GIS tools were used to evaluate geographical data and identify suitable areas, fish
carrying capacity was calculated, mussel settling in the selected areas was estimated, and a public consultation process was carried out in both regions. Hence,
such a spatial planning process will be crucial for aquaculture development as it
lowers the threshold for new entrepreneurs, minimizes the risk of appeals, makes
the business more environmentally safe, and lowers the risk of social conflicts.
But, increasingly, aquaculture siting will be conducted in a broader, multiple-use
context where tradeoffs will be more complex. As stated by Lovatelli et al. (2014),
“meeting the future demand for food from aquaculture will largely depend on the
availability of space [and] ‘MSP’ is needed to ensure [that] allocation of space.”
Although a variety of GIS-based tools and DSS are currently available to assist in the
planning process, the allocation of space in the ocean remains a complex, contentious
process unlikely to be fully resolved by even the most sophisticated mathematical
calculations. Successful MSP, including the co-location of compatible activities,
relies as much on the willingness of relevant stakeholders to become involved as it
does on tools and techniques for identifying optimum areas (Gopnik 2015). The
integration of relevant actors is a “complex and controversial issue” (Buck et al.
2008) which depends on a multitude of factors, including inclusiveness, transparency
of the process and of decision-making, timing, credibility of the data and science, and
impartial mediation.
Despite these caveats, GIS-based DSS will continue to play an important role in
planning and spatial decision-making because of their ability to evaluate the results
of many different spatial scenarios. Ideally, this should include assessments of the
economic and socio-cultural impacts of different siting decisions, which can be the
main sources of conflict and are too often overlooked (ICES 2013). Socio-economic
data integrate publicly-held values into the decision-making processes. Primary data
on socio-cultural values—such as the importance people give to cultural identity
and the degree to which that is related to the ecosystem (de Groot et al. 2010)—are
usually not available. Surveys on secondary data as well as their spatial analysis still
remain complex tasks. In general, the spatial aggregation of socio-economic data in
a GIS framework is difficult, involving close collaboration with the respective
sectors (Ban et al. 2013). Most progress can be found with regard to the mapping of
fleet-specific fisheries activities due to technical advances in combining Vessel
Monitoring System (VMS) and logbook information (Bastardie et al. 2010; Lee
et al. 2010; Hintzen et al. 2012). Finally, GIS-based DSS should be flexible enough
to respond to shifting circumstances, such as changes in environmental conditions,
environmental targets, growth expectations in the aquaculture sector, or policy
environments. Like all analytical tools, GIS-based DSS are only as good as the
quality and thoroughness of the data they are based on, and their strengths and
limitations should be clearly explained to stakeholders during the planning process.
Acknowledgements The German Federal Office for Agriculture and Food (Bundesanstalt für
Landwirtschaft und Ernährung, BLE) supported the contribution of AG as part of the project
Offshore Site Selection (OSS) (313-06.01-28-1-73.010-10). Case study data were freely provided
by National Oceanographic and Atmospheric Administration (NOAA), Helmholtz-Zentrum
6 Aquaculture Site-Selection and Marine Spatial Planning …
143
carrying capacity was calculated, mussel settling in the selected areas was estimated, and a public consultation process was carried out in both regions. Hence,
such a spatial planning process will be crucial for aquaculture development as it
lowers the threshold for new entrepreneurs, minimizes the risk of appeals, makes
the business more environmentally safe, and lowers the risk of social conflicts.
But, increasingly, aquaculture siting will be conducted in a broader, multiple-use
context where tradeoffs will be more complex. As stated by Lovatelli et al. (2014),
“meeting the future demand for food from aquaculture will largely depend on the
availability of space [and] ‘MSP’ is needed to ensure [that] allocation of space.”
Although a variety of GIS-based tools and DSS are currently available to assist in the
planning process, the allocation of space in the ocean remains a complex, contentious
process unlikely to be fully resolved by even the most sophisticated mathematical
calculations. Successful MSP, including the co-location of compatible activities,
relies as much on the willingness of relevant stakeholders to become involved as it
does on tools and techniques for identifying optimum areas (Gopnik 2015). The
integration of relevant actors is a “complex and controversial issue” (Buck et al.
2008) which depends on a multitude of factors, including inclusiveness, transparency
of the process and of decision-making, timing, credibility of the data and science, and
impartial mediation.
Despite these caveats, GIS-based DSS will continue to play an important role in
planning and spatial decision-making because of their ability to evaluate the results
of many different spatial scenarios. Ideally, this should include assessments of the
economic and socio-cultural impacts of different siting decisions, which can be the
main sources of conflict and are too often overlooked (ICES 2013). Socio-economic
data integrate publicly-held values into the decision-making processes. Primary data
on socio-cultural values—such as the importance people give to cultural identity
and the degree to which that is related to the ecosystem (de Groot et al. 2010)—are
usually not available. Surveys on secondary data as well as their spatial analysis still
remain complex tasks. In general, the spatial aggregation of socio-economic data in
a GIS framework is difficult, involving close collaboration with the respective
sectors (Ban et al. 2013). Most progress can be found with regard to the mapping of
fleet-specific fisheries activities due to technical advances in combining Vessel
Monitoring System (VMS) and logbook information (Bastardie et al. 2010; Lee
et al. 2010; Hintzen et al. 2012). Finally, GIS-based DSS should be flexible enough
to respond to shifting circumstances, such as changes in environmental conditions,
environmental targets, growth expectations in the aquaculture sector, or policy
environments. Like all analytical tools, GIS-based DSS are only as good as the
quality and thoroughness of the data they are based on, and their strengths and
limitations should be clearly explained to stakeholders during the planning process.
Acknowledgements The German Federal Office for Agriculture and Food (Bundesanstalt für
Landwirtschaft und Ernährung, BLE) supported the contribution of AG as part of the project
Offshore Site Selection (OSS) (313-06.01-28-1-73.010-10). Case study data were freely provided
by National Oceanographic and Atmospheric Administration (NOAA), Helmholtz-Zentrum
6 Aquaculture Site-Selection and Marine Spatial Planning …
143