Evaluating indicators of human well-being for ecosystem-based management

Abstract

Introduction: Interrelated social and ecological challenges demand an understanding of how environmental change and management decisions affect human well-being. This paper outlines a framework for measuring human well-being for ecosystem-based management (EBM). We present a prototype that can be adapted and developed for various scales and contexts. Scientists and managers use indicators to assess status and trends in integrated ecosystem assessments (IEAs). To improve the social science rigor and success of EBM, we developed a systematic and transparent approach for evaluating indicators of human well-being for an IEA.
Methods: Our process is based on a comprehensive conceptualization of human well-being, a scalable analysis of management priorities, and a set of indicator screening criteria tailored to the needs of EBM. We tested our approach by evaluating more than 2000 existing social indicators related to ocean and coastal management of the US West Coast. We focused on two foundational attributes of human well-being: resource access and self-determination.
Outcomes and Discussion: Our results suggest that existing indicators and data are limited in their ability to reflect linkages between environmental change and human well-being, and extremely limited in their ability to assess social equity and justice. We reveal a critical need for new social indicators tailored to answer environmental questions and new data that are disaggregated by social variables to measure equity. In both, we stress the importance of collaborating with the people whose well-being is to be assessed.
Conclusion: Our framework is designed to encourage governments and communities to carefully assess the complex tradeoffs inherent in environmental decision-making.

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Evaluating indicators of human well-being for
ecosystem-based management
Sara Jo Breslow, Margaret Allen, Danielle Holstein, Brit Sojka, Raz Barnea,
Xavier Basurto, Courtney Carothers, Susan Charnley, Sarah Coulthard, Nives
Dolšak, Jamie Donatuto, Carlos García-Quijano, Christina C. Hicks, Arielle
Levine, Michael B. Mascia, Karma Norman, Melissa Poe, Terre Satterfield,
Kevin St. Martin & Phillip S. Levin
To cite this article: Sara Jo Breslow, Margaret Allen, Danielle Holstein, Brit Sojka, Raz Barnea,
Xavier Basurto, Courtney Carothers, Susan Charnley, Sarah Coulthard, Nives Dolšak, Jamie
Donatuto, Carlos García-Quijano, Christina C. Hicks, Arielle Levine, Michael B. Mascia, Karma
Norman, Melissa Poe, Terre Satterfield, Kevin St. Martin & Phillip S. Levin (2017) Evaluating
indicators of human well-being for ecosystem-based management, Ecosystem Health and
Sustainability, 3:12, 1-18, DOI: 10.1080/20964129.2017.1411767
To link to this article: https://doi.org/10.1080/20964129.2017.1411767
© 2017 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
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China
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ARTICLE
Evaluating indicators of human well-being for ecosystem-based management
Sara Jo Breslow
a
,MargaretAllen
b
,DanielleHolstein
b
,BritSojka
b
,RazBarnea
b
, Xavier Basurto
c
,
Courtney Carothers
d
, Susan Charnley
e
, Sarah Coulthard
f
,NivesDolšak
b
, Jamie Donatuto
g
,
Carlos García-Quijano
h
, Christina C. Hicks
i,j
,ArielleLevine
k
, Michael B. Mascia
l
, Karma Norman
m
,
Melissa Poe
m,n
, Terre Satterfield
o
,KevinSt.Martin
p
and Phillip S. Levin
q
a
Center for Creative Conservation, University of Washington, Seattle, WA, USA;
b
School of Marine and Environmental Affairs, University
of Washington, Seattle, WA, USA;
c
Nicholas School of the Environment, Duke University, Beaufort, NC, USA;
d
College of Fisheries and
Ocean Sciences, University of Alaska Fairbanks, Anchorage, AK, USA;
e
Pacific Northwest Research Station, USDA Forest Service, Portland,
OR, USA;
f
Department of Social Sciences and Languages, Northumbria University, Newcastle upon Tyne, UK;
g
Community Environmental
Health Program, Swinomish Indian Tribal Community, La Conner, WA, USA;
h
Department of Sociology and Anthropology, The University
of Rhode Island, Kingston, RI USA;
i
Center for Ocean Solutions, Stanford University, Monterey, CA, USA;
j
Lancaster Environment Center,
Lancaster University, Lancaster, UK;
k
Department of Geography, San Diego State University, San Diego, CA, USA;
l
Moore Center for
Science, Conservation International, Arlington, VA, USA;
m
Northwest Fisheries Science Center, National Oceanic and Atmospheric
Administration, Seattle, WA, USA;
n
Washington Sea Grant, University of Washington, Seattle, WA, USA;
o
Institute for Resources,
Environment and Sustainability, University of British Columbia, Vancouver, BC, Canada;
p
Department of Geography, Rutgers, The State
University of New Jersey, Piscataway, NJ, USA;
q
School of Environmental and Forest Sciences, University of Washington, Seattle, WA,
USA
ABSTRACT
Introduction: Interrelated social and ecological challenges demand an understanding of how
environmental change and management decisions affect human well-being. This paper out-
lines a framework for measuring human well-being for ecosystem-based management (EBM).
We present a prototype that can be adapted and developed for various scales and contexts.
Scientists and managers use indicators to assess status and trends in integrated ecosystem
assessments (IEAs). To improve the social science rigor and success of EBM, we developed a
systematic and transparent approach for evaluating indicators of human well-being for an IEA.
Methods: Our process is based on a comprehensive conceptualization of human well-being,
a scalable analysis of management priorities, and a set of indicator screening criteria tailored
to the needs of EBM. We tested our approach by evaluating more than 2000 existing social
indicators related to ocean and coastal management of the US West Coast. We focused on
two foundational attributes of human well-being: resource access and self-determination.
Outcomes and Discussion: Our results suggest that existing indicators and data are limited
in their ability to reflect linkages between environmental change and human well-being, and
extremely limited in their ability to assess social equity and justice. We reveal a critical need
for new social indicators tailored to answer environmental questions and new data that are
disaggregated by social variables to measure equity. In both, we stress the importance of
collaborating with the people whose well-being is to be assessed.
Conclusion: Our framework is designed to encourage governments and communities to
carefully assess the complex tradeoffs inherent in environmental decision-making.
ARTICLE HISTORY
Received 21 July 2017
Revised 15 November 2017
Accepted 19 November 2017
KEYWORDS
Human well-being;
indicators; ecosystem-based
management; integrated
ecosystem assessment;
resource access; self-
determination
Introduction
Global climate change, widespread habitat conver-
sions, and the continued exploitation of natural
resources are dramatically affecting ecosystems and
the people who depend on them (Millenium
Ecosystem Assessment 2005; IPCC 2014; Díaz et al.
2015). It is critical to understand how such unprece-
dented environmental change –and related social
and management changes –affect human well-
being. Here, we develop a framework for measuring
human well-being as part of an integrated ecosystem
assessment (IEA). IEAs are widely used to assess the
status of social–ecological systems and evaluate
management and policy strategies to support ecolo-
gical integrity and human well-being (Levin et al.
2009; Levin and Möllmann 2015). IEAs analyze status
and trends in biophysical and human conditions
through carefully selected sets of indicators.
Indicators are commonly chosen according to prede-
fined criteria for their relevance to management, con-
ceptual validity, sensitivity to environmental change,
measurability, and understandability (Keeney and
Gregory 2005; Rice and Rochet 2005; Boyd and
Charles 2006). Hundreds of indicators have been
proposed for use in IEAs, and there are perhaps
equally as many frameworks for selecting indicators
CONTACT Sara Jo Breslow sarajo@uw.edu Center for Creative Conservation, University of Washington, Box 355674, Seattle, WA 98195, USA
The supplemental data for this article can be accessed here
ECOSYSTEM HEALTH AND SUSTAINABILITY, 2018
VOL. 3, NO. 12, 1–18
https://doi.org/10.1080/20964129.2017.1411767
© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of Ecological Society of China
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits
unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

