<strong>EUNIS-ESy</strong> is an expert system for automatic classification of Europe... more <strong>EUNIS-ESy</strong> is an expert system for automatic classification of European vegetation plots to habitat types of the EUNIS Habitat Classification. The EUNIS classification and the principles of the expert system are described by Chytrý et al. (2020). The classification of a set of vegetation plots can be run in the JUICE program (Tichý 2002; https://www.sci.muni.cz/botany/juice/), TURBOVEG 3 program (Hennekens 2015) and an R script developed by H. Bruelheide et al. (submitted). This dataset contains two parts: (1) the expert system and related files necessary for running it; (2) characterization of EUNIS habitats based on the results of the expert system classification. <strong>1. Expert system and related files necessary to run it</strong> 1.1. <strong>EUNIS-ESy-2020-06-08.txt </strong>is a file containing the script for classification of vegetation plots by EUNIS-ESy. This version contains tested definitions for the revised classification Coastal, Wetland, Grassland, Shrubland, Forest and Man-made habitats, and preliminary non-tested definitions of the older classification of Marine, Aquatic and Inland sparsely vegetated habitats. 1.2. <strong>Nomenclature-translation-from-Turboveg-2-databases.zip </strong>is an archive containing the scripts for automatic translation of taxon concepts and names used in individual European Turboveg 2 databases (Hennekens &amp; Schaminée 2001; https://www.synbiosys.alterra.nl/turboveg/) to the nomenclature that can be used as an input for EUNIS-ESy. 1.3. <strong>EUNIS-ESy-User-Guide.pdf </strong>contains a brief user guide to the classification of vegetation plots by EUNIS-ESy using the JUICE program. Please read this guide carefully before running the expert system to avoid misclassifications. <strong>2. Characterization of the EUNIS habitats based on the results of the EUNIS-ESy classification</strong> 2.1. <strong>Habitat-Factsheets.pdf </strong>contains a summary of data on EUNIS Coastal, Wetland, Grassland, Shrubland, Forest and Man-made habitats. These data wer [...]
This is a database of the occurrence of 1105 phytosociological alliances in 82 European territori... more This is a database of the occurrence of 1105 phytosociological alliances in 82 European territorial units and distribution maps generated from this database. The data correspond to those published by Preislerová et al. (2022). This article also contains a description of the methods.
I social network sono canali di comunicazione utilizzati per condividere enormi quantit\ue0 di da... more I social network sono canali di comunicazione utilizzati per condividere enormi quantit\ue0 di dati, che possono essere utilizzati per la ricerca scientifica, anche nel campo della biodiversit\ue0. Per sapere quanto i dati ricavati dai social network possono integrare quelli raccolti per scopi scientifici, \ue8 necessario individuarne i bias. Utilizzando i dati estratti da un gruppo Facebook specializzato nella flora vascolare siciliana, abbiamo analizzato quali sono i caratteri che aumentano la probabilit\ue0 che una pianta spontanea venga fotografata e postata su un social network. A tal fine, abbiamo confrontato frequenze e attributi delle specie fotografate dai membri del gruppo Facebook con quelli delle specie registrate nel database EVA, relative a 6.366 rilevamenti vegetazionali della Sicilia. I nostri risultati suggeriscono che i dati provenienti dal gruppo Facebook analizzato sono affetti da bias diversi da quelli relativi a dati floristici raccolti per altri fini, ad esempio, per il rilevamento della vegetazione. I membri del gruppo Facebook hanno intercettato con maggior frequenza specie aliene e specie rare rispetto a quanto rilevato da chi studia la vegetazione, dimostrando che i dati contenuti nei social network offrono un importante complemento a quelli raccolti dagli scienziati per fini di ricerca. Sintesi e applicazioni. Malgrado Facebook non supporti la georeferenziazione dei dati, n\ue9 una query per l'accesso e l'analisi degli stessi, esso rappresenta una potenziale fonte di dati sulla biodiversit\ue0, utili per integrare quelli raccolti da botanici professionisti. Il principale vantaggio dei dati provenienti dai social network \ue8 il loro elevato dinamismo, poich\ue9 registrano la presenza di una data specie quasi in tempo reale. Pertanto, i dati raccolti da gruppi Facebook moderati da esperti possono risultare utili (1) per monitorare le dinamiche di popolazione di specie minacciate ed esotiche; (2) come informazioni aggiuntive sulla presenza di specie rare, in particolare per quelle che maggiormente attraggono i botanici dilettanti, come le orchidee; (3) per individuare tempestivamente la presenza di nuove esotiche potenzialmente invasive; (4) per studi fenologici, in particolare per monitorare l\u2019inizio della stagione di fioritura delle specie.Social networks offer communication channels through which