Pelagic habitats under the MSFD D1 : scientific advice of policy relevance : recommendations to frame problems and solutions for the pelagic habitats’ assessment.
Date: 2021-04-21
Institutions: Joint Research Centre
Subjects: biotope, common fisheries policy, environmental monitoring, environmental protection, exploitation of the sea-bed, fishery management, fishery research, fishery resources, fishing area, marine ecosystem, marine environment, report

Pelagic habitats under MSFD D1: scientific 
advice of policy relevance 

Recommendations to frame 
problems and solutions for the 
pelagic habitats’ assessment  

Magliozzi, C., Druon, J. N., Palialexis, A., Aguzzi, L., Alexande, B., Antoniadis, K., Artigas, L. F , Azzellino, A., Bisinicu, 
E., Boicenco, L., Bojanic, N., Borrello, P., Boschetti, S., Carmo, V., Cervantes, P., Coll, M., Curmi, M., Del Amo, Y., 
Dutz, J., Francé, J., Garcés, E., Gea, G., Giannakourou, A., Goberville, E., Goffart, A., Gomes Pereira, J. N., González-
Quirós,  R.,  Gorokhova,  E.,  Guglielmo,  L.,  Helaouet,  P.,  Henriques,  F.,  Heyden,  B.,  Jaanus,  A.,  Jakobsen,  H., 
Johansen, M.,  Jurgensone, I.,  Korpinen,  S.,  Kremp,  A., Kuosa,  H.,  Labayle, L., Lazar, L., McQuatters-Gollop,  A., 
Nincevic, Z., Pagou, K., Penna, A., Pettersson, K., Ruiter, H., Skejić, S., Spada, E., Spinu, A., Tew-Kai, E., Totti, C., 
Tunesi, L., Vadrucci, M. R., Valavanis, V., Varkitzi, I., Vasiliades, L., Veldeki, G., Vidjak, O., Vincent, D., Zervoudaki, 
S.

2021 

EUR 30671 EN  

 
 
 
 
 
 
 
This publication is a Science for Policy report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. 
It aims to provide evidence-based scientific support to the European policymaking process. The scientific output expressed does not imply a 
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Contact information  
Name: Andreas Palialexis 
Address: Via E. Fermi 2749 
Email: andreas.palialexis@ec.europa.eu 
Tel.: +39 0332 78 9206 

EU Science Hub 
https://ec.europa.eu/jrc 

JRC124882 

EUR 30671 EN 

PDF 

ISBN 978-92-76-35958-6 

ISSN 1831-9424 

doi:10.2760/081368 

Luxembourg: Publications Office of the European Union, 2021  

© European Union, 2021  

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All content © European Union, 2021 
Front  page  image:  Phytoplankton  circulating  in  the  Alboran  Sea  captured  on  January  17,  2018,  by  Aqua/MODIS  (source:  NASA, 
https://oceancolor.gsfc.nasa.gov/gallery/530/). 

How to cite this report:  

Magliozzi, C., Druon, J. N., Palialexis, A., Aguzzi, L., Alexande, B., Antoniadis, K., Artigas, L.F., Azzellino, A., Bisinicu, E., Boicenco, L.,  Bojanic, 
N., Borrello, P., Boschetti, S., Carmo, V., Cervantes, P., Coll, M., Curmi, M., Del Amo, Y., Dutz, J., Francé, J., Garces, E. , Gea, G., Giannakourou, 
A., Goberville, E., Goffart, A., Gomes Pereira, J.N., Gonzalez-Quiros, R., Gorokhova, E., Guglielmo, L., Helaouet, P., Henriques, F., Heyden, B., 
Jaanus,  A., Jakobsen, H.H., Johansen,  M., Jurgensone,  I., Korpinen, S., Kremp, A., Kuosa, H., Labayle,  L.,  Lazar, L.,  Mcquatters-Gollop, A., 
Nincevic, Z., Pagou, P., Penna, A., Pettersson, K., Ruiter, H., Skejic, S., Spada, E., Spinu, A., Tew-Kai, E., Totti, C., Tunesi, L., Vadrucci, M.R., 
Valavanis, V., Varkitzi, I., Vasiliades, L., Veldeki, G., Vidjak, O., Vincent, D. and Zervoudaki, S., Pelagic habitats under the MSFD D1: scientific 
advice  of  policy  relevance,  EUR  30671  EN,  Publications  Office  of  the  European  Union,  Luxembourg,  2021,  ISBN  978-92-76-35958-6, 
doi:10.2760/081368, JRC124882.

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

Abstract ........................................................................................................................................................... 1 

Executive summary .......................................................................................................................................... 3 

1 

Introduction ............................................................................................................................................... 5 

1.1  Policy context and gaps ...................................................................................................................... 5 

1.2  Aim and objectives ............................................................................................................................. 5 

2  Spatio-temporal complexity of pelagic habitats ........................................................................................... 7 

2.1  D1C6 elements: evaluation of essential characteristics of pelagic habitats .......................................... 7 

2.2  D1C6 scale and areas: the pressure-response relationship .................................................................. 8 

3 

Indicators for pelagic habitat assessment.................................................................................................. 11 

3.1  D1C6 indicator selection: spatial consistency, relevance and feasibility ............................................. 11 

3.2  D1C6 Good Environmental Status (GES) ............................................................................................ 11 

4  The way forward the D1C6 assessment ..................................................................................................... 15 

References..................................................................................................................................................... 18 

List of abbreviations and definitions ............................................................................................................... 21 

List of boxes ................................................................................................................................................... 22 

Annexes ......................................................................................................................................................... 23 

Annex 1. Workshop’s agenda and format.................................................................................................. 23 

Annex 2. Pelagic habitats’ direct and indirect pressures. ........................................................................... 27 

Annex 3. Indicators’ selection at regional and EU-wide scales. .................................................................. 38 

i 

 
 
Abstract 

Pelagic habitats are a policy priority below Descriptor 1 (Biodiversity) of the Marine Strategy Framework Directive 
(MSFD). They are addressed under the D1C6 criterion, stating “the condition of the habitat type, including its 
biotic and abiotic structure and its functions…, is not adversely affected due to anthropogenic pressures”. The 
evaluation  of  pelagic  habitats  status  is  challenged  by  the  functional  and  structural  characteristics  of  pelagic 
habitat  diversity  and  processes.  To  date,  pelagic  habitats  assessments  are  lacking  in  common  criteria  and 
methodologies  that  characterize  the  habitat  while  accounting  for  the  effects  of  anthropogenic  pressures  to 
achieve  the Good  Environmental  Status (GES). It is  therefore  necessary  to  prioritise  communication  between 
scientific and policy communities and frame pelagic research to agree on common methods and approaches at 
regional or EU scale. This is key for achieving harmonised and comparable pelagic assessments for the MSFD. 
This report summarizes the outcomes on the assessment workflow of pelagic habitats of the JRC “MSFD pelagic 
habitats”  workshop  (9th  and  10th  March  2021),  and  the  need  for  coordinated  evaluations  of  the  scientific 
challenges of policy relevance. Recommendations on the MSFD implementation of D1C6, that were generated 
from the experts during the workshop, will be  communicated to the MSFD policy groups and the EU Member 
States competent authorities to support future harmonised assessment of pelagic habitats.   

Authors 

Chiara MagliozziJRC, Jean Noel DruonJRC, Andreas PalialexisJRC, Laura AguzziIT1, Brittany AlexandeBE1, Kostantinos 
AntoniadisCY,  Luis  Felipe  ArtigasFR1,  Arianna  AzzellinoIT2,  Elena  BisinicuRO,  Laura  BoicencoRO,  Natalia  BojanicHR, 
Patrizia  BorrelloIT3,  Simona  BoschettiJRC,  Vanda  CarmoPT1,  Pablo  CervantesES1,  Marta  CollES2,  Marta  CurmiMT, 
Yolanda Del AmoFR1, Jörg DutzDE1, Janja FrancéSI, Esther GarcésES2, Guillermo GeaBE2, Antonia GiannakourouEL, Eric 
GobervilleFR2,  Anne  GoffartBE3,  Jose  Nuno  Gomes  PereiraPT2,  Rafael  González-QuirósES3,  Elena  GorokhovaSE1, 
Letterio  GuglielmoIT4,  Pierre  HelaouetUK1,  Filipe  HenriquesPT3,  Birgit  HeydenDE2,  Andres  JaanusEE,  Hans 
JakobsenDK1,  Marie  JohansenSE2,  Iveta  JurgensoneLV,  Samuli  KorpinenFI,  Anke  KrempDE1,  Harri  KuosaFI,  Lucille 
LabayleBE2,  Luminita  LazarRO,  Abigail  McQuatters-GollopUK2,  Zivana  NincevicHR,  Kalliopi  PagouEL,  Antonella 
PennaIT5, Karin PetterssonSE3, Hans RuiterNL, Sanda SkejićHR, Emanuela SpadaIT3, Alina SpinuRO, Emilie Tew-KaiFR3, 
Cecilia  TottiIT5,  Leonardo  TunesiIT3,  Maria  Rosaria  VadrucciIT6,  Vasilis  ValavanisEL,  Ioanna  VarkitziEL,  Lavrendios 
VasiliadesCY, Georgia VeldekiEL, Olja VidjakHR, Dorothée VincentFR4, Soultana ZervoudakiEL 

JRC: Joint Research Centre (JRC), Ispra, Italy 
IT1: Environmental Protection Agency of Lazio Region (ARPA Lazio), Rieti, Italy 
BE1: European Marine Board, Oostende, Belgium 
CY:  Department  of  Fisheries  and  Marine  Research  (DFMR)  -  Ministry  of  Agriculture,  Rural  Development  and 
Environment, Cyprus 
FR1: Univ. Littoral Côte d’Opale, Univ. Lille, CNRS, UMR 8187, LOG, Laboratoire d’Océanologie et de Géosciences, 
Wimereux, France 
IT2: DICA Civil and Environmental Engineering Department, Politecnico di Milano, Italy 
RO: National Institute for Marine Research and Development “Grigore Antipa”  
HR: Institute of oceanography and fisheries (IOF), Split, Croatia   
IT3: Italian Institute for Environmental Protection and Research (ISPRA), Roma, Italy 
PT1: Secretaria Regional do Mar e das Pescas, Direção Regional dos Assuntos do Mar, Horta, Portugal 
ES1: Centro Tecnológico Naval y del Mar (CNT), Spain 
ES2: Institut de Ciències del Mar, Barcelona, Spain 
MT: Environment and Resources Authority, Malta 
DE1: Leibniz Institute for Baltic Sea Research, Rostock, Germany 
SI: National Institute of Biology, Marine Biology Station, Piran, Slovenia 
BE2: Milieu Consulting SRL, Belgium 
EL: Hellenic Centre for Marine Research, Anavyssos, Greece 
FR2: Sorbonne University, UMR 8067 BOREA, France 
BE3: University of Liège, Liège, Belgium 
PT2: Azores Regional Directorate of Maritime Affairs, Azores, Portugal 
ES3: Spanish Oceanographic Institute (IEO) Oceanographic Centre of Gijón, Spain 
SE1: Stockholm University, Stockholm, Sweden 
UK1: Marine Biological Association (MBA), Plymouth, United Kingdom 
PT3: Secretaria Regional de Mar e Pescas, Direção Regional do Mar, Madeira, Portugal 

1 

 
 
DE2: AquaEcology GmbH & Co. KG, Germany 
EE: Estonian Marine Institute, University of Tartu, Tallinn, Estonia 
DK1: Aarhus University, Aarhus, Denmark 
SE2: Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden 
LV: Latvian Institute of Aquatic Ecology, Daugavpils University Agency, Riga, Latvia 
FI: Finnish Environment Institute, Helsinki, Finland 
IT4: Stazione Zoologica Anton Dohrn Napoli, Napoli, Italy 
UK2: University of Plymouth, Plymouth, United Kingdom 
IT5: University of Urbino, Urbino, Italy 
SE3: Swedish Agency for Marine and Water Management, Gothenburg, Sweden 
NL: Directorate-General for Public Works and Water Management (Rijkswaterstaat), Netherlands 
FR3: DOPS/STM/Départment Transfert Opérationnel, Brest, France 
IT5: Università Politecnica delle Marche, Ancona, Italy 
IT6: Environmental Protection Agency of Puglia Region (ARPA Puglia), Bari, Italy 
FR4: Office Français de la Biodiversité (OFB), France 

2 

 
 
 
Executive summary 

The pelagic habitat is the largest biome on Earth, key for temperature regulation, oxygen, and food production. 
Its  physical  and  biological  components  and  processes  vary  spatially  and  temporally  depending  on  multiple 
drivers.  Understanding  this  variability,  processes  and  interactions  is  fundamental  to  identify  the  drivers  of 
changes  and  properly  assess  pelagic  habitats  under  the  Marine  Strategy  Framework  Directive  (MSFD).  A  JRC 
workshop  was  organised  to  align  scientific  and  policy  expectations  for  an  improved  MSFD  pelagic  habitat 
assessment. The workshop brought together experts from the  17 EU Member States and other organisations 
(e.g.  Regional  Sea  Conventions)  across  Europe  to  share  knowledge  and  methods  and  provide  a  coordinated 
regional input towards a harmonised assessment. This report summarizes the workshop outcomes and the way 
forward for pelagic Good Environmental Status (GES) determination. 

