Available onlineCall Number: [EL]Physical Description: 38 p.

The Manual of the Alien Plants of Belgium is a species checklist dataset published by the Botanic Garden Meise. It contains information on all (over 2.500) non-native vascular plants occurring in the wild in Belgium since 1800. The checklist is almost entirely based on a thorough herbarium revision of the main public Belgian herbaria (Verloove 2006), actively maintained, and updated regularly at Verloove (2018, http://alienplantsbelgium.be). Here it is published as a standardized Darwin Core Archive and includes for each species: the scientific name, kingdom, family, stable taxon identifier, and IPNI (2018) scientific name ID where available (in the taxon core), the presence in Flanders, Wallonia and the Brussels Capital Region, as well as the year of the first introduction (first collection) and last assessment/observation in Belgium (given as a year range in the event date in the distribution extension), coarse habitat information (in the species profile extension), and the pathway(s) of introduction, native range(s) and invasion stage in Belgium (in the description extension). The dataset can be used for researching and managing alien plants or compiling regional and national registries of alien species. Issues with the dataset can be reported at https://github.com/trias-project/alien-plants-belgium We have released this dataset to the public domain under a Creative Commons Zero waiver. We would appreciate it if you follow the GBIF citation guidelines (https://www.gbif.org/citation-guidelines) when using the data. If you have any questions regarding this dataset, don’t hesitate to contact us via the contact information provided in the metadata or via https://twitter.com/trias_project. This dataset was published as open data for the TrIAS project (Tracking Invasive Alien Species http://trias-project.be, Vanderhoeven et al. 2017), with technical support provided by the Research Institute for Nature and Forest (INBO). It is selected as one of the authoritative sources for the compilation of a unified and reproducible checklist of alien species in Belgium.

El objetivo de este proyecto es elaborar un manual ilustrado que incluya todas las especies de Orquídeas que crecen de manera silvestre en el estado de Morelos desarrollando, de forma paralela, una base de datos computarizada de los ejemplares de herbario revisados, así como de los especimenes recolectados durante el desarrollo del proyecto. Se publicará la obra "Manual ilustrado de las orquídeas silvestres del estado de Morelos", la cual incluirá: 1) claves artificiales de identificación y descripciones para cada uno de los géneros y especies presentes en la entidad. 2) fotografías y dibujos de especies selectas, particularmente aquellas en peligro de extinción, endémicas, de amplia distribución en el estado o indicadoras de condiciones ambientales específicas. 3) comentarios adicionales sobre la ecología, uso, reconocimiento, fenología. Base de datos (AMO-DATA) de los especimenes recolectados, así como de los revisados en los herbarios AMO, CHAPA, ENCB, HUMO, MEXU y UAMIZ. Dicha base de datos cumplirá con los lineamientos establecidos en el "Instructivo para la Conformación de Bases de Datos compatibles con el Sistema Nacional de Información sobre Biodiversidad". Colección de fotografías (diapositivas en color), las cuales serán debidamente registradas e incorporadas a las diapotecas de los herbarios AMO y UAMIZ.

A checklist providing patches to the automatically assembled GBIF backbone taxonomy.
Names and their classification in this list will take precedence over other backbone sources,
thus allowing small manual interventions in the backbone building process.
The list is hosted on github allowing for wider collaboration outside of the secretariat.
Names in this checklist should be removed once they appear in other trusted checklists.
When adding new names into this list all entries should be assigned some remarks why this
name exists and ideally a link to some other online resource via dc:references.

Se llevará a cabo la revisión de ejemplares de herbario que hayan sido colectados en el estado de Durango, se verificará la identidad de las especies, se actualizarán los nombres empleados en caso necesario, y se identificarán las especies no determinadas a la fecha. Para tal efecto se revisarán los principales herbarios nacionales (MEXU, ENCB, CHAPA, COCA, CIIDIR, IEB, ANSM, LPM, IBUG, UAA, y UAG); así como un solo herbario internacional, el US que cuenta con 5 millones de ejemplares, principalmente del Nuevo Mundo, el 10% de ellos (alrededor de 500,000) son gramíneas. El herbario US del Instituto Smithsoniano además de ser uno de los mayores en América (y quizá del mundo) contiene el mayor número de gramíneas mexicanas depositados en el extranjero. Se revisarán las gramíneas de Durango, se editarán las descripciones de un número aproximado de 90 géneros y 480 especies y se llevarán a cabo claves de separación de género y especies. Las descripciones así como sus claves de separación serán utilizados para editar un manual de las gramíneas existentes en Durango, con ilustraciones que apoyen su identificación, y con datos de distribución geográfica y preferencias ecológicas. Por otra pare se llevará a cabo una base de datos siguiendo los lineamientos de la CONABIO, donde se registrarán datos taxonómicos, de distribución y georreferenciación de los ejemplares de gramíneas de Durango, depositados en los herbarios revisados.

