Assessment protocol

·        Each management unit is evaluated against two sets of GES-boundaries, the GES-boundary for exponentially growing populations and the GES-boundary for populations at carrying capacity of the system (Table 1).

·        HELCOM assessment units used; Level 2 for all species of seals. For grey seals spatial units in the Baltic will be merged and treated separately from the Kattegat and Limfjord unit.

·        Samples from sub-adult seals (1-3 years) are used in the analysis.

·        Data on blubber thickness from samples collected over the year are transformed to reflect the situation in October, by using the polynome y = 0,7151x2 - 10,597x + 71,557, where x is the month of year.

·        Observed data is to be merged for 3-5 year intervals, depending on sample size, to be used as input values in Bayesian analyses with uninformative priors, where it is evaluated if observed data from an assessment unit achieve the GES-boundary value. In this process, 80% support for a growth rate ≥ GES is required. If the unit fails GES, the probability distribution is used to evaluate the confidence of the evaluation.

·        The package Bayesian in the program R is used in the analysis. To be added


Treatment of data

The blubber thickness of 1-3 year old grey seals shows a seasonal flux as illustrated in Figure 1. A polynome fitted to data can be used to merge data from all months, by recalculating each data point to the month of October. This month was chosen because the fit of the polynome is less affected by outliers here compared with end points (April and December), and that there is a reasonably amount of data in October. Another reason is to make data from Figure 11 and Figure 1 compatible. The mean of all data in Figure 1 recalculated to October is 39.1 mm (SD 9.9mm). Thus data can be used in this analysis regardless of which month the sample is taken.​

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Figure 1. Seasonal changes in blubber thickness of 1-3 year-old hunted grey seals (Combined Swedish and Finnish data, n=210).

 

Evaluating an assessment unit against the GES-boundary

The Baltic grey seal has been growing exponentially since the mid 1980's at about 8% per year, and are thus not approaching carrying capacity and the GES boundaries at 40 mm for hunted seals and 35 mm for by-caught seals are applicable. Data is merged separately for those categories for years 2007-2009, and a Bayesian analysis is performed, testing if observed data deviate from the GES-boundaries.

 

Management units and assessment units

The existing management plans for seals operate based on management units that are derived based on the distribution of seal populations. The management units typically encompass a handful of HELCOM Level 2 assessment units, i.e. sub-basins. Evaluations of assessment units is therefore done by grouping HELCOM assessment units to align with the management units defined for each seal population.

·        The Baltic grey seal is a single management unit, although genetic data show spatial structuring (Graves et al. 2013). Also behavioural data suggest some large scale structuring.

·        The Baltic Ringed seal is distributed in the Gulf of Bothnia on the one hand and Southwestern Archipelago Sea, Gulf of Finland and Gulf of Riga on the other, and represent two different management units. This subdivision is justified by ecological data that indicate separate dynamics of these stocks. Since ringed seals from both areas show a high degree of site fidelity, as seen in satellite telemetry data (Härkönen et al. 2008), it is unlikely that extensive migrations occur at current low population numbers, although some individuals can show more extensive movements (Kunnasranta et al. unpublished).

·        Harbour seals in the Kalmarsund, Sweden, constitute a separate management unit and is the genetically most divergent of all harbour seal populations in Europe (Goodman 1998). It was founded about 8,000 years ago, and was close to extinction in the 1970s as a consequence of intensive hunting, and possibly also impaired reproduction (Härkönen et al. 2005). The genetic diversity is substantially reduced as compared with other harbour seal populations.

·        Southwestern Baltic (Danish Straits, Danish, German, Polish Baltic and the Öresund region including Skåne county in Sweden) harbour seals. This stock is genetically distinct from adjacent populations of harbour seals (Olsen et al. 2014) and should be managed separately.

·        Harbour seals in the Kattegat are also genetically distinct from adjacent populations (Olsen et al. 2014). This population has experienced dramatic declines in 1988 and 2002 caused by phocine distemper epidemics. A third epidemic caused by an unknown virus caused substantial mortality in 2007 (Härkönen et al. 2008). And in 2014 this population was again negatively affected, this time by avian influenza (Zohari et al. 2014).

·        Harbour seals in the Limfjord form the fourth management unit and is genetically distinct from the Kattegat harbour seals (Olsen et al. 2014).

 

Methods to estimate nutritive condition

The nutritional status can be measured as;

1.      Blubber thickness at various points at the body

2.      Body length at age

3.      Different indices can be estimated from these parameters, often with the goal to estimate the percentage blubber of the total body mass.

Index of fat content (%) of total body mass (LMD-index)

All these measures must take into consideration the sex, age and season of collection, and the method of collection, before analysis.

 

Selection of appropriate data

In this step in developing the nutritional status indicator we will focus on grey seals, since there is much appropriate data available for this species, but other species will be included in the future. The data used is collected opportunistically from seals hunted for other purposes as well as by-caught seals in the fisheries.

The flux in blubber thickness is dependent on age and sex of the seal, where adult females are expected to show the greatest seasonal variation since they spend all their energy during lactation. However, also adult males spend much energy during reproduction, with substantial individual variation depending on size and rank of the male (Figure 2).​

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Figure 2. Decline in blubber thickness in Baltic ringed seals during spring. Data from the hunt (n=723) Olofsson 1930.

In this approach, a population segment that is least affected by reproductive activities is to be used, i.e. sub-adult seals of ages 1-3. In this segment energy intake is only used for metabolism, locomotion, somatic growth and storage of energy.  There is a seasonal flux in blubber thickness also in this segment (Figure 1), but much less pronounced than in adult seals. The age at sexual maturity is not a fixed parameter, and changes over time depending on fluctuations in e.g. food availability. An example of this is the Antarctic crabeater seals where a change from 3.7 to 6.3 years occurred within a couple of decades (Hårding and Härkönen 1995). However, the 1-3 year segment will still be comparable among years.

To be functional, an indicator must be sensitive enough to detect inter-annual variations, and be applicable in the entire area of distribution. Figure 3 shows that there has been a significant decrease in blubber thickness from 45 mm to 35 mm in seals hunted in the autumn in a 9-year long time series (2002-2009) of sub-adult grey seal. By-caught seals are leaner, but also display a similar trend, here blubber thickness decreased from 35 mm to 25 mm in this category of seals. Thus, both hunted and by-caught seals provide useful information on changes in nutritive condition. ​

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Figure 3. The mean annual blubber thickness ± SD in examined 1-3 years old non pregnant by-caught (1995-2009) and hunted (2002-2008) grey seals in Sweden and Finland. All were by-caught or shot between August and February (Bäcklin et al. 2013). Green line show GES at carrying capacity.​