Understanding the State of
the Ocean:
A Global Manual on Measuring SDG 14.1.1, SDG 14.2.1
and SDG 14.5.1
2021

© 2021, United Nations Environment ProgrammeISBN No: 978-92-807-3786-8
Job No: DEW/2284/NA

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A Global Manual on Measuring SDG 14.1.1, SDG 14.2.1 and SDG 14.5.1. Nairobi.

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Understanding the State of
the Ocean:
A Global Manual on Measuring SDG 14.1.1, SDG 14.2.1
and SDG 14.5.1

Foreword
Historically, gathering data on oceans could only bedone by oceanographic research vessels. However,today, remote sensing, citizen science and advanced
modelling techniques provide new opportunities forbetter understanding the oceans.
In 2015, the world agreed on an ambitious plan tosecure our ability to develop in a sustainable way whilesafeguarding our planet’s capacity to sustain us. A
healthy ocean is a central element to this Agenda.
It underpins much of our sustainable development
Healthy, well-managed oceans are central toefforts, including those to eliminate poverty, hunger

sustainable development and the future of the planet.

and ensure health and well-being for all. The

Covering almost three quarters of the Earth’s surface,

Sustainable Development Goal (SDG) framework

the ocean contains 97% of its water and supports every

recognizes the importance of monitoring oceans withlife form that inhabits it. The ocean produces overa dedicated goal on oceans (SDG 14). This includes

half of the oxygen in the atmosphere and regulates

targets dedicated to coastal eutrophication and marine

the Earth’s climate. It is crucial to the global economy,debris, marine area management and conservation.

supporting key industries such as fisheries, transport,
trade and tourism.

This report aims to provide guidance on how to bring
together traditional monitoring techniques with new

Our impact on the ocean is immense and we needtechnologies and data science in order to betterto urgently turn around its destruction. In order tomonitoring our oceans in the context of the SDGs. The

sustainably manage and protect oceans, we needreport focuses on the SDG indicators where UNEP is

to better understand the oceans. What is the state

the custodian and responsible for global monitoring,of pollution, ecosystem health and biodiversity?

including SDG 14.1.1(a) on coastal eutrophication; SDG

How is pollution impacting ecosystems and where?

14.1.1(b) on marine debris, SDG 14.2.1 on marine area

Are our efforts to curb nutrient and plastic pollution

management and SDG 14.5.1 on protected areas andworking in the way that we would expect? Who areconservation. We hope that this guide will not only

the winners and losers in terms of where pollution

support governments and other stakeholders to better

accumulates? How does pollution from one country

monitor, but also to develop policies that improve theimpact other countries and the rest of the world? In

health of our oceans.

order to answer these questions, there is a need forcomparable data which allows analysis of the ocean as
a complete system.
Unfortunately, there are major gaps in our knowledge
when it comes to oceans. Due to the vast sizeof marine ecosystems and the lack of access to

Jian Liu

remote marine areas, marine research and data

Director, Science Divisioncollection is expensive and logistically challenging.

United Nations Environment ProgrammeTable of Contents
LIST OF FIGURES................................................................................................................................ VII
LIST OF TABLES................................................................................................................................. VIIIACKNOWLEDGEMENTS........................................................................................................................ IX
LIST OF ACRONYMS............................................................................................................................ XILIST OF REGIONAL SEAS PROGRAMMES........................................................................................... XIV
EXECUTIVE SUMMARY......................................................................................................................... 1

PART 1 | Context of Understanding the State of the Ocean: A Global Manual on
Measuring SDG 14.1.1, SDG 14.2.1 and SDG 14.5.1

7

Sustainable Development Goals and indicators..................................................................................... 7
Data and information flows for reporting on SDG indicators................................................................... 8
Complexities of ocean monitoring and marine indicators....................................................................... 9
About Understanding the State of the Ocean: A Global Manual on Measuring SDG 14.1.1,
SDG 14.2.1 and SDG 14.5.................................................................................................................... 10
Progressive monitoring approach........................................................................................................ 10
Definitions.......................................................................................................................................... 11

PART 2 | Step-by-step guides to indicator implementation

14

Indicator 14.1.1a: Index of Coastal Eutrophication (including ICEP)..................................................... 14
Background................................................................................................................................................................ 14
Proposed indicators for SDG reporting................................................................................................................. 14
Step-by-step guide to implementing the indicator.................................................................................... 17
Level 1: Indicator for coastal eutrophication potential ...................................................................................... 17
Level 1: Chlorophyll-A deviation modelling........................................................................................................... 19
Level 2: In situ monitoring of nutrients.................................................................................................................. 24
Level 2: National ICEP modelling............................................................................................................................ 24
Indicator 14.1.1.b: Marine plastic debris.............................................................................................. 25
Background................................................................................................................................................................ 25
Proposed indicators for SDG reporting................................................................................................................. 26
Step-by-step guide to implementing the indicator.................................................................................... 28
Level 1: Plastic patches greater than 10 meters................................................................................................. 28
Level 1: Beach litter originating from national land-based sources................................................................. 28
Level 2: Beach litter (average count of plastic items per km2).......................................................................... 29
Level 2: Floating plastics (average count of plastic items per km2)................................................................. 30
Level 2: Water column plastics (average count of plastic items per km3)...................................................... 31
Level 2: Seafloor litter (average count of plastic items per km2)...................................................................... 33

Understanding the State of the Oceanv

Indicator 14.2.1: Number of countries using ecosystem-based approaches to manage
marine areas....................................................................................................................................... 34
Background................................................................................................................................................................ 34
Proposed indicators for SDG reporting................................................................................................................. 34
Step-by-step guide to implementing the indicator.................................................................................... 35
Level 2: Ecosystem-based approaches to manage marine areas in place .................................................... 35
Level 3: Ecological parameters (e.g. state of biodiversity, water quality, habitat quality,
ecosystem health).................................................................................................................................................... 36
Indicator 14.5.1: Coverage of protected areas in relation to marine areas............................................... 37
Background................................................................................................................................................................ 37
Proposed indicators for SDG reporting................................................................................................................. 37
Step-by-step guide to implementing the indicator.................................................................................... 39
Level 1 / 2: Coverage of marine and coastal areas by protected areas........................................................... 39
Level 3: Other elements of Target 14.5.................................................................................................................. 41
Findings on the bigger picture of SDG 14 – from national implementation to global monitoring.............43
Implementing SDG indicators at country level..................................................................................................... 43
Coordinated international monitoring of transboundary issues....................................................................... 44
Globally applicable methodologies to track global progress............................................................................. 44

REFERENCES...................................................................................................................................... 46

APPENDIX 1: Summary tables of existing indicator compilation (Regional Seas Programmes)............. 53
APPENDIX 2: Summary of regional seas and other relevant data collection efforts............................... 56
SDG Indicator 14.1.1a............................................................................................................................... 56
SDG Indicator 14.1.1.b.............................................................................................................................. 60
SDG Indicator 14.2.1................................................................................................................................. 64
SDG Indicator 14.5.1 ................................................................................................................................ 66
APPENDIX 3: Country case studies and examples................................................................................ 70
SDG Indicator 14.1.1a............................................................................................................................... 70
SDG Indicator 14.1.1b............................................................................................................................... 73
SDG Indicator 14.2.1................................................................................................................................. 75
SDG Indicator 14.5.1................................................................................................................................. 80
Pilot testing acknowledgements.............................................................................................................. 81

Understanding the State of the OceanviList of Figures
Figure 1: Illustration of the 17 SDGs across the three spheres of sustainable development:
biosphere, society and economy. ....................................................................................................................7
Figure 2: Anticipated Sustainable Development Goal data flow and reporting process...............................8
Figure 3: Summary of SDG 14.1.1a sub indicator levels ..............................................................................15
Figure 4: Process for Calculating the Annual Chlorophyll-a Deviations.......................................................21
Figure 5: Process for Calculating the Intra-annual EEZ Chlorophyll-a Anomalies.......................................22
Figure 6: Spatial distribution of progress in the implementation of ICZM for the period of
1999-2014 in Colombia..................................................................................................................................76

Understanding the State of the Oceanvii

List of Tables
Table 1: SDG 14 Targets for which UNEP is the custodian agency of the indicators. ..................................3
Table 2: Monitoring parameters for eutrophication to track progress against SDG Indicator 14.1.1a.......16
Table 3: Examples of the data needed to quantify nutrient export by rivers that is used in
ICEP estimates...............................................................................................................................................18
Table 6: Monitoring parameters for marine plastic litter to track progress against
SDG Indicator 14.1.1b....................................................................................................................................27
Table 7: Monitoring methods for floating plastics........................................................................................30
Table 8: Monitoring methods for water column plastics..............................................................................32
Table 9: Monitoring methods for seafloor litter............................................................................................33
Table 10: Monitoring parameters for implementation of the ecosystem-approach to track progressagainst SDG Target 14.2................................................................................................................................35
Table 11: Monitoring parameters to track progress against SDG Target 14.5. ..........................................38
Table 12: A summary of attributes of biodiversity importance included in widely known and usedprioritisation schemes for conservation. ......................................................................................................41
Table 13: Summary of eutrophication indicators and assessment criteria currently used by
Regional Seas Programmes and other key intergovernmental, international or regional bodies...............58
Table 14: Available guidance material for beach litter monitoring produced by Regional Seas
Programmes and other intergovernmental, international, regional bodies or national bodies...................61
Table 15: Summary of marine plastic debris indicators currently used by Regional Seas
Programmes and other key intergovernmental, international or regional bodies........................................63
Table 16: Summary of ecosystem approach indicators and assessment criteria currently used by
Regional Seas Programmes and other key intergovernmental, international or regional bodies...............65
Table 17: Key criteria of existing indicators, assessment criteria or reporting requirements related
to MPAs that are currently used by Regional Seas Programmes and by GEF-TWAP...................................66
Table 18: Summary of MPA coverage indicators and assessment criteria currently used by
Regional Seas Programmes and other key intergovernmental, international or regional bodies. .............68

Understanding the State of the Ocean

viii

Part 1

Table of contents

Part 2

SectionAc

Acknowledgements

Understanding the State of the Ocean: A Global Manual on Measuring SDG 14.1.1, SDG 14.2.1 and, SDG 14.5.1
has been jointly prepared by the UNEP and UNEP-WCMC.

Core drafting team
The Manual was drafted by a core team of lead authors consisting of Jillian Campbell (UNEP),
Laura Friedrich (UNEP-WCMC) and Sarah Ivory (UNEP-WCMC).

Contributors and overall coordination
The Manual was produced under the overall guidance of Jian Liu, Director of the Science Division andChief Scientist of UNEP. Additionally, the following UNEP-WCMC and UNEP staff were involved: fromthe World Conservation Monitoring Centre (UNEP-WCMC): Katherine Despot-Belmonte, Fiona Danks,
Steve Fletcher, Corinne S. Martin, Hilary Allison, Heather Bingham, Philip Bubb, Neil Burgess, Sanae Chiba,
Lisa Ingwall-King, Edward Lewis, Chris Mcowen, Sarah Morris, Hazel Thornton, Josie Wastell, andLauren V. Weatherdon. From the United Nations Environment Programme: Brennan Van Dyke,
Ludgarde Coppens, Christopher Cox, Heidi Savelli-Soderberg, Kanako Hasegawa, Takehiro Nakamura,David Marquis, Elisabetta Bonotto, Ole Vestergard, Rachel Kosse, Feng Wang, Dixon Waruinge,
Diana Ngina, Francesco Gaetani, Angeline Djampou, and Lev Neretin.
The core drafting team wishes to particularly thank the following colleagues from various affiliations
for their valued contributions: from the Group on Earth Observations (GEO) Blue Planet Initiative
and the National Oceanic and Atmospheric Administration (NOAA): Emily Smail, Samuel Djavidnia,
Sophie Seeyave, Keith VanGraafeiland, Sathyadev Ramachandran, Veronica Lance, Paul DiGiacomo,and Heng Gu; from the Nitrogen Management Expert Group: Wim Vries, Josette Garnier, Maryna Strokaland Mark Sutton; from the Commonthwealth Scientific and Industrial Research Organisation (CSIRO):
Britta Denise Hardesty, TJ Lawson, and Tim Reid; from the Global Citizen Science movement:
Jessie Oliver, Dilek Fraisl and Anne Bowser; Henrik Enevoldsen (IOC-UNESCO); Virginie Hart (Independent
Consultant); Eric Chassignet (Florida State University), and Julius Francis (Western Indian Ocean Marine
Science Association).

Table of contents

Part 1
Part 2

Collaborating Experts
The process of developing this Manual also involved consultations with a broad group of experts
on environment statistics and ocean sciences, who provided advice on the methodology and on theoperationalization of the indicators proposed herein. The authors wish to sincerely thank the following
experts who provided their input through the Expert Consultations held on this subject, virtually throughthe Community of Practice (CoP) and through the peer-review process: Genki Terauchi (NOWPAP),
Emilio Mayorga (University of Washington), Francois Galgani (French Research Institute for Exploitationof the Sea (IFREMER)), Isabelle Ansorge (University of Cape Town), Albert Fischer (IOC-UNESCO),
Emma Heslop (IOC-UNESCO); Alexander Turra (Joint Group of Experts on the Scientific Aspects of Marine
Environmental Protection (GESAMP)/University of Sao Paulo), Lex Bouwman (PBL), Arthur Beusen(PBL), Darryl Banjoo (Institute of Marine Affairs, Trinidad and Tobago), Ved Chirayath (NASA Ames
Laboratory for Advances Sensing), John Harrison (Washington State University), Nikolai Maximenko(University of Hawaii), Rose Osinde Alabaster (GEO Blue Planet), Simon Felgendreher (Federal Statistical
Office of Germany), Luisa Espinosa (Columbian Marine and Coastal Research Institute (INVEMAR)),Ramesh Ramachandran (National Centre For Sustainable Coastal Management, India), Tatjana Hema
(Mediterranean Action Plan), Ghada El Serafy (Aquawatch, Deltares), Blake Schaeffer (Aquawatch,
United States Environmental Protection Agency (EPA)), Merrie-Beth Neely (Aquawatch, Global
Science and Technology), Liana McManus (Global Resource Information Database (GRID) -Arendal),Costas Velis (University of Leeds), Imanol Zabaleta (Swiss Federal Institute of Aquatic Science andTechnology), Joana Veiga (Deltares), Paolo Corradi (European Space Agency), Peter Kershaw (GESAMP),Kei Ohno Woodall (Secretariat of the Basel, Rotterdam and Stockholm Conventions), Nao Takeuchi(UN-Habitat), Pascal Peduzzi (UNEP/GRID-Geneva), Michael Bordt (United Nations Economic andSocial Commission for Asia and the Pacific(UNESCAP)), Emil Ivanov (United Nations Statistics Division(UNSD)), Reena Shah (United Nations Statistics Division), Angelina Gutierrez (NOAA), Owen Rowe (Baltic
Marine Environment Protection Commission - HELCOM), Andrew Fitzgibbon (World Wide Fund for
Nature (WWF)), Linwood Pendleton (WWF), Jackie Thomas (WWF Pacific), Andrew Moss (Queensland
Department of Environment and Science), Authur Beusen (PBL Netherlands Environmental Assessment
Agency), Douglas Cripe (Group on Earth Observations), Jacqueline McGlade (Independent Consultant),
Blake Shaeffer (US Environmental Protection Agency), Takashi Ohmura (Institute for Global Environmental
Strategies, Japan), and Stefan Simis (Plymouth Marine Laboratory).

Further acknowledgements
UNEP-WCMC gratefully acknowledges in kind support from ODYSSEA (http://odysseaplatform.eu/),
a project funded by the European Union’s (EU) Horizon 2020 research and innovation programme.
The United Nations Environment Programme gratefully acknowledges funding from the Government of
Norway, which contributed to this document through the development of National Source Inventories
for marine litter. The authors also thank all those who answered an online survey circulated in 2017,
in support of this work.

Part 1

Table of contents

Part 2

SectionLA

List of acronyms

ASTER

Advanced Spaceborne Thermal Emission and Reflection Radiometer

AZE

Alliance for Zero Extinction

BOD

Biological oxygen demand

CAFF

Conservation of Arctic Flora and Fauna

CBD

Convention on Biological Diversity

CCAMLR

Convention for the Conservation of Antarctic Marine Living Resources

CEOS

Committee on Earth Observation Satellites

CMEMS

Copernicus Marine Environment Monitoring Service

COD

Chemical oxygen demand

CoP

Community of Practice

CPPS

Commission for the South Pacific

CSIRO

Commonwealth Scientific and Industrial Research Organisation

CZCS

Coastal Zone Color Scanner

DIN

Dissolved inorganic nitrogen

DIP

Dissolved inorganic phosphorus

EBSA

Ecologically or Biologically Significant marine Areas

EEZ

Exclusive Economic Zone

EPA

United States Environmental Protection Agency

ESA

European Space Agency

EU

European Union

EUMETSAT

European Organisation for the Exploitation of Meteorological Satellites

FAO

Food and Agriculture Organization (of the United Nations)

GCOM-C

Global Changing Observation Mission

GDP

Gross Domestic Product

GEF-TWAP

Global Environment Facility Transboundary Waters Assessment Programme

GEO

Group on Earth Observations

GESAMP

Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection

GIS

Geographic information system

GRID

Global Resource Information Database

HELCOM

Baltic Marine Environment Protection Commission – Helsinki Commission

HYCOM

Hybrid Coordinate Ocean Model

IAEG-SDGs

Inter-agency and Expert Group on SDG Indicators

IBA

Important Bird and Biodiversity Area

IBTS

International Bottom Trawl Surveys

Part 1

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Part 2ICC

International Coastal Clean-up

ICEP

Indicator for Coastal Eutrophication Potential

ICZM

Integrated Coastal Zone Management

IFREMER

French Research Institute for Exploitation of the Sea

IMOInternational Maritime Organisation

INVEMAR

Colombian Marine and Coastal Research InstituteIOC-UNESCO

Intergovernmental Oceanographic Commission of the United Nations Educational,
Scientific and Cultural Organization

IUCN

International Union for Conservation of Nature

JAMP

Joint Assessment and Monitoring Programme

JAXA

Japan Aerospace Exploration Agency

JRC

Joint Research Council (of the European Commission)

KBA

Key Biodiversity Area

LME

Large Marine Ecosystem

MAB

Man and Biosphere Reserves

MDG

Millennium Development Goal

MERIS

Medium Resolution Imaging Spectrometer

MODIS

Moderate Resolution Imaging Spectroradiometer

MPA

Marine Protected Area

MPW

mismanaged plastic waste

MSFD

Marine Strategy Framework Directive

MSP

Marine (or Maritime) Spatial PlanningMT

metric tons

NASA

National Aeronautics and Space Administration

NCODA

Navy Coupled Ocean Data Assimilation

NOAA

National Oceanic and Atmospheric Administration

NOWPAP

Northwest Pacific Action Plan

NUFER

Nutrient flows in Food chains, Environment and Resources use

OC_CCI

Ocean Colour Climate Change Initiative

OSPAR

Oslo Paris Convention for the Protection of the Marine Environment of
the North-East Atlantic

