Advertisement

Estuaries and Coasts

, Volume 42, Issue 4, pp 927–943 | Cite as

Patterns and Trends in Secchi Disk Depth over Three Decades in the Chesapeake Bay Estuarine Complex

  • Jeremy M. TestaEmail author
  • Vyacheslav Lyubchich
  • Qian Zhang
Article

Abstract

Water clarity is an important ecosystem indicator of eutrophication in Chesapeake Bay and other coastal and estuarine systems across the globe. Although a variety of measures are available to quantify light availability in water, Secchi disk depths have been the most consistent and frequent measure employed in water monitoring programs. Because light availability is influenced by multiple variables, such as phytoplankton biomass, non-living suspended particles, and colored dissolved organic matter (CDOM), understanding the factors driving long-term variability and trends in water clarity is critical for targeting watershed management actions related to eutrophication. Thus, we conducted a comprehensive statistical analysis of spatial and temporal variations in Secchi disk depth and the key internal and external variables that influence its variability in Chesapeake Bay and its tidal tributaries over the past 30 years. Our results indicate that although watershed nutrient, sediment, and freshwater inputs did not correlate with Secchi depth on a monthly timescale outside of low-salinity regions near river outflows, water-column variables that represent the consequences of those inputs (CDOM, chlorophyll-a, and total suspended solids [TSS]) were strongly associated with Secchi depth variability. The inconsistency of these two findings may be explained by controls on chlorophyll-a and TSS that are not directly related to watershed input, such as grazing and resuspension, and by lags of several months between watershed inputs and the associated water-column concentrations. While salinity (a proxy for CDOM) was a dominant spatial covariate with Secchi depth bay-wide, TSS concentrations were strongly associated with temporal changes in Secchi depths in low-salinity regions and indicators of phytoplankton biomass were more important in mesohaline and polyhaline regions. These findings related to spatially dependent controls on Secchi depth enhance our understanding of long-term changes in estuarine light availability and suggest a region-specific response of Secchi depth to variables (TSS and chlorophyll-a) targeted by watershed restoration actions designed to limit nutrient and sediment inputs to Chesapeake Bay.

Keywords

Secchi disk Time series Random forest Seasonality Clustering Water clarity 

Notes

Acknowledgements

This study was motivated by the Chesapeake Bay Program Scientific and Technical Advisory Committee (STAC)’s 2017 workshop entitled “Understanding and Explaining 30+ Years of Water Clarity Trends in the Bay’s Tidal Waters.” We thank all the workshop participants for insightful discussions. This work has benefited from data collected through the EPA Chesapeake Bay Program Water Quality Monitoring Program, the Maryland Department of Natural Resources, and the United States Geological Survey River Input Monitoring Program. We thank Carl Friedrichs and Jennifer Keisman for helpful reviews of this manuscript. This is UMCES Contribution Number 5610.

Funding Information

This work was supported by the U.S. Environmental Protection Agency under grants “EPA/CBP Technical Support 2017” (No. 07-5-230480 & CB-96305401).

Supplementary material

12237_2019_547_MOESM1_ESM.pdf (4.6 mb)
ESM 1 (PDF 4700 kb)

