Methods and Global Environmental Governance · Environmental Governance Kate O’Neill,1 Erika Weinthal,2 Kimberly R. Marion Suiseeya,2 Steven Bernstein,3 Avery Cohn,4 Michael W

EG38CH17-ONeill ARI 20 September 2013 14:27

Methods and GlobalEnvironmental GovernanceKate O’Neill,1 Erika Weinthal,2Kimberly R. Marion Suiseeya,2 Steven Bernstein,3Avery Cohn,4 Michael W. Stone,5and Benjamin Cashore5

1Department of Environmental Science, Policy, and Management, University of Californiaat Berkeley, California 94720; email: [email protected] School of the Environment, Duke University, Durham, North Carolina 27708;email: [email protected], [email protected] of Political Science, University of Toronto, Toronto, Canada M5S 3G3;email: [email protected] Center for Atmospheric Research, Boulder, Colorado 80385;email: [email protected] of Forestry and Environmental Studies, Yale University, New Haven, Connecticut,06511; email: [email protected], [email protected]

Annu. Rev. Environ. Resour. 2013. 38:441–71

First published online as a Review in Advance onAugust 5, 2013

The Annual Review of Environment and Resources isonline at http://environ.annualreviews.org

This article’s doi:10.1146/annurev-environ-072811-114530

Copyright c⃝ 2013 by Annual Reviews.All rights reserved

Keywordsglobal environmental governance, problem-focused research,complexity, scale, linkages, methodological pluralism, collaboration

AbstractThis review analyzes the methods being used and developed in globalenvironmental governance (GEG), an applied field that employs in-sights and tools from a variety of disciplines both to understand press-ing environmental problems and to determine how to address themcollectively. We find that methods are often underspecified in GEGresearch. We undertake a critical review of data collection and analysisin three categories: qualitative, quantitative, and modeling and scenariobuilding. We include examples and references from recent studies toshow when and how best to utilize these different methods to con-duct problem-driven research. GEG problems are often characterizedby institutional and issue complexity, linkages, and multiscalarity thatpose challenges for many conventional methodological approaches. Asa result, given the large methodological toolbox available to applied re-searchers, we recommend they adopt a reflective, pluralist, and oftencollaborative approach when choosing methods appropriate to thesechallenges.

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Contents1. INTRODUCTION . . . . . . . . . . . . . . . . 4422. GLOBAL ENVIRONMENTAL

GOVERNANCESCHOLARSHIP . . . . . . . . . . . . . . . . . . 443

3. FOUR CHALLENGES . . . . . . . . . . . . 4444. METHODOLOGICAL CHOICES

FACING CONTEMPORARYGLOBAL ENVIRONMENTALGOVERNANCE: A CRITICALREVIEW . . . . . . . . . . . . . . . . . . . . . . . . . 4474.1. Qualitative Methods . . . . . . . . . . . 4474.2. Quantitative Methods . . . . . . . . . . 4534.3. Modeling and Scenarios . . . . . . . . 458

5. STRATEGIES FORPROBLEM-DRIVEN GLOBALENVIRONMENTALGOVERNANCE RESEARCH . . . . 4615.1. Multiple Methods. . . . . . . . . . . . . . 4625.2. Collaboration. . . . . . . . . . . . . . . . . . 463

6. CONCLUSION . . . . . . . . . . . . . . . . . . . 463

1. INTRODUCTIONScholars of global environmental governance(GEG) are motivated not only to understandand explain the forms, functioning, effec-tiveness, and underlying dynamics of globalgovernance, but also to apply insights fromtheir findings to address complex and pressingenvironmental challenges (1). These goalsdemand approaches that tackle, rather thanbypass, major research challenges. Movingtargets, complexity, and incomplete informa-tion make it difficult to adjudicate betweencompeting alternatives for explaining GEGand, by extension, the policy prescriptions thatflow from such research to address global envi-ronmental problems. What then, are the mostappropriate ways to design and conduct rigor-ous problem-focused research in GEG? Whatmethods are available and most useful? Whatpitfalls must GEG scholars collectively avoid?Although other social science researchers facesimilar challenges, and thus our arguments

may apply more broadly, this review draws onand speaks most directly to GEG scholarship.

Our central argument is for problem-drivenresearch that confronts, rather than assumesaway the challenges of researching global envi-ronmental politics and governance. Althoughthree decades of GEG research have producedsophisticated analyses of global environmentalproblems, we also detect a tendency for re-searchers to choose methods based on their owntheoretical preferences or training. Althougha variety of methods may be fruitfully appliedto understand particular aspects of the sameenvironmental problems, some methods canbetter address certain questions and researchchallenges. Thus, methodological choicesshould be adopted and justified on the basisof their utility to explain and understand thequestions that motivate our research—usuallyto address an environmental problem—ratherthan choosing methods first and then selectingresearch questions those methods can address.

How, then, might GEG scholars developresearch designs that avoid being driven bymethodological predispositions? We answerthis question in four related steps. First, weidentify the study of GEG as a problem-drivenfield with roots in political science and interna-tional relations (IR) theory relevant for improv-ing global governance of the environment or,at the very least, our understanding of GEG.Second, we identify four research design andmethodological challenges confronting GEGresearch. Third, we review strengths and weak-ness of prevailing methodological approaches,techniques, and innovations within qualitativeand quantitative methods as well as within a rel-atively new methodological approach to GEGscholarship: modeling and scenario building(MSB), which has developed distinct quanti-tative and qualitative approaches. We draw onexamples from our own and others’ research toilluminate these challenges. Fourth, we discussstrategies for choosing methods to carry outproblem-focused GEG research, including thepotential of multiple methods and collaborativeresearch. We argue for greater methodologicalpluralism as a starting point and for research

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problem-methodology coherence as the goal.Thus, we urge GEG researchers to undertake areflective approach to research design in whichthey frame and make methodological choicesthat fit with the question(s) they ask. Scholarstrained in one tradition should learn to stepoutside their methodological comfort zoneto learn or appreciate other techniques, orthey should work with others on collaborativeprojects that get at a central question fromdifferent methodological directions.

This openness is especially important, asmany GEG researchers contribute to twosometimes countervailing academic commu-nities: (a) specific disciplinary fields such as(but not restricted to) political science andits subdisciplines of IR, political economy,and comparative politics; and (b) problem-focused interdisciplinary environmental studiesprograms that include public policy, admin-istration, and management. We also have inmind the needs of a new generation of GEGscholars, who often want, and are expected, todraw on a wider range of tools and methods toaddress complex, multiscalar problems.

2. GLOBAL ENVIRONMENTALGOVERNANCE SCHOLARSHIPGEG scholarship can trace its origins primarilyto those scholars within IR who created thesubdiscipline of international environmentalpolitics (IEP) (2, 3) (see the sidebar Approachesto Global Environmental Governance).Largely situated within the overarching frame-work of regime theory (4), IEP researchershave addressed questions of why and how statescame to cooperate over environmental prob-lems as well as what explained the negotiatingoutcomes that emerged in the form of environ-mental institutions (e.g., 5, 6). IEP scholarshiphas made important contributions to IRtheory, notably regarding the role of sciencein international politics (e.g., 7), North-Southpolitics (8), and the impacts and effectivenessof international environmental cooperation(for example, 9–11). Despite its initial focuson intergovernmental cooperation, this worksupplied insights into the influence of nonstate

APPROACHES TO GLOBAL ENVIRONMENTALGOVERNANCE

Global environmental governance (GEG) is a field that includesthe institutions, processes, initiatives, actors, and organizationsthat shape environmental actions and outcomes in the globalrealm. Although GEG is studied from several disciplinary per-spectives in the social sciences, we start by focusing on GEGresearch that has emanated from scholarship on global environ-mental politics, which, in turn, has its origins in the political sci-ence discipline of international relations. As the study of globalenvironmental politics matured, the questions it asks and theo-retical approaches it applies have, however, increased its connec-tions to other disciplines that study GEG, including geography,sustainability science, and sociology.

actors, including activists and corporate-sectoractors, on international negotiations andregime outcomes (e.g., 12, 13).

Later, comparative politics and policy schol-ars drew attention to the important influ-ence of international actors and ideas on do-mestic environmental policies, and vice versa,across different countries and regions (14–17).These insights also generated work on transna-tional environmental politics, including advo-cacy networks and governance arrangementsthat form networks across boundaries (e.g., 18–21). Scholars of the political economy of GEGhave also had a major impact on the field. By fo-cusing on the challenges of governing environ-mental problems driven by the globalization ofproduction and consumption chains or the mar-ketization of environmental governance (e.g.,22–24), they highlight the importance of theglobal economy and economic inequality. Oth-ers demonstrate how structures of power andauthority in the international system or particu-lar discourses define or delimit particular formsof governance (e.g., 22, 25, 26).

GEG scholarship is both theoreticallyinformed and diverse, and the range of GEGscholars goes beyond the more narrowlybounded IEP field. It includes “applied”research that aims to help ameliorate envi-ronmental problems, but it does this best

www.annualreviews.org • Global Environmental Governance 443

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when expanding knowledge about the politicssurrounding problems and their solutionsby translating the politics and practices ofenvironmental policy across multiple scales.Accordingly, the study of global environmentalproblems and politics is an interdisciplinary andcollaborative field, drawing from multiple andvaried theoretical frameworks and epistemolo-gies to explain environmental policy outcomesto both scholarly and policy communities.

Despite its growth, however, this field hasproduced very few methodological overviews(for exceptions, see 27–29), especially ones thatgo beyond the basic tools and methods of IRtheory. Likewise, although some reviews dis-cuss recent innovations in GEG theory (e.g.,30), few of these provide in-depth discussionof methods. Unfortunately, many research ar-ticles, especially those that have a qualitativeperspective, do not include methods sections,perhaps owing to article length constraints, anomission that gives other scholars fewer exam-ples from which to work.

To get a sense of how or whether scholarsare referring to their methods in peer-reviewedarticles, we turned to Global EnvironmentalPolitics (GEP)—the leading journal most

directly associated with GEG research. Ac-cording to the 2012 Thomson Reuters ISIJournal Citation Reports, GEP ranked thirdin political science and tenth in environmentalstudies. We focused on GEP because of itspolitical science origins and for manageability(we encourage similar exercises using otherjournals in the field). Our review of the 298forum/commentary and research articlespublished since its first issue in 2001 foundonly 7 out of 65 forum/commentary articles(or 11%) and 96 out of 233 research articles (or41%) included a discussion of, and justificationfor, the methodological techniques employed.Only three articles were explicitly devotedto the topic of methods (Figure 1) (31–33).Nonetheless, we found an increase over timein the number of articles discussing methods.

