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Eutrophication impacts on a river macrophyte
Aquatic Botany 92 (2010) 173–178
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Aquatic Botany journal homepage: www.elsevier.com/locate/aquabot
Eutrophication impacts on a river macrophyte Matthew T. O’Hare a,*, Ralph T. Clarke b, Michael J. Bowes c, Claire Cailes c, Paul Henville c, Nicola Bissett b, Caroline McGahey d, Margaret Neal c a
CEH Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB, UK Centre for Conservation Ecology and Environmental Change, Bournemouth University, Christchurch House, Talbot Campus, Poole, Dorset BH12 5BB, UK c CEH Wallingford, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire OX10 8BB, UK d HR Wallingford UK, HR Wallingford Ltd, Howbery Park, Wallingford, Oxfordshire OX10 8BA, UK b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 13 February 2009 Received in revised form 5 November 2009 Accepted 7 November 2009 Available online 17 November 2009
The postulated relationship between eutrophication, enhanced standing macrophyte crop and flow impedance was assessed in 14 rivers across the UK. We sampled the July standing crop of Ranunculus subgenus Batrachium at 14 rivers across England and southern Scotland, at sites where there is a known relationship between standing crop and flow impedance. We relate standing crop to variation in carbon concentrations and to elevated phosphorus concentrations, using regression analysis. Standing crop increased significantly with P availability as soluble reactive phosphorus (filtered SRP) and total phosphorus (TP). Best subsets multiple regression analysis suggests that, based on this sample of sites, there is evidence that macrophyte biomass increases with SRP concentrations and also increases with the amount of carbon as HCO3 for a given concentration of SRP in the water. Thus eutrophication is found to increase the standing crop of a submerged aquatic plant in UK rivers. Current targets for P reduction may not be sufficient and managers should now also recognise that eutrophication can exacerbate flood risk by elevating macrophyte standing crop. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Conveyance Crowfoot Phosphorus Ranunculus penicillatus
1. Introduction Eutrophication alters aquatic plant community structure and standing crop in rivers (Carr and Chambers, 1998; Carr et al., 2003). In the UK and elsewhere a large proportion of rivers are considered to have unnaturally high levels of macronutrients (Heathwaite et al., 1996). Here we address the specific concern that eutrophication may enhance flood risk by increasing macrophyte biomass which in turn physically impedes the flow of water, thereby reducing a river’s capacity to convey water in-channel. Field studies have confirmed that channel conveyance reduces as macrophyte standing crop increases (Hamill, 1983; Pitlo and Dawson, 1990; Champion and Tanner, 2000; Dun, 2006). What remains unconfirmed is the influence of eutrophication on standing crop. Papers that report on this issue present conflicting results, either finding no response to P and N or a decline in species diversity and an increase in biomass (Carr and Chambers, 1998). In UK rivers, water crowfoot species Ranunculus subgenus Batrachium are known to impede flow and hence they are routinely cut to maintain channel capacity in rivers (Westlake and Dawson, 1982; Gurnell and Midgley, 1994; Green, 2005, 2006; O’Hare et al.,
* Corresponding author. Tel.: +44 0131 445 8516; fax: +44 0131 445 3943. E-mail address: [email protected] (M.T. O’Hare). 0304-3770/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.aquabot.2009.11.001