Policy context 

Pelagic habitats are a policy priority below Descriptor 1 (Biodiversity) of the MSFD. They are addressed by the 
MSFD D1C6 criterion (Commission Decision 2017/848/EU, 2017) which states “the condition of the habitat type, 
including  its  biotic  and  abiotic  structure  and  its  functions…,  is  not  adversely  affected  due  to  anthropogenic 
pressures”. The criterion must be finally assessed as extent of habitat adversely affected in square kilometres 
(km2) or as a proportion (percentage) of the total extent of the habitat type. Habitat type refers to broad habitat 
types (i.e. variable salinity, coastal, shelf and oceanic/beyond shelf) or to additional habitat types selected by 
Member States as meeting scientific and practical criteria (Commission Decision 2017/848/EU, 2017). 

Key conclusions 

The  evaluation  of  pelagic  habitats  status  is  challenged  by  the  diversity  of  the  functional  and  structural 
characteristics of pelagic habitats.  
The  adoption  of  common  criteria  and  methodologies  for  their  MSFD  characterization  can  be  achieved  by 
reinforcing the coordination between MS and therefore promoting:  

1.  consistency of spatial and temporal data collection to the pelagic habitat variability and corresponding 

GES assessment. 

2.  specific workshops on data and indicators to harmonize data collection, quality control, analysis, and 

access.  

3.  collaboration  among  experts  from  different  scientific  fields  and  marine  regions  to  investigate  links 

between indicators, environmental variables and anthropogenic pressures. 

Long-term  funding,  notably  of  data  collection,  is  identified  as  a  key  condition  for  achieving  MSFD  D1C6 
characterization. 

A proposal was made to separate the GES evaluation of the multi-decadal processes (climate change effects and 
permanent bottom layer hypoxia) from the short-term processes evaluation (6-year MSFD cycle), thus resulting 
in two parallel assessments. This clear separation of time scales would have the merit to effectively mark the 
progresses made by MS at short timescale while monitoring and keeping awareness of the long-term issues. 

Main findings 

Criterion elements and scales: the assessment area and the data sampling are two key aspects to account for the 
spatio-temporal variability of pelagic habitat characteristics. A vertical and a horizontal definition are proposed 
for testing to account for physical and biological differences of the pelagic realm across marine regions. Regular 
sampling of biotic and abiotic factors is fundamental to detect the natural variability and anthropogenic impacts 
on the habitat. In situ-based indicators can be extrapolated on a regular grid using satellite data and/or model 
predictions  as  a  complementary  process  to  account  for  the  spatio-temporal  dynamics  of  pelagic  habitats 
(hereafter gridded approach).  

Indicators:  fourteen  out  of  sixteen  indicators  that  were  evaluated  by  the  experts  have  an  EU-wide  scale  of 
applicability  but regional  or  subregional  thresholds.  Although  these  indicators  are  less  accurate  than  regional 
indicators,  they  can  be  applicable inter-regionally.  Species-specific  indicators (e.g. M.  leidyi  and  N.  scintillans) 
have  a  regional  application  but  spatio-temporally  limited.  Regarding  biodiversity-based  indicators  (e.g.  PH3), 
taxonomic identification by experts is more accurate (and resource demanding) than semi-automatic software 

3 

 
 
(e.g.  Zooscan)  for  plankton  classification,  and  therefore  crucial  for  biodiversity  monitoring.  Across  regional 
marine  areas,  links  with  biotic  and  abiotic  environmental  variables  are  identified  but  research  is  required  to 
investigate these linkages and the indicators sensitivity. The methods for integrating the indicators for overall 
GES assessment are not yet agreed. However, proposal was made to first integrate the indicators of the same 
category or ecosystem component (e.g. phytoplankton, zooplankton) followed by their integration for the final 
GES assessment. 

GES: the estimation of GES in km2 or percentage does not inform on the overall system functioning because it 
would be biased by the sampling strategy of the selected indicators.  

Related and future JRC work 

The outcomes of the report will be communicated to the MSFD Working Group GES and to the Marine Strategy 
Coordination Group (MSGS), and it will be the input for the ongoing revisions of D1 in the MSFD Art. 8 Guidelines. 
Indicator-specific groups and closer collaboration with experts from different scientific fields (remote sensing, 
food  web  and  biogeochemical  modelling)  will  constitute  opportunities  for  testing  methods,  achieve  inter-
regional harmonization, and relate to other MSFD descriptors (e.g. D2, D3, D4, D5, D7, D8). 

Quick guide 

The report follows the assessment flow of the Art. 8 Guidance document which was presented in the 17th GES 
working group Common Implementation Strategy 17. Each section includes a short summary of the outstanding 
issues  related  to  pelagic  habitats  assessment  and  the  feedback  from  the  workshop’s participants. The  report 
covers the evaluation of the essential characteristics of pelagic habitats and the pressure-response relationship 
(Section  2),  the indicator  selection  (e.g.  spatial  consistency,  relevance  and  feasibility)  and GES  determination 
(Section  3).  Finally,  the  way  forward  in  the  GES  determination  along  with  challenges  and  uncertainties  is 
presented in Section 4. 

4 

 
1 

Introduction 

1.1  Policy context and gaps 

The Marine Strategy Framework Directive (MSFD, Directive (EC) 2008/56, 2008) includes pelagic habitats under 
Descriptor 1 (Biodiversity), criterion D1C6 (Commission Decision 2017/848/EU (2017), hereafter referred to as 
GES Decision) and forces their assessment for the determination of Good Environmental Status (GES).  

As for the Article 17(2) of the MSFD, Member States (MS) require updating their marine strategy every six years 
and therefore to report on Articles 8 (initial assessment), 9 (Determination of the Good Environmental Status) 
and 10 (Establishment of Environmental Targets). These articles inform on specific actions for D1C6 review and 
revision, where necessary, of the level of  development and ambition of the criterion set of the next reporting 
cycle (2018-2024).  

The JRC’s workshop on pelagic habitats was driven by the report “Review and analyses of Member States' 2018 
reports for Articles 8, 9, and 10” (Magliozzi et al., 2021a) which analysed and evaluated the D1C6 assessment 
from the MS MSFD official reports (2012-2018). It showed that: i) the assessment, when complete, is carried out 
at indicator level or at specific regions (e.g. ecohydrodynamic regions in OSPAR), and not by criterion elements 
(i.e. broad habitat types: variable salinity, coastal, shelf, oceanic beyond shelf), ii) indicators are characterized by 
different threshold across marine regions, iii) a lack of supporting information and harmonised approach when 
GES is reported as “achieved”, iv) a lack of agreement on the integration methods among indicators, and iv) the 
environmental targets are not measurable to inform on the distance to GES.  

The  outcome  of  the MS  reports  was  the  basis for  a  technical  review  on  the  state-of-the-art of  indicators  and 
approaches  related  to  the  pelagic  habitats’  assessment  in  EU  waters  (Magliozzi  et  al.,  2021b).  The  review 
summarises current methods to assess D1C6 with a focus on the limitations and challenges to comply with the 
MSFD requirements.  Four  main  recommendations  were  outlined.  First,  there  is  the  need  to  account  for  the 
spatio-temporal variability of pelagic habitats by revising the classification of criterion elements as in the GES 
Decision (i.e. broad habitat types and other habitat types). Second, the identification of major anthropogenic 
pressures  is  recommended  to  evaluate  the  assessment  of  the  indicators  that  reflect  pressure-response 
relationships. Third, the indicators should reflect relevance and feasibility at regional and EU scales. Finally, the 
need for harmonized approaches to GES determination and evaluation.  

Addressing these challenges and focusing on the gaps for the pelagic habitats’ assessment, require coordinated 
work  and exchanges  between  scientific communities. To  this  end,  appointed national experts  by  the  MS and 
representatives of the Regional Sea Conventions (RSCs) were invited to participate to an online workshop to align 
scientific and policy expectations for improving the coherence of the D1C6 assessment.  

1.2  Aim and objectives  

This report summarizes the scientific discussions on data and methodologies for the MSFD-GES assessment of 
pelagic  habitats.  It  follows  the  assessment  flow  (Figure  A1)  and  the  specific  workshop’s  objectives  (Annex  1), 
from general experts’ discussions on GES definition and determination (e.g. conditions for good and not-good 
status,  pressure-indicator  relationship)  to  specific  exchanges  on  criterion  elements  and  pressure-indicator 
relationships (e.g. spatial and temporal definition of pelagic habitats, selection of regional and EU indicators). 
The  report’s  outputs  include  the  way  forward  for  the  GES  determination  and  MSFD  assessment  of  pelagic 
habitats along with their challenges and uncertainties.  

Objective 1: To define pelagic habitats and adapt the criteria elements (e.g. habitat types) by considering the 
scale-specific processes that determine the variation in pelagic habitats status. This is key to accounting for the 
spatio-temporal specificities of pelagic habitats (highly dynamic fluid) across the EU marine regions. 

Objective  2:  To  identify  the  pelagic  habitats’  direct  and  indirect  pressures,  i.e.  the  physical/chemical 
characteristics and biological responses. This is key to uncover the linkages between pelagic physical/chemical 
and biological processes. 

5 

 
Objective 3: To determine the appropriate spatial and temporal scales useful for the consistent and comparable 
assessment within and across marine regions. This implies to screen the available data, data consistency, as well 
as data gaps. Key for this objective is the identification of the dynamics of main anthropogenic pressures.  

Objective  4:  To  select  the  regional  and  EU-wide  indicators  or  combination  of  indicators  that  best  reflect  the 
pressure-response relationship,  evaluate  their  applicability  across  marine  regions  and  describe how  they  can 
ensure consistency of GES assessment (MSFD Art. 8) in EU waters. 

Objective 5: The ultimate scope is to provide recommendations for a quantitative and regionally harmonised 
GES determination (MSFD Art. 9) for pelagic habitats. 

6 

 
2  Spatio-temporal complexity of pelagic habitats 

2.1  D1C6 elements: evaluation of essential characteristics of pelagic habitats  

The pelagic habitat originates from the interaction of the physical (i.e. water masses movements and properties) 
and  biological  (i.e.  lifeforms)  systems  over  multiple  spatio-temporal  scales  (see  examples  in  Magliozzi  et  al., 
2021b).  A  thorough  understanding  of  the  hydrographic  and  biological  variability  is  needed  to  identify  the 
essential characteristics (i.e. elements, Step 2, Figure A1) and the scale of analysis for D1C6 assessment (Magliozzi 
et al., 2021b). To this end, the following questions were raised during the workshop: 

•  How to best account for the spatio-temporal variability of pelagic habitats in D1C6 GES?  

•  Are  the  four  broad  habitat  types  (Box  1)  reflecting  the  spatio-temporal  variability  of  pelagic  habitat 

processes?  

Workshop's outcome and recommendation: 

Two aspects are key to account for the spatio-temporal variability of pelagic habitat processes: definition of the 
assessment area (i.e. habitat) and data sampling (i.e. collection and analysis).  

Assessment area  
Pelagic habitats, as fluid in movement, should be defined based on hydrological and biotic data. It is however 
very difficult and resource-intensive to characterize the scale of these processes as they vary in time and space. 
Different EU-funded projects, i.e. EUNOSAT, HELCOM BLUES, OSPAR NEA PANACEA, and ABIOMMED, could help 
with  the assessment  area  definition.  To  this  end,  a vertical  delimitation  of  pelagic habitats  for  testing  would 
consider  physical  and  biological  differences  of  the  pelagic  realm  across  marine  regions  (Figure  A2).  It  was 
proposed in seasonally temperature-stratified seas (e.g. Mediterranean Sea) that the vertical delineation would 
include from surface to the seabed, while in permanent halocline areas (e.g. Baltic and Black Seas) from surface 
to  the  upper  hypoxic  layer.  Sea  bottom layers  subject  to  permanent  hypoxia in  semi-enclosed  seas,  as  areas 
extremely vulnerable to the effect of eutrophication, were suggested to be excluded from the 6-year assessment 
since time-scales for potential improvement are several-fold longer and, instead, a longer time-scale assessment 
showing trends was proposed in parallel together with the temperature increase as a result of climate change. 
The  assessment  would  thus  result  in  two  parallel  and  independent  evaluations,  on  one  hand  the  long-term 
evaluation that includes climate change effects (e.g. multi-decadal temperature increase) and geomorphological-
induced bottom layer hypoxia (areas with permanent halocline and low water renewal time), and the short-term 
processes evaluation for all the others pressures on the other hand. This clear separation of the short- and long-
term  processes in  the GES  assessment  has  the merit  to  effectively mark  the  progresses made by  MS  at  short 
timescale (6-year cycle) while monitoring and keeping awareness of the longer-term issues (multidecadal), which 
is also addressed in assessments of other descriptors, e.g. eutrophication by short-term and long-term trends.  

