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Landscape Ecology

, Volume 28, Issue 3, pp 507–517 | Cite as

Spatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges

  • Samuel NicolEmail author
  • Jennifer K. Roach
  • Brad Griffith
Research Article

Abstract

Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring in National Wildlife Refuges in Alaska. We estimated power for large (930–4,560 sq km) study areas within refuges and for 2.6, 12.9, and 25.9 sq km cells nested within study areas over temporal extents of 4–50 years. We found that: (1) trends in study areas could be detected within 5–15 years, (2) trends smaller than 2.0 %/year would take >50 years to detect in cells within study areas, and (3) there was substantial spatial variation in the time required to detect change among cells. Power was particularly low in the smallest cells which typically had the fewest lakes. Because small but ecologically meaningful trends may take decades to detect, early establishment of long-term monitoring will enhance power to detect change. Our results have broad applicability and our method is useful for any study involving change detection among variable spatial and temporal extents.

Keywords

Statistical power Mixed model Lake drying Alaska Temporal sampling Regional trend Trend detection Climate change 

Notes

Acknowledgments

Funding was provided by the U.S. Fish and Wildlife Service and the U.S. Geological Survey. Special thanks to Jay Ver Hoef for his comments on an early draft of this manuscript. Use of trade names does not imply endorsement by the U.S. Geological Survey.

Supplementary material

10980_2013_9853_MOESM1_ESM.docx (2 mb)
Supplementary material 1 (DOCX 1999 kb)