References

  1. Alvarez-Cobelas, M., D.G. Angeler, S. Sánchez-Carrillo, and G. Almendros. 2012. A worldwide view of organic carbon export from catchments. Biogeochemistry 107 (1-3): 275–293.CrossRefGoogle Scholar
  2. Benjamini, Y., and Y. Hochberg. 1995. Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B 57: 289–300.Google Scholar
  3. Berk, R.A. 2016. Statistical learning from a regression perspective. New York: Springer.CrossRefGoogle Scholar
  4. Beusen, A.H.W., A.L.M. Dekkers, A.F. Bouwman, W. Ludwig, and J. Harrison. 2005. Estimation of global river transport of sediments and associated particulate C, N, and P. Global Biogeochemical Cycles 19: GB4S05.CrossRefGoogle Scholar
  5. Bianchi, T.S., L.A. Wysocki, M. Stewart, T.R. Filley, and B.A. McKee. 2007. Temporal variability in terrestrially-derived sources of particulate organic carbon in the lower Mississippi River and its upper tributaries. Geochimica et Cosmochimica Acta 71 (18): 4425–4437.CrossRefGoogle Scholar
  6. Boesch, D.F., R.B. Brinsfield, and R.E. Magnien. 2001. Chesapeake Bay eutrophication: Scientific understanding, ecosystem restoration, and challenges for agriculture. Journal of Environmental Quality 30 (2): 303–320.CrossRefGoogle Scholar
  7. Branco, A.B., and J.N. Kremer. 2005. The relative importance of chlorophyll and colored dissolved organic matter (CDOM) to the prediction of the diffuse attenuation coefficient in shallow estuaries. Estuaries 28 (5): 643–652.CrossRefGoogle Scholar
  8. Breiman, L. 2001. Random forests. Machine Learning 45 (1): 5–32.CrossRefGoogle Scholar
  9. Breiman, L., and J.H. Friedman. 1985. Estimating optimal transformations for multiple regression and correlation. Journal of the American Statistical Association 80 (391): 580–598.CrossRefGoogle Scholar
  10. Breiman, L., J.H. Friedman, C.J. Stone, and R.A. Olshen. 1984. Classification and regression trees. New York: CRC Press.Google Scholar
  11. Cerco, C.F., M.R. Noel, and L. Linker. 2004. Managing for water clarity in Chesapeake Bay. Journal of Environmental Engineering 130 (6): 631–642.CrossRefGoogle Scholar
  12. Cerco, C.F., S.-C. Kim, and M.R. Noel. 2013. Management modeling of suspended solids in the Chesapeake Bay, USA. Estuarine, Coastal and Shelf Science 116: 87–98.CrossRefGoogle Scholar
  13. Chanat, J.G., D.L. Moyer, J.D. Blomquist, K.E. Hyer, and M.J. Langland. 2016. Application of a weighted regression model for reporting nutrient and sediment concentrations, fluxes, and trends in concentration and flux for the Chesapeake Bay nontidal water-quality monitoring network, results through water year 2012, 76. Reston: U.S. Geological Survey.CrossRefGoogle Scholar
  14. Cleveland, W.S. 1979. Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association 74 (368): 829–836.CrossRefGoogle Scholar
  15. Dai, M., Z. Yin, F. Meng, Q. Liu, and W.-J. Cai. 2012. Spatial distribution of riverine DOC inputs to the ocean: An updated global synthesis. Current Opinion in Environmental Sustainability 4 (2): 170–178.CrossRefGoogle Scholar
  16. Devlin, M.J., J. Barry, D.K. Mills, R.J. Gowen, J. Foden, D. Sivyer, and P. Tett. 2008. Relationships between suspended particulate material, light attenuation and Secchi depth in UK marine waters. Estuarine, Coastal and Shelf Science 79 (3): 429–439.CrossRefGoogle Scholar
  17. Fisher, T.R., L.W.H. Jr, D.W. Stanley, and L.G. Ward. 1988. Phytoplankton, nutrients, and turbidity in the Chesapeake, Delaware, and Hudson estuaries. Estuarine, Coastal and Shelf Science 27 (1): 61–93.CrossRefGoogle Scholar
  18. Fisher, T.R., J.D. Hagy, and E. Rochelle-Newall. 1998. Dissolved and particulate organic carbon in Chesapeake Bay. Estuaries 21 (2): 215–229.CrossRefGoogle Scholar
  19. Fleming-Lehtinen, V., and M. Laamanen. 2012. Long-term changes in Secchi depth and the role of phytoplankton in explaining light attenuation in the Baltic Sea. Estuarine, Coastal and Shelf Science 102-103: 1–10.CrossRefGoogle Scholar
