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Content archived on 2024-06-18

Social complexity in Resource Management

Final Report Summary - SOCORM (Social complexity in Resource Management)

This research projects started from the observation that in some instances, government intervention is effective in conserving renewable natural resources, such as fish stock, but not in others. We argue that government intervention does not take place in a vacuum, as sets of social norms may exist that govern resource use. Success or failure of government intervention depends crucially on how this intervention interacts with the local set of social norms and biological complexity. We hypothesize that these social norms are shaped by the state and dynamics of the natural resources and hence co-evolve with these resources. The key objective of this project was to analyze how decisions of resource users are influenced by the biological and institutional environment. Specifically, we aimed to identify, first, under which conditions social norms of resource exploitation evolve; second, how quickly these social norms adapt and respond to environmental changes; and third, how government intervention interacts with these social norms.

Real world observations indicate that social norms of cooperation can be effective in overcoming social dilemmas such as the joint management of a common pool resource – but also that they can be subject to slow erosion and sudden collapse. In one of our papers we show that these patterns of erosion and collapse emerge endogenously in a model of a closed community harvesting a renewable natural resource. Individual agents face the temptation to overexploit the resource, while a cooperative harvesting norm spreads through the community via interpersonal relations. We analyze under what circumstances small changes in key parameters (including the size of the community, and the rate of technological progress) trigger catastrophic transitions from relatively high levels of cooperation to widespread norm violation –causing the social-ecological system to collapse.

An important refinement has been made in a second paper by considering individuals to be conditionally cooperative, which has been highlighted in experimental and observational studies. We formalize this mechanism in a theoretical model that portrays a small community having joint access to a common pool resource. The diffusion of norms of cooperation takes place via interpersonal relations, while individual agents face the temptation of higher profits by overexploiting the resource. Agents remain conditionally cooperative, unless other individuals are misbehaving already. We can observe a bubble of conditional cooperators slowly building up followed by a sudden burst, which means that a transition from a cooperative social norm to non-cooperation occurs. Interestingly, in some parameter regions alternative stable states and limit cycles arise. The latter implies that the same community goes through such a transition repeatedly over long time spans – history thus repeats itself in the form of the creation and erosion of social capital.

These two papers provided exciting results, but did not answer two important questions. First, how do social and ecological complexity mutually influence each other? Second, can a sudden collapse be anticipated – and if so how? These challenging questions have been addresses in a third paper. Indeed, a common pattern of environmental crises is a vicious cycle between environmental degradation and socio-economic disturbances. For example, environmental changes may drive fish stocks to a low productive regime that can lead to sudden losses in the livelihoods of coastal communities. This ecological transition in turn erodes social institutions, such as social norms of cooperation, with cascading pressure on the resource base. We show that while such feedbacks may give rise to critical transitions in social-ecological systems, at the same time they can offer novel opportunities for anticipating them. We model a community that has joint access to the harvest grounds of a resource that is prone to collapse. Individuals are tempted to overexploit the resource, while a cooperative harvesting norm spreads through the community via interpersonal relations. Both social and ecological collapses can be induced by environmental and socio-economic driving forces. Regardless of the type and cause of collapse we find that upcoming transitions may be detected using simple socio-economic response variables, such as individual profits. At the same time, adaptive behavior of resource users may mask signs of a nearby resource collapse. Our findings suggest that social-ecological systems not only hide vulnerabilities to collapse as changes spread from one system to the other, but that they may also provide alternative sources of information that can be used to detect upcoming critical transitions.

Finally, we have taking a closer look on how formal policy should be designed when one takes into account biological and also social complexity for the case of the Northeast Arctic cod fishery. First, we developed a bio-economic model that evaluates current harvest control rule (HCR) that was adopted in 2004 by the Joint Norwegian–Russian Fishery Commission to manage the world's largest cod stock, Northeast Arctic cod (NEA). The model is biologically and economically detailed, and is the first to compare the performance of the stock's current HCR with that of alternative HCRs derived with optimality criteria. In particular, HCRs are optimized for economic objectives including fleet profits, economic welfare, and total yield and the emerging properties are analyzed. The performance of these optimal HCRs was compared with the currently used HCR. This paper show that the current HCR does in fact comes very close to maximizing profits. Furthermore, the results reveal that the HCR that maximizes profits is the most precautionary one among the considered HCRs. Finally, the HCR that maximizes yield leads to un-precautionary low levels of biomass. In these ways, the implementation of the HCR for NEA cod can be viewed as a success story that may provide valuable lessons for other fisheries.

We have added social complexity by considering that a fishing fleet comprises different heterogeneous stakeholders and is not necessarily one entity – as the bulk of literature assumes. In fact, a major challenge of fisheries management is to understand how fleet structure affects optimal harvesting strategies, and equally important, how different vessels are affected by a policy change. Typically, vessels differ considerably in terms of efficiency, environmental impacts, and profitability. We develop a model that allows us to determine the optimal allocation of individual vessel quotas for a diverse fleet, for a variety of management objectives (e.g. maximizing long-run profits with or without environmental and/or employment constraints). We specifically take into account the occurrence of a fleet lock in, which means that the fishing fleet cannot be adjusted instantaneously, as several vessels cannot leave the fleet because of economic or political constraints.

We have added biological complexity by investigating how optimal policy should reflect the propensity of the fish stock to undergo genetic change. Fish stocks experiencing high fishing mortality show a tendency to mature earlier and at a smaller size, which may have a genetic component and therefore long-lasting economic and biological effects. To date, the economic effects of such eco-evolutionary dynamics have not been empirically investigated. Using 70 years of data, we develop a bio-economic model for Northeast Arctic cod to compare the economic yield in a model in which life-history traits can vary only through phenotypic plasticity with a model in which, in addition, genetic changes can occur. We find that evolutionary changes towards faster growth and earlier maturation occur consistently even if a stock is optimally managed. However, if a stock is managed optimally, the evolutionary changes actually increase economic yield because larger growth and earlier maturation raise the stock’s productivity. The optimal fishing mortality is almost identical for the evolutionary and non-evolutionary model and substantially lower than what it has been historically. Therefore, the costs of ignoring evolution under optimal management regimes are negligible. However, if fishing mortality is as high as it has been historically, evolutionary changes may result in economic losses, but only if the fishery is selecting for medium sized individuals. As evolution facilitates growth, the fish are younger and still immature when they are susceptible of getting caught. This outweighs the increase in productivity due to fish spawning at an earlier age.

To sum up, we have contributed new academic insights that are or will be published in the best academic journals. At the same time, we have combined theoretical work with an applied study on the Barents Sea ecosystem, which is a valuable natural resource and the habitat of North East Arctic (NEA) cod. Our focus on NEA cod is appealing for several reasons. First, it is currently the world’s largest cod stock, providing a valuable source of food not only to Europe, but for the whole world. Second, it is jointly managed by Russia and Norway, and an important source of income for both countries. Finally, management plans for NEA cod are regularly assessed and revised. Therefore, any results coming from this research can be used directly in the government policy setting process. This research has therefore met the overarching aim of enhancing the long term sustainable management of biological resources in Europe.