(e.g., Rice and Rochet 2005; Andrew et al. 2012). Yet
these efforts have largely focused on biophysical,
rather than social, indicators.
In the California Current, the large marine ecosys-
tem running the length of the US West Coast, IEA
practitioners have developed a systematic method for
selecting indicators of ecological integrity (James
et al. 2012; Kershner et al. 2011), but a similar effort
has not been completed for human well-being.
Elsewhere, indicators of human well-being have
been developed to inform sustainable development,
conservation (e.g., Mascia, Claus, and Naidoo 2010),
ecosystem recovery (e.g., Dillard et al. 2013;
Biedenweg et al. 2014), and vulnerability assessments
(e.g., Jepson 2007). We draw from these initiatives,
and modify the approach developed for biophysical
indicators (Kershner et al. 2011; James et al. 2012), to
develop a structured and transparent method for
identifying indicators of human well-being that is
tailored to the needs of an IEA. We present a proto-
type that can be adapted and developed for a variety
of management scales and contexts. Our goal is to
improve IEAs so that they capture the social, as well
as ecological, dimensions of ecosystem-based man-
agement (EBM).
We follow an established protocol for selecting
indicators: identifying overall goals for the assess-
ment, operationalizing these goals through a concep-
tual framework, collecting and developing candidate
indicators, defining screening criteria for selecting
indicators, evaluating the candidate indicators
according to these screening criteria, and selecting a
parsimonious suite of complementary indicators that
delivers useful information toward achieving the
overall goals (Michalos 1997; Sainsbury and Sumaila
2003; Boyd and Charles 2006). We tailor each of these
steps according to social science considerations and
the specific aim of selecting social indicators for
EBM. To ensure its relevance to management needs
(Sojka 2014), our process includes a detailed review
of human well-being goals and responsibilities found
in policy and management documents pertaining to
the California Current ecosystem (Appendix 1). Our
entire process –including conceptualizing human
well-being, developing a method for evaluation, and
evaluating indicators –was conducted over a 2-year
period, guided by a working group of environmental
social scientists with expertise in anthropology, poli-
tical science, geography, and international develop-
ment. If others begin with the frameworks we already
developed, the process will take less time, and we
recommend additional ways to shorten the process
in the discussion.
We test our approach for two focal attributes of
human well-being related to EBM: resource access and
self-determination (for more in-depth discussion of
human well-being attributes related to EBM, see
Breslow et al. 2016). We find these two attributes,
when fully conceptualized, provide rich insight into
multiple areas of human well-being. Resource access
means “the ability to benefit from nature and natural
resources”(Ribot and Peluso 2003) and includes the
physical, economic, legal, social, and cognitive capa-
cities to access these benefits. Self-determination
means the ability for individuals and communities
to shape their own lives and adapt to circumstances,
here broadly connoting agency, free will, and auton-
omy, and most specifically for an EBM context, local
and indigenous sovereignty and participation in deci-
sion-making (Sen 2000; Ryan 2009; Willow 2013).
Resource access and self-determination are interre-
lated attributes and provide a foundation for many
other dimensions of human well-being related to
EBM. When analyzed across social variables, they
are important to understanding inequities in envir-
onmental benefits and decision-making. We illustrate
a systematic process for selecting indicators of human
well-being by screening and evaluating existing indi-
cators of resource access and self-determination.
Conceptualizing human well-being for EBM
and indicator selection
A comprehensive conceptual framework of
human well-being
EBM strives to achieve the mutual well-being of
humans and ecosystems (McLeod et al. 2005), and
an IEA strives to assess conditions to inform choices
about potential management actions in and across
complex systems. To operationalize these aims, we
use a framework that facilitates a comprehensive yet
flexible understanding of human well-being (Breslow
et al. 2016). The framework is designed to address
several of the major challenges in assessing human
well-being: it captures the variable, interdependent,
and subjective qualities of well-being; accommodates
multidirectional relationships among ecological,
social, and management factors; and encourages
broadly comparable categories based on contextually
defined factors (Biedenweg et al. 2014; Ostrom 2007;
Leslie et al. 2015). Following this framework, we
conceptualize human well-being as a set of constitu-
ents, domains, and attributes that can be tailored to
specific contexts and assessed via indicators
(Figure 1) (Breslow et al. 2016).
Defining focal attributes
In this paper, we illustrate the indicator selection
process with two focal attributes of human well-
being: resource access and self-determination. These
attributes are widely recognized in the social science
literature as important areas of human well-being
2S. J. BRESLOW ET AL.

Figure 1. Steps, and definitions of terms, used in identifying indicators of human well-being, illustrated (in light grey columns) for two focal attributes, resource access and self-determination. This is
a procedural view of our conceptual framework of human well-being that illustrates how all elements are linked. Starting with a conceptual objective, human well-being is broken down into
recognizable categories (constituents, domains); focal areas are identified (attributes) and conceptualized (dimensions and related attributes); indicators are selected (indicators); and the cross-cutting
domains of well-being are assessed by analyzing all final indicators across demographic variables and time.
ECOSYSTEM HEALTH AND SUSTAINABILITY 3

related to environmental management. Both are
foundational for achieving multiple dimensions of
well-being identified in our conceptual framework,
and both can also account for idiosyncratic and unar-
ticulated areas of well-being. Access to resources and
nature makes it possible for people to enjoy attributes
of well-being they personally associate with the ocean
and coast, such as economic, social, and spiritual
qualities, in addition to unstated or ineffable qualities.
Similarly, the capacity to determine one’s own
choices and future means people are able to actively
participate in managing, using, and making decisions
about natural resources and natural places in ways
they find personally meaningful and beneficial. In
addition, self-determination has a known link to psy-
chological health (Ryan 2009) and facilitates indivi-
dual and collective resilience (Brown and Westaway
2011).
Drawing from the social science literature, we
developed definitions for each of these focal attributes
(Box 1 and Box 2) and identified their major dimen-
sions (Table 1). We then further conceptualized these
dimensions according to their most closely related
attributes, drawn from our conceptual framework
(see Breslow et al. 2016 for definitions of each attri-
bute). For example, resource access is composed of 8
dimensions, which can be collectively associated with
21 related attributes (see Table 1). We found that this
step effectively filters a large number of indicators
reflecting multiple attributes of well-being through
the lens of one focal attribute. It captures the way in
which many attributes of well-being are mutually
constituted and interdependent and illustrates how
it is possible to select indicators for only a handful
of focal attributes while still reflecting the multidi-
mensionality of human well-being.
Methods: a generalizable approach to
indicator selection
Collecting and developing candidate indicators
To develop a generalizable approach to indicator
selection, we conducted a global search for indicators
of human well-being already used or proposed in
existing social–ecological indicator projects. Projects
were selected according to five predefined criteria:
systematic assessment of social conditions; attention
to environmental conditions or natural resource
management; focus on real-world application; docu-
mentation of process and results; and potential to
influence other projects, whether due to geographic
scope, presence in the literature or media, or level of
funding (Sojka 2014). A total of 2310 indicators were
ultimately drawn from 34 projects focusing on envir-
onmental management, sustainability, indigenous
communities, or general well-being at national to
global scales. The indicators were then categorized
according to one or more of the attributes defined
in our conceptual framework of human well-being.
(Selected projects are listed in Appendices 2 and 3
under “Existing Projects,”and the resulting list of
indicators is published in Breslow et al. 2016,
Appendix B.)
Defining screening criteria
Following advice in the literature for achieving sys-
tematic analysis, consistency, and transparency, we
established screening criteria for evaluating and
selecting indicators (Keeney and Gregory 2005; Rice
and Rochet 2005; Boyd and Charles 2006). We began
with criteria established for biophysical indicators
(Kershner et al. 2011; James et al. 2012) and modified
these according to social science considerations for
social indicators. We organized the resulting criteria
into five sections (Table 2). General criteria (A) per-
tain to any indicators, regardless of context or data
availability. Context-specific criteria (B) relate to the
Box 1. Resource access.
Resource access is defined as “the ability to benefit”from nature
and natural resources (Ribot and Peluso 2003). Multiple factors
influence resource access. Departing slightly from Ribot and
Peluso, we distinguish dimensions of access from mechanisms of
access (Charnley, McLain, and Poe in press). “Dimensions”are
the structural conditions that influence one’s ability to benefit
from natural resources, such as physical barriers, economic
capacity, legal permission, the ecological condition of resources,
and ecological knowledge. “Mechanisms”are the processes and
strategies through which people gain, maintain, and control
access to resources (Ribot and Peluso 2003). Here we focus on
the dimensions of access.
Box 2. Self-determination.
Self-determination refers to the willingness, ability, and actions of
individuals or groups to actively shape their own lives and adapt
to circumstances and is considered a primary constituent of
human well-being (Ryan 2009; Durie 1998). Here we use self-
determination in a general sense to include the concepts of
agency, free will, and autonomy. These are enabled through
social conditions that promote freedom, availability of
appropriate choices, and the motivation as well as capability to
thrive (Sen 2000; Ryan 2009). Various conditions can hinder self-
determination, including: physical, monetary or material
constraints; lack of education or information; governmental,
social, or cultural restrictions; lack of culturally appropriate
opportunities; poor mental health; and lack of positive social
relationships. In the context of EBM, self-determination depends
on (1) social conditions enabling individuals and groups to
exercise free will as it relates to environmental management; (2)
individuals’perceptions of relatedness; and (3) stakeholders’
willingness and ability to fully participate in environmental
decision-making (Beierle 2002; Ryfe 2002; Ryfe 2005; Dietz 2013).
Here “stakeholders”can refer to individuals, interest groups,
government agencies, or sovereign entities such as indigenous
nations. For place-based and indigenous communities, the
exercise of rights to land and resources is especially central to
self-determination. This includes the ability to use resources for
livelihoods, as well as the ability to shape the regulations,
institutions, knowledge, discourse (Willow 2013), and priorities
that govern resource use, whether independently or through co-
management.
4S. J. BRESLOW ET AL.

