Abstract

Flow is widely considered one of the primary drivers of instream ecological response. Increasingly, hydroecological models form the basis of integrated and sustainable approaches to river management, linking flow to ecological response. In doing so, the most ecologically relevant hydrological variables should be selected. Some studies have observed a delayed macro-invertebrate (ecological) response to these variables (i.e. a cumulative inter-annual effect, referred to as multi-annual) in groundwater-fed rivers. To date, only limited research has been performed investigating this phenomenon. This paper examines the ecological response to multi-annual flow indicators for a groundwater-fed river. Relationships between instream ecology and flow were investigated by means of a novel methodological framework developed by integrating statistical data analysis and modelling techniques, such as principal component analysis and multistep regression approaches. Results demonstrated a strong multi-annual multi-seasonal effect. Inclusion of additional antecedent flows indicators appears to enhance overall model performance (in some cases, goodness of fit statistics such as the adjusted R-squared value exceeded 0.6). These results strongly suggest that, in order to understand potential changes to instream ecology arising from changing flow regimes, multi-annual and multi-seasonal relationships should be considered in hydroecological modelling.
Original languageEnglish
Pages (from-to)707–717
Number of pages11
JournalRiver Research and Applications
Volume33
Issue number5
Early online date18 Jan 2017
DOIs
Publication statusPublished - Jun 2017

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community response
macroinvertebrate
ecology
river management
groundwater
statistical data
river
modeling
indicator
principal component analysis

Cite this

@article{7574ba308cf44903a12d3be165e09f62,
title = "Macro-invertebrate Community Response to Multi-annual Hydrological Indicators",
abstract = "Flow is widely considered one of the primary drivers of instream ecological response. Increasingly, hydroecological models form the basis of integrated and sustainable approaches to river management, linking flow to ecological response. In doing so, the most ecologically relevant hydrological variables should be selected. Some studies have observed a delayed macro-invertebrate (ecological) response to these variables (i.e. a cumulative inter-annual effect, referred to as multi-annual) in groundwater-fed rivers. To date, only limited research has been performed investigating this phenomenon. This paper examines the ecological response to multi-annual flow indicators for a groundwater-fed river. Relationships between instream ecology and flow were investigated by means of a novel methodological framework developed by integrating statistical data analysis and modelling techniques, such as principal component analysis and multistep regression approaches. Results demonstrated a strong multi-annual multi-seasonal effect. Inclusion of additional antecedent flows indicators appears to enhance overall model performance (in some cases, goodness of fit statistics such as the adjusted R-squared value exceeded 0.6). These results strongly suggest that, in order to understand potential changes to instream ecology arising from changing flow regimes, multi-annual and multi-seasonal relationships should be considered in hydroecological modelling.",
author = "Annie Visser and Beevers, {Lindsay Catherine} and Sandhya Patidar",
year = "2017",
month = "6",
doi = "10.1002/rra.3125",
language = "English",
volume = "33",
pages = "707–717",
journal = "River Research and Applications",
issn = "1535-1459",
publisher = "John Wiley and Sons Ltd",
number = "5",

}

TY - JOUR

T1 - Macro-invertebrate Community Response to Multi-annual Hydrological Indicators

AU - Visser, Annie

AU - Beevers, Lindsay Catherine

AU - Patidar, Sandhya

PY - 2017/6

Y1 - 2017/6

N2 - Flow is widely considered one of the primary drivers of instream ecological response. Increasingly, hydroecological models form the basis of integrated and sustainable approaches to river management, linking flow to ecological response. In doing so, the most ecologically relevant hydrological variables should be selected. Some studies have observed a delayed macro-invertebrate (ecological) response to these variables (i.e. a cumulative inter-annual effect, referred to as multi-annual) in groundwater-fed rivers. To date, only limited research has been performed investigating this phenomenon. This paper examines the ecological response to multi-annual flow indicators for a groundwater-fed river. Relationships between instream ecology and flow were investigated by means of a novel methodological framework developed by integrating statistical data analysis and modelling techniques, such as principal component analysis and multistep regression approaches. Results demonstrated a strong multi-annual multi-seasonal effect. Inclusion of additional antecedent flows indicators appears to enhance overall model performance (in some cases, goodness of fit statistics such as the adjusted R-squared value exceeded 0.6). These results strongly suggest that, in order to understand potential changes to instream ecology arising from changing flow regimes, multi-annual and multi-seasonal relationships should be considered in hydroecological modelling.

AB - Flow is widely considered one of the primary drivers of instream ecological response. Increasingly, hydroecological models form the basis of integrated and sustainable approaches to river management, linking flow to ecological response. In doing so, the most ecologically relevant hydrological variables should be selected. Some studies have observed a delayed macro-invertebrate (ecological) response to these variables (i.e. a cumulative inter-annual effect, referred to as multi-annual) in groundwater-fed rivers. To date, only limited research has been performed investigating this phenomenon. This paper examines the ecological response to multi-annual flow indicators for a groundwater-fed river. Relationships between instream ecology and flow were investigated by means of a novel methodological framework developed by integrating statistical data analysis and modelling techniques, such as principal component analysis and multistep regression approaches. Results demonstrated a strong multi-annual multi-seasonal effect. Inclusion of additional antecedent flows indicators appears to enhance overall model performance (in some cases, goodness of fit statistics such as the adjusted R-squared value exceeded 0.6). These results strongly suggest that, in order to understand potential changes to instream ecology arising from changing flow regimes, multi-annual and multi-seasonal relationships should be considered in hydroecological modelling.

U2 - 10.1002/rra.3125

DO - 10.1002/rra.3125

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SP - 707

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JF - River Research and Applications

SN - 1535-1459

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ER -