Baltic Sea
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LME 23: Baltic Sea

Bordering countries:

Denmark, Estonia, Finland, Germany, Latvia, Lithuania, Poland, Russia, Sweden

LME total area:

396,838 km²

LME overall risk:

This LME falls in the cluster of LMEs that exhibit a significant influence of capacity-enhancing fisheries subsidies.
Based on a combined measure of the Human Development Index and the averaged indicators for fish & fisheries and pollution & ecosystem health modules, the overall risk factor is medium.

Productivity

Chlorophyll-A:

The annual Chlorophyll a concentration (CHL) cycle has a maximum peak (5.78 mg.m^-3) in July and a minimum (2.03 mg.m^-3) during February. The average CHL is 3.90 mg.m^-3. Maximum primary productivity (898 g.C.m^-2.y^-1) occurred during 2013 and minimum primary productivity (602 g.C.m^-2.y^-1) during 1998. There is a statistically insignificant increasing trend in Chlorophyll of 48.5 % from 2003 through 2013. The average primary productivity is 755 g.C.m^-2.y^-1, which places this LME in Group 5 of 5 categories (with 1 = lowest and 5= highest).

Primary productivity:

Sea Surface Temperature:

From 1957 to 2012, the Baltic Sea LME #23 has warmed by 0.93°C, thus belonging to Category 3 (fast warming LME). The Baltic Sea was the fastest warming LME in the World Ocean between 1982 and 2006 (delta SST = 1.35°C, according to Belkin, 2009). This extremely high warming rate was in a large part due to the extremely cold epoch of the late 1970s-1980s that began abruptly in 1976 and ended abruptly in 1989. After that, the temperature rise was rather modest. The absolute maximum SST (9.2°C) was reached in 2008, after which SST dropped by 1°C. The rapid warming of the Baltic Sea reported by Belkin (2009) is consistent with SST warming rates reported by Mackenzie and Schiedek (2007), who noted strong seasonality of the long-term warming: In the entire Baltic-North Sea region the temperature increase in summer is much higher (1.5°C) than in winter (0.3°C). The SST variations correlate with air temperature over the Baltic Sea, which increased by 2°C between 1870 and 2004 (HELCOM, 2007, Fig. 3).

Fish and Fisheries

In the Baltic Sea LME, cod (Gadus morhua), herring (Clupea harengus) and sprat (Strattus sprattus) dominate the fish community in terms of numbers and biomass.

Annual catch:

Total reported landings in this LME showed a steady increase from the 1950s to the 1980s. Since then, the catch declined slightly from the 1980s to the mid-1990s, and followed by a sharp increase to a peak with 980,000 t in 1997.

Catch value:

The value of the reported landings peaked in 1979, estimated at 1.4 billion US$ (in 2005 real US$).

Marine Trophic Index and Fishing-in-Balance index:

The MTI shows a significant decline from the mid-1980s to 2010 likely due to the increased sprat landings. However, as a notable decline in Atlantic cod landings is also evident, the decline in the mean trophic level constitutes a case of a "fishing down" of the local food web. The rapid decline in the FiB index also supports this interpretation.

Stock status:

The Stock-Catch Status Plots indicate that about 40% of the fished stocks in the LME have collapsed, but that the majority of the catch is supplied by fully exploited stocks, likely due to the large European sprat catch.

Catch from bottom impacting gear:

The percentage of catch from the bottom gear type to the total catch was around 8% in the 1950s and then started to decline in the early 1970s. In the recent decade, this percentage is lower than 2%.

Fishing effort:

The total effective effort continuously increased from around 100 million kW in the early 1950s to its peak at 500 million kW in the mid-2000s.

Primary Production Required:

The primary production required (PPR) to sustain the reported landings in this LME reached 25% of the observed primary production in the mid-1980s, but has declined to less than 10 % in recent years.

Catch potential projections (under global warming):

Pollution and Ecosystem Health

Pollution

Nutrient ratio, Nitrogen load and Merged Indicator:

Human activities in watersheds are affecting nutrients transported by rivers into LMEs. Large amounts of nutrients (in particular nitrogen load) entering coastal waters of LMEs can result in high biomass algal blooms, leading to hypoxic or anoxic conditions, increased turbidity and changes in community composition, among other effects. In addition, changes in the ratio of nutrients entering LMEs can result in dominance by algal species that have deleterious effects (toxic, clog gills of shellfish, etc.) on ecosystems and humans. An overall nutrient indicator (Merged Nutrient Indicator) based on 2 sub-indicators: Nitrogen Load and Nutrient Ratio (ratio of dissolved Silica to Nitrogen or Phosphorus - the Index of Coastal Eutrophication Potential or ICEP) was calculated.

