EuropaBON WP3.1

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Data Stream - modify

Tab created: 2022-01-14

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

Datasets
Benthos data were supplied by Belgium, Germany, the Netherlands and the United Kingdom, and processed by the Netherlands. For Belgium, Germany and the Netherlands it was assessed, based on expert judgement, that full areal coverage was obtained, for the United Kingdom it was assessed to be partial areal coverage, and no data from Denmark were available. A criterion for sufficient areal coverage had not been discussed and agreed at the time of writing but will be part of the further development of this indicator assessment. For the United Kingdom, some benthos data from assessment areas lying just north of the southern North Sea were assessed (Farnes East, North-East of Farnes Deep, Swallow Sand), in view of the limited data available. The assessment areas were combined with European Nature Information System (EUNIS) Level 3 habitat information (Sand, Mud, Coarse, Mixed), based on an average of 30 samples per area, per year. In addition, median depth data were collected for additional characterisation of the assessment area and reference value modelling. A more detailed characterisation of these data was given by Van Loon et al. (2017, Table 1).

Fisheries activity maps from the International Council for the Exploration of the Sea (ICES; surface and sub-surface activity per grid cell of 0.05° × 0.05°) version January 2016 were used (Figure 1 for an example)(ICES, 2016). The ICES grid cell activity values were averaged per assessment area, for surface and sub-surface activity separately, in order to average out the spatial variation sufficiently, which improved the pressure-impact relationship considerably. It should be noted that the disturbance values being used for the assessment of physical damage on special and predominant habitats were not used for this assessment, but that the same abrasion pressure layer, derived from the ICES fisheries data, was used.

Index Calculation
The optimal benthic index for the southern North Sea, Margalef diversity, was calculated for all southern North Sea benthos samples using the BENMMI tool (benthos multi-metric data analysis software). For each assessment area, the annual average normalised value of Margalef diversity was calculated. The normalised index value is the Margalef diversity value of a sample divided by the reference value of Margalef diversity for the specific assessment area where the sample was taken. It should be noted that Margalef reference values are obtained using reference data from the North Sea (where available) or modelled reference values using least disturbed benthos data monitored by the same national laboratory. This favours good comparability of the reference and assessment Margalef diversity values.

Reference Value Estimation and Validation
An important step in getting realistic normalised Margalef diversity values is to estimate realistic Margalef diversity reference values for each assessment area, such as for the UK_SwallowSand-Sandy habitat. This was done by calculating the 99 (or in some case 95 and 75) percentile index value of a sufficiently large set of Margalef diversity values (with a minimum of 20) for the specific assessment area, as has been used for the European Union WFD by several countries (Van Loon et al., 2015). The use of the 99 or 95 percentile value as the average reference value accounts for a certain amount of index degradation. However, this percentile method was refined by allowing the use of lower percentile values, in case of lower assessment area degradation, as published by Hering et al. (2006). For example, in a pristine assessment area the 50 percentile Margalef diversity value would be the correct reference value. This estimation of lower assessment area degradation could be made using the fisheries activity data from ICES (2016) (see Datasets).

The following quality codes were assigned to the benthos datasets per assessment area: quality code 1 (one monitoring year and at least 20 samples); quality code 2: (two monitoring years and 30 or more samples); quality code 3: (three or more monitoring years and 50 or more samples) (Van Loon et al., 2017. Note that only estimated reference values with quality codes 2 and 3 were used for the Depth-Reference_Value model.

The reference period used per assessment area was in principle six consecutive years, in which the highest period average of the annual average value of Margalef diversity was found. This means that the least disturbed benthos dataset per assessment area is used, as recommended in the OSPAR manual on Biodiversity (OSPAR, 2012). The use of a six-year period appears to give stable reference values, in which temporal variation has been averaged out.

The obtained reference value estimates were validated using the depth model for Margalef diversity (Figure d1; Van Loon et al., 2017), and in some case corrected for better fit on this curve using an adjusted percentile value based on the available fisheries activity data. All Margalef diversity reference values showed a deviation of less than 10% from the depth model, which was considered useful precision.

Assessment of the Southern North Sea
The period average (2010–2015) of the normalised index values of Margalef diversity for each assessment area with at least 20 samples and one monitoring year are shown in Figure 2. The precision of the annual average normalised Margalef diversity (Dn) value per assessment area was calculated as the 90% confidence interval.

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.