Diel turbidity cycles in a headwater stream: evidence of nocturnal bioturbation?
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A small number of recent studies have linked daily cycles in stream turbidity to nocturnal bioturbation by aquatic fauna, principally crayfish, and demonstrated this process can significantly impact upon water quality under baseflow conditions. Adding to this limited body of research, we use high-resolution water quality monitoring data to investigate evidence of diel turbidity cycles in a lowland, headwater stream with a known signal crayfish (Pacifastacus leniusculus) population and explore a range of potential causal mechanisms.
Materials and methods
Automatic bankside monitoring stations measured turbidity and other water quality parameters at 30-min resolution at three locations on the River Blackwater, Norfolk, UK, during 2013. Specifically, we focused on two 20-day periods of baseflow conditions during January and April 2013 which displayed turbidity trends typical of winter and spring seasons, respectively. The turbidity time-series, which were smoothed with 6.5-h Savitzky-Golay filters to highlight diel trends, were correlated against temperature, stage, dissolved oxygen and pH to assess the importance of abiotic influences on turbidity. Turbidity was also calibrated against suspended particulate matter (SPM) over a wide range of values via linear regression.
Results and discussion
Pronounced diel turbidity cycles were found at two of the three sites under baseflow conditions during April. Spring night-time turbidity values consistently peaked between 21:00 and 04:00 with values increasing by ~10 nephelometric turbidity units (NTU) compared with the lowest recorded daytime values which occurred between 10:00 and 14:00. This translated into statistically significant increases in median midnight SPM concentration of up to 76 % compared with midday, with night-time (18:00–05:30) SPM loads also up to 30 % higher than that recorded during the daytime (06:00–17:30). Relating turbidity to other water quality parameters exhibiting diel cycles revealed there to be neither any correlation that might indicate a causal link nor any obvious mechanistic connections to explain the temporal turbidity trends. Diel turbidity cycles were less prominent at all sites during the winter.
Considering the seasonality and timing of elevated turbidity, visual observations of crayfish activity and an absence of mechanistic connections with other water quality parameters, the results presented here are consistent with the hypothesis that nocturnal bioturbation is responsible for generating diel turbidity cycles under baseflow conditions in headwater streams. However, further research in a variety of fluvial environments is required to better assess the spatial extent, importance and causal mechanisms of this phenomenon.
KeywordsBioturbation Crayfish Diurnal Sediment Stream Suspended particulate matter
Elevated sediment concentrations represent an important and growing threat to the sustainable ecosystem functioning of many fluvial systems across the world (Beusen et al. 2005; Quinton et al. 2010). Excessive amounts of suspended particulate matter (SPM) increase water turbidity, reduce light penetration to submergent macrophytes, smother benthic habitats, scour invertebrate communities and reduce the lifetimes of reservoirs (Hilton et al. 2006; Bilotta and Brazier 2008). Suspended particulate matter is also a major vector for the transport of nutrients (e.g. phosphorus) through catchments which adsorb onto the surfaces of fine-grained material, thus enhancing the risk of developing eutrophic conditions (House 2003; Evans et al. 2004).
The detrimental impacts associated with elevated SPM concentrations are, however, temporally variable. These range from seasonal variations in SPM concentration driven by changing antecedent soil moisture conditions (Meybeck et al. 1999; Halliday et al. 2014) to hourly fluctuations driven by episodic high-energy, high-flow storm events which can mobilise large volumes of material through the initiation of rapid land-to-river surface sediment transfers (Navratil et al. 2012; Cooper et al. 2015). Intriguingly, recent research in North America and Europe has also found evidence of distinct diel cycles in fluvial SPM concentrations (Gillain 2005; Loperfido et al. 2010). Turbidity measurements, which can be used as a proxy for SPM concentration after calibration, were found to be elevated during the night and lower during the day, a trend attributed to in-stream bioturbation processes. Specifically, it has been demonstrated that the feeding and burrowing activities of nocturnal fish, crayfish and other aquatic organisms stir-up and entrain into suspension fine streambed and channel bank sediments, and it has been suggested that this is responsible for peaks in night-time turbidity measurements (Harvey et al. 2011, 2014; Rice et al. 2014). There is, therefore, the potential for diel turbidity cycles to occur in other riverine environments similarly inhabited by populations of sediment-mobilising aquatic fauna. However, for turbidity cycles to be directly attributed to SPM dynamics, other factors that can influence turbidity measurements have to be considered. This includes the presence of phytoplankton, fluctuations in stream pH causing the precipitation of dissolved constituents and the influence of water temperature on the accuracy of turbidity instruments.