  20. Gallegos, C.L. 2001. Calculating optical water quality targets to restore and protect submersed aquatic vegetation: Overcoming problems in partitioning the diffuse attenuation coefficient for photosynthetically active radiation. Estuaries 24 (3): 381–397.CrossRefGoogle Scholar
  21. Gallegos, C.L., P.J. Werdell, and C.R. McClain. 2011. Long-term changes in light scattering in Chesapeake Bay inferred from Secchi depth, light attenuation, and remote sensing measurements. Journal of Geophysical Research 116: C00H08.CrossRefGoogle Scholar
  22. Geider, R.J., H.L. MacIntyre, and T.M. Kana. 1996. A dynamic model of photoadaptation in phytoplankton. Limnology and Oceanography 41 (1): 1–15.CrossRefGoogle Scholar
  23. Hagy, J.D., W.R. Boynton, C.W. Keefe, and K.V. Wood. 2004. Hypoxia in Chesapeake Bay, 1950–2001: Long-term change in relation to nutrient loading and river flow. Estuaries 27 (4): 634–658.CrossRefGoogle Scholar
  24. Harding, L.W., Jr., R.A. Batiuk, T.R. Fisher, C.L. Gallegos, T.C. Malone, W.D. Miller, M.R. Mulholland, H.W. Paerl, E.S. Perry, and P. Tango. 2014. Scientific bases for numerical chlorophyll criteria in Chesapeake Bay. Estuaries and Coasts 37 (1): 134–148.CrossRefGoogle Scholar
  25. Harding, L.W., Jr., M.E. Mallonee, E.S. Perry, W.D. Miller, J.E. Adolf, C.L. Gallegos, and H.W. Paerl. 2016. Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay. Scientific Reports 6 (1): 23773–23773.CrossRefGoogle Scholar
  26. Harding, L.W., J.E. Adolf, M.E. Mallonee, W.D. Miller, C.L. Gallegos, E.S. Perry, J.M. Johnson, K.G. Sellner, and H.W. Paerl. 2015a. Climate effects on phytoplankton floral composition in Chesapeake Bay. Estuarine, Coastal and Shelf Science 162: 53–68.CrossRefGoogle Scholar
  27. Harding, L.W., C.L. Gallegos, E.S. Perry, W.D. Miller, J.E. Adolf, M.E. Mallonee, and H.W. Paerl. 2015b. Long-term trends of nutrients and phytoplankton in Chesapeake Bay. Estuaries and Coasts 39: 664–681.CrossRefGoogle Scholar
  28. Harrison, J.A., N. Caraco, and S.P. Seitzinger. 2005. Global patterns and sources of dissolved organic matter export to the coastal zone: Results from a spatially explicit, global model. Global Biogeochemical Cycles 19: GB4S04.Google Scholar
  29. Harvey, E.T., J. Walve, A. Andersson, B. Karlson, and S. Kratzer. 2019. The effect of optical properties on Secchi depth and implications for eutrophication management. Frontiers in Marine Science 5: 496.  https://doi.org/10.3389/fmars.2018.00496.
  30. Hastie, T., R. Tibshirani, and J.H. Friedman. 2001. The elements of statistical learning. New York: Springer.CrossRefGoogle Scholar
  31. Hirsch, R.M. 2012. Flux of nitrogen, phosphorus, and suspended sediment from the Susquehanna River basin to the Chesapeake Bay during tropical storm lee, September 2011, as an indicator of the effects of reservoir sedimentation on water quality, 17 p.: U.S. Geological Survey.Google Scholar
  32. Hirsch, R.M. 2014. Large biases in regression-based constituent flux estimates: Causes and diagnostic tools. JAWRA Journal of the American Water Resources Association 50 (6): 1401–1424.CrossRefGoogle Scholar
  33. Hirsch, R.M., D.L. Moyer, and S.A. Archfield. 2010. Weighted regressions on time, discharge, and season (WRTDS), with an application to Chesapeake Bay river inputs. Journal of the American Water Resources Association 46 (5): 857–880.CrossRefGoogle Scholar
  34. Jakobsen, H.H., and S. Markager. 2016. Carbon-to-chlorophyll ratio for phytoplankton in temperate coastal waters: Seasonal patterns and relationship to nutrients. Limnology and Oceanography 61 (5): 1853–1868.CrossRefGoogle Scholar
  35. Keefe, C.W. 1994. The contribution of inorganic compounds to the particulate carbon, nitrogen, and phosphorus in suspended matter and surface sediments of Chesapeake Bay. Estuaries 17 (1): 122.Google Scholar
  36. Kemp, W.M., R. Batleson, P. Bergstrom, V. Carter, C.L. Gallegos, W. Hunley, L. Karrh, E.W. Koch, J.M. Landwehr, K.A. Moore, L. Murray, M. Naylor, N.B. Rybicki, J.C. Stevenson, and D.J. Wilcox. 2004. Habitat requirements for submerged aquatic vegetation in Chesapeake Bay: Water quality, light regime, and physical-chemical factors. Estuaries 27 (3): 363–377.CrossRefGoogle Scholar
