Deliverable 4.5
Final Set of Management Tools: Final set of management tools and recommendations
for improvements
Due date of deliverable: month 48 (October 2013)
Actual submission date: month 48 (October 2013)
Coordinator: Dr Katherine Cronin
Stichting Deltares
(Partner 16, Deltares, The Netherlands)
Contributors:
Katherine Cronin
Stichting Deltares
(Partner 16, Deltares, The Netherlands)
Myra van der Meulen
Stichting Deltares
(Partner 16, Deltares, The Netherlands)
Frank Keppel
Stichting Deltares
(Partner 16, Deltares, The Netherlands)
Asbjørn Christensen
Danmarks Tekniske Universitet
(Partner 12, DTU-AQUA, Denmark)
Tore Hogaasen
Norsk Institute for Vannforskning
(Partner 17, NIVA, Norway)
Dr Vanessa Stelzenmuller
Johann Heinrich von Thuenen-Institut,
Bundesforschungsintitut Fuer Landliche Raume,
Waldund Fischerei
(Partner 20, VTI, Germany)
Klaas Deneudt
Universiteit Gent
(Partner 4, UGent, Belgium)
3
1 INTRODUCTION 4
2 TOOLS FOR MESMA (MONITORING AND EVALUATION OF SPATIALLY MANAGED AREAS) 7 2.1 TOOL CATEGORIES 8
3 USE OF TOOLS IN THE CASE STUDIES 14 3.1 TOOLS USED IN THE CASE STUDIES 21
4 TOOLS DEVELOPED OR IMPROVED IN MESMA AND RECOMMENDATIONS FOR IMPROVEMENTS 23 4.1 E-MANUAL 23 4.2 BIOLOGICAL VALUATION 25 4.3 SPAM 26 4.4 UNCERTAINTY ANALYSES 28 4.5 CHASE 30
5 REFERENCES 32
1 INTRODUCTION
There is a huge range of what one might classify as tools that can be used in the various stages of marine
spatial management. The aim of the MESMA project (www.mesma.org) was to monitor and evaluate
spatially managed areas and for this tools and methodologies are required. The type of tools used
depends on whether a new plan is being developed, an existing plan is being reviewed and how much
monitoring of human activities and impacts is being undertaken. One may also want to evaluate whether
the current spatial management plan is achieving the stated ecological and/or socio-economic goals, such
as Good Environmental Status (GES). One of the objectives of MESMA was to gather a set of tools that can
be used to evaluate the effectiveness of a spatially managed area and the marine planning process from
the perspective of ecosystem-based management and in the context of climate change.
This document provides a brief overview of tools for the monitoring and evaluation of spatially
management areas. Many of these tools can be found on the MESMA central exchange
(http://www.mesmacentralexchange.eu/) (Figure 1). It also includes a brief description of MSP-specific
conceptual tools and guidelines.
Figure 1 MESMA central exchange
Different stages of the marine spatial planning process may be tackled with a range of tools. In itself,
marine spatial planning (MSP) is advocated as a promising tool to support the implementation of
ecosystem-based marine management (Stelzenmüller et al., 2012). Not all steps of such a planning
process require fundamental science. Thus the main scientific input is required for the initial assessment,
the development of spatial management scenarios and for plan performance assessment (Stelzenmüller
et al., 2012).
Any successful MSP initiative will employ a range of tools, techniques and methods to achieve each of the
above MSP stages. In the widest sense, tools for marine spatial planning can encompass a wide variety of
range and forms - conceptual, operational, analytical or technical. A tool may be a model, map, database,
legal/legislative requirements, permits, guidelines, a framework (Figure 2), criteria i.e. for indicators, a
5
GIS, a statistical software package and include governance tools such as stakeholder interaction and
participatory mapping and so on. The use of the proper tools is essential to reap the benefits of
improving data availability and quality.
Figure 2 MESMA framework
The development of a marine spatial plan is becoming easier with the increasing availability of new tools
and techniques (Douvere and Ehler, 2010). Geographic information science has provided the tools
needed to manage and analyse data. A major challenge is processing the available information in a way
that will aid management decision-making. Tools allow for the management and analysis of data and give
managers the ability to create alternative scenarios. Use should also be made of geodatabases (Figure 3)
to maintain spatial data in a consistent and accurate manner (Stamoulis, 2010; Essid and Sutton, 2012).
Recent advances in habitat-mapping technologies and numerical modelling (Katsanevakis et al., 2010)
have greatly enhanced the ability to describe marine ecosystems in detail.
Figure 3 MESMA geonetwork
Monitoring, evaluation, reporting and adaptive management are fundamental components for effective
marine management (Day, 2008). A spatial plan for an area can have multiple objectives and it is
important to evaluate whether the management measures outlined in the plan actually achieve the
desired results. An adaptive approach to marine spatial management can therefore help to identify more
effective measures. Therefore evaluation and monitoring of performance of the management plan is
essential (Douvere and Ehler, 2010). Interactive decision support systems, such as Marxan with Zones,
can create alternate spatial management scenarios, along with a clear evaluation of the tradeoffs
associated with it.
7
2 TOOLS FOR MESMA (MONITORING AND EVALUATION OF SPATIALLY
MANAGED AREAS)
Understanding and proper application of tools is essential for a smooth work flow in marine spatial
planning. There are a large variety of tools available to aid from the start to the end of the process. Tools
can very broadly be divided into two classes:
Those that aid with the implementation of ecosystem based management i.e. legal/institutional
tools and permits
Those that aid in the creation and/or evaluation of a marine spatial plan.
