Climate Policy
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/tcpo20
A global assessment of policy tools to support
climate adaptation
Nicola Ulibarri, Idowu Ajibade, Eranga K. Galappaththi, Elphin Tom Joe,
Alexandra Lesnikowski, Katharine J. Mach, Justice Issah Musah-Surugu,
Gabriela Nagle Alverio, Alcade C. Segnon, A.R. Siders, Garry Sotnik, Donovan
Campbell, Vasiliki I. Chalastani, Kripa Jagannathan, Vhalinavho Khavhagali,
Diana Reckien, Yuanyuan Shang, Chandni Singh, Zinta Zommers & The
Global Adaptation Mapping Initiative Team
To cite this article: Nicola Ulibarri, Idowu Ajibade, Eranga K. Galappaththi, Elphin Tom Joe,
Alexandra Lesnikowski, Katharine J. Mach, Justice Issah Musah-Surugu, Gabriela Nagle Alverio,
Alcade C. Segnon, A.R. Siders, Garry Sotnik, Donovan Campbell, Vasiliki I. Chalastani, Kripa
Jagannathan, Vhalinavho Khavhagali, Diana Reckien, Yuanyuan Shang, Chandni Singh, Zinta
Zommers & The Global Adaptation Mapping Initiative Team (2021): A global assessment of policy
tools to support climate adaptation, Climate Policy, DOI: 10.1080/14693062.2021.2002251
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CLIMATE POLICY
https://doi.org/10.1080/14693062.2021.2002251
SYNTHESIS ARTICLE
A global assessment of policy tools to support climate adaptation
Nicola Ulibarri a, Idowu Ajibade b, Eranga K. Galappaththi c, Elphin Tom Joe d,
Alexandra Lesnikowski e, Katharine J. Mach f,g, Justice Issah Musah-Surugu h,i, Gabriela Nagle
Alverio j, Alcade C. Segnon k,l, A.R. Siders m, Garry Sotnik n, Donovan Campbell o, Vasiliki
I. Chalastani p, Kripa Jagannathan q, Vhalinavho Khavhagali r, Diana Reckien r,
Yuanyuan Shang s, Chandni Singh t, Zinta Zommers u and The Global Adaptation Mapping
Initiative Teama
aDepartment of Urban Planning & Public Policy, University of California Irvine, Irvine, CA, USA; bPortland State University,
Portland, OR, USA; cVirginia Polytechnic Institute and State University, Blacksburg, VA, USA; dWorld Resources Institute, New
Delhi, India; eConcordia University, Montreal, Canada; fDepartment of Environmental Science and Policy, Rosenstiel School of
Marine and Atmospheric Science, University of Miami, Miami, FL, USA; gLeonard and Jayne Abess Center for Ecosystem Science
and Policy, University of Miami, Coral Gables, FL, USA; hUnited Nations University, Bonn, Germany; iDepartment of Public
Administration, University of Ghana, Accra, Ghana; jDuke University, Durham, NC, USA; kCGIAR Research Program on Climate
Change, Agriculture and Food Security (CCAFS), ICRISAT, Bamako, Mali; lUniversity of Abomey-Calavi, Cotonou, Republic of
Benin; mUniversity of Delaware, Newark, DE, USA; nStanford University, Stanford, CA, USA; oUniversity of the West Indies,
Kingston, Jamaica; pDepartment of Water Resources and Environmental Engineering, School of Civil Engineering, National
Technical University of Athens, Zografou, Greece; qLawrence Berkeley National Laboratory, Berkeley, CA, USA; rUniversity of
Twente, Enschede, Netherlands; sThe Australian National University, Canberra, Australia; tIndian Institute for Human
Settlements, Bangalore, India; uUnited Nations Office for the Coordination of Humanitarian Affairs, New York, NY, USA
ABSTRACT ARTICLE HISTORY
Governments, businesses, and civil society organizations have diverse policy tools to Received 7 May 2021
incentivize adaptation. Policy tools can shape the type and extent of adaptation, and Accepted 31 October 2021
therefore, function either as barriers or enablers for reducing risk and vulnerability.
Using data from a systematic review of academic literature on global adaptation KEYWORDSClimate change adaptation;
responses to climate change (n= 1549 peer-reviewed articles), we categorize the types policy instruments;
of policy tools used to shape climate adaptation. We apply qualitative and systematic review; Global
quantitative analyses to assess the contexts where particular tools are used, along Adaptation Mapping
with equity implications for groups targeted by the tools, and the tools’ relationships Initiative (GAMI);
with transformational adaptation indicators such as the depth, scope, and speed of transformational adaptation;
adaptation. We find diverse types of tools documented across sectors and geographic equity
regions. We also identify a mismatch between the tools that consider equity and
those that yield more transformational adaptations. Direct regulations, plans, and
capacity building are associated with higher depth and scope of adaptation (thus
transformational adaptation), while economic instruments, information provisioning,
and networks are not; the latter tools, however, are more likely to target marginalized
groups in their design and implementation. We identify multiple research gaps,
including a need to assess instrument mixes rather than single tools and to assess
adaptations that result from policy implementation.
Key policy insights
. Information-based approaches, networks, and economic instruments are the most
frequently documented adaptation policy tools worldwide.
. Direct regulations, plans, and capacity building are associated with higher depth and
scope of adaptation, and thus more transformational adaptation.
CONTACT Nicola Ulibarri ulibarri@uci.edu
© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.
org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and
is not altered, transformed, or built upon in any way.
2 N. ULIBARRI ET AL.
. Capacity building, economic instruments, networks, and information provisioning
approaches are more likely to target specific marginalized groups and thus equity
challenges.
. There are many regions and sectors where certain tools are not widely documented
(e.g. regulations and plans in Africa and Asia), representing a key research gap.
Introduction
Climate change is affecting societies and ecosystems globally. With increasing warming, future climate impacts
could be severe, widespread, and potentially irreversible (IPCC, 2021; Sanderson & O’Neill, 2020). Warming of
more than 1.5°C is estimated to increase the risk of floods, droughts, and heatwaves by 2050, impacting
global food supplies, ecosystem services, human health, and economic growth (Hoegh-Guldberg et al., 2019;
IPCC, 2018; Xu et al., 2020), with impacts disproportionately affecting marginalized communities and low-
income countries (Levy & Patz, 2015; Moellendorf, 2015). To reduce climate change’s impacts, the Paris Agree-
ment converged on the goals of building adaptive capacity and reducing vulnerability to climate change, while
paying special attention to equity (i.e. the needs of marginalized populations) (UNFCCC, 2015). Yet adapting to
climate change impacts incrementally is insufficient to support capacity-building actions in many regions (af
Rosenschöld & Rozema, 2019; Fook, 2017; Kates et al., 2012).