3. FOUR CHALLENGESOur review addresses four challenges facingproblem-relevant GEG scholarship: complex-ity and uncertainty, vertical linkages acrossmultiple scales, horizontal linkages across issueareas, and (often rapidly) evolving problem setsand institutional initiatives. These challenges

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Figure 1Survey of methods discussions in Global Environmental Politics, 2001–2012. Abbreviation: RA, research article.


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are not unique to GEG; they also apply to otherareas of applied research. However, we draw onparticular examples from and challenges posedby the GEG arena in what follows.

First, some of the most profound changesin human behavior and notions of appropriateor legitimate governance are unpredictable.Studying environmental governance and pol-icy from a social science perspective requiresattention be paid to the dynamics, power,and authority relations underlying formal andinformal governance systems and initiatives aswell as their origins, (often nonlinear) trajec-tories, and impacts. This unpredictability, asconstructivists (34), organizational sociologists(35), and institutional theorists (36) haveelaborated, necessitates that research methodsbalance a quest for precision and predictability(the goals of deductive nomothetic theory)with the need to recognize messy contingencyand to study path dependencies and ruptures(37).

GEG scholars have often highlighted thescientific complexity and uncertainty inherentin environmental problems, such as climatechange, in their research as an additional bar-rier to fostering environmental governance andcooperation (38, 39). In terms of GEG, uncer-tainty as a methodological problem exists forlooking both forward (assessing future direc-tions and impacts) and backward (assessing howevents/behavior would have unfolded in the ab-sence of the institution). These problems areespecially acute for GEG. As Levin et al. (37)elaborate,

[W]hile the political system may mediateinterest group interactions regarding climatechange policy in similar ways as it doesregarding universal health care, the naturalenvironment has its own response that stake-holders and governments cannot wish away.Indeed, the powerful image of “compromise”that shapes most public policy processes doesnot fit. Human beings can, of course, controltheir behavior to alter their impacts, but theycannot control the response of the naturalsystem once a decision is made. (37, p. 127)

Lemos & Agrawal (40), moreover, have rec-ognized complexity as a characteristic of newenvironmental governance, which they link tothe challenges of multiscalarity and linkages.Nelson et al. (41) use the notion of complexsystems and environmental change as a founda-tion for understanding adaptive governance andresilience. Complex and unpredictable prob-lems, as we discuss below, necessitate diversemethods including historical process tracingand scenario development. Years of researchon the politics of climate change have revealedthe need to develop methodological approachesand models that adapt over time and space as aresult of the feedbacks and underlying complex-ities of the problems at hand, precisely becausehistorical norms and explanations for past be-havior may change and, hence, not serve as aguide to future norms and behaviors. Althoughrecognition of this frustrates most social scienceresearchers and may help explain the largelybackward-looking focus in our analysis of thingsthat have already happened, we also note a po-tential positive feature of an unpredictable fu-ture: As most GEG scholars agree, profoundnormative and behavioral changes must occurto address exceedingly intractable problems.The trick is to apply methods that can helpus understand the causal mechanisms throughwhich such processes may be initiated.

Second, multiple levels of governance are al-ways at play. Like scholars who study the inter-face of human-ecological systems (42), scholarsof GEG confront the challenge that governanceinstitutions operate at different levels of scale—physically, temporally, and across different ac-tors (e.g., see 30, 43). In addition, scholars oflocal institutions posit that institutional anal-ysis must take place not only at different lev-els of scale, but also across different fields ofaction (e.g., 44–46). The issues we choose tostudy pose significant challenges for individu-als, firms, communities, nation-states, and theworld as a whole. GEG researchers must assessand understand how choices made at one levelaffect and influence interactions and choicesacross and within many governance arenas thatoften lack formal rules and interrelationships


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(30). Because there are only a few attempts fromwhich to draw lessons regarding the study oflocal institutions for managing the global com-mons (47), understanding these multiple lev-els requires that particular attention be paid tothe development of appropriate methodolog-ical tools to introduce new actors into a fieldthat has traditionally focused almost entirely onglobal and domestic-international interactions.

As has been asserted for GEG scholarship,interactions across levels can lead to unintendedconsequences including complex interactionsranging from global supply and consumptionchains where apparent advances merely displacepollution or waste elsewhere (e.g., 48). Like-wise, different types of knowledge, ideas, andinitiatives move across political levels, creatingcomplex interaction effects (e.g., 49). This shifttoward an increasingly explicit study of scaleand the movement of actors, ideas, and knowl-edge up, down, and across scales has requiredGEG scholars to look for new tools to makethese phenomena visible. Such tools must thenbe incorporated into GEG research. Accord-ingly, insights from geography, anthropology,and other fields for which scale has long beena central concern have had to be incorporated,even though findings from these fields have notalways scaled up to global governance institu-tions and/or addressed the global nature of theissue in question.

Third, the horizontal interplay betweengovernance regimes, which often overlap onissue areas or governance functions, must beaddressed. Linkages occur across issue areasand regimes, for example, across climate anddeforestation regimes via a program aimingto reduce emissions from deforestation andforest degradation that also includes con-servation and sustainable management offorests (REDD+). Moreover, the deepeninginstitutionalization of international trade andthe relationship between the World TradeOrganization and environmental regimeshave given new salience to trade-environmentlinkages. These developments have generateda literature on the mitigation of regime conflictand the opportunities for creating synergy

across regimes, in particular, how these aremanaged and by whom (50, 51). Untanglingthese linkages across governance regimesposes significant challenges for researchers interms of understanding how they work, whichway influence runs, and how (or whether) aninterconnected set of regimes can add up tomore than the sum of its parts. The work weexamine below has focused attention on actors,such as treaty secretariats (52), and policydiffusion across regimes (53, 54). It is nearly,but not all, qualitative in nature, often in-volves triangulating methods, and may requiremultisited work on the part of the researcher.

Fourth, at its core, environmental gover-nance research concerns the study of gover-nance institutions that continue to evolve. Thisdirectly contravenes the conventional wisdomin public policy research (e.g., 55) that scholarscan gain insights only for policy that has beenin place for more than 20 years. Despite rec-ognizing the need to look forward, the litera-ture on how to think about, and research, evolu-tionary processes is relatively limited. Arguably,the most relevant analysis is on scenario build-ing, which, as discussed below, has developed aliterature applying quantitative and qualitativetechniques. However, even this literature tendsto sidestep key challenges—namely, that normsand preferences can, and do, change.

One way researchers have tackled thisproblem has been by identifying pathways thathave “plausible logics” for evolving in ways thatbuild GEG (e.g., 56). Such analysis starts withthe understanding that environmental policyinitiatives may change behavior and moves onto examine how and under what conditions theymay actually shape the preferences of partici-pating actors and systemic norms. For example,in the case of global coalitions working toaddress illegal logging by tracking legally pro-duced forest products, Cashore & Stone (56)posit that a two-step “evolution” and “interac-tion” process may be triggered. First, trackingsystems may evolve so they become entrenchedwhile expanding the number of actors involvedin the supply chain supporting this approach.Second, as a result, higher standard certification


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programs may be able to work more efficientlydespite their current struggles associatedwith the difficulty in tracking certified forestproducts. Cashore & Stone (56) argue that thispotential evolution and interaction can neverfit within the realm of a predictive model.Their approach illustrates the importance ofimagining futures that have “some plausiblelogic” and of using GEG scholarship to helptranslate this knowledge to forward-lookingstrategic interventions capable of creating“sticky” institutions.

Recognizing that we are always on an evolu-tionary trajectory means that research designsand methods that focus solely on generalizablepatterns of the past, even leaving aside the rangeof assumptions that must hold for that knowl-edge to apply in the present, has limited util-ity in building practical knowledge or analysisthat takes account of nonlinearities, feedbackeffects, and learning. Traditional GEG theory,still circumscribed by its ontological focus onthe nation-state system and international diplo-macy, has been slow to develop the tools andanalytical skills to address new and evolving in-stitutions, such as carbon markets or REDD+(57). As a result, less attention has been paidto questions of power, legitimacy, and author-ity that characterize GEG dynamics (for ex-ceptions, see 22, 58) and an overemphasis oneconomists’ analyses of the impacts of theseinitiatives.

Arguably, the methodological challengesfacing GEG scholars are an important rea-son for this gap. Below, we cite other exam-ples ranging from multisited analysis of fish-eries overexploitation to the complexities ofinteractions at global summits that illustratethese challenges. Likewise, GEG scholarshiphas spent little effort attempting to articulate acoherent approach regarding which methods toemploy or when to employ them. Even articlesand books that are explicit about methods lack acoherent approach to a broad suite of methodsor, indeed, an effort to identify or contributeto a new methodological/theoretical “canon”from which research questions can be drawn.For example, although the edited volume by

Sprinz & Wolinsky-Nahmias (59) on methodsprovides a comprehensive survey of the appli-cation of quantitative and formal methods tothe study of international environmental pol-icy, its focus remains restricted to traditional IRframeworks. The next section seeks to expandthis canon.

4. METHODOLOGICAL CHOICESFACING CONTEMPORARYGLOBAL ENVIRONMENTALGOVERNANCE: A CRITICALREVIEWThis section reviews existing and new method-ological approaches in GEG, particularly asthey have evolved over time. Here, we focuson three primary categories, or “families,” ofmethods: quantitative, qualitative, and MSB.For each section, we review how methodswithin each category have been used over time,some of their strengths, and some of their limi-tations in meeting the four challenges posed bythe contemporary GEG issues outlined above.Many of the methods we discuss here have longbeen applied by scholarly communities, includ-ing GEG, but some are new to GEG research.We see this trend related to the growth in thebreadth of the field in terms of problems and in-stitutions that have emerged or are recognizedas important for GEG scholarship. We also seemore researchers, especially graduate students,entering the field with interdisciplinary train-ing and perspectives. Finally, because we areinterested here in applied or problem-solvingGEG research, alternatives must be exploredand existing approaches must be adapted to getat complex, linked, and rapidly changing ques-tions and problems.