people share huge amounts of primary data that can be used for scientific analyses, including biodiversity research. To understand to what extent data extracted from social networks could complement data collected for scientific purposes, it is necessary to quantify the bias of such data. We analysed which plant traits increased the probability of a wild\u2010growing plant species to be photographed and posted to a social network based on the data from an unstructured citizen science tool; a Facebook group focused on the vascular flora of Sicily (Italy). Then, we compared botanical data collected by this Facebook group members with data collected by scientists in 6,366 vegetation plots sampled across Sicily, stored in the EVA database. Our results suggested that data proceeding from the analysed Facebook group were affected by various sampling biases, which differed from the biases inherent to other types of biodiversity data such as those from vegetation plots. Facebook users recorded a higher proportion of red\u2010listed and alien species than vegetation scientists. Therefore, social networks can provide a valuable complement to the data collected by scientists for research purposes. Synthesis and applications. Despite Facebook does not support geotagging and interface for data access and analysis, it is an invaluable source of biodiversity data that could complement those collected by professional researchers. The main advantage of data from social networks is their high dynamism, as they report large amounts of species occurrences in almost real time. Therefore, citizen science data from a Facebook group where the records are curated by expert volunteers can be used (a) for monitoring population dynamics of threatened and alien species; (b) as a source of additional data on rare species occurrences, particularly for plants that are attractive for amateur botanists, such as orchids; (c) for early warning systems of potential new invasions; and (4) for phenological studies, especially at the beginning of the flowering season
We asked what are the behavioural and logistic preferences of professional and amateur botanists ... more We asked what are the behavioural and logistic preferences of professional and amateur botanists when exploring flora in the field. We extracted temporal and spatial data on vas- cular plant species occurrences from three datasets of Sicilian flora: a subset of iNaturalist, a dataset collected by a Facebook group focused on the flora of Sicily and a subset of the professional database European Vegetation Archive. We used the time span of individual contributor\u2019s activity as a proxy of their commitment to collecting information about the flora of Sicily. Climate and landscape data were used to better characterize the spatial and temporal activity of data contributors. Finally, we assessed which habitat types were more frequently visited in each dataset. Our results suggest that amateur botanists can be divided into two categories, "experienced" and "occasional", playing different roles on digital plat- forms. While experienced amateur botanists are characterized by prolonged activity and many posts, occasional ones have short and erratic activity but collectively compile more data than the former category. The occasional botanists represent a new phenomenon in data collection, supported by the spread of digital platforms. While in the past, experienced botanists were primarily involved in biodiversity data collection, at present, they also play a fundamental role in validating the observations by occasional botanists and disseminat- ing floristic knowledge to them. Our study points out that the interaction through social media can catalyze the establishment of participatory monitoring networks, promote con- servation-oriented initiatives and influence policy-makers
Vegetation classification is a basic requirement of research and conservation. Numerous classific... more Vegetation classification is a basic requirement of research and conservation. Numerous classifications have been established throughout the world during the 20th century, but steps toward international classification systems and standards are currently being sought. We introduce here a new working group of the International Association of Vegetation Science, the Vegetation Classification Working Group (VCWG), which will function as a scientific panel devoted to vegetation classification at any spatial or organizational scale, particularly the underlying methodologies and standards, ultimately allowing greater understanding and crosswalks among national classification systems. The VCWG currently has 166 members from 41 countries of six continents, a website for information, established subgroups for specific activities, and initiated a Special Issue on classification for Phytocoenologia. We summarize here the background of the VCWG, current and future activities, and contact information for those interested in becoming involved.
