This pre-core indicator and its threshold values are yet to be commonly agreed in HELCOM. The indictor is included as a test indicator for the purposes of the 'State of the Baltic Sea' report, and the results are to be considered as intermediate.
A complete evaluation of whether good status is achieved in terms of the number of drowned mammals and waterbirds in fishing gear has not yet been carried out. Due to the lack of availability of suitable monitoring-based data, currently only two populations of harbour porpoises, long-tailed duck, common guillemot and greater scaup were included in the descriptive evaluation.
The data are from scientific case studies, not from regular monitoring programmes, as no such data are available. For other species, indicative results are presented. Since case studies used for the indicator evaluation may be not up to date, the assessment has to be considered as preliminary and is rather a descriptive evaluation.
The confidence in the presented results is low but can greatly be improved once a suitable monitoring scheme is agreed on at Baltic Sea level, and in the frame of the EU Data Collection Multiannual Programme DC-MAP (European Commission 2016). A time series of incidental by-catch estimations would best account for uncertainties in the data (see CLA in "alternative threshold setting approaches", below).
The overall tentative assessment is shown in Result table 1. Given the large uncertainties in the underlying data (incidental by-catch and population estimate) for the harbour porpoise population of the Western Baltic, Belt Sea and Kattegat and the small margin between the preliminary assessment and the threshold, the assessment of whether the threshold is met or not should be reconsidered in the future. This reconsideration should also take into account the exact area covered by the by-catch estimate (ICES 2016a) and the abundance estimate (Hammond et al. 2017) as the latter also includes the Western Baltic. It does not change the overall result of the tentative assessment but on the other hand a false positive (green) may open up for the interpretation that incidental by-catches may not be of concern for this population. A later switch to Catch Limit Algorithm (CLA, see "alternative threshold setting approaches", below) which has been proposed by ICES Working Group on Marine Mammal Ecology (WGMME) might change the colour of the assessment even without having new data.
Population estimates, trend analyses, the level of by-catch as well as the estimation of losses of individuals from other anthropogenic impacts is also a serious shortcoming in the assessment of diving waterbirds. Improved information on these parameters would greatly enhance the validity of the assessment.
Results table 1. Tentative assessment of incidental by-catch per species and sub-basin. The data basis for the three bird species lies before the assessment period (Žydelis et al. 2009).
x = incidental by-catch proven, ? = incidental by-catch mortality remains to be shown (occurrence of bird species and gillnet fishery in area but spatial/temporal overlap uncertain), n.a not assessed (occurrence of this population in the area uncertain). Red: not in good status. Grey: status cannot be assessed - by-catch rate close to the tentative threshold does not imply a good status or bad status.
Incidental by-catch of harbour porpoises and seals is difficult to estimate and reliable studies are scarce, but for harbour porpoise the suffocation through incidental by-catch in fishing gears is believed to be the greatest source of anthropogenic mortality and requires immediate action (ASCOBANS 2009, 2012, 2016b).
For harbour porpoises, the risk of incidental by-catch is highest in various types of gillnets: set gill nets (gear type: GNS), entangling nets (trammel nets, GTR) and driftnets (GND) (ICES 2013a). The latter are banned in the Baltic Sea, but some hybrid nets such as 'semi-driftnets', which are fixed on one end of the net with the other end drifting around this anchor are of special concern.
Only recently have incidental by-catch rates been calculated for the ICES Kattegat and Belt Seas assessment unit (AU) including ICES subdivisions 21, 22 and 23 (ICES 2015, 2016), which is not based on population boundaries. These are based on collated incidental by-catch data from net fisheries (Metier level 3) mainly from a Danish remote electronic monitoring project using CCTV cameras on commercial vessels 10 to 15 m long (see below). For ICES subdivision 24 in the Western Baltic, no estimate of harbour porpoise incidental by-catch has been made.
The 95% confidence interval (CI) for the incidental by-catch numbers applied to the ICES Kattegat and Belt Seas AU is 165-263 calculated for the known fishing effort in 2014 (ICES 2016a). However, there are several sources of uncertainty to this figure. The fishing effort is given in days-at-sea and not km net * soak time (see chapter Monitoring Requirements). The effort of the monitored vessels may thus not have been representative for total fishing effort by all vessels combined. Whereas recreational gillnet fishermen (in some countries) may only set a few nets, commercial vessels larger than 12 m are allowed to set 21 km of gillnets. Such variations do not allow for a realistic effort estimate. Another possible source for the underestimation of incidental by-catch numbers may be that due to a lack of logbook keeping obligations the effort for part-time fishermen and recreational fishermen is not included in extrapolations because data is not available. Another source of uncertainty, which could result in both an upward or downward bias, is that no account has been taken for differences in mesh sizes or other important gear characteristics that may affect the incidental by-catch rate, or spatio-temporal heterogeneity of fishing effort in relation to harbour porpoise density. It has recently been shown that the combination of both fishing effort and harbour porpoise density produce better predictions of the risk of incidental by-catch, than one factor only (Kindt-Larsen et al., 2016).