geographic, social, and management contexts in
which the indicators will be used. Data considerations
(C) are important for prioritizing and selecting indi-
cators with available data. Suite considerations (D) are
used to select a well-rounded set of indicators.
Finally, project considerations (E) are important ques-
tions that need to be addressed at a project level.
Here, we used the criteria in groups A–D to test a
general method for evaluating indicators, since pro-
ject considerations (E) are more specific and project
dependent.
Evaluating indicators using the screening criteria
From the master list of compiled human well-being
indicators (Breslow et al. 2016), we selected all indi-
cators associated with each focal attribute (resource
access and self-determination) and their related attri-
butes (Appendices 2 and 3). Since many indicators
are associated with multiple attributes of human well-
being, resulting lists consisted of more than 2000
candidate indicator-attribute pairs for each focal
attribute. To narrow these long lists to a useable
number, we used a stepwise process, detailed below
and illustrated in Figure 2.
1. First cut
Indicators were first evaluated by one working group
member, based on expert opinion, with respect to
how well they conceptually reflected the focal attri-
bute and its dimensions within a marine/coastal
environment and management context (a combina-
tion of criteria A1 and A2; see Table 2), with a score
of 2 = potential direct relevance; 1 = likely indirect
relevance; 0 = very general, very indirect, or no rele-
vance. If not stated, a marine or coastal linkage was
assumed. Those indicators scoring an average of 1.5
or above were selected for the next round. This
resulted in intermediate lists of approximately 650
indicator-attribute pairs for each focal attribute.
2. Quick screen
The next round of indicators were evaluated by two
working group members, using a similar 0–2 ranking,
Table 1. Typologies of resource access and self-determination.
Focal attribute
Dimensions of
focal attribute Brief explanation Most closely related attributes
Resource access Cognitive and
cultural
Knowledge required to identify, locate, harvest and process
resource; values and ethics about which resources to
harvest and quantities to harvest
Cultural values, education and information
Ecological Attributes of a resource that make it available and desirable
to potential users, such as resource characteristics (size,
sex, maturity, abundance, condition), and geographic
distribution; environmental conditions that foster
resource availability (e.g., water quality)
Environmental quality, pollution and
waste, resource abundance and
distribution
Economic Capital needed to invest in gear, permits, etc. required for
obtaining resource; labor and time needed to harvest
resource; market value of resource
Activities and time allocation, employment
and income, industry and commerce,
material wealth, subsistence
Legal/political Laws, policies, rules (customary or de jure), permits, quotas,
etc. that govern access to resources
Resource management
Physical The physical infrastructure that affects resource access (e.g.,
roads, barriers, dams); physical condition of resource user
Infrastructure, physical health
Resource access
(overall)
Access to resource harvests, access to open space for
recreation, etc.
Access to nature, recreation and tourism,
resource access and tenure, subsistence
Social The social context, identity, and networks of the resource
user that confer or deny rights of access, e.g., ethnicity,
kinship, group membership
Civil society, family and community
Technical The technical skills, equipment, etc. required to harvest
resources, such as fishing gear, locational devices, boats
Research and technology
Self-determination Economic capacity Material, financial, and time constraints and capacity Available time for fulfilling activities,
employment and income, industry and
commerce, material wealth
Freedom Social and/or governmental freedoms and restrictions Civil society, governance, independence,
public services, resource management,
sovereignty
Knowledge Understanding of current and future opportunities, the
consequences of current and future actions, and
alternatives.
Education and information, research and
technology
Motivation Motivation to do well, to improve, and to thrive Cultural values and practices, emotional
and mental health, senses of place
Physical capacity Physical constraints and capacity (e.g., security, safety and
health) to achieve self-determination
Disaster preparedness, peace and security,
physical health, physical safety, resource
access and tenure
Social capacity Social relationships and social capital needed for self-
determination; capacity for collective action
Equity and justice, family and community,
social diversity and integrity
Stability and
adaptability
Conditions necessary for long-term decision-making;
resilience; flexibility
Security and resilience
Voice Conceptual and practical possibilities for participation in
decision-making; having meaningful input in decision-
making; representation in government
Political participation
ECOSYSTEM HEALTH AND SUSTAINABILITY 5

