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Aquatic Sciences

, Volume 76, Issue 1, pp 145–154 | Cite as

Phosphorus loading, transport and concentrations in a lake chain: a probabilistic model to compare management options

  • Stephen R. CarpenterEmail author
  • Richard C. Lathrop
Research Article

Abstract

Phosphorus (P) loading, exports and concentrations of the four lakes of the Yahara chain (Wisconsin, USA) were compared under four load-reduction plans using a model calibrated with 29–33 years of annual data. P mitigation goals must balance reductions in P concentrations in the four lakes and the export from the lake chain to downstream waters. Lake Mendota, the uppermost lake, is most responsive to P load reductions, and benefits diminish downstream. Nonetheless, the greatest reductions in export from the lake chain to downstream waters derive from P load reductions to lakes lower in the chain. The effective grazer Daphnia pulicaria causes large improvements in water quality. Management to maintain populations of D. pulicaria has substantial benefits that augment those from reductions in P loading. Model projections show high variability in water quality and exports under all load-reduction plans. This variability is driven by inter-annual variation in runoff. Thus lake managers and the public should expect ongoing year-to-year variability in water quality, even though P load mitigation will improve water quality on average. Because of high variability from year to year, ongoing monitoring is essential to assess the effects of management of this chain of lakes.

Keywords

Lakes Landscape limnology Phosphorus Water quality 

Notes

Acknowledgments

Our work was supported by the US National Science Foundation through the North Temperate Lakes Long-Term Ecological Research Program and the Water Science and Sustainability program, and by the Wisconsin Department of Natural Resources.

