Draft
Overcoming the ‘Barriers’ Orthodoxy: A New Approach to
Understanding Climate Change Adaptation and Mitigation
Governance Challenges in the Canadian Forest Sector
Journal: Canadian Journal of Forest Research
Manuscript ID cjfr-2017-0465.R1
Manuscript Type: Reply
Date Submitted by the Author: 18-Feb-2018
Complete List of Authors: Wellstead, Adam; Michigan Technological University, Department of Social
Sciences Biesbroek, Robbert ; Wageningen University Cairney, Paul; University of Stirling Davidson, Debra; University of Alberta Dupuis, Johann; University of Lausanne Howlett, Michael; Simon Fraser University, Political Science Rayner, Jeremy; University of Saskatchewan Stedman, Richard; Cornell University
Keyword: mechanisms, climate change, adaptation, mitigation, policy
Is the invited manuscript for consideration in a Special
Issue? : N/A
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Overcoming the ‘Barriers’ Orthodoxy: A New Approach to Understanding Climate Change 2
Adaptation and Mitigation Governance Challenges in the Canadian Forest Sector 3
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Adam Wellstead (Corresponding author) 5
Department of Social Sciences 6
Michigan Technological University, 1400 Townsend Drive, Houghton, Michigan, USA. 49931 7
Email: [email protected] 8
Phone: (906) 487-2215 9
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Robbert Biesbroek 11
Public Administration and Policy Group, Wageningen University, Hollandseweg 1, 6700 EW 12
Wageningen, the Netherlands 13
Email: [email protected] 14
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Paul Cairney 16
Department of Politics and History 17
University of Sterling, Sterling, UK FK9 4LA 18
Email: [email protected] 19
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Debra Davidson 21
Department of Resource Economics and Environmental Sociology 22
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University of Alberta, Edmonton, Alberta, Canada T6G 2P5 23
Email: [email protected] 24
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Johann Dupuis 26
IDHEAP, Swiss Graduate School of Public Administration, University of Lausanne, Quartier 27
Mouline, Lausanne CH-1015, Switzerland 28
Email: [email protected] 29
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Michael Howlett 31
Department of Political Science, Simon Fraser University, 8888 University Drive, Burnaby, British 32
Columbia V5A 1S6, Canada 33
Email: [email protected] 34
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Jeremy Rayner 36
Johnson-Shoyama Graduate School of Public Policy, University of Saskatchewan, 101 37
Diefenbaker Place, Saskatoon, Saskatchewan S7N 5B8, Canada 38
Email: [email protected] 39
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Richard Stedman 41
Department of Natural Resources 42
Cornell University 43
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104 Fernow Hall, Ithaca, NY 14850 44
Email: [email protected] 45
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Abstract 68
We respond to Williamson and Nelson (2017) recent comprehensive review, “Barriers to 69
enhanced and integrated climate change adaptation and mitigation in Canadian forest 70
management” (47: 1567–1576). They employ the popular barriers analysis approach and 71
present a synthesis highlighting the numerous barriers facing Canadian forest managers. The 72
underlying functionalist assumptions of such an approach are highly problematic from both a 73
scholarly and a practical policy perspective. We argue that social scientists engaged in climate 74
change research who want to influence policy-making should understand and then empirically 75
apply causal mechanisms. Methods such as process tracing and qualitative comparative analysis 76
(QCA) are promising tools that can be employed in national level assessments or at the local-77
level. 78
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Key Words: adaptation, climate change, mechanisms, mitigation, policy 82
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Overcoming the ‘Barriers’ Orthodoxy: A New Approach to Understanding Climate Change 89
Adaptation and Mitigation Governance Challenges in the Canadian Forest Sector 90
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Introduction 92
Recently in this journal, Tim Williamson and Harry Nelson (2017), two well-known Canadian 93
forest economists, published a comprehensive review, “Barriers to enhanced and integrated 94
climate change adaptation and mitigation in Canadian forest management” (47: 1567–1576). To 95
do so, they borrow from Eisenack et al’s (2014) mainstream barriers analysis approach and 96
present a synthesis highlighting the numerous barriers facing Canadian forest managers. They 97
make critical contribution to forest climate change literature by making the case for an 98
integrated approach that adopts adaptation and mitigation concerns in forest management 99
decisions. Overshadowing this point, however, are the underlying functionalist assumptions 100
inherent in the barriers approach that they employ to illustrate challenges of integrated 101
considerations in forest management decision-making. This is problematic from both a 102
scholarly and a practical policy perspective. We argue that social scientists engaged in climate 103
change research need to abandon the barriers approach. Instead they should understand and 104
empirically apply causal mechanisms that may affect implementation (Wellstead and Stedman 105