Reino: 1Filo: 1Clase: 1Orden: 1Familia: 1Género: 89Especie: 330Epitetoinfraespecifico: 7

A dataset containing 90 species occurrences available in GBIF matching the query: DatasetKey: Plasm bearing foraminifera counts of multinet M21/2_MSN648. The dataset includes 90 records from 1 constituent datasets: 90 records from Plasm bearing foraminifera counts of multinet M21/2_MSN648. Data from some individual datasets included in this download may be licensed under less restrictive terms.

A dataset containing 18 species occurrences available in GBIF matching the query: TaxonKey: Puya obconica L.B.Sm.. The dataset includes 18 records from 7 constituent datasets: 1 records from SysTax - Botanical Gardens. 9 records from Tropicos Specimen Data. 1 records from NMNH Extant Specimen Records. 1 records from The AAU Herbarium Database. 3 records from University of Vienna, Institute for Botany - Herbarium WU. 2 records from Field Museum of Natural History (Botany) Seed Plant Collection. 1 records from Harvard University Herbaria. Data from some individual datasets included in this download may be licensed under less restrictive terms.

Natural history specimen data linked to collectors and determiners held within, "Manual de las gramíneas de Durango". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/8031a106-f762-11e1-a439-00145eb45e9a using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/8031a106-f762-11e1-a439-00145eb45e9a. Formatted as a Frictionless Data package.

Natural history specimen data linked to collectors and determiners held within, "Manual ilustrado de las orquídeas silvestres del estado de Morelos". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/803aa7c4-f762-11e1-a439-00145eb45e9a using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/803aa7c4-f762-11e1-a439-00145eb45e9a. Formatted as a Frictionless Data package.

This dataset contains the digitized treatments in Plazi based on the original journal article Lonsdale, Owen (2021): Manual of North American Agromyzidae (Diptera, Schizophora), with revision of the fauna of the " Delmarva " states. ZooKeys 1051: 1-481, DOI: http://dx.doi.org/10.3897/zookeys.1051.64603, URL: http://dx.doi.org/10.3897/zookeys.1051.64603

A comprehensive dataset of non-native species (NNS) was assembled by combining the SInAS database of alien species occurrences (Seebens, 2021) with several other publicly available databases and NNS lists to examine NNS diversity globally (Bailey et al., 2020; Campbell et al., 2016; Carlton & Eldredge, 2009; Casties et al., 2016; Eldredge & Carlton, 2015; Hewitt et al., 2002, 2004; Lambert, 2002; Meyer, 2000; NEMESIS, 2017, 2020; Paulay et al., 2002; Richardson et al., 2020; Schwindt et al., 2020; Sturtevant et al., 2019; U.S. Geological Survey, 2017; Wonham & Carlton, 2005) to examine NNS diversity globally. The SInAS_AlienSpeciesDB_2.4.1 file was used as the base file for our dataset. Species without assignment of invaded country/region were removed from the dataset. Then, species assigned only as CASUAL and ABSENT in the columns degreeOfEstablishment (N) and occurrenceStatus (L), respectively, were also removed due to their undetermined non-native establishment status in those particular regions (Groom et al., 2019). Following, species from other publicly available databases and NNS lists that had not been listed for particular region/s in the SInAS database were added to the file. The species that were both native and NNS within a continent were retained in the dataset. Accordingly, the dataset consisted 36 822 species established outside of their native regions, out of which 36 326 came from Seebens (2021) and 496 species from other databases and NNS lists. Binominal scientific names, phylum, class, and family levels were assigned to each species based on the SInAS_AlienSpeciesDB_2.4.1_FullTaxaList file that was originally determined following Global Biodiversity Information Facility (GBIF). When a species was not automatically assigned to binominal scientific name and/or taxonomic level, an additional manual search of GBIF, World Register of Marine Species (WoRMS) and a general internet search engine was conducted in June and July 2022, and September 2023. Also, to examine NNS diversity among different habitats (i.e., terrestrial, freshwater, and marine), we assigned one or more habitats for each species based on the Step2_StandardTerms_GRIIS file; habitat data in the Step2_StandardTerms_GRIIS file originated from the Global Register of Introduced and Invasive Species (GRIIS). Again, if habitat(s) was(were) not automatically assigned to a species, an additional manual search of WoRMS and a general internet search engine was conducted from July to September 2022. We emphasize that due to the great number of species in our dataset and changing information availability over time, there is a possibility that we did not list all potential habitats for all species. Brackish habitats were defined as marine based on the Venice System (1958). Regions were assigned based on the geographic continental definitions (i.e., North America, South America, Europe, Africa, Asia, and Australia), with Pacific islands as a separate region due to their unclear/undefined continental affiliations (National Geographic Society, 2022). Finally, global estimated biodiversity (i.e., numbers of species per taxonomic group) of each particular phylum, class, and family was obtained from the GBIF in October 2022 (GBIF, 2022).