OLCI

Ocean and Land Colour Instrument

PERSGA

Regional Organization for the Conservation of the Environment of the Red Sea andGulf of Aden

PML

Plymouth Marine Laboratory

PNN

National Natural Parks (Colombia)

PSSA

Particularly Sensitive Sea Area

ROMPE

Regional organization for the Protection of the Marine Environment

RUNAP

Colombian National Register of Protected Areas (in Spanish: Registro Único deÁreas Protegidas)

SeaWiFS

Sea-Viewing Wide Field-of-View Sensor

SDG

Sustainable Development Goals

SEEA-EEA

System of Environmental Economic Accounting – Experimental Ecosystem Accounting

SPREP

Secretariat of the Pacific Regional Environment Programme

Part 1

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Part 2

TDN

total dissolved nitrogen

TDP

total dissolved phosphorus

TOC

Total organic carbon

TSS

Total Suspended Sediment

UAC

Coastal and Oceanic Environmental Unit (in Spanish: Unidad Ambiental Costera)UN

United Nations

UNESCAP

United Nations Economic and Social Commission for Asia and the Pacific

UNEP

United Nations Environment Programme

UNEP-MAP

UNEP Mediterranean Action Plan (also Barcelona Convention)

UNEP-WCMCUNEP World Conservation Monitoring Centre

UNESCO

United Nations Educational, Scientific and Cultural Organization

UNSD

United Nations Statistics Division

VIIRS

Visible Infrared Imaging Radiometer Suite

VME

Vulnerable Marine Ecosystem

WDPA

World Database on Protected Areas

WFD

Water Framework Directive

WHS

World Heritage Site

WWF

World Wildlife Fund for Nature

Part 1

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Part 2

SectionLR
Antarctic Sea

List of Regional Seas ProgrammesCommission for the Conservation of Antarctic Marine Living Resources(CCAMLR), Antarctic Treaty

Arctic Sea

Arctic Council, Ottawa Declaration

Baltic Sea

Helsinki Commission (HELCOM), Helsinki Convention

Black Sea

Black Sea Commission, Bucharest Convention

Caspian Sea

Caspian Environment Programme, Tehran Convention

East Asian Seas

East Asian Seas Action Plan

Mediterranean Sea

UNEP Mediterranean Action Plan (UNEP-MAP), Barcelona Convention

Northeast Atlantic

Oslo-Paris Convention (OSPAR) for the Protection of the Marine Environment of
the North-East Atlantic

Northeast Pacific

Antigua Convention

Northwest PacificNorthwest Pacific Action Plan (NOWPAP)

Pacific

Pacific Regional Environment Programme, Secretariat of the Pacific Regional
Environment Programme (SPREP), Noumea Convention

Red Sea and Gulf of Aden Regional Organization for the Conservation of the Environment of the Red Sea
and Gulf of Aden (PERSGA), Jeddah Convention
ROMPE Sea Area*

Regional organization for the Protection of the Marine Environment (ROMPE),
Kuwait Convention *(the ROMPE Sea Area refers to the marine and coastal areas of
Bahrain, Iran, Iraq, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates)

Sargasso Sea

Hamilton Declaration

South Asian SeasSouth Asia Cooperative Environment Programme, South Asian Seas
Action Plan

Southeast Pacific

Permanent Commission for the South Pacific (CPPS), Lima Convention

West and Central Africa

Abidjan Convention

Western Indian Ocean

Nairobi Convention

Wider Caribbean

Caribbean Environment Programme, Cartagena Convention

© Maksymus | Shutterstock
Understanding the State of the Ocean

xv

Part 1

Table of contents

Part 2

SectionES

Executive summary

Importance and challenge of monitoring the ocean
The ocean provides essential ecosystem services

When monitoring the ocean, it is important tofor human populations, from global climate

consider the high degree of connectivity that

regulation to local livelihoods and nutrition.

exists within the marine environment, but also

Monitoring is key to understanding the ocean:

between marine and terrestrial systems. Most of

How is the state of the ocean changing? Who isthe changes in marine ecosystems are caused bybenefiting from the change and who is losing out?

activities on land. For example, nutrient run-off

What is causing the changes? How well are ourfrom agriculture is a main cause of eutrophication

efforts to address the changes working?

of coastal waters, and mismanaged plastic
waste from coastal communities often ends up

The ocean covers 70 percent of the surface of thein the ocean. About 40 percent of the Earth’s

Earth. Yet, compared to terrestrial systems, marine

population lives on the coast, and approaches

ecosystems and biodiversity are still poorly

like Integrated Coastal Zone Management (ICZM)

understood. The main reason for our limited

have recognised the need for integrated marine

understanding of the ocean is that most marine

and terrestrial management of these coastal

ecosystems are remote, vast in size and difficult

zones. In this context, it is important to note thatto access, making marine research expensive andthe agreed Sustainable Development Goals (SDG)

logistically challenging. Gathering data on marine

14 Indicators (and proposed indicators) relate tobiodiversity and ecosystem conditions requires

measuring the state and quality of the impacted

advanced technologies and equipment, such as

ecosystems, rather than measuring the drivers

oceanographic research vessels, submersibles,and pressures underlying these. Hence, theirremotely operated vehicles, specially designed

purpose is to assess the success of measures put

sensors and remote sensing facilities. Moreover,in place to prevent marine issues such as marine

the dynamic and connected nature of the marine

litter or eutrophication. Although this manualenvironment present additional challenges:

focuses on measuring the marine environment, it

monitoring methodologies that work well in one

is important to use this information in conjunction

location may not be suitable or relevant in another.

with other information related to the terrestrial
environment, freshwater, climate and thesocio-economic situation

Understanding the State of the Ocean

1Part 1

Table of contents

Part 2

SDG 14 ‘Life below water’ and country-level perspectives
Sustainable Development Goal SDG 14 ‘Life below

for sustainable development. United Nations

water’ sets the aim to conserve and sustainably

Programme (UNEP) is the custodian agency for

use the oceans, seas and marine resources

the following indicators related to SDG 14:

14.1.1a Index of Coastal Eutrophication
14.1.1b Plastic debris density
14.2.1 Number of countries using ecosystem-based approaches to manage marine areas
14.5.1 Coverage of protected areas in relation to marine areas

The purpose of Understanding the State of the

14.1.1.b and 14.2.1) under UNEP custodianship

Ocean: A Global Manual on Measuring SDG 14.1.1,(see Table 1 for indicators and related SDG 14

SDG 14.2.1 and SDG 14.5.1 or simply referred to as

Targets). This document provides a step-by-stepthe Global Manual on Ocean Statistics is to support

structure of the indicator methodologies, whichcountries in their efforts to track progress against

was thought to promote coherent approaches

the delivery of SDG 14, by providing a step-by-step

across and within countries.

guide for compiling the three indicators (14.1.1.a,

Understanding the State of the Ocean

2Part 1

Table of contents

Part 2

Table 1: SDG 14 Targets for which UNEP is the custodian agency of the indicators.
SDG Target 14.1 is analogous to Aichi Target 81 of the UN Strategic Plan for Biodiversity 2010-2020, for which
global indicators are not yet available. SDG Target 14.5 is analogous to Aichi Target 112.

TargetnumberTarget nameIndicator
numberIndicator
name

Custodian agency(and others involved)

Tier
class

14.1

By 2025, prevent and14.1.1a2

Index of Coastal

UNEP (Intergovernmental

significantly reduce marine

Eutrophication

Oceanographic

pollution of all kinds, in(ICEP)

Commission ofparticular from land-based

the United Nations

activities, including marine

Educational, Scientificdebris and nutrient pollution

and Cultural Organization(IOC-UNESCO), Food andAgriculture Organization(FAO))
14.1.1b

Plastic debris

UNEP (IOC-UNESCO, FAO)

2

UNEP (IOC-UNESCO, FAO)

2

1

density

14.2

By 2020, sustainably manage

14.2.1

Number ofand protect marine andcountries using

coastal ecosystems to avoid

ecosystem-

significant adverse impacts,

based

including by strengthening

approaches totheir resilience, and takemanage marine

action for their restoration inareas

order to achieve healthy andproductive oceans
14.5

By 2020, conserve at

Coverage of

UNEP (UNEP World

least 10 per cent of

14.5.1protected areas

Conservation Monitoring

coastal and marine areas,

in relation toCentre (UNEP-WCMC))

consistent with national

marine areasand international law andbased on the best available
scientific information

1

Aichi Target 8: By 2020, pollution, including from excess nutrients, has been brought to levels that are not detrimental toecosystem function and biodiversity. For more information about the target: https://www.cbd.int/aichi-targets/target/8

2

Aichi Target 11: By 2020, at least 17 per cent of terrestrial and inland water, and 10 per cent of coastal and marine areas,
especially areas of particular importance for biodiversity and ecosystem services, are conserved through effectively andequitably managed, ecologically representative and well connected systems of protected areas and other effective area-based
conservation measures, and integrated into the wider landscapes and seascapes. For more information about the target:
https://www.cbd.int/aichi-targets/target/11

Understanding the State of the Ocean

3

Part 1

Table of contents

Part 2For SDG Indicator 14.5.1, an internationally

The Global Manual on Ocean Statistics provides

established methodology already exists andstep-by-step methodologies for implementing

thus it is not extensively covered in this manual.

the indicators for SDG Indicators 14.1.1a, 14.1.1b

Instead, the Global Manual on Ocean Statistics

and 14.2.1. The methodologies are designed topoints towards the existing methodology forbe globally applicable approaches that provide

SDG Indicator 14.5.1 which is based on thethe minimum data required to implement the SDG

World Database on Protected Areas (WDPA).The

indicators at country-level. This is particularly

coverage of protected areas in relation to marine

relevant to countries with limited resources andareas is calculated using the WDPA, based ontechnical capacities, notably countries withnational data which countries either submit into

relatively large marine national waters such as

the WDPA, or approve.

“island nations”.

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Context of Understanding
the State of the
Ocean: A Global
Manual on Measuring
SDG 14.1.1, SDG 14.2.1
and SDG 14.5.1© Evgeniy Biletskiy | Shutterstock1

Part 1

Table of contents

Part 2PART

Context of Understanding
the State of the Ocean:1

A Global Manual on Measuring SDG 14.1.1, SDG 14.2.1
and SDG 14.5.1

Sustainable Development Goals and indicators
At the United Nations (UN) General Assembly

to foster action for people, planet, prosperity,

in September 2015, Heads of States andpeace and partnership. For each high-level

Governments agreed on 17 SDGs as framework for

goal, a number of specific targets have been

the 2030 Agenda for Sustainable Development.

agreed by the countries. (Further details on the

The SDGs integrate the three dimensions ofindividual SDGs and targets can be found at

sustainable development (biosphere, society

https://sustainabledevelopment.un.org/sdgs).

and economy, as illustrated in Figure 1) and aim

Source: Azote Images for Stockholm Resilience Center

Figure 1:

Illustration of the 17 SDGs across the three spheres of sustainable development: biosphere, society
and economy.

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To keep track of progress against these global

progress. This will require a significant level ofgoals and associated targets, the Inter-agency

capacity and resources from countries: manyand Expert Group on SDG Indicators (IAEG-

indicators do not currently have internationallySDGs) developed a framework of over 200

established methodologies nor available data

indicators, which was adopted by the UN General

and/or associated monitoring schemes in place.

Assembly in July 2017. Countries are leading

Countries are encouraged to prioritise and develop

on the delivery of the SDGs, on a voluntary

their various monitoring schemes over time, inbasis, and are encouraged to use the framework

accordance to their national capacities.

of globally agreed indicators to report on

Data and information flows for reporting on SDG indicators
Currently, there are few consistent approaches forcollected by Non-Governmental Organisations

data collection and reporting for global targets

and research institutes at country, regional orsuch as the SDGs, or the Aichi Targets of the UNeven global levels. To support the global reporting

Strategic Plan for Biodiversity (2010-2020). While

process for SDGs, the IAEG-SDGs is developing

social and economic data might be collected

guidelines on data and information flows fromby National Statistics Offices in the countries,

national to global levels, as illustrated in Figure 2.

environmental and ecological data are often

When estimated andmodelled data are used,

CSOs

agencies need to consult andget agreement by national
statistical authorities

Academia

UNSD Global
SDG Indicators
Database

PrivatesectorInternational
Agencies
National
Statistical
Systemunstats.un.org/sdgs/
indicators/database/

Countries havedifferent data flows
scenarios

Regional Mechanisms will
facilitate the data transmission
process from the national to

Regional
Mechanism

the global level

UNSD Country
Data Lab

Source: Guidelines on data flows and global data reporting, 5th Meeting of the IAEG-SDGs, 30-31 March 2017, Ottawa

Figure 2:

Anticipated Sustainable Development Goal data flow and reporting process.

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According to the IAEG-SDGs reporting guidelines,

Each SDG indicator falls under the responsibility

the monitoring data underlying the indicatorsof a specific international agency which functions

will be collected and processed at the national

as custodian agency for the indicator. Custodianlevel by relevant public and private-sector

agencies are UN bodies and other international

institutions and brought together in reportingorganisations, such as the UNEP-WCMC, that

platforms by the National Statistics Office of theare responsible for facilitating the data andcountry. From here, the data and information

information flow from the national to the global

will be transmitted to international agencies,

level. The custodian agencies also have theeither directly or through regional mechanisms

responsibility to standardise SDG indicator

such as the Regional Seas Programmes . The

methodologies and to support countries ininternational agencies will then aggregate thestrengthening national statistical capacity andcountry-level data at regional and global levels

reporting mechanisms.

3

and submit these aggregates, along with thecountry data, into the Global SDG Indicators
Database, which is maintained by the UNSD 4.

Complexities of ocean monitoring and marine indicators
Note that there is a layer of complexity added

remote marine environments, including the deepby a multitude of different jurisdictions, or lacksea. One cost-effective method for accessing

thereof, in the ocean. Depending on the country,

these areas, requiring low technological capacity,

territorial waters can extend to 12 nauticalis through international remote sensing initiatives

miles and exclusive economic zones (nationalthat use satellite telemetry to monitor large

waters) can reach out to 200 nautical miles.

areas of the high seas over time. These remote

However, over 60 percent of the ocean surface

sensing initiatives provide insight on physical,

and nearly 95 percent of the volume lie in areas

biological and biogeochemical ocean parameters.

beyond national jurisdiction, also called the highHowever, satellite sensors are less suitable forseas, where responsibilities for monitoring andmonitoring species and habitat biodiversity, or

reporting are not always straightforward.

even pollutants such as marine plastics, for which
in situ data collection is usually more appropriate.

In the high seas, monitoring often relies on

The issue here is that the cost of in situ monitoring

international scientific cooperation efforts, due toand lack of national mandates in the high seas

the vast areas involved and the cost of accessing

limit the options for such primary data collection.

3

For information about the Regional Seas Programmes: http://web.unep.org/regionalseas/who-we-are/regional-seasprogrammes

4

https://unstats.un.org/sdgs/indicators/database/

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About Understanding the State of the Ocean: A Global Manualon Measuring SDG 14.1.1, SDG 14.2.1 and SDG 14.5
The Global Manual on Ocean Statistics provides

marine issues such as ocean acidification or

guidance for national governments and national

marine plastics. For such issues, the monitoring

institutions to support the country-levelof national waters, which is the primary focus

implementation of SDG Indicators 14.1.1a, 14.1.1b,of the SDG indicators, only shows part of the

14.2.1 and 14.5.1 in their national waters.

picture. This manual focuses on national
monitoring, but there is a need for additional

Note that there are a number of challenges andresearch and support to measure the areas

limitations facing monitoring in the high seas.

beyond national jurisdiction for analytical use,

Particularly problematic are transboundary

including for analysis of the SDGs

Progressive monitoring approach
Agenda 2030 is a country-led and country-

nationally- derived data to report on Indicator

owned process. The Global Manual on Ocean

14.1.1. Where countries have the data andStatistics embraces this approach which places

capacity to do so, they should aim to report on all

responsibility on countries to monitor and report

aspects of Indicator 14.1.1. While it is beneficial

data on all SDG indicators. The environmental

to capture data on all aspects of the Indicator, it

dimension of the SDG indicators is relatively newis recognised that not all countries may have allcompared to the Millennium Development Goals

required data available to achieve this. Therefore,(MDGs) and nationally derived environmental

the progressive monitoring approach presented

data has not often been captured before. With

here encourages different levels of ambition,

this in mind, the methodology proposed in thisdepending on a country’s capacity.

manual encourages the use of globally available
environmental data to enhance country-derived

The progressive monitoring approach uses

data, filling data gaps and enabling countries to

3 Levels. Level 1 data utilizes data which ismore rapidly make progress towards achieving

already globally available and for which UNEP will

SDG targets. For SDG 14.1.1, both coastal

produce data products. This allows to establish

eutrophication and marine litter, a progressivea foundation which can be strengthened bymonitoring approach is proposed which brings

countries as they develop capacity and ability

together globally modelled data and national

to report on Level 2 data and Level 3 data.

data. This same approach has been adopted

Level 2 data is recommended for nationalfor other SDG indicator methodologies, such asdata collection in all countries. Level 3 data is

Indicator 6.6.1 and 15.3.1.

a list of supplementary information which issuggested that countries consider monitoring,This progressive monitoring approach means

but this manual does not go into detail on thethat countries can utilize both globally- andLevel 3 indicators. All globally available data

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Part 2will be shared with national statistical offices

global algorithms, some countries may choose

and other relevant authorities for in-country

to provide their own data derived from regionallyvalidation. Since this global data is derived fromtuned algorithms as part of the Level 2 data.

Definitions
Eutrophication – excess nutrient loading into

Marine litter - any persistent, manufactured

coastal environments from anthropogenic

or processed solid material which is lost or

sources, resulting in excessive growth of aquatic

discarded and ends up in the marine andplants, algae and phytoplankton.

coastal environment.

Coastal Zone – national Exclusive Economic
Zone (EEZ) (200 nautical miles from the coast)as outlined by the United Nations Convention on
the Law of the Sea.

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Step-by-step guides toindicator implementation© Carlos Achando | Shutterstock2

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Part 1
Part 2PART

2

Step-by-stepguides to indicator
implementation
Indicator 14.1.1a: Index of Coastal
Eutrophication (including ICEP)
Target 14.1: By 2025, prevent and significantly reduce marine
pollution of all kinds, in particular from land-based activities,
including marine debris and nutrient pollution

Backgroundand resources required to calculate nutrient
loading, a progressive methodology is proposed

Coastal areas are areas of high productivity where

which promotes country-derived data collection

inputs from land, sea, air and people converge.

to be complemented by other globally available

With over 40 percent of the human population

datasets such as publicly available satellite

residing in coastal areas, ecosystem degradation

remote sensing products that can be used asin these areas can have disproportionate

proxy indicators for eutrophication. Note that it iseffects on society (IGOS 2006). One of theimportant to consider the sources of nitrogen inlargest pressures on coastal environments isdeveloping nitrogen related interventions.

eutrophication, resulting primarily from landbased nutrient input from agricultural runoff
and domestic wastewater discharge. Coastal
eutrophication can lead to serious damage to

Proposed indicators for
SDG reporting

marine ecosystems, vital sea habitats, and cancause the spread of harmful algal blooms.

