Policy Uncertainty and Risk: Conceptual Developments and Approaches

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The second part of the survey was completed during the remote workshop and focused on understanding the relative importance of breeding, migrating, and overwintering life stages to support regional population abundance and distribution of forest birds in the study area. These questions were posed to provide a better context for understanding the influence of impacts on the breeding range, the area of focus for monitoring and over which agencies have some degree of management control, relative to other life stages where no monitoring would occur and over which agencies have little influence.

The relative importance of life stages was assessed using the analytical hierarchy process AHP , which required presenting all pairwise comparisons of life stages and then asking experts to indicate which are more important and the degree of importance using a standardized five-point scale, ranging from equally important to extremely more important Pavlikakis and Tsihrintzis Responses from multiple experts were combined by calculating the geometric mean of importance for each pair across all respondents.

Expert ratings were then entered into a pairwise comparison matrix to facilitate calculation of weightings for each individual life stage. This part of the survey also included assessing the relative importance of 19 stressors that were identified as having a potential impact on quality of breeding habitats. These ratings were made using a 5-point importance scale, ranging from not at all important to extremely important.

The last part of the survey asked participants to rank the relative importance of each of 16 pathways of effect. Given the complexity of this task, we applied a maximum difference conjoint approach MDC; Finn and Louviere Like AHP, the MDC is an iterative approach; however, it relies on experimental design principles to reduce the burden on respondents. With this approach, respondents were asked to identify the pathways they considered to be most and least important from 16 sets of 4 pathways. To ensure the independence of each parameter estimate, each combination of pathways was determined by an experimental design Raktoe et al.

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To reduce the possibility of biases associated with learning or fatigue effects Louviere et al. Statistical analysis of MDC surveys is grounded in random utility theory McFadden , which assumes that people choose the single option that maximizes their benefits. Under this assumption, the probability of an individual choosing one option i from a set of alternatives may follow a multinomial logit MNL function Louviere and Woodworth In the case of the MDC, the choice probability of the least important pathway is assumed to be inversely related to its benefits Cohen The resulting statistical model estimates underlying preferences by comparing each particular attribute value relative to a specified base.

In our case, effects coding was used to center the resulting parameters around a mean of zero Bech and Gyrd-Hansen The resulting model provided preference estimates on an interval scale for each pathway with constants accounting for the effect of list order Cohen The MDC portion of the survey was administered using the Delphi method Linstone and Turoff , in which experts were first asked to independently respond to a set of structured questions.

Data were analyzed in real time with the group convened on the phone shortly afterward to review results and encouraged to share with others why and how they answered the questions.

Policy uncertainty and risk : conceptual developments and approaches

They were then asked to break away again to review their initial responses and allowed to adjust them based on what was heard from others. Through this process, the experts identified two distinct types of pathways in the conceptual models that were not originally framed as such: pathways by which forest bird habitats are disturbed by various forms of human development and causal mechanisms related to the ecological responses of forest birds to habitat pressures.

To address this feedback, additional questions were developed with responses completed approximately two weeks later. These additional questions required experts to rate the strength of influence and certainty of evidence related to the causal mechanisms underlying each of eight habitat pathways of effect. For each pathway, causal mechanisms were rated using five-point scales to represent the strength of influence, ranging from none to dominant, and certainty of evidence related to understanding the causal mechanism, which was rated as theoretically a concern, evidence is ambiguous, evidence is preliminary, evidence is strong, or widespread agreement.

Across all parts of the survey, a fist-to-five voting system was used to gauge the level of agreement around the emerging responses from the group, with a fist representing a vote of no support and five fingers representing the strongest level of support. Fourteen conceptual models were developed at a hierarchy of scales to represent the complexity of the system: one ecosystem, two landscape, two bird guild, and nine species models. A systems model was used for the ecosystem level to illustrate the breadth of human stressors and natural drivers that influence the study area.

A state and transition model was used for the landscape level to represent habitat states and transitional processes that influence habitat dynamics, whereas a life cycle model was used to represent population dynamics for the migratory and resident terrestrial species occupying the study area.