The Observer Program database consists of fish, invertebrate, and marine mammal observations collected by fishery biologists while deployed on board commercial fishing vessels or at shoreside processing plants participating in the Bering Sea and Gulf of Alaska groundfish fisheries. This database covers observations from 1993-2004. The specific data components collected are outlined in the Groundfish Observer Manual. Once received by NOAA Fisheries, these data are extensively checked for quality. Each record represents the summary of all the observations made for a given taxa in a given year from each 20km by 20km grid square; counts and weights are statistical estimates.

Aims and scope

Member State authorities are required to report on the distribution in their territory of each of the invasive alien species (IAS) of Union concern. These are species with documented biodiversity impacts sensu the European Union Regulation on the prevention and management of the introduction and spread of Invasive Alien Species in Europe (IAS Regulation No 1143/2014) (European Union 2014). This distribution represents the official reporting under Article 24(1) of R.1143/2014 on invasive alien species for the period 2015–2018. Baseline distribution of these species has previously been reported and published (Adriaens et al. 2018, ).

Data were compiled from various datasets holding invasive species observations such as data from research institutes and research projects (9%), citizen science observatories (68%) and a range of other sources (23%) such as governmental agencies, water managers etc. More specifically the dataset includes:

• The citizen science recording portals www.waarnemingen.be and www.observation.be which has a specific alert system for IAS where nature volunteers can report their observations (Adriaens et al. 2018);
• Data from the Research Institute for Nature and Forest (INBO), the Flemish government institute that coordinates N2000, WFD and BIrd Directive and IAS monitoring in the terrestrial, estuarine and freshwater environment;
• Data from the Flemish Environment Agency which performs management of muskrat and invasive water plants in Flanders, gathered with a dedicated smartphone app since 2015;
• Data from the Flemish provinces and Rato vzw that manage water plants, muskrat, giant hogweed etc.;
• Some smaller datasets from cities;
• Data from the Brussels Capital Region from the Brussels Environment data portal;
• Plant inventories of the ‘contrats de rivière’ along watercourses in Wallonia, making use of a dedicated application to collect data directly from the field (fulcrum);
• The government reporting portals for IAS of the ‘Observatoire wallon de la flore, de la faune et des habitats (Service Public de Wallonie)’;
• Some validated data from specific datasets on gbif (iNaturalist, Natusfera, Naturgucker).

Data were normalized using a custom mapping of the original data files to Darwin Core (Wieczorek et al. 2012) where possible. Species names were mapped to the GBIF Backbone Taxonomy (GBIF 2016) using the species API (http://www.gbif.org/developer/species). The mapping was assisted by dedicated software (SMARTIE) which was specifically written for the purpose of aggregating IAS data from various sources. Appropriate selection of records was performed based on the cut-off dates (see data range) and record content validation (see validation procedure). Data were then joined with GRID10k layer Belgium based on GRID10k cellcodes (ETRS_1989_LAEA). The technical format is in line with the guidelines provided to the member states for the compilation of reports on Species Distribution (SD) of Invasive Alien Species of Union concern.

File description

The dataset contains a shapefiles (T1_Belgium_Union_List_Species.shp) with the distribution of the species of Union Concern at 10km² (European Terrestrial Reference System projection - 1989 ETRS_1989_LAEA) level. The attributes table contains Cellcode (ETRS grid cell code) and Species (scientific name + authority).