4.1. Qualitative MethodsQualitative methods have great potential formeeting the four challenges we identify in thisarticle (see sidebar Qualitative and QuantitativeMethods in the Social Sciences). Recent qual-itative studies have taken up these challenges,utilizing innovative methods, ranging from


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QUALITATIVE AND QUANTITATIVEMETHODS IN THE SOCIAL SCIENCES

In the social sciences, qualitative methods generally focus on ex-plaining outcomes, making causal inferences, identifying causalmechanisms, or identifying historical processes within a singleor small set of cases. Commonly used techniques include struc-tured, focused comparisons of cases, typological theory, processtracing, congruence testing, and counterfactual analysis. Qualita-tive methods may include interpretive approaches to understandsocial and political phenomena or cases through techniques suchas discourse analysis, ethnography, or hermeneutics. Quantita-tive methods include a range of mathematically based methodsthat generally employ statistical techniques to map simple andcomplex relationships, assess correlations, and/or make descrip-tive and causal inferences by analyzing large sets of data. Specifictechniques range from network analysis to inferential statisti-cal techniques. This category may also include mathematical orformal modeling. Although there is some debate in the litera-ture over whether both quantitative and qualitative methods areessentially concerned with techniques to make descriptive andcausal inferences or whether different epistemological or onto-logical assumptions underpin them, in this review we adhere tothe line of reasoning that quantitative and qualitative data andmethods provide both synergistic and countervailing epistemo-logical assumptions.

multisite research to large-scale collaborativedata gathering and analysis projects, therebybuilding on the existing body of qualitative,case-based research in the GEG field. Asdescribed below, GEG researchers have drawnon methods used in other social science andhumanities disciplines, including collaborativeethnographic methods. We find that the reper-toire of objects of study and questions haveevolved to encompass the four challenges andthat data collection techniques have expanded.Scholars still rely on long-established modesof data analysis, but more often, they are com-bining methods of data collection and analysisinto forms of triangulation that are applied indifferent ways to new sets of cases. These cases,which include commodity chains and cross-scale institutions, have not traditionally beenpart of mainstream GEG inquiry. In terms

of developing methods to extrapolate into anuncertain environmental future, the momen-tum resides with new approaches (qualitativeas well as quantitative) that allow for scenariobuilding. Therefore, we also discuss someof the limitations of qualitative approaches,even given recent innovations. Debates overthe distinction between qualitative and quan-titative methods continue (see also 60–62).This section and Section 4.2 demonstratesome common concerns as well as differencesbetween qualitative and quantitative methods.

4.1.1. Fewer cases, more dilemmas. Casestudies form the bulk of qualitative methods–based research. They are particularly useful forgenerating hypotheses, identifying key vari-ables, building theories, and “achieving highconstruct validity” (63, p. 34), because they al-low researchers to tease out causal mechanisms,often through process tracing, structured, fo-cused comparison, and/or counterfactual anal-ysis. During the first few decades of researchon global environmental regimes, scholarsfrequently selected a particular regime andmeticulously traced out the linkages between“possible causes and observed outcomes”—thatis, using process tracing (64)—to identify thecausal mechanisms at each critical stage toexplain the emergence and, sometimes, theevolution of the regime. Analyses took the formeither of individual case studies (7, 65) or of datacollected in edited volumes to enable cross-casecomparison (e.g., 5, 66) to examine primarilythe negotiation, impacts, and effectiveness ofinternational environmental regimes.

Frequently employed in single case studies,counterfactual analysis (or the construction of“thought experiments”) has enabled scholars toevaluate multiple causal variables (67). Coun-terfactual analysis has been deployed in quali-tative studies to assess whether an environmen-tal problem such as acid rain in Europe wouldhave been worse off without an institution (68).Such analysis also explores why some alterna-tive pathways of institutional development (e.g.,ecodevelopment) failed, whereas others (e.g.,sustainable development) succeeded (69).


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The utilization of structured focused com-parison further enabled researchers to analyzethe same set of questions and variables acrosscases (64). Several of these studies allowed forcross-scale and cross-national comparisonstoo. Examples include work by O’Neill (16)on hazardous waste trading, Weinthal (15) ondomestic sources of international cooperationin Central Asia, and Cashore et al. (70) onforest certification. In many cases, a team ofresearchers worked under a unified frameworkto draw out causal inferences from a largernumber of cases than could have been coveredby an individual researcher (e.g., 5, 9, 66). Forexample, the contributors to Weiss & Jacobson(9) applied common sets of factors to demon-strate what shaped compliance across fiveregimes and nine countries and blocs, whereasthe authors in Young (66) applied six behavioralpathways through which regimes exert impactsto three case studies. These benefits of collab-oration are echoed in some of the emergingqualitative methods we examine below.

Like their IR counterparts, GEG re-searchers have also begun to deal with small-Nproblems, long cited as a major drawback tounderstanding generalizable causal conditions(60), through the construction of what couldbe called “medium-N” analysis. One suchmethod, fuzzy-set qualitative comparativeanalysis (fsQCA), aims to identify complexcausal patterns by specifying potential combi-nations of drivers of change and then groupingcases accordingly (71). The approach drawson the in-depth knowledge the researcher hason each case to identify potential independentand dependent variables that may interactto produce an effect. Rather than separatingout independent variables to understand theireffects, fsQCA, often as part of a broader suiteof methods, allows researchers to examine howcombinations of variables work together toproduce an effect (72–74). The strength of theapproach rests in its ability to identify multiplecomplex causal mechanisms, which can belost in more standard quantitative techniques,and to produce generalizable explanationswithout sacrificing either the richness of case

studies or the elegance of parsimonious causalexplanations.

Although fsQCA can be a useful tool to studyGEG, there are some limitations to its use.In particular, because it relies on an intimateknowledge of the cases to calibrate membershipin a group, its use for very large-N studies is cir-cumscribed. As always, with new approaches inthe social sciences, careful attention must alsobe paid to establishing “best practices” for em-ploying fsQCA (75).

4.1.2. Expanding the qualitative repertoire:data, analysis, and cases. Over the pastdecade, GEG researchers have sought to in-tegrate or adapt additional methodological ap-proaches into the suite of qualitative methodsand research design. These approaches are of-ten more adept at capturing complexity, link-ages, and scale in contemporary GEG that char-acterize, for example, the interactions acrossdifferent issue areas, or mapping the networksof diverse actors that characterize global andtransnational policy arenas. Moreover, individ-ual researchers and teams of researchers nowhave access to more and better data sources andtechniques for data collection and sharing andto innovations in data analysis. Nevertheless,many studies continue to use the traditionaltools of process tracing and structured, focusedcomparison, including interviews and archivalresearch.

To address the complexity that character-izes contemporary GEG, researchers requirelarger data sets. Under the rubric of qualita-tive methods, methods and tools for data col-lection and analysis include collaborative eventethnography (CEE), participatory action re-search (PAR), and survey methods, some ofwhich require researchers, particularly from IRbackgrounds, to learn techniques not alwaystaught in disciplinary programs. Whereas priorcollaborative studies often consisted of editedvolumes, a new generation of scholars is en-gaging in more direct collaboration in terms ofdata collection and analysis. These scholars arealso working on multiple sites across and within


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scales. We chart the highlights of these devel-opments below.

4.1.2.1. Observing mega events: new tools foranalyzing complexity. New data collectiontechniques, subsequently used for analysis byteams of researchers, have emerged as toolsfor studying international negotiations ascomplex, linked, and cross-scale processes andevents. CEE is one such method that holdspotential for tackling problems pertaining toGEG across multiple governance spheres.CEE combines “rapid or time constrainedethnographic assessment. . .with institutionaland organizational ethnography” (76, p. 248) tocapture interactions and dynamics among net-works of actors at large international meetings;ultimately, CEE may be used to gather datathat can be accessed by a variety of actors. CEEresearch teams have attended various GEG“mega events,” including the 2008 WorldConservation Congress in Barcelona, the 2010Nagoya Conference of the Parties (COP)of the Convention on Biological Diversity,and the Rio+20 Summit in 2012, where theyhave studied actors inside and outside thenegotiating halls.

CEE rests on the assumption that GEG isnot simply a function of the interplay amongstate actors in a negotiation room and is bestsuited to scholars tracking the emergence ofideas around particular themes or topics, suchas the establishment of conservation targets, de-cisions on forest management, or how particu-lar principles or norms are embedded withindecision-making processes. However, it wouldbe very difficult for individual researchers totackle mega events in a way that illuminatesthe complex relationships among actors or thehorizontal and vertical linkages between insti-tutions and that captures the role of knowledgeand power in determining institutional out-comes. At a global event such as the COP, thereare hundreds of events including official ne-gotiations, working groups, chair groups, sideevents, media sessions, demonstrations, postersessions, and public information expos—all ofwhich contribute to shaping the agenda at the

COP. Through collaborative approaches fordata collection such as CEE as a research tech-nique (e.g., see 77, 78), researchers gain broaderanalytical insights into governance processes byblending the specialized contextual knowledgethat each individual researcher holds with thebroad data set gathered at the global event.

For example, Marion Suiseeya (79) studiesthe role of justice norms in the institutional dy-namics of global forest governance. Throughcollaboration as part of the CEE, Marion Su-iseeya was able to examine the evolution of theforest justice discourse at the Convention onBiological Diversity by mapping out who waspresent at particular events, their articulationsof justice and claims of injustice, and how theseshifted or changed depending on the condi-tions and substance of the event. CEE allows re-searchers to gather a broad data set that illumi-nates the diversity of and relationships betweenactors involved in GEG and includes how issuesare linked (76). It enables researchers to investi-gate important political moments in which ac-tors that are generally dispersed but working onthe same agenda interact in direct proximity toeach other.

Although the findings from these exampleswould not have been possible without CEE,there are some potential weaknesses or pitfallsto using CEE. First, research findings may bemainly descriptive, missing the opportunityfor more in-depth analysis on potential causalmechanisms or pathways. Scholars using CEEneed to be explicit regarding their methodsof data analysis and question construction aswell as what they are gaining from the use ofCEE. They should also clearly define theirhypothesized mechanisms that explain thephenomena they are examining. Otherwise,it may be hard to separate signal from noiseover short meeting time frames. Second, somegeneral concerns about the collection and useof CEE data revolve around the completenessor generalizability of data gathered on-site bythe particular team in place. These concernsraise comparisons with other leading datasources on environmental negotiations andmeetings, such as the highly regarded daily and


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weekly reports compiled and written by theEarth Negotiations Bulletin team at hundreds ofmeetings since 1992 and made available online(80). However, the emergence of multipledatabases from COPs of different regimeprocesses is likely to allow for better replica-tion and/or confirmation of data. Likewise,the Leverhulme Trust–sponsored networkon transnational climate change governanceincludes many political scientists, all workingfrom a common database jointly developed ontransnational climate initiatives (81).

4.1.2.2. Linkages across and within scales:multisited research. Recent qualitative GEGresearch focuses on the complexities of entiregovernance systems that operate at multiplelevels with multiple actors who straddle or cross“traditional” regime borders. This researchalso focuses, for example, on the flows of ideasand knowledge, policies, actors, and commodi-ties across scales. The associated literaturehas introduced the concept and method ofcommodity chain analysis to GEG scholarship(82–84), employing concepts of scale, linkages,or networks that draw from geography, sociol-ogy, and anthropology (e.g., 85). Researchersin this tradition have embraced multisitedresearch as a way to address “questions ofscale and the processes of globalization” (86,p. 262) that are critical to understanding andaddressing global environmental challenges.

One type of multisite research focuseson capturing the regulatory and productionprocesses that shape a single commoditysector—such as tuna, timber, or green beans—and the environmental relations associated withit (87–89). For example, to anchor their study,Havice & Campling (87; for more explication,see 90) place scalar concerns at the forefront oftheir analysis of the global political economyof tuna fisheries in the Western Pacific Ocean.They argue that most scholarship on the tunaindustry identifies environmental failures asemanating solely from “weak governance” atthe state level; thus, it ignores the context inwhich states operate (87). By contrast, theyhighlight that transnational (state and private),

institutional, ecological, historical, geographic,and economic variation as well as the interac-tions among actors across scales are critical tounderstand environment and resource-relateddevelopment trends in the tuna industry. Forthese reasons, problem-focused researcherswho examine issues that cut across scalesare increasingly identifying multiple levelsof governance that are situated within thesystems of states, in the private sector, andin state-firm relations. These researchers alsooften incorporate multiple methods consistentwith the causal pathways they seek to uncover.By collecting multiple data types (such asinterview data, survey data, and quantitativetrade or environmental data) and using dataanalysis methods such as comparative his-torical institutional analysis, they provide aclear explication of the vertical relationshipsbetween institutions, economics, states, andindustries that create environmental—andpolitical-economic—trends. They also offersites to address various challenges.

To employ qualitative methods for mul-tisited GEG research, investigators mustmanage complex methodological tasks inwhich they must often undertake fieldwork inmultiple geographic sites. They also need topay close attention to mapping the connectionsbetween the sites and to choosing betweensurvey and sampling techniques, longitudinalresearch, archival research, multiple methods,and multisited ethnographies. In her study ofkhat in Madagascar and its relationship to de-forestation, Gezon (86) discusses a number ofthe theoretical and methodological concerns ofmultisited research. She looks at the productionof khat through a commodity chain frame-work, investigating the links between economicprocesses of production, distribution, and con-sumption. Recognizing that these intercon-nected processes occur in “multiple geograph-ically dispersed locations, involving many dif-ferent actors” (86, p. 238), Gezon demonstrateshow an investigator could undertake research inmultiple locations by using purposive sampling,interviews, and questionnaires. Accordingly,she explores the ways geographically dispersed


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variables affect each other and environmentaloutcomes.

PAR is based on a long multidisciplinarytradition of community-based research andaction pioneered in the fields of internationaldevelopment and critical pedagogy (e.g., 91).As such, it has enabled researchers to focus onthe connective tissue between global commod-ity chains and local livelihoods. Specifically,PAR methods bring together researchersand communities seeking to improve theirlivelihoods or achieve particular goals (92, 93).

Although scholars initially applied PAR tovery local levels, researchers have become adeptat using this technique to capture the complexi-ties of nonstate actors and social movements op-erating at a global level. PAR researchers have,for example, demonstrated how to study the im-pact climate justice organizations have both onclimate activism and within the broader sphereof negotiations (94). In contrast to CEE, PARdoes not take a particular mega event as a start-ing point. Instead, it has focused more on a spe-cific group of actors in one arena or across sev-eral action arenas.

The deliberate blurring of traditionalboundaries between scholars and subjects isboth a strength and potential pitfall of PAR,especially when considering the ethics of work-ing with marginalized populations, which in-clude radical activists at global summits. How-ever, use of the PAR approach gives researchersa coherent framework to engage with move-ments that cannot “be engaged with using thestandard toolbox” (95, p. 1). With PAR, inves-tigators also have a position that enables themto take on the role of “empathetic insider” (94,p. 401; 96) while being able to identify struggles,contradictions, and unintended consequencesof group action (94).

Although they sit less easily within a posi-tivist framework, works on ideas and discourses(e.g., 26) often generate rich historical and/orconstructivist analysis of the changing contentand power of ideas across sites in time or space.Discourse analysis is more often attempted thandone well, although some systematic works of-fer good models: For example, Epstein’s (26)

study of discourses on whaling shows how anantiwhaling discourse cast commercial whal-ing as bad but aboriginal whaling as acceptable,which impacted a range of practices from bansto decision making in the regime.

Another growing body of qualitative workconsiders horizontal linkages—linkages acrossGEG regimes and problem areas at the levelof global politics. This work focuses on actorsand how they manage interactions or otherwiselink across regimes and problem areas, giveninstitutional constraints and opportunities. Ex-amples of such linkages may be across problems(such as between climate change and biodiver-sity or for ozone-depleting gases whose replace-ments include highly potent greenhouse gases)or across institutions (such that regime actorsmay work together to ameliorate potential con-flicts or duplicate actions). These insights havehelped reenergize work on organizations andbureaucracies in GEG, including treaty sec-retariats and larger organizations such as theUnited Nations Environment Programme andthe World Trade Organization (52, 97, 98).Others have noted how this system is becomingmore than the sum of its parts: Researchers haveidentified what could be termed global gover-nance “architectures” or “regime complexes”(99, 100) and have drawn attention to “insti-tutional density” (54).

This work has necessitated the use of tech-niques such as interviews and archival re-search, often including multisited fieldwork.Researchers then triangulate these methods topinpoint causal linkages to trace out complexand hard to discover processes and relation-ships, such as which and how actors influencespecific outcomes. Triangulation—the use ofmultiple methods of data collection and anal-ysis to determine or confirm causal hypotheseswith more confidence (12)—will become moreimportant with the emergence of more complexquestions and more collaborative or interdisci-plinary research designs. Many, if not all, of theauthors of works cited in this section discuss theuse of multiple methods of data collection (in-terviews, surveys, archival work, content, andtextual analysis) and analysis in their research


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(52). Performing triangulation well can, never-theless, be challenging for a researcher who hasnot been given training in multiple methods, es-pecially given that many of the methods we citein this section and below are difficult to master.

4.1.3. Critiques of qualitative methods. Anumber of developments in qualitative methodshave made it possible for scholars to work acrossscale and sites and to use multiple forms of datacollection and analysis to triangulate the data,especially through collaborative data collection.However, these developments also raise a num-ber of practical and epistemological issues. Firstand foremost, some innovations in qualitativemethods that deal with the challenges we out-line above have resulted in a movement awayfrom conventional comparative case studies tomore ethnographic approaches. Such a movecalls for a discussion between political scientistsand anthropologists similar to the one that tran-spired between economists and anthropologistsover the study of the commons (e.g., see 101).Even though classic works on multisite methodshave been influential for anthropologists (85),they remain of limited utility for GEG scholars,perhaps because the target audience of thoseworks are scholars who have been working in-tensely at a local or single-site level and want toextend their research to broader scales, ratherthan vice versa. Furthermore, through a focuson the microlevel and community approachesto governance, studies may lose or attenuatetheir connection with ameliorating global envi-ronmental challenges and/or the constructionand impacts of governance institutions with aglobal reach.

Second, there are a number of practical is-sues that arise in introducing CEE, PAR, ormultisite work. Because they entail workingat multiple sites, actively engaging communi-ties in the research design, or utilizing multi-ple qualitative methods to study the same megaevent, these new methodological approachespose significant challenges for a doctoral stu-dent or a junior scholar facing the tenure clock(also see 102). In particular, these studies re-quire significant funding, but more critically,

they also require significant time investmentsfor scholars to work collaboratively as wellacross multiple sites where research subjectsspeak different languages (89).

Third, replication remains problematic forqualitative methods, although whether it is pos-sible or even desirable depends on the researchquestion. If the question is about a “case” ofsomething that is part of a generalizable phe-nomenon, then generalization is a valid goal andfurther investigation of complementary meth-ods may be desirable. However, as discussedabove, qualitative methods are often under-taken precisely because the case is the focusand the goal is to attain “internal validity” byexamining how a policy trajectory may unfold.Such an approach is also meant to be highlyuseful in its application to other cases, such asidentifying different types of path-dependent“sequences” that help researchers to uncover“hidden” causal pathways that quantitative ap-proaches in other cases failed to uncover (e.g.,34, 37).

Finally, the complexities presented by con-temporary global environmental problems of-ten make it hard for researchers to answer thequestions they pose. For example, scholars whohave sought to evaluate the potential socioeco-nomic impacts of REDD+ have encountereddifficulties in applying counterfactual analysisgiven the absence of a baseline “no-interventioncase” (103). The need to address this sort ofquandary has helped drive growing interest inMSB methods (addressed below).

4.2. Quantitative MethodsUsing statistics, researchers can aggregate in-formation across many cases across space andtime. This method also allows investigators todraw inferences (104). Thus, quantitative meth-ods, particularly statistical methods, have be-come an essential component of training andscholarship in IR. However, despite the pleaby some scholars for greater use of quantitativemethods to study global environmental prob-lems (59), advocates have yet to champion suchan approach in ways that explicitly incorporate


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the four GEG challenges: complex and unpre-dictable processes, multiple levels of scale, hor-izontal linkages, and evolving governance in-stitutions. Nevertheless, promising advances inqualitative and quantitative methods have fos-tered construction of new data sets and use ofinnovative methods around data gathering andcoding across issue areas and scale. In manyways, GEG scholars are rising to the challengepresented by Nils Petter Gleditsch (105) call-ing for “major improvements in systematic datacollection—a Correlates of War project for theenvironment” (p. 396). One example includesthe Social Conflict in Africa Database, whichtracks social conflict events from 1990 to 2011and has been used to study rainfall variabil-ity and social conflict (106). Another area weexamine that holds promise is the use of net-work analysis that enables scholars to make con-nections across scales and to tease out complexinteractions among actors.

4.2.1. Statistical analysis in GEG research.Although scholars working on GEG havelargely employed qualitative methods in theirresearch, a smaller number of scholars have ap-plied statistical methods to the study of GEG,especially pertaining to the study of the for-mation and effects of international regimes andenvironmental treaties (32, 107–109). Withinthe broader field of global environmental poli-tics, statistical methods have been used to studythe relationship between democracy and en-vironmental performance (110) and the pro-vision and effectiveness of environmental aid(111, 112). Drawing on new project-level data,for example, recent research on environmentalaid effectiveness has shown that the strength ofa recipient country’s public sector is likely toinfluence the success of assistance projects.

With regards to carbon abatement, Dinaret al. (113) have used statistical methods to ex-amine the extent to which better business en-vironments, higher levels of governance, andstrong international trade relations have led tocooperation in the Clean Development Mech-anism market between certain countries, ex-plaining why China and India are the most

heavily involved. To tackle the question oflong-term uncertainty stemming from climatechange, Lempert et al. (33) applied statisticalmethods to examine “past patterns in data andproject them into the future” (p. 106). Thesestatistical methods, although not a panacea, mayhold some promise, as we discuss below, forforecasting and the development of scenarios.

Scholars are motivated by a desire to advancethe field from the collections of case studiesthat have accumulated in edited volumes to theconstruction of comprehensive data sets thatwould allow for more systematic comparisonsand analysis across multiple observations (28,114). By the late 1990s, scholars had begun toutilize the range of data points provided by somany multilateral environmental agreements toconstruct databases, such as the InternationalRegimes Database, that were designed to fos-ter more quantitative work (32, 115) and formalindices of performance, as in the Oslo-Potsdamsolution for measuring regime effectiveness(116, 117). These advances have allowed pro-ductive debates over what regime/treaty effec-tiveness means; how to measure it; and the con-ditions under which institutions, treaties, andorganizations could induce compliance. How-ever, such efforts have often been underutilized,although it is not clear exactly why.

In the field of environmental security andconflict, quantification has shifted away fromstudies of the various causal relations betweenenvironmental scarcity/abundance and/or en-vironmental change and conflict (105, 118) andthose between water and cooperation and con-flict (129) to examination of the relationshipbetween climate change and conflict. As a re-sult, researchers have begun to quantify, forexample, the relationship between temperatureand/or precipitation and civil war and/or socialunrest (106, 119). Although such studies haveforced scholars of global environmental poli-tics to shift away from descriptive case studiesand to draw broader generalizations about envi-ronmental factors and political outcomes (e.g.,the relationship between climate variability andconflict), they do not elaborate on the contin-gent causal mechanisms that may explain how


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conflicts transpire (120). Furthermore, they donot explain or capture relationships that tran-spire across scale. As a result, questions thatconcern GEG scholars pertaining to how cli-mate change could undermine human security,resilience, and state capacity and, thus, couldincrease the risk of violent conflict are harderto approach using these methods alone (in con-trast, see 121).

Thus, quantitative approaches also have lim-itations for studying questions that confrontGEG scholarship today. First, these methodsrequire already-available data and as such can-not be applied to the study of ongoing pro-cesses, which often comprise complex, mul-tiscalar, and linked problems. Because manyproblems that confront GEG scholars deal withongoing environmental issues, the focus onproduced data often does not comport withthe need to explain process and causal mech-anisms that are constantly being updated andshifting. Second, quantitative studies often takewhat may be considered an overly pared-downapproach to causal relationships. For example,the literature on the effects of democracy onthe environment mentioned above finds an in-significant effect (110). In contrast, qualitativeresearch has demonstrated not only the exis-tence and complexity of this relationship, butalso many mechanisms that shape its form fromcase to case (122, 123).

However, such a limitation does not haveto result from a quantitative approach. Forexample, where the literature on resourcewars has tended to conflate the link betweenoil and international conflict, Colgan’s (124)statistical study provides a more nuancedaccount that examines the role of revolutionsand revolutionary governments. In a differentvein, Axelrod (125) uses statistical methodsto examine the extent of the “chilling effect”in trade-environment politics, and the fsQCAwork cited above seeks to bridge the “qual-itative/quantitative” divide. Bernauer et al.(126) find a “democracy-civil society paradox”in global environmental governance that hadeluded qualitative researchers and that calls foradditional research. Hence, the fault of some

earlier-cited quantitative studies lies less withthe method per se than with the sorts of ques-tions researchers use these methods to addressor, indeed, their pursuit of often purely binaryanswers to those questions. One of the mainstrengths of quantitative approaches is theirability to address the limitations of qualitativemethods for achieving external validity. How-ever, even methodological critiques towardthe quantitative end of the spectrum (such asmatching-based statistical, pseudoexperimen-tal, and experimental approaches) are valid onlyfor the universe of cases they examine, whichmay be limited in the GEG field (see 127, 128).

4.2.2. Data collection and databaseconstruction across scale. Quantitativeapproaches can, and ought to be, part of theglobal environmental politics methodologicaltool kit. Such an orientation has proven fruitful,especially as scholars have begun to utilizeinnovative techniques for data collection andconstruction of large-N databases for indi-vidual and collaborative research that extendsacross scale (including both ecological andhuman/political). For example, scholars havestarted addressing a wider range of real-worldoutcomes and impacts of GEG, moving beyondtheir early emphasis on questions of formalinstitutions and compliance. In part, this trendis led by greater data availability on ecosystemimpacts and by the greater sophistication oftools and methods for mapping, estimating,and modeling environmental change. Othershave turned to large-N quantitative studies togeneralize results and correlate variables acrossa large number of cases (e.g., 53). The construc-tion of the Transboundary Freshwater DisputeDatabase, housed at Oregon State University,has enabled scholars to dispute systematicallythe proposition that riparian states are morelikely to engage in conflict over their sharedwater resources (129, 130). The existence ofsuch a large database has allowed subsequentscholars to examine the design of the treatiesthat comprise the database for more specificquestions that address temporal, spatial,and jurisdictional scales (131). Likewise, the


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construction of the AIDData database, housedat the College of William and Mary andconsisting of information on aid activitiesworldwide, has come with a resurgence inthe application of quantitative methods foranalyzing the delivery and impact of aid (132,133).

The International Forestry Resources andInstitutions (IFRI) database, housed at theUniversity of Michigan, focuses on examin-ing how governance arrangements affect forestsand forest-dependent communities. With it,researchers are attempting to generate a sys-tematic way of collecting data about institu-tions and outcomes as well as a rich data setthat spans the globe. Starting in 1993, datahave been collected using 10 core measurementprotocols that encompass biophysical measuresof forest conditions, climatic and soil condi-tions, demographic and economic indicatorsabout forest users, and details on institutions(134). Unlike many other databases mentionedabove, the IFRI data set relies on a processof collaborative engagement of scholars work-ing independently at different sites across theglobe, collecting the same set of informationrepeatedly at many sites every 3–5 years (134).Collaborative data sets are likely to becomemore commonplace, especially as the Internetfacilitates data sharing and access. A less sys-tematic, albeit collaborative, data set is Aqua-Pedia. According to its website (http://sites.tufts.edu/waterdiplomacy/aquapedia/), it isan interactive repository of “water managementinformation and wisdom collected and synthe-sized by users and producers of explicit (waterinformation) and tacit (water wisdom) knowl-edge” where individuals can directly submitcase studies of water basins. Housed at TuftsUniversity and with National Science Foun-dation funding, the repository relies on crowdsourcing for its contents.

IFRI’s innovation has been to probecorrelations between biophysical data andsocioeconomic and institutional data in specificsites, shedding light on the causal pathwaysthrough which institutional architectures im-pact livelihoods and forests. Such databases are

increasingly relevant for GEG studies in at leasttwo ways. First, their methodological approachis geared toward uncovering causal mechanismsin governance arrangements, which can be in-formative for GEG scholars and may be adaptedfor use at multiple scales. Second, because theIFRI database contains information on morethan 250 sites across 15 countries from 1992 tothe present, the data allow for cross-case com-parisons that can inform how new governancearrangements are developed at multiple scales.To date, researchers have drawn on IFRI datato answer questions about the effectiveness ofdifferent types of forest governance approachesand arrangements that are useful for forestprotection within local institutional settings(135). Researchers have also used these data toexamine the extent to which monitoring andenforcement of rules are necessary conditionsfor successful commons management (136).Although few metastudies using IFRI datacurrently exist (but see, e.g., 137), such datasets are likely not only to help scholars identifyphenomena across multiple scales but alsoto tease out the interactions among differentvariables in complex socioecological systems.

Despite the potential usefulness of IFRI andother large databases for the study of GEG,some limitations should be noted. First, datacollection for IFRI is enormously intensive andrequires substantial resources both in the fieldand to process the data once they are collected.A significant portion of the IFRI data is qual-itative and must be coded and quantified—i.e.,by assigning a numerical value for each datapoint to turn words into numbers—to be usedfor large-N studies. What is coded also affectsthe questions we ask and the results identified:McDermott et al. (138) suggest that, eventhough regulatory practices are recognized asessential to understanding forest managementpractices, they are often not systematicallycoded given their measurement complexity.Furthermore, by coding, categorizing, andassigning numerical values to the ideas, opin-ions, recollections, and reflections provided byinformants, much of the richness of the quali-tative data is necessarily lost as the data become


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http://sites.tufts.edu/waterdiplomacy/aquapedia/

http://sites.tufts.edu/waterdiplomacy/aquapedia/


simplified (139). Balancing data richness versusgeneralizability is perhaps one of the mostsignificant trade-offs that researchers confrontwhen navigating their methodological choices.

4.2.3. Using network analysis to map com-plex relationships. Network analysis is an in-novative method applied to study relationshipseither among large numbers of actors or be-tween complex human and natural systems. Itoften utilizes the sorts of databases described inthe previous section. According to Johnson &Griffith (140), network analysis can be used toreveal patterns that would not be evident withother methods that are less systematic. For ex-ample, by mapping the formal resources andinformal social resources in the aftermath of ahurricane, it can help to explain the evolution ofcooperative networks in a village, developmentof social capital, diffusion of knowledge, or theability to recover from a disaster (141). It has thepotential to be used by GEG researchers in con-junction with spatial analysis using geographicinformation system (GIS) techniques (142).

Fisher and colleagues (143) have usednetwork analysis to analyze hearings on cli-mate change within the US Congress: Theymapped out the ideological relationship amongdifferent types of speakers providing Congres-sional testimony on the topic. In contrast tostudies that examined the relationship betweensubnational and national policy making (e.g.,on federalism, see 144) in the United States,network analysis allowed these researchers tofocus on the specific role and coalitions of ac-tors involved in the policy-making process. Inaddition, they used a tool developed by Leifeldand colleagues (143)—which has some similar-ity to NVivo, a popular tool for qualitative dataanalysis—to code the content of testimoniesfrom Congressional hearings and then analyzeit to assess relationships quantitatively betweentypes of actors, the discourses they supportedor promoted around climate change policy,and the strength of the common discourse tiesamong them. Network analysis of this typeallows a more systemic treatment of discoursethan could be accomplished using only qual-

itative analysis of congressional testimony. Italso creates a way to visualize polarization andcoalitions of types of actors at different times.However, to code the discourses correctly,researchers must make qualitative judgmentsabout what speakers meant, making thisprocess quite labor intensive.

Network analysis has also been used tounderstand the complex institutional landscapegoverning climate change with the rise of alarge number of competing as well as overlap-ping institutions at the global, national, andlocal levels for dealing with climate change.Green (145) used network analysis to examine anew data set of private standards for managinggreenhouse gas emissions to demonstrate thecompatibility among those standards and theorder that exists within such an institutionallycomplex landscape. Although network analysisis useful for mapping these relationships,Green’s study also underscores the importanceof other conventional qualitative methods,such as semistructured interviews, to explicatethe motivations of the standard setters.

Some scholars are expanding network anal-ysis so that it integrates qualitative data withinferential statistics to make causal inferencesabout the impact of network membership. Forexample, Cao (146) has used network analysisto look at the relationship between partic-ipation in intergovernmental organization(IGO) networks—that is, countries sharingparticipation in particular IGOs—and theparticular type of IGO to explain policy diffu-sion and convergence. Simplifying a complexmethodology, Cao argued that different IGOsdepend on different mechanisms (some aremore coercive, others reflect learning environ-ments) and then used network analysis to seeif network linkages among states and the IGOsled to convergent policies and what type ofdiffusion mechanisms were most likely at work(coercion as opposed to learning, for example).