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Life cycle models were also used for the guild and species levels to represent interactions between the environment and all forest and wetland dependent birds that migrate annually from or through the study area. We focus on results related to the forest bird, i. Other models are provided in Appendix 1. The forest bird model is provided in Figure 3. The top left portion shows an annual life cycle separated into key life stages: breeding, fall migration, overwintering, and spring migration.

An inner ring represents the period until juveniles start breeding. Survival and fecundity have direct influences on populations arrows to the center , whereas changes in condition have indirect influences through their effect on subsequent life stages arrows to other life stages. Alternatively, fecundity is influenced both by the condition that birds are in when they return from overwintering and conditions on the breeding grounds themselves. Regional population outcomes, as opposed to continental outcomes, are the end points of interest because many migratory species have wide summer breeding ranges that are subject to different stressors in the boreal forest.

Human stressors and natural drivers are illustrated in the right portion of the model. These influences have the potential for impacts on summer breeding, migration, and overwintering as mediated by pathways resulting from impacts on habitat, health, and behavior. Broadscale monitoring is intended to provide information on the role and relative influence of various forcings on migratory birds: mining, forestry, agriculture, urbanization, and conventional oil and gas development, alongside oil sands development and an extensive transportation network to support these sectors.

To facilitate this understanding, we adapted the International Union for Conservation of Nature threats classification system Salafsky et al.

An alignment of development sectors with these stressors provided a way of clarifying the many overlapping interactions with migratory birds see Table A1. Major sources of these stressors include forest harvesting, oil sands development, conventional oil and gas, and the transportation network, with minor sources from mining, agriculture, and other forms of human use. Impacts on habitat include loss, transformation, and degradation. Impacts on survival include different sources of human-induced mortality, e. Impacts on nesting are influenced by the availability of habitat and processes that interfere with successful nesting.

Underlying mechanisms of influence include predation or parasitism of nests, destruction of nests by human actions or severe weather, detrimental changes in habitat quality, or disturbance as a result of human intrusion. Because of its breadth, the forest bird model lacked the specificity required to inform the model weighting process with experts. Using this generic model, we identified 8 distinct habitat pathways of effect Table 1 and 11 related causal mechanisms Table 2 affecting life-stage and population-level responses. The habitat pathways of effect were distinguished according to their spatial scale of effect, type of habitat impact, and form of habitat disturbance based on the sector of origin.

The full set of habitat pathways is summarized in more detail in Table A1.


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Results from a series of structured exercises with experts were used to derive weightings of importance of different components in the forest bird model to inform priorities for monitoring. On a linear scale between 0 and 1, the weighting of 3 life stages indicated that experts, in aggregate, placed relatively more importance on pathways influencing breeding bird habitats 0. A fist-to-five vote revealed a somewhat divergent and moderate level of support for these results with an average support of 3. This finding led to reanalysis of the data that revealed 2 contrasting opinions of experts, with group 1 weighting the breeding life stage as most important 0.

On a linear 5-point scale from not at all important to extremely important, 19 stressors were rated by experts based on their anticipated impact on the quality of breeding habitats in the study area Fig. The most important stressor, patch clearing, was consistently rated by experts as extremely important because of the potential for direct loss of nesting sites.

The next important stressors, rated as more than somewhat important, included vegetation extraction, water management, and linear clearing because of their impact on availability of nesting sites; pesticides, soil disturbance, and water pollution because of their impact on foraging activities and food sources; and linear infrastructure and traffic because of their direct impact on survival.

All other stressors were rated as less than somewhat important, specifically human intrusion, introductions, animal extraction, noise, dust, light, air emissions, soil contamination, solid waste, and structures. For several stressors, there was a wide variation in responses across experts, which included vegetation extraction, linear clearing, pesticides, soil disturbance, and water management.


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  7. A vote revealed a relatively strong and consistent level of support for these rankings across experts, with an average of 3. Parameter estimates in the model were rescaled to derive an interval scale of importance ranging from 1 least important to 8 most important. A process of ranking was repeated on 3 occasions to encourage experts to share information and learn from each other.

