As it turns out, the potential use of bowtie frameworks can extend far beyond their usual application to industrial hazards. Those who manage land and water resources encounter ecological risks every day. When these risks from diverse human and natural causes start to pile up and interact (something ecologists call ‘Cumulative Effects’), action is needed. Bowtie frameworks can portray the qualitative dimensions of these interactions to ecosystem managers and stakeholders alike, and support decision-making by quantifying the risks. Bowties have been used to illustrate risks in oceans and lakes, and for processes used to certify sustainable forests. At Natural Resources Canada (Canadian Forest Service, Pacific Forestry Centre), we are studying the application of bowties to the ecological services found in forested landscapes. Bowtie analysis can portray the science/policy interface for critical ecological issues, bringing scientific and regulatory concerns to the common ground of risk analysis and management. In our case, we were particularly interested in a species at risk (threatened caribou in the Canadian boreal forest).
Bowtie and threatened Caribou
In northeastern British Columbia (B.C.), caribou are at the heart of a decades-long conflict between a growing resource sector and associated risks to biodiversity. We have recently published a report applying a bowtie framework and Layers of Protection Analysis (LOPA) to the cumulative ecological risks faced by threatened caribou populations in northeastern B.C. (Figure 1). We applied the analysis at the landscape level, to three 8,000 km2 study areas. Several practical modifications were necessary to make this work. During framework development, we considered both human and natural sources of risk to be parts of the overall system of risk regulation. This allowed us to portray typical forest and caribou management interventions (barriers to risk) in an appropriate context. We also modified standard LOPA procedures, in part using a parallel set of calculations for herd growth rates to reconcile our estimates of probability for barrier failure. This meant that we could use remote sensing data and maps to estimate failure probabilities, while also using demographic data for caribou to fill in knowledge gaps concerning risks. We used all of this information to estimate the cost of improving risk mitigation. We were also able to perform a sensitivity analysis to establish the reliability of our estimates for threat barriers. All of this resulted in a framework relevant to those conversant with risk analysis, as well as those more familiar with the use of demographic information to manage caribou herds.
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Figure 1. A bowtie framework analyzing risks to the sustainability of boreal woodland caribou in northeastern British Columbia, Canada. In the framework components, ‘LOPA factors’ refer to an open-ended LOPA parameter, and lambda (λ) values refer to a demographic parameter (population growth rate) calculated in parallel with LOPA factors. See Winder et al. (2020) for a more detailed description.
Our report concludes that risk mitigation for caribou should involve more than just restoration of human-made linear forest disturbances (for example, traces made during seismic exploration for oil and gas resources). To ensure sustainability of caribou in our study areas, increased efforts to control and exclude predators will be needed in the short term. In the longer term, aggressive improvement of threat barriers (reduction of various disturbances) would also enter the picture. Beyond the caribou question, it is clear to us that bowtie frameworks have much to contribute when it comes to understanding and managing cumulative effects writ large, for many types of ecological problems. For the variety of industrial sectors operating on a land base, policy makers, regulators, and diverse stakeholders alike, it brings everyone to a common ground where the same language can be spoken—the language of risk analysis.
Interested to read the full article of Winder, Stewart, Nebel, McIntire, Dyk and Omendja (2020)? Read it here in the journal Frontiers in Ecology & Evolution.
Winder, R., Stewart, F. E., Nebel, S., McIntire, E. J. B., Dyk, A., & Omendja, K. (2020). Cumulative effects and boreal woodland caribou: How bow-tie risk analysis addresses a critical issue in Canada’s forested landscapes. Frontiers in Ecology and Evolution. https://doi.org/10.3389/fevo.2020.00001