Although all these examples show the powerof network analysis to establish patterns and,when combined with statistical tools, to makeinferences about network effects on outcomes,care is required in research design owing to the


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characteristics of environmental governancenoted above. For example, studies of diffusion(e.g., 146) assume states are the repositoriesof environmental policy. By contrast, otherstudies (e.g., 145) more self-consciously turnthe lens on standard setting bodies for whichgovernance is increasingly occurring, therebyproviding data that would not be captured by anetwork analysis of states and IGOs. Similarly,Paterson et al. (147) used network analysis toexamine policy diffusion regarding the idea ofcarbon markets, but they looked at networksof individuals who interacted with various“venues” where carbon markets were promotedor developed, almost none of which were statesin the initial adoption period. Instead, the mainvenues were in an international agreement (theKyoto Protocol, though that did not developas an operational system), a supranationalbody (the EU Emission Trading System), andsubregional systems in US states and Canadianprovinces. Network analysis of all the individu-als involved in these policy processes revealed,among other things, different clusters of actorswho largely independently developed emissiontrading in the United States and Europe.To trace accurately the flow of ideas underconditions of complex or polycentric globalgovernance, researchers also had to combinethat work with qualitative analysis. Such analy-sis revealed a picture of diffusion different fromthe one that would have developed from a studyfocused on states that adopted emission tradingor a study that looked only at qualitative dataabout which states pushed the idea in interna-tional gatherings. The latter approach wouldhave erroneously led to the view that emissiontrading was largely a story of US coercion.

The above sections identify the benefitsof methods within qualitative and quantitativetechniques as well as the key gaps each familyof methods displays in addressing the four chal-lenges relevant to GEG scholarship reviewedat the beginning of this article: unpredictabil-ity, multilevel governance, ongoing evolution-ary change, and dueling objectives. Partly as aresult, recent innovations in the methodologi-cal area of MSB are relevant for addressing the

problem of change in open systems, where con-tingency, complexity, and possible nonlineari-ties and system shocks mitigate against predic-tion in the positivist sense.

4.3. Modeling and ScenariosMSB has become a widely employed methodfor examining GEG, but scholars of global en-vironmental politics have not always joined inthese efforts, with the exception of a small bodyof work on game theory and GEG (148, 149).In this section, we begin by defining models andscenarios and noting the limited, but emerging,role of GEG scholarship in MSB through exam-ples from climate policy modeling and the de-velopment of climate scenarios. We use a recentset of articles on the sensitivity of climate out-comes to geopolitics to highlight both the po-tential and the challenges of a more robust rolefor GEG in global modeling. Finally we addressthe potential of MSB to address uncertainty andcomplexity in GEG evolution. MSB exercisesare fertile terrain for the sort of scholarly ex-change essential to support GEG. Such interac-tions may be marked by debate, but ultimately,and in the right hands, the exactitudes and un-certainties that MSB activities and outcomeselicit can help researchers to reconcile disparateideas, theories, and bodies of evidence.

4.3.1. What are models? Models are simpli-fied or idealized representations of structures,systems, and agents. They can be made of clay,binary code, mathematical equations, collec-tions of ideas, or any other medium. They arenot necessarily mathematical and can be quali-tative (150). A novel, for example, is a modelrepresenting social relations, just as an inte-grated assessment model represents global en-vironmental processes (151). Modeling activ-ities may be fully inductive, fully deductive,and anywhere in between (152). Models maybe used to develop stories and representationsabout any moment in time (both future and pastperiods) and to articulate how periods relate toeach other.

Experiments and theories are also mod-els. The aim of experimentation is to create


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constrained, idealized model worlds. Ex-perimentalists tell special, often falsifiable,stories—theories—to argue how experimentalworlds represent elements of the “real” world.Thought experiments are models constructedof prose and integrally intertwined with theo-ries explaining their implications. Thus, theo-ries, by definition, at minimum have models astheir foundation. Sometimes, the boundary be-tween theories and models can be undetectablyvague.

Models further contribute to the productionof knowledge both through their constructionand their use (153). The act of model makingmay prompt model builders to describe and ex-plore more formally the relationships and con-tingencies of the systems that they study. Al-though such modeling can and does generatesurprises, it cannot elucidate factors unknownto model makers unless it contains autonomousagents, as are found in experiments (154).

4.3.2. What are scenarios? Scenarios are col-lections of two or more stories assembled toelicit attention about processes of change (155).Scenarios overtly and covertly reflect the prior-ities, assumptions, and goals of those who de-velop them. For example, any one scenario orcollection of scenarios may be designed to beplausible, may be designed to be controversial,or may be designed to be a hybrid of controversyand plausibility (156). We use the term scenar-ios to refer to both the process of assemblingscenarios and the outputs of these processes.These products are individual stories and storycollections; the processes can comprise the de-velopment and/or the use of story collections.

The evolution of the IntergovernmentalPanel on Climate Change (IPCC) scenariosgives a sense of the breadth and varying depth ofGEG-relevant scenario-making activities withrespect to GEG themes. The first set of IPCCscenarios, the IS92 scenarios, were basically sto-ries of “how future greenhouse gas emissionsmight evolve in the absence of climate poli-cies beyond those already adopted” (157, p. 73).The IPCC’s characterization of these worlds asvarying widely meant strictly that “the resulting

range of possible greenhouse gas futures spansalmost an order of magnitude” (157, p. 73).

Another IPCC scenario set, the SpecialReport on Emissions Scenarios (SRES), moreexplicitly narrates a socioeconomic context foremissions pathways. Split into storylines A1,A2, B1, and B2, the SRES tells stories of fourdifferent groups of mid-twenty-first centuryworlds—A1, a world of rapid growth andtechnology development; A2, a heterogeneous,fragmented world of slower economic growth;B1, a dematerializing world with economicgrowth to rival A1; and B2, a world witheffective local sustainability efforts.

The latest effort, the Shared Socioeco-nomic Pathways (SSPs), provides further detailabout institutional and political elements ofpotential future worlds. The pathways are“Sustainability,” “Middle of the Road,” “Frag-mentation,” “Inequality,” and “ConventionalDevelopment.” Within SSPs, there is greaterGEG-salient nuance such as the representationof inequality within nations in addition toinequality between nations. Indeed, a numberof GEG scholars have contributed to thedevelopment of the SSPs.

In MSB-based assessments of the globalcosts and impacts of climate change, the bound-aries between scenarios and models sometimesblur. Some assessments start with scenariobuilding, others with model making. Construc-tion of the SSPs began with premodeling. Theoutcomes of these efforts form the grist forthe formation of the narrative SSP scenarios.The SSPs determine how modelers preparetheir models for simulations. Ex post, there areconsistency checks between the assumptionsand stories as well as across models.

As the evolution of GEG depth within IPCCscenarios indicates, the climate modeling com-munity has begun to place a heightened empha-sis on politics and institutions. To underscorethe importance of GEG themes to climate out-comes, Rogelj et al. (158) showed that politicsare the single most important determinant ofhow much the Earth may warm in the comingdecades. A 5- or 10-year delay in the develop-ment of a climate treaty could create irreversible


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INTEGRATED ASSESSMENT MODELS

Integrated assessment models (IAMs) aim to represent complexenvironmental problems, to identify potential solutions to theseproblems, and to orient future research. IAMs are so termedbecause they are used to integrate information, theories, andlaws from multiple disciplines. Compared with climate and otherEarth system models, IAMs tend to include some social, eco-nomic, and political variables in addition to biophysical variables.Some IAMs contain enormous complexity, run on supercomput-ers, and are primarily the domain of IAM experts. Other IAMsare built parsimoniously with the goal of encouraging broad lit-eracy and usage. One example of an IAM built to incorporatesocial science—albeit largely economic—variables is the DICE(dynamic integrated climate economy) model, whose develop-ment was led by Dr. William Nordhaus. Used by the US En-vironmental Protection Agency, among others, such models areimportant—although it is not entirely clear how far they are ableto incorporate the sorts of issues that concern other social scien-tists and humanities scholars. As we argue, there is much room forscholars of global environmental governance to engage in IAMbuilding and development.

damage to the Earth system. That the compar-ison of magnitude of political uncertainty withother sources of uncertainty was the primaryinnovation of the paper is an indicator of thenewness of the theme.

GEG scholarship can help the climate MSBcommunity to develop scenarios that treatpolitical and institutional themes with moresophistication. Its insights into the causes,dynamics, and consequences of fragmentedand networked climate governance could be arich addition to climate modeling (99). In fact,the fragmentation literature is the basis for anew class of climate modeling exercises thatseek to explore the implication of uneven andunilateral climate policies (but see, for example,159, 160). These analyses may be messy, butthey are a more plausible representation ofclimate institutions than analyses that representgovernment restrictions on greenhouse gasemissions as global and monolithic (see, forexample, 158, 161).

GEG themes and theories can be morethan just scenarios—they can be componentsof climate models that interact with otherelements of the modeled Earth system. Severalrecent articles use different MSB approachesto demonstrate how scientific uncertaintyabout the impacts of GHG emissions mayhave a chilling effect on international collectiveaction to fight climate change or may warp theimpacts of climate interventions (148, 162).

However, in circumstances of greatcomplexity and deep uncertainty, efforts toestablish bounding ranges around problemscan also be inaccurate (163). A grand challengefor MSB is to communicate contingenciesand uncertainties. Communicated poorly ortaken out of context, model results can beinterpreted as predictions and/or explanationswhen they are instead representations ofunknown elements and interactions. In thisway, GEG-focused MSB practitioners shareseveral aims and challenges with those engagedin the broader scholarship in the area ofglobal environmental politics. Both groupsseek out the unpredictable, evolving, complex,and uncertain nature of GEG, and both areconcerned with interactions that cross multiplescales and that are horizontally linked (164).

The shared challenge presents an oppor-tunity for a transdisciplinary conversationabout doing and about how to communicateresearch on complex systems. We see potentialfor part of this conversation to happen withinmodeling exercises that involve GEG scholars.Models can provide a space for scholars toconvene to pool resources and expertise. Fromregime databases to integrated assessmentmodels, this pooling can make the wholegreater than the sum of its parts (see sidebarIntegrated Assessment Models). The standardsand exactitudes of models can also promotediscursive clarity. Clear communication withinmodel groups and clear documentation ofmodel approaches are imperative, however,to avoid models that carry an imprimaturof harmony even when they are internallyinconsistent.