SDG Indicator 14.1.1a aims to measure thecontribution to coastal eutrophication fromTarget 14.1 aims to reduce the impacts of pollution

countries and the state of coastal eutrophication.

through prevention and reduction of marine

Therefore, two levels of indicators arepollution of all kinds, in particular from land-based

recommended with an optional third level for

activities, including marine debris and nutrient

relevant countries:

pollution. Due to the significant amount of data

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Level 1: Proposed global indicators

Level 3: Supplementary indicator

•

•

•

Indicator for Coastal Eutrophication

Described in the below table for information.

Potential (based on Nitrogen and Phosphate

The in-situ indicators proposed below matchloadings)

with the methods presented in SDG 6.3.2:

Chlorophyll-a deviations and anomalies

Proportion of bodies of water with goodambient water quality

Level 2: Proposed national indicators•

Chlorophyll-A concentration•

National modelling of coastal eutrophication
potential•

In-situ concentration of nitrogen, phosphateand silica

Global low
resolution
data

Level 1

National contribution to the Index of
Coastal Eutrophication Potential

Global Data Products
Chlorophyll-a deviations and anomalies

Chlorophyll-a concentrations

Level 2

Regional & National Data
Local highresolution

eutrophication potential

In-situ concentration of nitrogen,phosphate, and silica

Level 3

Supplementary Data

Figure 3:

National modelling of coastal

Other indicators

Summary of SDG 14.1.1a sub indicator levels

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Table 2: Monitoring parameters for eutrophication to track progress against
SDG Indicator 14.1.1a.
These indicators are marked as levels 1, 2 or 3, level 1 being global data or globally modelled, level 2 including
national monitoring and level 3 describing supplementary/recommended indicators.

Monitoring parameters

Level 1

Indicator for Coastal Eutrophication Potential (N and P loading)✕

Chlorophyll-a deviations (remote sensing)✕Level 2Chlorophyll-a concentration (remote sensing and in situ)✕

National modelling of ICEP✕

Total Nitrogen of DIN (dissolved inorganic nitrogen)✕Total Phosphorus or DIP (dissolved inorganic phosphorus)✕

Total silica✕

Level 3

Dissolved oxygen✕

Biological/chemical oxygen demand (BOD/COD)✕

Total organic carbon (TOC)✕

Turbidity (remote sensing)✕River parameters from SDG 6.3.2✕

Other water parameters (O2 % saturation, Secchi depth, river discharge,✕

salinity, temperature, pH, alkalinity, organic carbon, toxic metals, persistentorganic pollutants)
Microalgal growth, harmful algal blooms, submerged aquatic vegetation✕

coverage, biodiversity and hypoxia

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Step-by-step guide to implementing the indicator

Level 1: Indicator for coastal
eutrophication potentialof coastal eutrophication at a specific river mouth.
The indicator can be further developed byincorporating in situ monitoring to evaluateThis indicator is based on loads and ratios ofthe dispersion of concentrations of nitrogen,nitrogen, phosphorous and silica delivered byphosphorous and silica to ground-truth the index.

rivers to coastal waters (Garnier et al. 2010)

The indicator assumes that excess concentrations

which contribute to the ICEP. This indicatorof nitrogen or phosphorus relative to silica willassumes that excess nitrogen or phosphorus

result in increased growth of potentially harmful

relative to silica will result in increased growthalgae (ICEP>0). ICEP is expressed in kilograms ofof potentially harmful algae (ICEP>0). The basis

carbon (from algae biomass) per square kilometre

for these loads is collected from land-basedof river basin area per day (kg C km -2 day-1).

assessments of land use including fertilizer use,
population density, socioeconomic factors and

The ICEP model is calculated using one of twoother contributors to nutrient pollution runoff.

equations depending on whether nitrogen orGiven the land-based nature of the indicator,

phosphorus is limiting. The equations (Billen andit provides a modelled number indicating the risk

Garnier 2007) are

ICEP (N limiting) = [NFlx/(14*16)-SiFlx/(28*20)]*106*12
ICEP (P limiting) = [PFlx/31 – SiFlx/(28*20)]*106*12
Where PFlx, NFlx and SiFlx are respectively the mean specific values of total phosphorus, total nitrogen anddissolved silica delivered at the mouth of the river basin, expressed in kg P km-2 day-1, in kg N km-2 day-1
and in kg Si km-2 day-1.

In order to populate the variables in the ICEP,

management. Hydrology can be derived fromthe values of total nitrogen, total phosphorus

various global hydrological models. The socio-and dissolved silica delivered at the mouth of theeconomic, urbanization and nutrient management

river basin must be modelled. There are various

data are available from different sources

methods that have been employed to model(e.g., FAO national statistics, global models suchthese values. The modelling is based on globallyas IMAGE, MAgPIE, Globiom model), but varyavailable data and data collected directly fromgreatly in spatial and temporal level of detailcountries. To quantify nutrient export by rivers,(e.g., national versus 0.5-degree cell). Examples of

the information is needed for hydrology, socio-

the required data to quantify nutrient export byeconomic drivers, urbanization and nutrient

rivers is presented in Table 3.

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Table 3: Examples of the data needed to quantify nutrient export by rivers that is used in
ICEP estimates

Actual (“disturbed”) basin discharge
Natural (“pristine”) basin discharge
Fraction removed through consumptive water use

Hydrology and retentions in rivers

Basin-wide dam retention factor for DIN
Basin-wide dam retention factor for DIP
Basin-wide dam retention factor for Total Suspended
Sediment (TSS)
GDP, at market exchange rate
GDP at purchasing power parity
Population Density
Urban Population Density

Socio-economic data

Density of population connected to sewage system
Raw total elemental N & P emission to watershed fromhuman waste (excrement)
Raw total phosphorus emission to watersheds fromdetergents (laundry + dishwasher)
Removal efficiencies of N and P during treatment
Wetland

Land use data
Agricultural land (e.g., cropland, legumes, pasture)
Total fertilizer inputs to land
Animal manure inputs to land and to rivers

Nutrient management data
Atmospheric N deposition on land
Biological N fixation by crops and natural vegetation

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Table of contents

Part 1
Part 2The Global NEWS model (originated in Seitzinger

For SDG 14.1.1a, the MARINA model will be used

and Mayorga (2010) and applied in Strokal et alas the source of information for modelling the(2016)) is the most used global level analysis

nutrient exports (of Nitrogen and Phosphate).

of basin level nutrient exports to river-mouths.

MARINA can provide nutrient export from sub-This model uses river input data which takes into

basins to the river mouth (coastal waters) for

account fertilizer use, livestock data and othercountries that have the river mouths (theseinformation mentioned in the above table andcountries directly discharge nutrients to the

combines it with information on land cover andcoastal waters). For other counties (do not

run-off modelling. It includes point and diffuse

discharge directly to the coastal waters), MARINA

sources of nutrients in rivers, both of these arecan provide the information on the nutrient exportfunctions of the total dissolved nitrogen (TDN)by sub-basin that drain through those countries.

and total dissolved phosphorus (TDP). For
example, variables for point sources of nutrients

Additionally, UNEP aims to work with partners toinclude direct discharges of animal manuremake geospatial data on the nutrient flows andto rivers and human sewage and variables for

the ICEP at river mouths available every 5 years.

diffuse sources of nutrients include manureand synthetic fertilizers used in croplands,
atmospheric N deposition, biological N fixation,leaching of organic matter, and P-weathering.

Level 1: Chlorophyll-A deviation
modelling

The Global NEWS model measures the coastal
eutrophication potential at the river mouth (i.e.

Satellite-based assessments of ocean colour

the point when water flows into the ocean).

began in 1978 with the launch of the Coastal
Zone Color Scanner (CZCS) aboard the NASA

For SDG indicator 14.1.1a, further sub-basin level

Nimbus 7 satellite. Following a decade-long breakinformation is needed in order to nationalize thein observations, there have been continuous

contribution of nutrients by countries to the ICEP.

satellite ocean colour measurements since 1997

The MARINA (Strokal et al 2016) is a downscaledwith Sea-Viewing Wide Field-of-View Sensor

version of Global NEWS. MARINA calculates(SeaWiFS), followed by Medium Resolution

river export of nutrients at a sub-basin level

Imaging Spectrometer (MERIS), Moderate(Global NEWS at a basin level). MARINA brings

Resolution Imaging Spectroradiometer (MODIS),

in additional information on point source inputs

Visible Infrared Imaging Radiometer Suite (VIIRS),

of manure and direct discharge of human waste

Ocean Land Colour Instrument (OLCI), Second

into rivers. The MARINA model tracks the inputs

Generation Global Imager (SGLI) and Ocean Colorof nutrients into rivers, the retention of nutrientsand Temperature Scanner (OCTS) with additionalin rivers (which impacts river water quality) andsensors in development.

the potential release of nutrients into the ocean.
An important difference of MARINA from Global

Data gaps from individual sensors are common

NEWS is that MARINA is able to calculate thedue to revisit cycles, cloud cover, and spurious

contribution of upstream, middle stream andretrievals resulting from a host of confounding

downstream activities to the coastal water

atmospheric and aquatic conditions. Some ofpollution (contributing to coastal eutrophication).

these issues have been addressed by combining

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data from multiple sensors and creating a

resolution per pixel monthly mean product ofconsistent, merged ocean colour productthe OC-CCI project product5 for each pixel within(e.g., surface ocean chlorophyll-a concentration).

a country’s EEZ.

The ESA Ocean Colour CCI (OC-CCI) project,
led by Plymouth Marine Laboratory (PML), has

For purposes of this sub-indicator, reporting year

produced a consistent, merged chlorophyll-avalues are compared to a baseline of years 2000

product from SeaWiFS, MODIS, MERIS and VIIRS,

to 2004. The baseline climatology was calculated

spanning the years 1997 to 2019 (Sathyendranathas the mean of the 5 years of each month by pixel

et al., 2018). The merged multi-sensor product(e.g., mean of 5 years of January) resulting in a 5

will be updated in both time and with data fromyear mean of each calendar month over the period

additional sensors (e.g., OLCI) as part of the2000 to 2004. The processing steps are outlined

Copernicus Climate Change Service (C3S) andbelow and in figure 4.

the Copernicus Marine Service (CMEMS) thatwill continue the time series on an operational

1. Calculate the positive percent differencebasis. Future OC-CCI releases will also include

of monthly pixel values from the baseline

algorithmic improvements developed under themonthly pixel values

CCI+ initiative.

Using the monthly baseline averages, thepercentage difference of the pixel value for the

Chlorophyll-a concentrations for this indicator

reporting period from the baseline value will be

are obtained from the global ocean, 4 km spatial

calculated as follows:

Percent difference of pixel value from baseline = [ ( γ - β ) / β ] x 100 values >0
Where β = the average monthly pixel chlorophyll-a concentration for years 2000 to 2004
Where γ = the average monthly pixel chlorophyll-a concentration for the reporting year

2. Identify pixels with deviations
Pixels with differences from the baseline that

3. Calculate the percentage of the EEZwith deviations

are in the 90th percentile of values >0 across

The percentage of pixels in a country’s EEZ

the cumulative global EEZ area as defined inthat are identified as deviating from theWorld EEZ v11 .

baseline (falling in the 90th percentile) will be

6calculated for each national EEZ by month.
The annual average of these monthly values isthen calculated.

5

https://catalogue.ceda.ac.uk/uuid/5400de38636d43de9808bfc0b500e863

6

https://www.marineregions.org/downloads.php

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Part 1
Part 2Sub-indicator 1 Processing
Monthly
Chlor-aTimes 100 (%)

Minus

Monthly

Calculate 90 th
Percentile

Classify pixels

Monthly
Summary
Table

Figure 4:

Clip to Global EEZEEZ Boundary

DivideBaseline

Select Positive
ValuesSummarize pixels

as deviations

by Country EEZ

based on the 90 th
percentile

Process for Calculating the Annual Chlorophyll-a Deviations

Intra-annual EEZ chlorophyll-a
anomaliesdifference anomaly 7. The processing steps are

An additional sub-indicator will be provided

1. Classify and count pixels as moderate, high oroutlined below and in figure 5.

extreme anomalies

to evaluate the intra-annual changes inchlorophyll-a concentration anomalies in each

For each day in the reporting year, pixels in the

Exclusive Economic Zone (EEZ) using the NOAA

global EEZ area (as defined in World EEZ v118)

VIIRS chlorophyll-a ratio anomaly productthat are classified as:

produced daily for the globe at 2 km spatial
resolution. The daily global VIIRS chlorophyll-a•

moderate (in the 90th percentile),

concentrations are produced from the NOAA•

high (in the 95th percentile) andMulti-Sensor Level 1 to Level 2 (MSL12)•extreme (in the 99th percentiles).

processing of the VIIRS sensor on the Suomi
SNPP satellite. [Wang et al., 2017; Wang et al.,The number of days a given pixel is classified

2014] This anomaly product is defined as theas moderate, high, or extreme within eachdaily chlorophyll-a concentration subtracted frommonth is then calculated. The number of days

a rolling 61-day mean baseline with a 15 day lag

in each month where the pixel has valid data is(based on Stumpf et al., 2003), then normalized toalso counted.

the rolling 61 day mean to create the proportional

7

ftp://ftp.star.nesdis.noaa.gov/pub/socd1/mecb/coastwatch/viirs/science/L3/global/chlora/anom/WW00/(the proportional difference product is labelled as PDIF in the file, see https://www.star.nesdis.noaa.gov/socd/mecb/
color/notes.php for processing notes.

8

https://www.marineregions.org/downloads.php

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2. Calculating the monthly statistics

algorithm flags. To avoid bias due to non-valid

Because these anomalies are based on daily

data retrievals, the frequencies are normalized

observations, data gaps are expected due

using the number of days in the month with valid

to cloud cover, sun glint, high sensor zenith

observations, as follows:

angle, high sun zenith angle, and other possible

Relative frequency of classified pixel chlorophyll-a anomalies= αc / εWhere α = the number of days in the month with a classified (moderate, high or extreme anomaly) anomaly
Where c indicates the anomaly classification (moderate, high, or extreme anomaly)
Where ε = the number of days in the month with valid data

Finally, the monthly mean of the relative

3. Calculating the annual statistics

frequencies for each class is calculated for each

The monthly statistics described above are also

EEZ, resulting in 3 monthly values, one value inreported on an annualized basis by taking aneach of the 3 classes for each country.

average of the country’s twelve monthly frequency
values for the calendar year, for each EEZ.

Sub-indicator 2 Processing
STEP 1

UN Countries
List

Join

Proportional Difference

Global EEZ Boundary(PDIF) Anomaly

Clip

EEZ PDIF

Statistics

Figure 5:

Process for Calculating the Intra-annual EEZ Chlorophyll-a Anomalies

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Table of contents

Part 1
Part 2Count

90th Percentile

95th Percentile

99th Percentile

Classify

Classify

Classify

Moderate

High

ExtremeDivideDivideDivideMonthly Moderate

Monthly HighMonthly Extreme

Frequency Pixels

Frequency Pixels

FrequencyPixels

Summarize by country

Summarize by country

Summarize by country

Monthly High Statistics

Monthly Extreme Statistics

Sum each of 12 months

Sum each of 12 months

Sum each of 12 months

Yearly Moderate Sum

Yearly High Sum

Yearly Extreme Sum

Divide by 12 months

Divide by 12 months

Divide by 12 months

Yearly Moderate

Yearly HighYearly Extreme

Statistics

Statistics

Statistics

STEP 2

Valid Pixels(per month)

STEP 3UN
countries
Monthly Moderate
Statistics

STEP 4

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Level 2: In situ monitoringof nutrientsis basin-scale and quantifies river export ofvarious nutrients (nitrogen, phosphorus, carbon
and silica) in multiple forms (dissolved inorganic,

Where national capacity to do so exists, national

dissolved organic and particulate) as functions oflevel measurements of Chlorophyll-a and otherhuman activities on land and basin characteristics

parameters (including nitrogen, phosphate(Strokal et al 2016). Furthermore, the modeland silica) (in situ or from remote sensing),shows past and future trends. The NUFER model

should be used to complement and groundoriginally was established to quantify efficiencies

truth global remote sensing and modelledin nutrient flows in the food chain and inform

data and enable a more detailed assessment

management options throughout the foodof eutrophication. In particular, monitoring of

chain. The study of Strokal et al (2016) develops

supplementary eutrophication parameters isthe downscaled version (sub-basin scale) ofadvisable to determine whether an increase in

Global NEWS. This level adds value because it can

Chlorophyll-a concentration is directly linked toreveal nutrient issues in higher resolution, thus

an anthropogenic increase in nutrients. Pleaseholding the potential to expose new hotspots.

refer to Table 2 for parameters for monitoring

This could inform sub-basin-scale and innovative

eutrophication at the national level (Level 2).

management approaches. In addition, the study
couples these two models to better evaluate both

Level 2: National ICEP modelling

point and diffuse nutrient sources.
Refining this same model at the national level

Existing ICEP modelling at the national level iscould take into account more detailed information

limited, but could be further developed following

on livestock, fertilizer, sewage and various humanthe model of a current study analysing basin

activities. This would provide vital informationlevel data in Chinese rivers (Strokal et al 2016).

to management approaches at a level that could

The study utilises Global NEWS – 2 (Nutrient

implement action. Importantly, measuring andExport from Watersheds) and Nutrient flows incataloguing the data from this model at a national

Food chains, Environment and Resources use

level can further develop global understanding of(NUFER) as models. The Global NEWS-2 model

nutrient pollution in oceans.

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Indicator 14.1.1.b: Marine plastic debris
Background

There are large gaps in knowledge in terms ofunderstanding marine plastics and microplastics:

Marine litter is found in all the world’s oceansreliable figures for the volume of plastics enteringand seas. It constitutes an increasing risk to

the ocean, the accumulated volume of plastics inecosystem health and biodiversity while entailingthe marine environment, mapping of the source

substantial economic costs through its impacts

and sink location of plastics and basic data on

on public health, tourism, fishing and aquaculture.

microplastic are currently lacking. There is a

Marine plastics are of particular interest due to theneed to use existing data from remote sensing,fact that in the last 50 years, plastic production

citizen science and in situ monitoring to better

has increased more than 22-fold while the global

understand marine plastics and microplastics;

recycling rate of plastics in 2015 was only an

however, much of the research in this field is at an

estimated 9%. This rise in plastic production andinitial stage and in many regions only data related

unmanaged plastic waste has resulted a growing

to beach litter is available.

threat to marine environments with an estimated
5-13 million tons of plastic from land-based

In the marine environment, as it relates to 14.1.1b,sources ending up in marine environments.

there are four fates for marine plastics andmicroplastics:

Sources of plastics and microplastics to theocean are many and varied, but the actual
quantities involved remain largely unknown.