The incidental by-catch estimate for subdivisions 21, 22 and 23 (which is used in the initial descriptive evalution) has been calculated by ICES (2016a) on the basis of an incidental by-catch rate and an estimate of gillnet effort relating to "days at sea". Results table 2 lists 95 % CIs for the parameters used in the tentative assessment and the factor between lower and upper confidence limit.
Results table 2. Catch rate, fishing effort total incidental by-catch and abundance used in the tentative assessment of the harbour porpoise population of the Western Baltic, Belt Sea, Kattegat. The high ratios between upper and lower confidence limits in by-catch estimate and especially in abundance estimates, as well as the absence of a 95 % CI in the effort data illustrate the low confidence of underlying data.
This overview shows that no uncertainty estimate is available for the estimated total fishing effort. It is based on gillnet effort data for the region directly from the Danish and Swedish fishery. These fishing effort data are likely to be underestimated as it is apparent that effort from smaller vessels and from recreational fisheries which are not obliged to keep a logbook is not represented. On the other hand the data may be biased low because rather large vessels were sampled, which might not have been representative because it is assumed that larger vessels tend to set more nets than smaller vessels. Also, possible differences with respect to by-catch rate between fishing métiers have not been taken into account in this estimate.
Further, the ratio between the lower and upper 95% confidence limits is much bigger for the estimates of abundance than for those of incidental by-catch rate or total incidental by-catch, respectively. Thus, the resources for obtaining the most reliable incidental by-catch estimate should focus on investigating whether it is possible to obtain an estimate for the total fishing effort. Such estimate would have to be described as km of nets*soak time (see 'Monitoring requirements').
So far, incidental by-catch estimates and abundance estimates do not cover the same geographical areas, which adds further uncertainties to the initial assessment. So far no by-catch estimate is available for ICES subdivision 24 (see Results figure 1) of which the western half is covered by the Viquerat et al. (2014) survey which took place in summer 2012 and "Block 2" of the SCANS III survey completed in summer 2016 (Hammond et al. 2017). The latter however does not contain the northern Kattegat, which is on the other hand included in the by-catch estimate by ICES (2016a). Thus, in future abundance monitoring the assessment areas should be based on management needs rather than ICES subdivisions or other artificial boundaries. SCANS (I to III) and Mini SCANS data should then be re-evaluated in order to get a time sequence of abundance data to be fed into CLA calculations.
Results figure 1. Map illustrating the extent of HELCOM, OSPAR, ICES areas and porpoise survey areas mentioned in the text. The depicted OSPAR area do not define the general assessment area used in OSPAR's indicator assessment but is the area used in the specific assessment for Harbour porpoise bycatch. The SCANS-III B2 area is identical to the proposed management area for the Belt sea population (Sveegaard et al. 2015).
ASCOBANS (2016b) compiled available data and literature information on reported incidental by-catch of harbour porpoises in the Baltic Proper. In Latvia, two harbour porpoises were reported as incidentally by-caught in 2003 – 2004. In Poland (period 2010 to 2014), one individual incidentally by-caught in a cod gillnet was reported in 2014. No incidental by-catch had been reported by any other country during 2010-2015. Prior to this (1990-2009) 66 harbour porpoises were reported by Poland as incidentally by-caught, 39% in semi-driftnets, 35 % in cod gillnets, 21 % in other set gillnets, 3 % in pelagic trawls and 2 % in driftnets (banned since 2008). Due to the lack of systematic collection of such data it is not possible to draw any conclusions on trends or spatial distribution of incidental by-catches from these incidental by-catches. Thus, the compiled data must be regarded as minimum numbers.
