EuropaBON WP3.1

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Data Stream - modify

Tab created: 2022-01-12

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 data_stream_datatype_desc

Ebv ess type data_stream_ebv_ess_type_desc

Format data_process_format_desc

Method data_process_method_desc

Frequency data_process_frequency_desc

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

Name data_set_name_desc

Description

Trends are calculated per survey (=area).

Standard data collected on these surveys comprise numbers of each species of fish sampled in each trawl sample, measured to defined length categories (i.e. 1 cm below, so a fish with a recorded length of 14 cm would be between 14.00 cm and 14.99 cm in length). By dividing these species catch numbers-at-length by the area swept by the trawl on each sampling occasion, the catch data are converted to standardised estimates of fish density-at-length, by species, at each sampling location. Summing these trawl-sample species density-at-length estimates across all trawl samples collected within each sampling stratum in each year (e.g. ICES statistical rectangles), and dividing by the number of trawl samples within each stratum per year, gives estimates of the density (of each species and length category) within each sampling stratum in each year. Summing these sample stratum density estimates across all sampling strata sampled in each year, and dividing by the number of strata sampled, provides estimates of the average density (N), of each species (s) and length category (l), in each year, across the whole area covered by the survey. It is these last density estimates (Ns,l km2) that are used in the calculation of each survey LFI time series. However, the LFI is based on biomass rather than abundance, so these abundance densities have to be converted to biomass density data by applying species weight-at-length relationships (of the form w = alb, where w is weight and a and b are species-specific parameters).

Spatial Scope: Assessment Units
A single LFI time series was selected for each survey and individual survey-based assessments were performed. The individual survey-based assessments within each region were then considered to determine an overall assessment outcome for each region.

Baselines
The published study in the Greater North Sea (Greenstreet et al., 2011) established the early 1980s as the reference period for setting the OSPAR Ecological Quality Objective (EcoQO) for the North Sea first quarter (Q1) international bottom trawl survey (IBTS) LFI. This period was selected on the basis that this was the last time that ICES advice for setting fish quotas was to maintain status quo; i.e. to carry on fishing at prevailing levels because stocks were not considered to be unduly depleted (Greenstreet et al., 2011). Selection of this reference period led to the adoption of an LFI of >0.3 as the EcoQO for the North Sea (Heslenfeld and Enserink, 2008). In the Celtic Sea study, Shephard et al. (2011) noted a period of relatively stable LFI values during the late 1980s and early 1990s, which included the six highest LFI values recorded. The stability of the LFI, combined with these high values, led Shephard et al. (2011) to adopt this period as their reference period, and consequently to suggest an LFI of >0.4 as a possible EcoQO for the Celtic Sea.

Assessment Values
Where feasible, studies discussed in the previous (Baselines) section were drawn on to set assessment values for as many of the 13 groundfish survey LFI time series as possible. A number of approaches for doing this were applied.

Greater North Sea
In the Greater North Sea, the principle surveys used to support assessment were the GNSIntOT1 and GNSIntOT3 surveys. GNSIntOT1 is the same survey analysed by Greenstreet et al. (2011), so the same reference period of the early 1980s was used. The GNSIntOT1 and GNSIntOT3 surveys were strongly correlated, so the linear regression obtained was used to determine an assessment value for GNSIntOT3 that was equivalent to the assessment value for GNSIntOT1. Absolute assessment values could not be set for the remaining four Greater North Sea surveys, so a recovery trends-based approach was adopted.

Celtic Seas
In the Celtic Seas, the United Kingdom west coast groundfish survey (WCGFS) analysed by Shephard et al. (2011) ceased in 2004 and so was no longer available for assessment purposes. However, this analysis could be used to inform assessment value setting for the current surveys. The lowest LFI values reported by Shephard et al. (2011) during the reference period was 0.42, so this was adopted as the assessment value rather than their suggested value of 0.40. Generally, low values were observed between 1994 and 2004, and within this period, the lowest five year moving average LFI (0.138) was observed between 2000 and 2004. The assessment value of 0.42 was three times this lowest five year moving average value. So the procedure for setting assessment values for on-going otter trawl surveys in the Celtic Seas region was as follows:

Determine the lowest five year moving average LFI value;
Identify the period to which this five year low moving average LFI relates. If between 1994 and 2004, then this was deemed a valid five year low LFI;
The assessment value was then set at three times the five year low moving average LFI value.
Summary of Assessment Value Approaches
Where the setting of absolute assessment values was not feasible, a trends-based approach was adopted assuming that the demersal fish community in question had been impacted by fishing and that a recovery trend (increasing LFI values) was therefore necessary to rectify the harm done. Table c summarises the assessment value setting approach used and the resulting assessment values.

Deciding on the species to be included in the analysis is the first step in calculating each survey LFI time series. The FishBase website (www.fishbase.org) provided an ‘ecotype’ classification for all species encountered. The LFI has been designed as an indicator of size composition within demersal fish communities, so species assigned to the Pelagic and Bathypelagic ecotypes were automatically excluded, while species assigned to the Demersal and Bathydemersal ecotypes were automatically included. Species belonging to the Benthopelagic ecotype were generally included, but with the exceptions of Clupea harengus, Dysomma brivirostre, Hyperoplys immaculatus, Ammodytidae (family-level ID code), Salmo (genus-level ID code), Salmo salar and Sarpa salpa, which were all excluded on the basis that these species are relatively poorly sampled by the survey gear.

Determining the appropriate length value (LLF) that defined ‘large fish’ for each survey had next to be determined. Traditionally this has been achieved by fitting 5th degree polynomial functions to LFI time series derived using a range of LLF lengths, from 20 to 50 cm, where the LFILLF=l is calculated as:

and selecting the LFI time series with the best fit. In five instances the LFI time series with the best fit polynomial was not selected to support the assessment because resultant LFI values were either too high, or too low, so that either too great a fraction, or too small a fraction of fish were classified as ‘large fish’. Where this happened the actual signal in the LFI trend was markedly diminished, and an alternative LFI time series that addressed this issue was used instead (Table b). The proportion of total biomass at LLF > 50 cm becomes too small to derive a usable indicator; resulting indicators are too strongly influenced by the ‘noise’ associated with variation in the biomass of fish <50 cm in length.

data_set_description_desc

Target biodiversity data bio_data_target_bio_data_desc

Taxonomy

Target taxa data_set_target_taxa_desc

data_stream_taxa_subset_desc

Target species bio_data_target_species_desc

Spatial scale

Spatial scale data_set_spatial_scale_desc

Resolution data_set_resolution_desc

Resolution units data_set_resolution_units_desc

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 data_stream_user_by_policy_desc

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.