The type of tools listed in the MESMA inventory are mostly those of the second class. These tools can in
turn be categorised and applied at different stages of the MSP process. Legal and policy tools are
described in The Emerging Policy Landscape for Marine Spatial Planning in Europe: overview of key
policies, directives and regulations, and their interactions (Qiu and Jones, 2011).
At a higher level, tools can be broadly divided into technical and non-technical tools. Technical tools
comprise mostly software and programmes for modelling, mapping and other calculations. Non-technical
tools may consist of governance methods and incentives, guidelines and more conceptual tools. An
inventory of the different tool categories that can be used in MSP were gathered and are available on the
MESMA tool website (http://public.deltares.nl/display/MESMA/Home) and the MESMA central exchange
(http://www.mesmacentralexchange.eu/).
As well as organising the tools per category, tools are also organised into which analysis step they can
best be used within the MESMA framework. In this way a MESMA toolbox is available for users of the
framework (Figure 4). Some tools fit into several categories (Table 1 and Table 2 below).
Figure 4 MESMA analysis framework
2.1 Tool categories
o Data collection, processing and management tools: especially useful for large data sets
o Decision support: interactive computer-based information systems that support decision making
activities
o Communication: encompass a wide variety of tools/activities and are strongly linked with
governance approaches
o Participatory mapping and GIS tools: gathering of spatial information from a range of people and
mapping the result in some way
o Spatial analysis tools: commonly GIS based tools which are used to analyse and map marine
geospatial data and determine conflicts
o Visualisation and mapping tools: commonly GIS based tools that facilitate interpretation and
communication of environmental data
o Fisheries analysis tools: aiding in the analysis of fish populations and the evaluation of different
fisheries management strategies
o Numerical modeling tools: evaluate many marine processes important for MSP, both physical
and ecological
o Project management: generic tool used to optimize the process of managing a project
o Monitoring and impact assessment tools: used to study the current state of the ecosystem, and
predict possible changes as a result of (human induced) stress. An EIA assesses environmental
and socio-economic aspects of an action or project.
o Economics: helps to assess the impact of sectorial changes on goods and services
o Statistics: helps to calculate when and where conflicts may occur and summarise information
metrically which aids in decision making
o Conceptual tools and guidelines in MSP: abstract and presented in document form, this includes
documented methodologies to guide managers and scientists (i.e. UNESCO, etc.)
o Governance: include incentives and institutions that are combined in order to achieve long –term
and strategic conservation goals
A description of the most popular of the tools listed above are described in the next section. For a
description of each of the tools see http://publicwiki.deltares.nl/display/MESMA/Home and
http://www.mesmacentralexchange.eu/
Table 1 – Tool categories associated with different steps in the MESMA framework
FRAMEWORK
STEPS
Context Setting
(Step 1)
Existing information
collation and mapping
(Step 2)
Indicators
(Step 3)
Risk analysis and
state assessment
(Step 4)
Assessment of
findings against
operation objectives
(Step 5)
Evaluation of
Management
Effectiveness
(Step 6)
Adaptation to current
management (Step 7)
TOOL TYPE
Visualisation and
Mapping
X X X
Data Collection,
Processing &
Management
X X X
Decision Support X X X
Spatial Analysis X X
Statistical X
Conceptual
tools/guidelines
X X X
Participatory Mapping
and GIS
X
Uncertainty analysis X X X X X X X
Monitoring and
Assessment
X X
Fisheries Analysis X
Numerical Modelling X
Project Management X X X X X X X
Communication X
Socio-Economics X
Tool Category Visualisation
& Mapping
Data
Collection,
Processing
&
Management
Decision
Support
Spatial
Analysis
Statistical Participatory
mapping &
GIS
Monitoring
and Impact
Assessment
Fisheries
Analysis
Numerical
Modelling
Communication Socio-
Economics
Tool
Morpho x
Eonfusion x x
Habitat Digitizer Extension x
Kepler x
Benthic Terrain Modeller x x
Ecosystem Assessment and
Reporting Tool
x x x
MGET - Marine Geospatial Ecology
Tools
x x x x x x x
Marine Map x x x x x x x
CTAM - Coastal Transects Analysis
Model
x x x x x x
C-PLAN x x x
Netica x
SimCoast x x
Habitat Priority Planner x x x x
Marxan with Zones, and Zonae
Cogito
x x x x
ARIES - Artificial Intelligence for
Ecosystem Services
x x x
Expert Choice x x
AHP-OWA x x x
11
Tool Category Visualisation
& Mapping
Data
Collection,
Processing
&
Management
Decision
Support
Spatial
Analysis
Statistical Participatory
mapping &
GIS
Monitoring
and Impact
Assessment
Fisheries
Analysis
Numerical
Modelling
Communication Socio-
Economics
HIPRE x
LINK x x
MIDAS x x x x
MIMES x x x x
PAT x x
IAN (Integration and Application
Network)
x x
Open OceanMap x
E-Participation x x
Habitat Modelling Toolbox x x
SPAM (Sandeel Population
Analysis Model)
x x
Biomapper x x x
IBMlib x x x x
Fishery Analyst x x x x
Connectivity Analysis Toolkit x x
AHP in ArcGIS x x
EASy Mapping Solutions for Marine
Resources
x x
NatureServe Vista x x
SDM (Spatial Data Modeler) x x
NAMEM (Network Analyst for
Marine Ecosystem-based
management)
x
Tool Category Visualisation
& Mapping
Data
Collection,
Processing
&
Management
Decision
Support
Spatial
Analysis
Statistical Participatory
mapping &
GIS
Monitoring
and Impact
Assessment
Fisheries
Analysis
Numerical
Modelling
Communication Socio-
Economics
PANDA (Protected Areas Network
Design Application for ArcGIS)
x x
DIVA (Dynamic Interactive
Vulnerability Assessment)
x x x x
PATHMATRIX x x
WeMO x x
GADGET x x
ISIS-FISH x x
Marine Reserve and Local
Fisheries Interactive Simulation
x
EcoGIS x x x x
Multi-species Virtual Population
Analysis
x x
Atlantis x x x
GARP x
EcoWin 2000 x
ERSEM (the European Regional
Ecosystems Model)
x
Fisheries Libraries in R x x x
Hyper Niche x x
EcoPath x
Hydata Sonobuoy x
SAM v4.0 - Spatial analysis in
macroecology
x x x
13
Tool Category Visualisation
& Mapping
Data
Collection,
Processing
&
Management
Decision
Support
Spatial
Analysis
Statistical Participatory
mapping &
GIS
Monitoring
and Impact
Assessment
Fisheries
Analysis
Numerical
Modelling
Communication Socio-
Economics
CLUZ Conservation Land-Use
Zoning Software
EcoSeed x
ArcMarine x x x
MIRADI x x
Zonation x x
GRID (from Co-Exist) x x x
Biological Valuation Method x x x
BEQI x x x
Sustainability Indicator Tool x x x x
Table 2 A list of tools associated with different categories
3 USE OF TOOLS IN THE CASE STUDIES
Within MESMA, nine case studies were selected to test the MESMA analysis and governance frameworks.