<strong>EUNIS-ESy</strong> is an expert system for automatic classification of Europe... more <strong>EUNIS-ESy</strong> is an expert system for automatic classification of European vegetation plots to habitat types of the EUNIS Habitat Classification. The EUNIS classification and the principles of the expert system are described by Chytrý et al. (2020). The classification of a set of vegetation plots can be run in the JUICE program (Tichý 2002; https://www.sci.muni.cz/botany/juice/), TURBOVEG 3 program (Hennekens 2015) and an R script developed by H. Bruelheide et al. (submitted). This dataset contains two parts: (1) the expert system and related files necessary for running it; (2) characterization of EUNIS habitats based on the results of the expert system classification. <strong>1. Expert system and related files necessary to run it</strong> 1.1. <strong>EUNIS-ESy-2020-06-08.txt </strong>is a file containing the script for classification of vegetation plots by EUNIS-ESy. This version contains tested definitions for the revised classification Coastal, Wetland, Grassland, Shrubland, Forest and Man-made habitats, and preliminary non-tested definitions of the older classification of Marine, Aquatic and Inland sparsely vegetated habitats. 1.2. <strong>Nomenclature-translation-from-Turboveg-2-databases.zip </strong>is an archive containing the scripts for automatic translation of taxon concepts and names used in individual European Turboveg 2 databases (Hennekens &amp; Schaminée 2001; https://www.synbiosys.alterra.nl/turboveg/) to the nomenclature that can be used as an input for EUNIS-ESy. 1.3. <strong>EUNIS-ESy-User-Guide.pdf </strong>contains a brief user guide to the classification of vegetation plots by EUNIS-ESy using the JUICE program. Please read this guide carefully before running the expert system to avoid misclassifications. <strong>2. Characterization of the EUNIS habitats based on the results of the EUNIS-ESy classification</strong> 2.1. <strong>Habitat-Factsheets.pdf </strong>contains a summary of data on EUNIS Coastal, Wetland, Grassland, Shrubland, Forest and Man-made habitats. These data wer [...]
This is a database of the occurrence of 1105 phytosociological alliances in 82 European territori... more This is a database of the occurrence of 1105 phytosociological alliances in 82 European territorial units and distribution maps generated from this database. The data correspond to those published by Preislerová et al. (2022). This article also contains a description of the methods.
I social network sono canali di comunicazione utilizzati per condividere enormi quantit\ue0 di da... more I social network sono canali di comunicazione utilizzati per condividere enormi quantit\ue0 di dati, che possono essere utilizzati per la ricerca scientifica, anche nel campo della biodiversit\ue0. Per sapere quanto i dati ricavati dai social network possono integrare quelli raccolti per scopi scientifici, \ue8 necessario individuarne i bias. Utilizzando i dati estratti da un gruppo Facebook specializzato nella flora vascolare siciliana, abbiamo analizzato quali sono i caratteri che aumentano la probabilit\ue0 che una pianta spontanea venga fotografata e postata su un social network. A tal fine, abbiamo confrontato frequenze e attributi delle specie fotografate dai membri del gruppo Facebook con quelli delle specie registrate nel database EVA, relative a 6.366 rilevamenti vegetazionali della Sicilia. I nostri risultati suggeriscono che i dati provenienti dal gruppo Facebook analizzato sono affetti da bias diversi da quelli relativi a dati floristici raccolti per altri fini, ad esempio, per il rilevamento della vegetazione. I membri del gruppo Facebook hanno intercettato con maggior frequenza specie aliene e specie rare rispetto a quanto rilevato da chi studia la vegetazione, dimostrando che i dati contenuti nei social network offrono un importante complemento a quelli raccolti dagli scienziati per fini di ricerca. Sintesi e applicazioni. Malgrado Facebook non supporti la georeferenziazione dei dati, n\ue9 una query per l'accesso e l'analisi degli stessi, esso rappresenta una potenziale fonte di dati sulla biodiversit\ue0, utili per integrare quelli raccolti da botanici professionisti. Il principale vantaggio dei dati provenienti dai social network \ue8 il loro elevato dinamismo, poich\ue9 registrano la presenza di una data specie quasi in tempo reale. Pertanto, i dati raccolti da gruppi Facebook moderati da esperti possono risultare utili (1) per monitorare le dinamiche di popolazione di specie minacciate ed esotiche; (2) come informazioni aggiuntive sulla presenza di specie rare, in particolare per quelle che maggiormente attraggono i botanici dilettanti, come le orchidee; (3) per individuare tempestivamente la presenza di nuove esotiche potenzialmente invasive; (4) per studi fenologici, in particolare per monitorare l\u2019inizio della stagione di fioritura delle specie.Social networks offer communication channels through which people share huge amounts