2015; Wellstead et al 2016). Categorizing any factor or process as a “barrier” reduces complex 106
and highly dynamic decision-making into simplified, static and metaphorical statements about 107
why current outcomes are ‘incorrect’ (Biesbroek et al 2015). 108
109
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Williamson and Nelson (2017) adopt a systems-based lens where barriers and capacity 110
requirements affect forest-management policy outcomes. Critical to their systems analysis is 111
that an “ultimate outcome is specified precisely, the means necessary for implementation are 112
identified, and the reasons why the means are not being implemented (i.e., barriers) are 113
identified and evaluated” (p.1569). This is followed by their overview of barriers which are 114
broadly identified by three categories: harmonization, enabling, and implementation. 115
Harmonization barriers, they state are “attributable to differences between adaptation and 116
mitigation among forest management agents in beliefs, framing, knowledge, and awareness” 117
(p.1571). The presence or absence of enabling barriers (such as psychological factors, 118
institutions, and leadership) are critical in determining the extent of adaptation and mitigation 119
mainstreaming. Finally, implementation barriers such as governance, science and knowledge, 120
knowledge exchange, information, education, and training, funding, and monitoring present 121
challenges to achieving ‘ideal’ sustainable forest management (SFM) outcomes. 122
123
The Shortcomings of Functionalist Assumptions 124
While the barriers approach presented by Williamson and Nelson (2017) may be a useful 125
heuristic, its functionalist assumptions leave much to be desired in terms of understanding or 126
accurately characterizing political and social phenomena, including activities like public policy-127
making, law-making, as well as legislative and administrative behavior, and as outline below is 128
of little use to actual policy-makers. This approach assumes that society is a system of 129
interconnected parts that work together in harmony to maintain a state of balance and social 130
equilibrium for the whole (Little 1991; Elster 1983). More specifically, the “explanas specifies 131
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the function of the explanandum within the larger system and the benefits the feature confers 132
upon the smooth working of the system. The explanandum is to be explained, that is, in terms 133
of the beneficial consequences it confers on the system as a whole” (Little 1991, p.92). Elster 134
(1986) notes that functionalism is a “puzzling and controversial” mode of explanation in general 135
because, unlike other scientific modes such as causal or intentional explanations (where the 136
intended consequences occur earlier in time), early events are explained by another event later 137
in time (p. 31). Thus, in a functional explanation, “we cite the actual consequences of the 138
phenomenon in order to account for it” (p. 31).i And, Elster further notes, in political life there 139
are many examples of singular, non-recurring events that produce unintended policy 140
consequences (such as wars, riots, and rebellions), while feedback loops are often postulated or 141
tacitly assumed when they do not in fact exist (Elster 1986). 142
143
A second problem arises due to the lack of specificity about the mechanisms and internal 144
workings of institutional and other components of political and social systems: the so-called 145
‘black box’ problem. Such concerns about the limitations of high-level systems-theoretic 146
approaches also surfaced more than half a century ago when they first became vogue in the 147
social sciences. Many 1960s-era social scientists such as Talcott Parsons (1951), Gabriel Almond 148
(1965) and David Easton (1965) suggested that a high-level cybernetic view could explain much 149
political and social behavior and outcomes. 150
151
As early as the 1970s, this overly abstract approach had already been largely discredited. For 152
example, Lilienfeld (1978) labeled the functionalist approach as an “ideological movement” 153
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because of its tendency to assume that systems maintain themselves in a state of equilibrium, 154
and concluded that it contained little relevance to the real world where actors actively sought 155
and produced change. Similarly, Chilcote (1994) found black box systems-level frameworks did 156
little to explain political or policy change, yielded few testable hypotheses, and presented a 157
strong ideological underpinning that sought to downplay political conflict and promote a 158
technocratic understanding and approach to political life. Thorson (1970) found the whole 159
enterprise futile so long as the black box of real political and social processes remained 160
unopened and unexamined. Groth (1970) found that “structural-functionalism has run aground 161
trying to specify its model of the social system untangled by monumental ambiguities and 162
values in the guise of survival considerations” (p. 499). 163
164
By adopting this conceptually problematic top down and functionalist view of decision making 165
in a Canadian forest management context, Williamson and Nelson’s (2017) contribution does 166
little to actually explain decision-making. They simply outline the actors, ideas, and institutions 167