Nitrogen load:

The Nitrogen Load risk level for contemporary (2000) conditions was moderate (level 3 of the five risk categories, where 1 = lowest risk; 5 = highest risk). Based on a “current trends” scenario (Global Orchestration), this remained the same in 2030 and 2050.

Nutrient ratio:

The Nutrient Ratio (ICEP) risk level for contemporary (2000) conditions was moderate (3). According to the Global Orchestration scenario, this remained the same in 2030 and 2050.

Merged nutrient indicator:

The risk level for the Merged Nutrient Indicator for contemporary (2000) conditions was moderate (3). According to the Global Orchestration scenario, this remained the same in 2030 and 2050.

POPs:

Only one sample from Helsinborg, Sweden, is available because another sample from the same beach was only white (fresh) pellets, which could underestimate the pollution status. PCB concentration (ng.g^-1 of pellets) in the analyzed sample was 405, corresponding to risk category 4 of the five risk categories (1 = lowest risk; 5 = highest risk), suggesting heavy impact by PCBs. DDT concentration was 10 ng.g^-1 (category 2) and HCH concentration was 0.5 (category 1). More locations should be sampled and analyzed for proper evaluation of this LME.

Plastic debris:

Modelled estimates of floating plastic abundance (items km^-2), for both micro-plastic (<4.75 mm) and macro-plastic (>4.75 mm), indicate that this LME is in the group with relatively high levels of plastic concentration. Estimates are based on three proxy sources of litter: shipping density, coastal population density and the level of urbanisation within major watersheds, with enhanced run-off. The high values are due to the relative importance of these sources in this LME. The abundance of floating plastic in this category is estimated to be on average over 100 times higher that those LMEs with lowest values. There is good evidence from sea-based direct observations and towed nets to support this conclusion.

Ecosystem Health

Mangrove and coral cover:

Not applicable

Reefs at risk:

Not applicable

Marine Protected Area change:

The Baltic Sea LME experienced an increase in MPA coverage from 2,913 km² prior to 1983 to 17,150 km² by 2014. This represents an increase of 488%, within the low category of the 5 categories of MPA change (low, lowest, medium, high, highest).

Cumulative Human Impact:

The Baltic Sea LME experiences an above average overall cumulative human impact (score 3.65; maximum LME score 5.22), which is also well above the LME with the least cumulative impact. It falls in risk category 3 of the five risk categories (1 = lowest risk; 5 = highest risk). This LME is most vulnerable to climate change. Of the 19 individual stressors, three connected to climate change have the highest average impact on the LME: UV radiation (0.39; maximum in other LMEs was 0.76), sea level rise (0.71, the highest value for any LME), and sea surface temperature (0.99; maximum in other LMEs was 2.16). Other key stressors include commercial shipping, nutrient and pesticide pollution from land, ocean based pollution, pelagic low-bycatch commercial fishing, and demersal non-destructive low- and high-bycatch commercial fishing.

Ocean Health Index:

The Baltic Sea LME scores above average on the Ocean Health Index compared to other LMEs (score 80 out of 100; range for other LMEs was 57 to 82) but still relatively low. This score indicates that the LME is below its optimal level of ocean health, although there are some aspects that are doing well. Its score in 2013 increased 1 point compared to the previous year, due in large part to changes in the scores for coastal livelihoods and clean waters. This LME scores lowest on mariculture and tourism & recreation goals and highest on artisanal fishing opportunities, coastal protection, coastal economies, lasting special places, and biodiversity goals. It falls in risk category 1 of the five risk categories, which is the lowest level of risk (1 = lowest risk; 5 = highest risk).

Socio-economics

Indicators of demographic trends, economic dependence on ecosystem services, human wellbeing and vulnerability to present-day extreme climate events and projected sea level rise, are assessed for this LME. To compare and rank LMEs, they were classified into five categories of risk (from 1 to 5, corresponding to lowest, low, medium, high and highest risk, respectively) based on the values of the individual indicators. In the case of economic revenues, the LMEs were grouped to 5 classes of revenues from lowest, low, medium, high and highest, as revenues did not translate to risk.