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    Variation standard error in responses across experts declined, and the relative ranking of pathways changed with each iteration of the exercise Fig. For the final iteration, habitat alterations as a result of agriculture and forestry were rated as having the strongest relative importance, with effects at the stand level pathways D and F being more important than the landscape level pathways E and G. Pathways associated with industrial development pathways A and B were rated as slightly less important than top-rated pathways, but significantly higher than stand-level impacts on habitat quality pathway C and landscape-level transformations as a result of changing fire dynamics pathway H.

    Despite minor variations, patterns in the relative strength of influence of different causal mechanisms were largely similar across the eight habitat pathways. Expert judgments on the most influential causal mechanisms underlying stand-level conversion as a result of industrial development pathway A are shown in Figure 7.

    Habitat-mediated mechanisms leading to displacement and either complete mechanism a or partial mechanism b loss were consistently rated as having a major influence. A reduction in fecundity mechanism k was seen as being moderately influential, whereas dispersal mechanism c , food mechanism i , direct mortality mechanism j , and predation at varying ages mechanisms d and e were rated as having less influence. Parasitism mechanism f , weather mechanism g , and climate mechanism h were rated as having the weakest influence on this pathway. Developing visualizations to represent complexity of the study area was extremely challenging and time consuming.

    Session 1: Workshop Objectives and Challenges

    Although systems thinking encourages a more holistic representation of a system, the level of model completeness and complexity had to be balanced against the need for comprehension and simplicity to support clear communication. Technical experts demonstrate this dichotomy by advocating for simple conceptual models, yet simultaneously requiring that such models reflect observed complexities.

    More broadly, the realities of natural resource management also suggest that complex systems should be managed in a more holistic and integrated way but require simplification and prioritization to identify key variables that account for most changes Mitchell et al. In our research, conceptual model development provided a clear framework for representing the ecosystem using a solid foundation of scientific evidence and expert opinion.

    No level of complexity was seen as best serving all audiences and purposes. Rather, multiple models with a range of complexities were developed to provide a strong foundation from which to structure the elicitation of expert judgments and to serve the communication needs of other audiences, meeting the primary purpose of using the models to inform the monitoring program design. A hierarchy of conceptual models proved useful for characterizing the ecosystem because it forced a decrease in breadth and an increase in specificity at each level in the model and allowed for the use of different models at different scales.

    For instance, species-level models were the most detailed but also the easiest to develop because they were constrained in scope, grounded in the structure of the guild-level models, and supported with readily available summaries of evidence. The simultaneous development of our suite of models, from ecosystem level to species level, created several advantages. Internal coherence was the principle design advantage, especially the obvious linkages from the landscape- to the species-level models.

    This coherence helped enforce comprehensiveness and rigor across all models by ensuring a common typology and framework to accurately represent the many species, habitats, drivers, and stressors within the ecosystem. The relatively detailed mechanistic structure of the models clarified the cumulative and interactive nature of factors influencing migratory birds both within and outside the study area.

    Within the study area, this approach emphasized how multiple industries produce the same types of stressors. However, the spatial extent of development, size of the study area, and the sometimes overlapping and sometimes spatially clustered land uses mean it will be difficult to find suitable reference areas to make regional population inferences.

    The approach also enabled a clear representation of carryover effects across life stages Norris and the significant influence of factors outside of the oil sands area for one-half to three-quarters of the annual calendar for most migratory birds, including significant mortality during migration periods Sillet and Holmes Although the mechanistic approach facilitated development of individual pathways of effect within the breeding season, which was needed to engage experts in the near term and inform priorities for the monitoring program in the longer term, a disadvantage is that few data are available to support partitioned modeling of the system in detail.

    Therefore, direct links with existing landscape simulation models incorporating birds are limited but are growing as an emerging property of the monitoring efforts achieved in the area L. Mahon, personal communication. Engagement of technical experts at selective points in our research facilitated and strengthened conceptual model development Fig.