References

  1. Alvarez-Cobelas M, Cirujano S, Rojo C, Rodrigo MA, Piña E, Rodríguez-Murillo JC, Montero E (2006) Effects of changing rainfall on the limnology of a Mediterranean, flowthrough-seepage chain of lakes. Int Rev Hydrobiol 91(5):466–482. doi: 10.1002/iroh.200510836 CrossRefGoogle Scholar
  2. Belmont MA, White JR, Reddy KR (2009) Phosphorus sorption and potential phosphorus storage in sediments of Lake Istokpoga and the Upper Chain of Lakes, Florida, USA. J Environ Qual 38(3):987–996. doi: 10.2134/jeq2007.0532 PubMedCrossRefGoogle Scholar
  3. Box GEP, Tiao GC (1973) Bayesian inference in statistical analysis. Wiley, New YorkGoogle Scholar
  4. Cardille JA, Carpenter SR, Coe MT, Foley JA, Hanson PC, Turner MG, Vano JA (2007) Carbon and water cycling in lake-rich landscapes: landscape connections, lake hydrology, and biogeochemistry. J Geophys Res 112Google Scholar
  5. Carpenter S, Lathrop R (2008) Probabilistic estimate of a threshold for eutrophication. Ecosystems 11(4):601–613. doi: 10.1007/s10021-008-9145-0 CrossRefGoogle Scholar
  6. Carpenter SR, Lathrop RC, Nowak P, Bennett EM, Reed T, Soranno PA (2006) The ongoing experiment: restoration of Lake Mendota and its watershed. In: Magnuson JJ, Kratz TK, Benson BJ (eds) Long-term dynamics of lakes in the landscape. Oxford University Press, LondonGoogle Scholar
  7. Carpenter SR, Benson BJ, Biggs R, Chipman JW, Foley JA, Golding SA, Hammer RB, Hanson PC, Johnson PTJ, Kamarainen AM, Kratz TK, Lathrop RC, McMahon KD, Provencher B, Rusak JA, Solomon CT, Stanley EH, Turner MG, Vander Zanden MJ, Wu C-H, Yuan H (2007) Understanding regional change: a comparison of two lake districts. Bioscience 57(4):323–335. doi: 10.1641/b570407 CrossRefGoogle Scholar
  8. Chapra SC, Reckhow KH (1983) Engineering approaches for lake management. Mechanistic modeling, vol 2. Butterworth, BostonGoogle Scholar
  9. Choulik O, Moore TR (1992) Response of a subarctic lake chain to reduced sewage loading. Can J Fish Aquat Sci 49(6):1236–1245. doi: 10.1139/f92-139 CrossRefGoogle Scholar
  10. Einola E, Rantakari M, Kankaala P, Kortelainen P, Ojala A, Pajunen H, Mäkelä S, Arvola L (2011) Carbon pools and fluxes in a chain of five boreal lakes: a dry and wet year comparison. J Geophys Res Biogeosci 116 (G3):G03009. doi: 10.1029/2010jg001636
  11. Epstein D, Neilson B, Goodman K, Stevens D, Wurtsbaugh W (2013) A modeling approach for assessing the effect of multiple alpine lakes in sequence on nutrient transport. Aquat Sci 75(2):199–212. doi: 10.1007/s00027-012-0267-2 CrossRefGoogle Scholar
  12. Fisher MM, Miller SJ, Chapman AD, Keenan LW (2009) Phytoplankton dynamics in a chain of subtropical blackwater lakes: the Upper St, Johns River, Florida, USA. Lake Reservoir Manage 25(1):73–86CrossRefGoogle Scholar
  13. Forbes SA (1887) The lake as a microcosm. Ill Natural Hist Survey Bull 15(9):537–550Google Scholar
  14. Frisk T, Niemi JS, Kinnunen KAI (1981) Comparison of statistical phosphorus-retention models. Ecol Model 12(1–2):11–27. doi:http://dx.doi.org/10.1016/0304-3800(81)90022-3 Google Scholar
  15. Gassman PW, Reyes MR, Green CH, Arnold JG (2007) The soil and water assessment tool: historical development, applications, and future research directions. Trans Am Soc Agric Biol Eng 50:1211–1250Google Scholar
  16. Gelman A, Carlin JB, Stern HS, Rubin DB (2004) Bayesian data analysis. Chapman and Hall, New YorkGoogle Scholar
  17. Hillbricht-Ilkowska A (2002) Eutrophication rate of lakes in the Jorka river system (Masurian Lakeland, Poland): long-term changes and trophic correlations. Polish J Ecol 50(4):475–487Google Scholar
  18. Hilt S, Köhler J, Kozerski H-P, van Nes EH, Scheffer M (2011) Abrupt regime shifts in space and time along rivers and connected lake systems. Oikos 120(5):766–775. doi: 10.1111/j.1600-0706.2010.18553.x CrossRefGoogle Scholar
  19. Kitchell JF (ed) (1992) Food web management: a case study of Lake Mendota. Springer, New YorkGoogle Scholar
  20. Kling GW, Kipphut GW, Miller MM, O’Brien WJ (2000) Integration of lakes and streams in a landscape perspective: the importance of material processing on spatial patterns and temporal coherence. Freshw Biol 43(3):477–497. doi: 10.1046/j.1365-2427.2000.00515.x CrossRefGoogle Scholar
  21. Lathrop RC (2007) Perspectives on the eutrophication of the Yahara lakes. Lake Reservoir Manage 23:345–365CrossRefGoogle Scholar
  22. Lathrop RC, Carpenter SR (2013) Water quality implications from three decades of phosphorus loads and trophic dynamics in the Yahara chain of lakes. Inland Waters 3 (in press)Google Scholar
  23. Lathrop RC, Carpenter SR, Stow CA, Soranno PA, Panuska JC (1998) Phosphorus loading reductions needed to control blue-green algal blooms in Lake Mendota. Can J Fish Aquat Sci 55(5):1169–1178. doi: 10.1139/f97-317 CrossRefGoogle Scholar
  24. Lathrop RC, Carpenter SR, Robertson DM (1999) Summer water clarity responses to phosphorus, Daphnia grazing and internal mixing in Lake Mendota. Limnol Oceanogr 44:137–146CrossRefGoogle Scholar
  25. Lathrop RC, Johnson BM, Johnson TB, Vogelsang MT, Carpenter SR, Hrabik TR, Kitchell JF, Magnuson JJ, Rudstam LG, Stewart RS (2002) Stocking piscivores to improve fishing and water clarity: a synthesis of the Lake Mendota biomanipulation project. Freshw Biol 47(12):2410–2424. doi: 10.1046/j.1365-2427.2002.01011.x CrossRefGoogle Scholar
  26. Leavitt PR, Brock CS, Ebel C, Patoine A (2006) Landscape-scale effects of urban nitrogen on a chain of freshwater lakes in central North America. Limnol Oceanogr 51(5):2262–2277CrossRefGoogle Scholar
  27. Magnuson JJ (2002) Three generations of limnology at the University of Wisconsin-Madison. Verh Internat Verein Limnol 28:856–860Google Scholar
  28. Magnuson JJ, Kratz TK, Benson BJ (eds) (2006) Long-term dynamics of lakes in the landscape. Oxford University Press, OxfordGoogle Scholar
  29. Pace ML, Groffman PM (eds) (1998) Successes, frontiers and limitations in ecosystem science. Springer, New YorkGoogle Scholar
  30. Pitt R, Voorhees J (2002) SLAMM, the source loading and management model. In: Field R, Sullivan D (eds) Wet-weather flow in the urban watershed: technology and management. CRC Press, Boca Raton, pp 103–139Google Scholar
  31. Reckhow KH, Chapra SC (1983) Engineering approaches for lake management. Data analysis and empirical modeling, vol 1. Butterworth, BostonGoogle Scholar
  32. Sadro S, Nelson C, Melack J (2012) The influence of landscape position and catchment characteristics on aquatic biogeochemistry in high-elevation lake-chains. Ecosystems 15(3):363–386. doi: 10.1007/s10021-011-9515-x CrossRefGoogle Scholar
  33. Soranno PA, Webster KE, Riera JL, Kratz TK, Baron JS, Bukaveckas PA, Kling GW, White DS, Caine N, Lathrop RC (1999) Spatial variation among lakes within landscapes: ecological organization along lake chains. Ecosystems 2(5):395–410CrossRefGoogle Scholar
  34. Soranno PA, Spence Cheruvelil K, Webster KE, Bremigan MT, Wagner T, Stow CA (2010) Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation. Bioscience 60(6):440–454. doi: 10.1525/bio.2010.60.6.8 CrossRefGoogle Scholar

Copyright information

© Springer Basel 2013

Authors and Affiliations

  1. 1.Center for LimnologyUniversity of WisconsinMadisonUSA
  2. 2.Bureau of Science ServicesWisconsin Department of Natural ResourcesMadisonUSA

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