Increasingly, transformational adaptation – defined as actions that lead to the adoption of new behaviours
and functionings that take place across a wide spatial or sectoral range and signify a deep systemic change (de
Coninck et al., 2018) – is considered necessary for lessening the impacts of climate change and preventing
major losses (Ajibade & Adams, 2019; Few et al., 2017; Kates et al., 2012). Conventional definitions of transfor-
mational adaptation commonly focus on the depth and extent of change (de Coninck et al., 2018; Termeer et al.,
2017). However, such adaptations may entail adopting a future-oriented approach and can include a combi-
nation of technological and institutional innovations, changes in power structures and social and economic
behaviours, and shifts in individual and system capacities to allow for new development trajectories (Béné
et al., 2014; Eakin et al., 2016; Kofinas et al., 2013), making them inherently about social equity as well. Under-
standing how to incentivize adaptation that is both transformational and equitable can thus help the global
community achieve the provisions of the Paris Agreement.
Governments, corporations, and civil society organizations at multiple levels are spearheading climate
change adaptation efforts and incentivizing individuals and communities to take action (Berkhout, 2012;
Mubaya & Mafongoya, 2017). These organizations use various policy options, tools, instruments, actions, and
interventions (henceforth referred to as ‘policy tools’) to respond to specific impacts of climate change. The
types of policy tools used shape both adaptation governance approaches and longer-term reduction of risk
and vulnerability (Milhorance et al., 2020; Olazabal & Ruiz De Gopegui, 2021). Numerous typologies exist to
capture the range of tools that governments and other actors use to implement adaptation, but generally,
these encompass instruments like command and control mandates, economic incentives, information provi-
sioning, and support and capacity building (Clar & Steurer, 2018; Henstra, 2016; Lesnikowski et al., 2019; Milhor-
ance et al., 2020). The optimal mix of tools depends on the risk in question, geographical and institutional
contexts, organizational priorities, institutional path dependencies, perceptions about tool appropriateness,
and degrees of vulnerability of the affected population (Eliadis et al., 2005). For instance, slow-onset impacts
may require different tools than fast-moving extreme events. Likewise, a country’s capacity to finance the devel-
opment of tools or to enforce their implementation may make certain tools more effective at reducing risk.
A number of recent papers have reviewed adaptation policy tools at local, regional, and national scales (e.g.
Bhandary et al., 2021; Biesbroek & Delaney, 2020; Henstra, 2016; Hurlbert et al., 2019; Patterson, 2021; Thistle-
thwaite & Henstra, 2017). However, a global analysis of adaptation policy tools across regions, sectors, and types
of tools is pending. The lack of a global overview has three major implications. First, understanding what tools
are used and how they influence adaptation can contribute to the planned global stocktake of collective pro-
gress towards achieving the Paris Agreement goals (Berrang-Ford et al., 2019; Tompkins et al., 2018), specifically
understanding the ‘adequacy and effectiveness of… support for adaptation’ (UNFCCC, 2015). Second, a global
CLIMATE POLICY 3
overview of the types of tools available for incentivizing adaptation, and information on which tools work well
for different contexts, can inform organizations’ future choice of tools to match their capacity and goals. Third,
understanding where different policy tools andmixes are documented in the peer-reviewed literature can high-
light key research gaps.
This paper draws on a systematic and comprehensive review of the global climate adaptation literature
(2013–2019) to answer the following questions:
(1) What types of adaptation policy tools are documented in the peer-reviewed literature?
(2) How does tool use vary by type of organization, region, sector, and hazard?
(3) How are marginalized groups targeted by adaptation policy tools?
(4) How do policy tools shape transformational adaptation?
The paper first briefly reviews policy tool theory and its application in climate change research. It then
explores how the adaptation literature documents the use of policy tools to mandate, incentivize, or
support climate adaptation responses. It then examines the contexts underlying the tools that are used.
Lastly, it explores the relationship between tool type and the broader transformational nature of adaptation,
including equity, depth, scope, and speed. It concludes with a discussion of key research and policy needs.
Policy tools and climate change
Policy tool theory argues that tool choice is a fundamentally political process shaped by a policy problem’s
framing, the character of the instruments, and the context in which policy processes occur (Howlett, 2018;
Linder & Peters, 1989). Tool choices are reflected in distinct policy styles that emerge in different sectors and
countries (Hall, 1993; Howlett & Tosun, 2018; Richardson, 1982). Policy tools tend to accumulate over time in
increasingly complex policy mixes, rather than undergoing periodic dismantling and re-design (Béland,
2007; Howlett & del Rio, 2015; Rayner et al., 2017). Policy failure, therefore, often lays in poor policy design
and fit between tool choice, mix and institutional context.
Climate change scholarship increasingly draws from the policy design literature to explain tool choice and
change over time (Schaffrin et al., 2015). The policy mix concept has been applied to examine policy strategies
in sustainability transitions research (Kern et al., 2019; Kivimaa & Kern, 2016; Rogge & Reichardt, 2016), particu-
larly in the case of energy transitions (Johnstone et al., 2017; Lindberg et al., 2019; Schmidt & Sewerin, 2019).
Policy mixes are also central to climate policy integration analysis (Di Gregorio et al., 2017; Hogl et al., 2016;
Kalaba et al., 2014).
While early adaptation research focused on developing unique typologies of adaptation tools to track adap-
tation efforts across countries and levels of government (e.g. Biagini et al., 2014; Gagnon-Lebrun & Agrawala,
2007; Lesnikowski et al., 2011), recent work has pushed for the adoption of established frameworks from policy
design scholarship to examine the political and institutional factors that shape tool choice (Berrang-Ford et al.,
2019; Biesbroek et al., 2015; Henstra, 2016; Mees et al., 2014). Policy mix analysis is consequently becoming
more prominent in empirical adaptation scholarship (Biesbroek & Delaney, 2020; Hughes, 2020; Hurlbert &
Gupta, 2019; Milhorance et al., 2020). Comparative studies of adaptation policy mixes observe that distinct
policy approaches are emerging across countries at national and local levels, suggesting the possibility that
different adaptation policy styles are emerging in different contexts (Biesbroek et al., 2018; Lesnikowski
et al., 2020). These mixes tend to grow more complex over time, reflecting the layering pattern observed in
other policy areas (Lesnikowski et al., 2019).