1. Washed onto beaches or shorelines(beach litter)

Reliable quantitative comparisons between

2. Floating on the water or in the water column

the input loads of macro and microplastics,

3. Deposited on the seafloor/seabedtheir sources, originating sectors and users are

4. Ingested by biota (e.g. sea birds).

not possible at present, and this represents asignificant knowledge gap. Estimates of some

The methodology for SDG 14.1.1b includes

sources, such as municipal solid waste, havepotential measurement of these fourbeen made. These are useful to focus attention,

accumulation types; however, it is also important

but the numbers should be treated with someto note the importance of monitoring information

caution due to the large uncertainties involved.

on waste management and the sources of plastic

How much of this material enters the ocean

pollution for understanding plastic pollution.

will be dependent largely on the extent andeffectiveness of wastewater and solid waste
collection and management.

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Proposed indicators for SDG reporting
The agreed indicator for marine plastic litter

Level 1: Proposed global indicators:

under SDG Target 14.1, as proposed by the
IAEG-SDGs, is on marine plastic debris (14.1.1b).

•

Plastic patches greater than 10 meters

Based on the existing internationally agreed(for Areas Beyond National Jurisdiction orGroup of Experts on the Scientific Aspects ofTotal Oceans)

Marine Environmental Protection (GESAMP)

9•guidelines and the existing national data

Beach litter originating from national
land-based sources

collections, it is recommended that the SDG
reporting includes sub-indicators related to

Level 2: Proposed national indicators:

beach litter, floating plastic and plastic in the sea
column, plastic on the sea floor and additional•

option indicators. Indicators on micro-litter may
also be considered as optional. The proposed

Beach litter count per km2 of coastline (surveys
and citizen science data)•

global indicators are based on feasibility and

Floating plastic debris density (visualobservation, manta trawls)

relevance. All indicators described below are•

Water column plastic density (demersal trawls)

consistent with the GESAMP guidelines on•

Seafloor litter density (benthic trawls (e.g. fish

monitoring marine plastics which were publishedsurvey trawls), divers, video/camera tows,

in 2019. The GESAMP 2019 is an internationallysubmersibles, remotely operated vehicles)

agreed standard which was launchedin March 2019.10

Level 3: Supplementary indicators:•

These are listed in Table 6 for information, but
are not described in detail in this manual.

9More information on the UN Group of Experts on the Scientific Aspects of Marine Environmental Protection can be foundhere http://www.gesamp.org/. GESAMP is a collaboration of the UN System. The GESAMP working group 40 focuses on
marine litter and then and involved experts on marine litter.

10 Guidelines for the Monitoring and Assessment of Plastic Litter in the Ocean,
https://environmentlive.unep.org/media/docs/marine_plastics/une_science_dvision_gesamp_reports.pdf. The GESAMP
2019 was produced under working group 40

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Table 6: Monitoring parameters for marine plastic litter to track progress against SDG
Indicator 14.1.1b.

Monitoring parameters (and methods)

Level 1

Plastic patches greater than 10 meters*✕

Beach litter originating from national land-based sources✕

Level 2

Beach litter (beach surveys)✕

Floating plastics (visual observation, manta trawls)✕

Water column plastics (demersal trawls)✕

Seafloor litter (benthic trawls (e.g. fish survey trawls), divers, video/camera✕

Level 3

tows, submersibles, remotely operated vehicles)
Beach litter microplastics (beach samples)✕

Floating microplastics (manta trawls, e.g. Continuous Plankton Recorder)✕

Water column microplastics (demersal plankton trawls)✕

Seafloor litter microplastics (sediment samples)✕

Plastic ingestion by biota (e.g. birds, turtles, fish)✕

Plastic litter in nests✕

Entanglement (e.g. marine mammals, birds)✕

Plastic pollution potential (based on the use and landfilling of plastics)✕

River litter✕

Other parameters related to plastic consumption and recycling✕

Health indicators (human health and ecosystem health)✕* This indicator is most useful for areas beyond national jurisdiction or total ocean area, not for national
monitoring. These indicators are marked as levels 1, 2 or 3, level 1 being global data or globally modelled, level
2 including national monitoring and level 3 describing supplementary/recommended indicators.

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Step-by-step guide to implementing the indicator

Level 1: Plastic patches greaterthan 10 meters

are from the GOFS3.1, a global ocean forecast
system based on the Hybrid Coordinate Ocean
Model (HYCOM) and the Navy Coupled Ocean

Satellite-based global data products make up

Data Assimilation (NCODA). NCODA uses thethe statistics for this indicator. NASA and ESA

24-hour model forecast as a first guess in a 3D

both contribute satellite images to constructvariational scheme and assimilates available

information on the plastic patches greater thansatellite altimeter observations, satellite, and10 meters throughout the world’s oceans. Multi-

in-situ sea surface temperature as well as in-situ

spectral satellite remote sensing of plastic invertical temperature and salinity profiles fromthe water column is currently only possible for

XBTs, Argo floats and moored buoys. Surface

larger elements (more than 10m) and under good

information is projected downward into the water

atmospheric conditions (no clouds).

column using Improved Synthetic Ocean Profiles(Helber et al. 2013). The horizontal resolution

There are some promising methods looking atand output frequency for the GOF3.1 outputs areanomalies or particular signatures to identify

8 km at the equator, 6 km at mid-latitudes andocean plastic. For example, ESA’s Sentinel-3

3-hourly, respectively.

satellite has an ocean colour imager that is
potentially detecting unique signatures or large

OceanParcels v2.0 is a Lagrangian ocean analysis

agglomerations of plastic. However, this typeframework designed to combine (1) a wideof analysis is new. The applicability of this sub-flexibility to model particles of different naturesindicator is considered within the scope of theand (2) an efficient implementation in accordance

SDG for discussion but is most relevant for areas

with modern computing infrastructure. The latest

beyond national jurisdiction and not to create

version includes a set of interpolation schemes

national level indicators.

to read various types of discretized fields, fromrectilinear to curvilinear grids in the horizontal

Level 1: Beach litter originatingfrom national land-based sources

direction, from z- to s- levels in the vertical anddifferent variable distributions such as the
Arakawa’s A-, B- and C- grids (Delandmeter andvan Sebille, 2019).

Modelling of litter movement through theoceans occurs through numerical models using

The primary challenge of modelling the global

inputs including ocean flow and marine plastic

displacement of marine litter is the large

litter characteristics. UNEP and Florida State

uncertainties associated with the amount andUniversity are producing a global model oflocation of mismanaged plastic waste (MPW)

marine litter using OceanParcels v2.0, a state-of-entering the ocean. A zero-order estimate isthe-art Lagrangian Ocean analysis framework toprovided by Jambeck et al. (2015) who estimatedcreate customizable particle tracking simulation

the total amount of plastic waste generated byusing outputs from ocean circulation models.

192 coastal countries to be 275 million metric

The ocean circulation model outputs used here

tons (MT) of plastic waste, with 4.8 to 12.7 million

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MT entering the ocean in 2010. This data was

National efforts to collect data on beach litter canused to seed the model which is proposed forbe supported by campaigns to engage members ofuse for SDG 14.1.1b. This was used to estimate

the public as volunteers in beach clean-ups (see forwhere plastics that would be found on the coast

example the Ocean Conservancy’s International

likely originated from. As a simple example, for

Coastal Clean-up (ICC) initiative12) or citizen

Kenya, based on this model, of the plastic whichscience programmes (see for example NOAA’s

ends up on beaches, 11% likely originated from

Marine Debris Monitoring and Assessment Citizen

Kenya, 60% likely came from countries in Africa

Science Project13). Specific instructions on how to

and 29% likely came from outside the region.

conduct citizen science beach surveys are included

This model can be produced annually and updated

in the GESAMP Guidelines (GESAMP 2019).

as better waste emissions data becomes available

They provide resources on previous citizen sciencefor countries.

projects and guidance for ensuring sound datacollection and management with citizen science.

Level 2: Beach litter (average countof plastic items per km2)

Beyond the tools used to conduct beach littermonitoring, it is important to consider the timingof surveys in order to properly plan effective

METHODOLOGY: Beach litter surveys following

surveys. The GESAMP Guidelines explain two

the UNEP/Intergovernmental Oceanographic

main types of surveying beaches including

Commission of the United Nations Educational,

rapid assessment surveys and routine shoreline

Scientific and Cultural Organization (IOC-UNESCO)

monitoring. Rapid assessment surveys are best

operational guidelines (Cheshire et al. 2009) andconducted in response to natural disasters,

GESAMP Guidelines (GESAMP 2019)to build a baseline for future surveys and/or to11

identify beach litter hotspots. Routine shoreline•••

Step one: Identify the national authority

monitoring is also important because it provides

responsible for gathering data and reporting

insight to beach litter accumulation in a particularon marine pollution and the agency/

location. It is best to identify national needs andorganisation responsible for implementing

then define the approach to accommodate thosebeach litter surveys.

needs (GESAMP 2019).

Step two: Explore the use of existing data
which is being collected by citizen science

Beach litter is an important parameter that all

initiatives and beach clean ups.

countries should monitor and report on. Where

Step three: Conduct beach litter surveys

in-country capacity or opportunities exist tofollowing the UNEP/IOC-UNESCO operational

conduct more extensive marine litter monitoring,guidelines, which are provided in Appendix

countries can also conduct surveys of floating

4 and using resources from the GESAMP

plastics, plastics on the seafloor or microplastics

Guidelines (GESAMP 2019).

(as described below).

11 The UNEP/IOC-UNESCO methodology for comprehensive beach surveys has been developed with reference to a numberof existing survey protocols, including OSPAR and NOWPAP protocols.
12 Ocean Conservancy International Coastal Clean-up initiative:
https://oceanconservancy.org/trash-free-seas/international-coastal-cleanup/
13 NOAA Marine Debris Monitoring and Assessment Citizen Science Project:https://marinedebris.noaa.gov/research/marine-debris-monitoring-and-assessment-project

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Level 2: Floating plastics (averagecount of plastic items per km2)
METHODOLOGY: GESAMP Guidelines(GESAMP 2019)•

Step one: Identify the national authority•

Step two: Work with planning authority toresponsible for gathering data and reporting onunderstand local needs and determine themarine pollution and the agency/organisation

best monitoring approach. Descriptions

responsible for monitoring floating plastics.

of various approaches from the GESAMP
Guidelines are listed in Table 7 adapted fromthe GESAMP Guidelines.

Table 7: Monitoring methods for floating plastics

MethodDescription

Advantages

Limitations

Examples of use

Net tows

Floating plastics can

Easily deployed

Weather dependant

Viršek et al (2016)

be sampled usingfrom small to largea specific net withvessels

Prone to contamination

Lebreton et alwings built to keep iton the surface.

Underway sampling
Use of flow meter toestimate volume

Volume of water filtered(2018)

can only be estimatedwith flow meter
Towing speed andtime are limited due topotential net clogging
and under-sampling
surface waters
Materials smaller than
the net mesh are lost

Mega net

Large net to capture

Captures macro andlarger litter thanmeso litter

standard nets

Weather dependent
Due to the size, theLebreton et al(2018)

requirements to use thenet are great

Bulk water

Sampling large

Known volume

Litter fractions are small

samplevolume of water andsamplebecause the volume

volume reducing

It is possible tosample fromSong et al (2014)

that can be processed
is limited

vessels of

May be prone toopportunity

contamination

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MethodDescription

Advantages

Limitations

Examples of use

VisualSurveyors identify

Easy to do

Limited in location

Ryan (2013)

observations

floating marine litterfrom vessels of

because can only survey

from a shipfrom a vessel

opportunity

near the vessel

Use either fixed

Low cost andBiased based on what is

width transects

low equipment

easily visible(assuming all litter

requirements

Prone to error basedseen) or distanceon experience ofsampling (corrects forthe surveyor

decrease in detection
probability with
distance from vessel)
Photographic

Visual survey ofand aerial

floating marine littersurveysfrom an airplane or

Cover large areas
Good for mega-litter

High cost and highLebreton et al

equipment requirements(2018)

Limited to macro anddronemega plastics
Biased based on what
is easily visible by
the equipment

Level 2: Water column plastics(average count of plastic items
per km3)
METHODOLOGY: GESAMP14 Guidelines(GESAMP 2019)•

Step one: Identify the national authority•

Step two: Work with planning authority toresponsible for gathering data and reporting

understand local needs and determine theon marine pollution and the agency/

best monitoring approach. Descriptionsorganisation responsible for monitoring waterof various approaches from the GESAMP

column plastics.

Guidelines are listed in Table 8 adapted fromthe GESAMP Guidelines.

14 GESAMP (2019). Guidelines or the monitoring and assessment of plastic litter and microplastics in the ocean (Kershaw
P.J., Turra A. and Galgani F. editors), (IMO/FAO/UNESCO-IOC/UNIDO/WMO/IAEA/UN/UNEP/UNDP/ISA Joint Group ofExperts on the Scientific Aspects of Marine Environmental Protection). Rep. Stud. GESAMP No. 99, 130p
https://environmentlive.unep.org/media/docs/marine_plastics/une_science_dvision_gesamp_reports.pdf

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Table 8: Monitoring methods for water column plastics

MethodDescription

Advantages

Limitations

Examples of use

Bongo nets orNets used for

Easily deployable from

Prone toDoyle et al (2011)

horizontally

surveying thevessels

contamination,

hauled plankton

mid-water regionnets

in samples

Applicable at various
depthsUse of flow meter toestimate volume

particularly in sample
collection on thevesselUnder identifies
materials smaller thanNot weather dependent

the mesh

Paired with other nets

Vessel speed may be

for multiple sampling

restricted

Underway

Utilizing seawater

Ability to sample a

The size range of litter

Desforges et al

pumps

intakes fromknown volume of water

identified is limited(2014)

vesselsover a given time or

The sea state can

Lusher et al (2014)

distance
Easily controls forcontamination on vessel

impact results
Prone tocontamination fromsampling apparatus

Submersible

Deck pumpKnown volume of

The size range of litter

pumps

lowered to awater sampled

identified is limited

known depth

Setälä et al (2016)

The vessel must
be stationary

Bulk sample

Sampling large

Known volume of water

Prone tovolume of water

sampledcontamination on deck

Song et al (2014)

Continuous

Ability to use for a large

Risk ofThompson et alplankton recorderdistance and fromunderestimating(2004)

towed from ships

vessels of opportunity

larger particles due toand volume
reducing
CPR

underway

Ability to compare to

In use since 1946

archived samples

Fisheries

Ability to be

No equipment required

observeropportunistic bycapturing marine
litter samples
using pelagic
fishing gear

Observing long line
fisheries that capture
mostly nets and line

intake size

Dependent on

Uhrin (2018)

fisheries reporting
litterUnsystematic and not
specific to a selectedarea

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Level 2: Seafloor litter (averagecount of plastic items per km2)
METHODOLOGY: GESAMP Guidelines15(GESAMP 2019)•

Step one: Identify the national authority•

Step two: Work with planning authority toresponsible for gathering data and reporting onunderstand local needs and determine themarine pollution and the agency/organisation

best monitoring approach. Descriptions

responsible for monitoring seafloor litter.

of various approaches from the GESAMP
Guidelines are listed in Table 9 adapted fromthe GESAMP Guidelines.

Table 9: Monitoring methods for seafloor litter

MethodDescription

Advantages

Limitations

Examples of use

Shallow water/

Divers or snorkelers

Ability to be

Biased based on

Spengler and Costa

divingvisually identify

opportunistic bywhat is easily visible(2008)

marine litterusing ongoingbiodiversity
programmes orother existing

Limited locations
and size of areasampledsurveys
Trawling

Collection/ stratified

Good for deeper

Topography of

Spengler and Costa

sampling or fishingwaters and large-

seafloor may lead to(2008)

nets

scale evaluation

underestimation

Collection/ Pole

Opportunity to use

Bottom trawling

trawling

on-going fish stock

has a significant

assessments

impact of benthic
ecosystems

ROVs

Remotely operated

Good for continental

High equipment

Bergmann andvehicles used toslopes, uneven

costs

Klages (2012)

survey the seafloor

terrain and deep

Limited size of area

Miyake et al (2011)seafloor

sampledTekman et al (2017)
Chiba et al (2018)

15 GESAMP (2019). Guidelines or the monitoring and assessment of plastic litter and microplastics in the ocean (Kershaw
P.J., Turra A. and Galgani F. editors), (IMO/FAO/UNESCO-IOC/UNIDO/WMO/IAEA/UN/UNEP/UNDP/ISA Joint Group ofExperts on the Scientific Aspects of Marine Environmental Protection). Rep. Stud. GESAMP No. 99, 130p
https://environmentlive.unep.org/media/docs/marine_plastics/une_science_dvision_gesamp_reports.pdf

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Indicator 14.2.1: Number of countries using
ecosystem-based approaches to manage
marine areas
Target 14.2: By 2020, sustainably manage and protect marine andcoastal ecosystems to avoid significant adverse impacts, including
by strengthening their resilience, and take action for their restorationin order to achieve healthy and productive oceans

Backgroundplace, these plans can be helpful to assess ICZM.
For other countries, it is important to identify ways

From an ecological perspective, ecosystem

to measure existing plans and to build capacity for

approaches consider the connections between

integrated planning. All data for this indicator will

the living organisms, habitats, physical andbe based on country submissions to the Regional

chemical conditions within an ecosystem,

Seas Programme. As monitoring will not be done

focusing on the importance of ecological integrity,

through globally derived products, no level 1

biodiversity and overall ecosystem health. From

indicator is proposed; only level 2 and level 3

a management perspective, ecosystem-based

indicators are proposed.

approaches refer to integrated management
strategies for socio-ecological systems that

In order to promote the use of the Regional Seas

consider ecological, social and economic

as part of the follow-up and review mechanism

factors and apply principles of sustainable

for the Regional Seas, UNEP drafted report on

development. These different ways of interpreting

how Regional Seas data could be directly usedthe ‘ecosystem-based approach’ are reflected infor the SDGs.16

existing indicators. A review of these indicatorsand their underlying methodologies shows two

Level 2: Proposed national indicators:

ways in which Regional Seas Programmes andother key intergovernmental, international or•

Number of countries using ecosystem-

regional bodies are monitoring and assessing thebased approaches to manage marine areas

implementation of ecosystem-based approaches.