Date range

The data reflects the distribution of the IAS of Union concern in Belgium in the first reporting period for the EU Regulation hence comprises observations of Union List invasive species between January 2015 (2015-01-01) and December 2018 (2018-12-31).

Validation procedure

Record validation was performed to exclude dubious records, wrong identifications etc. This was done based on the IdentificationVerificationStatus field (to which validation information from original data were mapped) if available. In general, non-validated data were not considered. Data were validated in the original datasets based on evidence (e.g. pictures), on the observer’s experience, or based on a set of predefined rules (e.g. automated validation based on geographic filtering). Data from research institutes were generally considered validated. A few casual records of EU list species that were clearly planted were discarded manually. When the original dataset did not mention any validation status, records were not considered validated and therefore not taken into account unless for Chinese mitten crab Eriocheir sinensis, ruddy duck Oxyura jamaicensis, raccoon Procyon lotor, Siberian ground squirrel Tamias sibiricus, sacred ibis Threskiornis aethiopicus, Egyptian goose Alopochen aegyptiaca, Himalayan balsam Impatiens glandulifera, giant hogweed Heracleum mantegazzianum, muskrat Ondatra zibethicus and red-eared slider Trachemys spp. For these species, it was assumed all records were correct as they originate from dedicated sampling (E. sinensis) within research projects, were gathered by public bodies (e.g. muskrat), or represent species that are readily recognizable by people in the field. Data provided by EASIN in the care package and GBIF data were carefully checked.

A visual check was performed on the resulting distribution maps by representatives of the Belgian national scientific council on invasive alien species, an official consultative structure coordinating scientific input and data aggregation between Belgian regions and institutions with regards to technical implementation of the Regulation No 1143/2014 on invasive alien species.

Data providers

The providers of the invasive species data for this exercise (individuals and their respective organizations) are listed in the "data providers" section of the dataset metadata. Much of the primary occurrence data that formed the basis for this aggregated dataset will be published as open data on the Global Biodiversity Information Facility (GBIF).

Digital, community-sourced natural history records are valuable for understanding species attributes such as phenology and geographic distribution. When these records include photographs, they can also be analysed for individual phenotypes and species interactions to develop or test ecological hypotheses. Here, we use observational and experimental approaches to assess how insect herbivory affects reproductive success in a widespread forest plant, bunchberry (Cornus canadensis). We queried the Global Biodiversity Information Facility (GBIF) and assembled a dataset of 2,578 photographic records of fruiting plants. Of these, 891 showed evidence of insect herbivory, but herbivory was not significantly associated with fruit production. In a field study we monitored 200 plants over five weeks. Herbivory was widespread (78% of plants showed insect feeding), but damage was generally low—only 5% of plants experienced herbivory ≥40% of total leaf area. No relationship was found between natu..., , # Does the munch affect the bunch? Using community science to explore insect herbivory and fruit production in an understory plant

Dataset DOI: 10.5061/dryad.w6m905r15

Description of the data and file structure

All data is provided as CSV files.

GBIFSurvey data was visually recorded as herbivore ID, internal and external herbivory intensity, and fruit count from photos accessed through the GBIF database (https://doi.org/10.15468/dl.cj78zz)

LongitudinalFieldSurvey data was collected over 5 weeks spanning flowering to fruit ripening. External and internal herbivory intensities were visually estimated, and fruit counts were taken at the end.

SimulatedHerbivory data was collected as a fruit count after fruit ripening, following the manual defoliation of the two treatments. This was a 40% defoliation, performed during flowering for one treatment and during fruit-set for the second treatment.