A  gridded  approach  applied  to  any  broad  habitat  subdivision  can  be  used  (also  on  existing  sub-areas  of 
assessment) depending on regional specifications and data availability (Figure A3). Priority should be given to 
preserving the current assessment spatial scales as they are linked to different monitoring designs, when existing. 
Also “other habitat types” as criterion elements, must be defined.  

Data  

Data collection: sampling of biotic and abiotic factors with a frequency adapted to the local variability, is key to 
detect relevant natural and anthropogenic changes and their impacts on the habitat. Sampling would cover also 
offshore sampling stations to answer to the MSFD requirements for assessing D1C6 broad habitat types, while 
current monitoring is often spatially limited to coastal areas (e.g. Romanian coasts). Most of the MSFD monitoring 
programmes rely on existing monitoring surveys historically developed for the WFD.  

7 

 
With the exception of the ship-of-opportunity Continuous Plankton Recorder (CPR)1 survey, open sea areas are 
often sampled at specific times of the year. For example, in Greece (i.e. Aegean Sea, and partially Ionian and 
Levantine Seas) stratified and mixed waters are specifically sampled. Also, sampling stations representative of an 
anthropogenic  pressure  (e.g.  power  plant)  can  be  established  in  coastal  areas  for  long-term  monitoring  (e.g. 
Saronikos Gulf, Greece).  
Long-term  monitoring  sites  (e.g.  Long  Term  Ecological  Research  Network-  LTER)  are  very  important  to  study 
biological trends and to depict natural variability from direct anthropogenic pressures, but their data are often 
rare,  especially in  coastal  areas.  Both  fixed-site  and  opportunistic (CPR  since  1958)  long-term  data  collection 
should be supported to ensure monitoring of biodiversity multidecadal changes. 

Sampling  frequency  and  coverage  differ  across  marine  regions  according  to  the  main  physical  and  biological 
characteristics  of  the  area  and  to  the  available  funding  of  the  monitoring  programs.  In  fact,  data  acquisition 
offshore  is  heterogeneous  in  space  and  time  and  depends  on  costly  sea-campaigns.  If  data  collection  occurs 
within e.g. fisheries surveys, it does not necessarily provide the required seasonal coverage. In France, to achieve 
cost-effective monitoring, offshore sampling is optimized by innovative technologies (e.g. automated systems 
deployment, optical remote sensing data) providing useful information on the distribution of plankton dynamics 
and phenology.  

Data  analysis:  Fixed-point  and  spatial  survey  (e.g.  CPR)  sampling  can  be  integrated  with  satellite  data, 
oceanographic processes such as advection, research vessels data, and model predictions to better capture the 
spatio-temporal  variability  of  pelagic  physical  and  biological  processes.  This  requires  considering  new 
methodological and computational approaches (i.e. machine learning), and additional source of information (e.g. 
environmental DNA). 

In France, operational modelling is used to have information on stratification and mixing layers on coastal, shelf 
and ocean seascapes. For example, upwelling index and other physical indices at seascape scale are computed 
from these models also integrating satellite data.  

Box 1. Definition of habitat type for D1C6 

The GES Decision specifies four broad habitat types: variable salinity, coastal, shelf and oceanic/beyond shelf. 
Variable salinity refers to “retained for situations where estuarine plumes extend beyond waters designated as 
Transitional  Waters  under  Directive  2000/60/EC”,  and  coastal  “shall  be  understood  on  the  basis  of  physical, 
hydrological and ecological parameters and is not limited to coastal water as defined in Article 2(7) of Directive 
2000/60/EC”.  

MS by regional and subregional cooperation can select additional habitat types, if meeting the following criteria 
(GES  Decision):  i)  scientific  criteria:  e.g.  representative  of  the  ecosystem  (e.g.  high  biodiversity),  specific 
anthropogenic pressure, extent, and species; ii) practical criteria: e.g. monitoring viability and costs, timeseries. 

2.2  D1C6 scale and areas: the pressure-response relationship 

The identification of the major anthropogenic pressures is key for determining the appropriate scale of  pelagic 
habitats  assessment.  However,  this  is  a  challenge  because  the  temporal  and  spatial  dimensions  of  pelagic 
processes  interact  with multiple  pressures  (e.g.  hydro-meteorological factors, contaminants  and  litter inputs, 
human physical interventions; Magliozzi et al., 2021b). According to the GES Decision, the MSFD indicators need 
to  reflect  clear  pressure-response  relationships.  To  this  end,  the  following  aspects  were  raised  during  the 
workshop:  

•  How to tackle the pressure-indicator relationship? (discussion session) 

• 

Identify  the direct  and indirect  pressure  in  your marine  region  and  their  spatial  and  temporal  scales 
(excel tables exercise) 

1  The CPR survey which  has sampled plankton communities (~700 taxa) throughout the North Atlantic and North  Sea since 1958 using a 
consistent method. This is the world’s most spatially and temporally-extensive marine biodiversity dataset and is one of the few that 
samples at a monthly time scale in offshore and open ocean waters. CPR data are freely available online and via the Marine Biological 
Association, who run the survey. 

8 

 
 
Workshop's outcome and recommendation: 

Discussion session: pressure-indicator relationship 

The pressure-indicator relationship is not linear (i.e. the indicator’s change is not enough to link to a pressure) 
and requires a step-by-step approach to be investigated.  

First, we need a thorough understanding of the effect of the pressures and their interactions in the marine realm. 
This step includes considering multiple pressures, anthropogenic and natural, at different temporal scales, and 
integrating descriptors, e.g. D1 and D4 (diversity, abundance, biomass, productivity, trophic transfer). 

Second, we need to detect changes in the indicator. This step aims at studying the variability of the indicator and 
disentangling its drivers of change (i.e. pressures: e.g. SST, nutrients, etc.). To do this, multiple approaches can 
be adopted as, for example, the analysis of different time-series lengths and sampling strategies to highlight links 
to different pressures and depict extreme events (e.g. Bedford et al., 2020). Complementary tools can be risk 
metrics, as used for the cumulative risk assessments of benthic habitats, or sensibility matrices that can help to 
assess  the  connections  between  a  pressure  and  the  indicator.  Research  is  also  testing  the  behaviour  of 
biodiversity  indicators  in  relation  to  multiple  anthropogenic  pressures  defined  categorically  as  impact  levels 
(Francé  et  al.,  2021)  and  of  functional-based  plankton  indicators  (i.e.  PH1/FW5)2.  For  example,  using 
complementary  approaches, 
in  situ  phytopigment  concentrations  (HPLC 
measurements), France has adapted the PHYSAT-MED tool developed by Navarro et al. (2017) to a local scale 
allowing  the  biomass  identification  of  the  major  phytoplankton  functional  groups  in  coastal  waters.  The 
adaptation of the PHYSAT-MED tool led to the development of the OC5-PHYSAT prototype that offers a promising 
application in the framework of the MSFD (D1, D4, D5).  

i.e.  ocean  colour  data  and 

Finally, issues related to climate-driven changes should be addressed uniformly for all biological indicators using 
commonly accepted climate change model for a given region. 

Summary tables on the spatio-temporal variability of indicators and pressures by marine region (Annex 2) 

The main pressures on pelagic habitats (e.g. type of pressure, link with MSFD descriptor, unit) were summarized 
by  marine  region  in  a  table  format  following  what  reported  in  Magliozzi  et  al.  (2021b)  (see  Annex  2).  The 
operational  and  under-development  indicators  were  linked  to  each  pressure  and  the  indicator  confidence 
estimated based on the low, moderate or strong relationship (i.e. 1 to 5, where 1 is low level relationship) with 
the  pressure  (Annex  2,  Table  A2).  Pressures  and  indicators  were  also  discussed  by  analysing  the  indicator 
temporal and spatial sampling (Annex 2, Table A3), the pressures-scale of variability (Annex 2, Table A4), and the 
data gaps (Annex 2, Table A5).  

Among  the  anthropogenic  pressures  listed  in  the  GES  Decision  (Box  2),  eutrophication  and  non-indigenous 
species were characterized by the highest indicators’ confidence of pressure-indicator relationship (i.e. 4 and 5). 
For eutrophication, the pressure-response relationship is well represented (confidence scores between 3 to 5, 
Table A2) by the indicators: i) Chlorophyll-a (in-situ and satellite), which is commonly used across three marine 
regions  (e.g.  Mediterranean, Baltic  and  Black  Seas),  ii) Zooplankton  Mean  Size  and  Total  Stock  (MSTS) in  the 
Mediterranean and Baltic Seas, and iii) micro phytoplankton abundance in the Mediterranean and the Black seas. 
Also, there are two phytoplankton indicators exclusively scored in the Baltic Sea: the Cyanobacterial Bloom Index 
and the Seasonal Successional of Dominating Phytoplankton Group (Table A2). Finally, one more indicator, i.e. 
“microbial species indicator” (Ferrera et al., 2020), was added as potentially relevant to identify eutrophication 
impacts at subregional scale in the North West Mediterranean Sea (Table A2). Non-indigenous species represent 
a pressure in many subdivisions of the Mediterranean Sea, in the Black and the Baltic Seas. Mnemiopsis leidyi 
biomass is an operational indicator in the Black Sea and could also be used in the Adriatic Sea, although pressure-
impact  relationship  was  not  yet  tested  in  the  Mediterranean  Sea.  While  in  the  Baltic  Sea,  the  biomass  of 
Cercopagis pengoi could be used to complement M. leidyi. 
Climate change and overfishing were added to the list of pressures as having a strong link with combined phyto- 
and zooplankton indicators in the North-East Atlantic (i.e. OSPAR’s indicators: PH1/FW5, PH2) and with the size-

2  The PH1/FW5  used in the  North-East Atlantic assessment area, combines phyto- and zooplankton abundances and lifeforms (e.g. size, 
motility, trophic preferences) to investigate changes from primary to secondary producers, and to top predators (Mcquatters-Gollop et 
al., 2019). 

9 

 
 
based indicator Zooplankton Mean Size and Total Stock in the Baltic Sea (Table A2). Besides, OSPAR’s indicators 
were scored low to medium confidence (1-3) for eutrophication. 
Ten more indicators and metrics (e.g. multiple biodiversity and evenness indices) were listed to investigate the 
possible  relationships  with  overfishing  and  multiple-acting  pressures  (i.e.  eutrophication,  overfishing,  climate 
change) in the Mediterranean Sea (Table A2). 
Links  between  pelagic  habitats  and  hydrographical  conditions  (D7)  and  contaminants  (D8)  have  not  been 
explored yet. However, eco-hydrodynamic regions which are currently used as spatial scales in the NEA region, 
could be the base for harmonising the assessment scale and exploring possible links between state and pressures 
descriptors.  

The temporal and spatial sampling for each indicator at regional scale and across marine regions is presented in 
Table  A3  (Annex  2).  For  example,  in-situ  data  of  Chlorophyll-a  are  collected  monthly  to  seasonally  in  the 
Mediterranean Sea, with differences of sampling coverage depending on the MS, and bi-weekly to monthly in 
the Baltic Sea (Table A3). Although monthly sampling is required for most plankton indicator assessments in the 
Baltic  Sea,  e.g.  seasonal  succession  of  dominating  phytoplankton  groups,  there  are  some  data  gaps  due  to 
different monitoring strategies in MS, which require adjustments in frequency and spatial coverage to improve 
assessment results for pelagic indicators. In the North-East Atlantic, a combination of monthly data from fixed-
point station and CPR (since 1958) is used for PH1/FW5, PH2, and PH3 indicators (Table A3). However, there are 
several gaps because i) not all time-series capture all lifeforms and are of different duration (i.e. PH1/FW5) and 
ii) of the under sampling of small phytoplankton and zooplankton by some time-series (i.e. PH1/FW5, PH2, PH3); 
nevertheless,  there  are  few  datasets  that  can  support  indicators  at  such  a  spatial-temporal  scale  and  few 
indicators that are so ambitious. Physical data at regional scale (multidecadal) and nutrient data (timeseries <20 
years) are collected at the same fixed-point stations (Table A3).  
In  the  Black  Sea, most  of  the  data  for  the indicators  are  sampled  in  the warm (May  to  September)  and  cold 
seasons (Table A3) and across coastal, variable salinity and shelf waters (Table A4). 