(measured through ICZM, marine spatial planor other area-based, integrated planning andmanagement in place)

Proposed indicators for
SDG reporting

Level 3: Supplementary indicators:

Regional Seas Coordinated Indicator 22•‘Integrated Coastal Zone Management (ICZM) is

These are described in Table 10 for information,
but this manual does not go into detailproposed as the primary indicator. For countries
with Marine/Maritime Spatial Planning (MSP) in

16 https://wedocs.unep.org/bitstream/handle/20.500.11822/27295/ocean_SDG.pdf?sequence=1&isAllowed=y

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Table 10: Monitoring parameters for implementation of the ecosystem-approach to trackprogress against SDG Target 14.2.
These indicators are marked as levels 1, 2 or 3, level 1 being global data or globally modelled, level 2 including
national monitoring and level 3 describing all other parameters.
Monitoring parameters

Level 2

Number of countries using ecosystem-based approaches to manage

Level 3✕marine areas (measured through ICZM, marine spatial plan or otherarea-based, integrated planning and management in place)
Ecological parameters (e.g. state of biodiversity, water quality, habitat✕

quality, ecosystem health)Step-by-step guide to implementing the indicator

Level 2: Ecosystem-based
approaches to manage marine
areas in placecoastal and marine/maritime planning andmanagement to complete a questionnaire on
the ICZM plans (Shipman and Petit 2014).
•

Step three: Determine the status ofThis indicator aims to capture ICZM and other

implementation of each plan, andarea-based, integrated planning and management

categorise the spatial map according toin place in waters under national jurisdiction,

implementation stages:

including exclusive economic zones (e.g. marine/
maritime spatial planning, Marine Protected

1. Initial plan preparation

Areas (MPAs), marine zoning, sector specific

2. Plan development

management plans)

3. Plan adoption/designation
4. Implementation and adaptive management••

Step one: Identify national authorities/
agencies/organisations responsible forCollect the questionnaire responses andcoastal and marine/maritime planningdocument the answers to include with theand management.

spatial map as reporting for this indicator.

Step two: Identify and spatially map theboundaries of ICZM plans or other plans

The spatial map showing the boundaries ofat national, sub-national and local level.

relevant plans (produced in step two) could also

Coordinate with the national authorities/

be used to calculate the proportion of national

agencies/organisations responsible forwaters, or national exclusive economic zone,

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be compiled for national territories with theoverlaying the spatial layer of relevant planspossibility to provide regional and global data forwith a spatial layer of national waters, or ofinternational waters/high seas. These accounts

the exclusive economic zone, to identify where

can also be compiled at the sub-national level

the two layers coincide (following a similar

for example at a specific coastline or bay. The

methodology to calculating MPA coveragecomponents of oceans accounts include drivers,

for SDG Indicator 14.5.1 described in theassets (including extent and condition), ocean

relevant chapter).

services (including quantity and value) andgovernance (such as management practices) (UN-

Ideally, all countries should report on the spatial

ESCAP 2018).

boundaries of their relevant plans, including theimplementation stage. However, at a minimum
information on if a plan is in place should
be collected.
It is advised that all policy changes are reported

Level 3: Ecological parameters(e.g. state of biodiversity,
water quality, habitat quality,
ecosystem health)on annually and, in addition, that a review ofchanges in laws be conducted as an assessment

Monitoring ecological parameters in addition

to provide context on the state of environmental

to ecosystem-based management is usefulreporting in a 5-10 year reporting cycle.

to inform the effectiveness of management
practices. Understanding the state of biodiversity,

An additional tool for national planning forwater quality, habitat quality, ecosystem healthoceans includes ocean accounting (UN-ESCAP

and other ecological parameters can reveal2018). These would be an expansion of existing

disturbances in ocean health that may havetools known as System of Environmental

otherwise been overlooked. These disturbances

Economic Accounting – Experimental Ecosystem

can then be addressed in future management

Accounting (SEEA-EEA) (SEEA 2017) and would

and planning.

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Indicator 14.5.1: Coverage of protected areas
in relation to marine areas
Target 14.5: By 2020, conserve at least 10 per cent of coastal andmarine areas, consistent with national and international law andbased on the best available scientific information

Backgroundcurated by relevant Ministries (e.g. of theEnvironment) or National Park Agencies. The

The protection of marine areas is essential fornational data (including boundary data in a

protecting the oceans biodiversity and natural

Geographic information system (GIS) format,

resources. The importance of protection wasalong with associated ancillary information such

recognized in the MDGs and has been recognised

as MPA name, reported surface area, name ofin the SDGs. Due to the fact that the measurement

the management authority, etc.) are reported byof MPAs is well established, this section of thethe relevant authorities to the World Database onreport will not go into detail on the measurement

Protected Areas (WDPA)17, a global authoritativeof MPAs, but will instead propose some additional

database curated by UNEP-WCMC, with support

aspects of target 14.5 which might be consideredfrom International Union for Conservation offor monitoring.

Nature (IUCN). Using the information in the
WDPA, national-level statistics can be produced

Proposed indicators for
SDG reportingon protected area coverage for every country
and territory, on a monthly basis. A more detailed
description of the concepts, methodology anddata sources for the indicator is provided by the

The agreed indicator for SDG Target 14.5,

SDG 14.5.1 metadata18, available from the SDG

as proposed by the IAEG-SDGs, is ‘Coverage

indicators metadata repository19. As this cannotof protected areas in relation to marine

be monitored through global monitoring, level 1

areas’ (14.5.1). This indicator is classified as

and 2 are combined into a single level.

tier 1, meaning that data and methodology
are internationally established and available

Level 1 / 2: Proposed global indicators:

globally. Many countries already collect andmanage data on the coverage of coastal andmarine areas by MPAs, including the underlying•

Coverage of marine and coastal areas byprotected areas

geographic datasets. These data are largely

17 UNEP-WCMC and IUCN 2018. Protected Planet: The World Database on Protected Areas (WDPA) [Online], Cambridge, UK:
UNEP-WCMC and IUCN. Available at: www.protectedplanet.net
18 SDG Indicator 14.5.1 metadata: https://unstats.un.org/sdgs/metadata/files/Metadata-14-05-01.pdf
19 SDG indicators metadata repository: https://unstats.un.org/sdgs/metadata/

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Level 3: Proposed national indicators:•

Coverage, by protected areas, of areas of•Management effectiveness of protected areas

importance for biodiversity and derived•

Connectivity of protected areas

ecosystem services•

Equity in protected area benefits and costs

Table 11: Monitoring parameters to track progress against SDG Target 14.5.
The list of parameters in this table is not exhaustive. These indicators are marked as levels 1, 2 or 3, level 1
being global data or globally modelled, level 2 including national monitoring and level 3 describing allother parameters.
Monitoring parameters
Coverage of marine and coastal areas by protected areas
Coverage, by protected areas, of areas of importance for biodiversity andLevel 2

Level 3✕✕derived ecosystem services
Management effectiveness of protected areas✕

Connectivity of protected areas✕

Equity in protected area benefits and costs✕

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Step-by-step guide to implementing the indicator

Level 1 / 2: Coverage of marine andcoastal areas by protected areas

Countries that are not yet, or irregularly reporting
their national data to the WDPA are encouraged
to do so, according to the data submission

Countries that are already regularly reporting

guidelines available in the WDPA User Manual22.

national data on MPAs to the WDPA do not needAll countries, via the WDPA, should report on

to take further action towards reporting against

coverage of marine and coastal areas by protected

SDG Indicator 14.5.1. Using data reported by theareas as a key parameter. Where in-country

relevant authorities, UNEP-WCMC calculates

capacity or opportunities exist, countries can also

national-level statistics on the coverage ofassess supplementary parameters to address

coastal and marine areas by MPAs, and makes theother elements of SDG Target 14.5 (described in

information available to the UN Statistics Division

the following section). Please refer to Table 11

at their request. Countries can view the national-

for parameters for monitoring progress towards

level statistics produced using the WDPA via the

SDG Target 14.5.

Protected Planet website , where details of the20

step-by-step methodology for calculating national
protected area coverage can also be accessed21(see also Text Box 1).

20 See: www.protectedplanet.net/c/unep-regions
21 WDPA methodology for calculating protected area coverage:
www.protectedplanet.net/c/calculating-protected-area-coverage
22 See: www.wcmc.io/WDPA_Manual

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Text box 1: Calculation of MPA coverage (WDPA methodology):
When calculating protected area coverage, answers to the following questions will have a major influenceon the resulting coverage statistics:
1) What is a protected area?
When calculating protected area coverage, UNEP-WCMC only uses sites that have been reported as meeting
the IUCN definition of protected area23 and/or that of the Convention on Biological Diversity 24. For more
information on protected areas, see the dedicated page on the Biodiversity a to z25.
2) What protected areas data are used?
UNEP-WCMC does not include all sites in the WDPA in protected area coverage calculations. “Proposed”
protected areas are excluded, as are sites submitted as points with no reported area. Currently UNESCO
Man and Biosphere Reserves (MAB)26 are excluded, on the basis that that the MAB sites currently in the
WDPA include buffer and transition zones that in many cases are not protected areas (MAB Core areas
usually coincide with protected areas designated at a national level and are therefore generally accounted
for in the calculations). In cases where data providers request that their data are not shared, UNEP-WCMC
uses these data to calculate coverage statistics, but does not make them available through the Protected
Planet website.
3) Which base map (coastline) layer is used?
UNEP-WCMC uses a custom-designed dataset combining exclusive economic zones and terrestrial country
boundaries, a simplified version of which has been published by Brooks et al. (2016)27. This may differ fromthe more detailed national base layers used by countries to generate their own statistics. Therefore, there isan acknowledged potential for the results to differ slightly from those produced by countries.

23 IUCN definition of protected area: “a clearly defined geographical space, recognised, dedicated and managed,
through legal or other effective means, to achieve the long term conservation of nature with associated ecosystemservices and cultural values” (Dudley, N. (ed.) 2008. Guidelines for Applying Protected Area Management
Categories. IUCN: Gland, Switzerland. p.8-9)
24 CBD definition of protected area: a geographically defined area, which is designated or regulated and managed toachieve specific conservation objectives (Art. 2 of the Convention on Biological Diversity)
25 Biodiversity a to z: protected areas: http://www.biodiversitya-z.org/content/protected-area
26 Protected Planet description of UNESCO Man and Biosphere Reserves: https://www.protectedplanet.net/c/worlddatabase-on-protected-areas/internationally-designated-protected-areas/man-and-the-biosphere-reserves.
Definition of UNESCO MAB sites: https://en.unesco.org/mab
27 Data from Brooks et al. 2016: http://datadryad.org/resource/doi:10.5061/dryad.6gb90.2

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Level 3: Other elements ofTarget 14.5

The first step, in such a calculation, is todetermine which areas are of importance forbiodiversity. A number of different attributes

Coverage, by protected areas, of areasof importance for biodiversity

can be considered when defining areas of
biodiversity importance. Table 12 presents theattributes included in some of the most widely

Protected area coverage alone does not give a fullused, internationally recognised prioritisation

indication of the importance of an area in terms(via criteria) schemes for conservation. Theseof biodiversity (and derived ecosystem services),

schemes also offer spatial data layers to allow

for example the diversity of species that havelocating these areas on the ground. Countries

been protected or the number of people who are

may choose to select one or multiple schemes

benefiting from the protected area (Gill et al. 2017).

from this list, or they may define their own

As such, a calculation of the relative coverage,

national criteria for biodiversity importance.

by protected areas, of those marine areas which

Then and depending on available data,

are of particular importance for biodiversity (andinformation and knowledge, a spatial layer

derived ecosystem services) is a useful approach

can be created that shows areas considered

to assess the comprehensiveness and value ofto be important for biodiversity (and derived

an MPA network.

ecosystem services).

Table 12: A summary of attributes of biodiversity importance included in widely known andused prioritisation schemes for conservation.

EBSA

VME

PSSA

WHS

RamsarIBA

KBA

Natura
2000

AZE
Sites

Uniqueness or rarity



















Special importance for











































✕

?

✕



?

✕

Productivity



✕





✕

✕



✕

✕

Biodiversity



✕







✕

?

✕

✕

life history stages of
species
Importance tothreatened or
endangered species
Vulnerability, fragility,
sensitivity or slow
recovery

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EBSA

VME

PSSA

WHS

RamsarIBA

KBA

Natura
2000

AZE
Sites

Naturalness



✕







✕



✕

✕

Structure

✕





✕

✕

✕

?

✕

✕

Historical

✕

✕

✕



✕

✕

✕

✕

✕

geomorphologicalimportance

The Convention on Biological Diversity’s Ecologically or Biologically Significant Areas: Origins, development,
and current status (Dunn et al. 2014).

Acronyms – explanation and relevant policy instrument/organisation
EBSA

Ecologically or Biologically Significant marine Areas – Convention on
Biological Diversity (CBD)

VME

Vulnerable Marine Ecosystem –FAO

PSSAParticularly Sensitive Sea Area – International Maritime Organisation (IMO)

WHSWorld Heritage Site – UN Educational, Scientific and Cultural Organisation (UNESCO)

RamsarRamsar Sites (Wetlands of International Importance) – Convention on Wetlands ofInternational Importance (Ramsar Convention)

IBA

Important Bird and Biodiversity Areas – BirdLife International

KBA

Key Biodiversity Areas –IUCN, BirdLife International, PlantLife International,
Conservation International, Critical Ecosystem Partnership Fund and others(Note: KBAs include IBAs and AZE Sites)

Natura 2000 European network of protected sites under the European Habitats and Birds Directives – EU
AZE Sites

Alliance for Zero Extinction Sites – Alliance for Zero Extinction

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Table of contents

Part 1
Part 2The second step is to calculate the relativenecessarily ensure that conservation objectives

coverage, by protected areas, of areas ofare met, or that they have even been set andbiodiversity importance. This is done by

documented as part of a management plan.

overlaying the spatial layer of areas of biodiversity

Effective management is essential to ensure

importance with the spatial layer of protectedthat a protected area achieves the intended

areas, in the national waters of the country.

benefits for biodiversity and ecosystem services.

The results can be represented on a map or as a

A number of well-recognised mechanisms

graph showing trends in relative coverage over

for assessing management effectiveness oftime. This approach is already being used, at theprotected areas exist, for example from IUCN

global scale, for tracking progress against Aichi(Hockings et al. 2006). One current approach toTarget 11 of the UN Strategic Plan for Biodiversity

assess, at the global scale, the status and trends(2010-2020), using the indicator “Protected Area

in effectiveness of management of protected

Coverage of Key Biodiversity Areas” .

areas is the Aichi 11 indicator “Protected Areas

28

Management Effectiveness”29, which records theManagement effectiveness ofprotected areas

number and area of assessments of management
effectiveness completed by countries, and theoverall management effectiveness score for each

The designation of a protected area does notaspect of management.

Findings on the bigger picture of SDG 14 – from national
implementation to global monitoring

Implementing SDG indicators atcountry level

gathering systems and/or national indicators inplace that can be built on to implement the SDG
indicators. In contrast, Fiji and other Pacific island

The Global Manual on Ocean Statistics is intended

nations are only just starting to address the SDG

to support countries in their efforts to implementtargets and indicators at country level; here, theindicators for tracking progress against SDG

SDG process is mainly being driven forward at

14. The country missions to Fiji and Colombia

the regional level by the Pacific Regional Seas

highlighted that countries start off from different

Programme and other regional institutions.

contexts, and face different challenges, inOne common challenge that countries in both

implementing the SDG indicators. Some countries,

regions share is limited funds and capacity forlike Colombia, already have centralised data

monitoring programmes.

28 https://www.bipindicators.net/indicators/protected-area-coverage-of-key-biodiversity-areas. Note that information on
the applicability of this approach in the context of the SDGs is available in the SDG 14.5.1 metadata(https://unstats.un.org/sdgs/metadata/files/Metadata-14-05-01.pdf).
29 https://www.bipindicators.net/indicators/protected-area-management-effectiveness

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The recommendation that can be drawn fromare working towards coherent and coordinatedthese country insights is that, where possible, themonitoring approaches within, as well as across,

implementation of indicators for SDG 14 should

regional seas, and could play an importantbe aligned with, and build on, existing national androle in facilitating coordinated international

regional monitoring programmes and indicators,

monitoring efforts.

so as to optimise the use of limited available
resources. The Regional Seas Programmes arewell placed in supporting countries to identify
these synergies and find efficient ways of

Globally applicable methodologies
to track global progress

implementing the SDG indicators.
Finally, the Global Manual on Ocean Statistics

Coordinated international
monitoring of transboundary issues

recognises that the agreed SDG and theirindicators only capture part of the associatedSDG targets. In the long-term, these limitations
will have to be addressed to ensure that SDG 14

As mentioned in the introduction to the Global

is fully met. In the meantime, however, it isManual on Ocean Statistics, many issues

important to focus on what can be realisticallyremain to be resolved in order to achieve moreachieved by all countries, so that data can becomplete global monitoring of transboundary

meaningfully aggregated to give a global picturemarine issues, including in areas beyondof progress towards SDG 14. The Global Manual

national jurisdiction. This will require countries

on Ocean Statistics aims to support this effort by

to work together in a coordinated effort

providing step-by-step indicator methodologies

using both satellite remote sensing and inthat require minimum resources and technicalsitu international surveys, including sharedcapacity, can be integrated with existingdata collection protocols, good data sharing

national and regional approaches, and provide

practices, innovative and cost-effective sampling

the minimum parameters required to monitor

methodologies. The Regional Seas Programmes

progress against SDG Targets 14.1, 14.2 and 14.5.

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SectionR

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Wang, M., X. Liu, L. Jiang, S. Son, J. Sun, W. Shi, L. Tan, P. Naik, K. Mikelsons, X. Wang and V. Lance (2014), Evaluationof VIIRS Ocean Color Products, Proc. SPIE 9261, 92610E, doi: 10.1117/12.2069251.