submitted for publication). Their ability to impede flow can be beneficial too as they retain water in groundwater fed rivers during summer providing wetted habitat for other aquatic species (Hearne et al., 1994; Armitage and Cannan, 2000). In general water crowfoots are valued as keystone species of high conservation value and the habitats they form are protected under the European Union Habitats and Species Directive (92/43/EEC; Wright et al., 2002; O’Hare et al., 2007). When managing this group there is therefore a trade-off between conservation and flood management. Recently a conceptual model was proposed to describe the complex interaction between nutrient enrichment and macrophytes in rivers (Hilton et al., 2006). The model proposes that as nutrient load (which is not quantified) increases the biomass of the most competitive macrophytes increases until the macrophytes are out-competed by excessive epiphytic growth. This concept is key for flood risk management as the theory predicts eutrophication initially increases then subsequently decreases standing crop of macrophytes. As epiphytes cannot use nutrients held in the sediment as macrophytes can, they are dependent on the readily available nutrients supplied from the water column, hence rivers with high summer nutrient concentrations are most at risk of epiphytes suppressing macrophyte growth (Hilton et al., 2006). However benthic algae, including epiphytes, have a complex ecology
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exhibiting seasonality and responses to a wide range of parameters such as water flow and light (Biggs, 1995; Stevenson et al., 1996). Natural variation in water chemistry can potentially influence standing crop of submerged macrophytes too but to date no measure of the natural variation has been made in the field and its significance is not known. One important natural chemical variable is the availability and speciation of carbon. For photosynthesis, CO2 is less available to submerged aquatic plants than terrestrial plants (Madsen and Sand-Jensen, 2006). R. pseudofluitans can increase its carbon supply by using bicarbonate, an alternative source of inorganic carbon (Newman and Raven, 1999) Macrophytes that are able to use bicarbonate are considered to have a competitive edge in alkaline waters (Spence and Maberley, 1985). Bicarbonate is the major constituent of alkalinity (Neal, 2001). Ranunculus spp. occupy rivers which cover a range of alkalinity with high alkalinity chalk rivers considered their ideal habitat (Preston and Croft, 2001; JNCC, 2005). Yet there has been no quantitative comparison of standing crop along this range of carbon availability although there is strong evidence for changes in community composition (Riis et al., 2000). In this paper we use field data to quantify the relative influence of eutrophication and carbon availability on the standing crop of Ranunculus penicillatus (Dumort.) Bab. The standing crop of R. penicillatus was measured at sites representative of low to high nutrient and alkalinity concentrations, across England and southern Scotland. We test the hypotheses that the biomass of R. penicillatus will increase with nutrient (P) and carbon availability (HCO3, CO2). We also test to see if epiphyte cover increases with P too and whether or not macrophyte biomass is lower at high epiphyte cover than would be expected for a given concentration of P. 2. Materials and methods 2.1. Sites and sampling strategy Fourteen sites were selected where flow was not influenced by artificial instream structures, so that flow conditions at the sites were as natural as possible. At all sites local habitat conditions suited R. penicillatus and so it was abundant and dominated the submerged macrophyte flora. A detailed list of sites and a map of site locations are shown in Fig. 1. Their hydrological character and the response of flow conveyance to standing crop at these sites is detailed in O’Hare et al. (submitted for publication) and O’Hare et al. (2008). Sites were chosen to have a range of growth conditions and nutrient concentrations. None of the sites had significant riparian shading, which can significantly influence standing crop (Dawson and Kern-Hansen, 1978; Canfield and Hoyer, 1988), had been recently subjected to weed maintenance or showed any signs of grazing by waterfowl. Six sites were excluded (leaving the 14 sites used) when severe flooding reduced standing crop. All sites had a maximum water depth of 1 m or less and ranged in width from 2 to 13 m. Experience suggested that a completely random selection of sites in the UK produces a noisy data matrix where alkalinity (and HCO3) and phosphorus concentrations are highly correlated (Dawson et al., 1999). This reflects the fact that the largest inputs of phosphorus from urban areas and intensively farmed land are most often found in southern England, on limestone and chalk bedrock which produce hard, alkaline water. Here we selected sites so the two parameters would not correlate strongly with one another by using stratified random sampling. We created a 2 by 2 search matrix of high versus low alkalinity, as well as high versus low phosphorus, and randomly selected sites to match each of the four combinations in the matrix. Two matrices were used one for the south of England and a second for northern England and
