Modelling the impacts of flow regulation on fish distributions in naturally intermittent lowland streams: an approach for predicting restoration responses

Nick Bond, D. McMaster, Paul Reich, Jim THOMSON, P. Lake

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

1. Understanding the relationships between flow regime and the distribution of biota is critical for managing flows in regulated rivers. In northern Victoria, Australia, efforts are presently underway to restore a natural, intermittent flow regime to several streams which, for over 100 years, have received perennial diversions as part of a stock, irrigation and domestic water supply.2. Bayesian, model-averaged, binomial regression was used to predict probabilities of occurrence for 13 fish species, including five non-native species, based on hydrologic variables characterising both the current and modelled future flow regimes at 10 sites representing a range of hydrologic regimes (categorised here as heavily regulated, moderately regulated and unregulated).3. Regression models accurately predicted present probabilities of occurrence for most species across all sites. The models predicted a reduced likelihood of large, native, flow-dependent species occurring at regulated sites following flow restoration. Predictions regarding the future distribution of widespread species including two small-bodied native and four exotic species were less certain as current distributions of these widespread species were unrelated to hydrologic variables we examined and thus unlikely to be significantly affected by flow restoration. The distributions of two small native species currently restricted to unregulated sites are predicted to increase throughout the system.4. This study illustrates the effects of artificially induced perennial flow on lowland fish distributions. Furthermore, the combination of pre-restoration data together with predictive modelling provides valuable insights into the likely outcomes of flow regime shifts.5. This study clearly demonstrates the value of combining empirical research and modelling in guiding environmental flow and ecosystem restoration decisions. Knowledge from the study is now helping guide management decisions and the development of mitigation strategies to protect highly valued species in the system from potential future threats.
Original languageEnglish
Pages (from-to)1997-2010
Number of pages14
JournalFreshwater Biology
Volume55
Issue number9
DOIs
Publication statusPublished - 2010
Externally publishedYes

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flow regulation
lowlands
fish
modeling
hydrologic factors
Victoria (Australia)
distribution
restoration
ecological restoration
pollution control
native species
biota
indigenous species
mitigation
biogeography
irrigation

Cite this

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title = "Modelling the impacts of flow regulation on fish distributions in naturally intermittent lowland streams: an approach for predicting restoration responses",
abstract = "1. Understanding the relationships between flow regime and the distribution of biota is critical for managing flows in regulated rivers. In northern Victoria, Australia, efforts are presently underway to restore a natural, intermittent flow regime to several streams which, for over 100 years, have received perennial diversions as part of a stock, irrigation and domestic water supply.2. Bayesian, model-averaged, binomial regression was used to predict probabilities of occurrence for 13 fish species, including five non-native species, based on hydrologic variables characterising both the current and modelled future flow regimes at 10 sites representing a range of hydrologic regimes (categorised here as heavily regulated, moderately regulated and unregulated).3. Regression models accurately predicted present probabilities of occurrence for most species across all sites. The models predicted a reduced likelihood of large, native, flow-dependent species occurring at regulated sites following flow restoration. Predictions regarding the future distribution of widespread species including two small-bodied native and four exotic species were less certain as current distributions of these widespread species were unrelated to hydrologic variables we examined and thus unlikely to be significantly affected by flow restoration. The distributions of two small native species currently restricted to unregulated sites are predicted to increase throughout the system.4. This study illustrates the effects of artificially induced perennial flow on lowland fish distributions. Furthermore, the combination of pre-restoration data together with predictive modelling provides valuable insights into the likely outcomes of flow regime shifts.5. This study clearly demonstrates the value of combining empirical research and modelling in guiding environmental flow and ecosystem restoration decisions. Knowledge from the study is now helping guide management decisions and the development of mitigation strategies to protect highly valued species in the system from potential future threats.",
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author = "Nick Bond and D. McMaster and Paul Reich and Jim THOMSON and P. Lake",
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Modelling the impacts of flow regulation on fish distributions in naturally intermittent lowland streams: an approach for predicting restoration responses. / Bond, Nick; McMaster, D.; Reich, Paul; THOMSON, Jim; Lake, P.