Table 2. Screening criteria used to evaluate indicators.
A. GENERAL CRITERIA
A1. Conceptually valid
Is this indicator unambiguously related to the attribute it is intended to measure? Is there peer-reviewed evidence for its theoretical validity?
A2. Environmental linkage
Is this indicator linkable theoretically and/or via empirical evidence to environmental conditions, the human-environment connection, and/or
environmental management? This linkage can be direct and material, and/or intangible. The type of ecosystem can be specified if desired (e.g.,
marine/coastal).
A3. Social indicator
Is this indicator clearly related to social phenomena, and not strictly a measurement of the biophysical environment? (Note that biophysical
conditions may be used as proxies for human wellbeing when no suitable social indicators are available.)
A4. Understandable
Is this indicator understandable or identifiable by decision-makers and by the people being measured? Can it be explained in one paragraph or
less? Is it easy to understand the consequences and trade-offs revealed by this indicator?
A5. Concrete and measurable
Assuming scope is specified, does this indicator represent a specific aspect of the world that can be measured directly? (Note that many subjective
and seemingly qualitative indicators, such as “% of residents who are satisfied with their access to public shorelines,”are measurable via a Likert
scale using a survey.)
A6. Conforms to rules for good scales (Keeney and Gregory 2005)
Type of scale: Is this indicator natural, constructed or proxy? Range: Does this indicator capture a reasonably full range of possibilities?
Directionality/reference points: Is it possible to specify which direction in trends is positive or negative, and to identify reference points? Unit ratios:
Do points on the scale have a clear ratio of differentiation? Sensitivity to change: See B4 and B5. (Scored 0 if meeting 0–1 rules; 1 if meeting 2–3
rules; and 2 if meeting all 4 rules).
B. CONTEXT-SPECIFIC CRITERIA
B1. Geographically relevant and comprehensive
Is this indicator relevant to the geographic context and scale of interest? Does it reflect the diversity of ecosystem types of interest? Does the
indicator apply widely to a diversity of resource types?
B2. Socially relevant and comprehensive
Is this indicator relevant to the social and cultural context and scale of interest? Does it refer to the social diversity of interest? Does the indicator
apply widely to a diversity of people? Does this indicator reflect the social goals, priorities, and/or thresholds of wellbeing as defined by the people
whose wellbeing will be measured?
B3. Relevant for decision-making context
Is this indicator relevant to the local decision-making context(s) and scale of interest (e.g., federal, state, municipal, tribal, etc.)?
B4. Sensitive and responsive to specific, context-relevant environmental changes
Is this indicator something environmental conditions in the geographic area of interest can affect? Does the indicator respond quickly and
noticeably to real changes? Is it possible to distinguish how other factors influence the response?
B5. Sensitive and responsive to specific, context-relevant management changes
Does this indicator reflect something managers can influence? Does the indicator respond quickly and noticeably to real changes? Is it possible to
distinguish how other factors influence the response?
C. DATA CONSIDERATIONS
C1. Data availability
Are there data available appropriate to the target region, social groups, and/or questions?
C2. Variables measured
Which variables are measured in the available data set? Are these relevant to the overall assessment?
C3. Spatial scope & resolution
At what geographic scope and resolution is data available? Is this scope and resolution useful to the overall assessment?
C4. Temporal scope & resolution
How far back is data available, and at what frequency? Is this scope and resolution useful to the overall assessment?
C5. Level of data disaggregation
Are data broken down by different social characteristics of interest? If so, which ones? Are these adequate for assessing cross-cutting domains?
D. SUITE CONSIDERATIONS
D1. Objective or subjective
Is this an indicator of objective or subjective wellbeing? Does the indicator reflect a measureable state of things outside people’s thinking
(objective)? Or does the indicator reflect people’s intuitive assessment or perception of something, such as their own happiness; or the belief that
water is safe to drink, independent of water quality measures (subjective)?
D2. Units of social organization
What scale of social organization does the indicator reflect (e.g., individual, household, community, society)?
D3. Leading or Lagging
Does this indicator anticipate change (leading) or report on change that has already happened (lagging)?
D4. Broad or specific reflection of human wellbeing
Does this indicator reflect multiple domains of wellbeing (holding “big picture”value) or is it specific to one domain or attribute?
E. PROJECT CONSIDERATIONS
E1. Can this indicator be measured, reported, and integrated into an IEA?
What methods are best used to measure this indicator, and how are results best communicated? E.g., existing data, interviews, surveys; charts,
images, narratives, maps, etc.
E2. Estimated cost
What is the estimated cost to measure this indicator? Is it affordable?
E3. Potential harm
Are there any potential concerns about how this indicator may harm the people it measures –e.g., by revealing private information; specifying too
concretely what counts as wellbeing to the neglect of other hidden or poorly-understood dimensions; putting a limit on when wellbeing is
reached; etc.? Note if and how harm may vary with measurement method, level of detail, and how results are presented. Provide guidance on
whether and how the indicator should be used.
E4. Collaboration with populations whose wellbeing is being measured
Was this suite of indicators developed in collaboration with the people it measures? Were the indicators proposed and/or vetted through
interviews, focus groups, workshops, or other direct dialogue with the people they measure?
Criteria were developed by comparing, modifying and adding to criteria used in related studies (Keeney and Gregory 2005; Rice and Rochet 2005; Boyd
and Charles 2006; Kershner et al. 2011). This table has been color-coded for easy reference. If printing in grayscale, please refer to the main text for full
interpretation.
6S. J. BRESLOW ET AL.

according to seven criteria: marine/coastal linkage,
social or biophysical indicator, conceptual validity,
understandability, geographic relevance, social rele-
vance, and concreteness and measurability. For each
related attribute, all indicators scoring an average
score of 1.9 or above were selected for the next
round. If none scored this highly, then the two most
top-scoring indicators for each related attribute were
selected so that each had at least two candidate indi-
cators. Recurring indicators that had been coded with
more than one attribute were assigned to their most
relevant attribute, with other related attributes noted.
During this step, a number of indicators were re-
categorized according to expert opinion. This step
resulted in a list of approximately 200 distinct candi-
date indicators for each focal attribute.
3. Expert opinion screen
Multiple working group members then screened each
of these indicators based on their opinion of how well
it reflected its respective dimension of the focal attri-
bute within a US West Coast context, with 0 = poor;
1 = mediocre; 2 = best. Twelve group members eval-
uated the resource access indicators, and 10 evaluated
the self-determination indicators. All indicators scor-
ing an average of 1.33 (for resource access) or 1.5 (for
self-determination) or above, plus all those with at
least 6 (resource access) or 5 (self-determination)
scores of 2 were selected for the final round. If there
were no top-scoring indicators for a dimension, then
the top two highest-scoring indicators in that dimen-
sions were selected. As a final step, indicators with
similar meanings were merged.
We chose our cut-off points to achieve a manage-
able and roughly similar number of candidate indi-
cators for each focal attribute for further evaluation
via a literature review. Note that one could introduce
sensitivity analyses to investigate the robustness of
scores at this and other stages of evaluation: using
robustness as a decision cut-off may result in widely
varying numbers of candidate indicators for different
focal attributes and leave some dimensions without
candidate indicators. We chose to prioritize content
and complementarity over strictly robustness since a
degree of subjectivity in the evaluation process is
unavoidable anyway.
4. Literature review
Research assistants then evaluated the resulting lists
of candidate indicators according to all criteria and
considerations in sections A–DofTable 2.
Evaluations of conceptual validity (A1) and
Conceptual validity
Environmental linkage
Conceptual validity
Geographic relevance
Social relevance
A. General Criteria
B. Context-Specific Criteria
C. Data Considerations
D. Suite Considerations
Expert opinion score
Literature review score
Suite considerations
Additional considerations
1. First cut
2. Quick screen
3. Expert opinion screen
4. Literature review
5. Suite selection
Conceptual validity
Marine or coastal linkage
Social indicator
Understandability
Concreteness and measurability
Geographic relevance
Social relevance
Started with ~ 2,000
indicator-attribute pairs
~ 650 indicator-
attribute pairs
~ 200 indicators
~ 60 indicators
~ 15 indicators
Steps Screening criteria applied
Results per focal
attribute
~ 60 indicators,
fully evaluated
Figure 2. Steps in the indicator evaluation process. Starting with more than 2000 indicator-attribute pairs for each focal
attribute, we used a series of steps to filter and narrow these to a manageable number for a literature review and selection of a
suite. Colors match those used in Table 2. Each step of the evaluation was conducted by up to three experts from our team of
environmental social scientists, except for Step 3, which was conducted by groups of 10–12 experts. (Note: This figure has been
color-coded for easy reference. If printing in grayscale, please refer to the main text for full interpretation.)
ECOSYSTEM HEALTH AND SUSTAINABILITY 7

