Rate this item
(2 votes)

Potential Salmon Collapse

Main Contributors:

Daniele Crimella, Linnéa Joandi, Hanna Kylin, Kavita Oehme, Hanna Kylin

Other Contributors:

Reinette (Oonsie) Biggs, Jennifer Griffiths, Garry Peterson, Juan Carlos Rocha, Jennifer Griffiths


The potential regime shift in Alaska occurs in the marine system of the North Pacific Ocean. The present regime is characterised by a high abundance of salmon while a potential regime would be characterised by a low abundance of salmon. This is a speculative shift that has not yet occurred. The key feedbacks that maintains the current regime is the reinforcing loop of salmon population dynamics. Feedback mechanism are also present between the local communities´ needs, fishery regulation, salmon population and hatcheries´ effect. The key drivers that could cause the regime shift include climatic anomalies and extremes, fishing pressure, reduced population heterogeneity, variations in primary production, demand for food, the use of hatcheries, global warming, and changes in salmon population structure. Some possible leverage points for intervention to prevent this regime shift involves management concerned with fisheries, hatcheries and global warming.

Type of regime shift

  • Potential salmon fishery collapse

Ecosystem type

  • Marine & coastal

Land uses

  • Fisheries

Spatial scale of the case study

  • Sub-continental/regional (e.g. southern Africa, Amazon basin)

Continent or Ocean

  • North America
  • Pacific Ocean


  • Alaska, North East Pacific Ocean


  • United States

Locate with Google Map


Key direct drivers

  • Harvest and resource consumption
  • Adoption of new technology
  • Global climate change

Land use

  • Fisheries


Ecosystem type

  • Marine & coastal

Key Ecosystem Processes

  • Nutrient cycling


  • Biodiversity

Provisioning services

  • Fisheries

Cultural services

  • Aesthetic values
  • Knowledge and educational values

Human Well-being

  • Food and nutrition
  • Livelihoods and economic activity
  • Cultural, aesthetic and recreational values
  • Social conflict
  • Cultural identity

Key Attributes

Spatial scale of RS

  • Local/landscape
  • Sub-continental/regional

Time scale of RS

  • Years
  • Decades


  • Hysteretic


  • Models
  • Paleo-observation
  • Contemporary observations

Confidence: Existence of RS

  • Speculative – Regime shift has been proposed, but little evidence as yet

Confidence: Mechanism underlying RS

  • Contested – Multiple proposed mechanisms, reasonable evidence both for and against different mechanisms

Alternate regimes

Salmon abundance

This regime is characterized by abundant populations of all the different species of salmon that are present along the Alaskan coast. Apart from natural oscillations, populations are stable, as the life cycle is not critically influenced by human activities, rather, they are mainly limited by natural mortality causes such as predation, disease, or density-dependent effects (Quinn 2011). In this scenario, the ecological functions in the different ecosystems they are part of are maintained (e.g. Holtgrieve & Schindler 2011; Quinn 2011). The local fishery is profitable for companies, and in turn grants good livelihoods to local communities. At the same time, their food security needs are met through sustenance. Fishing practice, and the cultural, educational and recreational values are kept through the practice of fishing (Griffiths 2014, pers. comm.). Management successfully implements long-term sustainability of the fishery, hatchery recruitment is limited as natural recruitment is preferred (Schindler et al. 2008; Schindler et al. 2010).


Salmon depletion

In this potential regime, the adult individuals in the ocean offshore Alaska are reduced to consistently low numbers, and variability in population numbers through time is high (Schindler et al. 2010). Anthropogenic drivers that are external to the salmon life cycle are the ones that mainly drive the system (Schindler et al. 2008; Rogers et al. 2013). High rates of fishing strongly decrease adult salmon stocks, especially in areas where management fails to implement measures of sustainability (e.g. fishing quotas, hatcheries regulation). Hatcheries have a prominent role in recruitment, harming populations heterogeneity and resilience, making them increasingly vulnerable (Schindler et al. 2010). Global warming has a strong impact on primary productivity and smolt migration behavior, leading to reduced survival. The local fisheries are in a bad economic situation. The general income for local communities from the fishing industry dramatically decreases and there is a general decrease in people’s wellbeing on aspects related to the practice of fishing.