Understanding the State of the Ocean50© iarecottonstudio | Shutterstock
Understanding the State of the Ocean

51

Appendices© Leonardo Gonzalez | Shutterstock

Table of contents

APart 1

Table of contents

Part 2

SectionA1

Appendix 1:
Summary tables of existing indicatorcompilation (Regional Seas Programmes)

No

Category ofIndicator

Possible regional Seas
Coordinated Indicator

SDG 14(plus SDG
1 SDG 2others)

TWAP indicators

Desirability
in RS

1

Total inputs of nitrogen

Chlorophyll a concentration

14.1

Chlorophyll time

Med / BS/and phosphorus fromas an indicator ofseries; DIN, DIPNOWPAP/

agriculture, sewage

phytoplankton biomass(modelled data) (both

ROPME / SACEP

concentratıon and flux

/HELCOM /and atmosphericnitrogen2

Nairobi

Inputs of marine

Trends for selected priority

POPS (PersistentNOWPAP /chemical pollution

chemicals ıncludıng POPs

14.1

Organic Pollutants)

Nairobi / BS/

Trends for selected

and heavy metals

statusCPPS

Marine Plastic Litter

NOPAP /

priority chemicals
34Overall levels of marine

Quantification andlitter Quantification ofclassıfıcatıon of beach litter

14.1

HELCOM/

beach litter items

items

PERSGA /Nairobi

Ocean warming

Annual mean sea surface

14.2

temperature (25m below the

Sea Surface

AgreedTemperature (SST)

surface)

5

Fish landings

Fish catches within EEZs

Fish landings and

FAO to provide(tonnes) – total capture

14.4

Landed Value, Fishing

inputsproduction

effort, Fish stock
status, Primary
Production required,
Marine Trophic Index,
Fishing in Balance
Index

6

Aquaculture

Application of risk

14.4

FAO to provide inputs

assessment to account forpollution and biodiversity
impacts

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Part 1

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Part 2No

Category ofIndicator

Possible regional Seas
Coordinated Indicator

SDG 14(plus SDG
1 SDG 2others)7

Aquaculture

Destructıon of habitat due

FAO toto aquaculture

provideTWAP indicators

Desirability
in RS

Rural/ Urban

ROPME / MAP

population, %poor,/ NOWPAP/

inputs8

Population pressure /Length of coastal

urbanization

modification and km2 of

14.2

coastal reclamation
9

Eutrophication status

Locatıons and frequency of

SACEP
14.1

algal blooms reported
10

Pollution hot spots30

1. Concentration of Status

Index of coastal

agreedeutrophication
14.1

Floating plastic debris

agreed14.3

Pteropods at risk

ROPME (pH)

14.4

Catch Stock Status,

FAO to provide
inputsof selected pollutant
contamination in biota
and sediments andtemporal trends
2. Number of hotspots
11

Ocean acidification

1. Aragonite saturation
2. pH
3. Alkalinity

12

Level of exploitation of

FAO stock status: % stocks

commercial fisheries

overfished compared toMarine Trophic Index,

MSY

Fishing in Balance
Index

13

Species replacement

Marine trophic index

14.5

Marine Trophic Index

as a consequence

FAO to provide
inputsofcapture fisheries
14

Endangered species

Distribution of Red List

14.5

NOWPAP

Index species
15

Loss of critical habitat

Trends in critical habitat

14.5

extent and condition

Mangrove status;

NOWPAP / CPPS

Reefs at Risk Index;
seagrass; salt marshes

16

National Action Plans% National action plansto reduce input from

ratified / operational

14.1

Transboundary LegalagreedInstruments

LBS

30 Actual pollutıon hotspot and source of hotspot

Understanding the State of the Ocean

54

Part 1

Table of contents

Part 2No

Category ofIndicator

Possible regional Seas
Coordinated Indicator

SDG 14(plus SDG
1 SDG 2others)

TWAP indicators

Desirability
in RS

17

Waste water treatment

1. % coastal urban

14.1

NA

agreed14.1

NAagreed14.2

Transboundary Legalagreedfacilities

population connected to
sewage facilities
2. % of waste water
facilities complying withadequate standards
3. % of untreated waste
water

18

Incentive to reduce

1. % port waste reception

marine litter at source

facilities available
2. Incentives to reduce land
based sources31
3. Amount of recycled
waste on land (%)

19

Climate change
adaptation

1. % national adaptationplans in place

Instruments

2. Sector based national
adaptation plans
3. Number of existing
national and local
coastal and marine plansincorporating climatechange adaptation
20

Fish harvested within

Fisheries measures in place

safe ecological limits

14.4

Catch Stock Status,

FAO to provide(by-catch limits, area-

Marine Trophic Index,

inputsbased closures, recovery

Fishing in Balanceplans, capacity reduction

Index; Fisherymeasures) and multilateral/

Production Potential

bilateral fisheriesof LMEs

management arrangements
21

22

Critical marine habitat% Marine protected areas

under protection

designatedNational ICZM in place

National ICZM guidelines

14.5

Change in ProtectedagreedArea Coverage
14.2

agreedand enabling legislation
adopted

31 In monetary terms

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Part 1

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Part 2

SectionA2

Appendix 2:
Summary of regional seas andother relevant data collection efforts

SDG Indicator 14.1.1a
A review of existing indicators and methodologies

spectrometric methods (for information about

currently used by Regional Seas Programmes

sampling and measuring methods for nutrients,and other key intergovernmental, international orsee for example Oslo-Paris Convention (OSPAR)’sregional bodies highlights three main approaches

eutrophication monitoring guideline on nutrientsfor monitoring coastal eutrophication.

(OSPAR 2013a)).

1. Indicators for the cause of eutrophication

2. Indicators for the direct effects(nutrient input and concentrations): Coastalof eutrophication (e.g. Chlorophyll-aeutrophication is mainly caused by nutrient

concentrations, biomass growth, water clarity/

enrichment of coastal environments. Nutrient

turbidity): Nutrient enrichment of coastalenrichment is a direct consequence of nutrient

waters causes excessive growth of plants, algae

inputs from land-based (and atmospheric)and phytoplankton. This can be monitored bysources, in particular phosphorous andmeasuring the abundance of indicator species,

nitrogen run-off from agricultural fertilisers,

the clarity or turbidity of the water, or Chlorophyll-a

livestock waste and domestic wastewater. Fiveconcentrations. Chlorophyll-a is a pigment

Regional Seas Programmes , as well as the EU

contained in plants, algae and phytoplankton

Marine Strategy Framework Directive (MSFD,

that can be used to measure biomass levels,

subsequently referred to as “Marine Directive”),

thus providing an alternative indicator forinclude input and concentrations of nutrientseutrophication. Chlorophyll-a is the most(nitrogen and phosphorous) as indicators or

frequently used indicator/assessment criterion

assessment criteria for eutrophication. Nutrient

for eutrophication (or primary productivity) acrossconcentrations are measured from in situ water

the 18 Regional Seas Programmes33. In addition,

samples using colorimetric, fluorometric and UV

the European Environment Agency, the EU Marine

32

32 Regional Seas Programmes that use input and concentrations of nutrients as indicator for eutrophication: OSPAR(Northeast Atlantic), HELCOM (Baltic Sea), UNEP-MAP (Mediterranean Sea), CPPS (Southeast Pacific) and NOWPAP(Northwest Pacific)
33 Regional Seas Programmes that use Chlorophyll-a as indicator for eutrophication: OSPAR (Northeast Atlantic), HELCOM(Baltic Sea), UNEP-MAP (Mediterranean Sea), Nairobi Convention (Western Indian Ocean), NOWPAP (Northwest Pacific),(ROMPE sea area), PERSGA (Red Sea and Gulf of Aden) and CPPS (Southeast Pacific)

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Directive, the United States National Oceanic

can also be coupled with modelling, allowing toand Atmospheric Administration (NOAA) andfill gaps in satellite data that might be caused, for

the Global Environment Facility Transboundary

example, by cloud cover. An example of remote

Waters Assessment Programme (GEF-TWAP) also

sensing technology applied is the Northwest

use Chlorophyll-a as indicator for eutrophication

Pacific Action Plan Eutrophication Assessment(or primary productivity).

Tool (NEAT), which is a satellite imagery
technique for detection of potential dead zones

Regional Seas Programmes use twoin the sea. The Regional Seas Programme’s

methodological approaches for monitoring

Northwest Pacific Action Plan will collaborate

Chlorophyll-a:with Google and the Japan Aerospace Exploration
Agency to test NEAT to monitor eutrophication

1. In situ measurements, andby monitoring chlorophyll-a concentration levels

2. Remote sensing using satellite images.

and trends in oceans around the world with cloudcomputing (Liu 2019).

In situ measurements can be obtained fromships carrying measuring devices (e.g. the

3. Indicators for the indirect effects ofContinuous Plankton Recorder ), or fromeutrophication (e.g. dissolved oxygen levels):

moorings, buoys and autonomous underwater

Lastly, four Regional Seas Programmes35 andvehicles equipped with sensors. Setting up

the EU Marine Directive use dissolved oxygen

Chlorophyll-a observatories, where these arelevels in the water as an additional indicator

not already in place, requires considerable

for eutrophication. Oxygen depletion (hypoxia

technological and resource capacity. One way

or anoxia) is an indirect effect of nutrientof reducing the costs of in situ measurements isenrichment caused by bacterial decomposition

to use ships of opportunity, such as commercialof large amounts of dead plants and algae.

vessels or ferries. A less resource intensive

Dissolved oxygen levels can be determined fromalternative to in situ measurements is to monitor

water samples using electrochemical or optical

Chlorophyll-a using satellite remote sensing.

sensors (see for example OSPAR’s eutrophication

Remote sensing also enables larger temporal andmonitoring guideline for oxygen (OSPAR 2013b).

34

spatial coverage, compared to in situ methods,
for example providing daily snapshots of an area

The eutrophication indicators related to theseof approximately 500 metres. Remote sensing

methodologies are summarised in Table 13.

34 Continuous Plankton Recorder: https://www.cprsurvey.org/services/the-continuous-plankton-recorder/
35 Regional Seas Programmes that use dissolved oxygen levels as indicator for eutrophication: OSPAR (Northeast Atlantic),
HELCOM (Baltic Sea), NOWPAP and CPPS (Southeast Pacific)

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Table 13: Summary of eutrophication indicators and assessment criteria currently used by
Regional Seas Programmes and other key intergovernmental, international or regional bodies

Regional Seas
Programme/
Organisation

Indicator/assessment criteria

OSPAR

Harmonised assessment criteria:
Category I: Degree of nutrient enrichment
1. Riverine inputs and direct discharges [nitrogen, phosphorous]
2. Nutrient concentrations [DIN and/or DIP]
3. N/P ratio
Category II: Direct effects of nutrient enrichment (during growing season)
1. Chlorophyll-a concentration (area specific)
2. Phytoplankton indicator species (area specific)
3. Macrophytes including macroalgae (area specific)
Category III: Indirect effects of nutrient enrichment (during growing season)
1. Oxygen deficiency
2. Zoobenthos and fish
3. Organic carbon/organic matter (area specific)
Category IV: Other possible effects of nutrient enrichment (during growing season)
1. Algal toxins

HELCOM

Indicators for eutrophication:
1. Water clarity
2. Nitrogen/DIN
3. Total nitrogen
4. Chlorophyll-a concentration
5. Oxygen debt
6. Inputs of nutrients to the sub basins
7. Phosphorus/DIP
8. Total phosphorus
9. Cyanobacterial bloom index

UNEP-MAP

Common Indicators under Ecological Objective 5 Eutrophication:
1. Common Indicator 13 Concentration of key nutrients in water column
2. Common Indicator 14 Chlorophyll-a concentration in water column

Nairobi Convention

Chlorophyll-a concentration as indicator of phytoplankton primary productivity

NOWPAP

Common Procedures for Eutrophication Assessment (minimum required parameters):
1. Trend in chemical oxygen demand (DOD) or Total Organic Carbon (TOC)
2. Frequencies of red tide and hypoxia events
3. Level and trend in satellite derived Chlorophyll-a

ROMPE

Chlorophyll-a concentration as indicator of phytoplankton biomass

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Regional Seas
Programme/
Organisation

Indicator/assessment criteria

CPPS

Indicator 7 Water Quality Index, parameters include:
1. Phosphate
2. Nitrate
3. Dissolved oxygen
4. Chlorophyll-aEuropean Environment

Indicator 23 Chlorophyll in transition, coastal and marine waters

AgencyEU MSFD (Marine Directive)

Descriptor 5 (Eutrophication) indicators:
Criteria 5.1 Nutrients levels:• 5.1.1 Nutrients concentration in the water column.
• 5.1.2 Nutrient ratios (silica, nitrogen and phosphorus), where appropriate.
Criteria 5.2 Impacts of litter on marine life:• 5.2.1 Chlorophyll concentration in the water column.
• 5.2.2 Water transparency related to increase in suspended algae, where relevant.
• 5.2.3 Abundance of opportunistic macroalgae.
• 5.2.4 Species shift in floristic composition such as diatom to flagellate ratio,
benthic to pelagic shifts, as well as bloom events of nuisance/toxic algal blooms(e.g. cyanobacteria) caused by human activities.
Criteria 5.3 Indirect effects of nutrient enrichment:• 5.3.1 Abundance of perennial seaweeds and seagrasses (e.g. fucoids, eelgrass
and Neptune grass) adversely impacted by decrease in water transparency.
• 5.3.2 Dissolved oxygen, i.e. changes due to increased organic matterdecomposition and size of the area concerned.

EU Water Framework Directive

Chlorophyll-a as phytoplankton parameter indicative of biomass(WFD)
UN Strategic Plan for
Biodiversity (2010-2020)

Indicators for ‘Trends in nutrient levels’ (Aichi Target 8.4) include:
1. Trends in Nitrogen deposition
2. Trends in Loss of reactive nitrogen to the environment
3. Trends in Global surplus of nitrogen
4. Proportion of bodies of water with good ambient water quality
5. Proportion of wastewater safely treated

GEF-TWAP

Chlorophyll-a concentrations and trends as indicator for productivity

NOAA

Chlorophyll-a as indicator of primary eutrophication symptoms

Indicators in italics are not explicitly for eutrophication.

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Part 1

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Part 2SDG Indicator 14.1.1.b
A review of existing indicators andfor beach litter surveys and are used as

methodologies used by Regional Seas

guidance by several Regional Seas Programmes.

Programmes and other key intergovernmental,

The European Commission’s Joint Researchinternational or regional bodies shows thatCentre also provides beach litter monitoring

marine plastic debris is currently monitored

protocols in its Guidance on Monitoring of Marine

in four areas of the marine environment.

Litter in European Seas (European Commission
JRC 2013). Further available guidance documents

1. Plastic debris washed/deposited on beaches orand toolboxes for beach litter monitoring areshorelines (beach litter): Beach litter monitoring

listed in Table 14. Beach litter surveys often

is done through beach surveys following

take place in connection with beach clean-ups

standardised monitoring protocols or guidelines

involving the local public. For example, the Ocean

and can be completed in rapid assessment

Conservancy’s ICC initiative organises beachsurveys or routine monitoring. Rapid assessment

clean-ups around the world using standardised

surveys are applied to understand the effects of

ICC data cards36. The ICC data cards are useda major natural disaster, to establish a baseline

as protocols to collect beach litter data in thefor routine monitoring and to locate accumulation

four NOWPAP (Northwest Pacific) countries as‘hot-spots’ for mitigation. The GESAMP completed

well as some of the Caribbean Member States

Guidelines for the Monitoring and Assessmentof the Cartagena Convention. Another avenueof Plastic Litter in the Ocean that detail various

for collecting beach litter data is through citizen

methods for beach surveys including by typescience programmes, such as the Marineof litter (macro and mega litter, buried macro-

LitterWatch application and data viewer of theplastics, meso-litter and micro-litter). UNEP andEuropean Environment Agency, or NOAA’s Marine

IOC-UNESCO have jointly produced Guidelines on

Debris Monitoring and Assessment Citizen

Survey and Monitoring of Marine Litter (Cheschire

Science Project37.

et al. 2009), which include operational guidelines

36 Ocean Conservancy International Coastal Clean-up data card:
https://oceanconservancy.org/wp-content/uploads/2017/04/OC-DataCards_volunteerFINAL_ENG.pdf
37 NOAA Marine Debris Monitoring and Assessment Citizen Science Project:https://marinedebris.noaa.gov/research/marine-debris-monitoring-and-assessment-project

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Table 14: Available guidance material for beach litter monitoring produced by Regional Seas
Programmes and other intergovernmental, international, regional bodies or national bodies

Regional Seas Programme/
Organisation

Monitoring protocols andguidelines

Available at:Convention for the Conservation

The Arctic Marine Strategic Plan 2015-

https://oaarchive.arctic-council.org/

of Antarctic Marine Living

2025 provides standard data forms

handle/11374/413

Resources (CCAMLR)

and instructions for beach survey data

(Antarctic Sea)

collection (Arctic Council 2015)

European Commission Joint

Guidance on Monitoring of Marine Litter

https://ec.europa.eu/jrc/sites/jrcsh/

Research Centre (JRC)in Europeans Seas

files/lb-na-26113-en-n.pdf(European Commission JRC 2013)NOAANOOA Marine Debris Shoreline Survey

https://marinedebris.noaa.

Field Guide (Opfer et al. 2012), andgov/sites/default/files/

a monitoring toolbox with protocol

ShorelineFieldGuide2012.pdf

documents and field data sheets
NOWPAP (Northwest Pacific)

Guidelines for Monitoring Marine Litter

http://www.cearac-project.org/RAP_

on the Beaches and Shorelines of the

MALI/monitoring%20guidelines.pdf

Northwest Pacific Region(NOWPAP CEARAC 2007)
OSPAR (Northeast Atlantic)

UNEP and IOC-UNESCO

Guidelines for monitoring marine litter on

https://www.ospar.org/ospar-

the beaches in the OSPAR Maritime Area

data/10-02e_beachlitter%20(OSPAR 2010)

guideline_english%20only.pdf

UNEP/IOC Guidelines on Survey andhttp://staging.unep.org/gpa/

Monitoring of Marine Litter

Documents/Publications/(Cheshire et al. 2009)

MarineLitterSurveyand
MonitoringGuidelines.pdf

UNEP

Marine plastic debris and microplastics

https://wedocs.unep.org/rest/– Global lessons and research to inspire

bitstreams/11700/retrieve

action and guide policy change(UNEP 2016b)
GESAMP

Guidelines for the Monitoring andhttps://environmentlive.unep.org/

Assessment of Plastic Litter in the Ocean

media/docs/marine_plastics/une_science_dvision_gesamp_reports.pdf

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2. Plastic debris in the water column: Marine

4. Plastic ingested by biota (e.g. sea birds):

litter in the water column is monitored based on

The GESAMP guidelines outline methods forthe identification goals, the type of litter targeted

monitoring plastic ingested by biota such as

and the conditions of the sampling location.

taking samples from dead organisms and

The GESAMP guidelines explain various methods

sampling from live animals via regurgitated pellets,

based on the composition, size and location of thescat, nesting material or entangled litter. The

marine litter including considerations for the goals

guidelines also describe options for monitoringof the monitoring (GESAMP 2019). Methods include

various biota groups including: phytoplankton,

visual and/or photographic observations fromzooplankton, shellfish, other invertebrates andships or airplanes, bulk water samples, surface

marine mammals, birds and fish (GESAMP

water and water column trawls and remote sensing.