Files and variables

...,

Aim: Factors affecting bromeliad distribution depend on the life forms of the studied species, some could grow as terrestrial, saxicolous, or epiphytic depending on the type of habitat. We analyzed the distribution patterns of the life forms of a bromeliad species on different biogeographic domains and associated them with environmental variables and vegetation types. Location: Chaquenian, Amazonian, and Seasonally Dry Tropical Forest domains; South America. Taxon: The tank bromeliad Aechmea distichantha (Bromeliaceae: Bromelioideae). Methods: We compiled records of the biogeographic distribution and the vegetation types where Aechmea distichantha occurs based on bibliographic data, digital datasets, herbaria, and personal observations. We associated the distributional records of this species with altitude, five selected bioclimatic variables, four soil variables, and with the vegetation types where it occurs. Results: Aechmea distichantha has been recorded as epiphytic, terrestrial, and saxicolous in all biogeographic domains, but showed contrasting patterns in life form proportions among them. In the Amazonian domain, characterized by evergreen tropical and subtropical forests with high precipitation, it mainly grows as epiphytic. In the Chaquenian domain, dominated by xerophytic forests with low rainfall, high soil pH, and base saturation, it mainly grows as terrestrial, whereas in the Seasonally Dry Tropical Forest domain the three life forms were recorded in similar proportions. In azonal plant communities of all domains, it mainly grows as saxicolous. Main conclusions: This tank bromeliad species can thrive in sites with contrasting habitat and environmental conditions. Its ability to survive in different environments could be associated with its high frost tolerance, the presence of the CAM photosynthetic pathway, a well-developed phytotelma, and high phenotypic plasticity. The life form prevailing in each domain is influenced by water availability (i.e. the quantity of water available during each year, the precipitation in the driest month, and the plant water supply relative to demand).

Methods Occurrences data survey

Occurrence points were obtained by extensively searching the Google Scholar and Scopus databases for literature reporting information on its appearance, as well as reports about the interaction of this species with animal or fungi species. Specimens deposited in FACEN, FCQ, PY (Paraguay), and UNR (Argentina) herbaria, and other specimens available in digital databases (GBIF, 2019; Tropicos, 2019; Flora do Brasil, 2019), as well as journal datasets (Ramos et al., 2019), were also explored. JStor Global Plants (JSTOR, 2019) and ‘Flora del Conosur’ (Zuloaga & Belgrano, 2019) websites were consulted to check types or synonyms. Given that most occurrences and literature citations mentioned only the species name ‘Aechmea distichantha’, for the present analysis we did not make any distinction between infraspecific taxa.

As there could be many sources of potential errors when using large online datasets (Maldonado et al., 2015; Zizka et al., 2019, Zizka et al., 2020), the dataset was compiled and filtered by comparing recorded distributions with areas noted in the literature, as well as with the field experience of the authors. Obvious distribution outliers were checked and deleted when necessary and cultivated specimens were excluded from the analysis. For specimens lacking georeferenced data, coordinates were estimated only for records with accurate locality level spatial data (e. g. municipality or town name, station, farm, finca, estancia or mountain location, roads or rivers intersections, park, reserve or forested area, etc.). We performed manual georeferencing by meticulous interpretation of site descriptions. When available, we checked the original field notes, specimen labels, etc. to improve georeferencing precision and reduce spatial error. To assign the coordinates of each occurrence record we analyzed the site location, classified the type of locality, and then georeferenced it by using the point or point-radius methods in Google Maps and/or Google Earth respectively, following Chapman & Wieczorek (2020) Georeferencing Best Practices.

Records with unambiguous life form information were classified according to the presence of this species on the canopy (epiphytic), on the soil (terrestrial), and on rocky outcrops (saxicolous; Zotz, 2016). A final dataset of 1232 occurrences of A. distichantha was compiled, containing information either on life form, geographic coordinates, or biogeographic regions (provided or inferred).

Environmental data survey

For those records with vegetation description, vegetation types were identified for each biogeographic domain based on community structure description or from its floristic composition (DRYFLOR, 2016; Oliveira-Filho & Fontes, 2000; Prado, 2000). For the Amazonian domain (sensu Cabrera & Willink, 1980) we classified the records into wet forests, savannas, and azonal communities. For the Seasonally Dry Tropical Forest domain (sensu Prado, 2000; Särkinen, Iganci, Linares-Palomino, Simon, & Prado, 2011), we classified the vegetation as mesophytic forests or azonal communities. Finally, for the Chaquenian domain (sensu Prado, 1993a, b), we recognized the following vegetation types: tall xerophytic forests, low xerophytic forests, savannas, and azonal communities. We did not include in the vegetation dataset those records that corresponded to transitions between different domains (N=83; i.e. 63 transitions Chaquenian-SDTF domains, and 20 transitions SDTF-Amazonian domains). For the present contribution, we consider that other bioregionalization schemes (e.g. Morrone, 2014) are not suitable because they do not take into account the unique identity of the SDTF in South America (sensu DRYFLOR, 2016), to which the studied species shows an important association.

