Indicators are data or combinations of data used to measure and communicate complex phenomena for policy purposes. They simplify complex issues and provide early warnings. Developing good indicators requires defining policy goals, identifying available data sources, selecting appropriate indicators, and testing them. Biodiversity, socioeconomic, and governance indicators are needed at local and regional scales. Key steps in developing indicators include defining goals, identifying data sources, selecting indicators, and ensuring communication and agreement across countries and scales. Sources of uncertainty can arise from assumptions, models, linking evaluation to action, implementation, and mismatches across temporal and spatial scales.

1. • What are indicators?
• Indicators are data or a combination of data
collected and processed for a clearly defined
analytical or policy purpose.
That purpose should be explicitly specified
and taken into account when interpreting
the value of an indicator.
• Indicators generally simplify complex phenomena so
that communication of information to policy-makers
and other stakeholders is enabled or enhanced.
• They are powerful tools that provide feedback and
early warning signals about emerging issues.

2. A framework for Indicators of Sustainable Development
• There is no doubt that there is a need for an indicator-policy
cycle that includes monitoring of biodiversity, socio-
economic, and governance indicators, within an analytical
decision framework applied to local and regional scales and
for multiple resources
• In order to succeed, some steps in the indicator-policy cycle
need to be considered:
– Defined broad policy goals: Clear goals need to be defined
for the indicators.
– Identified the sources of data: Are there enough data to
evaluate de indicators? Without good data, based on
monitoring, it is not possible to develop indicators
• Select the indicators: Indicators need to be tested to
determine their use and validity. Can they detect trend?

3. Key players in the development of indicators for the management of
the coastal system/or coastal zone
Information
Knowledge
Data
Information Managers (Policy- Makers)Stakeholders Scientists
INDICATORS
Process indicators
Stress reduction indicators
Environmental status indicators
Decision support and policy
impact and evaluation
Information in a format that
is relevant and useful to
policymakers.
Inter-disciplinary scientists in
collaboration with subject
specialists.
Collaboration between
policy-makers,
stakeholders and
scientists
Information flux and role of indicators.

4. • The development and election of the indicators for this report
was based on the types of indicators defined by Duda (2002)
as:
• Process Indicators: Traditionally, process indicators have
been a measure of progress in project activities involving
procurement and production (inputs and outputs) of goods,
physical structures and services.
• Stress Reduction Indicators: Stress reduction indicators
relate to the specific, on-the-ground measures implemented by
the collaborating countries. They provide evidence that action
occurred on the ground.
• Environmental Status Indicators: Environmental status
indicators provide measures of actual performance or success
in restoring and protecting the targeted ecosystem or
community

5. • Process Indicators.
1 – Existence and/or adoption of various instruments (policies,
management plans, programs) and their application.
• The capacity to manage fisheries depends on available human and
financial resources as well as on the existence of competent
institutions.
2 – Global, regional and local efforts to promote sustainable coastal
and marine development.
• States should co-operate on bilateral, regional and multilateral
levels to establish, reinforce and implement effective means and
mechanisms to ensure sustainable coastal and marine
development. The management system is consistent with relevant
international conventions and agreements.
3 – Global warming and climate change.
• To recognize the threat of climate change to coastal habitats and to
ensure appropriate and ecologically responsible response

6. • Stress Reduction Indicators
4 – Water quality.
• Healthy waterways are necessary to maintain the variety of
aquatic habitats, and the economic, social and environmental
systems that rely on them. Degree of turbidity and changes in
turbidity levels in coastal and estuarine waters are an indicator for
the conditions of the marine resources.
5 – Levels of toxic substances in the marine environment (organic
and inorganic contamination).
• Monitoring major groups of contaminants (e.g., persistent organic
pollutants, hydrocarbons, heavy metals) dispersed/dissolved in the
water column and/or accumulated on surface sediments provides
a good indication of anthropogenic pollution pressure on the
marine resources.
6– Level of restoration/recuperation of ecosystems and species.
• Habitat measurements help identify and quantify habitat types
(number and percent coverage) and spatial patterns of key
habitats (diversity at the ecosystem-level). Such measurements are
helpful to review the current status of coastal habitats in terms of
natural versus impacted habitats.