These case studies reflected a large diversity of spatial scales, context, level of spatial management
implementation and operational objectives.
The type of tool needed by each of the nine case studies within MESMA depended very much on the
management questions being addressed. The use of the framework ranged from the observation of a
process, either analytically or not, to the development and evaluation of spatially managed scenarios
using spatial and temporal resolved data.
1. The Southern North Sea Case Study was the largest MESMA case study. It included nine MESMA
partners from five countries (Denmark, Germany, Netherlands, Belgium and part of the United Kingdom).
The case study area is very complex with is a high variety of biotopes, human activities and regulations.
Different countries were involved all with their own regulations. The shallow southern North Sea is a
highly productive sea because of the input of nutrients from the Atlantic, the Channel and several large
rivers. Fisheries is an important economic sector, but other activities in the area include shipping and
mineral extraction (sand, gas and oil mining). Wind farms and marine protected areas cover increasing
areas of the sea. All these activities compete for space, common resource or lead to changes in functions
in such a way that their value for others decrease. Four subareas (Wadden Sea, Belgium EEZ, Dogger Bank
and Skagerrak) were selected so an in depth analysis could be performed. The results are integrated to
draw conclusions at the higher Southern North Sea scale again. This so called ‘nested approach’ ensures
detailed insights in the spatial management process (Figure 5).
15
Figure 5 North Sea case study with nested sub-case studies
2. The Pentland Firth and Orkney Waters case study is located to the far north of Scotland. One unique feature of the Orkney biotopes is the diversity and close proximity of many different marine habitats, from exposed wave swept inter-tidal zones, to areas of deep mud, from tidal rapids to maerl beds and saline lagoons. The area is especially noted for its seabird populations, marine mammals, organisms endemic to high energy marine environments and organisms at the southern or northern limits of their distribution. The most well established activities are shipping and fishing but the most important issue for marine planning is the emerging wave and tidal energy industry (see figure) with the potential to occupy large areas of marine space. The preparation of a non-statutory pilot Marine Spatial Plan is underway by Marine Scotland which will be succeeded by statutory plans drawn up in accordance with the provisions of the recent Marine (Scotland) Act 2010.The aim of this case study was to analyse and critique the process of the Pentland Firth and Orkney Waters pilot MSP as it is developed. A principal objective of the plan, and of government policy, is to facilitate the development of marine renewable energy and the study will focus on work to anticipate the as yet unknown impacts of these new activities and their conflicts with existing uses and users.
3. The Barents Sea is Europe’s last large, clean, and intact marine ecosystem. It is home to the world’s
largest cod and herring stocks (during their juvenile stage), numerous species of whales and seals, some
of the largest bird colonies in Europe (including puffin and cormorant) and the world’s biggest cold-water
coral reef. But is also a region with rapid industrial development. Increasing human activities such as oil
and gas exploration, shipping and aquaculture add to the impacts from fisheries, climate change and
increasing levels of toxic chemicals. They pose serious threats to the marine ecosystem and biodiversity.
In 2006 the Barents Sea Management Plan
was launched. This plan aims at sustainable
use of the ecosystem, within acceptable
levels of pollution, with reduced risk of
accidental spills, with sufficient capacity and
readiness to deal with accidents, and seafood
that is safe for consumption, while
safeguarding biodiversity. The plan provides
an overall framework for managing all human
activities (oil and gas industry, fishing and
shipping) in the area. This case study
assessed experiences from the development,
implementation and revision of the Barents
Sea Management Plan as valuable input to
MESMA. These experiences can facilitate
development of practical tools for sustainable
development in European seas through use
of spatial managed areas. MESMA can
provide valuable input to the next revision of
the Barents Sea Management Plan in 2015.