Methods
Data collection
Our analysis draws on the Global Adaptation Mapping Initiative’s (GAMI) database of academic studies docu-
menting adaptation practices. GAMI is a global network of over 120 researchers who sought to analyze
4 N. ULIBARRI ET AL.
adaptation to climate change through the largest systematic review to date of articles in the peer-reviewed
literature (Berrang-Ford, Siders, et al., 2021b). The GAMI database was created through (1) article screening
and database constructing; (2) article coding; (3) data reconciliation and synthesis; and (4) expert elicitation
of results. Details on the construction and coding of the GAMI database are available in a series of published
protocols (Berrang-Ford, Lesnikowski, et al., 2021; Fischer et al., 2021; Lesnikowski et al., 2021). In brief, a search
of Scopus, Web of Science, and Google Scholar based on search terms that combined concepts of climate
change and adaptation or adaptation-related responses identified nearly 50,000 articles published between
2013 and 2019 (Fischer et al., 2021). These articles were screened through a combination of machine-learning
and manual review to include only articles that reported empirical data on adaptation-related responses by
human actors to climate change. Ultimately, 1682 articles were included in the final GAMI dataset and were
coded by at least two coders (Lesnikowski et al., 2021). The GAMI administrative team conducted a quality-
control assessment to re-code any unreliable codes and address conflicting codes. Finally, an expert elicitation
protocol was carried out to assess and confirm the validity of the results.
GAMI coders answered 27 questions about each paper. The full codebook is available in Lesnikowski et al.
(2021). A subset of these variables is analyzed in this paper, including geographic region, topical sector, actors,
equity, transformational nature, and motivating hazard (Table A1). Coding responses for geographic region,
topical sector, response type, and hazards were modelled on the structure of IPCC AR6 to enable future com-
parisons with IPCC analyses and syntheses (e.g. countries were assigned to continents and/or identified as Small
Island States based on the IPCC assignment of countries to these regions). ‘Actors’ reflect common organiz-
ational categories, including governments, businesses, and civil society, as well as individuals. ‘Equity’ asked
whether adaptation responses were designed or intended to specifically benefit one or more marginalized
groups (e.g. women, migrants, Indigenous peoples). Studies were not coded for, and often lacked information
about, whether the adaptation actions achieved their goal of improving equity, so our analysis measures
whether equity was noted as an intention rather than an outcome; future work will be needed to assess
equity outcomes (Araos et al., 2021).
To further understand the transformational nature of adaptation, we categorize adaptation actions in terms
of their depth, scope, and speed (Termeer et al., 2017; see Table A2 for GAMI definitions). Depth refers to the
degree to which an adaptation action differs from existing practices or alters fundamental systemic features
(Kates et al., 2012). Scope entails the spatial scale of change, the geographic reach, and/or the number of insti-
tutions and sectors affected. Speed reflects the rapidity with which a change occurs. A transformational adap-
tation involves activities that go beyond business-as-usual adaptations, extends over multiple sectors or larger
spatial scales, and occurs quickly (Ajibade & Adams, 2019; Termeer et al., 2017).
To identify broad classes of policy tools used to support adaptation, we conducted a deductive, qualitative
content analysis of quotes and summaries in the GAMI dataset. We used four predefined tool categories as
defined in Taylor et al. (2012)’s review of environmental policy instruments: direct regulation, economic instru-
ments, information-based instruments, and capacity building1 (Table 1). We added two additional categories
that have been documented as particularly important for climate adaptation: plans and networks. Plans, a
Table 1. Overview of policy tool types used in this paper.
Category Definition Examples from GAMI dataset
Direct regulation Law or policy mandating or restricting actions National water policy (Alam, 2015), zoning ordinance
(Bowden et al., 2019)
Plan Strategy or plan (voluntary or mandated) Hazard mitigation plan (Boyer et al., 2017), climate action
plan (Noblet & Brisson, 2017)
Economic Use of taxes, subsidies, insurance, or other financial Flood insurance (Thistlethwaite, 2017), agricultural subsidy
instrument mechanisms (Burnham & Ma, 2017)
Information-based Activities to raise awareness or promote particular Early warning system (Kaján, 2014), training on water
instrument actions through provisioning of information conservation techniques (Yaffa, 2013)
Capacity building Activities to help individuals be more effective at Providing seeds for farmers (Stoilova et al., 2019),
adaptation constructing irrigation infrastructure (Zhang et al., 2016)
Network Community networks or inter-organizational Water user association (Villamayor-Tomas & García-López,
collaborations to develop or implement adaptation 2017), regional adaptation collaborative (Khan et al., 2018)
responses
CLIMATE POLICY 5
form of procedural authoritative instrument (Howlett, 2000), are widely used to identify and direct climate
adaptation strategies at local and national levels (UNEP et al., 2021). The GAMI database includes studies
that provided evidence of plans being implemented (not planning activities alone), so our analysis captures
organizations whose plans are implemented or whose adaptation actions are guided by a plan, rather than
planning as an adaptive action itself (Fischer et al., 2021). Networks refer to groups of individuals or organiz-
ations that work collectively to plan or implement adaptation strategies; these can be seen as a form of co-regu-
lation or self-regulation (Taylor et al., 2012).
The full GAMI dataset of 1682 papers was scrutinized to eliminate papers where the adaptation response was
suggested but had not been documented in practice, as well as papers that lacked sufficient descriptions of
adaptation responses to determine whether policy tools were used. This process resulted in the exclusion of
133 papers and a final dataset of 1549 papers. These 1549 papers were coded for the six tool categories in
Table 1. Two team members coded 120 of these papers to check for intercoder reliability (which was 78%).
Papers with conflicting tool codes were reconciled by the lead author.
Data analysis
The GAMI database, as well as our additional coding, resulted in a variety of categorical variables describing
where and how adaptation tools are used (Table 1 and Table A1). We first cross-tabulated each tool type
with the sector, region, actor type, and climate hazard variables to assess the context in which each tool
type was used. A similar descriptive analysis was performed to understand what types of disadvantaged
groups were targeted by each tool type.
To formalize the conditions under which particular tools are used, we conducted a series of logistic
regressions, with tool use (a binary variable indicating the presence of each tool type) as the dependent variable
and sector, region, actor type, and climate risk type as independent variables. To analyze the transformational
nature of adaptation, we used ordered multinomial logistic regressions to model how the inclusion of each tool
type affected the probability that an adaptation was low, medium, or high in depth, scope, or speed. Regression
analysis was conducted using R’s MASS package (Ripley et al., 2021).
The cross-cutting analysis of policy tools was complemented by a case-study exploration of each type of
policy tool. In papers providing extended documentation of the application and outcomes of the different
types of policy tools, several case studies were identified in which each tool type was used alone or in combi-
nation with other policy tools. This comparative analysis focused on ways the policy tools influenced adaptation
and factors that enabled or constrained their implementation and impacts.
Results
Overview of policy tools in the adaptation literature
Of the 1549 papers in our dataset, 657 (42%) described one or more policy tools. Of these, 211 described infor-
mation provisioning, 182 described networks, 171 described economic instruments, 136 described plans, 135
described direct regulations, and 88 described capacity building. Each category contained diverse examples of
these tools (Table 1); they were implemented by diverse organization types and at local, regional, and national
scales. The remaining 58% of papers discussed autonomous adaptations2 that occurred without an associated
policy tool.