  37. Kemp, W.M., W.R. Boynton, J.E. Adolf, D.F. Boesch, W.C. Boicourt, G. Brush, J.C. Cornwell, T.R. Fisher, P.M. Glibert, J.D. Hagy, L.W. Harding, E.D. Houde, D.G. Kimmel, W.D. Miller, R.I.E. Newell, M.R. Roman, E.M. Smith, and J.C. Stevenson. 2005. Eutrophication of Chesapeake Bay: Historical trends and ecological interactions. Marine Ecology Progress Series 303: 1–29.CrossRefGoogle Scholar
  38. Lefcheck, J.S., D.J. Wilcox, R.R. Murphy, S.R. Marion, and R.J. Orth. 2017. Multiple stressors threaten the imperiled coastal foundation species eelgrass (Zostera marina) in Chesapeake Bay, USA. Global Change Biology 23 (9): 3474–3483.Google Scholar
  39. Lefcheck, J.S., R.J. Orth, W.C. Dennison, D.J. Wilcox, R.R. Murphy, J. Keisman, C. Gurbisz, M. Hannam, J.B. Landry, K.A. Moore, C.J. Patrick, J. Testa, D.E. Weller, and R.A. Batiuk. 2018. Long-term nutrient reductions lead to the unprecedented recovery of a temperate coastal region. Proceedings of the National Academy of Sciences 115 (14): 3658–3662.CrossRefGoogle Scholar
  40. Meybeck, M., L. Laroche, H.H. Dürr, and J.P.M. Syvitski. 2003. Global variability of daily total suspended solids and their fluxes in rivers. Global and Planetary Change 39 (1-2): 65–93.CrossRefGoogle Scholar
  41. Moyer, D.L., R.M. Hirsch, and K.E. Hyer. 2012. Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed, 118. Reston: U.S. Geological Survey.Google Scholar
  42. Moyer, D.L., M.J. Langland, J.D. Blomquist, and G. Yang. 2017. Nitrogen, phosphorus, and suspended-sediment loads and trends measured at the Chesapeake Bay nontidal network stations: Water years 1985–2016. In U.S. Geological Survey data release.  https://doi.org/10.5066/F7RR1X68.
  43. Orth, R.J., W.C. Dennison, J.S. Lefcheck, C. Gurbisz, M. Hannam, J. Keisman, J.B. Landry, K.A. Moore, R.R. Murphy, C.J. Patrick, J.M. Testa, Donald E. Weller, and David J. Wilcox. 2017. Submersed aquatic vegetation in Chesapeake Bay: Sentinel species in a changing world. BioScience 67 (8): 698–712.  https://doi.org/10.1093/biosci/bix058.CrossRefGoogle Scholar
  44. Palinkas, C.M., J.P. Halka, M. Li, L.P. Sanford, and P. Cheng. 2014. Sediment deposition from tropical storms in the upper Chesapeake Bay: Field observations and model simulations. Continental Shelf Research 86: 6–16.CrossRefGoogle Scholar
  45. Pedersen, T.M., K. Sand-Jensen, S. Markager, and S.L. Nielsen. 2014. Optical changes in a eutrophic estuary during reduced nutrient loadings. Estuaries and Coasts 37 (4): 880–892.CrossRefGoogle Scholar
  46. Prasad, M.B.K., M.R.P. Sapiano, C.R. Anderson, W. Long, and R. Murtugudde. 2010. Long-term variability of nutrients and chlorophyll in the Chesapeake Bay: A retrospective analysis, 1985–2008. Estuaries and Coasts 33 (5): 1128–1143.CrossRefGoogle Scholar
  47. Preisendorfer, R.W. 1986. Secchi disk science: Visual optics of natural waters. Limnology and Oceanography 31 (5): 909–926.CrossRefGoogle Scholar
  48. Riemann, B., J. Carstensen, K. Dahl, H. Fossing, J.W. Hansen, H.H. Jakobsen, A.B. Josefson, D. Krause-Jensen, S. Markager, P.A. Stæhr, K. Timmermann, J. Windolf, and J.H. Andersen. 2015. Recovery of Danish coastal ecosystems after reductions in nutrient loading: A holistic ecosystem approach. Estuaries and Coasts 39: 82–97.CrossRefGoogle Scholar
  49. Rochelle-Newall, E.J., and T.R. Fisher. 2002. Chromophoric dissolved organic matter and dissolved organic carbon in Chesapeake Bay. Marine Chemistry 77 (1): 23–41.CrossRefGoogle Scholar
  50. Roman, M., X. Zhang, C. McGilliard, and W. Boicourt. 2005. Seasonal and annual variability in the spatial patterns of plankton biomass in Chesapeake Bay. Limnology and Oceanography 50 (2): 480–492.CrossRefGoogle Scholar
  51. Sanden, P., and B. Hakansson. 1996. Long-term trends in Secchi depth in the Baltic Sea. Limnology and Oceanography 41 (2): 346–351.CrossRefGoogle Scholar