Box 2. Anthropogenic pressures listed in the GES Decision and linked to D1C6 

In the definition of D1C6 of the GES Decision: “The condition of the habitat type…is not adversely affected 
due  to  anthropogenic  pressures”,  anthropogenic  pressures  refer  to  the  adverse  effects  from  pressures 
assessed by the MSFD pressure Descriptors 2, 5, 7, 8 and criteria:  

•  D2C3: Adverse effects of Non-Indigenous Species (NIS) 

•  D5C2: Chlorophyll-a concentration in the water column  

•  D5C3: Harmful algal blooms (extent, frequency, duration) 

•  D5C4: Photic limit (transparency of the water column) 

•  D7C1: Permanent alteration of hydrographical conditions 

•  D8C2: Adverse effects of contaminants 

•  D8C4: Adverse effect of significant acute pollution events 

10 

 
3 

Indicators for pelagic habitat assessment 

3.1  D1C6 indicator selection: spatial consistency, relevance and feasibility 

The D1C6 elements and methodological standards (e.g. indicators) have to ensure consistency between marine 
regions  or  subregions (GES  Decision). Therefore,  the  selection  of indicators  would reflect  their relevance  and 
feasibility at large scale and suggest linkages with abiotic and biotic variables (Magliozzi et al., 2021b). This section 
is about spatial consistency (at sub-regional, regional or EU level) and indicators advantages and disadvantages. 
The MS reports of D1C6 (2012-2018 reporting cycle) show differences in the selection of habitat types and lack 
of agreed indicators and assessing methods (Magliozzi et al., 2021a).  

To this end, the following aspects were raised during the workshop:  

•  How to ensure the spatial consistency (by sub-region, region and/or at EU level) of pelagic habitat GES 

assessment? (Discussion session) 

• 

Selection of regional and EU-wide indicators for their relevance and feasibility (summary tables) 

Workshop's outcome and recommendation: 

Spatial consistency 
Three aspects are key to allow consistency of assessments between regional seas:  

i) 

ii) 

iii) 

The  definition  of  habitat  types  that  considers  environmental  (biotic  and  abiotic)  variables  and 
anthropogenic pressures. 
The  selection  of  indicators  and  the  process  for  setting  thresholds  should  conceptually  be  similar 
and methodologically traceable. The monitoring networks characterized by harmonized methods 
for  collection,  quality  control  and  analysis  would  help  to  capture  the  drivers  of  change  of  the 
plankton community. 
The definition of GES and related thresholds.  

Regional collaboration across MS is needed for progressing on these aspects and harmonizing the assessment 
methods. 

Indicator selection 
Fourteen out of sixteen indicators have an EU-wide scale of applicability but regional thresholds (Table A6). Only 
two  species-specific  indicators,  i.e.  M.  leidyi  and  N.  scintillans,  have  a  regional  application  (Table  A6).  The 
indicators’ links with biotic and abiotic environmental variables, which could be used to extrapolate the in situ-
based indicators, were identified for i)  satellite Chlorophyll-a, Chl-a horizontal gradient, ii) SST, iii) salinity, iv) 
inorganic and organic nutrients, and v) pH (Table A6). Research is required to investigate these linkages and the 
sensitivity of indicators to drivers and velocity of change (Table A7, e.g. Flo et al. (2019) in the WFD framework). 
The North-East  Atlantic  and  Mediterranean  Sea  working  groups  highlighted  the need  to  integrating D4  (food 
webs) indicators with D1C6. 

3.2  D1C6 Good Environmental Status (GES) 

The overall GES for marine resources in the MSFD means that their different uses are conducted at a sustainable 
level, ensuring their continuity for future generations (Article 1(3) of the MSFD). In addition,  the overall MSFD 
GES means that: 

i. 

ii. 
iii. 

ecosystems,  including  their  hydro-morphological  (i.e.  the  structure  and  evolution  of  the  water 
resources),  physical  and  chemical  conditions,  are  fully  functioning  and  resilient  to  human-induced 
environmental change;  
the decline of biodiversity caused by human activities is prevented and biodiversity is protected; 
human activities introducing substances and energy into the marine environment do not cause pollution 
effects. Noise from human activities is compatible with the marine environment and its ecosystems. 

11 

 
 
This section focuses on the qualitative definition of good and not-good status of D1C6 pelagic habitats indicators 
(hereafter D1C6 GES), their comparability and integration for the overall criterion assessment. To this end, the 
following aspects were raised during the workshop:  

•  What does good and not-good status (qualitatively) mean for each indicator? Is D1C6 GES consistent 
across  comparable 
indicators)?  How 
specific/general the D1C6 indicators should be as regards to relevance and spatial consistency? How to 
combine the resulting indicators for D1C6 GES status? What is the acceptable surface area in GES by 
region? (threshold value of criterion) 

the  phytoplankton-related 

indicators 

types  of 

(e.g., 

Workshop's outcome and recommendation: 

Indicators: good and not-good status  

The qualitative definition of good and not-good status for the indicators in Annex 2 is strictly linked with regional 
seas characteristics and the availability of long-term datasets using appropriate monitoring practices. To this end, 
long-term data allow identification of the drivers of change of plankton communities.  

For  example,  important  changes  of  phytoplankton  biomass  in  the  North-East  Atlantic  are  driven  by  human 
pressure,  including  climate  change,  rather  than  natural  variability.  When  changes  are  driven  by  local 
anthropogenic pressures, the not-good status can be identified by comparing biomass with data from subregions 
with similar abiotic and biotic characteristics. When considering biomass changes compared to baseline data, the 
difficulties are how to define i) baseline, ii) best length of time series and iii) the condition of shifting from the 
baseline due to anthropogenic pressures.  

investigated 

In  the  Mediterranean  Sea,  Chl-a 

For Chlorophyll-a, GES depends on the natural vertical and horizontal gradients, therefore it is first necessary to 
in  the  ABIOMMED  project 
evaluate  the  properties  of  the  water  masses.  This  will  be 
(https://ec.europa.eu/environment/marine/projects/index_en.htm). 
is 
evaluated  in  coastal  waters  up  to  1  nautical  mile,  following  the  classification  system  defined  during  the 
intercalibration exercise of Water Framework Directive Mediterranean Geographical Intercalibration Group and 
set in the Commission decision (EU) 2018/229, while different thresholds might apply beyond coastal waters. 
Depth of Chl-a sampling is an important point to clarify as the current levels are inherited by the WFD. This work 
should  be coordinated  with  the on-going  work  under  Descriptor  5.  Additionally,  in  the  Mediterranean  region 
research work is still ongoing for many subregional indicators (e.g. zooplankton indices, Table A2). For example, 
non-indigenous M. leidyi is found in the Adriatic Sea where it can form dense aggregations. Here, GES definition 
could  be  strongly  linked  to  the  possibility  of  mitigating  high  densities,  i.e.  the  species  high  abundance 
corresponds  to  not-good  status,  while  its  absence/low  abundance  do  not  necessary  inform  on  GES. 
Phytoplankton  and  Zooplankton  abundance/biomass  and  diversity, 
including  pigment  signatures  of 
phytoplankton  communities  and  phytoplankton  blooms  and  community  composition  assessed  using  pigment 
signature are also suggested because they can reflect environmental change. Good and not-good status can be 
established  as  a  deviation  of  natural  variability  defined  at  habitat  types 
level  (to  be  defined  at 
subregional/regional level). This deviation could be related to environmental pressures.  With the exception of 
PH2 which uses phytoplankton biomass, at present, the use of these indicators is still in the early stages of testing. 
It is also considered very useful in the Mediterranean to apply indicators based on phytoplankton or zooplankton 
functional  traits,  in  particular  morphological  (size  classes,  colonies)  and  physiological  (silica  demand,  trophic 
position-production type for zooplankton, toxin production etc.). In this context, for example, OSPAR indicator 
PH1/FW5 was designed to apply also on functional traits and can be used on any dataset and in any region. 

Specifically in the Baltic Sea, the MSTS indicator was designed from the food-web perspective, and it is related 
to  fish  predation  and  eutrophication.  The  mean  size  of  a  zooplankter  in  the  community  is  indicative  of  both 
grazing pressure on phytoplankton and fish feeding conditions. Large stocks of zooplankton composed of large-
bodied organisms have a higher capacity for transferring the energy of primary producers (phytoplankton) to fish 
than smaller-bodied organisms. Therefore, good status is defined when there is high energy transfer efficiency. 
For  the  Seasonal  Successional  of  Dominating  Phytoplankton  groups,  changes  in  species  composition  and 
phenology reflect deviations from normal variability based on the long-term observations in each Baltic subbasin. 
Deviation from this normal variability indicates not-good status. For example, the lack of large diatoms in spring 
is a symptom of poor sedimentation and poor food to benthos. 

12 

 
Indicators: spatial consistency and comparability for D1C6 assessment 

Spatial representativity is a key indicator property for detecting changes. It can be ensured by i) linking state and 
pressure  indicators  to  local  conditions,  ii) giving  adequate research  and  monitoring  resources  for  all  diversity 
indicators (these are as good as the data which populate them), and iii) preserving time-series and taxonomy as 
key to having good data.  
For  example,  in  the  Baltic  Sea,  Chl-a  values  as  Ecological  Quality  Ratio  (EQR)  are  already  used  to  establish 
thresholds for MSTS to account for eutrophication pressure and will be tested for the Seasonal Succession of 
Dominating Phytoplankton Group indicator. Further investigations will be carried out by the EU-funded project 
HELCOM BLUES in 2021. 
As for how should D1C6 indicators be as regards to relevance and spatial consistency, a compromise between 
EU-common and regional-specific indicators must be found to link with  anthropogenic pressures and balance 
costs  and  data  availability,  especially  regarding  the  indicators  that  translate  a  regional-specific  expression  of 
eutrophication. There are several advantages and disadvantages in the selection of more general and specific 
indicators.  
General indicators could allow comparing the marine regions but might not be relevant or less accurate to assess 
the pelagic habitats condition in regional seas or they might require an adjustment (e.g. Chl-a, phytoplankton 
and zooplankton biomass indicators).  

For  example,  surface  Chl-a  has  the  advantage  of  being  estimated  by  satellites  although  limited  to  the  upper 
optical depth of the water column. This satellite-based indicator well reflects eutrophication pressure, but it does 
not detect the deeper primary production that is an important process in subregions of the Western and Eastern 
Mediterranean  Sea.  During  the  stratification  period  from  late  spring  to  autumn,  there  is  a  deepening  of  the 
nutricline followed by the progressive deepening of the Chl-a maximum and primary production even below 50 
m, which cannot be depicted by satellite. Therefore, the satellite Chl-a requires to be complemented by in-situ 
sampling. On the other hand, sampling deeper waters could inform on the cumulative impact of anthropogenic 
pressures. A recent study by Francé et al. (2021) found that the effects of anthropogenic pressures (e.g. both on 
land  and  coastal  anthropogenic  activities)  on  phytoplankton  biodiversity  indices  (e.g.  evenness,  dominance, 
diversity) are more evident with increasing depth surface, where the communities are more uniform and less 
dominated by single species at low-impact than at high-impact sites.  

Specific  (regional)  indicators  have  the  advantage  to  reflect  changes  at  regional  scale  and  for  time  periods 
supporting policy implementation. They can be upscaled to other marine regions by using locally relevant taxa 
and looking at local pressures. For example, the PH1/FW5 indicator does not require species-level data because 
it  is  based  on  lifeforms  and  not  only  taxonomy,  which  widens  its  applicability  across  datasets.  In  the 
Mediterranean  Sea,  the  combined  use  of  multiple  biodiversity  indices  of  phytoplankton  and  zooplankton 
(evenness and dominance also) is under evaluation to link to regional scale pressures.  

It is important to set indicators that significantly reflect the environmental pressures, which is often difficult in 
pelagic habitats. A way forward would be to combine general pressure indicators of phytoplankton/zooplankton 
communities (such as chlorophyll a, jellyfish blooms, anomalous presence of NIS species) with species-specific 
functional traits or others status indicators in order to evaluate deviations with respect to pelagic communities 
where anthropogenic pressures are considered as not significant. 