2019). OSPAR (Northeast Atlantic), UNEP-MAP

Visual observations and trawls usually make(Mediterranean Sea) and the EU Marine Directive

use of monitoring activities for other ecologicalalso include provisions for monitoring marine

variables (e.g. fish populations). HELCOM (Helsinki

plastic litter through analysis of plastic ingested

Commission, Baltic Sea), UNEP Mediterranean

by stranded marine biota (mainly seabirds, turtles

Action Plan (UNEP-MAP; Mediterranean Sea) andand fish). This approach is limited by the natural

the South Asian Seas Action Plan have indicators

range of the indicator species and consistency

and methodologies in place for monitoring marineof availability of stranded animals, as well as

litter in the water column. Methodologies forrequiring the capacity to collect and analyse thefloating litter are also included in the guidelines

animals. In addition to ingestion by marine biota,

from UNEP/IOC-UNESCO and the European

the EU Marine Directive, as well as the Convention

Commission Joint Research Centre.

for the Conservation of Antarctic Marine Living
Resources (CCAMLR, Antarctic Sea), also consider

3. Plastic debris on the seafloor/seabed:marine plastic found in nests and seabird colonies

Methodologies used to monitor litter onand marine mammal entanglement.

the seafloor include that used by Europe’s
International Bottom Trawl Surveys (IBTS)

The marine plastic debris indicators related toand other fish bottom trawls, as well as visual

these methodologies are summarised in Table 6.

observations by divers and snorkelers (shallow

While the monitoring methods described above

waters), submersibles, remotely operated

focus largely on microplastics, some of the existingvehicles and camera tows (shallow andindicators also refer to microplastics. HELCOM

deeper waters). Three European Regional Seas

(Baltic Sea) and the European Commission Joint

Programmes currently have indicators andResearch Centre provide guidance on monitoring

monitoring methodologies in place for seafloor

methodologies for microplastic particles: 1) manta

litter. Guidance on seafloor litter monitoring

trawls/plankton nets in the water column, andmethodologies is also included in the guidelines2) sieving of sediment/sand samples fromfrom GESAMP, UNEP/IOC-UNESCO and thebeaches or the seafloor. Further guidanceEuropean Commission Joint Research Centre

on sampling and analysing of microplastics(GESAMP 2019).

is provided by GESAMP, Working Group 4039,

38

38 Regional Seas Programmes that are monitoring seafloor litter: OSPAR (Northeast Atlantic), HELCOM (Baltic Sea) and
UNEP-MAP (Mediterranean Sea)
39 GESAMP Working Group 40 is led by IOC-UNESCO and UNEP.

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which in 2016 produced a report on Sources,

Environment (GESAMP 2016) to inform the Second

Fate and Effects of Microplastics in the Marine

UNEP Assembly.

Table 15: Summary of marine plastic debris indicators currently used by Regional Seas
Programmes and other key intergovernmental, international or regional bodies

Regional Seas Programme/
Organisation

Indicator/assessment criteria

OSPAR

Three marine litter indicators:
1. Beach litter
2. Plastic particles in Fulmars’ stomachs
3. Seabed litter
Indicators under development:• Indicators using other biota• Indicators for microplastics

HELCOM

HELCOM indicators for marine litter:
1. Indicator on beach litter
2. Status of implementation of the HELCOM Regional Action Plan on Marine Litter
Indicators under development:• Litter on the seafloor• Micro litter in the water column

UNEP-MAP

Common Indicators under Ecological Objective 10 Marine Litter:• Common Indicator 22: Trends in the amount of litter washed ashore and/or
deposited on coastlines.
• Common Indicator 23: Trends in the amount of litter in the water column
including microplastics and on the seafloor.
• Candidate Indicator 24: Trends in the amount of litter ingested by or entangling
marine organisms focusing on selected mammals, marine birds, andmarine turtles.

NOWPAP

Indicator for marine litter (Ecological Quality Objective 5) to be developed

UNEP

Beach litter as an indicator for floating plastic debris density

UN Strategic Plan for[…] Floating Plastic Debris Density (Aichi Target 8)

Biodiversity (2010-2020)
Ocean Conservancy

Ocean Trash Index: presence of litter items in five ‘activity categories’:
1. Shoreline and recreational
2. Ocean and waterway
3. Smoking related
4. Dumping
5. Medical or personal hygiene

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Regional Seas Programme/
Organisation

Indicator/assessment criteria

EU MSFD (Marine Directive)

Descriptor 10 (Marine litter) indicators:
Criteria 10.1 Characteristics of litter in the marine and coastal environment:• 10.1.1 Trends in the amount of litter washed ashore and/or deposited oncoastlines, including analysis of its composition, spatial distribution and, where
possible, source.
• 10.1.2 Trends in the amount of litter in the water column (including floating at
the surface) and deposited on the seafloor, including analysis of its composition,
spatial distribution and, where possible, source• 10.1.3 Trends in the amount, distribution and, where possible, composition of
microparticles (in particular microplastics).
Criteria 10.2 Impacts of litter on marine life:• 10.2.1 Trends in the amount and composition of litter ingested by marine
animals (e.g. stomach analysis).

SDG Indicator 14.2.1
Indicator 14.2.1 refers to the management ofmethodologies may vary between different

exclusive economic zones using ecosystem-

locations within one region.

based approaches.
2. Indicators for integrated management and1. Ecological indicators for the quality of marine

planning strategies for socio-ecological systems:

ecosystems: OSPAR (Northeast Atlantic) and

Other ecosystem approach indicators are based on

UNEP-MAP (Mediterranean Sea) are using

the implementation status of marine area-based,

ecological indicators to monitor and assess theintegrated planning and management approaches,

implementation of the ecosystem approach.

such as Marine/Maritime Spatial Planning (MSP)The OSPAR indicators are in line with theand/or Integrated Coastal Zone Management

descriptors of ‘good environmental status’ which(ICZM). HELCOM (Baltic Sea) has adopted theare used to assess ecosystem-based marine

ecosystem approach as one of ten Baltic Sea

management under the EU Marine Directive.

Broad-Scale Maritime Spatial Planning Principles

The ecological indicator approach taken by OSPAR,(HELCOM-VASAB 2010) and has identified

UNEP-MAP and the EU requires the measurementdrawing up and application of maritime spatial

and monitoring of a large number of biochemicalplans throughout the Baltic Sea by 2020 as one ofparameters for an integrated assessment of thethe HELCOM regional targets that will contributestate of marine ecosystems and biodiversity.

towards the delivery of SDG 14.2 (HELCOM 2017).

This implies high levels of resources and technical

The HELCOM indicator for the delivery of thiscapacity for ecological monitoring. Moreover,target is ‘number of countries having maritime

as evidenced by experience in the OSPAR

spatial plans coherent across borders and applying

region (Northeast Atlantic), the applicability andthe ecosystem approach’. Similarly, the Strategic

relevance of ecological indicators and associated

Action Plan under the Nairobi Convention

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The ecosystem approach indicators and‘Integrated Coastal Zone Management policies,

assessment criteria described here areplans and/or legislation in place in all countries’ assummarised in Table 16. Referring back to SDG

one of the indicators for protection, restoration

14, Target 14.2 calls for sustainable management

and sustainable management of critical coastal

and protection of marine and coastal ecosystems.

habitats (Nairobi Convention Secretariat 2009).

Integrated planning and management approaches,

The Nairobi Convention indicator is translated

such as Marine/Maritime Spatial Planning or

into a target with a baseline and short, medium

Integrated Coastal Zone Management, have beenand long-term outcomes against which progress

identified as key tools for sustainable, ecosystem-

can be measured. In comparison to ecologicalbased management (Ehler and Douvere 2009).

indicators, management-based indicators incur

Consequently, the implementation of these

low implementation costs, as they do not requireapproaches can be considered as a valid indicator

technical capacity or resources for ecologicalfor ecosystem-based management.

monitoring and can easily be applied at regionaland national levels across the world.

Table 16: Summary of ecosystem approach indicators and assessment criteria currently used by
Regional Seas Programmes and other key intergovernmental, international or regional bodies

Regional Seas Programme/
Organisation

Indicator/assessment criteria

OSPAR

Ecological indicators that are in line with MSDF Descriptors of goodenvironmental status

HELCOM

HELCOM indicator for maritime spatial planning: Number of countries having maritime
spatial plans coherent across borders and applying the ecosystem approach

UNEP-MAP

Common Indicators (ecological indicators)

EU MSFD (Marine Directive)

Descriptors of good environmental standard (ecological indicators)

NOWPAP

Mid-Term Strategy 2018-2023 Objective: NOWPAP countries increasingly apply
ecosystem-based approach to planning and management as a basis to achieve
healthy and productive coastal and marine ecosystems.
Outcomes/ Expected Accomplishments for this priority area:• NOWPAP member states are developing and applying ecosystem-based
management policies, tools and practices to support sustainable development ofcoastal zones and the marine environment;• Planning and decision-making processes for ICZM and MSP by NOWPAP member
states recognize inter-connectedness between the land and the sea and promote
cross-sectoral cooperation;• 1.3. Planning mechanisms, including integrated water resources management,
ICZM and MSP in NOWPAP member states contribute to reduced pressures on the
coastal and marine environment.

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Part 2SDG Indicator 14.5.1
A review of existing indicators and methodologies

Table 17 summarises the key criteria of thefor monitoring the coverage of MPAs useddifferent approaches. The two most frequently

by Regional Seas Programmes and other key

assessed and reported criteria are ‘number

intergovernmental, international or regionalof MPAs’ and ‘total (surface) area covered bybodies shows that six Regional Seas Programmes

MPAs (coverage in km2)’. Some Regional Seas

currently have indicators, assessment criteria

Programmes also calculate ‘the percentage ofor reporting in place for MPA coverage, as does

total marine area covered by MPAs (percentage %)’the Global Environment Facility Transboundaryor ‘changes in coverage (in km2 or percentage %)’.

Waters Assessment Programme (GEF-TWAP).

Table 17: Key criteria of existing indicators, assessment criteria or reporting requirements
related to MPAs that are currently used by Regional Seas Programmes and by GEF-TWAP.

OSPAR

HELCOM

Bucharest
Convention

NOWPAP

CPPS

ArcticCouncil

GEFTWAP

Number of MPAs















Total area covered by



✕





✕









✕



✕



✕

✕

✕



✕







✕

✕

✕

✕





✕

Management in place





✕

✕

✕

✕

✕

Ecological coherence



✕

✕

✕

✕

✕

✕

Geographic extent

✕

✕

✕

✕

✕

✕



MPAs (km2)
Percentage of total
marine area covered by
MPAs (%)
Trends/changes in MPA
coverage (km2; %)Distribution across IUCN
management categories(in terms of global
distribution of MPAs)

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Percentage of marine

OSPAR

HELCOM

Bucharest
Convention

NOWPAP

CPPS

ArcticCouncil

GEFTWAP

✕

✕

✕



✕

✕

✕

areas covered by MPAs
in relation to Aichi
Target 1140

Existing regional approaches to calculating MPA

Others use the protected area definition41 andcoverage require clear definitions of 1) what is

management categories42 of the IUCN. CPPS

considered as an MPA, and 2) the total (surface)(Southeast Pacific) and the Arctic Council (Arctic

area considered by the indicator. These areSea), for example, report on the distribution of

prerequisite for being able to calculate MPA

MPAs across IUCN management categories.

coverage, and the proportion (percentage) of
total marine area covered. Some Regional Seas

MPA coverage indicators and assessment criteria

Programmes, for example OSPAR (Northeast

currently used by Regional Seas Programmes

Atlantic) and HELCOM (Baltic Sea) have theirand other key intergovernmental, international orown definitions of what they consider as an MPA.

regional bodies are summarised in Table 18.

40 UN Strategic Plan for Biodiversity (2010-2020) – Aichi Target 11 By 2020, at least 17 per cent of terrestrial and inland water
areas and 10 per cent of coastal and marine areas, especially areas of particular importance for biodiversity and ecosystemservices, are conserved through effectively and equitably managed, ecologically representative and well-connected systems ofprotected areas and other effective area-based conservation measures, and integrated into the wider landscape and seascape.
For more information about the target: https://www.cbd.int/sp/targets/rationale/target-11/
41 IUCN definition of protected area: “a clearly defined geographical space, recognised, dedicated and managed, through legal orother effective means, to achieve the long term conservation of nature with associated ecosystem services and cultural values”(Dudley, N. (ed.) 2008. Guidelines for Applying Protected Area Management Categories. IUCN: Gland, Switzerland. p.8-9.)
42 IUCN protected area management categories: Ia Strict Nature Reserve, Ib Wilderness Area, II National Park, III Natural
Monument or Feature, IV Habitat/Species Management Area, V Protected Landscape/Seascape, VI Protected area withsustainable use of natural resources. Online: https://www.iucn.org/theme/protected-areas/about/protected-areacategories

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Table 18: Summary of MPA coverage indicators and assessment criteria currently used by
Regional Seas Programmes and other key intergovernmental, international or regional bodies.

Regional Seas
Programme/
Organisation

Indicator/assessment criteria

OSPAR

Criteria for assessing the ecological coherence of OSPAR MPAs:
1. Geographically well distributed (connectivity),
2. Cover at least 10% in area of all biogeographic provinces (representativeness),
3. Represent all EUNIS Level 3 habitat classes and OSPAR threatened and/or declining
species and habitats (features and resilience).

HELCOM

HELCOM indicators:
1. Coverage of protected areas in relation to marine areas, including in individual subbasins of the Baltic Sea and exclusive economic zone
2. Percentage of HELCOM MPAs having management plans or measures in place

Bucharest Convention

Indicator for Ecological Quality Objective 2b (Conserve coastal and marine habitats andlandscapes): Number and total area of marine and coastal protected areas increased

NOWPAP

Reporting on:• Number of MPAs
• Area of MPAs in km2• Total regional coverage of MPAs in % of exclusive economic zone

CPPS

Indicator 1: Marine and Coastal Protected Areas, reported as:
1. Number of marine and coastal protected areas per IUCN category
2. Total surface of marine and coastal protected areas per IUCN category (km2)
3. Marine and coastal surface area by country
4. Marine and coastal protected areas in the Southeast Pacific5. Increase in surface area of marine and coastal protected areas bycountry 2004–2015 (km2)
6. Percentage of marine and coastal protected areas in relation to Aichi Target 11

Arctic Council

Reporting on:
1. Number and area covered (% and km2 of Arctic marine area), based on clear
definitions of Arctic marine area boundaries (from the Conservation of Arctic Floraand Fauna (CAFF) working group) and of MPAs;
2. Trends in MPA coverage within the CAFF boundary 1900-2016 (in % of area covered)
3. Distribution of MPAs across each of the six IUCN Management Categories (in % ofarea covered)
Also reporting on number and area covered (% and km2) of other area-based measuresof importance for Arctic marine biodiversity, including % within MPAs:
1. Areas of heightened ecological and cultural significance2. Ecologically or Biologically Significant marine Areas (EBSAs)
3. Particularly Sensitive Sea Areas (PSSAs)

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Regional Seas
Programme/
Organisation

Indicator/assessment criteria

GEF-TWAP

Indicator: Change in protected area coverage within Large Marine Ecosystems (LMEs)
1. Number
2. Total area
3. Geographic extent
4. Index of percentage change (1982-2014) in total area covered by MPAs per LME© Tom Fisk | Pexels

5. Cumulative area of MPAs in all LMEs

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SectionA3

Appendix 3:Country case studies and examples

As mentioned, the approaches in this manual

manual was pilot testing in Colombia and Fiji.

have been extensively testing in various Regional

The country case studies in this section focuses

Seas Programmes. In addition, the experiences

on Fiji and Colombia while also brining in someon specific indicators, the overall approach in thisadditional information and experiences.

SDG Indicator 14.1.1a
Deviations in chlorophyll-a for different thresholds

the West Coast and the Gulf of Mexico). Based on

was analysed in order to choose a threshold forthis analysis, negligible and moderate deviations

anomalies. This approach was tested in Australia,

as defined below are relatively common whereas a

Italy, Madagascar and the United States (including

cut of 50% represents an anomaly.

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Text Box 2 summarises findings from the country

and national capacity for using satellite remote

missions to Fiji and Colombia on national

sensing to collect Chlorophyll-a data for tracking

monitoring programmes for eutrophication,

progress against SDG Target 14.1.

Text Box 2: Insights from the country missions on eutrophication monitoring using Chlorophyll-a

Fiji: Focus on regional scale and institutions
Fiji does not currently have a national monitoring programme for eutrophication. Using satellite remotesensing to provide Chlorophyll-a data for monitoring eutrophication was seen as a possible option by thegovernment representatives consulted during the country mission. However, an issue of scale was noted:
would satellite image resolutions be sufficiently fine for the monitoring of eutrophication around small
islands? For Fiji and other small, multi-island states in the Pacific, satellite remote sensing of Chlorophyll-amight be more appropriate to monitor eutrophication at a regional scale than at country/island level.
In this context, it is worth noting that, for Fiji and other Pacific island states, regional institutions play animportant role in data collection, indicator assessment, reporting and policy implementation. Key regional
bodies are the Secretariat of the Pacific Regional Environmental Programme (SPREP; i.e. the Secretariatof the Pacific Regional Seas Programme), and the Pacific Community, a regional intergovernmentalorganisation that supports the island states and has responsibility for data. This regional support is key as
Pacific island states often lack the resources and capacity for large scale data collection and monitoring.
Of note is the fact that SDG Indicators 14.1.1a and 14.1.1b are not included in the 109 SDG indicators that
the Pacific SDGs Taskforce and the Pacific Statistics Steering Committee has decided to take forward in
the region. This could present a major issue for countries in the region, such as Fiji, given the major role that
regional bodies play there in monitoring and reporting.
Colombia: Strong in-country capacity for national monitoring
Colombia is not currently monitoring eutrophication at national level. It is understood that data collected on
dissolved oxygen, nutrients, Chlorophyll-a and microplastics feed into the national indicator on marine andcoastal water quality.
For Chlorophyll-a, Colombia is using satellite observations from the NASA MODIS-Aqua mission, withdaily temporal resolution, and spatial resolution of 1 km, as well as monthly composite images at 4 km.
The Chlorophyll-a satellite data are calibrated with samples taken in situ and measured in the laboratory by
spectrophotometry, using the Lorenzen method.
Colombia has in-country capacity for using satellite remote sensing to monitor Chlorophyll-aconcentrations at national level. The country is currently planning a pilot study at sub-national level anddeveloping a roadmap for monitoring Chlorophyll-a.

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Text box 3 illustrates two examples of Southpollutants that could contribute to chlorophyll

African cities evaluating marine pollution andspikes and portray a need for collecting data toseeking to understand the impacts on theinform indicator 14.1.1a so that localities have themarine environment. These examples include

resources to respond to pollution events.