7. • Environmental Status Indicators
7 – Changes in the spatial coverage of marine ecosystems.
• Changes in the area of habitat can indicate changing conditions in the
environment that could be caused by natural disturbances or by
anthropogenic factors, such as habitat use and fishing. Geospatial
information improves our understanding of our environment, allows for
more comprehensive and transparent planning, and can help increase
stakeholder participation in environmental management.
8 – Landings/catches from the populations of exploited fishing resources.
• Fish abundance, age and size composition, and length and weight
relationships are the primary parameters scientists require to describe the
status of a fish population. In addition to static parameters (i.e., those at a
single point in time), dynamic parameters that quantify rates of
population processes, such as survival, growth, reproduction and
mortality, provide greater insight into a fish population’s ecological state.
9 – Levels of fishing effort.
•Effective fishing effort” is a measure of fishing mortality. Landings (in terms
of volume or value) and fishing efforts (e.g., number of vessels, types and
number of nets, gear, etc.) may be a useful proxy to assess the quantity of
resources harvested and it may be an indication, although indirect, of the
status of local fisheries and fish stocks.

8. • The development of indicators and their use in evaluating progress
is dependent on a data and information management and reporting
system being put in place by government, non-governmental
organizations (NGOs), civil society, and the private sector. Within
the CLME region there a several national, regional and international
programs targeting the collection of environmental indicators.
These include: CARICOM’s Caribbean Coastal Marine Productivity
Programme, Organization of Eastern Caribbean States (OECS),
UNEP under different programs (such as Caribbean Environmental
Program and Environmental Data Explorer GEO), United Nations
(UNSD Environmental Indicators), World Resource Institute
(Ecosystem Service Indicators database), Worldwide Governance
Indicators, Latin American and Caribbean Initiative for Sustainable
Development (ILAC), The World Bank, and The Nature Conservancy,
among others.

9. • The process of establishing a set of indicators for the CLME in
coastal and marine zones is not easy.
• Significant scientific, technical and administrative effort, as well as,
consensus with stakeholder groups must be achievement before the
definition of indicators and targets are established.
• It also implies agreement between governments (local and regional)
on the intensity of monitoring, the goals and the resources required.
• It is recommended to develop indicator factsheets based on the
existing data. This fact sheets should be regional or country specific
depending of the data available.
• Communication is the key for success of an indicator policy.
• A common framework is needed in the CLME region.
Recommendations on Indicator Information

10. • Indicators must be established under baseline conditions. Indicators are
most effectively assessed when baseline information on the governance,
ecological and socioeconomic conditions of the management area is
available.
• Indicators should relate to the specific management issues, such as
multiple user conflicts, ecological degradation, community interest, or a
commitment to improve the management of a local marine area.
• It is strongly recommended that stakeholders are consulted as early as
possible in the indicator development process in order to determine the
purpose of the indicator and its audience.
• Transparency in the decision making process promotes credibility and
provides opportunities for stakeholders to introduce new information.

11. • The indicators selected for use should be based on the best scientific
understanding currently available and have been developed in
consultation with international and country experts, other agencies and
stakeholder groups.
• The more an indicator meets a real decision-making need and it is
effectively communicated, the greater the likelihood that a national or
regional statistic agency will recognized the value of the indicator.
• The calculation of an indicator must be accompanied by documentation of
the methods used and data sources. This ensures that the calculation is
transparent and open to scrutiny and can be repeated in the future for
consistent production of the indicator.
• The agreement on the indicator set and the standardization of
methodology and formats for compilation and presentation of results
ensures the comparability, correct assessment and aggregation of the
results obtained in different countries and at different scales around the
CLME. Furthermore, the identification of data gaps or limitations will
allow prioritization of effort on the monitoring of required datasets.

