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Evaluating Network Analysis Indicators of Ecosystem Status in the Gulf of Alaska

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Abstract

This is the first study on the emergent properties for empirical ecosystem models that have been validated by time series information. Ecosystem models of the western and central Aleutian Islands and Southeast Alaska were used to examine indices of ecosystem status generated from network analysis and incorporated into Ecopath with Ecosim. Dynamic simulations of the two ecosystems over the past 40 years were employed to examine if these indices reflect the dissimilar changes that occurred in the ecosystems. The results showed that the total systems throughput (TST) and ascendancy (A) followed the climate change signature (Pacific decadal oscillation, PDO) in both ecosystems, whereas the redundancy (R) followed the inverse trend. The different trajectories for important species such as Steller sea lions (Eumetopias jubatus), Atka mackerel (Pleurogrammus monopterygius), pollock (Theragra chalcograma), herring (Clupea pallasii), Pacific cod (Gadus macrocephalus) and halibut (Hippoglossus stenolepis) were noticeable in the Finn cycling index (FCI), entropy (H) and average mutual information (AMI): not showing large change during the time that the Stellers sea lions, herring, Pacific cod, halibut and arrowtooth flounder (Atheresthes stomias) increased in Southeast Alaska, but showing large declines during the decline of Steller sea lions, sharks, Atka mackerel and arrowtooth flounder in the Aleutians. On the whole, there was a change in the emergent properties of the Aleutians around 1976 that was not seen in Southeast Alaska. Conversely, the emergent properties of both systems showed a change around 1988, which indicated that both systems were unstable after 1988.

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References

  • Anderson PJ, Piatt JF. 1999. Community reorganization in the Gulf of Alaska following ocean climate regime shift. Marine Ecol Progr Series 189:117–23

    Google Scholar 

  • Christensen V. 1995. Ecosystem maturity−towards quantification. Ecol Model 77:3–32

    Article  Google Scholar 

  • Christensen V, Pauly D. 1992. ECOPATH II−a software for balancing steady-state ecosystem models and calculating network characteristics. Ecol Model 61:169–85

    Article  Google Scholar 

  • Christensen V, Walters CJ. 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecol Model 172:109–39

    Article  Google Scholar 

  • Christensen V, Walters C, Pauly D. 2000. Ecopath with Ecosim: a User’s guide. Vancouver, BC and Penang, Malaysia: Fisheries Centre, University of British Columbia and ICLARM. pp 1–131

  • Christensen V, Walters C, Pauly D. 2005. Ecopath with Ecosim: a User’s guide. Vancouver, BC: Fisheries Centre, University of British Columbia. 154 p

  • Finn JT. 1976. Measures of ecosystem structure and function derived from analysis of flows. J Theor Biol 56:363–80

    Article  PubMed  CAS  Google Scholar 

  • Guénette S. 2005. Model of Southeast Alaska. In: Guénette S, Christensen V, Eds. The Steller sea lion decline: models and data of the Northeast Pacific Fisheries Centre Research Reports 13(1). p 106–78

  • Guénette S, Heymans SJJ, Christensen V, Trites A. 2006. Ecosystem models show combined effects of fishing, predation, competition, and ocean productivity on Steller sea lions (Eumetopias jubatus) in Alaska. Can J Fish Aquatic Sci 63:2495–517

    Article  Google Scholar 

  • Hare SR, Mantua NJ. 2000. Empirical evidence for North Pacific regime shifts in 1977 and 1989. Progr Oceanogr 47:103–45

    Article  Google Scholar 

  • Heymans JJ. 2003. Comparing the Newfoundland-Southern Labrador marine ecosystem models using information theory. In: Heymans JJ, Ed. Ecosystem models of Newfoundland and Southeastern Labrador (2J3KLNO): additional information and analyses for “back to the future”. vol. 11(5): Fisheries Centre Research Reports. pp 62–71

  • Heymans JJ. 2005. Ecosystem model of the Western and Central Aleutian Islands in 1963, 1979 and 1991. In: Guénette S, Christensen V, Eds. The Steller sea lion decline: models and data of the Northeast Pacific Fisheries Centre Research Reports 13(1). pp 8–82

  • Heymans JJ, Ulanowicz RE, Bondavalli C. 2002. Network analysis of the South Florida Everglades graminoid marshes and comparison with nearby cypress ecosystems. Ecol Model 149(1/2):5–23

    Article  Google Scholar 

  • Heymans JJ, Guénette S, Christensen V, Trites A. 2005. Changes in the Gulf of Alaska ecosystems due to ocean climate change and fishing. ICES CM 2005(M22):1–31