To investigate evidence of diel turbidity cycles in the River Blackwater using high-resolution (30 min) turbidity data captured by automatic bankside monitoring stations, and
To understand the causal mechanisms of diel turbidity cycles by investigating the temporal dynamics of other water quality parameters that could influence turbidity measurements.
2 Materials and methods
2.1 Study location
2.2 Data collection
The Blackwater catchment has been intensively monitored since 2011 as part of the River Wensum Demonstration Test Catchment project (Outram et al. 2014) and is split into six nested ‘mini-catchments’ A to F for observational purposes. Each mini-catchment has an automatic bankside kiosk at its outlet monitoring a range of water quality parameters at 30-min resolution, which includes turbidity, temperature, pH, dissolved oxygen, chlorophyll, electrical conductivity, ammonium and stage. The optical turbidity data were collected by water being drawn out of the stream via peristaltic pumps and sampled by YSI multi-parameter sondes (6600 series) mounted in flow cells. Turbidity was measured in nephelometric turbidity units (NTU), and the probes have a manufacturer-derived accuracy of ±2 %. The kiosks at sites E and F additionally measured total phosphorus, total reactive phosphorus and nitrate, whilst two weather stations in the catchment measured precipitation and temperature at 15-min intervals.
For this study, the analysis was restricted to turbidity data collected during 2013 from the three bankside kiosks (A, B and E) with the most complete turbidity records. Further details of these three sites can be found in the Electronic Supplementary Material (Online Resource 1, ESM_1). We specifically focused on two 20-day periods of baseflow conditions in January and April 2013 which displayed turbidity trends typical of winter and spring/summer seasons in the River Blackwater, respectively.
Records of P. leniusculus sightings (100 m presence records) were provided for five locations on the River Blackwater by Norfolk Biodiversity Information Service and the Environment Agency courtesy of the National Biodiversity Network Gateway (Fig. 2). At each of the five locations, 23–25 recorded sightings of signal crayfish were made between 1986 and 2014. These were informally corroborated by further frequent sightings during weekly site visits for water quality monitoring between 2011 and 2015.
2.3 Data processing
Turbidity measurements (NTU) were calibrated against SPM concentrations (mg L−1) by ordinary least squares regression using ~300 stream water grab samples collected at each of the three sites under a range of high- and low-flow conditions between May 2012 and March 2014. One litre grab samples were filtered through pre-weighed Millipore quartz fibre filter (QFF) papers with a particle retention rating of 99.3 % at 0.45 μm to extract SPM (Cooper et al. 2014). Filters were then oven dried at 105 °C for 2 h and reweighed to determine SPM concentration.
The high-resolution (30 min) turbidity time-series were smoothed with 13 point (6.5 h), first order Savitzky-Golay filters (Savitzky and Golay 1964) to highlight underlying diel trends and to remove the spurious isolated turbidity peaks which were present throughout much of the turbidity record. This random high-frequency ‘noise’ in turbidity datasets has been observed in other water quality monitoring studies (e.g. Navratil et al. 2011; Sherriff et al. 2015) and is potentially linked to the temporary biofouling of the turbidity probe or debris interference around the sensor by leaves and air bubbles.
Suspended particulate matter loads were calculated from estimated SPM concentrations using stage–discharge rating curves constructed from manual flow-gauging measurements made under a wide range of flow conditions (0.002–0.543 m3 s−1) at each site. Turbidity was correlated by ordinary least squares regression against four other water quality parameters (stage, temperature, dissolved oxygen and pH) to assess potential causal mechanisms.