12. INSTITUTION NAME
CZMU
ICRI
NEPA
TNC
NOAA-Habitat
INSTITUTION NAME
FAO
OSPESCA
FishBase
SeaAround Us
SocMon
Issue
Poll
ution
Ha
bitat
Degr
adati
on
Type of Fisheries
Coastal
Shelf
Fisheries
Reef Fisheries
Pelagic Fisheries
Coastal
Shelf
Fisheries
Reef Fisheries
Pelagic Fisheries
Coastal
Shelf
Fisheries
Reef Fisheries
Pelagic Fisheries
Coastal
Shelf
Fisheries
Reef Fisheries
Pelagic Fisheries
INSTITUTION NAME
CARICOMP
University of the West Indies (UWI)
UNEP-SPAW
UNEP-GAP
WEBSITE
http://www.unesco.org/csi/act/caricomp /ecosystem.htm
http://www.mona.uwi.edu/cms/ccdc /ccdc.html
http://www.gpa.unep.org/
http://www.cep.unep.org/
http://www.unesco.org/csi/act/caricomp /ecosystem.htm
WEBSITE
http://www.coastal.gov.bb/
http://earw.icriforum.org/
http://www.nepa.gov.jm/index.asp
http://www.nature.org/
http://www.habitat.noaa.gov/ protection/efh/
newInv/index.html.
WEBSITE
http://www.fao.org/index_en.htm
http://www.sica.int/ospesca/
http://www.fishbase.org/home.htm
http://www.seaaroundus.org/
http://www.socmon.org/default.aspx
IMS
INDICATOR BOXWORD DOCUMENT
(Description of the Indicators)
EXCEL FILE
(Includes the
database)
INSTITUTION NAME
Caribbean Climate Centre (CCCC)
Caribbean Policy Centre
(CPACC)
Caribbean Action Plan (CAP)
WEBSITE
http://www.caribbeanclimate.bz/
http://caribbeanresearchandpolicycenter.org/
http://www.cep.unep.org/
DESCRIPTION
Indicators:
Water quality
Amount of
sedimentation.
Frequency of algal blooms
Sources and quantity/velocity of runoff
Levels of toxic substances in the marine
environment (organic and inorganic
contamination).
Origin of sediments
Land use changes.
Indicators:
 Level of restoration/ recuperation
of ecosystems and species.
Area mapped
Spatial and temporal resolution
 Existence of legislation on coastal
and marine resources
 Management plans (guidelines and
regulations)
 Changes in the spatial coverage of marine
Geographical units
Zoning plan
Mapping Essential Fish Habitat
Demographic information
Indicators:
 Landings/catch from populations
of exploited fishing resources.
Changes in the population structure
of exploited species.
Levels of fishing effort.
Existence of regulations or
management plans and their
application.
Indicators:
Global warming and Climate change
Acidification
Sea level rise,
Hurricane incidence.

13. Sources of uncertainty and
potential failure
Examples Solutions Problem
solvers
1) Assumptions in the
evaluation process
Poor problem definition resulting in unclear
goals, badly defined or ambiguous targets
A clear understanding of the problem at
hand, clear goals, and a way of
translating goals into specific and
realistic targets.
Collaboration
between
policy-
makers,
stakeholders
and scientists
Uncertainty in models: underestimating or
not accounting for key processes (e.g.,
ecological responses, the indirect effects of
policy (e.g. redistribution of fishing effort, or
the impacts of other external drivers (e.g.
economic forces or climate change
Strong conceptual frameworks and
inter-disciplinary models, with
sensitivity analyses to understand the
impacts of uncertainties.
Inter-
disciplinary
scientists in
collaboration
with subject
specialists.
2) Link between
evaluation and selection
of actions: most
appropriate course of
action might not be taken
because decision-makers
have other priorities or
the action is unpalatable
Fisheries management: scientific
advice on actions such as total
allowable catch is often not
implemented.
Ensure the set of actions is realistic and
can be implemented through
stakeholder participation and
consultation, and improve
understanding of the public and
decision-makers.
Collaboration
between
policy-
makers,
stakeholders
and scientists
Potential sources of uncertainty and failure identified by Nicholson et al (2012)

14. 3) Link between action
selection and
implementation
Actions may fail to be implemented
effectively due to under-resourcing,
poor governance or lack of
compliance with rules at the local
level. e.g. ineffective protected areas
.
Improved understanding of human
decision making, information on
governance and corruption,
participatory selection of a set of
possible actions to ensure support at
implementation.
Social
scientists,
managers
and
interdisciplin
ary scientists
4) Impact of the action
differing from the
anticipated impact, due
to other drivers, indirect
effects and externalities
The effects of other drivers
obscuring any impact of policy. For
example, poor understanding of the
interactions between harvesting and
fish spwaning aggregations.
Acknowledgement and understanding
of types and sources of uncertainty
during the evaluation process, leading
to better and broader models and
improved information
Inter-
disciplinary
scientists in
collaboration
with
fishermen.
5) Link between
biodiversity change and
indicator change
Poor indicator design renders the
indicator a poor proxy for
biodiversity, e.g. protected area
coverage provides little indication of
the effectiveness of protected areas
in conserving biodiversity
More extensive modelling of the
behavior of indicators as the system
changes; e.g. extensive testing of
indicators in fisheries science;
improved suite of indicators to ensure
a more structured coverage of aspects
of biodiversity change.
Scientists
Data quality makes trends difficult
to detect or interpret due to
taxonomic, spatial and temporal
gaps and biases
More, and more targeted, data, more
systematic sampling of taxonomic
groups, revise indicators to require
less data