  • Latham LGI, Scully EP. 2002. Quantifying constraint to assess development in ecological networks. Ecol Model 154:25–44

    Article  Google Scholar 

  • Mageau MT, Costanza R, Ulanowicz RE. 1998. Quantifying the trends expected in developing ecosystems. Ecol Model 112(1):1–22

    Article  Google Scholar 

  • Murie OJ. 1959. Fauna of the Aleutian Islands and Alaska Peninsula. North Am Fauna US Fish Wildlife Service 61:1–406

    Google Scholar 

  • Odum EP. 1969. The strategy of ecosystem development. Science 164:262–70

    Article  PubMed  CAS  Google Scholar 

  • Proulx SR, Promislow DEL, Phillips PC. 2005. Network thinking in ecology and evolution. Trends Ecol Evol 20(6):345–53

    Article  PubMed  Google Scholar 

  • Ulanowicz RE. 1986. Growth and development: ecosystems phenomenology. Lincoln, NE: toExcel Press. 203p

  • Ulanowicz RE. 1997. Ecology, the ascendant perspective. Allen TFH, Roberts DW, eds. New York: Columbia University Press. 201p

  • Ulanowicz RE. 2000. Toward the measurement of ecological integrity. In: Pimentel D, Westra L, Noss RF, eds. Ecological integrity: integrating environment, conservation, and health. Washington DC: Island Press. pp 99–113

    Google Scholar 

  • Ulanowicz RE. 2001. Information theory in ecology. Computers Chem 25:393–9

    Article  CAS  Google Scholar 

  • Ulanowicz RE. 2004. Quantitative methods for ecological network analysis. Comput Biol Chem 28:321–39

    Article  PubMed  CAS  Google Scholar 

  • Ulanowicz RE, Abarca-Arenas LG. 1997. An informational synthesis of ecosystem structure and function. Ecol Model 95:1–10

    Article  Google Scholar 

  • Ulanowicz RE, Kay JJ. 1991. A package for the analysis of ecosystem flow networks. Environ Software 6(3):131–42

    Article  Google Scholar 

  • Ulanowicz RE, Norden JS. 1990. Symmetrical overhead in flow networks. Int J Systems Sci 21(2):429–37

    Article  Google Scholar 

  • Ulanowicz RE, Puccia CJ. 1990. Mixed trophic impacts in ecosystems. Coenoses 5(1):7–16

    Google Scholar 

  • Vasconcellos M, Mackinson S, Sloman K, Pauly D. 1997. The stability of trophic mass-balance models of marine ecosystems: a comparative analysis. Ecol Model 100:125–34

    Article  Google Scholar 

  • Walters C, Kitchell JF. 2001. Cultivation/depensation effects on juvenile survival and recruitment: implications for the theory of fishing. Can J Fish Aquat Sci 58:39–50

    Article  Google Scholar 

  • Walters C, Christensen V, Pauly D. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Rev Fish Biol Fish 7:139–72

    Article  Google Scholar 

  • Walters C, Pauly D, Christensen V, Kitchell JF. 2000. Representing density dependent consequences of life history strategies in aquatic ecosystems: EcoSim II. Ecosystems 3:70–83

    Article  Google Scholar 

  • Welch DW, Ward BR, Smith BD, Eveson JP. 2000. Temporal and spatial responses of British Columbia steelhead (Oncorhynchus mykiss) populations to ocean climate shifts. Fish Oceanogr 9:17–32

    Article  Google Scholar 

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Acknowledgments

This paper was prepared under Award Number NA16FX0124/NA16FX2629 from the National Oceanic and Atmospheric Administration, US Department of Commerce through the North Pacific Universities Marine Mammal Research Consortium. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration or the Department of Commerce. The authors wish to thank Pat Livingston, Kerim Aydin, Sarah Gaishas, Ivonne Ortiz and other scientists from the NMFS Alaska Fisheries Science Center in Seattle, WA for their help and access to data. We also wish to acknowledge the various scientists from the Alaska Department of Fish and Game, Glacier Bay National Park, the Department of Fisheries and Oceans, Andrew Trites and the Marine Mammal Research Unit and the Fisheries Centre at the University of British Columbia for data, advice and other help.

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Correspondence to Johanna Jacomina Heymans.

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Heymans, J.J., Guénette, S. & Christensen, V. Evaluating Network Analysis Indicators of Ecosystem Status in the Gulf of Alaska. Ecosystems 10, 488–502 (2007). https://doi.org/10.1007/s10021-007-9034-y

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