Macroinvertebrate responses to flow and thermal variability associated with impoundments James. C. White 1, Paul. J. Wood 1, David. M. Hannah 2 and Andy House 3. 1 Loughborough University; 2 University of Birmingham; 3 Wessex Water.

The significance of impoundments >50,000 large dams worldwide (≈1/6 of global annual river flows) 1. 2 Multiple ecological implications. Flow Temperature Sediment Faunal migration Phytoplankton 1) Lehner, B. et al. (2011). Frontiers in Ecology and the Environment, 9(9). 2) Grill, G. et al. (2015). Environmental Research Letters, 10(1).

Environmental flows Over 200 methodologies exist A need to establish ‘building blocks’. - A need to look at multiple environmental controls. Magnitude Frequency Duration Timing Rate of change 1) Tharme, R. E. (2003). River Research and Applications, 19(5-6). 2) Acreman, M.. et al. (2014). Frontiers in the Ecology and the Environment, 12(8). Flow and thermal regimes

Study aims 1.Assess how reservoirs influence stream temperature and flow (discharge) variability. 2.Examine how impoundments have affected macroinvertebrate communities. 3.Quantify macroinvertebrate responses to flow and thermal variability.

Study sites Continuous aeration systems Compensation flow releases Spill weir at maximum capacity Non-regulated (control) sites upstream Regulated (impact) sites downstream

Flow and thermal alterations Comparable thermal regimes throughout the study period Consistent differences in stream temperature magnitude Reduced low flow variability Rapid rises in discharge during peak flows

72 32 Macroinvertebrate responses Community abundances Functional traits Biomonitoring indices Sample 1345 Sample 2520 Body size Locomotion Reproductive traits Velocity preference

Macroinvertebrate responses Response variablesPositionReservoir r2r2 p-valuer2r2 Taxonomic Biological traits (NS) Functional traits (NS) Functional traits and biomonitoring indices (NS) Clear differences in macroinvertebrate communities Most variance explained by traits (marginally) Comparable trait compositions between river systems

Ecohydrological and ecothermal associations ModelAbiotic indicesr All non-regulated samplesQNCRR0.22* QNCRR, TDAYMIN (NS) QNCRR, QPORR, TDAYMIN (NS) All regulated samples QCVANNMAX, QSEPMIN, QPORR, TDAYMAX *** QCVANNMAX, QSEPMIN,TDAYMAX ** QCVANNMAX, QSEPMIN, QPORR, TDAYMAX91, TNERR 0.38** Spring non-regulated samplesQJUNMIN, QSTDMAXJW, QSTDMINJW0.42** QJUNMIN, QSTDMAXJW0.38* QJUNMIN0.36* Spring regulated samplesQJULMIN, QMEPOS0.42** QJULMIN0.39* QJULMIN, QD35MAX50, QMEPOS0.31* Autumn non-regulated samplesQLPC, QD91MAX500.60*** QLPC, QD91MAX50, QMAXJW0.53** QLPC, QD91MAX50, QMAXJW, QMEMAXJW 0.45** Autumn regulated samplesQJUNMIN0.44** QCVANNMAX, QJUNMIN0.35* QCVANNMAX, QJUNMIN, QMEMAXJW0.25 (NS) Lowest correlations Various flow and thermal indices Seasonal models typically improved correlations Timing of flows Timing of minimum summer flows No thermal indices

Univariate macroinvertebrate responses o = non regulated; + = regulated

Study implications Biotic responses to both flow and thermal controls has been sparsely explored. Comparable regimes that can be incorporated within environmental flows. Paired non-regulated 1 versus regulated 2 sites: 1.Key environmental controls (building blocks). 2.Primary drivers of ecological change. Traits could indicate underlying ecological responses.

Conclusions Impoundments altered flow variability more than thermal regimes. Macroinvertebrate communities differed significantly between regulated and non-regulated sites. Functional traits could underpin future environmental flow methodologies. Macroinvertebrate communities responded significantly to flow parameters, but were less sensitive to thermal variability. The timing of extreme flows was influential in both regulated and non-regulated systems.

Acknowledgements Alex Martin Shawn Beatson Iain Harris Mitch Perkins Jeanette Collette