Population:

The coastal area stretches over 567 489 km². A current population of 34 273 thousand in 2010 is projected to decrease to 25 679 thousand in 2100, with a density of 60 persons per km² in 2010 decreasing to 45 per km² by 2100. About 29% of coastal population lives in rural areas, and is projected to decrease in share to 27% in 2100.

Coastal poor:

The indigent population makes up 11% of the LME’s coastal dwellers. This LME places in the very low-risk category based on percentage and in the high-risk category using absolute number of coastal poor (present day estimate).

Revenues and Spatial Wealth Distribution:

Fishing and tourism depend on ecosystem services provided by LMEs. This LME ranks in the low-revenue category in fishing revenues based on yearly average total ex-vessel price of US 2013 $236 million for the period 2001-2010. Fish protein accounts for 12% of the total animal protein consumption of the coastal population. Its yearly average tourism revenue for 2004-2013 of US 2013 $89 034 million places it in the very high-revenue category. On average, LME-based tourism income contributes 8% to the national GDPs of the LME coastal states. Spatial distribution of economic activity (e.g. spatial wealth distribution) measured by night-light and population distribution as coarse proxies can range from 0.0000 (totally equal distribution and lowest risk) to 1.0000 (concentrated in 1 place and most inequitable and highest risk). The Night Light Development Index (NLDI) thus indicates the level of spatial economic development, and that for this LME falls in the category with low risk.

Human Development Index:

Using the Human Development Index (HDI) that integrates measures of health, education and income, the present-day LME HDI belongs to the very high HDI and very low risk category. Based on an HDI of 0.866, this LME has an HDI Gap of 0.134, the difference between present and highest possible HDI (1.000). The HDI Gap measures an overall vulnerability to external events such as disease or extreme climate related events, due to less than perfect health, education, and income levels, and is independent of the harshness of and exposure to specific external shocks.
HDI values are projected to the year 2100 in the contexts of shared socioeconomic development pathways (SSPs). This LME is projected to assume a place in the very low risk category (very high HDI) in 2100 under a sustainable development pathway. Under a fragmented world scenario, the LME is estimated to place in a high-risk category (low HDI) because of reduced income levels and population values from those estimated in a sustainable development scenario.

Climate-Related Threat Indices:

The Climate-Related Threat Indices utilize the HDI Gaps for present-day and projected 2100 scenarios. The contemporary climate index accounts for deaths and property losses due to storms, flooding and extreme temperatures incurred by coastal states during a 20-year period from 1994 to 2013 as hazard measures, the 2010 coastal population as proxy for exposure, and the present day HDI Gap as vulnerability measure.
The Contemporary Threat Index incorporates a Dependence Factor based on the fish protein contribution to dietary animal protein, and on the mean contribution of LME tourism to the national GDPs of LME coastal states. The HDI Gap and the degree of dependence on LME ecosystem services define the vulnerability of a coastal population. It also includes the average of risk related to extreme climate events, and the risk based on the degrading system states of an LME (e.g. overexploited fisheries, pollution levels, decrease in coastal ecosystem areas).
The 2100 sea level rise threat indices, each computed for the sustainable world and fragmented world development pathways, use the maximum projected sea level rise at the highest level of warming of 8.5 W/m² in 2100 as hazard measure, development pathway-specific 2100 populations in the 10 m × 10 km coast as exposure metrics, and development pathway-specific 2100 HDI Gaps as vulnerability estimates.
Present day climate threat index of this LME is within the medium-risk (medium threat) category. The combined contemporaneous risk due to extreme climate events, degrading LME states and the level of vulnerability of the coastal population, is high. In a sustainable development scenario, the risk index from sea level rise in 2100 is very low, and increases to medium risk under a fragmented world development pathway.

Governance

Governance architecture:

The arrangements for pollution (both marine and land-based) and biodiversity in this LME – under the Helsinki Convention - appear to be well integrated. This Convention also has structural components that address fisheries and biodiversity and as such, provides an integrating mechanism for the LME at a level that is lacking in most LMEs. The extent to which HELCON has any formal linkages with NASCO and NAMMCO is not clear. It is also likely that ICES provides a common science advisory role within all of the arrangements.
The overall scores for ranking of risk were: