Flow variability and macroinvertebrate community response within riverine systems

Monk, Wendy; Wood, Paul J.; Hannah, David M.; Wilson, Douglas A.; Extence, Chris A.; Chadd, Richard

doi:10.1002/rra.933

Cited by 150 publications

(202 citation statements)

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“…In both applications, the magnitude of the hydrological regime was quantified by four indices: mean, maximum, minimum and standard deviation of the annual (single year) or long-term (1980 -1999) discharge time-series. Prior to classification of the flow regime, discharges (m 3 s -1 ) were converted to runoff (mm month -1 ) and transformed to zscores (mean = 0; standard deviation = 1) to remove any statistical bias associated with catchment area (Monk et al, 2006). The hydrological time-series for each site was divided into hydrological years commencing in August, since July was identified as the most frequent month of minimum runoff across the selected rivers.…”

Section: Data Analysesmentioning

confidence: 99%

“…Previous research has demonstrated the utility of the LIFE methodology compared to other metrics (e.g., total abundance, number of taxa and diversity indices) when using data recorded in log 10 abundance categories at the family level; and that the LIFE score is a more appropriate and statistically powerful metric compared to other macroinvertebrate biotic indices (e.g., BMWP and ASPT) when examining the ecological response to flow regime variability (Monk et al, 2006). Other research has shown the LIFE score to be sensitive to both natural river flow variability and anthropogenic modification (Extence et al, 1999;Dunbar and Clarke, 2004).…”

Section: Data Analysesmentioning

confidence: 99%

“…Instream faunal communities are adapted to the 'natural' flow regime and the variability in magnitude, frequency, timing and duration of high, low and intermediate flow events (e.g., Jowett and Duncan, 1990;Lytle and Poff, 2004;Monk et al, 2006). As a result, there is a growing interest in the identification of ecologically relevant hydrological descriptors, which may be used to characterise and quantify 'natural', seminatural, and anthropogenic modifications to river flow regimes (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, there is a growing interest in the identification of ecologically relevant hydrological descriptors, which may be used to characterise and quantify 'natural', seminatural, and anthropogenic modifications to river flow regimes (e.g. Clausen and Biggs, 1997;Jowett and Duncan, 1990;Monk et al, 2006;Olden and Poff, 2003;Richter et al, 1998;Sheldon and Thoms, 2006). When combined with biological data, these hydrological descriptors can be used as a basis for the development of ecologically sustainable management strategies that balance anthropogenic demands on water resources against protecting, conserving and even enhancing, instream habitat and communities (Petts et al, 2006;Poff et al, 2003;Richter et al, 2006;Tharme, 2003).…”

Section: Introductionmentioning

confidence: 99%

“…Results from the available long-term hydroecological studies indicate that instream communities are influenced by variations in both the climatological (Bradley and Ormerod, 2001;Daufresne et al, 2003;Scarsbrook et al, 2003) and hydrological regimes (e.g., Lamouroux et al, 2006;Monk et al, 2006, Scarsbrook, 2002Wagner and Schmidt, 2004;Wood et al, 2001). However, attempts to quantify macroinvertebrate community response to river flow variability, and in particular high and low flows, are currently limited in terms of their temporal (typically <5 years study period) and/or geographical coverage (e.g., Caruso 2002;Clausen and Biggs, 1997;Sheldon and Thoms, 2006;Suren and Jowett, 2006).…”

Section: Introductionmentioning

confidence: 99%

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Macroinvertebrate community response to inter‐annual and regional river flow regime dynamics

Monk

Wood

Hannah

et al. 2008

River Research & Apps

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Spatio‐temporal variability in river flow is a fundamental control on instream habitat structure and riverine ecosystem biodiversity and integrity. However, long‐term riverine ecological time‐series to test hypotheses about hydrology–ecology interactions in a broader temporal context are rare, and studies spanning multiple rivers are often limited in their temporal coverage to less than five years. To address this research gap, a unique spatio‐temporal hydroecological analysis was conducted of long‐term instream ecological responses (1990–2000) to river flow regime variability at 83 sites across England and Wales. The results demonstrate clear hydroecological associations at the national scale (all data). In addition, significant differences in ecological response are recorded between three ‘regions’ identified (RM1–3*) associated with characteristics of the flow regime. The effect of two major supra‐seasonal droughts (1990–1992 and 1996–1997) on inter‐annual (IA) variability of the LIFE scores is evident with both events showing a gradual decline before and recovery of LIFE scores after the low flow period. The instream community response to high magnitude flow regimes (1994 and 1995) is also apparent, although these associations are less striking. The results demonstrate classification of rivers into flow regime regions offers a way to help unravel complex hydroecological associations. The approach adopted herein could easily be adapted for other geographical locations, where datasets are available. Such work is imperative to understand flow regime–ecology interactions in a longer term, wider spatial context and so assess future hydroecological responses to climate change and anthropogenic modification of riverine ecosystems. Copyright © 2008 John Wiley & Sons, Ltd.