Fig. 1. Site sampling locations, latitude, longitude, with sampling date: 1, R. Allen, 508480 18.746300 , 18590 14.804000 , 2nd August 2007; 2, R. Aln, 558250 1.470000 , 18480 48.864000 , 11th July 2007; 3, R. Avon (Wiltshire), 518150 44.943600 , 18470 52.339500 , 12th July 2007; 4, R. Axe, 508450 48.661100 , 3810 55.836900 , 9th July 2007; 5, R. Biggar, 558370 14.647600 , 38310 16.241800 , 10th July 2007; 6, R. Bourne, 51840 45.886200 , 18460 33.911200 , 31st July 2007; 7, R. Darent 518220 58.948500 , 08130 33.213100 , 26th July 2007; 8, R. Dunn, 518250 2.160700 , 18310 41.813400 , 17th July 2007; 9, East Burn Beck Tributary, 538 590 43.140600 , 08260 27.600100 , 17th July 2007; 10, Great Stour Side Stream, 518170 15.557400 , 1850 6.039700 , 25th July 2007; 11, R. Hooke, 508460 35.602100 , 28340 32.771900 , 5th July 2007; 12, R. Isle, 508580 26.426900 , 28550 1.899100 , 18th July 2007; 13, R. Rye, 548130 4.808400 , 1800 55.497900 , 24th July 2007; 14, R. Wellow, 518180 36.888000 , 28220 57.223800 , 24th July 2007.
southern Scotland. In reality not all squares could be completely filled despite visiting over 600 possible sites because most were partially shaded and high alkalinity sites were rare in the north. All sites were sampled in July and early August 2007. Two teams worked in parallel, one in the north of the survey zone and one in the south. Members of the two teams trained together in the methods used and agreed common routines to ensure all methods
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were carried out in the same way. Plants were identified in the field and were referable to R. penicillatus. 2.2. Macrophyte biomass Plant biomass was sampled using a 0.1 m internal diameter corer (sample area 0.0078 m2). Five replicate samples were taken. The method was adapted to take account of the growth form of R. penicillatus. Biomass is often only collected from within the corer area, but this provides a gross under estimate of the biomass produced from that area of bed. As the plant stand develops during the growing season long stems with capillary leaves grow downstream. To get a clear picture of growth up to the sampling date, each biomass sample was taken at the main point of rooting, normally found at the upstream end of the plant where growth had begun in the spring, and all material arising within the corer area was harvested. On occasion this necessitated uprooting the stems where they had started to root downstream. Plants were cleaned and any roots were removed. The plants were then dried to constant weight at 60 8C and dry weight was measured. Macrophyte biomass is therefore presented as kg DW m2 initial growing area. Macrophyte biomass was chosen in part because it has been demonstrated to influence flow conveyance. It is positively correlated with other biotic metrics which influence conveyance such as plant cover and on its own and in combination with other biotic parameters it is a predictor of Manning’s n roughness value (O’Hare et al., submitted for publication). 2.3. Epiphyte cover Epiphyte cover was measured by taking a section of leaf and stem (each 10 cm long) from 5 plants. The plants differed from those sampled for biomass. Epiphytes were removed from the sections, using a technique from Zimba and Hopson (1997). Samples were shaken vigorously in a bag filled with 500 ml of water for 2 min. The water sample was filtered through preweighed and dried GF/C 0.45 mm filter paper. The material collected on the filter paper was then dried to constant weight at 60 8C and its dry weight measured. The 0.1 m pieces of macrophyte stem were similarly dried and weighed. Epiphyte cover is reported as g DW g1 DW of macrophyte. Samples were always taken from the outside and upper side of stands.