Of papers that described a policy tool, the majority (n = 454, 69%) focused on only one type. One hundred
forty six papers (22%) described two tool types, 51 (8%) described three, and 6 (1%) described four tool types.
This implies either that many adaptations are supported by a single tool type or that researchers tend to focus
on single tools or tool types and, therefore, only describe those in their analysis. Additionally, correlations
between tool types are negative, suggesting that no specific tools tend to be documented in tandem with stat-
istically significant frequency (Figure A1).
Literature documenting adaptation in different regions and sectors varies in its focus on policy tools (Figure 1).
For reference, Table A3 reports the total number of papers in the dataset by region and sector. In this summary,
6 N. ULIBARRI ET AL.
Figure 1. Frequency of tool description by region and sector. Circles depict the percentage of papers in a region/sector combination that
describe each tool. (Poverty: Poverty livelihoods & sustainable development; Health: Health, well-being & communities; Cities: Cities settlements
& key infrastructure; Food: Food fibre & other ecosystem products; Water: Water & sanitation; Ocean: Ocean & coastal ecosystems; Terrestrial: Ter-
restrial & freshwater ecosystems).
we ignore region/sector combinations with fewer than five papers overall. For instance, while 67% of Poverty,
livelihoods & sustainable development (‘Poverty’) papers in Europe describe direct regulations, there are only
three papers total, so it is unclear whether this frequency is representative of adaptation tools in practice.
. Direct regulations feature in 24% of papers describing adaptations for the sector Cities, settlements & key
infrastructure (‘Cities’), and are common in Europe (21%) and papers describing multiple continents (18%).
. Plans are most common in the Cities sector (25% of papers) as well as across sectors in Europe (23%) and
Small Island States (23%); they are also particularly common in the Ocean & coastal ecosystems sector in
Europe (46%).
. Economic instruments are not a predominant tool in any region or sector, appearing in less than 15% of
papers in any region or sector; however, they are more common in Terrestrial & aquatic ecosystems
CLIMATE POLICY 7
(‘Terrestrial’) papers from Central and South America (22%) and Small Island States (29%), as well as Water &
sanitation (‘Water’) papers describing multiple continents (30%).
. Information-based approaches are most frequent in North America (20%) and Multiple Continents papers
(20%), and they are used across continents in the Health, wellbeing & communities (‘Health’) sector (16%).
. Networks appear frequently in the Cities sector (18%), in North America (18%), and in papers describing mul-
tiple continents (18%), and they are particularly common in Central & South American adaptations in the
Terrestrial (44%) and Health sectors (27%), as well as in the Poverty sector in North America (31%).
. General capacity building approaches are the least commonly described of any tool (<12% in any region or
sector), but they do appear regularly in the Terrestrial sector in Central & South America (22%) and in Small
Island States (29%).
. Despite being the most common regions in the dataset overall, papers in Africa and Asia did not describe
specific policy tools as frequently as other regions; however, economic instruments, information provision-
ing, and networks were the three most common types in both regions. Only 4% of papers in Africa and 8% in
Asia described either direct regulations or plans.
Factors associated with tool use
To understand the contexts where tools are most frequently used, Table 2 shows the odds ratios (ORs) for logis-
tic regressions predicting when particular tools are documented by region, sector, actor type, and hazard. The
OR can be interpreted as the difference in likelihood of having a tool documented when a particular character-
istic is present versus absent; for instance, in the Regulation model, an OR of 2.48 on Cities says that a paper
describing adaptation in the Cities sector is 2.48 times more likely to describe a direct regulation than one
not in the Cities sector. An OR greater than one means that variable increases the likelihood of a tool being
described, and an OR less than one decreases the likelihood that the tool is described (holding all other vari-
ables constant).
Autonomous adaptations are negatively associated with all six tool types, with papers describing an auton-
omous adaptation being significantly less likely to describe a policy tool. This suggests either that autonomous
adaptations are truly ‘autonomous’, in that they are taken by individual actors acting independently, or that
researchers are unlikely to explore both policy tools and autonomous adaptations in the same manuscript.
The latter indicates that papers describing tools are unlikely to describe the individual level adaptations that
may result from the tool’s application, and that papers on autonomous adaptations are unlikely to explore
external policies that may have influenced individual decisions.
Different tools are used in different contexts. In the articles we assessed, direct regulations are described
more frequently than average in the Cities and Poverty sectors, and they are less likely to accompany an adap-
tation in Africa. Direct regulations are strongly associated with national and local governments, as well as cor-
porations; they are less likely to be used in adaptations with large scale civil society organizations present. No
specific hazard is associated with the use of direct regulations.
Plans or strategies are most frequently used in Cities, but surprisingly they are statistically less likely to be
described in academic studies documenting Health sector adaptations.3 Adaptations addressing extreme
heat are significantly more likely to be described as using plans. Plans are less frequently described in Africa.
Plans are described in tandem with international organizations and national and local governments, and
they are unlikely to appear when individuals are involved.
Economic instruments are significantly associated with the Food, fibre, and other ecosystem products (‘Food’)
sector, and they are often described in tandem with international organizations and national governments.
Economic instruments (especially insurance) are frequently used to respond to flooding. No region is signifi-
cantly more or less likely to use economic instruments.
Information-based approaches are often described in tandem with local level civil society organizations
and are used to respond to precipitation variability and a loss of Arctic sea ice. Holding actors and hazards
8 N. ULIBARRI ET AL.
Table 2. Odds ratios (ORs) predicted by logistic regression models of factors associated with tool use.