We selected altitude and five bioclimatic variables based on the effects that they could have on the growth and survival of a facultative epiphytic bromeliad, and therefore on its distribution (Males & Griffiths, 2017; Males, 2018). Mean Annual Precipitation (MAP, mm) was considered as a proxy for the absolute quantity of water available during each year (Males, 2018). Precipitation in the driest month (Pdry, mm) was a proxy for the absolute degree of water limitation during the dry season (Males, 2018). Precipitation Seasonality (Pseas, %) was used as a proxy for the severity of the dry season relative to the remainder of the year (Males, 2018). Aridity Index (AI, mm mm-1) is measured as MAP/MAE, where MAE is Mean Annual Evapotranspiration, and hence is affected by precipitation, potential evaporation, and temperature. It was used as a proxy for the degree of dryness, where higher AI values denote lower dryness (Zomer et al., 2007). Actual Evapotranspiration/Potential Evapotranspiration (AET/PET, mm mm−1) was used as a proxy for plant water supply relative to demand (Males, 2018).

As terrestrial bromeliad distribution could also be affected by soil features (Benzing, 2000; Barberis et al., 2014), we selected four soil variables (i.e. pH, Percentage of Clay (Clay, %), Cation Exchange Capacity (CEC, cmolc kg-1), and Base Saturation (BSAT, %)) that are known to vary widely among biomes (Rubio et al., 2019).

Altitude, MAP, Pdry, and Pseas, were taken from Worldclim version 2.0 (Fick & Hijmans, 2017, available in http://www.diva-gis.org/), at 30 seconds spatial resolution (~1 km2). Aridity Index, Actual Evapotranspiration (AET), and Potential Evapotranspiration (PET) layers were obtained at the same resolution from the CGIAR-CSI portal (Zomer et al., 2007). The selected soil variables were taken from The Soil and Terrain database for Latin America and the Caribbean (SOTERLAC), version 2.0, at a scale 1:5 million (available in http://www.isric.org/). DIVA GIS v7.5 (Hijmans et al., 2012) was used to extract the environmental information associated with each record.

REFERENCES

Barberis, I. M., Torres, P. S., Batista, W. B., Magra, G., Galetti, L., & Lewis, J. P. (2014). Two bromeliad species with contrasting functional traits partition the understory space in a Southamerican xerophytic forest: correlative evidence of environmental control and limited dispersal. Plant Ecology, 215, 143-153. https://doi.org/10.1007/s11258-013-0261-3

Benzing, D. H. (2000). Bromeliaceae. Profile of an adaptive radiation. Cambridge, England: Cambridge University Press.

Cabrera, A. & Willink, A. (1980). Biogeografía de América Latina. Washington, USA: Secretaría General de la Organización de los Estados Americanos.

Chapman, A. D., & Wieczorek, J. (2020). Georeferencing best practices. Copenhagen, Denmark: Global Biodiversity Information Facility.

DRYFLOR, Banda, K., Delgado-Salinas, A., Dexter, K. G., Linares-Palomino, R., Oliveira-Filho, A., … Pennington, R. T. (2016). Plant diversity patterns in neotropical dry forests and their conservation implications. Science, 353, 1383-1387. https://doi.org/10.1126/science.aaf5080

Fick, S. E., & Hijmans, R. J. (2017). Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37, 4302–4315. https://doi.org/10.1002/joc.5086

Flora do Brasil (2019). Jardim Botânico do Rio de Janeiro. Retrieved from: http://floradobrasil.jbrj.gov.br/ (accessed 12 July 2019].

GBIF (2019). GBIF - Global Biodiversity Information Facility. Retrieved from: https://www.gbif.org (accessed 12 July 2019).

Hijmans, R., Guarino, L., Bussink, C., Mathur, P., Cruz, M., Barrentes, I., & Rojas, E. (2012). DIVA-GIS: A geographic information system for the analysis of species distribution data. Version 7, 476-486.

JSTOR (2019). JSTOR Global Plants. Retrieved from: http://plants.jstor.org (accessed 12 July 2019).