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the phosphomolybdenum blue method of Murphy and Riley (1962). The level of detection was 7 mg l1. Ammonium was determined by automated colorimetry using a Seal Autoanalyser III and a method based on the Berthelot reaction. TP concentration was determined by acid-persulphate digestion and analysis by colourimetry using a Unicam SP1800 spectrophotometer and the phosphomolybdenum blue method (Eisenreich et al., 1975). 2.5. Data analysis Data were tested for normality and relationships tested using regression analysis. The statistical analyses are based on the 14 study sites for which all predictor variables were measured to give consistency in the variation in biomass and sites analysed in all of the multiple and best subsets regressions. Analysis was carried out using Minitab version 15.1 (Systat software, 2006). The relationship between the macrophyte biomass and the individual potential predictor variables was assessed by parametric Pearson’s correlation. Spearman rank correlations were also determined to assess the strength of any non-linear but monotonic relationship between biomass and water chemistry or epiphyte cover and to avoid undue impact of outliers on the estimate of strength of relationship. Best subsets multiple regression (based on Minitab BREG procedure) was then used to assess the joint relationship of two or more predictors with macrophyte biomass at a site. Various alternative forms of best subset regression equations are reported to allow for inter-correlations of predictor variables on their partial regression significance. To allow for the effect of the relative small sample size on inflating true degrees of fit, adjusted R2 (R2adj) are given for each multiple regression. 3. Results All sites were wadeable (mean depth circa 0.48 m) at base flow and ranged in width from 2 to 13 m. All sites had either cobble/ gravel or sand river bed substrates with surface water gradients of circa 1 in 100. Cross-section water velocity ranged from 0.13 to 0.71 m s1. Alkalinity ranged from 1353 to 5033 mequiv. l1, pH from 7.4 to 8.1 and HCO3 ranged from 92 to 98% of total carbon. SRP concentration ranged from the level of detection 7 mg l1 to 319 mg l1. TP ranged from 33 mg l1 to 473 mg l1. R. penicillatus biomass ranged from 3.3 to 121 kg DW m2 initial sample area. 3.1. Primary correlates of standing crop
2.4. Water chemistry In the field, three water samples were taken. The first sample was filtered through a 0.45 mm cellulose nitrate filter and analysed for soluble reactive phosphorus (SRP). The SRP fraction is equivalent to the bioavailable inorganic phosphorus fraction (Nurnberg and Peters, 1984). A second sample was taken and placed in a bottle pretreated with 0.45 g of Potassium persulphate and later analysed for total phosphorus (TP). The final sample was taken by filling a glass bottle to the brim to prevent contamination by air. This sample was later used to measure pH and alkalinity. The samples were taken mid-afternoon and from water adjacent to plants, i.e. not from within the centre of stands. All water samples were insulated and mailed to the laboratory where they were analysed on arrival. Normally samples arrived by the morning after sampling. In the laboratory, pH was measured using a Radiometer PHM210 pH meter. Alkalinity was determined by an acidometric Gran titration (Mackereth et al., 1978). The carbon fractions (CO2 and HCO3) were calculated from alkalinity and pH (Mackereth et al., 1978). SRP concentration was determined by automated colorimetry using a Seal Autoanalyser III and a method based on
To test the hypothesis that standing crop will increase with nutrient and carbon availability we examined the influence on standing crop of the natural drivers of plant growth, HCO3 and CO2 and the influence of the eutrophication drivers, SRP and TP. Because our study sites were carefully chosen using a stratified random selection from a two-way stratification of sites based on phosphorus level (low/high) and alkalinity level (low/high HCO3), then, in our dataset, neither TP or SRP were significantly correlated with either carbon as HCO3 or as CO2 (all correlation p > 0.05; Table 1). Thus any effects of phosphorus (in either form) on macrophyte biomass will be largely uncorrelated and unconfounded with any effects of carbon levels (in either form). The two forms of carbon, CO2 and HCO3, have a moderate correlation but it is not quite statistically significant (r = 0.48, p = 0.081). However, the correlation between SRP and TP amongst our study sites is very high (r = 0.97, p < 0.001), making it potentially difficult to differentiate their relationship with macrophyte biomass. Both forms of phosphorus have significant Pearson correlations (r) with macrophyte biomass, the correlation of biomass with SRP and TP are respectively; r = 0.71, p = 0.004 and r = 0.62, p = 0.018. However, although the relationships between biomass and each
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Table 1 Pearson correlations of macrophyte biomass, soluble reactive phosphorus (SRP), total phosphorus (TP), carbon as CO2 and as HCO3, and epiphyte cover.