Overall,  general/EU-wide  indicators  tend  to  be  less  accurate  than  regional/specific  indicators,  they  however 
allow  testing  inter-regional  consistency.  The  satellite-based  Chl-a  indicator  furthermore  allow  the  frequent 
monitoring of surface pelagic habitats at local scale with relevant patterns to GES (e.g. changes in frequency, 
time  of  initiation,  duration  and  peak  of  blooms).  Satellite-based  Chl-a  combined  with  hydrographic  variables 
would inform about processes. In situ-based (general and specific) indicators, because of under-sampling in time 
and space, can fruitfully be extrapolated on a grid that reflects the pelagic habitat variability provided a link is 
found with environmental variables. Such extrapolation would enhance the quality of in situ-based indicators 
while accounting for most of the spatio-temporal variability of pelagic habitats. 

In  the  future,  3-D  physical  -  biogeochemical  and  spatially-explicit  ecosystem  models  will  be  promising 
complementary tools since, by construction, the effect of the main pressures on the ecosystem functioning can 
be quantified. 

13 

 
 
Integrating indicators for an overall GES assessment 

The integration of indicators requires evaluating both the characteristics of the indicator, i.e. state or pressure, 
and its importance for assessing the pelagic habitat condition. A prerequisite for the indicator integration is the 
understanding of the major environmental factors and of their effects on pelagic habitat condition. Therefore, 
the  choice  of  the  integration  method,  e.g.  hierarchical  and  weighting,  between  indicators  is  linked  to  the 
indicators’ confidence and relevance regarding GES assessment.  

A recommendation for testing would be to combine indicators for each pelagic component (i.e phytoplankton 
indicators,  zooplankton  indicators)  with  a  multi-metric  approach  for  each  component.  The  average  of  the 
indicator values within a pelagic component could define the component GES. The overall D1C6 GES (of all the 
pelagic components) could then be defined by the one-out all-out integration rule.  

For example, if a strong species indicator of eutrophication is not-good status, the overall assessment could also 
be not-good. 

In the North-East Atlantic and Baltic marine regions, the NEA PANACEA and HELCOM BLUES projects are going to 
test  indicator  changes  in  relation  to  the  ecosystem  functioning  and  integration  approaches.  Similarly,  in  the 
Mediterranean  Sea,  the  ABIOMMED  project  will  explore  how  common  methodologies  and  indicators  can 
improve coherence of pelagic habitat assessments.  

In  the  Black  Sea,  it  was  proposed  that  the  combination  of  three  main  indicators  covering  phytoplankton, 
zooplankton  and  Chl-a  could  provide  a  scientific  sound  assessment  for  the  pelagic  habitats.  As  such  the 
assessment  of  selected,  i.e.  phytoplankton  biomass,  total mesozooplankton  biomass  and  Copepoda  biomass, 
could  be  integrated  using  an  averaging  method.  Such  indicators,  which  are  well-covered  by  the  established 
monitoring programmes could achieve consistent assessment at regional level, at least for the Black Sea. 

Finally, in addition to eutrophication descriptor (D5), the integration of the food web MSFD Descriptor (D4) in 
D1C6  would  need  consideration,  given  the  existing  strong  link  between  pelagic  biodiversity  and  food  web 
functioning. 

Once a list of indicators is set and tested by region, different integration methods should be tested accounting 
for the relevance and reliability to GES, but a first integration level could be  done at indicator type level (e.g. 
phytoplankton or zooplankton indicators) and then between different indicator types. The GES assessment of 
long-term processes (climate change and permanent hypoxia) could be kept independent to the other shorter-
term processes in order to disentangle the possible progresses made over an assessment cycle  (6 years) from 
the multidecadal trends. 

GES extent for pelagic habitats 

The MSFD requests to provide the fraction of surface area in percentage or square kilometres that is in GES for 
each broad habitat in a marine region. However, given the physical and biological variability of pelagic habitats, 
the estimation of GES in km2 or percentage does not inform on the system functioning because it would be biased 
by the assessment system of selected indicators and the related sampling strategy (e.g. seasonal versus annual 
sampling,  integrations  between  stations,  regions,  and  basins).  Moreover,  this  estimation  would  imply  that 
available data are fully representative of the pelagic habitat. Standardizing sampling strategies is a key step to 
compare GES between marine regions.  For MS like Romania that have provided a final GES assessment in the 
reporting cycle 2012-2018, the evaluation was based on statistical analysis and expert judgement.  

As a result, the final GES assessment relies upon the definition of habitat and spatio-temporal consistency of the 
assessment areas (Section 2.1). One should question whether a necessarily limited network of sampling stations 
(stationary  and  of  opportunity)  and  subsequent interpolation  of GES  assessment  at  sub-regional  level  (broad 
habitat types) is consistent with the pelagic habitat variability in space and time. The gridded approach, based 
on  spatial  indicators  (e.g.  satellite-based  Chl-a)  and  on  the  extrapolation  of  in  situ-based  indicators,  is  a 
complementary spatio-temporal strategy to account for the dynamics of pelagic habitats. This extrapolation step 
would be data-driven and directly allow mapping GES assessment at the scale of the pelagic habitat variability 
no longer needing broad habitat types. Furthermore, a temporal assessment (e.g. annual) of this highly spatial 
complementary  step  would  valuably  inform  on  the  GES  trend  over  the  assessment  period,  and  thus,  on  the 
relative distance to the GES objective. 

14 

 
 
4  The way forward the D1C6 assessment 

In the MSFD perspective, a key aspect for harmonizing sampling strategies and standardizing protocols is to 
reinforce the coordination among MS. It can be achieved by promoting: 

i) 
ii) 

iii) 

specific workshops on data- and indicators,  
collaboration  among  experts  from  different  fields  (e.g.  remote  sensing,  food  web  and 
biogeochemical modelling) and marine regions,  
long-term funding.  

Workshops for harmonizing sampling strategies and protocols  

Monitoring data is limited in space and time  so that sampling should be optimized for investigating pressure-
response  relationships  and  the  spatial  representativity  of  the  GES  assessment.  In  a  second  step,  a  better 
harmonized  sampling  strategy  would  help  being  compliant  with  statistical  tools  for  indicators  and  threshold 
settings and lead to a better assessment in the gridded approach.  

In the Mediterranean Sea, there are sub-regional differences in the frequency, duration, and spatial coverage of 
plankton  data.  Also,  data  access  is  currently  limited  to  EU-funded  projects  and  upon  requests  on  national 
websites. In Slovenia for example, only Chl-a monitoring is carried out, while phytoplankton is sampled at one 
station  which  is  included  in  the  Long  Term  Ecological  Research  Network  (LTER)  and  considered  as  reference 
condition. On the contrary, the zooplankton monitoring was dismissed due to lack of agreement on a common 
assessment methodology. In Greece (representing the Aegean, and partially the Ionian and Levantine seas), the 
MSFD monitoring network for plankton biodiversity (phytoplankton and zooplankton) is at present focused on 
open waters. This network is under revision and considered to be extended to coastal waters also (hot spot areas 
mostly), and from 6 to 12 nm for open waters in the Ionian Sea only. Chl-a monitoring is conducted in coastal 
stations by the WFD network and in open water stations by the MSFD network, therefore Chl-a is covered in all 
marine water bodies of Greece, France, Italy and Spain. HCMR is currently building a dedicated database for the 
access of monitoring parameters for all Descriptors in the frame of the MSFD monitoring program in Greece. 
France is building an information system (SIMM; Système d’Information Milieu Marin3 combining data collected 
in  the  frame  of  European  Directives  (e.g.  WFD,  Natura  2000,  MSFD)  and  integrating  activities  pressure  and 
impacts  on  marine  ecosystems.  In  the  Black  Sea  region,  sampling  protocols  are  already  harmonized  among 
countries,  but  intercalibration  exercises  are  necessary  to  share  expertise  and  capabilities.  Beyond  the  added 
value of workshops for sharing expertise and capabilities, intercalibration exercises would decrease the risk of 
bias when data are compared among systems (data consistency). 

In the HELCOM area, indicator-based assessments should be adjusted to the monitoring design, whereby it is 
important to identify data gaps and address them through adaptations. The harmonization of sampling protocols 
was already addressed by HELCOM COMBINE (Cooperative Monitoring in the Baltic Marine Environment) and 
applied in the Holistic Assessment of Ecosystem Health Status (HOLAS).  

In the OSPAR region, continuation of existing monitoring is key to support long-time series and informing MSFD 
indicators (e.g. the CPR).  

3 https://www.milieumarinfrance.fr/Nos-rubriques/Cadre-reglementaire/Directive-Cadre-strategie-pour-le-milieu-marin 

15 

 
 
Box 3. Workshops on sampling strategies and methods are important to: 

• 

• 

• 

set data networks at regional scale to harmonize plankton data collection, quality control and methods 
of analysis.  

promote data access at regional scale to test and evaluate common and new protocols. 

secure  long-term  funding  at  regional  scale  to  allow  data  exploration  and  evaluation  of  regular 
monitoring data and its extension in areas with low spatial and temporal coverage. 

Workshops on indicators  

Many questions are still unsolved about indicators spatial consistency at sub-regional, regional or EU levels, and 
what indicators are better pressure-representative across marine regions. Moreover, there is a need to discuss 
if and how integration among indicators types (e.g. general and specific) is to be carried out for D1C6 assessment, 
and of potential methods. 

In terms of indicator development, taxonomic accuracy is key to functional and diversity indicators and can be 
highly  variable  depending  on  the  operator’s  expertise.  Taxonomic  identification  by  trained  operators  can  be 
complemented – but not substituted - by automated technologies (e.g. CytoSense, ZooScan, FlowCam), that are 
still characterized by large differences in outputs depending on the targeted taxa and sampling method. More 
research is needed to integrate these different types of data (e.g. this is one of the objectives of NEA PANACEA) 
and facilitate the aggregation of datasets across MS, laboratories and research teams. The harmonization of data 
measurements,  analysis  and  products from  automated  approaches  has  been explored  by  the  H2020  INFRAIA 
projects JERICO-NEXT and JERICO S34. 

When spatial and temporal protocols are available, priority should be given to developing flexible indicators that 
can be used with different dataset types and account for different sampling regimes (e.g. PH1/FW5, PH2, PH3). 

Finally, links between the main indicators and environmental variables need to be investigated and discussed in 
targeted  working  groups  in  association  with  environmental  data  experts  (satellite  remote  sensing  and 
operational physical models) to explore the extrapolation potentials by indicator and region. 

Joint work at the Regional Seas Convention level 

Promoting  collaborations  between  RSCs  is  particularly  needed  for  those  MS  with  assessment  areas  in  two 
regional Seas, which could also increase inter-regional harmonization and comparability in the GES assessment. 
To this end, the foreseen exchanges between the new EU-funded projects, the NEA PANACEA, HELCOM BLUES 
and ABIOMMED would support this level of collaboration. 

Box 4. Workshops on indicators are key to: 

• 

• 

• 

• 

share  experience  and  discuss  advantages  and  disadvantages  of  the  plankton  indicators  that  are 
considered in the different regions.  

develop flexible indicators to datasets. 

involve  experts  from  different  scientific  disciplines,  e.g.  remote  sensing,  food  webs,  biogeochemical 
modelling, for investigating the link with the environmental variables (extrapolation to a spatial grid).  

promote data access at regional scale to test and evaluate common and new protocols. 

4 www.jerico-ri.eu 

16 

 
 
 
 
 
 
Long-term funding for monitoring 

The assessment of pelagic habitats is challenged by insufficient funding that, in turn, affect data collection (i.e. 
monitoring), quality (i.e. curation issues), accessibility (i.e. data storage, format), and analysis (i.e. workflow) (e.g. 
HELCOM  BalticDataFlows  project).  When  monitoring  protocols  are  already  available,  stable  funding  is  key  to 
ensure  spatial  and  temporal  consistency  of  the  time  series  collection.  To  this  end,  the  integration  of  novel 
monitoring methods based, for example, on real time satellite observations and molecular approaches has to be 
considered complementary to current monitoring design.  

Finally, joint efforts for peer-review publications would help sharing the scientific challenges of relevance for the 
MSFD pelagic assessment at regional and EU scales. 