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Furthermore, MSB of GEG has tended tofocus on the “easy problems” that “God gavephysicists” (to paraphrase an article that arguesevolutionary biology is a more productive anal-ogy than classical physics for social sciences) asopposed to the complex, messy problems thatGEG scholars tackle (34). Biophysical Earthmodels represent physical processes accordingto the laws of classical physics and the equilibri-ums that these laws predict. Likewise, models ofthe world economy often assume an overarch-ing set of governing principles that suggest thepossibility for steady states and equilibriums.The problems of physics and economics are notactually easy. Rather, fairly universal theoriesprovide these simplified representations.

Meanwhile, scholars in the broader GEGfield focus on norms, values, politics, andcultural proclivities. Few see these elementsof GEG as having equilibrium characteristicsor even the stability to be represented withstraightforward functional forms. These are theelements of the Earth system that create fat tails,uniform distributions, and black swans: in otherwords, highly unexpected outcomes that are notpredictable, no matter how many data pointson previous similar events have been collected.GEG themes are the elements that generate themost climate uncertainty (158). Because GEGscholars tend to be suspicious of approachesthat lead to narrow conclusions about complexenvironmental systems, they can help to enrichMSB. In turn, by participating in MSB, GEGscholars can benefit from rich and meaningfulinteractions with other researchers seeking tounderstand and inform GEG.

5. STRATEGIES FORPROBLEM-DRIVEN GLOBALENVIRONMENTALGOVERNANCE RESEARCHWe argue that contemporary GEG researchersface four challenges identified at the outsetof this article—unpredictability, complexity,linkages, and scale. As Miller et al. (165,p. 4) point out, “[n]ormal science has becomeless capable of addressing complex social-

ecological interactions in particular, and lessresilient to dramatic changes in the societaldemands for knowledge and to revelationsfrom ongoing research that demand reconsid-eration of accepted theories” (166, 167). Or,as Andonova & Mitchell suggest (30, p. 258),“rescaling of environmental politics reflectsboth an ontological shift driven by increasinglyinterdependent countries facing increasinglycomplex and interconnected environmentalproblems and an epistemological shift drivenby scholars studying global environmentalpolitics with increasingly interdisciplinary anddiverse theoretical frameworks.”

Designing the rigorous, applied researchprojects that are needed to address globalenvironmental problems in the context of thesechallenges and in broader research contextsthat downplay or do not create incentives forapplied work may pose significant obstaclesfor the individual researcher. In the abovesections, we identify some tools and approachesas well as debates around specific techniques.This section pulls together some of the com-mon themes of these debates and discussespossible strategies researchers can adopt. Weexamine the potential of multiple methodsand collaborative research. Although these arenot necessary for successful applied research,many and various forms of collaboration andmethodological pluralism exist, making it pos-sible for even the most individualist researcherto draw on different analytical traditions anddata sources. Undergirding these strategies isa need for researchers to be more reflectiveabout their methodological choices, especiallywhen researchers face the dilemma of choosingamong a wide range of possible methods andresearch designs (also see 27). We likewise echoa need for pragmatism in real-world appliedresearch design. Among other implications,this means that researchers do not always needto reinvent the wheel: The above analysisshows that GEG researchers across disci-plinary traditions still use many long-extanttools for data collection and analysis, albeitin different ways and in different sorts ofcontexts.


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5.1. Multiple MethodsA small but thriving body of literature has be-gun to examine how to incorporate both mul-tiple methods and plural epistemologies (165,168) into reflective research designs and how tobridge disciplinary divides; this approach has al-ready taken hold in literature on the commonsat the local level (101, 102, 169), which goesbeyond similar attempts that have not yet man-aged to break out of the constraints of politicalscience (e.g., 170). Miller et al. (165), for exam-ple, call for “epistemological pluralism,” which“recognizes that, in any given research context,there may be several valuable ways of knowingand that accommodating this plurality can leadto more successful integrated study” (p. 1).

Multiple methods or what have also beenreferred to as mixed methods within the po-litical science canon can take many forms, butthey have often brought together qualitativeand quantitative methods to answer a researchquestion. In Section 4.1, we discuss the signifi-cance of triangulation, i.e., the use of multiplemethods to get a firmer fix on a complex re-search question. Betsill & Corell (12), in par-ticular, have demonstrated that multiple datatypes and methods are essential for understand-ing the different ways through which NGOsexert influence on international environmen-tal negotiations. However, the use of triangu-lation is not confined to qualitative research.It is helpful in establishing causal relationshipsby applying both qualitative and quantitativeinsights that add up to a more complete pic-ture. Snow’s identification of cholera as an in-fectious disease provides a classical depictionof this approach: He performed a qualitativestudy to identify victims, then a statistical anal-ysis to identify contaminated drinking water asthe source (171). This study advanced the fieldof epidemiology, and utilizing both qualitativeand quantitative data, statisticians and politicalscientists have championed it as a methodolog-ical breakthrough for showing the importanceof causal inference (172).

Within the study of regime effectiveness,Young (10) has called for scholars to use multi-

ple methods whenever possible to tackle manyof the same challenges we describe above and,in doing so, “to think in terms of a methodolog-ical portfolio or toolkit containing a range ofdistinct but complementary modes of analysis”(p. 19858). Mitchell & Bernauer (173) suggestthat more large-N studies can complementqualitative studies and ultimately facilitatetriangulation. Studies of regime effectivenessconcur that, to grasp fully patterns of regimeeffectiveness and causal mechanisms (includingthe role of power), qualitative methods mustbe combined with quantitative methods (72).

As an example of the effective use of multiplemethods, Cashore et al. (70), in their compar-ative study of forest certification, first appliedsurvey data and analysis to map out the broadterrain and assess support and interest in thetargets of this innovative market mechanism.Drawing on these quantitative data, they thendeveloped questions and concepts with whichto undertake careful casual historical processtracing and structured focused comparisons toget at questions of why some countries adoptedcertain forest certification programs and othersdid not. Their work shows how such an ap-proach can generate exploratory, descriptive,and explanatory research that would not havebeen possible by applying only a single methodor bringing a single researcher’s perspective tobear. Another area where there may be a grow-ing desire for multiple methods with GEG re-search is with the use of spatial analysis (GIS)(27), especially to deal with issues of multi-scalarity and the interface between human andecological systems. GIS technology can help re-searchers to visualize boundaries and relationsamong people and their environment as well asto bring policy and science together so as tobetter address environmental problems (174).

One of the debates around multiple meth-ods, especially mixed methods, has to do withtheir commensurability (168): Do they add upto more than the sum of their parts, or can theyreflect yet another form of methodologicallydriven research? Can methods that reflect verydifferent epistemologies be brought togethereffectively? And how can research design take


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into account multiple epistemologies or waysof knowing? Miller et al. (165, p. 4) argued that“ignoring the role of multiple ways of knowing,process, etc., in interdisciplinary research cantorpedo efforts from the beginning.” Poteeteet al. (102, p. 13) further pointed out that the“use of multiple methods, however, does notguarantee methodologically superior socialscience research.” Seen in this light, we arguethat methods must be justified in their abilityto address an environmental challenge thatinitially motivated the research as well as theimplications and challenges of the range ofmethodological choices scholars will necessar-ily have to make. Many mixed-method theoristsexplicitly call for a pragmatic approach to socialscience research: Small (168, p. 60; paraphras-ing 175, p. 8) noted that “pragmatism encour-ages researchers to set aside considerationsabout what is ultimately true in favor of whatis ultimately useful and to remain comfortablewith uncertainty and that it orients itself towardsolving practical problems in the ‘real world.’”

5.2. CollaborationOne of the challenges of multiple methods con-cerns whether individual scholars need to bewell versed in a suite of methods, often rang-ing from quantitative to qualitative methods,or whether the use of multiple methods alsocalls for collaborative and interdisciplinary un-dertakings. Increasingly, collaborative researchis viewed not only as central to fostering in-terdisciplinary research, but also as the foun-dation upon which multiple methodologicalapproaches can be applied to solve problems(e.g., 102). One of the desirable aspects of col-laboration and the use of multiple methodsfosters greater generalizability and breadth ofstudies: Investigators are able to work at mul-tiple field sites and across scale simultaneously,and they can foster greater comparability.

Within the study of GEG, encouragingsigns indicate that collaboration is becomingmore widespread. Research on GEG has re-sulted in collaborative endeavors, such as theGlobal Governance Project carried out by 13

European research institutions, that have ex-amined different components of GEG, rang-ing from public-private partnerships to regionalgovernance arrangements. Research on inter-national regime effectiveness has led to the de-velopment of collaborative research teams aswell as looser networks of researchers (10). Inparticular, collaboration was instrumental increating the International Regimes Database(72).

Collaboration can be organized in a numberof different ways. Scholars—faculty, postdoc-toral researchers, and graduate students—maywork and publish in groups. Others (as withthe CEE approach discussed above) may workjointly to collect data that are then used in in-dividual or joint projects and increasingly madepublicly available. Yet others may be far moreloosely organized around a single theme, for in-stance, or source of funding, thus enabling moreindividual outputs.

The main constraints, however, to encour-aging collaboration outside of interdisciplinaryprograms are the traditional means by whichjunior scholars are evaluated within disciplinarydepartments. For collaboration to be morecommonplace, universities will need to make afirm commitment to junior scholars that theirefforts to work outside of the conventionalmores will be given equal weight. In addition,although collaboration (for example, in labgroups) is a common feature in the naturalsciences, it is far less prevalent in the social sci-ences and humanities. As a result, researchersin the latter disciplines face more difficulties intheir attempts to draw on established norms andpractices over, for example, ownership of dataor author accreditation. Notable exceptionsinclude the humanities labs at the FranklinHumanities Institute at Duke University aswell as those at Stanford University.

6. CONCLUSIONThis review has surveyed appropriate methodsfor studying GEG and has connected thisdiscussion to broader debates about methodsand research design in the social sciences.


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The above analysis demonstrates that greatadvances have been made in developing re-search methods relevant for GEG scholarship,especially for handling historically complexcausal processes and meeting the challenges ofdeveloping theory that is critical for problemsolving. Old tools are being applied in newways, and traditional divides between quantita-tive and qualitative methods of data collectionand analysis are breaking down. However,methods and their applications have often re-mained underexplored, and in published work,many researchers only implicitly connect theirmethodological choices to address effectivelythe problem at hand.

