Modelling Spatial Distribution of the Barents Sea Cod Fishery

Eide, Arne

doi:10.1007/978-3-319-11520-7_30

Cited by 6 publications

(19 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Models are used when experiments are costly, require significant labour effort, ethics, and effects of spatial or temporal scales associated. Cellular automata and agent-based models are useful tools for addressing such issues (Bastardie et al, 2013;Convertino et al, 2015;DeAngelis and Yurek, 2015;Eide, 2012Eide, , 2014Moustakas and Silvert, 2011;Moustakas et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

The effects of marine protected areas over time and species' dispersal potential: a quantitative conservation conflict attempt

Moustakas¹

2016

Web Ecol.

View full text Add to dashboard Cite

Abstract. Protected areas are an important conservation measure. However, there are controversial findings regarding whether closed areas are beneficial for species and habitat conservation as well as for harvesting. Species dispersal is acknowledged as a key factor for the design and impacts of protected areas. A series of agent-based models using random diffusion to model fish dispersal were run before and after habitat protection. All results were normalized without the protected habitat in each scenario to detect the relative difference after protecting an area, all else being equal. Model outputs were compared with published data regarding the impacts over time of MPAs on fish biomass. In addition, data on species' dispersal potential in terms of kilometres per year are compared with model outputs. Results show that fish landings of species with short dispersal rates will take longer to reach the levels from before the Marine Protected Areas (MPAs) were established than landings of species with long dispersal rates. Further, the establishment of an MPA generates a higher relative population source within the MPA for species with low dispersal abilities than for species with high dispersal abilities. Results derived here show that there exists a feasible win-win scenario that maximizes both fish biomass and fish catches.

show abstract

Section: Discussionmentioning

confidence: 99%

The effects of marine protected areas over time and species' dispersal potential: a quantitative conservation conflict attempt

Moustakas¹

2016

Web Ecol.

View full text Add to dashboard Cite

show abstract

“…Such concepts enable efficient determination of defined rights to activities and setting proper international standards [46], policies and actions to account for information asymmetries when trying to internalize externalities like the introduction of damaging invasive species [47], and other spatially explicit management interventions for invasive species [48]. Presentations also included principles of marine spatial planning and ecosystembased management in international contexts [49][50][51], and other spatial bio-economic modeling [52].…”

Section: Ecosystem-based Management In a Spatial Context: Questions Fmentioning

confidence: 99%

Spatial issues in Arctic marine resource governance workshop summary and comment

et al. 2015

Self Cite

View full text Add to dashboard Cite

“…The population dynamics of the NEA cod stock are represented by a cellular automata model set up and parameterised on the basis of empirical data from historical catches and research surveys (following Eide, 2014). The time resolution in the model is one month, and a homogeneous grid of 80 km x 80 km cells provides the spatial resolution.…”

Section: Physical Conditions and Biological Dynamicsmentioning

confidence: 99%

“…Following the set up in Eide (2014), zooplankton biomass is used as a proxy for cod food availability in the spatially distributed model. Other constraining factors for the spatial and temporal distribution of NEA cod are ocean temperature and ocean bathymetry.…”

Section: Physical Conditions and Biological Dynamicsmentioning

confidence: 99%

See 1 more Smart Citation

Causes and consequences of fleet diversity in fisheries: The case of the Norwegian Barents Sea cod fishery

Eide

2016

Elementa: Science of the Anthropocene

Self Cite

View full text Add to dashboard Cite

F isheries operate under f luctuating environmental conditions, targeting f ish stocks that appear in varying densities in different areas, often with abrupt and unexpected local changes. Physical conditions, markets and management regulations constrain vessels in different and varying ways. These factors all contribute to forming the f leet diversity we f ind in most f isheries. Here, a simulation model of the Northeast Arctic cod f ishery is used in order to investigate how this diversity is formed and maintained, assuming rational economic behaviour under varying combined constraints. The study also focuses on how the ability of vessels to f ind f ish inf luences f leet diversity, prof itability, stock development and seasonal prof iles of the f ishery. Results indicate that an increased ability to target the most prof itable f ishing grounds may inf luence f leet diversity positively or negatively, depending on overall exploitation level. High exploitation rates also increase the temporal f luctuations in f leet diversity and prof its, which are amplif ied as the f ish-f inding ability increases.

show abstract

Modelling Spatial Distribution of the Barents Sea Cod Fishery

Cited by 6 publications

References 8 publications

The effects of marine protected areas over time and species' dispersal potential: a quantitative conservation conflict attempt

The effects of marine protected areas over time and species' dispersal potential: a quantitative conservation conflict attempt

Spatial issues in Arctic marine resource governance workshop summary and comment

Causes and consequences of fleet diversity in fisheries: The case of the Norwegian Barents Sea cod fishery

Contact Info

Product

Resources

About