Box 5. Secure long-term EU funding at regional scale to: 

• 

• 

• 

o 

o 

o 

allow data exploration and evaluation of regular monitoring data and its extension in areas with low 
spatial and temporal coverage. 

recognize and support groups of taxonomy experts as they are critical for continuing supplying data for 
the MSFD assessment. 

fund RSCs (BAL NEA MED BLK) as: 

regional coordination is ecologically consistent (similar needs of sampling within one region). 

specific funding would engage MS to collaborate giving the means to the RSCs to effectively coordinate 
the sampling strategies. 

streamlined governance at EU level would ensure that (a) the regional sampling coordination serves the 
EU marine policies, and (b) the RSCs collaborate between them for a consistency at EU level (standards, 
sampling strategies, environmental assessments, good practices, data quality/storage/access). 

17 

 
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Marine Strategy Framework Directive, Integration of assessment results. 

20 

 
List of abbreviations and definitions 

ABIOMMED 

Assessment of Biodiversity and Measures across Mediterranean 

BAL 

BLK 

CPR 

EQR 

EU 

Baltic Sea 

Black Sea 

Continuous Plankton Recorder  

Ecological Quality Ratio 

European Union 

EUNOSAT Eutrophication of the North Sea with Satellite data 

GES 

Good Environmental Status 

HELCOM  Helsinki Commission (Helsinki Convention) 

HELCOM BLUES 

 HELCOM Biodiversity, Litter, Underwater noise and Effective regional measures for the Baltic 

Sea 

HOLAS 

Holistic Assessment of Ecosystem Health Status 

JRC 

Joint Research Centre 

JERICO S3  Joint European Research Infrastructure of Coastal Observatories: Science, Service, Sustainability  

JERICO NEXT 

 Joint  European Research  Infrastructure  of  Coastal Observatories:  Novel European  eXpertise 

for coastal observaTorie 

LTER 

Long Term Ecological Research Network 

MS 

Member States 

MSFD  Marine Strategy Framework Directive 

MSTS 

Zooplankton Mean Size and Total Stock 

MWE   Mediterranean Western Mediterranean Sea 

NEA PANACEA 

 North  East  Atlantic  Project  on  Biodiversity  and  Eutrophication  Assessment  Integration  and 

Creation of Effective Measures 

OSPAR  OSPAR Commission (Oslo-Paris Convention) 

RSC 

Regional Sea Convention 

WFD 

Water Framework Directive 

UNEP-MAP 

Barcelona Convention 

21 

 
 
List of boxes 

Box 1. Definition of habitat type for D1C6 ............................................................................ 8 

Box 2. Anthropogenic pressures listed in the GES Decision and linked to D1C6 ...................................10 

Box 3. Workshops on sampling strategies and methods ............................................................16 

Box 4. Workshops on indicators ......................................................................................16 

Box 5. Secure long-term EU funding at regional scale ...............................................................17 

22 

 
 
 
Annexes 

Annex 1. Workshop’s agenda and format 

This first JRC workshop on MSFD pelagic habitats held online on the 9th and 10th March 2021, brought together 
58 participants from 17 EU Member States, including MS nominated experts and Regional Sea Conventions (e.g. 
HELCOM, OSPAR) representatives. 

A Microsoft Team called “GRP-MSFD Pelagic Habitats D1C6 assessment” was created on purpose to share the 
workshop material and foster a collaborative approach. Four channels were created to allow participants working 
in sub-groups. 

Table A1. Workshop’s agenda. 

Tuesday 9th March 2021 

09:30-09:35 

Welcome participants (JRC) 

09:35-09:50 

MSFD policy requirements (JRC) 

09:50-10:10 

Member States’ reports on D1C6 (Arts. 8, 9, 10): gaps and priorities (JRC) 

10:10-10.25 

Presentation of the Objectives and Agenda (JRC) 

10:25-10:40 

Presentation of Objective 1 (JRC): To define pelagic habitats and adapt the criteria elements to the 
scale-specific processes. 

10:40-10:55 

Discussion on Objective 1 (All, plenary) 

10:55-11:15 Break 

Presentation of Objectives 2 and 3 (JRC): 

11:15-11:20 

Objective  2:  To 
physical/chemical characteristics and biological responses.  

identify  the  pelagic  habitats’  direct  and 

indirect  pressures, 

i.e.,  the 

Objective  3:  To  determine  the  appropriate  spatial  and  temporal  scales  of  main  anthropogenic 
pressures within and across marine regions. To prepare recommendations on data gaps (day 2). 

11:20-12:00 

SUB-GROUPS: discussion on Objectives 2 and 3 (groups) 

12:00-12:30 

Summary of sub-groups results (All, plenary) 

12:30-13:30 Lunch break 

13:35-13:45 

Presentation of Objective 4 (JRC): To select the a priori indicators, evaluate their applicability across 
marine  regions  (regional  and  EU-wide)  and  describe  how  they  can  ensure  consistency  of  GES 
assessment  (MSFD  Art.  8)  (relevance  and  feasibility).  To  suggest  paths  for  finding  relationships 
between environmental variables & indicators. 

13:45-14:30 

SUB-GROUPS: discussion on Objective 4 (groups) 

14:30-14:50 Break 

14:50-15:20 

Summary of sub-groups results (All, plenary) 

15:20-16:00 Questions and End of Day 1 

Wednesday10th March 2021 

23 

 
09:30-10:00 

Summary and questions on 1st day meeting (JRC) 

10:00-10:15 

Presentation of Objective 5 (JRC): brainstorming session first by sub-groups 

10:15-11:15 

SUB-GROUPS: discussion on Objective 5 (groups) 

11:15-11:35 Break 

11:35-12:00 

Summary of sub-groups results (All, plenary) 

12:00-13:00 

Presentation recommendation on Objective 5 (All, plenary)  

13:00-14:00 Lunch Break 

14:00-15:50 

SUB-GROUPS: recommendation (groups) 

15:50- 16:00 Follow-up and end of workshop 

Figure A1. Assessment flow for Descriptor 1, pelagic habitats in Magliozzi et al., 2021b. 

24 

 
 
 
 
Figure A2. Vertical limits of pelagic habitats: (a) marine regions with seasonal thermoclines (e.g. Mediterranean 
Sea), (b) marine regions with permanent halocline (e.g. Baltic Sea) (from Magliozzi et al., 2021b). 

25 

 
 
 
 
Figure A3. Horizontal delineation of pelagic habitats: (a) pelagic habitats as described in the MSFD (four habitat 
types: variable salinity, coastal, shelf and oceanic and beyond shelf) (b) description at the scale of variability of 
the coastal and oceanic processes (continuous grid of few km) interpolating most in-situ-based criteria using 
environmental and operational model data such as satellite chlorophyll-a and the Marine Copernicus 
operational physical models (CMEMS5). [CPR: Continuous Plankton Recorder; HAB: Harmful Algal Blooms; NIS: 
Non-Indigenous Species]. (c) sampling frequency of in-situ and satellite/operational model data. Dashed arrows 
relate to spatiotemporal discontinuity and grey colour depicts lower absolute precision (from Magliozzi et al., 
2021b). 

5 https://marine.copernicus.eu/ 

26 

 
 
 
 
Annex 2. Pelagic habitats’ direct and indirect pressures.  

Table A2. Pelagic habitats’ direct and indirect pressures by marine region. The confidence score is provided when the indicators is applicable to the marine region or it is under 
development. 

pressure 

MSFD descriptor and 
criterion 

Non-Indigenous 
Species 

D2C3- Adverse effects of 
Non-Indigenous Species  

MSFD unit 

indicators pre(operational) 

confidence of pressure-indicator relationship (1 to 5, 1 is low) 

reference 

MED 

BAL 

NEA 

BLK 

extent (km2)  Mnemiopsis leidyi biomass  

5 (relevant in the Adriatic Sea) 

Eutrophication 

D5C2- Chlorophyll a 
concentration;  

ug/l  

Chlorophyll-a (Chl-a)  

D5C3- Harmful algal 
blooms;   

D5C4- Photic limit 

no. events, 
duration 
(days), 
extent 
(km2) per 
year 

m  

5 

5 

5 

3 

3 

BSIMAP 2017 

Commission 
Decision (EU) 
2018/229 
HELCOM, 
2018a 
HELCOM, 
2018b 
Ferrera et al., 
2020 
HELCOM, 
2018c 

BSIMAP, 2017 

BSIMAP, 2017 

HELCOM, 
2018d 

OSPAR, 2018 

OSPAR, 2019a 

1 

OSPAR, 2019b 

5 

5 

5 

3 

2 

3 

1 

5 

5 

Chlorophyll-a (Chl-a)  

Cyanobacterial Bloom Index 

1 (not relevant) 

Microbial species indicator 

potentially relevant for NW  

Diatom/Dinoflagellate Index 

Phytoplankton abundance  

1 (not accurate when 
heterotrophic dinoflagellates 
are dominant) 
3 (it gives us the same 
information as Chlorophyll) 

Phytoplankton biomass  

not used 

Seasonal succession 
of Dominating Phytoplankton 
group  

PH1/FW5: Changes in 
Phytoplankton and 
Zooplankton Communities  
PH2: Changes in Phytoplankton 
Biomass and Zooplankton 
Abundance  
PH3: Changes in Plankton 
Diversity  

it does not reflect pressure 
unless you have a time series 
long enough to understand the 
ecological mechanisms behind 
2 under development 

2 under development 

1 under development 

27 

 
 
  
  
 
 
 
 
 
 
 
 
  
  
  
 
  
  
  
 
  
 
  
  
  
  
  
  
  
  
  
  
  
pressure 

MSFD descriptor and 
criterion 

MSFD unit 

indicators pre(operational) 

confidence of pressure-indicator relationship (1 to 5, 1 is low) 

reference 

Zooplankton H-Shannon 

2 under development 

1 under 
development 

BSIMAP, 2017 

MED 

BAL 

NEA 

BLK 

Overfishing 

D3 

Climate change 

? 

4 

4 

4 

3 

Zooplankton abundance  

4 under development 

Zooplankton biomass  

4 under development 

Copepoda biomass  

4 under development 

Noctiluca scintillans biomass  

Zooplankton Mean Size and 
Total Stock 
Fishing Mortality 

CPUE of pelagic fish species 

1 (maybe relevant for coastal 
areas in Eastern Med)  

2 under development 

3 

 5 

 3 

Copepod Mean Size and Total 
Abundance 

3 (potentially relevant in the 
NW) 

Zooplankton Mean Size and 
Total Stock 

 2 under development 

3 

OPFish/OPHarvest  

 4 under development 

Fishing effort / Fishing effort 
fleets overlap 

Distribution change 

Climate refugia 

PH1/FW5: Changes in 
Phytoplankton and 
Zooplankton Communities  

28 

2 under development 

5 

BSIMAP, 2017 

BSIMAP, 2017 

BSIMAP, 2017 

BSIMAP, 2017 

HELCOM, 
2018e 

Stock 
assessments 
(e.g. GFCM) 
Stock 
assessments 
(e.g. GFCM) 
Pitois et al., 
2021 

Druon et al. 
(under review) 

Stock 
assessments 
(e.g. GFCM) 
Pennino et al., 
2020 
Pennino et al. 
2020 

OSPAR, 2018 

 
 
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
pressure 

MSFD descriptor and 
criterion 

Linked with several 
descriptors 

Cumulative 
impacts (areas 
under various 
pressures), e.g. 
eutrophication/
overfishing/clim
ate change 

MSFD unit 

indicators pre(operational) 

confidence of pressure-indicator relationship (1 to 5, 1 is low) 

reference 

MED 

BAL 

NEA 

BLK 

2 under development 

2 under development 

4 

2 

2 under development (see 
comment) 

PH2: Changes in Phytoplankton 
Biomass and Zooplankton 
Abundance  
PH3: Changes in Plankton 
Diversity  

Surface of persistent optimal 
environmental areas 
Surface of safe operational 
space 
Combination of multiple 
biodiversity and evenness 
indices (Shannon-Wiener's 
index, Simpson's index, Berger-
Parker's index, McNaughton's 
index) 

OSPAR, 2019a 

OSPAR, 2019b; 
Villarino et al. 
2020 
Ramirez et al. 
2021 

Ramirez et al. 
2021 

Ferrera et al., 
2020, Varkitzi 
et al., 2018, 
Cozzoli et al., 
2017, Francé et 
al., 2021. 

anomalous jelly fish blooms 

3 (species-specific to 
subregions) 

Table A3. Indicators’ temporal and spatial sampling (e.g. frequency and duration, sampling coverage) by pressure and marine region. 

pressure 

indicator 

data type 

indicator temporal and spatial sampling (frequency and duration, sampling coverage) 

MED 

BAL 

NEA 

BLK 

Eutrophication 

Chlorophyll-a (Chl-a)  

in-situ 

bi-weekly to 
monthly, good to 
complement with 
CPR data 

warm season (May-
September) 

