Updated 2024-07-01 18:27:36
Lake Huron -> 8.0 Prey -> Prey Fish Biomass
Reporting Interval
2018 - 2022
Area
main basin
Meeting Target?
Does Not Meet
Indicator Trend
Upward trend
Confidence?
Low
8.1.3. Prey fish biomass is within limits predicted by spring phosphorous and/or chlorophyll-a and condition of Lake Trout is above the observation period mean
The extent to which prey fish abundance in Lake Huron is balanced with primary production and predator demand is difficult to evaluate but important for forecasting prey population trends and responses to changes in predator stocking levels. Phytoplankton and fish production in lakes is limited by phosphorous (Downing and Plante 1993, Dillon and Rigler 1974), so statistical relationships between prey fish biomass and nutrient availability and/or chlorophyll-a—if they exist—can be used to determine if prey fish population levels are within the range expected from lower tropic level productivity. Likewise, trends in predator condition can be used to index if prey are meeting predator demand (He et al. 2016, He 2024).
Both spring total phosphorous and chlorphyll-a were statistically significant predictors of prey fish biomass in Lake Huron, which was consistent with results of another study (Bunnell et al. 2014) that suggested the Lake Huron food web is bottom-up regulated. Prey fish biomass in 2018 and 2019—the only years in the reporting period when both nutrient and fish biomass data were available—was well within the range predicted from the statistical relationship between prey fish biomass and spring total phosphorous (Figure 1). Prey fish biomass during the years 2018, 2019, 2021, and 2022 also was within the range predicted from spring chlorophyll-a (Figure 2).
Conversely, condition of Lake Trout Salvelinus namaycush, as measured by the predicted weight of an individual with total length (TL) equal to 700-mm, was below target in four years of the current reporting period (2018, 2019, 2021, 2022) and exceeded target only in 2020 (Figure 3). Lake Trout condition decreased gradually from 1980 through the early 2000s and then declined sharply after the collapse of Alewife Alosa pseudoharengus in 2004 (Figure 3). Since then, Lake Trout condition has slowly rebounded, possibly due to the introduction and proliferation of Round Goby Neogobius melanostomus, which may be replacing Alewife in the diet of Lake Trout (Roseman et al. 2014).
The processes regulating prey fish biomass and community structure in Lake Huron are dynamic in space and time, so confidence in the preceding trends is low. However, ongoing oligotrophication of offshore waters and the recent recovery of native predators such as Walleye Sander vitreus and Lake Trout suggest that Lake Huron is unlikely to support prey fish populations at levels observed during the 1970s, 1980s, and 1990s (Hondorp et al. 2023).
Prey fish biomass versus spring total phosphorous concentration in Lake Huron for the years 1983-1999, 2000-2007, and 2009-2019. The regression relating prey fish biomass to (PF) to phosphorous concentration ([TP]) was ln(PF) = 1.95 × (ln[TP]) + 1.03 (r-squared = 0.47, P < 0.01, df = 28). Lines denote the regression prediction interval. Values between the upper and lower bounds of the prediction interval suggest prey fish biomass is matched to lower trophic level productivity.
Prey fish biomass versus spring chlorophyll a concentration in Lake Huron for the years 2001-2007, 2009-2019, and 2020-2021. The regression relating prey fish biomass to (PF) to chlorophyll a concentration ([Chla]) was ln(PF) = 2.60 × (ln[Chla + 1]) + 1.26 (r-squared = 0.32, P = 0.02, df = 14). Lines denote the regression prediction interval. Values between the upper and lower bounds of the prediction interval suggest prey fish biomass is matched to lower trophic level productivity.
Lake Trout condition (predicted weight of adult individual with total length equal to 700-mm) in Lake Huron, 1978-2022.