3 Results and discussion
3.1 Turbidity-suspended particulate matter (SPM) calibration
3.2 Diel turbidity cycles
Considering the time of sunset (20:00) and sunrise (05:45) in mid-April, the timings of these turbidity peaks and troughs are consistent with the hypothesis that nocturnal bioturbation is responsible for generating these cycles. These timings are also consistent with the observations of Harvey et al. (2014) and Rice et al. (2014), who similarly found turbidity peaked at around midnight in the River Windrush, Oxfordshire and River Nene, Northamptonshire, UK, respectively, with both studies linking these cycles to the nocturnal activities of signal crayfish.
At site B, diel turbidity cycles were noticeably less pronounced during spring than observed at sites A and E (Fig. 5). Considering the close proximity of these three sites (<600 m distance), it is unlikely that wider environmental factors (e.g. temperature/rainfall variations) are responsible for the absence of diel cycles at site B. Similarly, all three sites used the same type of turbidity probe and were serviced regularly, meaning instrument effects are also unlikely to be responsible. A reduced impact from localised bioturbation could, however, explain these differences. Lower water levels (0.03 m mean stage during this period) and denser stream vegetation in mini-catchment B likely make this part of the channel less accessible to larger fish and crayfish, thus reducing the incidences of streambed and channel bank sediment disturbance from nocturnal feeding and burrowing activities. Similarly, a greater incidence of stream channel bank slumping in mini-catchment B likely reduced the availability of suitable burrowing sites compared to mini-catchments A and E where more frequent bank re-profiling and dredging to improve channel drainage results in steeper, cleaner bank faces into which crayfish can burrow. Lastly, the bed substrate in mini-catchment B is largely gravel dominated as opposed to silt dominated in mini-catchments A and E, thus limiting the availability of fine sediment for resuspension.
3.3 Impacts on suspended particulate matter (SPM) concentration and load
Median (± standard deviation) suspended particulate matter (SPM) concentrations recorded throughout the day at sites A, B and E during 10–29th April 2013
Concentration (mg L−1)
t test: midday vs. midnight (p value)
23.0 ± 6.2
22.9 ± 15.0
15.3 ± 15.0
23.6 ± 6.8
27.9 ± 4.2
23.5 ± 5.7
18.0 ± 7.5
26.0 ± 6.8
19.5 ± 0.7
19.8 ± 1.9
19.5 ± 5.5
20.0 ± 0.7
19.7 ± 0.7
19.9 ± 1.0
19.8 ± 2.3
20.1 ± 1.0
20.6 ± 3.6
17.4 ± 3.8
11.6 ± 2.9
16.4 ± 6.8
21.4 ± 3.6
16.9 ± 4.1
12.1 ± 2.5
17.5 ± 7.8
0.073 ± 0.021
0.063 ± 0.024
0.065 ± 0.016
0.083 ± 0.018
These load estimates are comparable to those obtained by Rice et al. (2014) in the headwaters of the River Nene, UK, who calculated an increase in night-time suspended sediment load of 46.9 % compared to daytime load under baseflow conditions. This reduced to a 20.3 % increase in night-time loads when higher-flow flood days were included due to the reduced importance of bioturbation in initiating sediment mobilisation during heavy precipitation events. In headwater streams exhibiting diel cycles in Iowa, USA, Loperfido et al. (2010) also reported that mean total phosphorus (TP) concentrations were twice as high at night (0.41 mg L−1) than during the day (0.20 mg L−1) which may be linked to elevated night-time SPM concentrations. In our study, we found only limited evidence for this, with midnight median TP concentrations of 0.073 mg L−1 being marginally greater than the 0.065 mg L−1 recorded at midday, although this difference was not significant (Table 1). This can be explained by the relatively weak correlation between TP and SPM concentration during this period (r = 0.34) indicating that the dissolved fraction is more important than particulate material in controlling TP concentration under these low-flow conditions.
3.4 Causal mechanisms
With such a strong and regular diel turbidity cycle observable at sites A and E during the spring and summer months, it is important to rule out any potential instrument artefacts being responsible for inducing these trends if there is to be confidence in relating them to bioturbation. Firstly, it is necessary to recognise that turbidity is just a surrogate measure of SPM concentration and other factors, such as phytoplankton blooms, can lead to an increase in turbidity without the requirement for elevated SPM concentrations. However, the SPM-turbidity calibrations were robust over a wide range of values (Fig. 3), so there is confidence in relating turbidity to SPM concentrations.