sensitivity and responsiveness to environmental and
management changes (B4, B5) were based on peer-
reviewed literature and expert opinion. Evaluations
of understandability (A4) and social and geographic
relevance (B1, B2) relied additionally on popular
media sources relating to the California Current
region. Conformity to rules for good scales (A6)
(Keeney and Gregory 2005) was evaluated using
logical deduction. Relevance to decision-making
context (B3) was evaluated through an analysis of
human well-being responsibilities and priorities
articulated in the major US federal and state envir-
onmental laws, policies, and management guidelines
pertaining to marine and coastal management of
the US West coast (for methods and results, see
Appendix 1).
Literature review results for criteria A1-C1 were
quantified such that indicators with evidence suggest-
ing they fully met a given criteria were scored 2,
indicators with evidence suggesting they met criteria
only partially or in selective circumstances were
scored 1, and indicators with negative evidence or
no discovered literature were scored 0. Scores,
weighted equally, were averaged to arrive at a “litera-
ture review”score for each indicator. Note that cri-
teria can be weighted according to project priorities
(Kershner et al. 2011; James et al. 2012). Note also
that a literature review of this sort involves consider-
able interpretation: reliance on different literature
sources or avenues of logic could result in substan-
tially different results.
5. Evaluation of top-scoring indicators
Our final step was to select the top-scoring indicators
of each related attribute within each dimension of our
focal attributes. We opted to select indicators that
scored 1.5 or above according to the literature review
and expert opinion screening steps toward ensuring
consistency of quality in the final suite. Using both
the literature review and expert opinion scores repre-
sents a form of triangulation, since each resulted from
a different set of reviewers. This approach effectively
weighted conceptual validity, geographic relevance,
and social relevance, since these criteria were used
in both evaluations. Once the top-scoring indicators
were identified, we evaluated them according to their
data availability, suite-level considerations, and addi-
tional considerations.
Suite considerations (Table 2,sectionD)areuse-
ful for selecting a final set of indicators with a mix of
complementary qualities (Levin et al. 2009;Kershner
et al. 2011). In crafting suite considerations for
socialindicators,westroveforanumberofqualities:
a combination of objective measures, which reflect
conditions observable regardless of an individual’s
personal experience, and subjective measures, which
reflect an individual’s perceptions or feelings about a
matter (D1); indicators that collectively represent
well-being at different levels of social organization,
from individual well-being to community and soci-
etal well-being (D2); both “leading”indicators that
anticipate changes in well-being, and “lagging”indi-
cators that report on changes that have already hap-
pened (D3); and indicators that are both “broad,”
reflecting multiple attributes or domains of well-
being, and “specific,”primarily reflecting one attri-
bute (D4).
Results
Candidate indicators
From the 2000 indicator-attribute pairs initially iden-
tified, we used steps 1–3 outlined above to select 53
candidate indicators of resource access and 67 candi-
date indicators of self-determination for detailed eva-
luation via literature review (Step 4; full results in
Appendices 2 and 3). Through this structured process
we identified several high-scoring, currently measur-
able indicators of each focal attribute. We also iden-
tified gaps where further indicator development and
data collection are needed.
Results (Appendices 2 and 3) reveal that the
number of candidate indicators and data availabil-
ity varied widely among the dimensions and related
attributes of the focal attributes. This variability is
summarized in Figures 3 and 4.Ingeneral,more
candidate indicators and data were available for the
ecological, economic, and resource access dimen-
sions of resource access, while fewer were available
for the cognitive, legal/political, social, and techni-
cal dimensions. More candidate indicators and data
were available for the economic capacity, physical
capacity, and social capacity dimensions of self-
determination, and fewer for its knowledge, stabi-
lity and adaptability, and voice dimensions. A high
number of subjective indicators in the freedom and
motivation dimensions explains the low data avail-
ability for these dimensions, since subjective indi-
cators can only be measured directly via surveys or
interviews, while objective indicators are often
measured indirectly via available data, such as eco-
nomic, spatial, and legal data that has been col-
lected for other purposes (e.g., property values,
length of trails, number of permits). The patterns
we observed in indicators and data availability cor-
roborate the growing acknowledgement that tangi-
ble dimensions of human well-being are frequently
assessed, using readily available economic and
demographic data, while intangible, cultural, and
largely subjective dimensions remain understudied
(Turner et al. 2008;Chanetal.2012; Satterfield
et al. 2013).
8S. J. BRESLOW ET AL.

Top-scoring indicators
Resource access indicators
A total of 19 candidate indicators of resource access
scored 1.50 or above out of 2.00 in both the expert
opinion screen and literature review evaluation
(Appendix 2, “Candidate Indicators”). These were
distributed among 6 of the 8 dimensions, and 12 of
the 20 related attributes, leaving 2 dimensions and 8
related attributes without high-scoring indicators.
Of the 13 top-most scoring indicators for each
related attribute (2 tied as top scorers in the resource
abundance and distribution attribute), 6 had data
available for the topic and region of interest; 3 had
partial data available for the topic or region; and 4
had no data available, or the indicator was too vague
to determine if data were available (Table 3). One
wasasubjectivemeasureofwell-being(%ofresi-
dents who are satisfied with their access to public
shorelines), and all others were objective measures.
In other ways, they represented a mix of suite-level
qualities.
Self-determination indicators
A total of 36 candidate indicators of self-determina-
tion scored 1.50 or above out of 2.00 in both the
expert opinion screen and literature review evaluation
(Appendix 3, “Candidate Indicators”). These were
distributed among 7 of the 8 dimensions, and 18 of
the 25 related attributes, leaving 1 dimension and 7
related attributes without high-scoring indicators. Of
the 18 top-most scoring indicators for each related
attribute (Table 4), 6 had data available for the topic
and region of interest; one had partial data available
for the topic or region; and 11 had no data available.
These top-scoring indicators represented a mix of
suite-level qualities.
Indicator suite selection
Selecting a final suite of indicators to include in an
integrated assessment is an art as much as a science,
ideally involving deliberation by managers and stake-
holders (Levin, Damon, and Samhouri 2010). We
Figure 3. Resource access candidate indicators: summary of evaluation results.
Figure 4. Self-determination candidate indicators: summary of evaluation results.
ECOSYSTEM HEALTH AND SUSTAINABILITY 9

Table 3. Top-scoring resource access indicators, with suite characteristics, recommended data collection method, and data availability for each.
Dimension Indicator O S Social scale →←B s Method Data available Variables measured
Spatial scope and
resolution
Temporal scope and
resolution
Disagg. by social
variables
Cognitive No top-scoring indicator
available
−− − − − −− − − − − − −
Ecological Access to clean water x Individual x x Multiple No: Too vague −−−−
Days x miles of shoreline
closed due to sewage,
biotoxins or pollution
x NA x x Existing
data
Yes: WA Department of
Health, OR Health Authority,
CA State Water Resources
Control Board
Days and miles of shorelines
closed due to sewage and
pollution.
By state (OR, WA); by
county (CA)
Weekly (during
summer only in OR
& WA)
None
Abundance of selected key
species
x Society x x Existing
data
Some: Some data is available
for certain species
−−−−
Marine habitat health (%
cover key ecosystems/
species)
x Society x x Existing
data
Yes: Ocean Health Index Index score calculated via
Ocean Health Index
US West Coast Annually
Economic Coastal Livelihoods and
Economies: current
adjusted values by sector
for jobs, wages, and
revenue (value)
x Society x x Existing
data
Yes: Ocean Health Index Job & wage data for 20
marine-related sectors
By state Differs for each
variable
By job sector and
livelihood
No. [of type] of vendors of
locally caught and raised
seafood
x Community x x x Survey No: may be available for
specific location
−−−−
Legal and
political
No. of fish permits/licenses (by
community and fishery;
total per capita; held locally
and non-locally, indigenous,
% of productive activity by
plan area companies and
indigenous)
x Community-
Society
x x Survey Yes: PacFIN, Karma Norman at
NWFSC (not all variables)
# of permits/licenses WA, OR, CA, by
community/port
group
Weekly and annually
since 1981 (varies)
By fishery and
community
Physical Boat ramps (No.; per capita;
per 1000 people; use)
x NA x x Existing
data
Yes: OR State Marine Board
(data.gov), WA Recreation
and Conservation office, CA
State Parks, Division of
Boating and Waterways
Y: No. of boat ramps By state (WA only) Once in 1997 (WA
only)
None
Resource access % of residents who are
satisfied with their access to
public shorelines
x Individual x x Survey No: can be collected via survey −−−−
% of shoreline that is publicly
accessible or owned
x Society x x Existing
data
Yes: CA Coastal Access Guide,
OR: All shoreline is public,
WA Department of Ecology
Marine Shoreline Access
Project
Miles of accessible shoreline By local jurisdiction
(CA); by county
(WA); all public
(OR)
2008–2010 (WA),
1999–2010 (CA);
updated irregularly
None
Recreational fishing licenses/
permits (sold annually/used
on recreational lands)
x Individual x Some: WA Dept of Fish and
Wildlife, OR Dept of
Agriculture; Recfin; Karma
Norman at NWFSC
Number of recreational fishing
licenses/permits (no fresh/
saltwater distinction)
WA, OR by
community, CA by
marine area
Annually since 1980
(dependent on state
and permit type)
Broken down by
target species
and
community
Subsistence harvest (No. and
type of species consumed)
x Individual x Some: Listed in Puget Sound,
WA-Human Wellbeing
Indicators in Hood Canal
Per regulatory area Annual catch data,
survey data
Puget Sound: by
gender, age,
and sub-region
(Continued )
10 S. J. BRESLOW ET AL.

