Influence of wind, wave, and water level dynamics on walleye eggs in a north temperate lake

Raabe, Joshua K.; Bozek, Michael A.

doi:10.1139/cjfas-2014-0320

Cited by 10 publications

(6 citation statements)

References 27 publications

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“…In contrast to Day's (1991) study of Walleye larvae in the Muskegon River during 1986, we observed significantly lower densities of Walleye larvae at the downriver site (Maple Island Road) than at sites further upstream in both years. Walleyes are known to spawn on gravel-cobble substrates (Raabe and Bozek 2015), which are found primarily upstream of the Thornapple site, rather than on sandy substrates, which are common in the lower river. We cannot explain why Day (1991) found higher catches of Walleye larvae at the Maple Island Road site than at upstream sites.…”

Section: Discussionmentioning

confidence: 99%

“…Walleye reproductive success and potential recruitment are known to be influenced by biotic and abiotic factors occurring during the egg and larval stages. Abiotic factors-primarily river flow and temperature-are known to affect the production and survival of Walleye eggs and larvae, with higher discharges and colder temperatures decreasing egg and larval survival and abundances (Mion et al 1998;Ivan et al 2010;Crane and Farrell 2013;DuFour et al 2014;Raabe and Bozek 2015). Cold water temperatures can delay egg development and can reduce survival through increased exposure to predation or disease.…”

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confidence: 99%

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Density and Survival of Walleye Eggs and Larvae in a Great Lakes Tributary

et al. 2016

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The Walleye Sander vitreus is an important sport fish that has experienced low reproductive success in some Great Lakes tributaries since severe population declines began in the late 1940s. In the Muskegon River, a Lake Michigan tributary, natural reproduction of Walleyes remains low and is largely supplemented by stocking. We evaluated the influence of abiotic factors on Walleye reproductive success in the Muskegon River during April and May 2009 and 2010 by (1) estimating Walleye egg density and survival; (2) estimating the size, density, abundance, and survival of Walleye larvae; and (3) relating our estimates to physical habitat conditions. Egg densities were 70‐fold higher in 2009 than in 2010, but eggs experienced colder water temperatures, higher river discharge rates, and lower survival in 2009 relative to 2010. Egg survival in incubators was positively related to temperature and negatively related to flow at most sites. In both years, Walleye larvae that hatched during periods of cooler temperature were smaller than larvae that hatched later during periods of warmer temperature. Walleye larval densities were highest near spawning grounds and decreased downstream. Bayesian estimates of variability in larval densities indicated that temporal variability was twice as high as spatial variability in the Muskegon River. Larval survival was much lower in 2009 than in 2010, resulting in an approximately sevenfold higher production of larvae in 2010 than in 2009. Survival was highest for smaller larvae that hatched early in April 2010, when temperatures were warm and discharges were low and stable; in contrast, survival was much lower for larger larvae hatching later in 2010 or for large and small larvae in 2009, when water temperatures were colder and discharges were higher and more variable. Our results suggest that abiotic factors, primarily temperature and river flow, likely control the early survival of Walleyes in the Muskegon River. Received February 9, 2015; accepted January 11, 2016 Published online April 19, 2016

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Density and Survival of Walleye Eggs and Larvae in a Great Lakes Tributary

et al. 2016

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“…The present results are also consistent with other models demonstrating the occurrence of silt deposition in areas of low wave energy (Rasmussen and Rowan 1997;Hakanson and Jansson 2002). Higher critical velocity thresholds for large substrates (Raabe and Bozek 2015) reduce their erosion potential along shorelines where wind-wave energy may be sufficient to move silt, sand, or gravel substrates.…”

Section: Discussionmentioning

confidence: 99%

Use of Wind Fetch and Shoreline Relief to Predict Nearshore Substrate Composition in a North Temperate Lake

Schall

Cross

Katzenmeyer

et al. 2017

N American J Fish Manag

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Spawning habitat assessments often focus on substrate composition, but few studies have predicted shoal substrates by using environmental factors. We developed a model for predicting shoal substrates in Belle Lake, Minnesota, using wind fetch and shoreline relief characteristics. Percent composition of four substrate classes (silt, sand, gravel, and rock), water depth estimated at 1 m from shore (shoal slope), effective wind fetch measured using a GIS model, and riparian bank height derived from LIDAR imaging were determined at 50 transects. Classification and regression tree (CART) analysis grouped substrates into categories, and general additive modeling described the effects of three predictor variables on the percent composition of substrate classes. The CART analysis correctly grouped 39 of 50 transects into four categories, and misclassifications primarily resulted from the movement of sand. Effective fetch most influenced silt (low fetch) and rock (high fetch) substrate classes, shoal slope was predictive of rock, and riparian height was useful in distinguishing sand from gravel. These results demonstrate the utility of a single empirical model for determining shoal substrate composition. Fisheries managers can use this technique to determine potential fish spawning locations and identify potential areas for habitat restoration or protection projects. Received December 5, 2016; accepted May 5, 2017 Published online July 19, 2017

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“…However, these models were focused on predicting coarse‐ and fine‐grained substrates throughout their systems, with little information regarding the nearshore area. Raabe and Bozek () documented water velocities high enough to transport nearshore sediments in Big Crooked Lake, Wisconsin. These measurements were correlated to wind velocity measurements from the same location (Raabe and Bozek ).…”

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confidence: 99%

“…Raabe and Bozek () documented water velocities high enough to transport nearshore sediments in Big Crooked Lake, Wisconsin. These measurements were correlated to wind velocity measurements from the same location (Raabe and Bozek ). This suggests that wind has the ability to influence nearshore substrate composition within lakes, a hypothesis shared by Schall et al (2017).…”

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Using GIS to predict habitat in lakes: An example using nearshore substrate categories

Zentner

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Raabe

et al. 2018

Limnology & Ocean Methods

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Habitat is an integral component of lake ecosystems and threatened by anthropogenic alterations. Quantifying habitat is typically done with labor intensive and spatially limited surveys (i.e., transects) or with surveys requiring specialized field equipment combined with computer analyses (i.e., sonar). These approaches are limited to inventorying habitat condition and do not directly describe processes that influence habitat distributions. We developed a framework that utilizes geographic information systems (GIS) to answer habitat-based questions and allows for an understanding of the factors that influence its distribution. This framework uses GIS-derived data to describe factors input as predictive variables. We tested this framework by predicting nearshore substrate composition in Minnesota lakes. Substrate composition was measured during the summers of 2014-2016 along transects in 28 lakes across Minnesota. Composition was then grouped into three size categories (muck, sandy gravel, and coarse). For each transect, we obtained GIS-derived data describing exposure (fetch), riparian height, maximum depth, wind power, and bathymetric aspect to use as predictor variables in a classification tree model. We randomly selected 15% of transects to validate the model. Using repeated sampling with replacement, we determined this model predicted substrate composition with 62.0-71.0% accuracy. We then used data from all study lakes and examples from Belle Lake, Minnesota, to determine sources of error. Our results demonstrate that a GIS framework can describe both the distribution of a habitat component and the factors structuring it. This framework can enhance communication effectiveness and decision-making processes regarding habitat protection, management, and restoration.

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Influence of wind, wave, and water level dynamics on walleye eggs in a north temperate lake

Cited by 10 publications

References 27 publications

Density and Survival of Walleye Eggs and Larvae in a Great Lakes Tributary

Density and Survival of Walleye Eggs and Larvae in a Great Lakes Tributary

Use of Wind Fetch and Shoreline Relief to Predict Nearshore Substrate Composition in a North Temperate Lake

Using GIS to predict habitat in lakes: An example using nearshore substrate categories

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