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Section: Data Analysesmentioning

confidence: 99%

Section: Data Analysesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Macroinvertebrate community response to inter‐annual and regional river flow regime dynamics

Monk

Wood

Hannah

et al. 2008

River Research & Apps

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126

117

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Coupling self‐organizing maps with a Naïve Bayesian classifier: Stream classification studies using multiple assessment data

Fytilis

Rizzo

2013

Water Resources Research

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Organizing or clustering data into natural groups is one of the most fundamental aspects of understanding and mining information. The recent explosion in sensor networks and data storage associated with hydrological monitoring has created a huge potential for automating data analysis and classification of large, high‐dimensional data sets. In this work, we develop a new classification tool that couples a Naïve Bayesian classifier with a neural network clustering algorithm (i.e., Kohonen Self‐Organizing Map (SOM)). The combined Bayesian‐SOM algorithm reduces classification error by leveraging the Bayesian's ability to accommodate parameter uncertainty with the SOM's ability to reduce high‐dimensional data to lower dimensions. The resulting algorithm is data‐driven, nonparametric and is as computationally efficient as a Naïve Bayesian classifier due to its parallel architecture. We apply, evaluate and test the Bayesian‐SOM network using two real‐world hydrological data sets. The first uses genetic data to classify the state of disease in native fish populations in the upper Madison River, MT, USA. The second uses stream geomorphic and water quality data measured at ∼2500 Vermont stream reaches to predict habitat conditions. The new classification tool has substantial benefits over traditional classification methods due to its ability to dynamically update prior information, assess the uncertainty/confidence of the posterior probability values, and visualize both the input data and resulting probabilistic clusters onto two‐dimensional maps to better assess nonlinear mappings between the two.

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Water management strategies for run-of-river power plants: Profitability and hydrologic impact between the intake and the outflow

et al. 2013

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[1] In Alpine regions, especially when energy production by run-of-river plants is subsidized through state incentives, the indiscriminate growth of small plants built in cascade along the same river threatens aquatic ecosystems by depleting significant fractions of the river network. This paper compares the economic profitability of small run-of-river power plants and the ensuing hydrologic disturbance between the intake and the outflow, as resulting from the adoption of two alternative management strategies, namely the minimum flow discharge and a percent-of-flow rule. The capacity that maximizes the produced energy or the economic value of the plant, as well as the flow regime between the intake and the outflow, are analytically expressed as a function of the frequency distribution of the available streamflows. A quantitative framework relying on a set of synthetic hydrologic and economic indices is then proposed to compare the effectiveness of management strategies. The application of the method to three case studies in North-Eastern Italy evidences that the compliance of the minimum flow discharge does not prevent huge alterations of some key attributes of the flow regime, especially the temporal flow correlation. For a given and equal economic profitability of the investment, the two management strategies produce similar ecodeficits and an analogous reduction of the mean discharge between the intake and the outflow. However, the percent-of-flow strategy allows a reduced disturbance on the temporal correlation and the skewness of river discharges. Furthermore, when a percent-of-flow strategy is implemented, possible policy redefinitions aimed at reducing the hydrologic disturbance of the plant in the reach between the intake and the outflow can be complied with at reduced costs in terms of missed energy production. The framework developed may be a valuable tool to assess the ability of water management strategies to trade between hydrologic disturbance and anthropogenic uses of fresh water.Citation: Lazzaro, G., S. Basso, M. Schirmer, and G. Botter (2013), Water management strategies for run-of-river power plants: Profitability and hydrologic impact between the intake and the outflow, Water Resour. Res., 49,[8285][8286][8287][8288][8289][8290][8291][8292][8293][8294][8295][8296][8297][8298]

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Flow variability and macroinvertebrate community response within riverine systems

Abstract: • This is the pre-peer reviewed version of the article, which has been published in final form at: http://dx.doi.org/10.1002/rra.933

Cited by 150 publications

References 50 publications

Macroinvertebrate community response to inter‐annual and regional river flow regime dynamics

Macroinvertebrate community response to inter‐annual and regional river flow regime dynamics

Coupling self‐organizing maps with a Naïve Bayesian classifier: Stream classification studies using multiple assessment data

Water management strategies for run-of-river power plants: Profitability and hydrologic impact between the intake and the outflow

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