4. The Celtic Sea provides important habitats for a
number of bird and marine mammal species, as well as
other coastal and marine organisms. The wide variations
in coastal geography cause a large range of habitats, like
kelp forests, sea grass beds and cold-water corals. The
large range of habitats support a diverse fish fauna such as
herring and mackerel. In the Celtic Sea there is increasing
competition for ocean space. Initiatives have been started
to designate marine protected areas. There are also two
wind farms being planned. Fishermen feel that they are
increasingly being displaced from fishing grounds, due to
the allocation of ocean space for nature conservation and
offshore renewable energy development. This and other
developments create growing conflicts between the
different sectors that use the Celtic Sea. In this case study
several on-going initiatives were analysed and the
conflicts, challenges and good practices of marine spatial
management that emerged from these initiatives
assessed. This provided important information for the
MESMA framework, particularly in evaluating the key
governance/institutional issues that affect the
management effectiveness of spatial management.
5. The Basque continental shelf is located in the south eastern part of the Bay of Biscay, in the border
between France and Spain. This case study is considered representative of the eastern Atlantic area of the
MESMA study area. The area shows some specific characteristics in terms of biodiversity and marine
resources, but it also shares common human activities with other European regions. The Basque
continental shelf is small in extent but human activity is intense and diverse. It is characterised by holding
some specific (or nearly specific) economic activities such as red seaweed extraction Gelidium corneum.
17
Moreover, new activities are foreseen to develop such as wave energy converter installation which may
involve conflicting interests. At present there is not a spatial planning/management in place. Most of the
policy/regulations are sectoral, or at least, they just take into account one activity and in most cases there
is not spatial boundary definition for these regulations. The main problems that could be highlighted are
the different governance issues at local, regional and international level. And the lack of coordination and
iteration between different stakeholders, uses and interests in the marine environment.
6. The Strait of Sicily is located between Sicily and Tunisia and has a high primary productivity with high
values of biodiversity due to the moderate depths, singular hydrography and the variety of habitat types.
Prominent features include deep coral assemblages, cold seep communities, rare or endemic species
(such as Maltese ray), high habitat heterogeneity, spawning and nursery grounds for several fish (i.e.
bluefin tuna and sword fish), persistent hotspots of diversity of demersal species, and large fluxes of
Atlantic and Indo-Pacific exotic species. Most important human uses of the area are fishing, aquaculture,
conservation, shipping and tourism. Other important uses are oil drilling and extraction, deployment of
gas pipelines and communication cables, and construction of wind-mill farms. Currently there is no
integrated spatial management plan in the area. This case study assessed the potential for the
implementation of a spatial management plan in the Strait of Sicily in order to minimize conflicts between
users. The main objectives were firstly to ensure and organize stakeholder participation and secondly, to
ensure protection of fragile and important areas by managing their uses, and to pressure ecosystem
functions and services.
Pelagic fisheries activity
distribution in the Bay of Biscay
7. The Inner Ionian Archipelago and Adjacent
Gulfs is host to a great variety of habitats and
species included in the Annexes of the EU
Habitat Directive, such as Posidonia
oceanica meadows (priority habitat), reefs,
monk seals (the most endangered marine
species in the Mediterranean), nesting sites of
loggerhead sea turtle, bottle-nosed dolphins,
fan mussels, date mussels and other
endangered species as the common dolphin
and sperm whales, included in the protocols of
Barcelona Convention.
Diverse human activities, mainly fisheries, shipping, industry, tourism and aquaculture, occur both along
the coast of the study area and in offshore waters. Conflicts of interest exist among the aforementioned
sectors, and between some human activities and specific nature conservation goals. Moreover, the study
area is characterized by strong seismic and faulting activity, which is the triggering factor for various
geohazards threatening the coastal zones. The above highlight the need for a comprehensive spatial plan,
as compared to the fragmented institutional management currently in action, focusing either on the
operation of certain sectors, or on conserving specific MPAs and Natura zones. One of the major tasks of
this case study was the creation of detailed, complete maps of the marine area, identifying where and
how it is used, and what protected species and habitats exist within it. The study also focussed on the
identification of factors driving specific patterns of use, and how existing uses are related to existing
policies. Innovative tools (ie. Marxan) were used to find a range of near optimal systems of protected
areas that meet conservation targets while attempting to minimize socio-economic costs. The ultimate
goal being to provide recommendations aiming to sustainable use of the marine environment,
contributing thus to achieving Good Environmental Status in the context of the MSFD.
The different boundaries defined in
conservation and fisheries
management plans in the Strait of
Sicily Area
19
8. The Black Sea is bordered by Bulgaria,
Georgia, Romania, Russia, Turkey and
Ukraine. Inflow water from the large river
systems coupled with limited outflow have
led to the Black Sea being nutrient rich and
highly productive. Common interests and
potential conflicts are present in the Black
Sea region in nature protection and
restoration, fisheries, regional industrial
activities and accompanying pollution
impacts, including oil development and
production, development of transport
infrastructure, including projects for regular
maritime links between the ports of
bordering states. Minor pressures exist from
tourism and sand mining. It is important to
balance the different economic, social and
ecological interests in the area. However,
cooperation efforts are often hindered by a
number of factors such as uneven economic
and political development within and among
countries and nationalist forces. This case
study focussed on environmental
improvement and cross border issues
related to marine spatial planning.
Important topics are. The links between
economic, social and ecological marine
spatial planning processes are described ad
analysed with the aim of provide practical input for the development of a long term strategy towards
evaluation and monitoring of marine spatial planning in the Black Sea, both national and regional.