Regulation Plan Economic Information Capacity Network
(Intercept) 0.06*** 0.21*** 0.06*** 0.19*** 0.02*** 0.13***
Sector
Cities 2.48** 1.87* 1.26 0.74 1.89 1.50
Food 1.01 0.91 1.75* 1.34 2.03* 1.30
Health 1.01 0.62* 1.05 1.07 1.14 0.78
Ocean 1.00 1.07 0.51 1.00 0.31 0.65
Poverty 1.66* 0.91 1.39 0.93 1.38 1.08
Terrestrial 0.97 0.95 1.18 0.61 2.27* 1.15
Water 0.89 1.65 0.89 0.80 0.73 0.59*
Region
Africa 0.46** 0.43** 0.92 1.42 1.83 0.78
Asia 1.11 1.11 1.14 1.12 1.68 0.92
Oceania 1.53 1.43 0.97 1.17 1.12 1.49
Central/South America 1.29 0.86 0.98 0.80 1.89 0.95
Europe 1.21 1.13 1.15 1.09 0.22* 0.94
North America 0.78 0.93 1.48 1.58 1.25 1.05
Small Island States 0.56 1.39 0.80 0.82 0.43 0.44
Actor
International 1.40 2.42** 2.06** 0.66 2.73** 1.36
National Government 2.67*** 2.07** 2.86*** 1.29 1.56 0.83
Subnational Government 1.02 0.76 0.78 1.38 0.76 0.96
Local Government 2.36*** 1.98** 0.82 0.76 1.19 1.47
Corporation 1.96* 0.54 1.02 0.71 0.68 1.14
Small/Med Enterprise 0.99 0.72 1.29 1.14 1.17 1.11
National Civil Society 0.51* 0.92 0.67 1.27 1.40 1.98**
Local Civil Society 0.87 0.93 0.94 2.27*** 1.10 2.73***
Individual 0.89 0.56* 1.31 1.23 1.72 0.93
Hazard
Sea level rise 0.71 1.19 1.32 0.67 0.81 0.79
Flooding 0.82 0.71 1.47* 1.18 1.08 1.26
Heat 1.40 1.68* 0.99 0.96 1.01 0.97
Precipitation variability 0.95 0.79 1.11 1.57* 0.82 0.82
Drought 1.25 1.16 1.29 1.05 1.09 1.21
Ocean temperature 2.22 2.07 0.20 0.68 3.65 1.73
Arctic Ice 1.36 0.22 0.48 3.96** 1.31 1.57
General Climate 1.27 1.21 0.85 0.89 0.85 1.29
Autonomous adaptation 0.20*** 0.13*** 0.28*** 0.15*** 0.24*** 0.27***
AIC 750 702 1011 1107 637 1012
Significance codes: ***p < 0.001; **p < 0.01; * p < 0.05; n = 1549. AIC = Aikake’s Information Criteria, a common measure of model goodness-of-
fit.
constant, they are not significantly associated with any specific sectors or regions (contrasting the visual trends
in Figure 1).
Capacity building is used more frequently in the Food and Terrestrial sectors. It is unlikely to be used in Euro-
pean adaptation and is most often accompanied by international organizations.
Networks are unlikely to appear in adaptations in the Water sector and are strongly associated with both
national and local scale civil society organizations. They do not appear more or less frequently for specific
regions or hazards.
Relationship with equity
Figure 2 displays how often each tool was intended to target specific marginalized groups. Overall, capacity
building was the tool that most often targeted marginalized groups (75% of papers documenting capacity
building), followed by economic instruments (64%), networks (63%), and information-based approaches
(60%). Direct regulations (47%) and plans (38%) were less likely to target marginalized groups. Low-income
groups were the equity category targeted most frequently by every kind of tool, while migrants and people
with disabilities were targeted the least. Across marginalized groups, information-based approaches were
the most frequently used tool, apart from ethnic minorities (most commonly targeted by networks), migrants
CLIMATE POLICY 9
Figure 2. Tools by the targeted marginalized group.
(most commonly targeted by regulations), and people with disabilities (most commonly targeted by economic
instruments).
Although we cannot make definitive claims about why certain tools were utilized to target certain groups,
we obtained a richer qualitative understanding of how tools promote equity from the studies examined. For
instance, in Baja California Sur, Mexico, Finkbeiner (2015) highlights the critical role that networks, in the
form of fishing cooperatives, play in climate adaptation for small-scale fishers. Caretta (2014) describes econ-
omic instruments (specifically microcredit schemes) that target women’s groups; combined with training
about agricultural adaptations, the credit enhances women’s adaptive capacity to climate change. In northern
Mali, local strategies based on livelihood diversification, specifically targeting seasonal migrants, provide mech-
anisms to cope with climate change, while sub-national and national plans are needed to elevate coping to
adaptation (Brockhaus et al., 2013). In Mexico, after Hurricane Dean, government regulations on forest harvest-
ing allowed for low-income subsistence farmers to adapt to the damage of the hurricane by shifting to charcoal
harvesting (Schramski & Keys, 2013). Capacity building is exhibited in the roll-out of extension services targeted
at low-income farmers, which significantly increased their adoption of conservation farming practices, thereby
making them more resilient to climate change and protecting their livelihoods (Arslan et al., 2014).
Tools and transformative potential of adaptation
A core question underlying tool use is whether certain policy tools lead to more transformational adaptation.
Importantly, adaptation responses demonstrating high depth, scope, or speed are rare. Only 25 studies (2%)
were high depth, 72 (5%) high scope, and 119 (8%) high speed, and no studies were high in all three transform-
ation categories. Nevertheless, some policy tools are associated with more transformational adaptations.
Three hundred thirty nine studies (22%) reported medium depth adaptations and 417 (27%) reported
medium scope adaptations.
Table 3 displays results from ordered logistic regressions predicting the depth, scope, or speed of adap-
tation. The coefficients are the ORs of being low versus medium or medium versus high depth, scope, or
speed when a given tool is present. For example, an adaptation associated with a direct regulation is 2.24
times more likely to be in a higher depth category than one not using a direct regulation. Adaptations
Table 3. Ordered logistic regression predicting depth, scope, and speed of adaptation by tool use.
Depth Scope Speed
Direct regulation 2.24*** 2.66*** 0.99
Plan 2.04*** 2.65*** 0.94
Economic instrument 1.19 1.57** 1.22
Information provisioning 0.96 1.27 0.85
Capacity building 2.23*** 2.11*** 1.12
Network 1.80*** 1.38 0.81
Intercept Low/Med 1.33 0.96 0.72
Intercept Med/High 4.36 3.30 1.69
AIC 1750 2168 1363
n 1279 1424 801
Significance codes: ***p < 0.001; **p < 0.01; *p < 0.05.
10 N. ULIBARRI ET AL.
supported by direct regulations, plans, capacity building, and networks are significantly more likely to be higher
in depth (i.e. resulting in a more substantial transformation of behaviour or practice). Adaptations supported by
regulations, plans, economic instruments, and capacity building are more likely to be higher scope (i.e. impact-
ing a larger region or number of sectors). None of the tool types were significantly associated with slower or
faster adaptations.
To understand how and why different tools have differential relationships with the extent of adaptation, we
draw on case studies from specific papers in the database.
National level regulations are shown to catalyze local planning and infrastructure changes with mixed
success. Flyen et al. (2018) discuss how three Norwegian municipalities incorporated climate change into
their local planning after an amendment to the Norwegian Planning and Building Act. In one municipality,
the revisions catalyzed political and administrative support for climate-adapted storm water management
through legally binding provisions in local plan documents. In another municipality, planning agencies had
several directions for climate adaptation, but these were fragmented and difficult to exercise holistically. Li
et al. (2013) analyze several policies developed for local communities in China to help adapt to climate
change. A regulation to enhance the use rights of small rural water infrastructure and farmlands led to invest-
ments in water infrastructure and application of water saving technology.