15. 6) Link between indicator
change and target
assessment: assessing
indicators against poorly
defined targets, rendering
assessment meaningless
Targets are qualitative or ambiguous. Define targets more clearly and in a
meaningful way, e.g. SMART targets
(specific, measureable, ambitious, realistic and
time-bound).
Scientists and
policy-makers
Targets are not meaningful biologically (e.g.
to avoid tipping points)
Improve understanding of underlying
processes
Scientists
Targets are not compatible, requiring trade-
offs between targets. e.g. different groups of
species provide different ecosystem services
(e.g. climate regulation versus food
production versus biodiversity conservation)
and may have different management needs
Identify potential impacts of alternative
policies and achievability of targets through
modelling; identify and acknowledge trade-
offs, conflicts and synergies between targets
and policies
Scientists and
policy-makers
7) Mismatches in temporal
and spatial scales throughout
the cycle
Policies decided at a range of scales from
global to local; Transboundary effects of
national policies on issues such as fisheries
management; implementation and data
collection occur at the national to local scale.
Identify where spatial mismatches may occur
throughout the cycle; Better negotiation and
cooperation across borders.
Collaboration
between policy-
makers,
stakeholders
and scientists.
Ecological processes at a wide range of
scales from daily to centuries, including
ecological time lags: e.g. extinction debt,
time for stock recovery after reduction of
fisheries pressure
Explicitly consider processes at different
spatial and temporal scales.
Scientists and
policy-makers

16. Indicators for Small Scale Fisheries
Type of Indicator Indicator Explanation
Added value of the artisanal
fisheries at the national level.
Indicates the economic contribution of
fisheries to local incomes
Process
Contribution of fisheries to
national economic development
Including fisheries and associated
economic activities (transport, boats,
marketing)
Resource users involved in small
scale fishing (number and
demographics)
Important for understanding resource
users involved in small scale fisheries
(eg. gender, age)
Stress Reduction
Number of communities
involved in small scale fishing
(including indigenous groups)
Information to guide the development
of training programs
Revenue generated by small
scale fisheries
Allows an assessment of the amount of
fishing effort
Percentage of time spent on this
activity
Amount of time that is dedicated to
these activities compared with other
activities.
Environmental Status
Change in levels of poverty Indicates the condition or well-being
of the population

17. • An indicator approach provides a useful tool
for appraising sustainability and for assessing
policies – in particular for assessing measures
and actions taken or proposed in relation to
marine resources.
• Indicators can help to inform citizens, policy-
makers, scientists and other stakeholders
about the status of marine resources, human
impacts on the marine ecosystem, mitigating
actions and the roles and responsibilities of
stakeholders.

18. A framework for Indicators of Sustainable
Development
• Specify targets that are measurable using
indicators.
• Define actions that can be implemented or
achieve; use models to make predictions
about the potential impacts.
• Indicators must therefore be able to take into
account different locations, people, cultures
and institutions
• All this information can be used to improve
monitoring and collection of better indicator
datasets.

19. Database questions
• The development of an effective indicator framework requires data and
information, as well as appropriate data, information management and
mechanisms to calculate, review and revise the indicators on a continuous
basis. However, there are fundamental gaps in data collection and
monitoring for sustainable development in coastal areas of the CLME. As
mentioned by Heileman and Walling (2008), a number of initiatives have
been undertaken in the region to improve environmental statistics. Some
of the main problems are summarized below:
• The coastal zone is not well represented as a distinct reporting unit or as a
specific area in most GIS information sources or databases.
• There is a lack of coherence in data gathering programs in terms of
geographic and temporal coverage, and in the definition of measurements.
This can be due to the absence of guiding policies, deficient benchmark
information or inadequate analysis.
• Indicators calculated by research centers, government, public
administrations or agencies may be limited in scope (methodology,
definitions, coverage), which restricts their usefulness at a wider regional
level.
• Differences in statistical data between countries may result in a bias in
calculations and in comparison of 'the coastal zone' between CLME
countries, in particular for population and socio-economic data.

20. • Differences in the composition of sampling units for different reporting purposes
may cause inconsistencies at the moment of reporting indicators between
countries and over time.
• Frequency and interval of sampling may not coincide between countries. For
instance, frequency and period of sampling for two related indicators or indicators
(e.g. number of overnight fishing trips and numbers of fishing boats) may not
coincide, generating an unknown bias in the results.
• Changes in methodology over time, within the data gathering program, may create
an interruption and/or a breach in time series. This can be due to changes in
measuring instruments, modifications in the location of measuring stations,
changes in weighting factors in the analysis of data from surveys, etc.
• Geo-referenced data is limited. Data needs to be geo-referenced in order to allow
comparisons and representation of socio-economic and environmental
information.
• Consistent data and data flow should provide a more realistic picture of the
processes taking place and support decision-making at different levels (from local
to national to CLME level). The best way to ensure comparability data or indicators
at all levels is a bottom-up approach in data collecting and information systems:
starting from reliable and sound data at the local level and aggregating it at higher
levels in common databases.