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A predictive model for water clarity following dreissenid invasion


Optical transparency, or water clarity, is a fundamental property of lake ecosystems which influences a wide range of physical, chemical and biological variables and processes. The establishment of non-native dreissenid mussels in lake and river ecosystems across North America and Europe has been associated with often dramatic, but highly variable, increases in water clarity. The objective of this study was to develop a predictive model for water clarity (Secchi depth, m) in lakes following the establishment of dreissenids. We compiled water clarity data before and after dreissenid invasion from North American lakes that varied in size and nutrient status. An AIC model averaging approach was used to generate post-invasion water clarity predictions based on pre-invasion water clarity and lake morphometric characteristics from a 53 lake dataset. The accuracy of the model was verified using cross-validation. We then extended this model to existing empirical models of lake mixing depth and Walleye (Sander vitreus) yield, to demonstrate that increased water clarity associated with dreissenid invasion may have far-reaching physical and ecological consequences in lakes, including deeper thermoclines and context-dependent changes in fish yields.

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Many individuals and organizations assisted with the provision of data for this project, including the US Environmental Protection Agency, Minnesota Pollution Control Agency, Michigan and Wisconsin Departments of Natural Resources, J. Young and H. Jarjanazi (OMOECC), S. Sandstrom and M. (OMNRF), J. Halfman (Hobart and William Smith Colleges), L. Rudstam and R. Jackson (Cornell University). Financial support was provided by Fisheries and Oceans Canada to M.D.R. and the Experimental Lakes Area Graduate Fellowship and Major G.E.H. Barrett-Hamilton Memorial Scholarship to M.E.G. We acknowledge the input from H. MacIsaac, D. Strayer and two anonymous reviewers in helping prepare this manuscript for publication.

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Correspondence to Marianne E. Geisler.


Appendix 1

See Table 3.

Table 3 List of freshwater lakes (n = 62) included in analysis of dreissenid effects

Appendix 2

See Table 4.

Table 4 Table 2 from (Lester et al. 2004)

Appendix 3

Predictive equations of thermal-optical habitat area and walleye yield based on (Lester et al. 2004).

This Appendix describes the formulae developed by Lester et al. (2004) to estimate walleye thermal-optical habitat area (TOHA, ha) and yield (kg/ha/yr).

Walleye thermal-optical habitat area

TOHA was approximated as

$${{\text{TOHA} = ({\text {GDD}} - 623)}}^{ 0. 7 3} {\text{Area P}}_{\text{T}} {\text{z}}_{\text{rel}} {\text{e}}^{{ -{\text{ z}}_{\text{rel}} / 0. 1 2w}}$$

where GDD = growing degree days (°C), Area = lake surface area (ha), PT = proportion of lake area above the thermocline, zrel = relative Secchi depth of the epibenthic zone (m) and w = water clarity parameter (set to 2.12, Lester et al. 2004).

Relative Secchi depth of the epibenthic zone (zrel) is calculated as

$${\text{z}}_{\text{rel}} = \frac{{{\text{z}}_{ \sec } }}{{{\text{z}}_{\text{T}} ( 1 - {\text{e}}^{{{ - }s}} )}}$$

where zsec = Secchi depth (m), zT = thermocline depth, or maximum depth of the epibenthic zone (m) and s = basin shape parameter of the epibenthic zone.Basin shape (s) of the epibenthic zone is calculated as

$$s = \frac{{3{\text{r}} + ({\text{r}}^{2} + 8{\text{r}})^{0.5} }}{{4(1 - {\text{r}})}}$$

where \({\text{r = }}\frac{{{\text{z}}_{\text{E}} }}{{{\text{z}}_{\text{T}} }}\), where zE = mean depth of the epibenthic zone (m) and zT = thermocline depth (m). In mixed lakes, zT = zmax or maximum depth.

Walleye yield

Yield was approximated as

$${\text{Yield }} = \, 0.011\frac{\text{TOHA}}{\text{Area}} {\,\text{TDS}}^{0.534}$$

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Geisler, M.E., Rennie, M.D., Gillis, D.M. et al. A predictive model for water clarity following dreissenid invasion. Biol Invasions 18, 1989–2006 (2016).

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  • Dreissena
  • Mussel
  • Transparency
  • Thermal stratification
  • Sander vitreus
  • Ecological modelling