Drivers and causes of the regime shift

The primary drivers of this potential regime shift would be changes in oceanic conditions (Kilduff et al. 2014) and overfishing (Schindler et al. 2010). The second climatic regime shift of the North Pacific in 1989 caused widespread fluctuations in fish population numbers, although it was regarded as a minor shift compared to the first one in 1976-77 (Ruggerone et al. 2007). However, the decline in population numbers may have been amplified by unsustainable fishing (Litzow et al. 2014) causing alternations in population structures and functions (Schildler et al. 2008).

With this in mind when regarding the future it can be suggested that the ongoing global warming potentially will effect both the oceanic and fresh-water conditions of the salmon habitats (Post et al. 2009). As the timing of smolt migration is crucial for population recruitment (Kilduff et al. 2014), increased unpredictability in oceanic water conditions due to a warming climate may cause declining survival rates of smolt at the ocean entry stage (Kilduff et al. 2014) and therefore put stress on the population. In addition to this, the populations’ resilience to natural variability may be reduced by fishing (Schindler et al. 2010), meaning that the effects of changes in water conditions might put more stress on the population than it would have had under pristine conditions. However, overfishing on its own could also cause population collapse due to e.g. tropic cascades, causing shifts in top-down or bottom-up structures of the ecosystem, or Allee effect, meaning that low numbers of reproductively mature adults leads to reduced rates in population growth. Other important causes for a regime shift could be reduced genetic and behavioural diversity (Schindler et al. 2010) due to the extensive use of hatcheries. As only a part of the returning adults are selected to hatcheries, the groups of smolt released from this artificial spawning will have a lower genetic diversity than a group resulting from natural spawning (Wild Salmon Centre 2014).

How the regime shift worked

Salmon population dynamics in the Alaskan system maintain equilibrated number of individuals, if the system is not affected by external anthropogenic disturbances, as paleo-records show (Rogers et al. 2013). Alaskan local communities have needs in terms of food security, income, recreation, education, and other. To cover for these needs they rely on fishing as their main activity (Schindler et al. 2010), and salmon not only has a value in food and nutrition, but also is one of the major drivers of the local economy, ensuring several aspects of wellbeing (Schindler et al. 2010). These needs therefore cause the necessity for fishing economically valuable salmon at their life stage of adulthood. At the same time, being identified as a common pool resource, there is a necessity to apply management on the resource, to avoid potential issues of non-excludability and conflict among users. Management therefore regulates the fishery using as proxy the amount of salmon returning upstream to spawn (Schindler et al. 2010). To sustain high enough levels of catch hatching activity is also implemented by management (Schindler et al. 2008). These variables related to the social drivers of the system are mutually affected through feedback systems.

Global warming, enhanced by human activity, affects population dynamics mainly in two ways. On the one hand migration from rivers to oceans in the smolt stage is affected due to increased variability of environmental signals for migration (Post et al. 2009) whereas Alaskan salmon smolts migrating too early show less survival at the critical ocean entry stage than those that migrate later (Kilduff et al. 2014). On the other hand, increased climate variability affecting oceanic currents patterns varies the amount of nutrients in these areas and in turn ecosystem productivity. Less productive waters determine lower survival of smolts as they enter the ocean (Kilduff et al. 2014).

The drivers act simultaneously on the populations, leading them in an escalating loop of lower survival of juveniles, low abundance of adults and reduced population heterogeneity (Krosek & Drake 2014). This high instability of population dynamics would make it difficult to reverse the trend into the desirable state of abundance (Griffiths 2014, pers. comm.). Loss of key ecosystem services and failure of societal objectives would be an inevitable consequence (Schindler et al. 2010).

Impacts on ecosystem services and human well-being

A regime with a high abundance of salmon benefits the societies in terms of cultural, provisioning and regulating ecosystem services. It also profits them concerning employment, pest regulation, food-web regulating mechanisms, biodiversity and regulation of hypoxia (Schindler et al. 2010; MA 2006).

