI-determined maximum probability month for flower buds, flowers or fruits would be expected to result in a > 90% likelihood of finding individual plants of a given species in each of these phenophases. PPI may fail to predict phenophase for species with supra-annual reproductive events or with high event contingency. For bimodal species, the PPI-determined maximum probability month is that in which a specific phenophase is likely to be most intense. In planning an all-purpose collecting trip to an area with seasonal plant fertility, PPI scores are useful when selecting the best month for travel.","PeriodicalId":39376,"journal":{"name":"Edinburgh Journal of Botany","volume":"78 1","pages":"1-18"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"USING HERBARIUM DATA TO INCREASE THE LIKELIHOOD OF FINDING FERTILE PLANTS IN THE FIELD\",\"authors\":\"J. S. Silva, E. Lenza, A. Moreira, C. Proença\",\"doi\":\"10.24823/EJB.2021.355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Phenological Predictability Index (PPI) is an algorithm incorporated into Brahms, one of the most widely used herbarium database management systems. PPI uses herbarium specimen data to calculate the probability of the occurrence of various phenological events in the field. Our hypothesis was that use of PPI to quantify the likelihood that a given species will be found in flower bud, flower or fruit in a particular area in a specific period makes field expeditions more successful in terms of finding fertile plants. PPI was applied to herbarium data for various angiosperm species locally abundant in Central Brazil to determine the month in which they were most likely to be found, in each of five areas of the Distrito Federal, with flower buds, flowers or fruits (i.e. the ‘maximum probability month’ for each of these phenophases). Plants of the selected species growing along randomised transects were tagged and their phenology was monitored over 12 months (method 1), and two one-day field excursions to each area were undertaken, by botanists with no prior knowledge of whether the species had previously been recorded at these sites, to record their phenological state (method 2). The results showed that field excursions in the PPI-determined maximum probability month for flower buds, flowers or fruits would be expected to result in a > 90% likelihood of finding individual plants of a given species in each of these phenophases. PPI may fail to predict phenophase for species with supra-annual reproductive events or with high event contingency. For bimodal species, the PPI-determined maximum probability month is that in which a specific phenophase is likely to be most intense. In planning an all-purpose collecting trip to an area with seasonal plant fertility, PPI scores are useful when selecting the best month for travel.\",\"PeriodicalId\":39376,\"journal\":{\"name\":\"Edinburgh Journal of Botany\",\"volume\":\"78 1\",\"pages\":\"1-18\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Edinburgh Journal of Botany\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24823/EJB.2021.355\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Edinburgh Journal of Botany","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24823/EJB.2021.355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
USING HERBARIUM DATA TO INCREASE THE LIKELIHOOD OF FINDING FERTILE PLANTS IN THE FIELD
The Phenological Predictability Index (PPI) is an algorithm incorporated into Brahms, one of the most widely used herbarium database management systems. PPI uses herbarium specimen data to calculate the probability of the occurrence of various phenological events in the field. Our hypothesis was that use of PPI to quantify the likelihood that a given species will be found in flower bud, flower or fruit in a particular area in a specific period makes field expeditions more successful in terms of finding fertile plants. PPI was applied to herbarium data for various angiosperm species locally abundant in Central Brazil to determine the month in which they were most likely to be found, in each of five areas of the Distrito Federal, with flower buds, flowers or fruits (i.e. the ‘maximum probability month’ for each of these phenophases). Plants of the selected species growing along randomised transects were tagged and their phenology was monitored over 12 months (method 1), and two one-day field excursions to each area were undertaken, by botanists with no prior knowledge of whether the species had previously been recorded at these sites, to record their phenological state (method 2). The results showed that field excursions in the PPI-determined maximum probability month for flower buds, flowers or fruits would be expected to result in a > 90% likelihood of finding individual plants of a given species in each of these phenophases. PPI may fail to predict phenophase for species with supra-annual reproductive events or with high event contingency. For bimodal species, the PPI-determined maximum probability month is that in which a specific phenophase is likely to be most intense. In planning an all-purpose collecting trip to an area with seasonal plant fertility, PPI scores are useful when selecting the best month for travel.
期刊介绍:
Edinburgh Journal of Botany is an international journal of plant systematics covering related aspects of biodiversity, conservation science and phytogeography for plants and fungi. The journal is a particularly valued forum for research on South East and South West Asian, Sino-Himalayan and Brazilian biodiversity. The journal also publishes important work on European, Central American and African biodiversity and encourages submissions from throughout the world. Commissioned book reviews are also included. All papers are peer reviewed and an international editorial board provides a body of expertise to reflect the wide range of work published and the geographical spread of the journal’s authors and readers. Published on behalf of the Royal Botanic Garden Edinburgh