of primary data that can be used for scientific analyses, including biodiversity research. To understand to what extent data extracted from social networks could complement data collected for scientific purposes, it is necessary to quantify the bias of such data. We analysed which plant traits increased the probability of a wild\u2010growing plant species to be photographed and posted to a social network based on the data from an unstructured citizen science tool; a Facebook group focused on the vascular flora of Sicily (Italy). Then, we compared botanical data collected by this Facebook group members with data collected by scientists in 6,366 vegetation plots sampled across Sicily, stored in the EVA database. Our results suggested that data proceeding from the analysed Facebook group were affected by various sampling biases, which differed from the biases inherent to other types of biodiversity data such as those from vegetation plots. Facebook users recorded a higher proportion of red\u2010listed and alien species than vegetation scientists. Therefore, social networks can provide a valuable complement to the data collected by scientists for research purposes. Synthesis and applications. Despite Facebook does not support geotagging and interface for data access and analysis, it is an invaluable source of biodiversity data that could complement those collected by professional researchers. The main advantage of data from social networks is their high dynamism, as they report large amounts of species occurrences in almost real time. Therefore, citizen science data from a Facebook group where the records are curated by expert volunteers can be used (a) for monitoring population dynamics of threatened and alien species; (b) as a source of additional data on rare species occurrences, particularly for plants that are attractive for amateur botanists, such as orchids; (c) for early warning systems of potential new invasions; and (4) for phenological studies, especially at the beginning of the flowering season
We asked what are the behavioural and logistic preferences of professional and amateur botanists ... more We asked what are the behavioural and logistic preferences of professional and amateur botanists when exploring flora in the field. We extracted temporal and spatial data on vas- cular plant species occurrences from three datasets of Sicilian flora: a subset of iNaturalist, a dataset collected by a Facebook group focused on the flora of Sicily and a subset of the professional database European Vegetation Archive. We used the time span of individual contributor\u2019s activity as a proxy of their commitment to collecting information about the flora of Sicily. Climate and landscape data were used to better characterize the spatial and temporal activity of data contributors. Finally, we assessed which habitat types were more frequently visited in each dataset. Our results suggest that amateur botanists can be divided into two categories, "experienced" and "occasional", playing different roles on digital plat- forms. While experienced amateur botanists are characterized by prolonged activity and many posts, occasional ones have short and erratic activity but collectively compile more data than the former category. The occasional botanists represent a new phenomenon in data collection, supported by the spread of digital platforms. While in the past, experienced botanists were primarily involved in biodiversity data collection, at present, they also play a fundamental role in validating the observations by occasional botanists and disseminat- ing floristic knowledge to them. Our study points out that the interaction through social media can catalyze the establishment of participatory monitoring networks, promote con- servation-oriented initiatives and influence policy-makers
Vegetation classification is a basic requirement of research and conservation. Numerous classific... more Vegetation classification is a basic requirement of research and conservation. Numerous classifications have been established throughout the world during the 20th century, but steps toward international classification systems and standards are currently being sought. We introduce here a new working group of the International Association of Vegetation Science, the Vegetation Classification Working Group (VCWG), which will function as a scientific panel devoted to vegetation classification at any spatial or organizational scale, particularly the underlying methodologies and standards, ultimately allowing greater understanding and crosswalks among national classification systems. The VCWG currently has 166 members from 41 countries of six continents, a website for information, established subgroups for specific activities, and initiated a Special Issue on classification for Phytocoenologia. We summarize here the background of the VCWG, current and future activities, and contact information for those interested in becoming involved.
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