SRP TP CO2 HCO3 Epiphyte cover * ** ***
Biomass
SRP
TP
CO2
HCO3
0.71** 0.62* 0.29 0.56* 0.22
0.97*** 0.01 0.21 0.19
0.07 0.22 0.22
0.48 0.39
0.13
Denote correlations significance at p < 0.05 (n = 14 sites. Denote correlations significance at p < 0.01 (n = 14 sites). Denote correlations significance at p < 0.001 (n = 14 sites).
form of phosphorus were monotonic, the corresponding Spearman rank correlation (rS) was statistically significant for SRP (rS = 0.65, p < 0.02) but not for TP (rS = 0.47, p > 0.05) (Fig. 2). The Pearson correlations between biomass and the two phosphorus variables were not improved by log transforming either SRP (r = 0.70) or TP (r = 0.56) and were poorer when working with log biomass or using log–log relationships.
macrophyte biomass increases with SRP concentrations and also increases with the amount of carbon as HCO3 for a given concentration of SRP in the water. The practical strength of this partial relationship with carbon as HCO3 is shown in a double-residual plot (Fig. 3) where the residuals of biomass regressed on SRP are plotted against the residuals of HCO3 regressed on SRP; the correlation between these two sets of residuals is 0.59, which with the correct 11 degrees of freedom has a p value of 0.033. 3.3. The role of epiphytes As theory predicts epiphytes will out compete macrophytes at high P concentrations, we wished to see if there is a decrease in macrophyte biomass with increasing epiphyte cover. Across the 14 sites examined a Pearson correlation between macrophyte biomass and epiphyte cover was not significant and there was no significant trend found when Lowess regression fits were applied (Fig. 2). Epiphyte cover was not significantly correlated with either TP or SRP across the 14 sites (Table 1 and Fig. 2). 4. Discussion
3.2. Can eutrophication and natural drivers work in concert to influence standing crop? To answer this question we first tested the ability of combinations of drivers to predict macrophyte biomass using best subsets multiple regression analysis. This analysis showed that the only multiple regression, involving two or more predictor variables, in which the individual partial regression coefficients of all variables were statistically significant (i.e. p < 0.05) was that involving SRP (p = 0.004) and HCO3 (p = 0.033) (Table 2). This suggests that, based on this sample of sites, there is evidence that
Our primary hypothesis that Batrachian macrophyte biomass would increase with nutrient (P) availability was supported. Anthropogenically elevated concentrations of phosphorus had a more significant influence on biomass than the natural variation in bicarbonate availability. The secondary hypothesis that at high nutrient concentrations epiphytes growth can reduce macrophyte biomass was not supported in the present data (but see Ko¨hler et al., in press). The increase in macrophyte biomass with increasing P is in agreement with observations of increased macrophyte growth
Fig. 2. Bivariate plots of macrophyte biomass, soluble reactive phosphorus (SRP), total phosphorus (TP), carbon as CO2 and as HCO3, and epiphyte cover; lines from Lowess regression fits; rS = Spearman rank correlations of variables with biomass, and * denotes significance at p < 0.05 (n = 14 sites). Biomass units are per initial sample area, kg DW m2.