Methodology
The United States Geological Survey (USGS) monitors prey fish abundance and species composition in the main basin of Lake Huron each fall using bottom trawls towed along fixed transects in both Michigan and Ontario waters. USGS bottom trawl surveys began in 1976 and have been conducted each year except for 2000 and 2008 (sampling in Ontario waters did not begin until 1998). All trawl catches are sorted by species, counted, and weighed. Mean catch weighted by the area of lake bottom occurring within 10-m depth strata is used to generate estimates of prey fish abundance expressed in biomass per unit area (Hondorp et al. 2023, Riley et al. 2008).
To determine if current prey fish population levels in Lake Huron were consistent with primary production, prey fish biomass (in kg/ha) was regressed against mean spring total phosporous (ug/l) and chlorophyll-a concentrations (ug/l) in offshore waters (fish biomass and lower trophic level variables were log transformed prior to analysis). Phosphorous and chlorophyll-a data were obtained from annual lake-wide surveys conducted by the U.S. Environmental Protection Agency (Barbiero et al. 2018). Regressions excluded the years within the current reporting period (2018-2022). For statistically-significant relationships between prey fish biomass and lower trophic level variables, the prediction interval—the range in which prey fish biomass is expected to occur given future observations of total phosphorous or chlorphyll-a—was used to determine if prey fish biomass during the reporting period was within predicted limits and therefore matched/not matched to primary production.
Condition of adult Lake Trout was used to index if prey fish were sufficiently abundant to meet predator demands for food. Lake Trout were selected as an index predator because historically they were the dominant offshore predator in Lake Huron. Condition was assessed as the modelled weight of a 700-mm adult with total length equal to 700-mm (~28 inches). Details about the model used to predict Lake Trout weight can be found in He et al. (2016) and He (2024). Mean Lake Trout weight for the entire time series was used as the target value. For plotting, Lake Trout condition was centered (i.e., the mean was subtracted from each observation), so that each value represents a deviation from the observation period mean, which is equal to zero.
Other Resources
Barbiero, R. P., et al. (2018). A Comparative Examination of Recent Changes in Nutrients and Lower Food Web Structure in Lake Michigan and Lake Huron. J Great Lakes Res 44(4): 573-589.
Bunnell, D. B., et al. (2014). Changing Ecosystem Dynamics in the Laurentian Great Lakes: Bottom-Up and Top-Down Regulation. BioScience 64(1): 26-39.
Dillon, P. J. and F. H. Rigler (1974). The phosphorus-chlorophyll relationship in lakes1,2. Limnology and Oceanography 19(5): 767-773.
He, J. X., et al. (2016). Using time-varying asymptotic length and body condition of top piscivores to indicate ecosystem regime shift in the main basin of Lake Huron: a Bayesian hierarchical modeling approach. Canadian Journal of Fisheries and Aquatic Sciences 73(7): 1092-1103.
He, J. X. (2024). Growth stability after the collapse of alewives in Lake Huron and direct size-at-age comparisons between stocked and wild lake trout. Journal of Great Lakes Research 50(3): 102315
Hondorp, D.W., O’Brien, T.P., Roseman, E.F., and Esselman, P.C. (2023). Status and Trends of the Lake Huron Prey Fish Community, 1976-2022. U.S. Geological Survey, Ann Arbor, MI. URL: https://www.glfc.org/pubs/lake_committees/common_docs/Huron_2022preyfish_final_20230516.pdf
Riley, S.C., Roseman, E.F., Nichols, S.J., O'Brien, T.P., Kiley, C.S., and Schaeffer, J.S. (2008). Deepwater demersal fish community collapse in Lake Huron. Trans. Am. Fish. Soc. 137(6): 1879-1890.
Roseman, E. F., et al. (2014). Angler-caught piscivore diets reflect fish community changes in Lake Huron. Transactions of the American Fisheries Society 143(6): 1419-1433.
Contributing Author(s)
- Darryl Hondorp - United States Geological Survey
- Tim O'Brien - United States Geological Survey
- Ryan Lauzon - Saugeen Ojibway Nation
- Jason Smith - Bay Mills Indian Community
- Jeff Jolley - Michigan Department of Natural Resources