that define the forest policy regime (See Lindquist and Wellstead 2001; Rayner et al 2001; St. 168
Laurent et al 2017). The underlying assumption in their review is that there is a ‘gap’ between 169
the actual and expected output of climate change decision-making, something must be 170
preventing policymaking from attaining an ideal equilibrium, or ‘ideal outcome. Thus, ex ante 171
barriers to climate change adaptation and mitigation are presented in order to explain this gap. 172
According to Biesbroek et al (2015), the key problem with this line of thinking is “that it 173
originates with the normative assumption that collective decision-making at national, regional, 174
and local levels should be producing climate-adaptive decisions and actions (p.493). Overly 175
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linear, functionalist approaches assume that socio-political systems will automatically adjust to 176
changes providing barriers are removed. Unfortunately, the complexities and ambiguities of 177
collective forest management decision-making related to climate changes is reduced to a 178
simple input–output model in which important internal dynamics and processes are absent 179
(Cairney et al 2015). 180
Functionalist Overtures in Williamson and Nelson’s Analysis 181
Despite being largely discredited in social science fields, in particular political science and 182
sociology, functionalism has made a comeback in a growing multi-disciplinary climate change 183
research program that has readily embraced this type of explanation (Smit and Pilifosova 2001; 184
Fussell and Klein 2006; Smith and Wandel 2006; Preston et al 2010). Wellstead et al (2013, 185
2014, 2015) highlighted the functionalist assumptions in the literature examining forestry 186
adaptation frameworks and vulnerability assessments. We speculate that that many non-social 187
science scholars may be unaware of its limitations when trying understand complex social 188
problems (Wellstead et al 2016). Many climate change scholars come from biology and ecology 189
where functionalism is a legitimate form explanation (Elster 1983). Moreover, epistemological 190
debates about functionalism are not widespread in mainstream neo-classical economics, 191
Williamson and Nelson’s discipline. Nonetheless, many economic assumptions about market 192
pertubations leading to equilibrium are functionalist in nature. For example, the market is 193
perceived as an institution that self-attains and self-maintains equilibrium. General equilibrium 194
theory that sustains most economic models assume human interactions by means of demands 195
resulting ultimately in a functional equilibrium. As a result of contingency, complexity, 196
institutional constraints and agency, societies and political systems are erratic and chaotic 197
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systems which completely differ theoretically and empirically with how classical economics 198
picture market interactions (Polanyi 1957). The market system does not subsume socio-political 199
systems but on the contrary, markets are embedded in socio-political systems, which is why 200
markets often do not reach the predicted state of equilibrium due to influences of and 201
interaction with socio-political system where power asymmetry, cognitive biases and limited 202
information hinder economic rationally and perfectly functional markets. The point is that the 203
trap of functionalism is one that many well-meaning scholars fall into. Our goal is to lend a 204
helping hand out. 205
206
Although they refer to forest management, Williamson and Nelson’s (2001) actual unit of 207
analysis is more specifically a political system within a forest management context. Their 208
approach begins with a “normative” overview of an “ultimate outcome” and “ideal outcome” 209
for this system that reflects mainstreaming goals to include adaptation and mitigation 210
considerations in sustainable forest management policies and programs. “Barriers” they argue 211
are “impediments and capacity deficits that can stop, delay, or divert the development and 212
implementation of comprehensive and integrated adaptation and mitigation”(p.1568). Their 213
systematic overview of barriers rightly highlights the challenges associated with mainstreaming 214
climate change into SFM policy-making. To their credit, Williamson and Nelson (2017) 215
acknowledge that overcoming barriers will be a difficult process. However, the key functionalist 216
assumption that the system maintains itself through the consequences that benefit some 217
groups, means that their assessment ultimately treats government and governance as 218
manipulated reactive or automatic system variables. Similar to economic input–output models, 219
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important internal dynamics and processes are absent throughout their paper. Barriers are 220
understood as an input variable inhibiting system-wide adaptation functionality. When 221
removed, SFM goals can be more readily achieved. For example, lack of policy capacity is 222
considered a critical component of the governance barrier which in turn impedes system wide 223
implementation. Williamson and Nelson (2017) state that there are “disconnect between 224
increasing policy mandates associated with climate change and decreasing governance 225
capacity”(p.1572). Their solution is to reduce the disconnects. Policy capacity, like all of the 226