9. The Baltic Sea is a marine area with brackish water. Due to this unique mix of marine and freshwater
species adapted to the brackish conditions, as well as a few true brackish-water species are present in this
ecosystem. Species that can be found in the area are e.g. bladderwrack (see figure below), blue mussels,
cod, herring, perch, pike, white tailed eagle and seals. The Baltic Sea case study is nested with the Helsinki
Commission Baltic Sea Action Plan (HELCOM BSAP) at the higher level and the coastal areas of Puck Bay in
Poland and Östergötland county in Sweden at the lower level. The HELCOM BSAP is an ambitious
programme to restore the good ecological status of the Baltic marine environment by 2021. The plan aims
to be fully in line with the Marine Strategy Framework Directive (MSFD) and all countries around the
Baltic Sea have developed or are developing National Implementation Plans (NIPs) in which they apply
national instruments for the implementation of the BSAP. In this case study the applicability of the
MESMA framework on the transnational, non-binding HELCOM BSAP will be evaluated as well as on the
local level of Puck Bay and Östergötland County.
Map of fairways, anchorage areas,
areas forbidden for shipping, dump
sites for dredged material disposal,
gas pipelines, cables, military zones
for the Bulgarian marine area
A number of tools that were used in the MESMA case studies are presented here. Some were developed
within MESMA and others are popular tools used for monitoring and evaluating spatially managed areas
worldwide or more general tools used in different fields. In summary, the nature of the management
issues varied throughout the case studies and depended on the operational objective of the analysis in
question.
Case Study Management objective
Belgium EEZ The designation and evolution of MPAs in the wider Belgium part of the North Sea
Dogger Bank To restore and maintain the natural features on the Dogger Bank to a favourable condition
Wadden Sea To restore and maintain the natural features represented in the SACs and SPAs in the
Wadden Sea
Skaggerak To restore and maintain the harbour porpoise conservation features represented in the SAC
Barents Sea Protection of the VVAs and species management
Bay of Biscay To develop an ocean infrastructure for research, demonstration and operation of offshore
wave energy harnessing devices and minimise impacts on fisheries
Celtic Sea To design a network of marine conservation zones in SW England, taking into account socio-
economic impacts
Pentland Firth To facilitate the generation of 1.6GW of wave and tidal energy from the PFOW area by 2020
and complementary environmental and social objectives
Strait of Sicily
(Sicily)
Maintaining or restoration to favourable conservation status of conservation features
Strait of Sicily
(Malta)
Maintaining or restoration to favourable conservation status of conservation features
Inner Ionian
Strait
To designate a representative network that fulfils sufficiency requirements and effectively
protect sites so they are maintained or restored.
Baltic Sea/Puck
Bay
Maintenance or restoration of favourable conservation status of conservation features in
the Natura2000 sites
Black Sea Maintenance or restoration of favourable conservation status of conservation features in
the Natura2000 sites
Tools that were used and evaluated within MESMA by the case studies include:
Tools for monitoring and evaluating spatially managed areas:
1. Biological Valuation Tool
2. CHASE
3. Marxan
4. Medium Scale Commercial Fisheries Effort (MeSCoFE)
21
5. SeaTrim
6. Small Scale Coastal Fisheries Pressure (SmaSCoFiP)
7. SPAM
8. VMSBase
And more generally applicable tools including:
1. ArcGIS and ArcGIS with the spatial analyst extension
2. Pedigree Matrix
3. Semi-structured interviews
4. Walker Matrix
The central tool used by all the MESMA case studies was the flexible and generic assessment framework
developed through the project (Stelzenmüller et al., 2010), which facilitates the linkage between the
structured assessment, governance analysis, required tools and geodata infrastructure. This framework
tool was in turn developed into an online database through which case studies or other users of the
MESMA framework can step through electronically (http://mesma.ucc.ie/emanual/).
The use of the framework ranged from the observation of a process, either analytically or not, to the
development and evaluation of spatially managed scenarios using spatial and temporal resolved data
(Stelzenmüller et al., 2013). Those case studies that mainly observed the processes in place (Östergötland
[Baltic Sea], Pentland Firth, Puck Bay [Baltic Sea], Southern North Sea) did not extensively use tools as the
majority of the work was based on desk study analysis. Most of the case studies that were more involved
in the actual evaluation and development of spatial managed scenarios applied a variety of tools (Ionian
archipelago, Strait of Sicily, Basque), although certain sub case studies of the ‘observing’ case study of the
Southern North Sea, such as the Dogger Bank and Skagerrak sub case studies did also apply some tools.
Marxan and the Biological Valuation Tool were the two most popular tools used in the case studies. The
use of both tools was stimulated by the organization of two tool workshops by the Institute of Marine
Research in Norway (IMR) for Marxan and the University of Gent for the Biological Valuation Tool (see
Cronin et al., 2013a for a description of the workshops). Many of the other tools were used by individual
case studies and often the institute involved in the case studies were also involved in the development of
the tool i.e. SPAM, SSCFP, MSCFE, CHASE (HELCOM).
3.1 Evaluation of tools used in the Case Studies
The tools used by the different case studies were evaluated within the MESMA project by members of
each case study, based on a set list of pre-defined criteria in order to capture the main attributes of each
tool. These criteria had to be flexible enough to be applicable to a wide range of different tools, from
governance tools to the more technical tools. Table 3 gives an overview of the tools that were evaluated
and a summary of the outcomes. For each of the tools indicated in Table 3 more detailed information for
each criterion is given in Cronin et al., 2013b.
Table 3 Tool assessment undertaken in MESMA. Blank white cells represent an unknown field or not applicable, a represents a yes per case study. Multiple ticks are present when more
than one case study evaluated the tool and a indicates a data dependent answer
Accurate Relevant
to
question
posed
Well
validated
Trans-
parent?