The population estimate of harbour porpoises in the Baltic Proper assessed by means of 304 acoustic data loggers is 497 animals (95% CI: 80-1091) (ASCOBANS 2016b). The abundance of the porpoises inhabiting the Western Baltic, the Belt Sea and Kattegat has been estimated four times (SCANS in 1994, SCANS-II in 2005, MiniSCANS in 2012 and SCANS-III in 2016). The geographical extent of the survey areas differs between years and only block 2 of the SCANS-III survey (Abundance = 42 324 (CV = 0.304, 95% CI: 23 368 – 76 658), Hammond et al. 2017) corresponds to the proposed management unit (from the Kattegat as far north as the Limfjord to the Western Baltic and east to a line between the Island of Rügen and Scania) of the Belt Sea population (Sveegaard et al. 2015). The survey area from 2012 with an abundance of 40 475 (CV = 0.24, 95% CI: 25 614-65 041) corresponds better to the bycatch estimate in ICES area 22, 23 and 24. Due to the geographical differences, the four survey results are at present not directly comparable although they are not significantly different. The SCANS-III group is currently working on calculating model-based abundance estimates for all the surveys and with this method, abundances for selected areas may be compared.
In the SAMBAH project considerable numbers of harbour porpoises from the Western Baltic, Belt Sea and Kattegat population were estimated in an area east of the Darss Sill and south of the Limhamn ridge in the Sound (ASCOBANS 2016b). Using a different method, the SAMBAH abundance estimation for this area alone is 21 390 (95 % CI: 13 461-38 024) based on data from acoustic data loggers between 2011 and 2013.
The population boundaries of the harbour porpoise population of the Western Baltic, Belt Sea and Kattegat must be better defined. Arbitrarily, the northern boundary of the population of the Western Baltic, Belt Sea and Kattegat can be used from Sveegaard et al. (2015). Tissue samples to be taken during incidental by-catch monitoring would allow assigning specimen to one of the two populations present in the Kattegat through advanced genetic sequencing techniques (such as Genome-wide Single Nucleotide Polymorphism (SNP) analysis) (Lah et al. 2016). An increasing number of analysed specimens would then allow to more reliably identify the boundaries.
Since no incidental by-catch estimate is available for the whole area and there is no reliable correction for North Sea population animals in the overlap zone in the Kattegat, a tentative assessment can currently only be made on the basis of ICES sub-divisions 21, 22 and 23 which accounts for the major part of the population range. ICES (2016a) gives a 95% confidence interval for their incidental by-catch estimate of 165 to 263 harbour porpoises in these ICES sub-divisions. The best geographical fit with these sub-divisions is the abundance assessment by Viquerat et al. (2014) to which the incidental by-catch estimate has been related. A combined 95 % confidence interval for abundance and incidental by-catch rate estimates (Buckland 1992) results in 0.3 to 0.9 % which is in the same range as the removal target. However, fishing effort from small vessels have to be estimated and taken into account additionally. If the abundance estimate from Hammond et al (2017) is taken, which corresponds with the population management borders suggested by Sveegaard et al. (2015), but less with the area for which a by-catch estimate is available, the range of a combined 95 % confidence interval for abundance and incidental by-catch rate would result in a by-catch of 0.26 to 0.92 % of the abundance estimate. Due to uncertainties in both the population estimates and estimate of fishing pressure, a bycatch rate close to the tentative threshold does not imply a good status (by-catch rate < tentative threshold) or bad status (by-catch rate > tentative threshold).
For the Baltic proper, the threshold of zero incidental by-catch is exceeded by one by-catch in 2014 officially reported (ASCOBANS 2016b). This can be taken as the absolute minimum number as in earlier years incidental by-catches reported by fishermen to the Hel Marine Station were much higher. The EU driftnet ban in 2008 resulted in the cessation of fishermen reports (Pawliczka 2011).
The next step in refining incidental by-catch estimates could be the identification of high-risk areas for incidental by-catch. The number of harbour porpoises does not only have an effect on the evaluation of the total incidental by-catch in relation to the total abundance, but the local density of harbour porpoises also affects the incidental by-catch rate on a temporal and spatial scale. Given the solitary nature of harbour porpoises, the incidental by-catch rate in a certain fishery is expected to be as dependent on the harbour porpoise density as on the fishing intensity. In other words, if the fishing effort with a certain fishery is doubled in an area, the total number of incidental by-catches is expected to double as well. Or, alternatively, if the fishing effort is kept constant but the harbour porpoise density is doubled, the total number of incidental by-catches is expected to double. This relationship is the basis in a recently published paper on identification of high-risk areas for harbour porpoise incidental by-catch (Kindt-Larsen et al. 2016). All concerns expressed by ICES WGBYC (ICES 2015) on using "imported" observed bycatch rates on fisheries lacking observer data that are quoted in the indicator relate to differences in fisheries parameters, such as vessel size and fishing practices, but never to variation in harbour porpoise density. Even though the "import" primarily is made for fisheries within the same ICES division (e.g. IIId), the spatio-temporal variation in harbour porpoise density may be considerable within these areas. Using the approach of a by-catch risk assessment, it should be possible to estimate a removal rate that includes the uncertainties of both the incidental by-catch rate and the abundance by simulating incidental by-catches from the estimated distributions of both parameters.
