BSEP116B Biodiversity in the Baltic Sea - Helcom

Figure 3.2.7. Left panel shows prediction of perch spawning habitats in the southern Quark area (by U.
Bergström, A. Sandström and G. Sundblad, in Dinesen et al. 2008). The right panel shows classes of marine
conservation values at Svenska Högarna, Stockholm Archipelago (Isæus et al. 2007). The map is constructed
from overlay analyses of eight layers of species and habitat distributions. Light green shows high conservation
values and dark green very high conservation values. Permission for reprinting the images has been
given by the Swedish Board of Fisheries and Stockholm Administrative County Board.
for example, the software MARXAN (Ball & Possingham
2000, see Chapter 7).
Along with the many advantages of maps produced
by spatial modelling, it is important to
acknowledge that for the production of reliable
maps it is crucial to have high-quality background
data. The quality and resolution of predictive maps
can never be better than the underlying data
layers. The first step for predictive spatial modelling
must, therefore, always be to assemble highquality
maps of the environmental factors that are
expected to explain the distribution of the species
or habitats of interest.
Quark to the Skagerrak. There are also examples of
modelled benthic species and habitats on Swedish
offshore banks in the Gulf of Bothnia and the
Bothnian Sea (SEPA 2008). In Latvia and Lithuania,
habitat modelling has been combined with the
EUNIS classification to produce national benthic
maps also including mussel-dominated habitats.
In Estonia, spatial modelling is used as a standard
technique for mapping the distribution of key
species and habitats in the inventories of marine
Natura 2000 sites (Martin et al. 2009). See also
Box 3.2.1 for an example of modelling changes
in Fucus vesiculosus distribution in the Askö area,
Stockholm archipelago.
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There are a number of successful examples of maps
of benthic seaweeds, plants, sessile animals, fish,
and habitats that have been produced using these
techniques. A table with references to a number
of habitat or species distribution models is given
in Annex IV of this report. The examples mainly
include detailed models at a local scale, but also
some overview modelling examples including the
whole Baltic Sea. Many of the studies were performed
within the BALANCE project and are found
in the BALANCE interim reports 11 (Bergström et
al. 2007), 21 (Dahl et al. 2007), 23 (Müller-Karulis
et al. 2007), and 27 (Dinesen et al. 2008). These
modelling examples are located from the southern
Several additional activities were completed
during 2008 or early 2009. In Sweden, detailed
maps of species distributions have been produced
for three pilot areas in the Bothnian
Bay, the Bothnian Sea, and the Baltic Proper. A
first attempt has also been made to model the
distribution of habitat-forming species on the
scale of the entire Baltic Sea within the project
MOPODECO, funded by the Nordic Council of
Ministers. Experience from this first application
of large-scale species modelling shows that the
results vary in quality owing to variations in the
abundance and quality of the input data.