EuropaBON WP3.1

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Data Stream - modify

Tab created: 2021-11-02

Project

1) Data origin - from where is data coming from

Origin integration node

2) Data process - how is the data processed (if)? And how does it flow?

Data type Options: 1) Raw: data as collected in the field ; 2) Aggregated: raw data is aggregated (not processed!); e.g. occurrence data collected in linear sampling transects of 1 km is aggregated (summed) at 10 km resolution; e.g. data from seasonal sampling is aggregaged at annual level ; 3) Essential Biodiversity Variables (EBVs) ; 4) Ecosystem Services vales (ESS); 5) Indicators: other processed indicators such as for example species trends

Ebv ess type If the data flowing or generated by a given integration node is an EBV or an ESS, please, select the category from the list

Format Format of the data flowing between biodiversity monitoring initiatives and integration nodes or between integration nodes

Method If there is any type of data integration (i.e. if data type is other than Raw or Aggregated) , indicate the method used to integrate data. Please, use the field “Description” below to give further details about the method used to process the data, including relevant bibliographic references and URL links if available.

Frequency Indicate the frequency of the data flow (e.g. annual, seasonal)

3) Data set - which dataset/integrated product is processed and how?

Name Name of the dataset (please provide an informative name for the dataset flowing)

Description

Digital distribution maps were created using distribution
data collated from available literature, internet sources,
and the Atlas Flora Europaeae (Kurtto et al. 2013). The data
varied immensely in terms of quantity and quality. For
some countries (and for some species), including Spain,
France, Bulgaria, Sweden and Switzerland, distributions
were available as either point location data (latitude/
longitude) or in grid cell format and are therefore very
precise. Where point or grid data were available, data
were projected in a Geographical Information System
(GIS) (ESRI ArcMap) and polygons drawn manually,
clustering points where appropriate. For some countries
it was only determined that the species is extant in that
country and therefore the distribution was mapped to
the whole country (e.g. Romania and, in other cases,
the countries of former Yugoslavia), whilst in some cases
data were only available at the subnational level and a
taxon was mapped to the appropriate administrative
unit (e.g. regions in Italy). Depending on information
availability, metadata coding was used to distinguish
presence, origin, and seasonality across the spatial extent
of a species’ distribution. These codes differentiate the
species presence (species are recorded as extant, possibly
extant or extinct); seasonal presence of the species in the
location (the default setting of ‘resident’ was assigned);
and the origin of the species (native, introduced,
reintroduced or uncertain). The coding information can
be found in the Red List digital distribution metadata
guidance (IUCN 2014).
In the analysis of the spatial data, only distributions with
the following Presence, Seasonal and Origin codes were
used:
• Presence: Extant and Possibly Extant
• Origin: Native and Re-introduced
• Seasonality: Resident
Spatial data were analysed using a geodesic discrete global
grid system, defined on an icosahedron and projected to
the sphere using the inverse Icosahedral Snyder Equal
Area (ISEA) Projection (S39). This corresponds to a
hexagonal grid composed of individual units (cells) that
retain their shape and area (865 km2
) throughout the
globe. These are more suitable for a range of ecological
applications than the most commonly used rectangular
grids (S40). The range of each species was converted to
a hexagonal grid for analysis purposes. Coastal cells were
clipped to the coastline. The pattern of overall species
richness (Figure 5) was mapped by counting the number
of species in each cell (or cell section, for species with
a coastal distribution). Patterns of threatened species
richness (Figure 6) were mapped by counting the
number of threatened species (categories CR, EN, VU at
the European regional level) in each cell or cell section.
The pattern of endemic species richness was mapped
by counting the number of species in each cell (or cell
section for coastal species) that were flagged as being
endemic to geographic Europe as defined in this study
(Figure 7). Finally, the distribution of species assessed as
Data Deficient is shown in Figure 8.

Brief description of the data flowing (e.g. if the dataset represents aggregated data, please explain here how the aggregation is made); if the data set is a “product” – EBV, ESS, indicator – give more information here about how its values are estimated and provide relevant bibliographic references or URL links if available)

Target biodiversity data Select biodiversity data initiatives included in the dataset. No need to choose them in upper levels when creating products.

Taxonomy

Target taxa Target taxa

check this box if you have a list of taxa to upload for this data stream (no need to check it when sending all species available from data origin). If the DataStream generates a product integrating data for specific taxa, please try to upload the list of taxa included in the product.

Target species List of the target species/habitats covered in the monitoring initiative. If you don´t find a thesaurus for the taxa of your interest, you might need to upload a New Thesaurus first – see tab New Thesaurus – and then, use the option “Choose Thesaurus” to select all or a subset of the taxa concerning this particular DataStream (the species integrated in a particular indicator/EBV/ESS)

Spatial scale

Spatial scale Spatial scale coverage of the dataset

Resolution Spatial scale resolution value (numeric)

Resolution units Spatial scale resolution units (km or m)

4) Data destination - where does the data/product flow to?

Two options here:

a) The data flows into an upper-level integration node b) The data is a generated Product

Select the destination integration node

Dest integration node

Is the product generated used by policy - e.g. EBV, EESV, indicator?

Used by policy Is the indicator generated used by policy ?

Note here that some indicators might currently lack connection to policy but we want to capture them here too because of their potential to inform policy in the future.