recommend an approach that provides transparency
and flexibility in selecting indicators that best meet
the situation at hand.
A list of candidate indicators evaluated according
to desirable qualities, as illustrated in Tables 3 and 4,
can help structure decisions. There are multiple
potential pathways to a final suite. Initial lists of
indicators and screening criteria may vary; evaluation
results may differ; criteria may be weighted according
to unique priorities and circumstances; and evalua-
tors as well as decision-makers may use different lines
of reasoning. Under each of these scenarios, top-
scoring indicators will differ. For example, under
the current evaluation, the top-most scoring indicator
for resource access is “% of shoreline that is publicly
accessible or owned”and for self-determination it is
“% of (rural) residents who agree that they have input
into decision services in area.”If data availability is
imposed as a requirement, the top-most scoring indi-
cator for resource access does not change, but for
self-determination it becomes “% of jobs paying a
living wage, by household type,”tied with “%
employed people living in poverty.”
Suite-level considerations
Once a list of high-scoring indicators has been iden-
tified, one can review dimensions and related attri-
butes with multiple high-scoring indicators and select
among them to achieve a balanced mix of suite-level
qualities. For example, to help balance subjective and
objective indicators in the resource access suite, one
could substitute “% of (rural) residents who agree
that they have input into decisions (services) in
area”as a possible high-scoring subjective indicator
of the “legal and political”dimension.
Additional considerations
A number of additional considerations are useful in
selecting a final suite. First, one can review the
interim list for internal redundancies. For example,
“% of jobs paying a living wage, by household type”
and “% employed people living in poverty”suggest
very similar aspects of well-being, so only one of
them needs to be included in a parsimonious assess-
ment of self-determination. Furthermore, “% of resi-
dents who are satisfied with their access to public
shorelines”ranked among the top-most indicators
for both focal attributes, so should be assigned to
only one. One can also review the list for redundan-
cies within the IEA as a whole. For example, “abun-
dance of selected key species”and “marine habitat
health (% cover key ecosystems/species)”will likely
be included in a suite of ecological indicators so need
not be selected here.
Second, one could modify or clarify promising
indicators to improve their quality and usability. For
example, “access to clean water”scored highly for
Table 3. (Continued).
Dimension Indicator O S Social scale →←B s Method Data available Variables measured
Spatial scope and
resolution
Temporal scope and
resolution
Disagg. by social
variables
Social % of residents who have
worked with other residents
to share harvested goods in
the past year
x Community x x Survey No: Would likely have to be
obtained via a survey.
−−−−
Technology No top-scoring indicator
available
−− − − − −− − − − − − −
O = objective; S = subjective; →=leading; ←=lagging; B = broad; s = specific.
ECOSYSTEM HEALTH AND SUSTAINABILITY 11

Table 4. Top-scoring “self-determination”indicators, with suite characteristics, recommended data collection method, and data availability for each.
Dimension Indicator O S Social scale →← B s Method Data available Variables measured
Spatial scope
and resolution
Temporal scope
and resolution Disagg. by social variables
Economic
capacity
% of jobs paying a living
wage, by household type
x Household x x Existing
data
Yes: Living wage is defined by
$15/hour (The Job Gap
2015).
% job openings
paying <$15/hr
By state Once in 2013 By single adult and single
adult w/2 children
% employed people living in
poverty
x Individual x x Existing
Data
Yes: WPFP (2014) Low Income Working
Families
By state Annually Minority working families,
with no HS Degree/GED,
with no postsecondary
experience, paying 1/3 or
more for housing, parent
without health insurance,
children, adults 18–64
with no HS Degree/GED,
occupations paying below
poverty
Somewhat, mostly or
completely satisfied with
their amount of leisure time
x Individual x x Existing
Data
Yes: By state (GFK 2015). Satisfaction w/ amt of
leisure time
US, by state Once in 2014;
research
ongoing
By gender
Freedom Proportion of persons active in
civic or political groups
x Society x x Survey No −−− −
No. of residents who report
trust in experts and local
and state government and
collaborative government
efforts
x Society x x Survey No −−− −
Public satisfaction with social
services/Satisfaction with
access to services
x Society x x Survey No −−− −
Lands and waters co-
management by indigenous
and local communities
x Community x x All Some: NOAA Fisheries 2015 Descriptive: guidance,
members
WA, OR, CA NA NA
Knowledge No. persons participating in
natural resource education
activities
x Individual x x Survey No −−− −
Motivation Proportion of adults
encountering barriers which
prevent them from
experiencing particular
cultural activities
x x Community x x Interview No −−− −
% reporting very or somewhat
strong sense of belonging
to community
x Community x x Survey No −−− −
% of residents who express
high life satisfaction or
happiness and % who
express living in the region
as a contributor to this
x Individual x x Survey No −−− −
(Continued )
12 S. J. BRESLOW ET AL.

Table 4. (Continued).
Dimension Indicator O S Social scale →← B s Method Data available Variables measured
Spatial scope
and resolution
Temporal scope
and resolution Disagg. by social variables
Physical Capacity Capacity to anticipate change
and to develop strategies to
respond (measured by
content organizing
responses to open ended
questions relating to a
hypothetical 50% decline in
fish catch)
x x Individual-Society x x Interview No −−− −
% of people who feel safe in
their communities
x Community x x Existing
Data
Yes: Only per state and the
cities with the highest
populations along the coast
(San Jose, San Francisco,
San Diego, and LA) (Gallup
2015).
Communities where
people feel unsafe
CA cities Annually,
2013–2014
None
% of Adults ages 18+ with
limited activity due to poor
physical or mental health
x x Individual x x x Existing
Data
Yes: WA Department of
Health, OR Health Authority,
CA Department of Health
Same as indicator By state Annually By age and risk factor (WA)
and gender (OR);
prevalence and disease
(CA)
% of residents who are
satisfied with their access to
public shorelines
x Individual x x Survey No
Social Capacity Reports of recent treatment
that is perceived as unfair
based on gender, age, race
or color, ethnic background,
language, socioeconomic
position, social class, sexual
orientation, religion or
disability
x Society x x Existing
Data
Yes: By state, not broken
down to coastal areas
(EEOC 2015).
No. of filings (EEOC
Charge Receipts)
By state Annually,
2009–2014
By race, sex, national origin,
religion, gender, age,
disability, pay, etc.
% of residents who have
worked with other residents
to manage resources
x Individual–
Community
x x Survey No −−− −
Stability &
Resilience
No top-scoring indicator
available
−− − − − −− − − − − − −
Voice % of (rural) residents who
agree that they have input
into decision services in
area
x Individual x x Survey No −−− −
O = objective; S = subjective; →=leading; ←=lagging; B = broad; s = specific.
ECOSYSTEM HEALTH AND SUSTAINABILITY 13