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Table 2 Best subsets multiple regression equations of macrophyte biomass and a range of habitat variables with, for each variable, its partial regression coefficient, standard error of coefficient and partial significance p values in brackets. Overall adjusted R2 (R2adj) of the full regression is in the last column. Analysis
Variable(s)
Intercept
Bivariate
SRP TP
244 82 196 110
CO2
167 259
SRP
HCO3 Epiphyte cover Multiple subsets
SRP + CO2
R2adj
Partial regression coefficient TP
CO2
HCO3
Epiphyte cover
2.45 0.69 (0.004)
47% 33%
1.52 0.55 (0.018) 2537 2394 (0.310)
194 277
1% 178 77 (0.039)
341 139
25% 1485 1882 (0.445)
6 188
2.43 0.66 (0.004)
SRP + HCO3
208 197
2.14 0.60 (0.004)
SRP + epiphyte cover TP + HCO3
214 111 260 230
2.39 0.73 (0.008)
SRP + HCO3 + epiphyte cover
219 210
2.11 0.63 (0.008)
2455 1678 (0.172)
resulting from effluent discharge in the River Tees, England, the Great Stour, England the Bow River, Alberta and the South Saskatchewan River, Alberta (Butcher, 1933; Fox et al., 1989; Chambers et al., 1991; Carr and Chambers, 1998). Laboratory experiments and field studies conclude that species which dominate in high alkalinity waters do so because they can use bicarbonate as a carbon source, and that high alkalinity waters are likely to support bicarbonate users (Spence and Maberley, 1985; Sand-Jensen, 1989; Madsen and Sand-Jensen, 2006). For a number of species there is evidence that photosynthetic performance is enhanced when bicarbonate is more available (Kahara and Vermaat, 2003). Our findings add weight to these arguments by showing the biomass of R. penicillatus increases with bicarbonate for a given level of SRP across sites. In English rivers it is common for P and N to positively correlate and hence N may increase with P availability at our sites (Bowes et al., 2005). Carr and Chambers (1998) observed that sediment P and N worked in concert to increase macrophyte biomass in rivers with primary limitation by P and secondary limitation by N. If our sites function in a similar manner then this would explain why we did not observe saturation in the macrophyte standing crop response to summer P concentrations.
51% 136 56 (0.033)
1.28 0.50 (0.025)
0%
141 65 (0.052) 134 58 (0.044)
62% 596 1430 (0.685)
43% 49%
328 1218 (0.793)
59%
4.1. Conceptual model revised The conceptual model of river eutrophication (Hilton et al., 2006) contains an inherent assumption that epiphytes do not compete successfully against macrophytes until P concentrations are very high at which stage the macrophytes are rapidly outcompeted and disappear. Macrophytes were not competitively excluded from any of our sites, even those with high P concentrations. This may, in part, be due to the ability of Ranunculus plants to produce more standing crop at higher P, i.e. if their growth rate is faster at higher P then they can compete more effectively with epiphytes than previously believed. Detailed analysis of macrophyte–epiphyte interactions in the River Spree, Germany, suggests that macrophyte growth may not be limited by epiphytes at unshaded sites (Ko¨hler et al., in press). As our study sites were not shaded, conditions may have suited R. penicillatus well and epiphytes may not have limited growth. All study reaches were relatively fast flowing for the rivers concerned too. To successfully exclude macrophytes by shading or by reducing gas flux (carbon and oxygen) to the leaf, epiphytes must reduce light or carbon reaching the plants to a level below that needed for photosynthesis, i.e. the compensation point when carbon fixation matches carbon loss through respiration (Spencer and Bowes, 1990). It is notable that R. penicillatus is quite resistant to light reduction, continuing to grow, albeit very weakly, at circa 20% normal incident light (Dawson and Kern-Hansen, 1978). Where factors other than nutrients (e.g. herbivory or scour) reduce epiphyte cover, as may have happened at our sites, macrophytes may persist all along the P gradient. Although this study was strengthened by the use of a stratified sampling design it was weakened by the small number of sites used and the exclusion of some parameters such as N. 4.2. Recommendations for river management
Fig. 3. Double-residual relationships between R. penicillatus standing crop biomass and carbon as HCO3 adjusted for SRP concentration at a site based on the residuals from their separate linear regression relationships with SRP concentration.