Papers documenting how plans shape on-the-ground adaptations are scarce in the dataset. Beaudoin and
Gosselin (2016) analyzed the implementation of the health component of Québec, Canada’s Climate Change
Action Plan for 2006–2012. Implementation included pilot projects using city greening and suggested that sig-
nificant gains in coolness can only be achieved with large projects. Koski and Siulagi (2016) analyzed climate
action plans in large United States cities to assess whether they included adaptation. They found that 33%
of plans had no adaptation planning, while 21% integrated adaptation throughout the plan. Cities that
framed climate change effects in the language of hazards were more likely to incorporate adaptation
approaches in their climate action plans.
Economic instruments are often used to incentivize behaviour that builds individual and community resili-
ence. Pasaribu and Sudiyanto (2016) found that rice farmers responded positively to a pilot insurance scheme
introduced by the Indonesian government, although they also identified many constraints for wider implemen-
tation. Caretta (2014) analyzed the impact of two microfinance schemes in Kenya to improve women’s capacity
to adapt to climate change. The study found that all women increased their income, while also expanding and
diversifying their small business or agricultural production. The microfinance scheme’s success depended on
factors including learning new farming and retail practices and experience sharing with other members.
Information provisioning has mixed effects on adaptation practices. Allaire (2016) conducted an experiment
to test the effect of information provision on flood management actions taken by households in Bangkok, Thai-
land. The treatment group received details on home retrofits and home insurance, and were told about the
insurance purchasing practices of their peers. These interventions had no effect on home retrofits but increased
insurance purchase by about 5%. Haworth et al. (2018) analyzed 27 ICT initiatives for communicating climate
and agricultural information to smallholder farmers. Most programmes were top-down initiatives from non-
profits, government, and companies. One exception, Digital Green, identified local ‘champions’ to create
videos on farm practices that were then viewed by the community. As a result, sustainable livelihood practices
increased in the community. Haworth et al. (2018) identify several traits that tend to determine the initiative’s
success, including affordability, accessibility, and local relevance of the information provided.
Capacity building tools generally incentivized individuals to adopt more adaptive strategies, but not all tools
effectively mitigated climate impacts. Examples included governmental and non-governmental organization’s
interventions to increase access to improve seed and irrigation technology for farmers in Afghanistan, an inter-
vention that significantly reduced flood risks and improved economic and financial opportunities for farmers
(Jawid & Khadjavi, 2019). In Bangladesh, the government offered resources to residents to build cyclone resi-
lient housing. However, only 6% of reconstructed houses could withstand cyclones, indicating a need for
increased institutional and infrastructural support (Islam et al., 2018). In China, government support for con-
struction of private tubewells in villages improved adaptation to drought; while this enhanced irrigation for
farmers, there were concerns about groundwater tables and its redistribution around villages and households
(Zhang et al., 2016).
CLIMATE POLICY 11
Networks were important for enabling higher depth adaptations, but often focused at very local scales.
Dapilah et al. (2020) evaluate how social networks supported livelihood diversification and climate change resi-
lience in rural Ghana. The networks provided material and non-material resources necessary for diversification.
However, social networks could simultaneously reinforce exclusion or lead to the marginalization of some
groups, limiting the resilience of the whole community. Murtinho (2016) showed that in response to water scar-
city, Water Users Associations in Andean Colombia helped build community capacity for micro-watershed man-
agement (land purchases, reforestation, and establishing fences to protect water sources).
Discussion
This paper reviewed the climate adaptation literature’s depiction of adaptation policy tools. Our findings
suggest that most of the adaptation literature focuses on single tools rather than the dynamics of tool
mixes. Of papers that documented any tool, nearly 70% focused on only one tool type. This runs counter to
the policy design literature, which demonstrates that major problems are rarely addressed through single
policy tools. Policy responses – including in climate adaptation – tend to see the accumulation of multiple
tools over time (Del Rio & Howlett, 2013; Lesnikowski et al., 2019). This empirical gap is concerning: it presents
a partial view on how adaptation is being implemented in different contexts, and leaves open questions about
how tool interactions shape adaptation and risk reduction. Individual policy tools interact within policy mixes in
unique ways and can produce unintended consequences that either support or undermine progress towards
policy goals. A focus on single instruments may miss these interactions and raises the possibility that outcomes
ascribed to individual tools (whether negative or positive) may actually be outcomes of tool interactions or
other tools within a mix.
Additionally, very few of the 30% of papers that described multiple tools documented relationships between
these tools. Many discussed different tools used in different locations or contexts (e.g. one city that adopted a
plan and another that developed a new zoning code). Others did not describe the relationship between tools in
enough detail to draw conclusions about their influence on equity or transformational adaptation. Studying the
dynamics between policy tools is an important research gap.
We also find that papers that focus on autonomous adaptations rarely describe policy tools that may have
prompted or supported those adaptations, and that papers describing policy tools often do not depict individ-
ual-level adaptations that may result. For a full understanding of how adaptation is progressing, documenting
both policy triggers and resulting adaptations is important.
Our logistic regression results (Table 2) indicate that tool use is most significantly associated with differences
in actor types, with regulations, plans, and economic tools (unsurprisingly) associated with governments, and
informational and network-based tools associated with civil society. The significant associations between regu-
lations and corporations and national civil society, and between plans and individuals, likely reflects the target-
ing of these tools, rather than their implementation.4 These relationships suggest that tool choice reflects
differences in authority over more coercive instruments like regulations, plans, or taxes, as well as the
different actors’ financial capacity to create market- or subsidy-based adaptation interventions.
Trends by region and sector were less pronounced, apart from direct regulations and plans being predomi-
nant in cities. Moreover, some specific relationships appear counterintuitive; for instance, women’s networks
and Water User Associations are considered a primary tool in water and sanitation (e.g. Murtinho, 2016; Villa-
mayor-Tomas & García-López, 2017), yet networks are described less frequently in the water sector within the
GAMI database than in other sectors. This may relate to the limits of keyword-based literature searches and to
challenges with defining adaptation: if many studies on water and sanitation policies do not use climate adap-
tation language, they would not show up in a review of the adaptation literature despite potentially having
climate resilience implications (see Nalau et al., 2021). Similar search biases may affect other sectors as well.
Policy instrument choice theory may help us to understand the relationship between tool choice and the
transformational potential of adaptation efforts, and more specifically why economic instruments, infor-
mation-based instruments, and networks are not consistently associated with depth or scope of adaptation.