Maldonado, C., Molina, C. I., Zizka, A., Persson, C.,

In the framework of the Lifewatch marine observatory a number of fixed stations in the Belgian Part of the North Sea (BPNS) are visited on a monthly or seasonal basis using RV Simon Stevin. A grid of nine stations covers the coastal zone and are sampled monthly. Eight additional stations, located further at sea, are sampled on a seasonal basis. Samples are taken using a 55µm mesh size Apstein net and fixed in Lugol's iodine solution. In the lab, the samples are processed using a VS-4 FlowCAM model at 4X magnification, size range imaged is 55-300µm. The identification of the image data is done with the use of a classifier and followed by a manual validation step. Since May 2017, this dataset provides micro- and phytoplankton observations, mainly covering diatoms, dinoflagellates and cilliates, for the Belgian Part of the North Sea (BPNS).

Shaken Creek Preserve (“SCP”) is a 2,448 ha (6,050 ac) natural area in Pender and Onslow Counties, North Carolina (U.S.A). Best known for its high-quality longleaf pine savanna habitat, the site contains seven savanna or savanna-like plant community types (i.e., flatwoods or sandhills), three of which are globally critically imperiled (G1): Sandy Pine Savanna (Rush Featherling subtype), Wet Loamy Pine Savanna, and Very Wet Loamy Pine Savanna. SCP hosts three Federally Endangered plant species and six Federal Species of Concern. Formerly a private hunting club, the site was virtually unknown to scientists until the 1990s; consequently, few biological inventories of SCP have been conducted. In particular, no systematic floristic inventories of the species-rich savannas have been undertaken, despite the fact that floristic data is critical to the effective management of any natural area. The goals of this study were to (1) inventory the vascular flora of the savannas, flatwoods, and sandhill community types on site through the collection of voucher specimens; (2) provide a comprehensive checklist of the flora based on collections and reports made from the site and from the same or similar habitats in the vicinity (i.e., within 2 miles of SCP); and (3) create an illustrated guide based on the checklist. In order to increase the usefulness of the guide, taxa not currently known from SCP but collected or reported from the same or similar habitats within two miles of SCP, are included in the guide. Eighty-three families containing 450 taxa, including thirty-two Significantly Rare and thirty-eight Watch List taxa, were collected or reported from SCP; an additional seven families containing a total of 102 taxa, including eighteen Significantly Rare and seven Watch List taxa, were collected or reported from the vicinity. In total, ninety families containing 552 taxa, including fifty Significantly Rare and forty-five Watch List taxa, are treated in the guide. Dichotomous keys are provided to all vouchered or reported families, genera, and species. The following features are provided for all species and infraspecific taxa: flowering and fruiting phenology; synonymy with Manual of the Vascular Flora of the Carolinas, the Flora of North America, and Flora of the Southern and Mid-Atlantic States; relevant voucher information; and, for most taxa, line drawings and/or photographs. For taxa collected from SCP, community types in which the taxa occur and estimates of abundance on site are also provided.

The national monitoring program was initiated by the Swedish Environmental Protection Agency and is now financed by the Swedish Agency for Marine and Water Management.

Monitoring is performed by Umeå University. Data are stored in the Swedish Ocean Archive (SHARK) by the Swedish Meteorological and Hydrological Institute (SMHI).

Data should be sampled and analyzed according to the HELCOM COMBINE Manual - Part C Annex C11 Guidelines concerning bacterioplankton growth determination (https://helcom.fi/media/documents/Manual-for-Marine-Monitoring-in-the-COMBINE-Programme-of-HELCOM_PartC_AnnexC11.pdf). However, deviations from the manual might occur. Information about the program and the methods are available in Swedish at the website of Swedish Agency for Marine and Water Management, https://www.havochvatten.se/hav/vagledning--lagar/vagledningar/ovriga-vagledningar/undersokningstyper-for-miljoovervakning/undersokningstyper/bakteriell-syrekonsumtion.html

Manual of the Vascular Plants of North-West Russia (Tzvelev, 2000): accepted names

In the framework of the Lifewatch marine observatory a number of fixed stations on the Belgian Part of the North Sea (BPNS) are visited on a monthly or seasonal basis using the RV Simon Stevin. A grid of nine stations covers the coastal zone and are sampled monthly. Eight additional stations, located further at sea, are sampled on a seasonal basis.

This dataset contains zooplankton observations in the Belgian Part of the North Sea (BPNS) since 2012.

Zooplankton is sampled by vertical WP2 net tows, samples scanned with ZooScanner and identification with plankton analyser software, followed by manual validation.