Roles of density-dependent growth and life history evolution in accounting for fisheries-induced trait changes

The relative roles of density dependence and life history evolution in contributing to rapid fisheries-induced trait changes remain debated. In the 1930s, northeast Arctic cod (Gadus morhua), currently the world’s largest cod stock, experienced a shift from a traditional spawning-ground fishery to an industrial trawl fishery with elevated exploitation in the stock’s feeding grounds. Since then, age and length at maturation have declined dramatically, a trend paralleled in other exploited stocks worldwide. These trends can be explained by demographic truncation of the population’s age structure, phenotypic plasticity in maturation arising through density-dependent growth, fisheries-induced evolution favoring faster-growing or earlier-maturing fish, or a combination of these processes. Here, we use a multitrait eco-evolutionary model to assess the capacity of these processes to reproduce 74 y of historical data on age and length at maturation in northeast Arctic cod, while mimicking the stock’s historical harvesting regime. Our results show that model predictions critically depend on the assumed density dependence of growth: when this is weak, life history evolution might be necessary to prevent stock collapse, whereas when a stronger density dependence estimated from recent data is used, the role of evolution in explaining fisheries-induced trait changes is diminished. Our integrative analysis of density-dependent growth, multitrait evolution, and stock-specific time series data underscores the importance of jointly considering evolutionary and ecological processes, enabling a more comprehensive perspective on empirically observed stock dynamics than previous studies could provide

A bio-economic analysis of harvest control rules for the Northeast Arctic cod fishery

Harvest control rules (HCRs) have been implemented for many fisheries worldwide. However, in most instances, those HCRs are not based on the explicit feedbacks between stock properties and economic considerations. This paper develops a bio-economic model that evaluates the HCR adopted in 2004 by the Joint Norwegian-Russian Fishery Commission to manage the world's largest cod stock, Northeast Arctic cod (NEA). The model considered here is biologically and economically detailed, and is the firt 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 profit, 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 fishries

Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management

Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). while the number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently in fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behavior, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause fisheries-induced evolution with effects accumulating over time. Consequently, FIE may alter then utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons, An important reason this is not happening is the lack of an appropriate assessment framework. We therefor describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary outcomes of alternative management options. EvoIA can contribute to the ecosystem approach to fisheries management by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries

Global connectivity and cross-scale interactions create uncertainty for Blue Growth of Arctic fisheries

The Arctic faces high expectations of Blue Growth due to future projections of easier access and increased biological productivity. These expectations are, however, often based on global and regional climate change projections and largely ignore the complexity of social-ecological interactions taking place across different temporal and spatial scales. This paper illustrates how such cross-scale interactions at, and across, different dimensions (e.g., ecological, socioeconomic and governance) can affect the development of Arctic fisheries; and potentially create uncertainties for future Blue Growth projections. Two Arctic marine systems, The Barents Sea and the Central Arctic Ocean (CAO), are used as focus areas. The former hosts productive fisheries and is mostly covered by the EEZs of Norway and Russia, while the latter is still mainly covered by sea-ice and is a high seas area with no multilevel governance system in place. The examples show that, both systems are affected by a number of processes, beyond the environmental change, spanning a wide range of dimensions, as well as spatial and temporal scales. To address the complexity of the Arctic marine systems calls for an increase in holistic scientific understanding together with adaptive management practices. This is particularly important in the CAO, where no robust regional management structures are in place. Recognizing how cross-scale dynamics can cause uncertainties to the current fisheries projections and implementing well-functioning adaptive management structures across different Arctic sub-systems can play a key role in whether the Blue Growth potential in Arctic fisheries is realized or lost

A bio-economic analysis of harvest control rules for the Northeast Arctic cod fishery

Harvest control rules (HCRs) have been implemented for many fisheries worldwide. However, in most instances, those HCRs are not based on the explicit feedbacks between stock properties and economic considerations. This paper develops a bio-economic model that evaluates the HCR adopted in 2004 by the Joint Norwegian-Russian Fishery Commission to manage the world's largest cod stock, Northeast Arctic cod (NEA). The model considered here 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 merging 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 unprecautionary 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 fisherie

Population growth across heterogeneous environments: effects of harvesting and age structure

Population growth is affected by several factors such as climate, species interaction and harvesting pressure. However, additional complexity can arise if fishing increases the sensitivity to environmental variability. To predict the effects of fisheries and climate on marine populations, there is a need for improved understanding of how they affect key ecological processes such as population growth. In this study, we used a comparative approach investigating commercially fished species across different ecosystems: the Norwegian Sea−Barents Sea (Northeast Arctic cod), the North Sea (North Sea cod), the Atlantic Ocean (European hake), the Mediterranean Sea (European hake), and the Gulf of Alaska and Bering Sea (walleye pollock). Our objective was to compare the effects of commercial fisheries, age structure and environmental variability on population growth rate. We show that although all stocks experienced a decline in abundance, only 3 of them showed a concomitant decreasing trend in generation time (South Atlantic hake, North Atlantic hake and Northeast Arctic cod), suggesting a fishing-induced erosion in their age structure. Intra-specific analysis shows that changes in generation time triggered an increase in the relative contribution of recruitment to population growth. Furthermore, the contribution from recruitment to population growth changes due to large-scale climate indices or regional-scale environmental covariates, such as sea temperature. This study illustrates how and where the interaction between large-scale ecological patterns and regional/short-scale processes are important for designing management regulationsPublicado