resource access, but is too vague to measure: does it
mean access to clean drinking water, access to clean
bodies of water, or something else? More specific
language would improve its eligibility for the final
suite. Improving candidate indicators could further-
more help fill gaps in dimensions and related attri-
butes lacking top-scoring indicators. For example, the
related attribute of self-determination, “indepen-
dence,”currently lacks a high-scoring indicator. The
candidate indicator “decision latitude at work”scored
1.50 in expert opinion and 1.36 in the literature
review, putting it just below our selection threshold.
The literature review (Appendix 3) reveals its low
score is due to it being marked “unclear”for under-
standability, and in need of a measurable scale. Using
more common language and developing a consistent
scale could improve this indicator sufficiently to serve
as an indicator of “independence.”
Third, and finally, it is important to identify gaps
where additional indicators and primary data collec-
tion are needed to achieve a robust assessment of
focal attributes. Gaps may be filled by clarifying or
modifying existing indicators, or by developing new
indicators. Or, gaps may suggest a dimension of well-
being that is difficult to assess using a quantitative
measure. For example, cultural values related to
resource access are likely best understood through
qualitative research presented as narrative explana-
tion alongside the quantitative results of the IEA.
Filling gaps inevitably entails the costs of developing
new indicators and collecting new data.
Discussion: cautions and recommendations
The limitations of existing indicators and data
From a starting list of more than 2000 globally
sourced indicators, our screening process identified
short lists of potential indicators of resource access
and self-determination for the California Current IEA
(Tables 3 and 4). What these indicators can actually
tell us about human well-being related to specific
environmental conditions and management strategies
requires a closer look at the resolution and disaggre-
gation of available data. While the indicators are able
to offer general insight into our focal attributes, they
are limited in their ability to answer specific manage-
ment questions.
Currently measurable indicators could broadly
assess several ecological, economic, physical, and
legal dimensions of resource access as an attribute
of well-being: namely, how pollution and waste result
in shoreline closures; general marine ecosystem
health; the economic conditions of ocean-dependent
livelihoods; boat ramps per capita; number of
acquired fishing permits; and the ownership patterns
of shorelines. Similarly, currently measurable
indicators of self-determination could broadly assess
its economic and physical dimensions by tracking
wages, poverty levels, and satisfaction with leisure
time, perceptions of safety, and physical and mental
health. In addition, equity and justice as an attribute
of social capacity can be assessed through measuring
reports of discrimination.
However, of the resource access indicators, only
three currently have data available for the whole
California Current region that are collected at spatial
and temporal resolutions relevant to environmental
or management changes: days x miles of shoreline
closed due to sewage, biotoxins or pollution; general
marine ecosystem health; and certain sectors mea-
sured in the coastal livelihoods and economies index
(i.e., mariculture, whale-watching, ports and harbors,
and shipping and boat-building). None of the top-
scoring self-determination indicators have data avail-
able at a resolution that can capture responses to
specific environmental or management changes.
The only indicator sufficiently disaggregated by
social variables to assess the cross-cutting domain of
equity and justice is the one self-determination indi-
cator of equity and justice: “reports of recent treat-
ment that is perceived as unfair based on gender, age,
race or color, ethnic background, language, socioeco-
nomic position, social class, sexual orientation, reli-
gion or disability.”In addition, several of the listed
datasets could be potentially paired with other exist-
ing data, such as census data, to gain insight into
social variability. For example, one could overlay the
location of shoreline closures with spatialized demo-
graphic data of coastal residents to understand how
closures affect them differently. Note that this would
not account for differential effects on long-distance
visitors.
Gaps, and the need for new social indicators and
original research
For resource access, no top-scoring indicators with
adequate existing data were found for its cognitive
and cultural, social, and technological dimensions.
For self-determination, no top-scoring indicators
with adequate existing data were found for the
dimensions of freedom, knowledge, motivation, sta-
bility and resilience, and voice.
In addition, 12 of the 16 top-scoring indicators
with any measurable data lacked data with the spatial
and temporal resolution necessary to assess how
human well-being is affected by specific environmen-
tal changes or management strategies: that is, they are
collected for only part of the region, at a spatial
resolution that is too large (i.e., by county or state),
and/or too irregularly in time. In addition, all but one
of the currently measurable indicators lacked the
disaggregation by social variables, such as race,
14 S. J. BRESLOW ET AL.

class, and gender that is necessary to assess equity, a
major cross-cutting constituent of well-being.
Many of the indicators for which data were una-
vailable measure the subjective perceptions or experi-
ences of resource users and area residents. Obtaining
data for these indicators would require conducting
surveys and interviews. These research methods
could also enhance the assessment of objective social
indicators. For example, a survey question regarding
how health conditions facilitate or limit resource
access would increase the resolution of the physical
health indicator and its sensitivity to environmental
and management changes. Likewise, additional sub-
jective social indicators can helpfully complement
objective indicators. For example, a question about
individuals’perceptions of how economic conditions
affect resource access would greatly assist in inter-
preting the coastal livelihoods index. In general, sur-
veys and interviews can significantly increase the
amount, resolution, local validity, and explanatory
power of information collected for any social
indicator.
These results corroborate two common observa-
tions among environmental social scientists. One, the
preponderance of EBM indicators have focused on
the ecological, economic, and physical “conditions”of
human well-being, with considerably less attention
directed to those constituents of well-being we iden-
tify as “connections”and “capabilities,”and the cross-
cutting domain of “equity and justice.”This discre-
pancy is likely due to narrow conceptualizations of
human well-being and limited data availability (Satz
et al. 2013; Breslow et al. 2016). Two, existing social
indicators and data are typically too broad in scope
and resolution to meet the needs of an IEA and EBM.
We need new social indicators that are tailored and
measured specifically for environmental questions.
Generalizability, scalability, and the need for
tiered indicator systems
Our overall approach to selecting indicators was
designed to be generalizable, with appropriate mod-
ifications, to multiple contexts and scales. Specifically,
our conceptual framework of human well-being
(Figure 1), screening criteria (Table 2), method for
analyzing management relevance (Appendix 1), and
process for selecting indicators (Figure 2) may be
applied to IEAs and EBM, in general, if adapted for
individual circumstances. In addition, our database of
available indicators (Breslow et al. 2016) was gener-
ated from worldwide sources and may be used, and
added to, as a reference. However, our resulting ana-
lyses and indicators are specific to marine and coastal
management of the western United States (the
California Current) and should not be generalized
to other regions –with several exceptions. Our
analysis of management relevance (Appendix 1)
may be extended to other US environmental manage-
ment contexts. In addition, it may be desirable to
develop indicators that are comparable to those pre-
sented here. For example, the National Oceanic and
Atmospheric Administration (NOAA) may wish to
compare the status of the same indicators across
multiple IEAs under its jurisdiction. In this case, it
will be necessary to screen these indicators for geo-
graphic, social, and management relevance in all
areas where they will be applied.
These questions of generalizability lead to the
more complicated dilemma of scalability. In screen-
ing indicators for the California Current ecosystem, it
was difficult to find indicators reflecting its full geo-
graphic and social diversity. We were forced to
exclude a number of indicators that were crucial to
distinct places and communities within the region
(such as shellfish closures, subsistence harvesting
expenses, and outdoor recreational amenities), but
were not sufficiently applicable to the region’s popu-
lation as a whole to warrant inclusion in the final
suite. In this way, the expectation to compare gener-
alizable indicators of human well-being risks over-
looking areas of well-being that are extremely
important to certain people, and especially to margin-
alized communities, such as non-English speakers,
who are unable to advocate for their interests in a
management context. In contrast, indicators of well-
being pertaining to high-profile or economically valu-
able resources, such as commercial fisheries, will
likely be prioritized by managers. In effect, a standar-
dized set of indicators informing policy at a large
scale can undermine the well-being of sub-popula-
tions by excluding their concerns, including their
very disenfranchisement, from view.
This dilemma illustrates that not only are the suites
of indicators presented here for the California Current
not scalable; they are also not sufficient. Instead, the
implicit function of indicators of human well-being –
to be comparable, and to actively promote the well-
being of a diverse society –suggests the need for tiered
sets of indicators, that is, one set that is broadly com-
parable, and one or more sets that are tailored to
smaller scales. The broader set can consist of objective
indicators measured with available data, as well as
subjective indicators assessed through standard survey
questions. The localized sets can be developed such
that different indicators appropriate to local scales are
developed for the same attribute, which is then quali-
tatively compared across people and regions. For local
validity, as well as to promote self-determination as an
attribute of well-being, locally specific indicators
should be developed by the people whose well-being
is to be assessed (e.g., see Mascia, Claus, and Naidoo
2010; Biedenweg et al. 2014; García-Quijano 2015;
Donatuto, Campbell, and Gregory 2016).
ECOSYSTEM HEALTH AND SUSTAINABILITY 15

