Indigenous knowledge on marine systems and Bayesian applications

Climate change disrupts ecological dynamics, rendering IK, rooted in historical observations, inaccurate in predicting marine resource availability and access. While ICs will adapt and update their knowledge, this process may lag behind the rapid pace of environmental change. This disparity hinders wellbeing from marine resource utilization. Integrating IK with observations or employing Bayesian methods to integrate it with empirical data offers a nuanced approach to climate resilience.

Bayesian applications in a marine context could encompass establishing a prior distribution for sustainable harvest, grounded in IK. In the face of uncertainties surrounding measurements of this harvest quantity, Bayes’ rule can be applied to combine these into a posterior distribution. Despite inherent difficulties, the translation of knowledge and perceptions into prior distributions has been explored [3]. Bayesian elicitation requires statements translatable into probabilistic terms–a challenge given the diverse forms IK takes (beliefs, species’ behavior, habitat knowledge, ice conditions, oral traditions, cultures). The challenge for successful Bayesian applications is to translate this input into probabilistic terms while acknowledging implicit uncertainties.

Fairness and distributional equity in fisheries allocations

Fairness and equity in fisheries rights’ distribution are persistent concerns across Arctic ICs, with climate change exacerbating disparities. Shifting fish stock distribution, including poleward shifts and establishment of new harvestable species, induces socioecological changes involving both opportunities and losses [4,5]. These are further complicated by colonial histories that have shaped Indigenous fishery allocations. New allocations must be approached with sensitivity to historical contexts and economic tools can help navigate these complexities. Insights from economics research [6] exploring wealth accumulation and distribution can help clarify how historical wealth disparities persist and shape today’s landscape.

While existing fishery management plans often integrate equity principles, robust definitions and tools to address equity in practice are absent. In anticipation of more pronounced effects of climate change in the Arctic, there is an urgent need to proactively design policies that minimize conflicts from shifts in fish stock abundance and distribution. Economic approaches can aid in this direction, depending on the definition of equity and scope considered [7].

Commonly used inequality metrics include the Lorenz curve and the Gini coefficient assessing benefit distribution among different fishing groups. Generalized entropy measures (i.e. Theil index) identify disparities within and between fishing groups, while the Atkinson index considers society’s aversion to inequality in assessing distribution of fishing benefits. The Herfindahl-Hirschman index assesses the concentration of fishing rights while the Robin Hood index gauges the redistributive impact of fisheries management measures. Ratios such as decile dispersion highlight the disparity between the most and least privileged fisher groups, while the Palma and 20/20 ratio provide insights into distributional disparities in fisheries benefits and the disparity between the most and least affluent fisher groups, respectively. The index choice depends on context, data availability and relevant equity aspects [7]. In general, the notion of a uniform distribution as fair is narrow with many arguing for progressivity, where lower percentiles (less privileged groups) receive greater percentage of benefits. Importantly, Indigenous perspectives may diverge from conventional income-centric approaches encompassing considerations such as historical connection and access to harvest grounds. Such differences highlight the need to understand alternative notions of equity and develop suitable measurement methods.

Beyond inequality indices, impact assessments, including fishery economic assessment models, social accounting matrices and computable general equilibrium models are other tools capturing the sector’s economic impacts [8]. Economic impact assessments can help understand climate change effects on the wellbeing of Arctic ICs. This involves assessing various indicators, including income, employment and other economic factors associated with fisheries. Income and wealth distribution analyses identify disparities and assess whether fisheries’ benefits are equitably distributed. Input-Output analyses enable understanding of economic linkages and impacts of changes in the fishing industry on other sectors and the overall economy [7]. While insightful, these tools have limitations, especially in small ICs where data are scarce. Their focus on transfer payments rather than consumer and producer surplus hinders estimation of net benefits and allocation decisions. Additionally, income impacts, often used as a surplus proxy, may overstate consumer or producer value. These tools also overlook economic efficiency considerations, such as minimizing production costs or optimally allocating resources. Despite these drawbacks, they offer a useful framework for understanding fishing sector linkages and evaluating the economic impact of management decisions.

Arctic coastal/ocean predictions and value of information

Forecast tools predicting weather, ice conditions and other marine or oceanographic parameters that inform the status of resources have revolutionized the climate resilience of Arctic ICs. While essential for safe resource access, sustaining these tools in remote Arctic areas is challenging due to high costs and limited infrastructure. Despite evident benefits of predictions to Indigenous wellbeing, communicating these to secure investments in sustaining forecast systems requires a compelling tool. The Value of Information (VOI) serves this purpose, demonstrating the difference in economic consequences of adopting a policy action, with-and-without the knowledge from investments in prediction and research [9].

Sea ice forecasts aid harvesters in navigation planning, temperature and ocean forecasts help optimize fishing seasons, and predictions of extreme weather events enhances preparedness, safeguarding infrastructure and coastal habitats. Continued investments in such forecast systems supporting climate resilience hinge on understanding their benefits.

Assessing the VOI on climate scenarios and their impact on fish stocks allows communities to adapt fisheries management strategies effectively, minimizing overexploitation through redistributing harvest across time and space. Similarly, VOI for more accurate stock assessments and migration patterns improves harvesting patterns enhancing long-term sustainability. The VOI also empowers communities to lead conservation efforts by integrating weather forecasts with fisheries management plans, preventing unnecessary stress on fish populations during vulnerable times.

Early warning systems for Harmful Algal Blooms are critical to human health, particularly for subsistence and recreational harvesters [10], as observed in Alaska. Beyond just commercial shellfish harvest testing, timely risk identification underscores the benefits of forecast programs, contributing to climate resilience, food security and preservation of economic, social, and cultural values [11].