EuropaBON WP3.1

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Data Stream - modify

Tab created: 2021-10-27

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

Indicators of breeding failure were constructed using time series of annual mean breeding success (number of chicks fledged per pair, clutch or nest) of marine bird species at colonies throughout the North-East Atlantic (total counts or survey plots). A separate assessment was conducted for each species in each OSPAR Region. An assessment was also conducted for each sub-division of the Greater North Sea, as shown in Figure a, and the Norwegian parts of the Arctic Waters. Separate assessments were not conducted for each Arctic sub-division because there were too few colonies included in each sub-division.

The breeding failure assessments for each species were constructed from time series of annual estimates of breeding success at a sample of colonies. The time series used covered the periods 1991–2015 for the Greater North Sea and Celtic Seas and 2010–2015 for the Norwegian parts of Arctic Waters. Not all colonies in the sample will have been observed every year in the time series, therefore (prior to the analysis) missing annual observations were predicted using models (for methodology see Trend Analysis).

Species-Specific Assessment of Breeding Failure
Rationale for Assessment Values
The assessment values applied for this indicator were developed by Cook et al. (2014a) and were agreed to be technically appropriate by the Joint OSPAR / ICES / HELCOM Working Group on Marine Birds (ICES 2015). The rationale and values are described in the following sections.

OSPAR Intermediate Assessment (IA) 2017 Indicator Assessment values are not necessarily to be considered as equivalent to proposed EU Marine Strategy Framework Directive (MSFD) criteria threshold values, however they can be used for the purposes of their MSFD obligations by those Contracting Parties that wish to do so.

Parameter / metric
‘Annual colony failure rate’, that is, the percentage of colonies failing per year, per species (from Cook et al. 2014a).

‘Failure’ is defined as when a colony fails to produce any young or produces very few young during a single breeding season. Failure is quantified by Cook et al. (2014a) as when the mean annual productivity of a breeding colony is 0.1 or less chicks per pair, clutch or nest. As failure could be interpreted as an unusual deviation from ‘normal’ levels of breeding success, the precise assessment value below which a colony is defined as failing may be different at some colonies, even for the same species. The assessment value used for determining failure can be adjusted according to knowledge of the colony in question. Ideally, the assessment value should be obtained from any clear response to important environmental factors such as low food availability (e.g. Cury et al. 2011). The assessment value of 0.1 chicks per pair, clutch or nest should be used as the default assessment value, unless there is good evidence to show that ‘failure’ of some species in some areas should be set at a different level (ICES 2015).

Trend analysis
The assessments for each species are constructed from a time series of annual estimates of breeding success at a sample of colonies. Not all colonies in the sample will have been observed every year in the time series. Missing annual observations were predicted using a Generalised Linear Model (GLM) framework with a binomial error structure (after Cook et al. 2014a and 2014b). Breeding success for each colony in each year was calculated, and where this value was 0.1 or less chicks per pair, clutch or nest, the colony was assessed as having failed in that year. Breeding success or failure was modelled in relation to year and site, because not all sites were covered in all years. The coefficient for each year was then taken to represent the probability of breeding failure occurring at any given site within that calendar year. The parameter ‘Year’ was included in the GLM as a fixed effect factor, rather than a random effect, so that the coefficients would not be constrained to follow a normal distribution.

To minimise the impact of differences in sampling rate, and to ensure that breeding success was likely to be representative of the colony as a whole, minimum criteria were set for inclusion of data within the model. Only those colonies at which a mean of ten nests were monitored for at least three years were considered. To prevent any individual site having an undue influence over the value of the coefficients, a jack-knife statistical approach was used, dropping each site from the model in turn. Models were run for each species in each sub-region in turn. The final indicator value presented for each species, in each sub-region, in each year is the mean probability of breeding failure calculated from each run of the jack-knife analysis.

Assessment
In summary, ‘breeding failure’ is when the annual mean breeding success of a colony is 0.1 or less chicks per pair, clutch or nest, and ‘annual colony failure rate’ is the percentage of colonies of species that are experiencing breeding failure in a single breeding season.