Generic Well
docu-
mented
Used
with
other
tools
Can it be
modified
Can it be
expanded
Require
certain
skills
Require
certain
operating
system
Require
special
libraries
Accept
standard
data
formats
Do what
was
expected
in the
case study
Semi-
structured
interviews
Walker
Matrix
Pedigree
Matrix
Marxan
Biological
Valuation
Tool
SeaTrim ArcGIS VMSbase
SmaSCoFiP
MeSCoFE ArcGIS with
spatial
analyst
SPAM SLAM Chase
4 TOOLS DEVELOPED OR IMPROVED IN MESMA AND
RECOMMENDATIONS FOR IMPROVEMENTS
A number of tools are being developed or expanded through MESMA (Table 4), based on the
requirements identified by the case studies. Some have been identified by the case studies as necessary
for the evaluation and monitoring of a marine spatial plan in their study area. Others are more generic
and can be applied case-study wide. A description of these tools is provided in Cronin et al., 2012b.
Tool Name Institute Contact Person Existed
previously
E-Manual Deltares and CMRC Katherine Cronin No
SPAM DTU Aqua Thomas Kirk Sørensen Yes
Biological Valuation
Methodology
University of Gent Jan Van Yes
BEQI VLIz Kris Hostens Yes
Scenario analysis tools HWU Kate Johnson Yes
CHASE Tool NIVA Tore Hogaasen Yes
Methodological
guidelines for
governance analysis
University College
London
Peter Jones No
Sustainability Indicator
Tool
Senckenberg Sandra Voege No
Table 4 Tools developed through MESMA
4.1 E-manual
The E-MANUAL is a prototype tool that was developed as an electronic version of the analysis framework
(Stelzenmüller et al., 2010) by Deltares in the Netherlands and CMRC in Ireland. This enables a user to
step through the analysis framework electronically and on the web rather than in a static document. It
also aids ease of use by storing fields in a database and filling them in automatically in other tables. This
tool is part of the final MESMA product for marine spatial managers and scientists involved in the
evaluation and monitoring of spatially managed areas and is available at (http://mesma.ucc.ie/emanual/)
and through the MESMA Central Exchange.
The entire WP2 framework has been implemented in a PostGreSQL database, an open-source, object-
relational database system that runs on all operating systems, so that entries are connected and
recorded. An electronic version of the analysis framework was deemed necessary as many pieces of
information are duplicated and filling in the tables is labour intensive (Figure 6). With an electronic
version, parameters such as ecosystem components and pressures can be selected from predefined lists,
thus also improving consistency and reducing errors. It also allows for ease of update and allows multiple
entries to be compared.
Each framework ‘run’ will have a unique ID. Data can be entered for specific steps and incomplete records
recalled from the database at any time for editing. The database can also hold multiple runs for any case
study (each with a different ID).
For each step in the E-manual there is an explanation text mirrored from the paper version and additional
instructions where required. The E-manual has been developed as a three tier web application. The first
tier or client tier is simply the Web browser in use by the end user (Figure X). The second tier is a Java
application server running the E-manual application developed using Wavemaker. The third tier is the
data storage, which is implemented using PostgreSQL RDBMS. To support the E-manual development
process, executed by CMRC (Ireland) and Deltares (The Netherlands), Subversion version control system
and a JIRA issue management system were set-up.
Once users are satisfied with their framework, the contents of the table can be exported into a document
for free editing, to create a run report.
Current the E-manual is a prototype tool with much potential. It is planned that additional features are
added after the end of the project (October 2013). Such features include:
Password protection of analyses
Version control to allow multiple users to contribute to one case study simultaneously
Figure 6 MESMA e-manual of analysis framework
25
4.2 Biological Valuation
MSP projects often cover a wide area and it can be difficult to obtain consistent datasets across the area
of interest, particularly for ecological and human use data. Biological valuation can be a method to
standardise different ecological datasets if consistent dataset is not available. Defining and analyzing the
existing ecological, environmental and oceanographic conditions for a specific study area is put forward
by Ehler and Douvere, (2009) as one of the essential steps toward ecosystem-based management.
Biological valuation maps compile all available biological and ecological information for a study area and
allocates an overall biological value to subzones, which can be used as baseline maps for future spatial
(Derous et al., 2007). These methods (biological valuation etc.) can serve as inputs into the growing range
of analytical tools that aid reserve design (e.g. Marxan, C-plan) and other methods that allow forecasts of
fishery responses to reserves (Ecopath and Ecospace) (Leathwick et al., 2008).
This need led to a marine biological valuation protocol that provides a framework for producing maps on
biological value of marine areas in a transparent, generally applicable and scientifically acceptable way
(Derous et al., 2008a). It aims at assessing two valuation criteria for the different organizational levels of
biodiversity within an area. To assess these criteria the protocol uses assessment questions to produce
assessment values for each of the subzones of that area. Several ecosystem components can be included
in the valuation. The concept was applied for the first time on the Belgian part of the North Sea in 2008
(Derous et al., 2008). A number of successful case studies have been carried out, more recently the
Basque continental shelf (Bay of Biscay) by Pascual et al. (2011) and the Belgian coastal zone by Vanden
Eede (2013, in prep.).