  52. Sanford, L.P., S.E. Suttles, and J.P. Halka. 2001. Reconsidering the physics of the Chesapeake Bay estuarine turbidity maximum. Estuaries 24 (5): 655–669.CrossRefGoogle Scholar
  53. Schubel, J.R. 1968. Turbidity maximum of the northern Chesapeake Bay. Science 161 (3845): 1013–1015.CrossRefGoogle Scholar
  54. Smith, E.M., and W.M. Kemp. 1995. Seasonal and regional variations in plankton community production and respiration for Chesapeake Bay. Marine Ecology Progress Series 116: 217–231.CrossRefGoogle Scholar
  55. Spencer, R.G.M., G.R. Aiken, M.M. Dornblaser, K.D. Butler, R.M. Holmes, G. Fiske, P.J. Mann, and A. Stubbins. 2013. Chromophoric dissolved organic matter export from U.S. rivers. Geophysical Research Letters 40 (8): 1575–1579.CrossRefGoogle Scholar
  56. Tango, P.J., and R.A. Batiuk. 2013. Deriving Chesapeake Bay water quality standards. JAWRA Journal of the American Water Resources Association 49: 1007–1024.Google Scholar
  57. Testa, J.M., R.R. Murphy, D.C. Brady, and W.M. Kemp. 2018. Nutrient- and climate-induced shifts in the phenology of linked biogeochemical cycles in a temperate estuary. Frontiers in Marine Science 5.  https://doi.org/10.3389/fmars.2018.00114.
  58. Tzortziou, M., P.J. Neale, C.L. Osburn, J.P. Megonigal, N. Maie, and R. JaffÉ. 2008. Tidal marshes as a source of optically and chemically distinctive colored dissolved organic matter in the Chesapeake Bay. Limnology and Oceanography 53 (1): 148–159.CrossRefGoogle Scholar
  59. Xu, J., and R.R. Hood. 2006. Modeling biogeochemical cycles in Chesapeake Bay with a coupled physical-biological model. Estuarine, Coastal and Shelf Science 69 (1-2): 19–46.CrossRefGoogle Scholar
  60. Xu, J., R.R. Hood, and S.-Y. Chao. 2005. A simple empirical optical model for simulating light attenuation variability in a partially mixed estuary. Estuaries 28 (4): 572–580.CrossRefGoogle Scholar
  61. Zhang, Q., and J.D. Blomquist. 2018. Watershed export of fine sediment, organic carbon, and chlorophyll-a to Chesapeake Bay: Spatial and temporal patterns in 1984–2016. Science of the Total Environment 619-620: 1066–1078.CrossRefGoogle Scholar
  62. Zhang, Q., D.C. Brady, and W.P. Ball. 2013. Long-term seasonal trends of nitrogen, phosphorus, and suspended sediment load from the non-tidal Susquehanna River basin to Chesapeake Bay. Science of the Total Environment 452-453: 208–221.CrossRefGoogle Scholar
  63. Zhang, Q., D.C. Brady, W.R. Boynton, and W.P. Ball. 2015. Long-term trends of nutrients and sediment from the nontidal Chesapeake watershed: An assessment of progress by river and season. JAWRA Journal of the American Water Resources Association 51 (6): 1534–1555.CrossRefGoogle Scholar
  64. Zhang, Q., C.J. Harman, and W.P. Ball. 2016a. An improved method for interpretation of riverine concentration-discharge relationships indicates long-term shifts in reservoir sediment trapping. Geophysical Research Letters 43 (19): 10215–10224.CrossRefGoogle Scholar
  65. Zhang, Q., R.M. Hirsch, and W.P. Ball. 2016b. Long-term changes in sediment and nutrient delivery from Conowingo Dam to Chesapeake Bay: Effects of reservoir sedimentation. Environmental Science & Technology 50 (4): 1877–1886.CrossRefGoogle Scholar
  66. Zhang, Q., R. Murphy, R. Tian, M. Forsyth, E. Trentacoste, J. Keisman, and P. Tango. 2018. Status and trends of the Chesapeake Bay water quality standards criteria attainment in 1985-2016: Insights from assessment of thirty years of tidal water quality monitoring data. Science of the Total Environment 637-638: 1617–1625.CrossRefGoogle Scholar

Copyright information

© Coastal and Estuarine Research Federation 2019

Authors and Affiliations

  1. 1.Chesapeake Biological LaboratoryUniversity of Maryland Center for Environmental ScienceSolomonsUSA
  2. 2.University of Maryland Center for Environmental Science / U.S. Environmental Protection Agency Chesapeake Bay ProgramAnnapolisUSA

Personalised recommendations