The Environment Agency of England and Wales has set an annual mean target of 100 mg l1 SRP for rivers (Mainstone and Parr, 2002). To attain this concentration requires substantial changes to water treatment facilities and diffuse pollution sources (Kronvang et al., 2009). Currently tertiary treatment is being put in place across the UK at sewage treatment works with the aim of reducing P loading. We know that the ability of macrophytes to impede flow is directly related to their biomass so we can expect
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less flow impedance in the future as P levels drop. In chalk stream systems this has significant implications for biodiversity and flood management. The contribution to flood risk by excess weed growth is likely to be reduced. Acknowledgements This work was partly funded by the Environment Agency of England and Wales through the Aquatic Plant Management Group. Kathryn Hutchinson, Pete Scarlett and Will Beaumont took part in the site search. An anonymous reviewer of an earlier draft provided useful comment. References Armitage, P.D., Cannan, C.E., 2000. Annual changes in the summer patterns of mesohabitat distribution and associated faunal assemblages. Hydrol. Process 14, 3161–3179. Biggs, B.J.F., 1995. The contribution of flood disturbance, catchment geology and land-use to the habitat template of periphyton in stream ecosystems. Freshwater Biol. 33, 419–438. Bowes, M.J., Hilton, J., Irons, G.P., Hornby, D.D., 2005. The relative contribution of sewage and diffuse phosphorus sources in the River Avon catchment, southern England: implications for nutrient management. Sci. Total Environ. 344 (1–3), 67–81. Butcher, R.W., 1933. Studies on the ecology of rivers. I. On the distribution of macrophytic vegetation in the rivers of Britain. J. Ecol. 21, 58–91. Canfield, D.E., Hoyer, M.V., 1988. Influence of nutrient enrichment and light availability on the abundance of aquatic macrophytes in Florida streams. Can. J. Fish Aquat. Sci. 45, 1467–1472. Carr, G.M., Chambers, P.A., 1998. Macrophyte growth and sediment phosphorus and nitrogen in a Canadian prairie river. Freshwater Biol. 39, 525–536. Carr, M.G., Bod, S.A.E., Duthie, H.C., Taylor, W.D., 2003. Macrophyte biomass and water quality in Ontario rivers. J. N Am. Benthol. Soc. 22, 182–193. Chambers, P.A., Prepas, E.E., Hamilton, H.R., Bothwell, M.L., 1991. Current velocity and its effect on aquatic macrophytes in flowing waters. Ecol. Appl. 1, 249–257. Champion, P.D., Tanner, C.C., 2000. Seasonality of macrophytes and interaction with flow in a New Zealand lowland stream. Hydrobiologia 441, 1–12. Dawson, F.H., Newman, J.R., Gravelle, M.J., Rouen, K.J., Henville, P., 1999. Assessment of the trophic status of rivers using macrophytes: evaluation of the Mean Trophic Rank. Environment Agency (R.D. Technical Report E39) 179. Dawson, F.H., Kern-Hansen, U., 1978. Aquatic weed management in natural streams; the effect of shade by marginal vegetation. Verh. Int. Ver. Limnol. 20, 1429–1434. Dun, R.W., 2006. Reducing uncertainty in the hydraulic analysis of canals. Water Manage. 159 WM4 211–WM4 224. Eisenreich, S.J., Bannerman, R.T., Armstrong, D.E., 1975. A simplified phosphorus analytical technique. Environ. Lett. 9, 45–53. Fox, I., Malati, M.A., Perry, R., 1989. The adsorption and release of phosphate from sediments of a river receiving sewage effluent. Water Res. 23, 725–732. Green, J.C., 2005. Velocity and turbulence distribution around lotic macrophytes. Aquat. Ecol. 39, 1–10. Green, J.C., 2006. Effect of macrophyte spatial variability on channel resistance. Adv. Water Resour. 29, 426–438. Gurnell, A.M., Midgley, P., 1994. Aquatic weed growth and flow resistance: influence on the relationship between discharge and stage over a 25 year river gauging station record. Hydrol. Process 8, 63–73. Hamill, L., 1983. Some observations on the time of travel of waves in the River Skerne, England, and the effect of aquatic vegetation. J. Hydrol. 66, 291–304. Hearne, J., Jonhson, I., Armitage, P., 1994. Determination of ecologically acceptable flows in rivers with seasonal changes in the density of macrophyte. Regul. Riv. 9, 117–184. Hilton, J., O’Hare, M.T., Bowes, M.J., Jones, J.I., 2006. How green is my river? A new paradigm of eutrophication in rivers. Sci. Total Environ. 365, 66–83. Heathwaite, A.L., Johnes, P.J., Peters, N.E., 1996. Trends in nutrients. Hydrol. Process 10 (2), 263–293.