Italy: monthly transects in 
eutrophicated area / bi-
monthly in less 
eutrophicated area with 
fixed (54 transects). 
Slovenia: monthly at 
sampling stations 
representative for water 
bodies. France: monthly at 
coastal sampling stations, 
monthly to seasonally in 

29 

 
 
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
pressure 

indicator 

data type 

indicator temporal and spatial sampling (frequency and duration, sampling coverage) 

MED 

BAL 

NEA 

BLK 

Eutrophication 

Chlorophyll-a (Chl-a)  

Eutrophication 

Cyanobacterial Bloom Index 

Eutrophication 

Diatom/Dinoflagellate Index 

in-situ,  
satellite 

in-situ,  
satellite 
in-situ 

Eutrophication 

Phytoplankton abundance  

in-situ 

Eutrophication 

Phytoplankton biomass  

in-situ 

Eutrophication 

Seasonal Succession 
of Dominating Phytoplankton 
group  

offshore water. Greece: 
monthly to seasonal 
sampling in coastal waters, 
seasonal sampling in 
offshore waters (fixed point 
stations). 
Relative variation respect to 
2012-2017 vs 2004-2010 
Chlorophyll a data in Italy  

not relevant 

under development 

Italy: transects monthly in 
eutrophicated area / bi-
monthly in less 
eutrophicated area (54 
transects), with fixed 
sampling stations with two 
sampling points: surface 
layer and DCM. Two size 
classes. Greece: monthly to 
seasonal sampling in 
selected coastal areas, 
seasonal sampling in 
offshore waters (fixed point 
stations). Slovenia: monthly 
at one LTER station. 
not used 

under development 

30 

NO use of satellite data - 
under development 

under development 

warm season (May-
September) 

warm season (May-
September) 

 
 
  
 
  
  
 
  
  
  
  
  
  
 
  
  
 
pressure 

indicator 

data type 

indicator temporal and spatial sampling (frequency and duration, sampling coverage) 

MED 

BAL 

NEA 

BLK 

Eutrophication 
/climate change 

PH1/FW5: Changes in 
Phytoplankton and Zooplankton 
Communities  

in-situ 

under development 

PH2: Changes in Phytoplankton 
Biomass and Zooplankton 
Abundance  

in-situ, satellite 
(phytoplankton) 

under development 

PH3: Changes in Plankton 
Diversity  

in-situ 

under development 

Eeutrophication 
/physical hydro-
climatic 
changes/climate 
change 

Eutrophication 
/physical hydro-
climatic 
changes/climate 
change 

31 

Samples from 1958 
- present for CPR 
but shorter for fixed 
point t-s. A 
combination of CPR 
and fixed-point 
stations. Monthly 
data required for 
indicator. 

Samples from 1958 - 
present for CPR but shorter 
for fixed point t-s (though 
may be more frequent). A 
combination of CPR and 
fixed-point stations used. 
Monthly data required for 
indicator. 

Samples from 1958 
- present for CPR 
but shorter for fixed 
point t-s. A 
combination of CPR 
and fixed- point 
stations. Monthly 
data required for 
indicator. 

Samples from 1958 - 
present for CPR but shorter 
for fixed point t-s (though 
may be more frequent). A 
combination of CPR and 
fixed- point stations used. 
Monthly data required for 
indicator. Remote sensing 
data useful for 
phytobiomass, increasing 
spatial coverage. 

Samples from 1958 
- present for CPR 
but shorter for fixed 
point t-s. A 
combination of CPR 
and fixed- point 
stations. Monthly 
data required for 
indicator. 

Samples from 1958 - 
present for CPR but shorter 
for fixed point t-s (though 
may be more frequent). A 
combination of CPR and 
fixed- point stations used. 
Monthly data required for 
indicator.  

 
 
 
 
 
pressure 

indicator 

data type 

indicator temporal and spatial sampling (frequency and duration, sampling coverage) 

MED 

BAL 

NEA 

BLK 

Eeutrophication 

Zooplankton H-Shannon 

in-situ 

under development 

Eutrophication 

Zooplankton abundance  

in-situ 

Eutrophication 

Zooplankton biomass  

Eutrophication 

Copepoda biomass  

Eutrophication 

Noctiluca scintillans biomass  

in-situ 

in-situ 

in-situ 

Italy: seasonal (not linked to 
eutrophication-(54 
transects); 3 size class. 

Monitoring starting in 2021 

under development 

abundance - transects 
monthly in eutrophicated 
area / bi-monthly in less 
eutrophicated area (54 
transects) 

Overfishing, 
eutrophication 

Zooplankton Mean Size and 
Total Stock 

in-situ 

seasonal samples, under 
development 

Non-Indigenous 
Species 

Mnemiopsis leidyi biomass  

in-situ 

abundance – spp. sampled, 
but not indicators developed 

There are data, under 
testing, threshold values 
to be established 

warm and cold season 

warm and cold season 

warm and cold season 

warm and cold season 

Table A4. Pressures’ temporal and spatial sampling (e.g. range m to km, days, weeks, months) by marine region. 

pressure 

indicator 

pressure temporal and spatial scale of variability (range m to km, days, weeks, months) 

MED 

BAL 

NEA 

BLK 

Eutrophication 

Chlorophyll-a (Chl-a)  

3, 6, 12 miles from the 
coast (MSFD) data 
integrated with WFD/ 200 
M - 1 NM - monitoring 
programmes under WFD, 
(also hydrographical and 
chemical parameters are 
monitored in Greece and 
in Italy). 

32 

coastal, variable salinity and 
shelf waters (0-200m isobath)  

 
 
  
  
  
  
 
  
  
  
  
  
  
  
  
 
  
  
 
 
 
  
  
pressure 

indicator 

pressure temporal and spatial scale of variability (range m to km, days, weeks, months) 

MED 

BAL 

NEA 

BLK 

Eutrophication 

Chlorophyll-a (Chl-a)  

Physico-chemical 
parameters are sampled 
along with Chl-a (Slovenia) 

Relative variation respect 
to 2012-2017 vs 2004-
2010 Chlorophyll a data in 
Italy  

Eutrophication 
Eutrophication 

Eutrophication 

Cyanobacterial Bloom Index 
Diatom/Dinoflagellate Index 

not relevant in MED 
under development 

Phytoplankton abundance  

Eutrophication 

Phytoplankton biomass  

3, 6, 12 miles from the 
coast (MSFD) data 
integrated with WFD/ 200 
M - 1 NM - monitoring 
programmes under WFD 
(also hydrographical and 
chemical parameters are 
monitored in Greece) 
Physico-chemical 
parameters are sampled 
along with phytoplankton 
abundance (Slovenia) 
not used 

33 

NO use of satellite data - under 
development 

not relevant in BLK 
under development 

coastal, variable salinity and 
shelf waters (0-200m isobath)  

warm season (May-September) 

 
 
 
 
  
  
  
  
  
  
  
  
  
  
pressure 

indicator 

pressure temporal and spatial scale of variability (range m to km, days, weeks, months) 

MED 

BAL 

NEA 

BLK 

Eutrophication 

Seasonal Succession 
of Dominating Phytoplankton 
group  

under development 

Eutrophication /climate 
change 

PH1/FW5: Changes in 
Phytoplankton and Zooplankton 
Communities  

under development 

Climate data at regional 
scale. Nutrient data 
shorter time-series and 
more spatially constricted, 
but often coinciding with 
fixed-point stations 

Eutrophication /physical 
hydro-climatic 
changes/climate change 

PH2: Changes in Phytoplankton 
Biomass and Zooplankton 
Abundance  

under development 
Physico-chemical 
parameters sampled along 
with phytoplankton 
community composition 
(Slovenia) 

Climate data at regional 
scale. Nutrient data 
shorter time-series and 
more spatially constricted, 
but often coinciding with 
fixed-point stations 

Climate data at regional 
scale (multidecadal). 
Nutrient data shorter 
time-series (<20 years) 
and more spatially 
constricted than climate, 
but often coinciding with 
fixed-point stations.  

Climate data at regional 
scale (multidecadal). 
Nutrient data shorter 
time-series (<20 years) 
and more spatially 
constricted than climate, 
but often coinciding with 
fixed-point stations.  

34 

 
 
 
 
  
  
 
 
 
 
pressure 

indicator 

pressure temporal and spatial scale of variability (range m to km, days, weeks, months) 

Eutrophication /physical 
hydro-climatic 
changes/climate change 

PH3: Changes in Plankton 
Diversity  

MED 

BAL 

NEA 

BLK 

under development (also 
hydrographical and 
chemical parameters are 
monitored in Greece) 

Climate data at regional 
scale. Nutrient data 
shorter time-series and 
more spatially constricted, 
but often coinciding with 
fixed-point stations 

Climate data at regional 
scale (multidecadal). 
Nutrient data shorter 
time-series (<20 years) 
and more spatially 
constricted than climate, 
but often coinciding with 
fixed-point stations. 

Eutrophication 

Zooplankton H-Shannon 

  under development 

Eutrophication 

Zooplankton abundance  

Eutrophication 

Zooplankton biomass  

3, 6, 12 miles from the 
coast (MSFD)  

Monitoring starting in 
2021 

Eutrophication 

Copepoda biomass  

under development 

Eutrophication 

Noctiluca scintillans biomass  

Overfishing, eutrophication 

Zooplankton Mean Size and 
Total Stock 

Non-Indigenous Species 

Mnemiopsis leidyi biomass  

3, 6, 12 miles from the 
coast (MSFD) data 
integrated with WFD/ 200 
M - 1 NM - monitoring 
programmes under WFD 

under development 

abundance -sampled, but 
not indicators developed 

35 

coastal, variable salinity and 
shelf waters (0-200m isobath)  

coastal, variable salinity and 
shelf waters (0-200m isobath)  

coastal, variable salinity and 
shelf waters (0-200m isobath)  

coastal, variable salinity and 
shelf waters (0-200m isobath)  

coastal, variable salinity and 
shelf waters (0-200m isobath)  

 
 
 
 
 
 
  
  
  
  
 
  
  
  
  
  
  
 
  
  
 
  
  
 
 
 
Table A5. Pressures’ temporal and spatial sampling (e.g. range m to km, days, weeks, months) by marine region. 

pressure 

indicator 

comments on current data gaps 

MED 

BAL 

NEA 

BLK 

Eutrophication 

Chlorophyll-a (Chl-a) -in situ 

coverage depends on 
the MS 

Eutrophication 

Cyanobacterial Bloom Index 

not relevant 

Eutrophication 

Diatom/Dinoflagellate Index 

Eutrophication 

Phytoplankton abundance  

not promising results 
so far 
2-6 times per year 
depending on the 
area 
not used 

Eutrophication 

Eutrophication 

Eutrophication /climate change 

Phytoplankton biomass  

Seasonal Succession 
of Dominating Phytoplankton 
group  

2-6 times per year 
depending on the 
area 

PH1/FW5: Changes in 
Phytoplankton and Zooplankton 
Communities  

2-6 times per year 
depending on the 
area 

Eutrophication /physical hydro-
climatic changes/climate change 

PH2: Changes in Phytoplankton 
Biomass and Zooplankton 
Abundance  

2-6 times per year 
depending on the 
area 

Spatial gaps, not all time-series capture all 
lifeforms, time-series are different lengths, 
small phytoplankton are not well sampled, 
few zooplankton time-series, pico-nano 
component not often sampled (and 
lifeforms not developed).  *** The priority is 
preserving existing time-series over starting 
new ones*** 
Spatial gaps, time-series are different 
lengths, few zooplankton time-series.  *** 
The priority is preserving existing time-series 
over starting new ones*** 

36 

 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
pressure 

indicator 

comments on current data gaps 

MED 

BAL 

NEA 

BLK 

Spatial gaps, not all time-series go to genus 
level, time-series are different lengths, small 
phytoplankton are not well sampled, few 
zooplankton time-series, pico-nano 
component not often sampled.  *** The 
priority is preserving existing time-series 
over starting new ones*** 

Eutrophication /physical hydro-
climatic changes/climate change 

PH3: Changes in Plankton 
Diversity  

2-6 times per year 
depending on the 
area 

Eutrophication 

Zooplankton H-Shannon 

Eutrophication 

Zooplankton abundance  

Eutrophication 

Zooplankton biomass  

Eutrophication 

Copepoda biomass  

Eutrophication 

Noctiluca scintillans biomass  

Overfishing, eutrophication 

Zooplankton Mean Size and 
Total Stock 

Non-Indigenous Species 

Mnemiopsis leidyi biomass  

Slovenia: no on-going 
monitoring for 
zooplankton 
Slovenia: no on-going 
monitoring for 
zooplankton 
Slovenia: no on-going 
monitoring for 
zooplankton 
Slovenia: no on-going 
monitoring for 
zooplankton 

Slovenia: no on-going 
monitoring for 
zooplankton 

37 

 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
 
  
  
  
 
 
 
 
Annex 3. Indicators’ selection at regional and EU-wide scales.  