As fish stocks become depleted due to overfishing, and before the hatcheries manage to level out the discrepancy, the relational dynamic of fishermen and governing institutions might possibly change. If the governing institutions that manage the fish stocks stop the fishing temporarily, or lower the fishing quotas, the relationship between the fishermen and institutions risk to become worse due to a mismatch between the fishermen´s needs, and the governments management (their wants). A conflict is consequently more likely to arise (Chun & Choi, n.d). In other words, their relational wellbeing, defined as peoples´ “satisfaction with relationships”, is likely to be negatively affected (De Leersnyder et al. 2014: 242). In sum, the fishing communities, and less resilient ecosystems, might accordingly be the long run loser of the SES. Loss of species´ heterogeneity, intensified climate change and increased fishing pressure makes the system more sensitive to perturbation. A less resilient system might, ultimately, lead to a decrease in salmon stocks and consequently, have negative impacts on food security, economic activity, cultural ecosystem services and cultural identity (Hilborn et al. 2003; Kelty & Kelty 2011). i.e., if losing the provisioning ecosystem service, an aspect of human wellbeing that is concerned with the food- and economic security in this case, the communities will not only risk to lose the regulating-, but also the cultural values. The latter one is part of subjective wellbeing (Villamagna&Giesecke 2014). However, subjective wellbeing is also concerned with peoples´ own satisfaction of their situation (Villamagna & Giesecke 2014). If they lose the salmon, there is a high risk that they consider themselves worse off than before. Thus the loss of the providing ecosystem service would not only affect the material-, but also the subjective well-being. Relational wellbeing is yet another aspect of human wellbeing that will be affected.






Management options

Alaska Department of Fish and Game (ADFG) acts to maintain an abundant salmon population (ADFG, 2014). To keep salmon population stable management in Alaska mainly acts in two ways. One management action is through fishery regulations and quotas. Fishing quotas are primarily set by the ADFG who regulates the amount of fish to catch each year (ADFG 2014). Quotas are partly set dependent on salmon abundance in the ocean. One way to assess salmon abundance is by counting returning spawners (Schindler et al. 2010). Another management action is connected to Alaska’s salmon hatcheries. Alaskan hatcheries were introduced some decades ago as one way to maintain abundant salmon populations. The hatcheries are mostly used as way to complement natural recruitment and to enhance Alaska’s commercial fisheries and the economical opportunities that follow (ADFG 2014). When natural recruitment fails to maintain high abundance of salmon, increased management through hatchery recruitment can maintain abundant salmon populations (Griffiths, 2014, pers. comm.).

There are different actions to take in order to return to abundant salmon populations if collapse of salmon populations in Alaska would occur. Firstly, a ban on salmon fishing would have to be implemented in order to save what is left (Schindler et al. 2010). ADFG controls fishery management in the region and actions taken would emerge from this department. Co-management, to include local stakeholders, could be central in order to build trust, solve potential conflicts that could occur and to join forces in solving the problem of how to adapt to the low abundance of salmon (Berkes 2009). Secondly, if hatcheries have been managed in ways that caused a decrease in heterogeneity between and within salmon populations, this could cause a potential collapse of salmon. In this case management would have to be modified. Hatchery management would have to have focus on a higher degree of diversity when selecting individuals to breed. This would increase heterogeneity between and within future salmon populations. Increased heterogeneity builds more resilient populations (Schindler et al. 2008; Schindler et al. 2010). Thirdly, changes in ocean conditions due to global warming could lead to a decreased smolt survival at the ocean entry stage (Kilduff et al. 2014) that could lead to a potential salmon collapse. In order to reach a stop to global warming international management must be implemented (IPCC 2014).