Economic tools like market-based instruments or subsidies tend to be adopted where government capacity
is high, when the problem being addressed is complex, and when many actors are being targeted. Tools
12 N. ULIBARRI ET AL.
like national flood insurance programmes or crop insurance programmes would fall into this category; they
address many actors with diverse circumstances (Howlett, 2005). Our results indicate that economic instru-
ments are associated with a wider scope but shallower depth of change and with international actors and
national governments. This suggests that economic instruments are being adopted at higher levels of govern-
ance and reach many people, but may not provoke a deeper level of behavioural or cultural change. This same
theory suggests that information provisioning is prevalent where capacity is high but policies target a smaller
number of actors (Howlett, 2005). This may result in adaptation outcomes that are shallower and narrower in
scope. We find information-based tools are significantly associated with local civil society organizations but no
other types of actors, suggesting that these types of tools tend to be smaller in extent. Finally, the policy
implementation styles model predicts that networks are prevalent where capacity is low, but actors are
aiming to affect many people or other targets. Our results appear inconsistent with this expected relationship,
as networks are associated with great depth of change but not a wider scope. This relationship may be
influenced, however, by our finding that networks are associated with national and local civil society organiz-
ations, but no other types of actors. Adaptation activities implemented by civil society may tend to be more
targeted than those of government actors, and so achieve a greater depth of change but to a limited scale.
Notably, no policy tools appear to be associated with speed of change. This is consistent with scholarship
that argues transformational change is a long, and sometimes discontinuous, process (Termeer et al., 2017).
The relationship with equity also points to considerations for incorporating equity into transformational
adaptation. Whereas policy tools are being applied to support and target some groups such as low-income
communities and women, there are also marginalized groups insufficiently considered in documented adap-
tation policy tools, especially migrants and individuals with disabilities (see also Araos et al., 2021). This
study is limited to adaptation tools documented in the academic literature, and it is possible that non-docu-
mented adaptation tools are focusing on a wider range of disadvantaged groups. However, the lack of aca-
demic documentation demonstrates a gap in the research and most likely signals areas for improved
knowledge and practice. In particular, research and practice will need to consider which policy tools or mix
of tools enable adaptation by marginalized groups and underserved communities. Further, understanding
how different combinations of tools can best serve groups with multiple marginalized identities is essential,
as climate impacts frequently are amplified where intersectional vulnerabilities and government disinvestment
magnify outcomes. In this study, tools with greater transformational potential, particularly regulations and
plans, were found to be less likely to consider equity, as compared to tool types less associated with high
depth and scope of adaptation (i.e. networks, economic instruments, and information provisioning). This
pattern highlights the potential for certain types of potentially transformational adaptation to perpetuate or
exacerbate existing inequities in societies (Blythe et al., 2018; Pelling et al., 2015).
Conclusion
This paper presented an overview of how policy tools are depicted in the global adaptation literature. We found
that information-based approaches, networks, and economic instruments are the most frequently documented
adaptation policy tools worldwide. Each tool type was associated with particular actors, geographies, sectors,
and contexts, with (for instance) regulations and plans prominent in cities and economic instruments common
in food-related adaptations. Direct regulations, plans, and capacity building are associated with more transfor-
mational adaptation, while capacity building, economic instruments, networks, and information provisioning
approaches are more likely to target specific marginalized groups. These findings underscore a key policy
need: developing policy tools that both support transformational adaptation and protect the needs of margin-
alized groups. Our work suggests that capacity building tools already do this, and that direct regulations and
plans could if they added more attention to supporting equity.
As a limit of the GAMI systematic review and this subsequent evaluation, published articles are the unit of
analysis. The relationships identified are, therefore, those that exist in the peer-reviewed literature. Any biases
that exist in what is studied are present in our work. The literature in some cases may robustly reflect relation-
ships between specific policy tool types and factors affecting their adoption. In other cases, however, there are
likely limits in the degree to which prevalence of tool types and their documented outcomes in the literature
CLIMATE POLICY 13
represent overall prevalence and outcomes. For example, economic instruments and general capacity building
approaches were documented relatively infrequently across sectors, and it remains uncertain whether their
prevalence in the systematic review dataset is a function of their actual prevalence or of tool types most com-
monly studied. Similarly, papers focusing on Africa and Asia described policy tools less frequently. The relative
importance of actual prevalence versus research-topic bias is another important question for future research, as
geographic biases in adaptation literature have been well-documented (Hendrix, 2017; Nalau & Verrall, 2021).
Addressing such limits, future research could productively explore mixes of tool types, their evolution
through time, and their impact on adaptation responses. Such research could involve process-tracing and
explanatory work on how and why policy tools are changing (Lesnikowski et al., 2020), as well as evaluative
assessment of how tool interactions influence risk and vulnerability reduction and outcomes. Additionally,
future research should document the relationship between autonomous adaptation and policy tools,
explore why capacity building can be transformational, and study policy tool use in under-documented con-
texts (e.g. Africa and Asia and in food sector adaptations). Finally, further exploring the interaction between
equity and transformational adaptation will help identify policy tools that support both goals.
Notes
1. While many ‘capacity building’ activities entail provisioning of financial support or education, these were coded as economic
instruments and information-based instruments, respectively. The ‘capacity building’ category captures capacity building
activities that were not explicitly financial or educational.
2. Autonomous adaptations are risk management strategies undertaken by individuals or organizations, without planning,
coordination, or external interventions (Fankhauser et al., 1999).
3. The health sector often has a strong government focus. Adaptations in the health sector may not be catalogued as such in the
academic literature or there may be a lack of research in the health sector (Scheelbeek et al., 2021).
4. The GAMI dataset is not explicit about the specific roles each actor played.
Acknowledgements
Thank you to Angel Castro, Ariel Daniels, Nervana Fadle, Ivan Fonseca, Janette Hernandez, Joshua Nacino, Nathan Potter, Alyssa
Schaff, and Cassandra Vo for assistance coding for policy tools.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
This work was supported by the National Science Foundation (CNH2-L-RUI-ROA award 2010014) (I. A.); Portland State University
Vision 2025 (I. A.); Social Sciences and Humanities Research Council of Canada (A. L.); Fonds de recherche de Québec- Société et
Culture (A. L.); China Scholarship Council (Y. S.); Australian National University Climate Change Institute Supplementary
Scholarship (Y. S.).
ORCID
Nicola Ulibarri http://orcid.org/0000-0001-6238-9056
Idowu Ajibade http://orcid.org/0000-0002-9767-0435
Eranga K. Galappaththi http://orcid.org/0000-0002-3926-2206
Elphin Tom Joe http://orcid.org/0000-0003-1468-6413
Alexandra Lesnikowski http://orcid.org/0000-0003-4576-2765
Katharine J. Mach http://orcid.org/0000-0002-5591-8148
Justice Issah Musah-Surugu http://orcid.org/0000-0002-3058-169X
Gabriela Nagle Alverio http://orcid.org/0000-0001-7050-3381
Alcade C. Segnon http://orcid.org/0000-0001-9751-120X
A.R. Siders http://orcid.org/0000-0001-6788-8313
Garry Sotnik http://orcid.org/0000-0002-2422-1110
14 N. ULIBARRI ET AL.
Donovan Campbell http://orcid.org/0000-0003-4511-838X
Vasiliki I. Chalastani http://orcid.org/0000-0002-1404-0682
Kripa Jagannathan http://orcid.org/0000-0003-4584-8358
Vhalinavho Khavhagali http://orcid.org/0000-0002-9553-7710
Diana Reckien http://orcid.org/0000-0002-1145-9509
Yuanyuan Shang http://orcid.org/0000-0002-8405-1352
Chandni Singh http://orcid.org/0000-0001-6842-6735
Zinta Zommers http://orcid.org/0000-0003-4755-6279
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Appendix
Table A1. Variables from the GAMI dataset.