For seals, in addition to various types of gillnets: set gill nets (gear type: GNS), entangling nets (trammel nets, GTR) and driftnets (GND), incidental by-catch risks stem from fykenets (FYK) and push-up traps without excluding devices in their entrance are of special concern (ICES 2013a, Vanhatalo et al. 2014).
Based on interviews of fishermen from Sweden, Finland and Estonia, and accounting for the variability in seal abundance and fishing effort and also for underreporting, the annual incidental by-catch of grey seals in trap nets and gill nets in these countries is estimated around 2,180-2,380 individual seals in 2012, probably representing at least 90% of the total incidental by-catch in the whole Baltic Sea (Vanhatalo et al. 2014). Annual population growth rates were estimated to be 9.4% (2000-2004) and 3.5% (2004-2009) in Finland (Kauhala et al. 2012) and 7.5% along the Swedish Baltic Sea coast since the 1990s. The incidental by-catch rate would result in 7.7-8.4% of counted seal numbers (Finnish Game and Fisheries Research Institute 2013). This rate is an overestimation because not all animals of the population are recorded during counts. Thus a low confidence of data results from the monitoring method and the lack of a population estimate (including confidence intervals).
Diving waterbirds are especially vulnerable to set gill nets (GNS), entangling nets (trammel nets, GTR) and driftnets (GND), but incidental by-catch also occurs in other static fishing gears such as longlines and traps (ICES 2013a, b). Several studies have shown that the gillnet fishery in the Baltic Sea can in certain places cause high bird mortality. A rough estimate comprised 100,000-200,000 waterbirds drowning annually in the North and Baltic Seas, of which the great majority refers to the Baltic Sea (review of studies in Žydelis et al. 2009, 2013). Locally, incidental by-catch rates have decreased during the last two decades, likely as a result of declined abundance of wintering waterbirds and resulting reduced density at sea (Bellebaum et al. 2013).
Areas where waterbirds aggregate are often overlapping with gillnet fisheries (Sonntag et al. 2012), thus the incidental by-catch risk is high when gillnet fishing is exercised in areas with high abundance of foraging waterbirds, which can be present during the breeding period, during migration, for moulting and for wintering. High incidental by-catch numbers are reported from regions of high bird abundance (e.g. wintering birds on offshore banks and in coastal areas, Larsson & Tydén 2005, Žydelis et al. 2009, 2013, Bellebaum et al. 2013). Taxonomic groups under high pressure from incidental by-catch in the Baltic Sea are divers, grebes, cormorants, alcids, mergansers and ducks.
For waterbirds the potential biological removal (PBR) method (see 'Thresholds and Status evaluation) is used to compare incidental by-catch numbers in a population to its size. The level of pressure on a population is considered to be at an unacceptable level if the contribution of incidental by-catch brings human-caused mortality above the removal target. PBR values by Žydelis et al. (2009) were generally used as tentative threshold values for this descriptive core indicator evaluation. If recent information suggests a sharp decline in abundance a different recovery factor was used. For long-tailed duck, greater scaup (including wintering birds in the Netherlands) and common guillemot, the PBR approach has been applied (Žydelis et al. 2009) in order to derive removal targets that can be provisionally considered.
In contrast to Žydelis et al. (2009), a recovery factor of 0.1 was applied to the long-tailed duck owing to the sharp decrease in population size reported by Skov et al. (2011), Bellebaum et al. (2014) and Nilsson & Haas (2016). The total long-tailed duck incidental by-catch from available estimates was about 22,000 birds by the time of PBR calculation. Adding mortality by hunting (c. 30,000 birds in hunting bag and cripple losses in EU countries alone, Mooij 2005) and oiling ('tens of thousands', Larsson & Tydén 2005), the tentative threshold of 22,600 is clearly exceeded. Incidental by-catch has presumably dropped since then, but so has population size and hence the recent PBR. Hunting has decreased as well, in Finland and Sweden combined from up to nearly 90,000 birds (1994) to less than 10,000 birds annually since 2000 (Skov et al. 2011). The assessment should be refined using more recent data as soon as this becomes available.