Key References

  1. ADFG (2014). Alaska department of game and fishery. State of Alaska, USA. Web 01 Dec 2014.
  2. Bakun, A., Field, D. B., REDONDO‐RODRIGUEZ, A. N. A., & Weeks, S. J. (2010). Greenhouse gas, upwelling‐favorable winds, and the future of coastal ocean upwelling ecosystems. Global Change Biology, 16(4), 1213-1228.
  3. Berkes, F. (2009). Evolution of co-management: Role of knowledge generation, bridging organizations and social learning. Journal of environmental management, 90(5), 1692-1702.
  4. Brenner, R. E., Moffitt, S. D., & Grant, W. S. (2012). Straying of hatchery salmon in Prince William Sound, Alaska. Environmental Biology of Fishes, 94(1), 179-195.
  5. Chun, J., & Choi, J. (n.d). Members' Needs, Intragroup Conflict, and Group Performance. Journal Of Applied Psychology, 99(3), 437-450.
  6. Cooney, R., & Brodeur, R. (n.d). Carrying capacity and North Pacific salmon production: Stock-enhancement implications. Bulletin Of Marine Science, 62(2), 443-464.
  7. De Leersnyder, J., Mesquita, B., Kim, H., Eom, K., & Choi, H. (2014). Emotional fit with culture: A predictor of individual differences in relational well-being. Emotion, 14(2), 241-245. doi:
  8. FAO. 2012. The state of world fisheries and aquaculture. UN Food & Agriculture Organization.
  9. Friedland, K. D., Ward, B. R., Welch, D. W. & Hayes, S. A. (2014). Postsmolt Growth and Thermal Regime Define the Marine Survival of Steelhead from the Keogh River, British Columbia. Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, 6(1), 1-1.
  10. Grant WS (2012) Understanding the adaptive consequences of ecological interactions between hatchery and wild salmon in Alaska. Environ Biol Fish, Volume 94, Issue 1, pp 325-342.
  11. Gunderson, H. Leslie, J. Norberg, M. Nystrom, P. Olsson, H. Osterblom, M. Scheffer, and B. Worm. (2006). Ecology - Globalization, roving bandits, and marine resources. Science 311:1557–1558.
  12. Gunderson, L. H., Garmestani, A., Rizzardi, K. W., Ruhl, J., & Light, A. (2014). Escaping a Rigidity Trap: Governance and Adaptive Capacity to Climate Change int he Everglades Social Ecological System [article]. Idaho Law Review, (1), 127.
  13. Heard, W. (2012). Overview of salmon stock enhancement in southeast Alaska and compatibility with maintenance of hatchery and wild stocks. Environmental Biology Of Fishes, 94(1), 273. doi:10.1007/s10641-011-9855-6.
  14. Hilborn, R., Quinn, T. P., Schindler, D. E., & Rogers, D. E. (2003). Biocomplexity and Fisheries Sustainability. Proceedings of the National Academy of Sciences of the United States of America, (11). 6564.
  15. Hirokawa, K. H. (2011). Sustaining Ecosystem Services Through Local Environmental Law. Pace Environmental Law Review, 28760.
  16. Hobbie, J. E. (2014). Alaska's Changing Arctic : Ecological Consequences for Tundra, Streams, and Lakes. New York: Oxford University Press.
  17. Holtgrieve, G. W., & Schindler, D. E. (2011). Marine-derived nutrients, bioturbation, and ecosystem metabolism: reconsidering the role of salmon in streams. Ecology, 92(2), 373-385.
  18. Hutchings, J. A., & Reynolds, J. D. (2004). Marine fish population collapses: consequences for recovery and extinction risk. BioScience, 54(4), 297-309.
  19. Kelty, R., & Kelty, R. (2011). Human dimensions of a fishery at a Crossroads: Resource valuation, Identity, and way of life in a seasonal fishing community. Society And Natural Resources, 24(4), 334-348. doi:10.1080/08941920903476814.
  20. Kilduff, D. P., Botsford, L. W., & Teo, S. L. (2014). Spatial and temporal covariability in early ocean survival of Chinook salmon (Oncorhynchus tshawytscha) along the west coast of North America. ICES Journal of Marine Science: Journal du Conseil, fsu031.
  21. Kirby, R. R., Beaugrand, G., & Lindley, J. A. (2009). Synergistic effects of climate and fishing in a marine ecosystem. Ecosystems, 12(4), 548-561.
  22. Kofinas, G. P., Chapin III, F. S., BurnSilver, S., Schmidt, J. I., Fresco, N. L., Kielland, K., & ... Rupp, T. S. (2010). Resilience of Athabascan subsistence systems to interior Alaska's changing climate. Canadian Journal Of Forest Research, 40(7), 1347-1359. doi:10.1139/X10-108.
  23. Krkošek, M., & Drake, J. M. (2014). On signals of phase transitions in salmon population dynamics. Proceedings of the Royal Society B: Biological Sciences, 281(1784), 20133221.