Table A6. Indicators’ applicability across marine regions and linkages with environmental variables. 

indicator 

region 

scale of 
application  

threshold 
scale 

methods for threshold 

ecological and environmental variables (biotic and abiotic) 

MED 

BAL 

NEA 

BLK 

Chlorophyll-a (Chl-
a) 

MED 

EU 

REGIONAL 

Deviation from baseline 

Chlorophyll-a (Chl-
a) 
Cyanobacterial 
Bloom Index 

BAL 

BAL 

EU 

EU 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

daily satellite Chl-a, 
SST, nutrients, 
salinity, oxygen 
(when available), 
Secchi disk depth 
daily satellite Chl-a 

daily satellite Chl-
a 

daily satellite Chl-
a 

satellite Chl-a, 
SST  

satellite Chl-a 

Zooplankton, Wind 
speed/weather 
conditions?, SST, 
salinity?, 
Phosphorus pool, 
summer and/or 
winter? 
satellite Chl-a, SST, 
Silica 
concentration?, 
winter SST? 
Salinity?, N/P ratio? 

Diatom/Dinoflagella
te Index 

BAL 

BLK 

BLK 

BAL 

Phytoplankton 
abundance 
Phytoplankton 
biomass 
Seasonal Succession 
of Dominating 
Phytoplankton 
group 

EU 

EU 

EU 

EU 

REGIONAL 

Deviation from baseline 

satellite Chl-a, SST  

REGIONAL 

Deviation from baseline 

satellite Chl-a, SST, 
nutrients 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

satellite Chl-a, SST,  
nutrients 

satellite Chl-a, SST, 
salinity?, Nutrients? 

satellite Chl-a, 
SST  

38 

 
 
 
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
indicator 

region 

scale of 
application  

threshold 
scale 

methods for threshold 

ecological and environmental variables (biotic and abiotic) 

NEA 

EU 

REGIONAL 

PH1/FW5: Changes 
in Phytoplankton 
and Zooplankton 
Communities  

NEA 

EU 

REGIONAL 

No thresholds yet, new 
project (NEA PANACEA) 
to explore if we will set 
them and how.  
Identifying drivers of 
change is important. A t-s 
can be in GES if changes 
are because of natural 
variability, but not 
because of anthropogenic 
pressure. 
Velocity of change should 
also be investigated. This 
can also reveal 
synchrony. 
see above 

MED 

BAL 

NEA 

BLK 

satellite Chl-a, Chl-a 
horizontal gradient, 
SST, nutrients 

SST, oscillations 
(eg NAO), pH 
change, 
nutrients 

satellite Chl-a, 
Chl-a horizontal 
gradient 

satellite Chl-a, Chl-a 
horizontal gradient, 
SST,nutrients 

see above 

satellite Chl-a, 
Chl-a horizontal 
gradient 

NEA 

BLK 

BLK 

BLK 

EU 

EU 

EU 

EU 

REGIONAL 

see above 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

satellite Chl-a, Chl-a 
horizontal gradient 

satellite Chl-a, Chl-a 
horizontal gradient 

satellite Chl-a, Chl-a 
horizontal gradient 

satellite Chl-a, Chl-a 
horizontal gradient 

see above 

satellite Chl-a, 
Chl-a horizontal 
gradient 
satellite Chl-a, 
Chl-a horizontal 
gradient 
satellite Chl-a, 
Chl-a horizontal 
gradient 
satellite Chl-a, 
Chl-a horizontal 
gradient 

39 

PH2: Changes in 
Phytoplankton 
Biomass and 
Zooplankton 
Abundance 
(Copepod 
abundance) 
PH3: Changes in 
Plankton Diversity  

Zooplankton H-
Shannon 

Zooplankton 
abundance  

Zooplankton 
biomass  

 
 
  
  
  
  
  
  
  
  
  
indicator 

region 

scale of 
application  

threshold 
scale 

methods for threshold 

ecological and environmental variables (biotic and abiotic) 

MED 

BAL 

NEA 

BLK 

satellite Chl-a, SST, 
salinity, size of 
hypoxic layer? 

satellite Chl-a, 
Chl-a horizontal 
gradient 
satellite Chl-a, 
Chl-a horizontal 
gradient 
satellite Chl-a, 
SST (operational 
and high) 
SST 

Copepoda biomass  

BLK 

Zooplankton Mean 
Size and Total Stock 

BAL 

Noctiluca scintillans 
biomass  

BLK 

Mnemiopsis leidyi 
biomass  
Mnemiopsis leidyi 
biomass 

Anomalous jelly fish 
blooms (species-
specific to 
subregions 
Microbial species 
indicator (pico-nano 
plankton diversity) 

BLK 

MED 

MED 

MED 

EU 

EU 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

REGIONAL 

REGIONAL 

Deviation from baseline 
and expert judgement 

REGIONAL 

REGIONAL 

Literature 

REGIONAL 

REGIONAL 

trends (timeseries length 
to be discussed) 

SUB-
REGIONAL 

SUB-
REGIONAL 

trends (timeseries length 
to be discussed) 

SUB-
REGIONAL 

can be SUB-
REGIONAL 

not set yet (to be 
discussed) 

Ratio of microbial 
biomass 

MED 

SUB-
REGIONAL 

can be SUB-
REGIONAL 

not set yet (to be 
discussed) 

satellite Chl-a, Chl-a 
horizontal gradient 

satellite Chl-a, Chl-a 
horizontal gradient 

satellite Chl-a, SST 
(operational and 
high) 
SST 

SST, satellite Chl-a, 
increasing trophic 
potential for 
zooplankton) 
SST, satellite Chl-a, 
zooplankton biomass 

temperature, salinity, 
nutrients (gradient 
from coast to open 
ocean) 
temperature, salinity, 
nutrients (gradient 
from coast to open 
ocean) 

CPUE of pelagic fish 
species 

Fishing Mortality 
Fishing effort / 
Fishing effort fleets 
overlap 

Distribution change 

MED 

MED 

MED 

MED 

40 

 
 
  
  
  
  
  
  
  
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
  
  
  
 
 
 
  
  
  
  
 
 
 
  
  
  
  
 
 
 
  
  
  
  
indicator 

region 

scale of 
application  

threshold 
scale 

methods for threshold 

ecological and environmental variables (biotic and abiotic) 

MED 

BAL 

NEA 

BLK 

MED 

MED 

MED 

MED 

Climate refugia 
Surface of 
persistent optimal 
environmental 
areas 
Surface of safe 
operational space 
Combination of 
multiple 
biodiversity and 
evenness indices 
(Shannon-Wiener's 
index, Simpson's 
index, Berger-
Parker's index, 
McNaughton's 
index) 

SUB-
REGIONAL 

SUB-
REGIONAL 
(AT LEAST) 

deviation from baseline 

satellite Chl-a, SST, 
nutrients, salinity, 
oxygen (when 
available), Secchi disk 
depth 

41 

 
 
 
 
 
  
  
  
  
 
 
 
  
  
  
  
 
 
 
  
  
  
  
  
  
  
 
 
 
Table A7. Methods for linking the indicator with spatio-temporal env. variable(s) (e.g. strengths and significance of relationships, spatial clustering, geostatistical analysis etc.) 

indicator 

region 

scale of 
application  

threshold 
scale 

methods for threshold 

methods for linking the indicator with spatio-temporal env. variable(s) (e.g. 
strength and significance of relationships, spatial clustering, geostatistical analysis 
etc.) 

MED 

BAL 

NEA 

BLK 

Chlorophyll-a (Chl-
a) 

MED 

EU 

SUB-
REGIONAL 

Relation to pressures 
(outcome of MEDGIG) 

Strong relation to 
nitrogen and 
phosphorus in 
Aegean coastal 
waters (Greece). 
Adriatic Sea: good 
correlation between 
Chl-a and Total 
Phosphorus 

provided a good 
intercalibration 
between the in-situ 
Chl-a and satellite 
data, medium to 
strong correlation is 
expected 

BAL 

BAL 

BAL 

BLK 

BLK 

BAL 

Chlorophyll-a (Chl-
a) 
Cyanobacterial 
Bloom Index 

Diatom/Dinoflagella
te Index 

Phytoplankton 
abundance 
Phytoplankton 
biomass 
Seasonal Succession 
of Dominating 
Phytoplankton 
group 

EU 

EU 

EU 

EU 

EU 

EU 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

medium-to-low, 
potential 
correlations -> need 
evaluation 

potential 
correlations -> need 
evaluation 

Diatom/Dinofl. in 
relation to 
salinity gradient 

REGIONAL 

Deviation from baseline 

low 

42 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
indicator 

region 

scale of 
application  

threshold 
scale 

methods for threshold 

methods for linking the indicator with spatio-temporal env. variable(s) (e.g. 
strength and significance of relationships, spatial clustering, geostatistical analysis 
etc.) 

MED 

BAL 

NEA 

BLK 

NEA 

EU 

REGIONAL 

PH1/FW5: Changes 
in Phytoplankton 
and Zooplankton 
Communities  

No thresholds yet, new 
project (NEA PANACEA) 
to explore if we will set 
them and how.  
Identifying drivers of 
change is important. A t-s 
can be in GES if changes 
are because of natural 
variability, but not 
because of anthropogenic 
pressure. 
Velocity of change should 
also be investigated. This 
can also reveal 
synchrony. 
see above 

testing 
sensitivity and 
using all t-s 
together by 
selecting 
current 
assessment 
period as 
reference 
period and 
looking 
backwards 

see above 

NEA 

EU 

REGIONAL 

PH2: Changes in 
Phytoplankton 
Biomass and 
Zooplankton 
Abundance 
(Copepod 
abundance) 
PH3: Changes in 
Plankton Diversity  
Zooplankton H-
Shannon 
Zooplankton 
abundance  
Zooplankton 
biomass  
Copepoda biomass  

Zooplankton Mean 
Size and Total Stock 

NEA 

BLK 

BLK 

BLK 

BLK 

BAL 

EU 

EU 

EU 

EU 

EU 

EU 

REGIONAL 

see above 

see above 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

REGIONAL 

Deviation from baseline 

low, need testing 

Noctiluca scintillans 
biomass  

BLK 

REGIONAL 

REGIONAL 

Deviation from baseline 
and expert judgement 

43 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
indicator 

region 

scale of 
application  

threshold 
scale 

methods for threshold 

methods for linking the indicator with spatio-temporal env. variable(s) (e.g. 
strength and significance of relationships, spatial clustering, geostatistical analysis 
etc.) 

MED 

BAL 

NEA 

BLK 

BLK 

MED 

MED 

MED 

MED 

MED 

MED 

MED 

MED 

MED 

MED 

MED 

MED 

Mnemiopsis leidyi 
biomass  
Mnemiopsis leidyi 
biomass 

anomalous jelly fish 
blooms (species-
specific to 
subregions 
Microbial species 
indicator (pico-nano 
plankton diversity) 
Ratio of microbial 
biomass 

CPUE of pelagic fish 
species 

Fishing Mortality 
Fishing effort / 
Fishing effort fleets 
overlap 

Distribution change 

Climate refugia 
Surface of 
persistent optimal 
environmental 
areas 
Surface of safe 
operational space 
Combination of 
multiple 
biodiversity and 
evenness indices 
(Shannon-Wiener's 
index, Simpson's 

REGIONAL 

REGIONAL 

Literature 

REGIONAL 

REGIONAL 

trends (timeseries length 
to be discussed) 

SUB-
REGIONAL 

SUB-
REGIONAL 

trends (timeseries length 
to be discussed) 

SUB-
REGIONAL 

can be SUB-
REGIONAL 

not set yet (to be 
discussed) 

SUB-
REGIONAL 

can be SUB-
REGIONAL 

not set yet (to be 
discussed) 

SUB-
REGIONAL 

SUB-
REGIONAL 
(AT LEAST) 

deviation from baseline 

Non-linear 
relationship between 
indices and pressure 
categories 

44 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
indicator 

region 

scale of 
application  

threshold 
scale 

methods for threshold 

methods for linking the indicator with spatio-temporal env. variable(s) (e.g. 
strength and significance of relationships, spatial clustering, geostatistical analysis 
etc.) 

MED 

BAL 

NEA 

BLK 

index, Berger-
Parker's index, 
McNaughton's 
index) 

45 

 
 
 
 
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doi:10.2760/081368 

ISBN 978-92-76-35958-6