References

  1. Carroll ML, Townshend JRG, DiMiceli CM, Loboda T, Sohlberg RA (2011) Shrinking lakes of the Arctic: Spatial relationships and trajectory of change. Geophys Res Let 38:L20406CrossRefGoogle Scholar
  2. Elmberg J, Nummi P, Pöysä H, Sjöberg K (1994) Relationships between species number, lake size and resource diversity in assemblages of breeding waterfowl. J Biogeogr 21:75–84CrossRefGoogle Scholar
  3. Fairweather P (1991) Statistical power and design requirements for environmental monitoring. Mar Freshwater Res 42(5):555–567CrossRefGoogle Scholar
  4. Hinzman L, Bettez N, Bolton W, Chapin F, Dyurgerov M, Fastie C, Griffith B, Hollister R, Hope A, Huntington H, Jensen A, Jia G, Jorgenson T, Kane D, Klein D, Kofinas G, Lynch A, Lloyd A, McGuire A, Nelson F, Oechel W, Osterkamp T, Racine C, Romanovsky V, Stone R, Stow D, Sturm M, Tweedie C, Vourlitis G, Walker M, Walker D, Webber P, Welker J, Winker K, Yoshikawa K (2005) Evidence and implications of recent climate change in northern Alaska and other arctic regions. Clim Chang 72(3):251–298CrossRefGoogle Scholar
  5. Hodges JI, King JG, Conant B, Hanson HA (1996) Aerial surveys of waterbirds in Alaska 1957–94: population trends and observer variability. National Biological Service Information and Technology, Report 4Google Scholar
  6. Jassby AD (1998) Interannual variability at three inland water sites: implications for sentinel ecosystems. Ecol Appl 8(2):277–287CrossRefGoogle Scholar
  7. Johnson DH, Grier JW (1988) Determinants of breeding distributions of ducks. Wildlife Monogr 100:3–37Google Scholar
  8. Karl TR, Derr VE, Easterling DR, Folland CK, Hofmann DJ, Levitus S, Nicholls N, Parker DE, Withee GW (1995) Critical issues for long-term climate monitoring. Clim Chang 31(2):185–221CrossRefGoogle Scholar
  9. Kaufman DS, Schneider DP, McKay NP, Ammann CM, Bradley RS, Briffa KR, Miller GH, Otto-Bliesner BL, Overpeck JT, Vinther BM, Members ALkP (2009) Recent warming reverses long-term arctic cooling. Science 325(5945):1236–1239PubMedCrossRefGoogle Scholar
  10. Klein E, Berg E, Dial R (2005) Wetland drying and succession changes across the Kenai Peninsula Lowlands, south-central Alaska. Can J For Res 35:1931–1941CrossRefGoogle Scholar
  11. Niemuth ND, Wangler B, Reynolds RE (2010) Spatial and temporal variation in wet area of wetlands in the Prairie Pothole Region of North Dakota and South Dakota. Wetlands 30:1053–1064CrossRefGoogle Scholar
  12. Osterkamp TE (2005) The recent warming of permafrost in Alaska. Glob Planet Chang 49(3–4):187–202CrossRefGoogle Scholar
  13. Overpeck J, Hughen K, Hardy D, Bradley R, Case R, Douglas M, Finney B, Gajewski K, Jacoby G, Jennings A, Lamoureux S, Lasca A, MacDonald G, Moore J, Retelle M, Smith S, Wolfe A, Zielinski G (1997) Arctic environmental change of the last four centuries. Science 278(5341):1251–1256CrossRefGoogle Scholar
  14. Peterman RM (1990) Statistical power analysis can improve fisheries research and management. Can J Fish Aquat Sci 47(1):2–15CrossRefGoogle Scholar
  15. Pinheiro J, Bates D (2000) Mixed-effects models in S and S-PLUS. Springer, New YorkCrossRefGoogle Scholar
  16. Pospahala R, Anderson D, Henny C (1974) Population ecology of the mallard: breeding habitat conditions, size of the breeding populations, and production indices. US Fish and Wildlife Service Resources 115Google Scholar
  17. R Development Core Team (2011) R: A language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  18. Riordan B, Verbyla D, McGuire AD (2006) Shrinking ponds in subarctic Alaska based on 1950–2002 remotely sensed images. J Geophys Res 111:G04002. doi: 10.1029/2005JG000150 CrossRefGoogle Scholar
  19. Roach J (2011) Lake area change in Alaskan National Wildlife Refuges: magnitude, mechanisms and heterogeneity. University of Alaska Fairbanks, DissertationGoogle Scholar
  20. Roach J, Griffith B, Verbyla D, Jones J (2011) Mechanisms influencing changes in lake area in Alaskan boreal forest. Glob Chang Biol 17(8):2567–2583CrossRefGoogle Scholar
  21. Roach J, Griffith B, Verbyla D (2012) Comparison of three methods for long-term monitoring of boreal lake area using Landsat TM and ETM + imagery. Can J Remote Sens 38(4):427–440Google Scholar
  22. Rover J, Ji L, Wylie BK, Tieszen LL (2011) Establishing water body areal extent trends in interior Alaska from multi-temporal Landsat data. Remote Sens Lett 3(7):595–694CrossRefGoogle Scholar
  23. Serreze MC, Walsh JE, Chapin FS, Osterkamp T, Dyurgerov M, Romanovsky V, Oechel WC, Morison J, Zhang T, Barry RG (2000) Observational evidence of recent change in the northern high-latitude environment. Clim Chang 46(1):159–207CrossRefGoogle Scholar
  24. Smith L, Sheng Y, MacDonald GH, Hinzman LD (2005) Disappearing Arctic Lakes. Science 308(5727):1429PubMedCrossRefGoogle Scholar
  25. Steidl RJ, Hayes JP, Schauber E (1997) Statistical power analysis in wildlife research. J Wildl Manage 61(2):270–279CrossRefGoogle Scholar
  26. Stoddard JL, Driscoll CT, Kahl JS, Kellogg JH (1998) Can site-specific trends be extrapolated to a region? An acidification example for the Northeast. Ecol Appl 8(2):288–299CrossRefGoogle Scholar
  27. Suter W (1994) Overwintering waterfowl on Swiss lakes: how are abundance and species richness influenced by trophic status and lake morphology? Hydrobiologia 279(280):1–14CrossRefGoogle Scholar
  28. Urquhart NS, Paulsen SG, Larsen DP (1998) Monitoring for policy-relevant regional trends over time. Ecol Appl 8(2):246–257Google Scholar
  29. Wagner T, Bence J, Bremigan M, Hayes D, Wilberg M (2007) Regional trends in fish mean length at age: components of variance and the statistical power to detect trends. Can J Fish Aquat Sci 64:968–978CrossRefGoogle Scholar
  30. Wagner T, Vandergoot C, Tyson J (2009) Evaluating the power to detect temporal trends in fishery-independent surveys: a case study based on gill nets set in the Ohio waters of Lake Erie for walleyes. N Am J Fish Manag 29:805–816CrossRefGoogle Scholar
  31. Weatherhead EC, Reinsel GC, Meng XL, Tiao GC, Choi D, Cheang WK, Keller T, DeLuisi J, Wuebbles DJ, Kerr JB, Miller AJ, Oltmans SJ, Frederick JE (1998) Factors affecting the detection of trends: statistical considerations and applications to environmental data. J Geophys Res 103(D14):17149–17161CrossRefGoogle Scholar
  32. Wiens J (1989) Spatial scaling in ecology. Funct Ecol 3(4):385–397CrossRefGoogle Scholar
  33. Yoshikawa K, Hinzman LD (2003) Shrinking thermokarst ponds and groundwater dynamics in discontinuous permafrost near Council, Alaska. Permafrost Periglac 14(2):151–160CrossRefGoogle Scholar
  34. Zhou L, Tucker CJ, Kaufmann RK, Slayback D, Myneni RB, Tucker CJ (2001) Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. J Geophys Res 106(D17):20069–20083CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht (outside the USA) 2013

Authors and Affiliations

  • Samuel Nicol
    • 1
    • 3
    Email author
  • Jennifer K. Roach
    • 1
  • Brad Griffith
    • 2
  1. 1.Institute of Arctic BiologyUniversity of Alaska FairbanksFairbanksUSA
  2. 2.U.S. Geological Survey, Alaska Cooperative Fish and Wildlife Research UnitUniversity of Alaska FairbanksFairbanksUSA
  3. 3.CSIRO Ecosystem SciencesBrisbaneAustralia

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