Interim report of the HELCOM CORESET project

42
termined by application of the 75th percentile on surface density models (e.g. GAMs and GLMs) based on
the transect data. Species should be selected based on data availability and accessible background information.
Knowledge on their biology, behaviour and seasonal rhythm as well as habitat dependency should
be available. Changes in species distribution have to be analysed with respect to habitat suitability and
anthropogenic pressures taking into account species-specifi c density thresholds, species-specifi c pressure
sensitivity as well as within- and between-species competition. Time series data may provide information
on reoccurring spatio-temporal patterns allowing for a differentiation between naturally driven variation
and pressure based changes.
Because of its tight linkage to waterbird abundance, this indicator should be used together with the indicator
Abundance of wintering populations of waterbirds.
For the time being focus shall be put on wintering seabirds. This pays tribute to the important role of the
Baltic Sea as wintering area and goes along with the proposed core indicator on wintering seabird abundances.
Being among the most abundant and ecologically dominating seabirds wintering in the Baltic Sea
the following four species are proposed for the appliance of the presented indicator: Common Eider, Velvet
Scoter, Common Scoter and Long-tailed Duck. Other species may be added. For the time being all species
should be analysed separately interpreting indicator results on the species level only. In the future, as
knowledge improves, the quantitative changes in distribution of several species may be integrated on the
level of functional groups.
Policy relevance
The proposed indicator applies to the MSFD GES criteria 1.1 “species distribution” and the parameters
“distributional range” (1.1.1) and “distributional pattern” (1.1.2) listed under descriptor 1.
The EC Birds Directive requires special conservation measures for seabird species to ensure their survival
and reproduction in their distribution areas. Measures specifi cally include classifying the most suitable territories
as Special Protection Areas. Consequently assessments are required to provide information on the
distribution of species for the designation of SPAs as well as ongoing monitoring schemes to detect changes
in distribution to adapt management and secure conservation of the target species.
The ecological objectives of the Baltic Sea Action Plan (BSAP) currently do not comprise targets and indicators
for wintering waterbirds or distribution of waterbirds in general. However, the biodiversity segment
of the BSAP includes the objective of natural landscapes and seascapes and the parameter “percentage of
important migration and wintering areas for birds within the Baltic Sea covered by the BSPAs, Natura 2000
and Emerald sites”. This implies knowledge on the distribution of seabird species.
Testing of the core indicator and examples from the literature
The proposed indicator has not been used as such in the past nor have there been - to the knowledge of
the authors - any attempts. However, seabird distribution and density measures have been used for the
identifi cation of Important Bird Areas and Special Protected Areas and are integral elements of environmental
impact assessments. The underlying studies have detected relations between seabird distribution
and anthropogenic activities.
Demonstrations of how the 75 percentile of density measures can provide a robust indication of changes
in main distribution areas of waterbirds can be found in the recently fi nished report of the SOWBAS (Status
of wintering waterbird populations in the Baltic Sea) project (Skov et al. 2011). SOWBAS was launched in
2006 and carried out co-ordinated surveys of waterbirds in all Baltic waters during 2007-2009. The project
attempted to fi ll gaps in knowledge of the status and recent trends in the populations of wintering
waterbirds in the Baltic Sea and provides a follow up of the fi rst Baltic wide survey on seabird distribution
in 1992-1993 (Durinck et al. 1994). Compared to the report covering the results from the fi rst census the