Breeding failure for each species was assessed in two stages:

1. Assessing if colony failure is widespread - the annual colony failure rate (the percentage of colonies experiencing breeding failure) can be considered to be ‘widespread’ if it exceeds the assessment values set for each species (see below).

2. Assessing the frequency of widespread breeding failure occurrence. Widespread breeding failure will be considered to be frequently occurring if it occurs in four years or more out of six.

Assessing if colony failure rate is widespread
The annual colony failure rate (the percentage of colonies failing) of each species was assessed against one of the two upper assessment values below, depending on the species. This was done for each region:

a) terns: mean percentage of colonies failing per year, over the preceding 15 years;

b) all species except terns: 5% of colonies failing per year.

The aim of the assessment values for annual colony failure rate is to identify widespread breeding failures and to differentiate large-scale impacts from local problems, where only a small proportion of colonies fail per year. The above assessment values were taken from Cook et al. (2014a), who tested various assessment values for each species.

A different assessment value was applied to the breeding failure rate of terns because they often desert colonies, sometimes before laying eggs, in response to local disturbances or impacts on food supply (Shealer and Kress 1991; Holt 1994; Cook et al. 2011). The assessment value for terns is designed to identify years of unusually high rates of breeding colony failure.

A fixed assessment value of 5% was appropriate for all other species that do not tend to desert colonies all at once. Cook et al. (2014a) found that years in which colony failure rate is more than 5% are much rarer in other species and they therefore provide a good indicator that pressures may be impacting on the population.

Assessing the frequency of widespread colony failure
For each species, the frequency of widespread colony failure was assessed over the most recent six-year period from 2010 to 2015, inclusive. A six-year period was chosen because it equals the length of the EU’s MSFD reporting cycle. To carry out an assessment of a species over a certain time period, there needed to be some observed data of breeding success at some colonies during the most recent year in the period (2015).

One or two years of widespread colony failure were considered as ‘acceptable’, given the wide range of possible natural and anthropogenic factors that could cause breeding failure in some species. The cumulative effect of widespread colony failure in four or more years out of six, was considered most likely to have a significant impact on recruitment into the regional population (Cook et al. 2014a). Low recruitment could lead to declines in population size and to affect the assessments of the OSPAR indicator on marine bird abundance.

Breeding failure is a ‘life history’ strategy for some species such as Arctic tern which, if conditions are sub-optimal, will desert a colony all at the same time, rather than remaining and trying, but failing, to raise young. Therefore, the definition of failure used in this indicator assessment (i.e. <0.1 chicks fledged per pair, clutch or nest) may provide an overly pessimistic indication of breeding performance in such species. However, this approach of assessing the frequency of widespread failure could reduce the chance of false negative assessments being made (ICES 2015).

Species Selection and Aggregation (functional groups)
There were sufficient time series data to conduct assessments of 16 species in the Norwegian parts of Arctic Waters, 20 in the Greater North Sea and 20 in the Celtic Seas. Overall, 25 different species were assessed in at least one region.

Some species were omitted from the regional assessments because the time series did not contain an estimate of breeding success in 2015 and the model was unable to predict missing values beyond the length of the time series. These included data from the Netherlands on common eider (Somateria mollissima), Eurasian spoonbill (Platalea leucorodia), pied avocet (Recurvirostra avosetta), and oystercatcher (Haematopus ostralegus) and from roseate tern (Sterna dougallii) colonies in Ireland (Celtic Seas). However, the breeding failure rates for these species in the years when data were available are presented in Figure b26 to Figure b29 for information.

Table a presents the five marine bird functional groups. The species assessed in each region were all seabirds from two of the five functional groups:

a) Surface feeders, which forage on small fish, zooplankton and other invertebrates at or within the surface layer (within 1 m to 2 m of the surface);

b) Water column feeders, which actively dive below the surface to a broad range of depths to feed on fish and invertebrates (for example, squid, zooplankton) in the water column or close to the seabed.

The 25 different species assessed and the functional groups to which they were assigned, are presented in Table b.

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.