To advance these explorations, GEGresearch and methods must begin by beingconsistent with and incorporating the fourunpredictable, multiscale, horizontal, andevolutionary challenges that frame this review.Accordingly, scholars must be reflective aboutthe most appropriate methodological ap-proaches for the question they are addressing,rather than limiting their choices to preexistingpreferences or the techniques that their homeinstitutions emphasized. Breaking out of thesebiases means consciously embracing method-ological pluralism. This will not be easy,

however, because it means figuring out ways ofmoving beyond one’s own disciplinary or inter-disciplinary comfort zones. Studies that are toonarrow in their approach and design lose sightof bigger questions and concepts. As a result,they forego the possibility of contributions tointerdisciplinary collaborations about GEG ingeneral and problem solving in particular. Tohelp in this endeavor, our review has identifiedan expanding toolbox of methodologicalapproaches available to scholars that is likely togenerate innovations in data collection, collab-oration, and new modeling tools. In addition,although canon may be too strong a word, therenow exists a substantial range of publishedworks that utilize these techniques and may becontributing to the expansion of GEG articlesthat are more explicit about methodologicaltechniques employed, as we found over time inour survey of articles in GEP. Overall, our anal-ysis suggests that many avenues are availablefor GEG scholars as they move forward and de-sign problem-focused research that deals withpressing issues facing the global community.Some involve more collaboration or retrainingthan do others, but in all cases, reflectionand methodological pluralism are required togenerate rigorous and relevant research.

DISCLOSURE STATEMENTThe authors are not aware of any affiliations, memberships, funding, or financial holding thatmight be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTSThe authors thank the journal’s two anonymous reviewers for their helpful comments. We alsothank Matt Hoffmann, Chris Paul, Paul Steinberg, and Elizabeth Havice for input on earlierdrafts as well as Luke Maier, Laura Driscoll, Jaimini Parekh, and Devin Judge-Lord for researchassistance. Earlier versions of this article were presented at the Duke University Program inEnvironmental Policy’s Environmental Institutions Seminar; the School of International Serviceat American University; the InterdisciplinariTEA Seminar in the Department of EnvironmentalScience, Policy, and Management at the University of California at Berkeley; the 2012 AnnualConvention of the International Studies Associations in San Diego, California; and the OceanicConference on International Studies in Sydney, held in July 2012.


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171. Snow J. 1965. On the Mode of Communication of Cholera. London: Oxford Univ. Press172. Freedman DA. 1991. Statistical models and shoe leather. Sociol. Methodol. 21:291–313173. Mitchell R, Bernauer T. 2004. Beyond story-telling: designing case study research in international

environmental policy. See Ref. 59, pp. 81–106174. Brondizio E, Chowdhury RR. 2010. Spatio-temporal methodologies in environmental anthropology:

geographic information systems, remote sensing, landscape changes and local knowledge. See Ref. 176,pp. 266–98

175. Feilzer MY. 2010. Doing mixed methods research pragmatically: implications of the rediscovery ofpragmatism as a research paradigm. J. Mixed Methods Res. 4:6–36

176. Vaccaro I, Smith EA, Aswani S, eds. 2010. Environmental Social Sciences: Methods and Research Design.Cambridge, MA: Cambridge Univ. Press


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EG38-FrontMatter ARI 15 September 2013 14:5

Annual Review ofEnvironmentand Resources

Volume 38, 2013

ContentsIntroduction ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣vWho Should Read This Journal? ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣vii

I. Earth’s Life Support Systems

Environmental Tipping PointsTimothy M. Lenton ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 1

Regional and Global Emissions of Air Pollutants: Recent Trendsand Future ScenariosMarkus Amann, Zbigniew Klimont, and Fabian Wagner ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣31

Pyrogeography and the Global Quest for Sustainable Fire ManagementDavid M.J.S. Bowman, Jessica A. O’Brien, and Johann G. Goldammer ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣57

II. Human Use of Environment and Resources

A Global Assessment of Manufacturing: Economic Development,Energy Use, Carbon Emissions, and the Potential for EnergyEfficiency and Materials RecyclingTimothy G. Gutowski, Julian M. Allwood, Christoph Herrmann, and Sahil Sahni ♣ ♣ ♣ ♣ ♣81

Life-Cycle Assessment of Electric Power SystemsEric Masanet, Yuan Chang, Anand R. Gopal, Peter Larsen, William R. Morrow III,

Roger Sathre, Arman Shehabi, and Pei Zhai ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 107

Methods and Models for Costing Carbon MitigationJayant Sathaye and P.R. Shukla ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 137

On the Sustainability of Renewable Energy SourcesOttmar Edenhofer, Kristin Seyboth, Felix Creutzig, and Steffen Schlomer ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 169

Smart GridsPeter Palensky and Friederich Kupzog ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 201

Water Conservation: Theory and Evidence in Urban Areas of theDeveloped WorldDavid Saurı ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 227

Agricultural Biotechnology: Economics, Environment, Ethics,and the FutureAlan B. Bennett, Cecilia Chi-Ham, Geoffrey Barrows, Steven Sexton,

and David Zilberman ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 249

viii

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EG38-FrontMatter ARI 15 September 2013 14:5

Recent Advances in Sustainable Buildings: Review of the Energy andCost Performance of the State-of-the-Art Best Practices fromAround the WorldL.D. Danny Harvey ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 281

Smart Everything: Will Intelligent Systems Reduce Resource Use?Jonathan G. Koomey, H. Scott Matthews, and Eric Williams ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 311

State of the World’s Nonfuel Mineral Resources: Supply, Demand,and Socio-Institutional FundamentalsMary M. Poulton, Sverker C. Jagers, Stefan Linde, Dirk Van Zyl,

Luke J. Danielson, and Simon Matti ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 345

Global Environmental Change and Human SecurityKaren O’Brien and Jon Barnett ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 373

III. Management, Guidance, and Governance of Resources and Environment

Actionable Knowledge for Environmental Decision Making:Broadening the Usability of Climate ScienceChristine J. Kirchhoff, Maria Carmen Lemos, and Suraje Dessai ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 393

Market Instruments for the Sustainability TransitionEdward A. Parson and Eric L. Kravitz ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 415

Methods and Global Environmental GovernanceKate O’Neill, Erika Weinthal, Kimberly R. Marion Suiseeya, Steven Bernstein,

Avery Cohn, Michael W. Stone, and Benjamin Cashore ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 441

Humans and Nature: How Knowing and Experiencing Nature AffectWell-BeingRoly Russell, Anne D. Guerry, Patricia Balvanera, Rachelle K. Gould, Xavier Basurto,

Kai M.A. Chan, Sarah Klain, Jordan Levine, and Jordan Tam ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 473

IV. Integrative Themes

Preindustrial Human Impacts on Global and Regional EnvironmentChristopher E. Doughty ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 503

IndexesCumulative Index of Contributing Authors, Volumes 29–38 ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 529

Cumulative Index of Article Titles, Volumes 29–38 ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ ♣ 533

Errata

An online log of corrections to Annual Review of Environment and Resources articles maybe found at http://environ.annualreviews.org

Contents ix

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ANNUAL REVIEWSIt’s about time. Your time. It’s time well spent.

ANNUAL REVIEWS | Connect With Our ExpertsTel: 800.523.8635 (US/CAN) | Tel: 650.493.4400 | Fax: 650.424.0910 | Email: [email protected]

New From Annual Reviews:Annual Review of Statistics and Its Application=VS\TL��6USPUL�1HU\HY`��O[[W!��Z[H[PZ[PJZ�HUU\HSYL]PL^Z�VYN

Editor: Stephen E. Fienberg, Carnegie Mellon UniversityAssociate Editors: Nancy Reid, University of Toronto

Stephen M. Stigler, University of ChicagoThe Annual Review of Statistics and Its Application aims to inform statisticians and quantitative methodologists, as well as all scientists and users of statistics about major methodological advances and the computational tools that HSSV^�MVY�[OLPY�PTWSLTLU[H[PVU��0[�^PSS�PUJS\KL�KL]LSVWTLU[Z�PU�[OL�ÄLSK�VM�Z[H[PZ[PJZ��PUJS\KPUN�[OLVYL[PJHS�Z[H[PZ[PJHS�\UKLYWPUUPUNZ�VM�UL^�TL[OVKVSVN ��HZ�^LSS�HZ�KL]LSVWTLU[Z�PU�ZWLJPÄJ�HWWSPJH[PVU�KVTHPUZ�Z\JO�HZ�IPVZ[H[PZ[PJZ�and bioinformatics, economics, machine learning, psychology, sociology, and aspects of the physical sciences.

*VTWSPTLU[HY`�VUSPUL�HJJLZZ�[V�[OL�ÄYZ[�]VS\TL�^PSS�IL�H]HPSHISL�\U[PS�1HU\HY`��TABLE OF CONTENTS:

��What Is Statistics? Stephen E. Fienberg��A Systematic Statistical Approach to Evaluating Evidence

from Observational Studies, David Madigan, Paul E. Stang, Jesse A. Berlin, Martijn Schuemie, J. Marc Overhage, Marc A. Suchard, Bill Dumouchel, Abraham G. Hartzema, Patrick B. Ryan

��The Role of Statistics in the Discovery of a Higgs Boson, David A. van Dyk

��Brain Imaging Analysis, F. DuBois Bowman��Statistics and Climate, Peter Guttorp��Climate Simulators and Climate Projections,

Jonathan Rougier, Michael Goldstein��Probabilistic Forecasting, Tilmann Gneiting,

Matthias Katzfuss��Bayesian Computational Tools, Christian P. Robert��Bayesian Computation Via Markov Chain Monte Carlo, 9HK\�=��*YHP\��1LɈYL`�:��9VZLU[OHS

��Build, Compute, Critique, Repeat: Data Analysis with Latent Variable Models, David M. Blei

��Structured Regularizers for High-Dimensional Problems: Statistical and Computational Issues, Martin J. Wainwright

��High-Dimensional Statistics with a View Toward Applications in Biology, Peter Bühlmann, Markus Kalisch, Lukas Meier

��Next-Generation Statistical Genetics: Modeling, Penalization, and Optimization in High-Dimensional Data, Kenneth Lange, Jeanette C. Papp, Janet S. Sinsheimer, Eric M. Sobel

��Breaking Bad: Two Decades of Life-Course Data Analysis in Criminology, Developmental Psychology, and Beyond, Elena A. Erosheva, Ross L. Matsueda, Donatello Telesca

��Event History Analysis, Niels Keiding��:[H[PZ[PJHS�,]HS\H[PVU�VM�-VYLUZPJ�+5(�7YVÄSL�,]PKLUJL��

Christopher D. Steele, David J. Balding��Using League Table Rankings in Public Policy Formation:

Statistical Issues, Harvey Goldstein��Statistical Ecology, Ruth King��Estimating the Number of Species in Microbial Diversity

Studies, John Bunge, Amy Willis, Fiona Walsh��Dynamic Treatment Regimes, Bibhas Chakraborty,

Susan A. Murphy��Statistics and Related Topics in Single-Molecule Biophysics,

Hong Qian, S.C. Kou��Statistics and Quantitative Risk Management for Banking

and Insurance, Paul Embrechts, Marius Hofert

Access this and all other Annual Reviews journals via your institution at www.annualreviews.org.

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Methods and Global Environmental Governance · Environmental Governance Kate O’Neill,1 Erika Weinthal,2 Kimberly R. Marion Suiseeya,2 Steven Bernstein,3 Avery Cohn,4 Michael W