other barriers, is understood as an entity rather than process or activity that leads to actual 227
outcomes rather than ideal outcomes. 228
229
The Way Forward: Thinking Mechanistically 230
Explaining decision-making requires the identification of causal processes that are responsible 231
for producing a certain outcome or effect. Barriers thinking, with its overly reductionist 232
comprehension of the decision-making process, prevents such explanations. There is large 233
social science ‘mechanisms’ literature, which is influenced by the natural sciences and 234
philosophy of science. Mechanisms are sets of entities and activities organized to produce a 235
regular series of changes from a beginning state to an ending (McAdam 2008). They usually 236
“invoke some form of 'causal agent' that is assumed to have generated the observed 237
relationship between the entities and are analytical constructs providing hypothetical links 238
between observable events (Hedström and Swedberg 1998). Often mechanisms are 239
unobservable or hidden phenomena, sensitive to variations in context, but empirically traceable 240
processes that act as a cause in generating the outcome (Pawson and Tilly 1997). Assessing the 241
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logic of association helps us open the black box of the limited X (barriers) → Y (forest 242
management outcomes) causal inferences so prevalent in the barriers literature, and prominent 243
in Williamson and Nelson’s (2017) argument. Causality is not simply a functional description of 244
a certain variable, but requires uncovering how X actually produces Y under specific conditions. 245
Thus, context is important to this relationship and the role it plays in determining outcomes. 246
Initial conditions play a key role in determining how mechanisms are triggered and how they 247
respond to certain contextual conditions. Identifying the context and the mechanism is 248
important when formulating hypotheses. It is critical to understand under what conditions that 249
mechanisms are most likely to occur or produce a particular outcome (Pawson and Tilly 1997). 250
Various scholars have adopted “context-mechanism-outcome” (CMO) approach: namely the 251
observed patterns of (un)intended outcomes can be explained by identifying the plausible 252
causal set of mechanisms within the situational context of the process (Pawson and Tilly 1997; 253
Biesbroek et al 2017) (Figure 1). 254
255
--Figure 1 About Here-- 256
257
This more robust understanding of causality opens up the black boxes of forest management 258
decision-making. In doing so, social scientists will find a diversity of causal mechanisms that 259
affect policy outcomes. There are different broad mechanism types: structural cognitive, and 260
relational. Second, mechanisms can span between micro-level (individual) and macro-level 261
(structural) phenomena (Bunge 1997; Checkel 2006). Given the multi-level nature of climate 262
change decision-making, these mechanisms are particularly important. These are illustrated in 263
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Figure 2. ‘Situational’ mechanisms occur when social structures or environmental phenomenon 264
constrain individuals’ action or shape and beliefs. ‘Action-formation’ mechanisms link 265
individual micro-level activities or behaviour to their actions. 266
267
--Figure 2 About Here-- 268
269
Transformational mechanisms are those in which individuals, through their actions and 270
interactions, generate intended and unintended outcomes. Third, forest social science 271
researchers need to be aware of the temporal nature of mechanisms which includes the time 272
horizons of both the mechanism and outcomes (Pierson 2003; Beach and Pedersen 2013). For 273
example, some slow-moving causal processes result in a threshold event resulting a sudden 274
change. In the social sciences, there are many examples of mechanisms that fit these broad 275
categories. For example, where Williamson and Nelson (2016) refer to inflexible top down 276
traditional modes of governance as a barrier. However, a situational action-formation 277
mechanism such as Robert Dahl’s (1957) well known power resources approach may in part 278
explain utilized a sub-optimal policy outcome. The emergence of new values can be attributed 279
to the role negative feedbacks challenging the long-term stability of policy monopolies is an 280
example of a cognitive transformative mechanism (Baumgartner and Jones 2010). Finally, the 281
intervention by collaborative leaders (a situational action-formation mechanism) can be 282
explained by measurable rational choice models of key officials to maximizing their control of 283
government (Downs 1957), seeking intrinsic rewards of their office (Riker 1962) or the 284
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combination of vote-seeking party, the office-seeking, and policy-seeking behavior (Strom 285
1990). From each of these more specific mechanisms, testable hypotheses can be developed. 286
287
Policy Relevant Research 288
A related problem with the barriers approach is the absence of a rigorous research program 289
that will ultimately inform policy-making. Beyond a long list of barriers, researchers have, 290
without understanding the dynamics and processes hidden in the forest management black 291
box, no way of assessing actual outputs. A mechanism methodological approach allows 292
researchers to pinpoint specific mechanisms and test them. When the mechanisms are 293
