2012
DOI: 10.1016/j.ecoleng.2011.06.037
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Design and assessment of weirs for fish passage under drowned conditions

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Cited by 12 publications
(8 citation statements)
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“…However, was significantly influenced by the typology of obstacles, with high and steep obstacles showing an overall effect size 40% higher than low and gentle obstacles (Table 3, Figure 3). This finding is in line with classical expectations about the impact of dam typology (e.g., Januchowski-Hartley et al, 2019) and conclusions from other studies (e.g., Amaral et al, 2019; Keller et al, 2012; Zigler et al, 2004), as well as with the obstacle drowning hypothesis: the highest dams (≥ 2 m) might rarely be drowned (leading to the increase in ), but, in presence of a gentle slope (< 45°), they might become partly crossable by some individuals, at least at intermediate drowning conditions, so that only the highest and steepest obstacles have an overall significant effect size ( = 54.6%; Figure 3). This result should of course be confirmed and refined with additional datasets, but it provides a relevant and meaningful benchmark for practitioners to adjust restoration planning even in the absence of any individual quantification of barrier effects.…”
Section: Discussionsupporting
confidence: 93%
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“…However, was significantly influenced by the typology of obstacles, with high and steep obstacles showing an overall effect size 40% higher than low and gentle obstacles (Table 3, Figure 3). This finding is in line with classical expectations about the impact of dam typology (e.g., Januchowski-Hartley et al, 2019) and conclusions from other studies (e.g., Amaral et al, 2019; Keller et al, 2012; Zigler et al, 2004), as well as with the obstacle drowning hypothesis: the highest dams (≥ 2 m) might rarely be drowned (leading to the increase in ), but, in presence of a gentle slope (< 45°), they might become partly crossable by some individuals, at least at intermediate drowning conditions, so that only the highest and steepest obstacles have an overall significant effect size ( = 54.6%; Figure 3). This result should of course be confirmed and refined with additional datasets, but it provides a relevant and meaningful benchmark for practitioners to adjust restoration planning even in the absence of any individual quantification of barrier effects.…”
Section: Discussionsupporting
confidence: 93%
“…These discrepancies illustrate how barrier effects can be highly species- or genus-dependent (Amaral et al, 2021; Blanchet et al, 2010; Prunier et al, 2018), and thus hardly predictable given our limited knowledge about fish movement behavior and capacities (Baudoin et al, 2014; Thurow, 2016). In absence of a dedicated fish pass, individuals are supposed to take advantage of drowned conditions, that is, of periods where water level rises above the height of the dam, to cross the obstacle (Keller et al, 2012). However, such propitious conditions of obstacle drowning might not be encountered every year, at all localities, and equally across all species/individuals, depending on their swimming behavior and capabilities in various environmental conditions and to the timing of submersion compared with the timing of individual movements (Carpenter-Bundhoo et al, 2020; Holthe et al, 2005; Keller et al, 2012).…”
Section: Discussionmentioning
confidence: 99%
“…In this context the drown out threshold of a barrier is defined as the river discharge at which the downstream water level rises to a height where it begins to affect flow over a barrier, which is the discharge at which fish have opportunity to move upstream past the barrier (Koehn and Crook, 2013). Many of the drown out values for these barriers are estimates that have not been validated with specific field assessments, but those that have been validated (as per Keller et al, 2012) generally indicate estimates are reasonable at approximating these characteristics (Kerr et al, 2018).…”
Section: Limitations To Fish Movement From In-stream Barriersmentioning
confidence: 99%
“…Tudorache et al . ; Keller, Peterken & Berghuis ). These approaches are exemplified by the widely used software fishxing (http://www.stream.fs.fed.us/fishxing) and by species‐specific classification trees or connectivity indices developed to classify road crossings according to their passability (Love & Taylor ; Cote et al .…”
Section: Introductionmentioning
confidence: 99%