Along with temperature, the influence of probe exposure to sunlight can also be ruled out as a potential driver of these cycles because the turbidity probes used here were located in flow cells inside the bankside-monitoring kiosks and therefore kept in darkness. Additionally, comparison of turbidity values with an additional probe that was located instream at site E revealed that both probes recorded very similar diel cycles in turbidity with respect to both timing and magnitude (data not shown). Correlation of turbidity with other parameters which display diel cycles, including stage (r = 0.02) and dissolved oxygen (r = 0.33) which can both vary diurnally due to changes in temperature, transpiration and photosynthesis, revealed that changes in these parameters were also unlikely to be causal factors as they do not align with the timings of the turbidity peaks and there exists no obvious mechanistic connection (Fig. 7).
However, diel cycles in stream water pH, which peak at around midday and decline to a minimum around midnight, do correspond more strongly with the turbidity trends. This daily pH variability relates to CO2 consumption during photosynthesis by submergent macrophytes and algae during the day decreasing water acidity and CO2 release at night during respiration increasing acidity (Nimick et al. 2005). Whilst correlation between pH and turbidity is relatively strong (r = 0.45), it is difficult to understand why a regular ~0.1 decrease in pH at night would induce a ~10 NTU increase in turbidity. This is because the more acidic conditions at night should favour dissolution, not precipitation, of carbonate material in the stream and would therefore reduce the suspended particulate fraction. Additionally, the pronounced ~0.2 decline in pH on the 26th April in response to a small rainfall event was not matched by a similarly pronounced shift in turbidity values, indicating low turbidity sensitivity to fluctuating pH.
3.5 Significance and further research
Whilst the evidence presented here does not conclusively prove that the diel turbidity cycles witnessed in the River Blackwater were driven by bioturbation, the seasonality and timing of elevated turbidity, visual observations of crayfish activity and an absence of robust mechanistic connections with other water quality parameters means this represents a plausible causal mechanism. These findings therefore support a growing body of research highlighting the detrimental impact of non-native signal crayfish on fluvial geochemistry, fluvial geomorphology and native aquatic biota (Crawford et al. 2006; Johnson et al. 2010; Harvey et al. 2011). Their large size (typically 10-15 cm in length), aggressive nature, high population densities (up to 20 per square metre) and ability to rapidly colonise new environments have seen signal crayfish populations spread rapidly across Europe putting an increasing number of freshwater environments at risk (Holdich et al. 2014; Kouba et al. 2014). Further research is required in a wider range of fluvial environments at a variety of spatial and temporal scales to fully understand the importance, extent and underlying processes behind the nocturnal fine sediment mobilisation phenomena reported here.
Using high-resolution bankside water quality monitoring, this research presents clear evidence of pronounced diel turbidity cycles under spring baseflow conditions in a lowland headwater river. Increases in median midnight SPM concentrations of up to 76 % compared to midday values, coupled with increased night-time (18:00–05:30) SPM loads of up to 30 % compared with daytime (06:00–17:30) SPM transport, are hypothesised to be caused by the nocturnal feeding and burrowing habitats of aquatic fauna, principally signal crayfish. Correlation of turbidity with other abiotic water quality parameters which similarly exhibit diel cycles (stage, temperature, dissolved oxygen and pH) yielded no robust mechanistic connections which could explain the observed trends. The results presented here add to a growing body of evidence that nocturnal bioturbation may be responsible for significantly impacting upon SPM concentrations under baseflow conditions in headwater streams.
RJC acknowledges financial support from a NERC BGS CASE studentship (NE/J500069/1). The authors would like to thank Jenny Stevenson, Simon Ellis and Zanist Hama-Aziz for fieldwork support and Gilla Suennenberg for providing the GIS data. We are grateful to Salle Farms Co. for their cooperation in granting land access. We thank three anonymous reviewers for their constructive comments which helped improve an earlier version of this manuscript. Further details of this study can be found in the Electronic Supplementary Material.
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