For the greater scaup the PBR limit is 3,700 birds (Žydelis et al. 2009), a value exceeded by losses from fisheries in northern Europe alone and intensified by losses owing to other pressures. Due to the large decline in abundance recorded during 1990–2000 and the greater scaup being classified as endangered in EU countries, this PBR limit is based on the recovery factor of 0.1, the lower of two values presented by the authors. Incidental by-catch is known in the southern Baltic but estimates are not available. However, about 2,000 incidentally by-caught birds in the Dutch lakes Ijsselmeer and Markermeer alone impact the same population. An unknown number of incidental by-catches for the southern Baltic contributes to exceeding the pre-defined threshold of human induced mortality for that population which also suffers from hunting and other anthropogenic impacts (the hunting bag is about 2,000 birds). The tentative threshold value of 3,700 birds (valid for the Western Palearctic population) is clearly exceeded.
For the Baltic-breeding common guillemot population, the calculated PBR limit of 620 individuals is more than twice exceeded by the estimated minimum incidental by-catch for the Baltic Sea (Žydelis et al. 2009). 1,500 incidental by-catches are estimated from recoveries of ringed birds alone. Oiled birds have not yet been taken into account and should still be added. In this population however, immature birds are more likely to die in gillnets than adults. Since PBR assumes that all cases of additional mortality are equally distributed, the PBR chosen is rather conservative.
All uncertainties identified show that sufficient monitoring of incidental by-catch, fishing effort, population size, trend analyses and other sources of anthropogenic mortality are a prerequisite for getting a more reliable assessment. The European Commission has decided to include incidental by-catch monitoring of protected bird and mammal species in the Data Collection Multiannual Programme DC-MAP (European Commission 2016). Further participation of HELCOM and HELCOM Contracting Parties on a regional scale is necessary for the implementation process in order to ensure suitable monitoring methods and sufficient coordinated coverage, as well as effort monitoring, are developed into meaningful parameters (fishing effort must be measured in net km * days, see Monitoring Requirements, Description of optimal monitoring). So far, only fishing effort from logbooks and VMS data is used for by-catch calculations (ICES 2015, 2016). The additional effort by commercial vessels <10 m for which a logbook is not required and by recreational fishermen must be estimated and taken into account. Then the uncertainty in the fishing effort estimates which underlie the incidental by-catch estimate needs to be specified by also adding a CV or 95 % confidence interval.
Since many species of diving seabirds are prone to accidental by-catch, additional species should be included in the indicator evaluation.
The shortcomings in relation to population estimates, trend analyses and the level of anthropogenic impacts on these populations in common give a low confidence in this indicator. High priority should be given to improvement of these shortcomings.
The overall confidence is low.
Monitoring data on numbers of incidentally by-caught mammals and waterbirds collected on an annual basis are virtually non-existent. However, limited data from scientific studies and pilot studies can – with the appropriate caution - be used for an initial assessment for a few species. Some of these data may not be up-to-date and thus have to be related to previous abundance data. Also, in some areas gillnet effort may have decreased during in the last two decades. So far, the confidence in any previous estimates of the pressure exerted by incidental by-catch of the relevant populations is low. Estimates are believed to be either underestimates or very uncertain because the proportion of unreported cases is likely to be high. In some areas, there are serious caveats in the underlying data. In other areas, the extrapolation of recorded by-catch numbers to estimated gillnet effort may be problematic due to the unavailability of effort data during that time. For example, in older Polish studies such as Stempniewicz (1994) extrapolations were based on the total number of registered fishing vessels possibly resulting in an overestimation (unpublished information from the Polish National Marine Fisheries Research Institute). Incidental by-catch numbers for seals and harbour porpoises are either absolute minimum numbers (from reported incidental by-catches) or estimates from pilot studies. For harbour porpoises, there is a high degree of uncertainty both in the estimated numbers of incidentally by-caught animals and in the estimated removal targets (see chapter 'Targets', below) needed for evaluation of these. For seals, the study by Vanhatalo et al. (2014) has recently increased the knowledge. For waterbirds, the magnitude of the incidental by-catch has been slightly better clarified on the scale of localised case studies (Žydelis et al. 2009). In order to increase the confidence of the core indicator evaluation, annual monitoring data of incidental by-catches based on a sufficient number of observer days, and associated with well-described fishery effort, is a prerequisite.