Addressing the social consequences of indicators
In selecting indicators of well-being, it is important to
keep in mind that indicators are themselves products
of a social system, and can have unintended social
consequences. For example, indicators can simplify
reality in ways that can undermine human well-being;
they can shift attention toward easily quantifiable
conditions, and away from other critical aspects of
well-being; they are often presented as objective mea-
sures without acknowledgment of their political ori-
gins and underlying assumptions about social change;
they can present social–ecological challenges as tech-
nical rather than moral and political problems; and
they shift resources, power and attention away from
stakeholders and democratic processes to professional
experts and indicator development and measurement
processes (Mccool and Stankey 2004; Merry 2011;
Breslow 2015; Hicks et al. 2016).
Indicators, and indicator selection and measure-
ment processes, must be deliberate in addressing
these, and other, cautions. Cobb and Rixford note
that the “symbolic value of an indicator may out-
weigh its literal value”(1998, 1, 19) in its political
utility and ultimate capacity to effect real change.
They observe that indicators will more likely lead to
meaningful change if they focus on the causes rather
than symptoms of underlying problems, and if they
are tailored to the needs of agents with the power and
authority to effect change. Furthermore, they explain
that a democratic indicators program requires more
than a good public participation process: social indi-
cators must inherently serve to enhance principles of
justice and equity in the way they are defined, ana-
lyzed, and reported.
Key takeaways for practitioners
By testing a comprehensive approach to evaluating
social indicators, we show environmental practi-
tioners that it is possible to think systematically, and
deeply, about human well-being. We illustrate why it
is important to consider a rich set of indicators that
reflects the multiple dimensions, and all four “Cs,”of
well-being (Table 1). We recommend using a fully
participatory process to ensure indicators are valid
and useful for local people. And we identify an
important need to invest in collecting social data in
more subject areas and at finer scales if human well-
being is to be taken seriously as part of IEAs.
Practitioners need not repeat all of our steps. We
designed adaptable frameworks, compiled and cate-
gorized worldwide indicators (Breslow et al. 2016),
developed a full set of screening criteria, and scoped
indicators for two central areas of well-being
(resource access and self-determination) as a founda-
tion for others to build from. Concretely, an
immediate next step for users of our approach is to
evaluate indicators for an additional focal attribute
drawn from each “C,”and continue this process in an
iterative way until overlap in selected indicators
reaches a saturation effect (Strauss and Corbin
1990). To save time, users may choose to forego the
conceptualization of focal attributes into dimensions
and related attributes, reduce or group the screening
criteria, and use an expert team to evaluate indicators
rather than a full literature review. Priorities are to
adapt the frameworks to the local context, ensure
local validity of indicators through a participatory
process, and develop indicators that truly address
the environmental –and social –questions at hand.
The subsequent steps are to scope the data needed
to measure the resulting indicators; and, assuming
resources are limited, prioritize the most important
indicators to invest in with actual assessment, namely
by measuring existing data or collecting new data.
(Keep in mind that new data collection is not neces-
sarily more resource-intensive than compiling and
assessing sources of existing data.) An important
caveat to remember is that indicators will never be
fully comprehensive, but are meant to provide suc-
cinct insights into a complex system to aid in deci-
sion-making (Gregory 2012).
The method we propose is admittedly meticulous.
Its strength lies in its transparency: in the face of
competing indicators, too many indicators, or a
highly political atmosphere, this comprehensive and
systematic approach demonstrates why certain indi-
cators are chosen over others (Kershner et al. 2011;
James et al. 2012). It also reveals important areas of
human well-being that have not figured into IEAs
and policy and management decisions, in part
because we have not yet invested in the necessary
human dimensions data collection.
In this paper, we model a way to respond to
these cautions and recommendations. A compre-
hensive conceptualization of human well-being can
raise awareness about the multilayered social
dynamics of resource management, help identify
priorities, and call attention to matters that need
further attention. A detailed analysis of manage-
ment and policy documents ensures indicators are
tied directly to the power and stated responsibilities
of decision-makers. To mitigate for potential shifts
in power and agency away from stakeholders, as
well as to improve the local validity of indicators,
we emphasize the importance of understandability
and transparency, context-specific research, and
participatory processes in all stages of indicator
development and implementation. Finally, we illus-
trate how to build equity and justice directly into an
indicator system by emphasizing the importance of
measuring indicators of resource access and self-
determination across social variables, and thereby
16 S. J. BRESLOW ET AL.

assessing inequities and injustices in who benefits
from the environment, and in who has a say in
environmental decision-making.
Conclusion
An IEA strives to assess the social and ecological
conditions of an ecosystem over time in order to
track and predict how different management strate-
gies may be affecting ecological integrity and human
well-being (Levin et al. 2009). Like the biophysical
system, human well-being varies across contexts, and
it is difficult to disentangle the influence of environ-
mental and management changes from other social,
political, and psychological factors. Furthermore,
human well-being depends on both the use and the
protection of the environment, and where the balance
lies varies for different people. Fairly evaluating
human well-being with respect to EBM requires eval-
uating trade-offs, not only between ecological integ-
rity and human well-being, but also between the well-
being of different groups of people. Yet for the most
conceptually valid indicators, we found that data are
either unavailable, too coarse, or too general to eval-
uate these trade-offs. These gaps speak to the need to
significantly expand our capacity to understand the
human well-being of a diverse society, and how it is
affected by environmental change and decision-
making.
The framework presented here is a prototype: it
needs further testing and developing and will need
considerable modification to suit diverse contexts.
Any further steps should involve the people whose
well-being is to be assessed. The framework is
designed to encourage governments and commu-
nities to support a more just and livable world by
rigorously conceptualizing human well-being and
deliberately assessing the complex tradeoffs inherent
in environmental decision-making.
Acknowledgements
This work was supported by the National Oceanic and
Atmospheric Administration (NOAA), and Washington
Sea Grant. NOAA initiated the work described in this
paper to identify indicators of human well-being for the
IEA of the California Current large marine ecosystem.
Disclosure statement
No potential conflict of interest was reported by the
authors.
Funding
This work was supported by the National Oceanic and
Atmospheric Administration (NOAA) and Washington
Sea Grant.
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