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

Pup production estimates from all colonies within a given AU were summed to generate an overall assessment for that area. Quantitative assessments of trends in pup production were only completed for those AUs where three or more annual data points were available.

In addition to the assessment of the Wadden Sea (AU17), a separate assessment was conducted on the Dutch part of the Wadden Sea, where the time series began in 2001, compared to 2008 for other parts of the Wadden Sea. Earlier data exist, both for Dutch and German waters, but these were collected using different methods and so are difficult to compare with data collected subsequently.

Grey seal pup production estimates were assessed in relation to a baseline set at 1992 (or the start of the time series where this was after 1992), and by calculating the average rate of annual population change within the last reporting round (2009–2014).

To determine the change in pup production since the baseline year, generalised linear models or generalised additive models were fitted to the sum of pup production data within an AU with a quasi-Poisson error distribution and log link using all available annual survey data for the period 1992–2014. The percentage change in pup numbers since the baseline year (Formula A; Δabundance) and 80% confidence intervals were calculated from fitted values. Although no formal hypothesis testing was conducted, 80% confidence intervals were calculated to reflect the choice to set the significance level, α, equal to 0.20 or 20%.

To estimate the annual change in pup production over the previous six-year reporting round, a linear trend was fitted to the sum of all available data in each AU for the reporting round 2009–2014. GLMs were fitted to the sum of pup production data within an AU with a quasi-Poisson error distribution and log link. Annual growth rate (%) and 80% confidence intervals were estimated for each of the AUs. Although no formal hypothesis testing was conducted, 80% confidence intervals were calculated to reflect the choice to set the significance level, α, equal to 0.20 or 20%.

Indicator metrics and associated confidence intervals were assessed against two thresholds: the average annual growth rate (%) and 80% confidence intervals within the last reporting round were less than -1% per year, and the percentage change in abundance since baseline year (Δbaseline) and 80% confidence intervals were less than -25%. If the 80% confidence intervals encompassed the threshold, the assessment was classified as ‘inconclusive’.

Statistical power of detecting change in pup production

There are many reasons why pup counts could vary, aside from representing true changes in pup production, These include variation in weather and a recent disturbance at a colony. It is therefore advisable to examine the variability in survey counts and to incorporate this variability into trend estimates. The International Council for the Exploration of the Sea (ICES) Working Group for Marine Mammal Ecology (WGMME) (ICES, 2014) provided general advice on the need to understand the statistical power of monitoring programmes. In the present context, statistical power is the percentage confidence in not missing a significant decline. Statistical power depends on the sample size (number of surveys), the level of statistical significance set (α-level), variance in the counts, and the magnitude of the trend, that is, -1% and -25%. The ICES WGMME (ICES, 2014) recommended that monitoring should achieve a minimum of 80% power – which equates to a 20% chance of making a Type II error (i.e. the frequency with which a true decline would not be detected). The same group also recommended that the threshold for detection of a statistically ‘significant’ trend be relaxed from the traditional α=0.05 to α=0.20. The α parameter, or statistical significance level, equates to the probability of concluding that a statistically significant trend exists when it does not (Type I error). A α value of 0.2 and power of 80% means there is equal probability of making an incorrect conclusion (either Type I or Type II error) about the detection of a trend.

Current monitoring programmes vary in the level of statistical power achievable. To carry out a full study of retrospective power to detect changes in the observed population trends, detailed information about the between- and within-year variability in all survey counts would be necessary. A full assessment of power was not undertaken here but confidence intervals (CIs)  provide a measure of confidence in the assessment. Simply said, they describe the frequency with which the true, unobservable, population parameter (here, the mean count) could be expected to fall within the intervals described by an upper and lower confidence limit. Where the confidence intervals encompass the assessment value the data do not provide conclusive evidence for the calculated value being above or below the assessment value.

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.