Text Box 3: Challenges in Monitoring Marine Outfall Sites in South Africa

Durban: Environmental Surveys in Outfall Regions
Researchers in Durban have developed a monitoring programme to study the effects of wastewater
discharge into the marine environment (Newman 2019). Many coastal cities discharge their wastewater tothe sea through deep water outfalls, but due to the changing composition of modern wastewater (as a resultof shifts in household and industry waste), there is limited knowledge about the impacts of these outfalls on
the marine environment.
The monitoring programme in Durban is managed by The Council of Scientific and Industrial Research(CSIR) and it has lasted over 40 years, making it one of the longest continuous monitoring programmesin South Africa (Newman 2019). This monitoring programme is an example of how sub-national datacollection is important. Information from this monitoring programme could build toward data collection forindicator 14.1.1a.
Cape Town: Responding to New Pollutants in Sewage Outfall Sites
Cape Town needs to adapt wastewater treatment technologies in response to recent evidence thathousehold pollutants are spiking in the marine environment (Petrik et al 2017). Following proposals to
produce drinking water by desalination, this study examined the marine environment near sewage outfall
sites to assess evidence of factors that could only have been sourced from human sewage. The findings
confirm that seawater and beach water samples occasionally present health risks. Despite these findings,
city officials failed to respond, with recent articles stating that the city did not publish water quality tests
for two years and that chemicals from sewage outfall sites are accumulating on Cape Town beaches(Kretzmann 2019a; Kretzmann 2019b). This lack of data is a critical issue to approaching solutions; in
response, researchers are calling for investigation into new treatment technologies.
Ongoing monitoring and data collection toward SDG 14.1.1a as recommended throughout this manual
could support this issue with a knowledge base to inform past pollutants. This could assist in developing
new technologies by providing proof that the new technologies are required to respond to the pollutants.
Furthermore, the data nationally could build capacity and therefore help local governments with guidance toon how to react to marine pollution problems.

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Part 2SDG Indicator 14.1.1b
For modelling of plastic flow, the below is thesimulation. Colour-shaded countries have particles

results of a simulation of particle accumulationthat reached Kenya coast. For legibility purpose,in Kenya based Simulated particles that flow

1 out of 5 particles are shown for Comoros

within 15-km of the Kenyan coastline from the(618), Kenya (552), and Somalia (875); 1 out ofeastern African countries (top panel) and from the

10 particles are shown for the United republic of

Asian countries (bottom panel) during the 2-year

Tanzania (1151) and for Indonesia (1073).

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UNEP in collaboration with CSIRO pilot tested

https://uneplive.unep.org/egm, on the CSRIO

the methodology on collecting data. CSIRO has

website or in the GESAMP methodologies.

led pilots (or is in the process of finalizing apilot) int the following countries: Bangladesh,

Text Box 4 summarises findings, from the country

China, Republic of Korea, Vietnam, Chile, Ghana,

missions to Fiji and Colombia, on national

Kenya, Mauritius, Nigeria, Brazil, India, Indonesia,

monitoring programmes for marine plastics, andPakistan, Peru, Philippines, South Africa, Srion using beach litter surveys for tracking progress

Lanka, Thailand and the United States. Moreagainst SDG Target 14.1.

information on this piloting can be found at

Text Box 4: Insights from the country missions on marine plastics monitoring using beach litter

Fiji: Potential to capitalise on existing beach clean-ups
Fiji does not currently have a national monitoring programme for marine plastics. Beach clean-ups dotake place in the country; however, these events tend to be organised locally and data are not generallycollected. A future national monitoring programme could build on these local beach clean-ups byintegrating them into the step-by-step methodology for the beach litter SDG indicator.
Some national and regional data are also available for microplastic concentrations in surface waters,
sediments and organisms. These microplastics data are gathered using NOAA methodologies for marine
samples.
As already noted for eutrophication monitoring (see Text Box 1), regional bodies play a key role in Fijiand other Pacific island states with regard to data collection, indicator assessment, reporting and policy
implementation. As noted earlier, SDG Indicators 14.1.1a and 14.1.1b are not included in the 109 SDG
indicators that the Pacific SDGs Taskforce and the Pacific Statistics Steering Committee decided to takeforward in the region.
Colombia: Focus on microplastics
Colombia is not currently monitoring marine plastics at the national level. However, microplastics data
are being collected in six pilot stations from in situ sediment, water and fish samples. These data areunderstood to feed into the national marine and coastal water quality indicator.

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Part 2SDG Indicator 14.2.1
Text Box 5 summarises findings from the countryof ecosystem-based approaches and using

missions to Fiji and Colombia on national

ICZM plans for tracking progress against

efforts towards monitoring the implementation

SDG Target 14.2.

Text box 5: Insights from the country missions on monitoring the implementation of ecosystembased approach using ICZM

Fiji: Awaiting a national marine spatial planning framework
Fiji is committed to implementing marine spatial planning across its entire national waters, including the
Exclusive Economic Zone. One way for Fiji to realise this commitment might be to adopt a similar approachto that taken in Colombia, which has developed its own tailored ICZM approach, based on UNESCO’s
Methodological Guide to Integrated Coastal Zone Management (Henocque and Denis 2001). This way forward
was noted by participants consulted during the in-country mission. However, a national framework formarine spatial planning or ICZM in Fiji is not yet in place. Consequently, there is currently no clear plan for
the implementation of SDG Indicator 14.2.1 or its ICZM indicator. A possible option noted during the country
mission would be for Fiji to assess the implementation of ecosystem-based management in its waters
through Locally Managed Marine Areas, which are taking an ecosystem-based approach.
Colombia: A national indicator on ICZM implementation
Colombia is already implementing its own national indicator for SDG Indicator 14.2.1. The national indicator‘progress in the implementation of planning instruments for marine and coastal zones’ provides information on
the existence, and state of implementation progress of ICZM in geographically defined coastal zone areas,
which are referred to as Coastal and Oceanic Environmental Units (UAC in Spanish). The indicator measures
the number of UACs that are making progress towards the implementation of ICZM and specifies whatstage of the ICZM implementation process each UAC is at. It is calculated using the following formula:# UAC with progress in N stage from the ICZM methodology x 100# Total of UAC in coastal zones
Where ‘N’ refers to one the following stages:
1.

Preparation

6.

Formulation2.

Characterization

7.

Adoption

3.

Diagnostic

8.

Implementation/Execution

4.

Foresight and environmental zoning

9.

Monitoring and evaluation

5.

Guidelines

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Part 2The indicator results are spatially presented as a map, onto which the UACs are colour-coded dependingon their ICZM implementation stages (see Figure 6). The Colombian indicator currently focuses on coastal
areas but has the potential to be adapted to include the country’s Exclusive Economic Zone.
Colombia’s national indicator approach is very similar to the step-by-step methodology for the‘ICZM protocol’ indicator presented in the Global Manual. The Colombian formula to calculate ICZM
implementation progress could provide an alternative option to the step-by-step methodology for countries
to implement the indicator for SDG Target 14.2.

The colours refer to the different implementation stages: White: no progress; Yellow: preparation; Orange: characterization;
Red: foresight and environmental zoning; Green: formulation and adoption; Brown: implementation/execution;
Blue: monitoring and evaluation. (Source: INVEMAR 2015)

Figure 6:

Spatial distribution of progress in the implementation of ICZM for the period of 1999-2014
in Colombia

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Text box 6 provides an overview of examples

Regional Seas Indicator 22: National Integrated

where ICZM is currently implemented in different

Coastal Zone Management (ICZM) guidelines andRegional Seas Programmes. All examples wereenabling legislation are adopted (see Annex 2).

adapted from the informational document on the

Text Box 6: Examples of ICZM in PracticeMediterranean Sea:
Beginning in 2008, this ICZM protocol was the first adopted at the supranational level, and as a result, there
was call for capacity building to implement the ICZM. With the intent to establish a knowledge base of ICZM
capacities in the region and assess institutional integration, a comprehensive questionnaire (mentioned instep two of ICZM implementation) was developed and circulated. Since, the questionnaire was adapted to
update existing information and a core set of 15 indicators for the Regional Seas to measure effectiveness of
implementation of ICZM policies and programmes. They include: (1) added value per sector; (2) area of builtup space; (3) bathing water quality; (4) commercial fish stocks; (5) coastal and marine litter; (6) economic
production; (7) employment; (8) erosion and instability; (9) natural capital; (10) hypoxia; (11) number ofenterprises; (12) population size and density; (13) sea level rise; and (14) water efficiency index.
Black Sea:
While an earlier plan for the Black Sea Integrated Coastal and Shelf Zone Monitoring and Modeling
Program was existing in 1999, it is unclear what the program achieved. Later, the Black Sea followed
the Mediterranean ICZM Protocol and participated in a similar stock taking survey using the questionnaire(with results published in 2015). Finally, the Black Sea Regional ICZM Guidelines were written and accepted.
Wider Caribbean:
The Caribbean Environment Programme (CEP) serves as the Convention Secretariat for the Cartagena
Convention which was adopted in 1983 and entered into force in 1986. By 1990, CEP identified a regional
programme on Integrated Planning and Institutional Development for the Management of Marine andCoastal resources (IPD) in order to pilot ICZM and to establish a regional methodological framework
document. Shortly after, to strengthen national competence and develop region-wide ICZM approaches,
the Guidelines for Integrated Planning and Management of Coastal and Marine Areas in the Wider Caribbean
Region were published. Currently, Integrating Water, and Ecosystems Management in Caribbean SIDs
(GEF-IWECO) is being implemented to reduce pollution and improve land management.
Northwest Pacific:
NOWPAP was adopted in 1994 and since, the Pollution Monitoring Regional Activity Centre (POMRAC)
established the Integrated Coastal and River Basin Management (ICARM) Working Group in 2007. Following
the Working Group, several publications were developed to establish an overview of management, present
experiences and lessons learned in member countries and build guidelines for users in the NOWPAP

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region. Respectively they include: the 2010 report, Regional Overview on Integrated Coastal and River BasinManagement (ICRAM); Part 1 of the 2015 technical report on Integrated Coastal Planning and Ecosystembased Management in the Northwest Pacific Region and Part 2 of the technical report.
ROPME Sea Area:
ROPME was established through the Kuwait Convention in 1979 and published its Guidelines on Integrated
Coastal Areas Management in 2000. There has not been much evidence for action and successful
implementation of ICZM within ROPME. National efforts are vital to integrate ICZM into planning andmanagement at the national scale first in order to support ICZM development at the regional scale.
Unfortunately, low reporting on ICZM at the national scale causes issues in understanding and supporting
ICZM implementation at the regional scale.
Baltic Sea:
Within this region, there is no existing ICZM documentation, but there is information compiled on Maritime
Spatial Planning (MSP) throughout the region. This information includes maps and documentation of thesea areas, national laws and regulations, governance, contact information, existing spatial plans and plansin development, and other relevant information for MSP. In 2016, the Guideline for the Implementation of
Ecosystem-based Approach in Maritime Spatial Planning (MSP) in the Baltic Sea area was published andadopted by HELCOM. Prior to publication, a Strategic Environmental Assessment (SEA) was conducted
including public consultation and transparent information. This represents how the MSP process can feed
into ICZM, being a broader process than ICZM, and can provide a tool to make target areas and interventions
spatially explicit.

SDG Target 14.2 is broad and encompasses three

As the Fiji government representatives explained,

objectives for marine and coastal ecosystems:

it is not always clear whether conservation efforts

1) sustainable management and protection,

are part of sustainable management or marine

2) resilience, and 3) restoration. SDG Indicator

protection, and thus whether they should be

14.2.1 addresses the first objective: ecosystem-

counted towards SDG Target 14.2 or 14.5.2.

based approaches are a key element ofsustainable management and encompass marine

The objectives of resilience and restoration are

and coastal protection. The latter is further

not covered by SDG Indicator 14.2.1. Resilience

covered by SDG Target 14.5 . This overlap

and restoration are partially covered by ecologicalbetween SDG Targets 14.2 and 14.5 was noted

indicators and ecosystem-based monitoring

during the country mission, by government

programmes, like those under OSPAR (Northeast

representatives from Fiji, as a possible challenge

Atlantic), UNEP-MAP (Mediterranean Sea) andfor implementing the related SDG indicators.

the EU Marine Directive, which provide information

43

43 SDG Target 14.5 By 2020, conserve at least 10 per cent of coastal and marine areas, consistent with national and internationallaw and based on the best available scientific information

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about the status and trends of marine andof marine ecosystems. One possible solution iscoastal ecosystems.

to focus on a set number of regionally relevant
critical habitats, for example the four ‘critical
habitats’ identified by NOWPAP (Northwest

restoration tend to focus on individual marine andPacific) and CPPS (Southeast Pacific):coastal habitats, such as coral reefs, seagrass,mangroves, reefs, seagrass and saltmarsh. Oncesaltmarsh and mangroves. These individuala small number of critical habitats is selected,

indicators cannot be easily aggregated, making

countries could be encouraged to monitor andit difficult to develop a standardised indicator

report on the status and trends of those habitats

and methodology for resilience or restorationthat happen to occur in their jurisdiction.

© iarecottonstudio | Shutterstock

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Text Box 7 summarises findings from the country

towards monitoring and reporting on MPA coverage

missions to Fiji and Colombia on national efforts

to track progress against SDG Target 14.5.

Text box 7: Insights from the country missions on MPA coverage

Fiji: An ambitious national target
According to Protected Planet, 0.92% of Fiji’s national waters are currently covered by protected areas:
11,953km2 of a total marine area of 1,293,035km2 (UNEP-WCMC 2018a). During the country mission, it wasnoted that data on Fiji’s MPAs are submitted to the WDPA by the National Trust of Fiji, with plans for the
Fiji Locally Managed Marine Areas, the Ministry of Environment and the Secretariat of the Pacific Regional
Environment Programme to contribute information in the future.
Fiji has set itself an ambitious target to put 30% of its national waters under protection by 2020.
Colombia: A National Register of Protected Areas
In Colombia, the National Natural Parks (PNN in Spanish) is the national administrative body responsible
for coordinating the national system of protected areas; collated data on protected areas are submitted to
the WDPA. According to Protected Planet, 10.45% of Colombia’s national waters are currently covered byprotected areas: 76,392km2 of a total marine area of 730,742km2 (UNEP-WCMC 2018b).
All information related to protected area coverage is also made available by PNN on the National Registerof Protected Areas (RUNAP in Spanish) 44. RUNAP is a centralised protected area database on which
Colombian environmental authorities can register protected areas under their jurisdiction, and upload
information about these sites. PNN staff provide technical support and training where required to facilitate
this process. The information uploaded into RUNAP includes metadata, geographic data and related
images. RUNAP has an in-built validation and quality control process to ensure that all metadata andgeographical data are accurate before being uploaded into the system. All data on protected area coverage
are made freely available on the RUNAP website a month after a protected area has been declared. Data
users can download geographic data in GIS (Geographic Information System) format (shapefile) andmetadata as PDF (Portable Document Format).

44 Colombia’s National Register of Protected Areas (RUNAP): http://runap.parquesnacionales.gov.co/

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Pilot testing acknowledgements
A special note of gratitude is extended to the

For the pilot testing in Kenya, we wish to thankgovernments of the Republic of Fiji, the Republic

the following individuals for their valued input:of Colombia, the Republic of Kenya, and theCatherine Mbaisi, Antony Mwangi, Caroline

Republic of Seychelles for their involvement in

Muriuki, Charles Lange, Edith Kalo, Issak Elmi,

the pilot testing of this Manual. The participants

James Kamula, Jojina Minis, Maureen Njeri,

at workshops in each country provided valuable

Maymuna Abdinasir, Njoki Mukiri, Protus Musawa,

feedback which contributed to the improvement of

Ruth Ndentu, Sherry Saiva, Sophie Mutemi,

the methodologies herein.

Stephen Katua, Moses Mburu, Siasa Juma,
Saadia Mohamed, Sylvester Maithia, Dan Ashitiva,

For the pilot testing in Fiji, we wish to thank the

Senewa Messopir, Mercy Amai, Nuru Mohamed,following individuals for their valued input: Epeli

Sief Landi, Sidi Kadzitsu, Rogers Wangila, Marcel

Waqavonovono, Litia Kurisaqila, Eleni Tokaduadua,

Otieno, Mohamed Ali Hirey, Abdulahi Omar,

Aisake Batibasaga, Leilani Kotobalavu, Richard

Mohamed Sagara, Haji Shibu, Patricia Akinyi

Veeran, Nanise Kuridrani, Ribanataake Awira,

K’Omudho, Eric Okuku, Mary Chiphatsi, Gilbert

Jeremy Hills, Philipp Gassner, Tommy Moore,

Owato Omondi, Catherine Mwalugha, Linet Kiteresi

Herman Timmermans, Paul Anderson, Amanda

Imbayi, Anne Tek, Ayub Macharia, Joseph Chege,

Wheatley, Anthony Talouli, Vainuupo Jungblut,

Nafialy Mutuma, Betty Ojuka, Lilian Machocho,

Warren Lee Long, Malakai Vakautawale, Molly

Betterman Simidi, Nancy Ogonje, Daniel Letoiye,Powers-Tora, Jeremy Hills, Marta Ferreira, Cherie

Edward Mwamuye, David Olendo, Edward

Morris, Sanjesh Naidu, Sangeeta Mangubhai,

Kimakwa, Zachary Maritim, Karen Njue, Julie Myra

Yashika Nand, Jone Tamanitoakula, Rusila Savou,

Alego, Griffins Ochieng, Dorothy Otieno, Sharon

and Clare Postlethwaite.

Okwany, Irene Westra, Walter von Opzeeland, Joel
Amisi, Angela Kimaru, Lilian Mulupi, Leah Ambani,

For the pilot testing in Colombia, we wish to

Winnie Awuor, Adegbile Oyeronke, Kofi Agbogah,

thank the following individuals for their valued

Refilwe Mofokeng, and Peter Ryan.

input: Diana Nova Laverde, Juan Camilo Barbosa,Carolina Cacino, Gloria Lucia Vargas Briceno,

For the pilot testing in Seychelles, we wish

Francisco Arias, Diana Isabel Gomez, Carolina

to thank the following individuals for their

Garcia, Paula Sierra, Anna Maria Gonzales

valued input: Alain de Comarmond, Nanette

Delgadillo, Constanza Ricaurte Villota, Carlos

Laure, Fredrick Kinloch, Flavien Joubert, Julio

Arturo, Tania A. Romero, Johana Andrea Martinez

Moustache, Marvis Keddy Estico, Francisca

Cuesta, Santiago Arango Botero, Diana Marcela

Veronica Hollanda, Patrick Dubois, Dainise Lyne

Moreno Barco, Andres Ochoa, Oscar Fagua, Ana

Quatre, Amina Giselle Furneau, Ricky Nigel

Maria Gonzalez, Kelly Moreno, Zoraida Jimenez,

Simeon, Marie-Antoinette Micock, Ronny Joseph,

Paula Bueno Martinez, Marta Diaz, Laura

Jude Moustache, Ryley Barbe, Marcus Moumou,

Camacho, Margarita Rozo, Jorge Duarte, Nidia

Camilla Labonte, Farida Moncherry, Alison Lucas,

Mayorga, Maria Claudia Vasquez, Laura Juliana

and Victoria Alis.

Arciniegas Rojas, Sonia Angelica Jurado Caicedo,
Paula Andrea Zapata Ramirez, Jackson Reina, andArgirio De Jesus Ramirez.

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