  24. Krupa, M., Stuart Chapin III, F., & Lovecraft, A. (2014). Robustness or resilience? Managing the intersection of ecology and engineering in an urban Alaskan fishery. Ecology And Society, 19(2), doi:10.5751/ES-06274-190217.
  25. Litzow, M. A., Mueter, F. J., & Hobday, A. J. (2014). Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal‐scale biological variability. Global change biology, 20(1), 38-50.
  26. Morita, K., Nagasawa, T., Tamate, T., & Kuroki, M. (2014). Temperature-dependent variation in alternative migratory tactics and its implications for fitness and population dynamics in a salmonid fish. Journal Of Animal Ecology, 83(6), 1268-1278. doi:10.1111/1365-2656.12240.
  27. Pauly, D., J. Alder, A. Bakun, S. Heileman, K. Koch, P. Mace, W. Perrin, K. Stergiou, U. Sumaila, M. Vierros, K. Freire, Y. Sadovy, V. Christensen, K. Kaschner, M. Palomares, P. Tyedmers, C. Wabnitz, R. Watson, and B. Worm. 2006. Chapter 18: Marine Fisheries Systems. Pages 1–35 in R. Hassan, R. Scholes, and N. Ash, editors. Millennium Ecosystem Assessment. Island Press, Washington, D.C.
  28. Peterman, R. M., Dorner, B., & Rosenfeld, J. S. (2012). A widespread decrease in productivity of sockeye salmon ( Oncorhynchus nerka) populations in western North America. Canadian Journal Of Fisheries & Aquatic Sciences, 69(8), 1255-1260. doi:10.1139/f2012-063.
  29. Post, E., Forchhammer, M. C., Bret-Harte, M. S., Callaghan, T. V., Christensen, T. R., Elberling, B. & Aastrup, P. (2009). Ecological dynamics across the Arctic associated with recent climate change. Science, 325(5946), 1355-1358.
  30. Quinn, T. P. (2011). The behavior and ecology of Pacific salmon and trout. UBC Press.
  31. Rand, P., Berejikian, B., Pearsons, T., & Noakes, D. (2012). Ecological interactions between wild and hatchery salmonids: An introduction to the special issue. Environmental Biology Of Fishes, 94(1), 1-6. doi:10.1007/s10641-012-9987-3.
  32. Rogers, L. A., Schindler, D. E., Lisi, P. J., Holtgrieve, G. W., Leavitt, P. R., Bunting, L., Finneyd, B. P., Selbiee, D.T., Chenf, G., Gregory-Eavesf, I., Lisach, M. J., & Walsh, P. B. (2013). Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries. Proceedings of the National Academy of Sciences, 110(5), 1750-1755.
  33. Ruggerone, G. T., Nielsen, J. L., & Bumgarner, J. (2007). Linkages between Alaskan sockeye salmon abundance, growth at sea, and climate, 1955–2002. Deep Sea Research Part II: Topical Studies in Oceanography, 54(23), 2776-2793.
  34. Schindler, D. E., Augerot, X., Fleishman, E., Mantua, N. J., Riddell, B., Ruckelshaus, M., Seeb, J. & Webster, M. (2008). Climate change, ecosystem impacts, and management for Pacific salmon. Fisheries, 33(10), 502-506.
  35. Schindler, D. E., Hilborn, R., Chasco, B., Boatright, C. P., Quinn, T. P., Rogers, L. A., & Webster, M. S. (2010). Population diversity and the portfolio effect in an exploited species. Nature, 465(7298), 609-612. doi:10.1038/nature09060.
  36. Villamagna, A., & Giesecke, C. (2014). Adapting Human Well-being Frameworks for Ecosystem Service Assessments across Diverse Landscapes. Ecology And Society, 19(1).
  37. Walker, B., Gunderson, L., Kinzig, A., Folke, C., Carpenter, S., & Schultz, L. (2006). A handful of heuristics and some propositions for understanding resilience in social-ecological systems. Ecology and society, 11(1), 13.
  38. Wild Salmon Centre (2014). Wild Salmon Centre, Portland, Oregon, USA. Web 10 Dec 2014.
  39. Yatsu, A., Aydin, K. Y., King, J. R., McFarlane, G. A., Chiba, S., Tadokoro, K., ... & Watanabe, Y. (2008). Elucidating dynamic responses of North Pacific fish populations to climatic forcing: Influence of life-history strategy. Progress in Oceanography, 77(2), 252-268.
  40. Zabel, R. W., Tyler, W., Congleton, J. L., Smith, S. G., & Williams, J. G. (2005). Survival and Selection of Migrating Salmon from Capture-Recapture Models with Individual Traits. Ecological Applications, (4). 1427.
  41. [Untitled photograph1 of Fisherman with salmon catch]. (n.d.). Retrieved November 27, 2014, from
  42. [Untitled photograph2 of Salmon that migrate]. (n.d.). Retrieved November 27, 2014, from,_Oncorhynchus_tshawytscha.jpg
  43. [Untitled photograph3 of Adult salmon]. (n.d.). Retrieved November 27, 2009, from


Daniele Crimella, Linnéa Joandi, Hanna Kylin, Kavita Oehme, Hanna Kylin, Reinette (Oonsie) Biggs, Jennifer Griffiths, Garry Peterson, Juan Carlos Rocha, Jennifer Griffiths. Potential Salmon Collapse. In: Regime Shifts Database, Last revised 2017-02-07 12:43:18 GMT.
Read 3314 times
Login to post comments