In: Freshwater Biology, Vol. 55, No. 9, 2010, p. 1997-2010.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Modelling the impacts of flow regulation on fish distributions in naturally intermittent lowland streams: an approach for predicting restoration responses

AU - Bond, Nick

AU - McMaster, D.

AU - Reich, Paul

AU - THOMSON, Jim

AU - Lake, P.

PY - 2010

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N2 - 1. Understanding the relationships between flow regime and the distribution of biota is critical for managing flows in regulated rivers. In northern Victoria, Australia, efforts are presently underway to restore a natural, intermittent flow regime to several streams which, for over 100 years, have received perennial diversions as part of a stock, irrigation and domestic water supply.2. Bayesian, model-averaged, binomial regression was used to predict probabilities of occurrence for 13 fish species, including five non-native species, based on hydrologic variables characterising both the current and modelled future flow regimes at 10 sites representing a range of hydrologic regimes (categorised here as heavily regulated, moderately regulated and unregulated).3. Regression models accurately predicted present probabilities of occurrence for most species across all sites. The models predicted a reduced likelihood of large, native, flow-dependent species occurring at regulated sites following flow restoration. Predictions regarding the future distribution of widespread species including two small-bodied native and four exotic species were less certain as current distributions of these widespread species were unrelated to hydrologic variables we examined and thus unlikely to be significantly affected by flow restoration. The distributions of two small native species currently restricted to unregulated sites are predicted to increase throughout the system.4. This study illustrates the effects of artificially induced perennial flow on lowland fish distributions. Furthermore, the combination of pre-restoration data together with predictive modelling provides valuable insights into the likely outcomes of flow regime shifts.5. This study clearly demonstrates the value of combining empirical research and modelling in guiding environmental flow and ecosystem restoration decisions. Knowledge from the study is now helping guide management decisions and the development of mitigation strategies to protect highly valued species in the system from potential future threats.

AB - 1. Understanding the relationships between flow regime and the distribution of biota is critical for managing flows in regulated rivers. In northern Victoria, Australia, efforts are presently underway to restore a natural, intermittent flow regime to several streams which, for over 100 years, have received perennial diversions as part of a stock, irrigation and domestic water supply.2. Bayesian, model-averaged, binomial regression was used to predict probabilities of occurrence for 13 fish species, including five non-native species, based on hydrologic variables characterising both the current and modelled future flow regimes at 10 sites representing a range of hydrologic regimes (categorised here as heavily regulated, moderately regulated and unregulated).3. Regression models accurately predicted present probabilities of occurrence for most species across all sites. The models predicted a reduced likelihood of large, native, flow-dependent species occurring at regulated sites following flow restoration. Predictions regarding the future distribution of widespread species including two small-bodied native and four exotic species were less certain as current distributions of these widespread species were unrelated to hydrologic variables we examined and thus unlikely to be significantly affected by flow restoration. The distributions of two small native species currently restricted to unregulated sites are predicted to increase throughout the system.4. This study illustrates the effects of artificially induced perennial flow on lowland fish distributions. Furthermore, the combination of pre-restoration data together with predictive modelling provides valuable insights into the likely outcomes of flow regime shifts.5. This study clearly demonstrates the value of combining empirical research and modelling in guiding environmental flow and ecosystem restoration decisions. Knowledge from the study is now helping guide management decisions and the development of mitigation strategies to protect highly valued species in the system from potential future threats.

KW - Adaptive management

KW - Bayesian model averaging

KW - Environmental flows

KW - Stream restoration.

U2 - 10.1111/j.1365-2427.2010.02421.x

DO - 10.1111/j.1365-2427.2010.02421.x

M3 - Article

VL - 55

SP - 1997

EP - 2010

JO - Freshwater Biology

JF - Freshwater Biology

SN - 0046-5070

IS - 9

ER -