Variable Options Description
Geography . Africa Countries assigned to geographic regions in accordance with the IPCC
. Asia assessment reports; Papers may be associated with multiple regions if they
. Australasia described adaptations in multiple locations
. Central & South America
. North America
. Europe
. Small Island States
Sector . Terrestrial & freshwater Coders selected all that apply; each had a further description in the coding book
ecosystems to provide examples for coders.
. Ocean & coastal ecosystems
. Water and sanitation
. Food, fibre, and other ecosystem
products
. Cities, settlements, and key
infrastructure
. Health, well-being, and
communities
. Poverty, livelihoods, and
sustainable development
Actors . International or multinational Coders selected all that apply.
governance institutions
. Government (national)
. Government (sub-national)
. Government (local)
. Private sector (corporations)
. Private sector (small enterprises)
. Civil society (national,
multinational, international)
. Civil society (sub-national or local)
. Individuals or households
Equity (Targeting) . Women Coders asked whether adaptation responses were designed or specifically
. Youth intended to affect any of these groups (or select none).
. Elderly
. Low-income
. Disability
. Migrants
. Indigenous
. Ethnic minorities
. Other
. None
(Continued )
CLIMATE POLICY 19
Table A1. Continued.
Variable Options Description
Hazards . Sea level rise Hazards listed based on major threats identified in IPCC assessment reports.
. Extreme precipitation and inland Coders asked to identify the threat(s) to which the adaptation description in
flooding the paper was responding/was intended to address.
. Increased frequency and intensity
of extreme heat
. Precipitation variability
. Drought
. Rising ocean temperature and
ocean acidification
. Loss of Arctic sea ice
. General climate impacts
. Other
. No information or not assessed
More information available in GAMI Protocol 3 (Lesnikowski et al., 2021).
Table A2. Transformation potential coding.
Depth Depth relates to the degree to which change reflects something new, novel, and different from existing norms or practices.
High High depth (in-depth) change is more transformational: it might involve radically changing practices by altering frames, values,
logics, and assumptions underlying the system. This might involve deep structural reform, complete change in mindset, radical
shifts in perceptions or values, and changing institutional or behavioural norms. Adaptation actions are increasingly radical (depth
of change), including altering of values, re-framing of problems, and dramatic changes in practices.
Medium Medium (moderate) depth describes incremental changes: a shift away from existing practices, norms, or structures, but only to a
limited degree. Perspectives, values, and practices are changing to involve novel or more radical approaches (depth of change).
Changes in risk perception may be medium depth.
Low Low (limited) depth follows business-as-usual practices, with no real difference in underlying values, assumptions, or norms. This
includes practices that are largely expansions of existing practices. Adaptations largely are incremental by expanding existing
practices, with limited evidence of novel change beyond business-as-usual practices (depth of change).
Scope Scope refers to the scale of change – geographic or institutional.
High High (broad, large) scope refers to large-scale and system-wide changes that involve an entire organization, a country or large
region, and large populations. Broad scope efforts may be multi-dimensional, multi-component, and/or multi-level. Development
of networks, inter-organizational coordination are more likely to lead to changes of broad scope. Adaptation is implemented at or
very near its full potential across multiple dimensions. Adaptations are widespread and substantial, including most of the possible
sectors, levels of governance, actors (e.g. nationally implemented legislation or policy), or reflect widespread changes in
behaviour (scope of change). For example, this may include numerous cities or national-level changes, or institution-wide change.
It may also address shifts in underlying norms and behaviours across entire populations.
Medium Medium scope could describe multiple communities or households acting without coordination, a single sector taking action, or a
small regional action. Adaptation is expanding and increasingly coordinated. There are growing efforts that exceed business-as-
usual practices and challenge the fundamental attributes of the social-ecological system. There is some expansion and/or
mainstreaming of change (scope of change) to include a wider region, or involvement of coordinated, multi-dimensional, multi-
level adaptation.
Low Low (small) scope might refer to local initiatives, activities taken by individuals or households. Adaptation is largely localized. There
are primarily disjointed adaptation initiatives, with limited evidence of coordination or mainstreaming across sectors, jurisdictions,
or levels of governance (scope of change). This could be a single city or government department.
Speed Speed of change refers to the dimension of time within which changes are happening.
High High (fast) speed adaptation actions are either (a) those described as being fast for their type of action (e.g. building a bridge in a
year might still be considered fast) or (b) those that can take place and see results within 1–3 years.
Medium Medium (moderate) speed adaptations are those that occur or see results over 3–5 years. Adaptations are increasingly exceeding
business-as-usual behavioural or institutional change to reflect accelerated adaptive responses (speed of change).
Low Low (slow) speed adaptations are those that take 5 years or more to be executed or to see results. Adaptations are largely slow,
consistent with existing behavioural or institutional change, and limited evidence of accelerated adaptive response (speed of
change). Change is evident, but not rapid.
Table A3. Total papers in dataset by region and sector.
Terrestrial Ocean Water Food Cities Health Poverty All sectors
Africa 42 16 42 375 24 113 321 492
Asia 55 44 76 376 56 167 252 524
Central & South America 9 4 12 48 10 11 26 69
Europe 14 13 30 30 47 31 3 116
(Continued )
20 N. ULIBARRI ET AL.
Table A3. Continued.
Terrestrial Ocean Water Food Cities Health Poverty All sectors
North America 40 29 27 80 42 69 45 175
Oceania 7 24 14 26 8 41 24 81
Small Island States 7 22 12 19 7 26 16 43
Multiple Continents 20 14 20 37 26 39 29 87
All Continents 187 145 222 972 215 472 700 1549
Note: A single paper may be listed in multiple sectors. Small Island States papers are double counted with other regions. Poverty: Poverty liveli-
hoods & sustainable development; Health: Health, well-being & communities; Cities: Cities settlements & key infrastructure; Food: Food fibre &
other ecosystem products; Water: Water & sanitation; Ocean: Ocean & coastal ecosystems; Terrestrial: Terrestrial & freshwater ecosystems.
Figure A1. Phi correlations between presence or absence of tool types. Analysis uses the subset of papers that described at least one tool type,
to remove spurious (0,0) data points.