understood, analysts can collect diagnostic evidence, theorize variables and empirical proxies, 294
and test hypotheses which then provides a narrative explaining how a particular outcome or set 295
of events came about (Kay and Baker 2014). Beach and Petersen (2013) identify three types of 296
‘process tracing’: theory-testing, theory building, and explaining outcomes. Process tracing is a 297
qualitative technique for capturing causal mechanisms in action (George and Bennett 2005). In 298
some cases, researcher might be interested in a simple change of events related to a single 299
phenomenon. However, in the case of the complex world of sustainable forest management 300
policy-making there often is a convergence of a number of conditions, or complex interactions 301
causal factors (Trampusch and Palier 2016). Theory-testing process tracing is employed when a 302
phenomenon X is causing outcome Y is known but the mechanism is not specified. Since 303
mechanisms are portable concepts, they can applied by policy researchers to further elaborate 304
the long-term nature of policy change. Alternatively, in theory-building process-tracing, the 305
relationship between X and Y is detected but the researcher cannot identify the mechanism or 306
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when the outcome (Y) is known, but X is unknown. In both cases, the researcher develops a 307
new mechanism. Theory building would require considerably more time and effort than theory-308
testing. In explaining-outcome process tracing the outcome (Y) is known but X is unknown or 309
the researcher is interesting in fully explaining why X happened. In each type of process 310
tracing, the analyst will develop a causal mechanism. The second step involves operationalizing 311
the mechanism based on ‘observable manifestation’ from different types of evidence. From 312
collecting such information, the inferential weight of the evidence and the hypotheses can be 313
assessed using four well known tests that apply Bayesian probability (straw-in-the-wind, hoop, 314
smoking gun, and doubly decisive tests) (See Van Evera 1997). These tests examine necessary 315
and/or sufficient conditions for inferring evidence from the hypotheses exist. The principles of 316
certainty and uniqueness of the evidence reflect the necessary and sufficient conditions. The 317
straw-in-the-wind test supports or weakens a hypothesis but does not exclude it. The smoking-318
gun test confirms that the hypothesis but does not exclude other hypotheses. Hoop tests reject 319
a hypothesis but does not influence other hypotheses. Finally, a double-decisive test confirms a 320
single hypotheses and disconfirms other rival hypotheses. 321
322
Often researchers will be interested in comparing a number of cases. For example, comparing 323
climate change policy in a number of jurisdictions. Qualitative Comparative Analysis (QCA) is 324
popular approach which applies set theory and conceives cases as configurations of attributes. 325
QCA examines the necessary and sufficiency of configurations of conditions combine to 326
generate outcomes and enable causal interpretation (Ragin 2014). These popular methods 327
could be incorporated into national-level assessments such as the “Canada in a Changing 328
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Climate: Advancing our Knowledge for Action” assessment currently underway or by local level 329
decision makers interested in integrating climate change into decision-making processes 330
(Gleeson et al 2011). 331
332
Conclusion 333
We agree with Williamson and Nelson’s (2017) claim that the “ability of Canadian forest 334
managers to incorporate climate change considerations into all aspects of sustainable forest 335
management is an open question” (p.1573). In order to answer this question, climate change 336
researchers need to transition from the barriers approach and take up the challenge of 337
identifying specific mechanisms affecting forest management decisions outcomes. 338
A toolkit equipped with well-elaborated mechanisms is not only useful for precision and depth 339
to understand the generative processes of existing theoretical models but is also valuable for 340
empirical research and enhancing decision-making (Tranow et al 2016). This may lead to what 341
Dietz et al (2003) refer to as ‘analytical deliberation’ which provides for “improved information 342
and the trust in it that is essential for information to be used effectively, builds social capital, 343
and can allow deal with inevitable conflicts” (p.1910). Thus, the social scientist and public 344
official can benefit from deeper understanding of causal mechanisms. 345
346
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i Specifically Elster (1986) noted that an institution or a behavioral pattern X is explained by its
function Y for group Z if and only if (1) Y is an effect of X, (2) Y is beneficial for Z, (3) Y is
unintended by the actors producing X, (4) Y (or at least the causal relationship between X and Y)
is unrecognized by the actors in Z, and (5) Y maintains X by a causal feedback loop passing
through Z (p. 28).
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Figure 1 Context Mechanism Output (CMO) model
Source: Pawson and Tilly (1997)
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Figure 2- “Bath tub” approach for identifying different levels of mechanisms
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