The method was further enhanced by the development of a computational tool to assist in the application
of the BVM methodology. A publicly available computational tool was developed and published on
MESMA tool wiki (https://publicwiki.deltares.nl/display/MESMA/TOOLS). The R scripts that make part of
this tool can be downloaded from the site and run from the user’s computer desktop using the freely
available R software available at http://www.r-project.org. The applicability of the tool and validation of
the method was testing during the marine biological valuation training course that was organized in the
framework of the MARES and MESMA EU projects in April 2012. During this workshop a prototype version
of the R-scripts was presented to twenty-two participants with different levels of background in
computing, GIS and R. Teaching the script to candidate users gave insight in the ease of use and
difficulties of the prototype version.
One of the main strengths of the tool is that it makes the biological valuation procedure a lot easier and
straightforward. The user can perform the entire procedure within the same environment, without the
need of transferring data or intermediate results from one software package to another. By choosing the
R language for coding the procedure, the software environment for running the tool is freely available.
Providing the procedure as a script allows for automation of the individual calculation steps, making it
possible to calculate a biological valuation map in a timeframe of hours or days. In addition, if the data is
stored in a structured way updates of biological valuation maps can be produced on a regular basis. This
timing clearly aligns better with the needs of policy makers who often need to make informed decisions
within a short period of time.
A limitation of the tool is that it only works with the available data. Therefore results might be produced
that could be contested by expert knowledge. This might be caused by insufficient data coverage or by
lack of data for certain ecosystem components. On the other hand, expert judgment might also be biased.
Another potential weakness of the tool and the way it was developed is the fact that it uses a number of R
packages and the available higher level functions within these packages. Nor the R software itself, nor any
of the installed packages can give full guarantee on compatibility with previous versions. However, the
working versions are documented and these versions will always be available for installation in the R
archives.
In short, the tool is freely accessible, fully documented and invites people to use, adapt and elaborate
upon in accordance with their own view on the optimal procedure for their data and study area (Figure 7).
Figure 7 Example of biological valuation maps of macrobenthos of the Belgian Part of the North Sea per
assessment question solved and final macrobenthos biological valuation map (based on Macrobel dataset)
4.3 SPAM
SPAM (Sandeel Population Analysis Model) was originally developed in 2007 to explore the possibility to
create short term high resolution fish stock forecasts for sedentary species (Figure 8). Since then the
model was developed further with added capabilities to support marine spatial planning, e.g. assess stock
impact scenarios (e.g. wind mills or MPAs (Christensen et al., 2009)) and alternative stock management
scenarios as well as future climate simulations, based on input from predicted future physical forcing
(Christensen et al., 2013). The incentive for focusing on a single species (presently sandeel) is that
biological interactions cannot be parameterized at this time with sufficiently certainty to support realistic
multistock models for marine ecosystems. The chances are bigger to build quasi-realistic single stock
models for stocks which can be considered indicative for ecosystem status.
The current major features of SPAM are:
High resolution (10 km) resolution of North Sea sandeel biomass dynamics based on a life cycle model
27
Stock recruitment computed spatially resolved from underlying physical and biological processes (Christensen et al., 2008)
Includes stock-density self-regulation effects
Includes multispecies interaction (predation pressure) and fishery effort as external drivers
Based on the previous work and experience with the model the following issues are identified as highly
important to expand/improve the SPAM model to provide cutting edge scientific decision support:
To implement higher temporal representation of intra annual processes, e.g. stock catch dynamics
Currently primitive schemes for data assimilation of catch and regional scale stock assessment are available; it would be desired to improve data assimilation methodologies
To include zooplankton variability coupling (larval survival and adult growth)
Currently fishery effort are supplied as and external driver (user set parameter). To achieve realistic scenario models it would be desired to make modelling of fishery effort reallocation more advanced, in response to fishing restrictions.
The model currently exists as a set of Python classes, which are applied from scripts reflecting whatever
one wishes to do with the model, e.g. run an alternative stock management scenario. These scripts setup
and run the model, and extracts whatever information is needed about the stock dynamics, and easily
connects to whatever plotting tools the user prefers, e.g. Matlab. The scripts are typically spawned from a
template and invoked from a command prompt, giving a high degree of functional flexibility.
The SPAM model was recently applied to assess the ecological consequences alternative N2000
designations (Goldsborough et al., 2013) by David Goldsborough, Thomas Kirk Sørensen and Asbjørn
Christensen. This case study tested and compared three proposed scenarios developed by members of
the North Sea Regional Advisory Council (NSRAC), and the effect of closing the whole Natura 2000 site.
The simulations were run with two options: without and with reallocation of displaced fishing effort.
Results show that the effect of all three scenarios without reallocation of fishing effort on the biomass of
sandeel is positive with up to approx. 3% increase in sandeel abundance on a North Sea scale. The NGOs’
proposal, which emphasises connectivity between areas, produces a biomass increase that is more than
twice that of the fishing sector’s scenario.
Currently a GUI (graphical user interface) is not available with the model. However, the screen shot shows
the typical usage of the SPAM model: the model application script in a text editor, the command prompt
where the script and data post processing are invoked ad hoc graphical plots invoked from the script,
displaying various aspects of the stock dynamics.
Figure 8 Examples of the SPAM model use
4.4 Uncertainty Analyses
The WP2 framework (Stelzenmüller et al., 2010) contains several structured steps and action points from
the scoping, gathering of data, analysis and extraction of recommendations for decision makers in marine
planning. Thus this technical ‘tool’ supports policy making. In this work, the typology of the uncertainties
at each step is mapped following the good practice described in Walker et al (2003) or van der Sluijs et al
(2004). At this workshop we aimed to move from a qualitative description of the typology of uncertainty
to the application of a pedigree matrix for most case studies.
The objectives of this workshop were to:
Further development of methods to characterize and quantify uncertainty of the MESMA framework
application outputs,
Develop a MESMA specific pedigree matrix
Scope for the development of tools and methods for uncertainty analysis and communication
Communication of uncertainty assessment (who will use this information and what does it mean for
the use of the assessment outputs)
Integration of uncertainty assessment in the e-manual
The aim of this methodological development was to characterise and quantify the uncertainty, emerging
also through structure and design of the framework. Therefore standardised tools were developed and
tested by the case studies.
29
When analysing uncertainty, the type and location of uncertainty should be identified first (see level 1 and
level 2 in Figure 9). To identify where uncertainties lie and communicate their presence to decision
makers, an uncertainty matrix was proposed by (Walker et al. 2003). This matrix enables a systematic
overview of the main features of uncertainty. Walker et al. (2003) distinguished three dimensions of
uncertainty: (i) location, (ii) level (i.e. range between deterministic knowledge and total ignorance), and
(iii) nature (i.e. whether it is due to imperfect knowledge or inherent system variability). The uncertainty
matrix developed by (Walker et al. 2003) was modified to represent the types of uncertainties
encountered when applying the framework for monitoring and evaluation of spatially managed areas
(Stelzenmüller et al. 2013).
Each case study described uncertainty associated with each action of the framework by eight descriptors
which characterised the uncertainty along the three dimensions (Walker at al. 2003). For each action the
variables that best described the uncertainty were given a score of 1 (presence), while those describing
uncertainty that was either absent or irrelevant for the purposes of the framework were scored as zero
(absence). For more details on how the analysis was performed and the results visualized see
Stelzenmüller et al., (2013).
After having characterised and explored the observed pattern of uncertainties within each step of the
assessment framework the next step was to describe and quantify uncertainty. Semi-quantitative
assessments of uncertainty as it is provided by the NUSAP (numerical, unit, spread, assessment, and
pedigree) system (Funtowicz & Ravetz 1990) are regarded as level 3 in Figure 9. NUSAP tools can assess
both qualitative and quantitative uncertainties. The general goal of these tools is to structure the critical
appraisal of the knowledge base. The method has been extended by adding expert judgment of reliability
(assessment) and systematic multi-criteria analysis of the production process (pedigree) (Van der Sluijs et
al. 2004). Thus here we focused on the pedigree matrix which was first introduced by (Funtowicz & Ravetz
1990) and which results in a semi-quantitative scoring of a number of qualitative criteria. We defined
therefore a pedigree matrix with eight semi-quantitative criteria to allow for an overall transparent
assessment of the uncertainty of the framework application and its respective outputs, by considering
those aspects of the framework which could compromise the reliability of the overall result (Funtowicz &
Ravetz 1990) (Table 3). The quality levels of the below described criteria have been scored by the case
studies with values ranging between 0 (low quality) and 4 (high quality). Thus we computed for each case
study the average score across the eight qualitative scores to express the relative overall confidence in
the particular framework assessment outputs. The specifications for each score are described further in
Stelzenmuller et al., (2013).
To compare and evaluate the actual average case study scores of the pedigree matrix Monte Carlo
simulations (MCS) were undertaken (Robert & Casella 2004) to generate a distribution of 10,000 possible
average scores derived from any pedigree matrix with eight criteria and a scoring scale from 0 to 4. More
precisely with this probabilistic analysis (see level 4 and beyond in Figure 9) we generated assumption-
free probability distributions by randomised resampling of the possible scores, allowing the quantification
of the probability of the actual average case study scores. For results see Stelzenmuller et al., (2013).
Figure 9 Different tools that may be used in an uncertainty analysis
4.5 Chase
The tool was developed specifically for establishing a baseline for the implementation of the Baltic Sea
Action Plan (BSAP) and to meet the requirements of the Marine Strategy Framework Directive (MSFD) to
establish good environmental status of marine waters. It has also been used in the HARMONY project in
the North Sea using data from Eionet. In both cases a large number of sites were included. The tool itself
is based on an Excel spreadsheet with formulas and VBA code that calculates the contamination ratio for
each substance and matrix (Figure 10).
The substances to use and their threshold values are chosen by the user, but it is preferable not to mix
threshold values from derived from different criteria, i.e. threshold values for food security and EAC’s
(Environmental Assessment Criteria). In the Baltic Sea some threshold values were taken from national
guidelines based on various criteria as well as EAC’s. In the North Sea only EAC’s from OSPAR were used.
In both cases the individual sites were aggregated to larger assessment units to enable an integrated
approach as biota, biomarkers and sediments are usually not sampled in exactly the same place. The
assessment units for coastal areas were smaller than those used for Open Sea units. The data are rather
heterogenous with respect to data quality, sampling frequency and the substances measured, and some
considerations should be given to temporal trends and spatial distribution as well as the representivity of
the data. An indication of “HIGH” status do not necessarily reflect reality as monitoring data for certain
substances can be missing (Figure 11).
Status for each matrix is calculated automatically as well as the final status. In the original
implementation, data had to be typed in by the user. However, in the North Sea, the process was
automated using VBA code to fill a spreadsheet for each site from a database table as well as to extract
the results to another table for plotting on maps and further evaluation. For single site evaluation or for a
small number of sites the first approach can be used. For larger datasets the automated approach is
preferable, however this has not been implemented into a distributable package. Another feature that is
recommended to be developed is the ability to produce a table that identifies the individual substances
and matrices that is causing the status to be Poor or Bad.
31
Figure 10 The CHASE spreadsheet
Figure 11 Final classification combining both the North Sea and the Baltic.
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