JNCC, 2005. Common Standards Monitoring Guidance for Rivers. Joint Nature Conservancy Council, Peterborough. Kahara, S.N., Vermaat, J.E., 2003. The effect of alkalinity on photosynthesis-light curves and inorganic carbon extraction capacity of freshwater macrophytes. Aquat. Bot. 75 (3), 217–228. Ko¨hler, J., Hachoł, J., Hilt, S., in press. Regulation of submersed macrophyte biomass in a temperate lowland river: interactions between shading by bank vegetation, epiphyton and water turbidity. Aquat. Bot. doi:10.1016/j.aquabot.2009.10.018. Kronvang, B., Rubaek, G.H., Heckrath, G., 2009. International phosphorus workshop: diffuse phosphorus loss to surface water bodies-risk assessment, mitigation options, and ecological effects in River Basins. J. Environ. Qual. 38 (5), 1924– 1929. Mackereth, F.J.H., Heron, J., Talling, J.F., 1978. Water Analysis: Some Revised Methods for Limnologists. Freshwater Biological Association Scientific Publications No. 36, Titus Wilson, Windemere. Madsen, T.V., Sand-Jensen, K., 2006. Aquatic plants. In: Sand-Jensen, K., Freiberg, N., Murphy, J. (Eds.), Running Waters, Historical Development and Restoration of Lowland Danish Streams. National Environmental Research Institute, Denmark, pp. 67–74. Mainstone, C.P., Parr, W., 2002. Phosphorus in rivers—ecology and management. Sci. Total Environ. 282, 25–47. Murphy, J., Riley, J.P., 1962. A modified single solution method for the determination of phosphorus in natural waters. Anal. Chim. Acta 12, 31–36. Neal, C., 2001. Alkalinity measurements within natural waters: towards a standardised approach. Sci. Total Environ. 265, 110–115. Newman, J.R., Raven, J.A., 1999. CO2 is the main inorganic species entering photosynthetically active leaf protoplasts of the freshwater macrophyte Ranunculus penicillatus spp. pseudofluitans. Plant Cell Environ. 22, 1019–1026. Nurnberg, G., Peters, R.H., 1984. Biological availability of soluble reactive phosphorus in anoxic and oxic fresh-waters. Can. J. Fish Aquat. Sci. 41, 757–765. O’Hare, M.T, Bissett, N., Cailes, C., Henville, P., Scarlett, P., McGahey, C., submitted for publication. Variability in roughness measurements for vegetated rivers near base flow, in England and Scotland. O’Hare, M.T., Stillman, R.A., Mc Donnell, J., Wood, L., 2007. The effects of mute swan grazing on a keystone macrophyte. Freshwater Biol. 52, 2463–2475. O’Hare, M.T., Cailes, C., Henville, P., Bissett, N., Neal, M., Scarlett, P., 2008. Manning’s n values for vegetated river channels in the UK. National Snapshot Study. (Regional differences in growth patterns within species and implications for uncertainty in conveyance estimation). An Aquatic Plant Management Group Report, Centre for Ecology and Hydrology, UK. Pitlo, R.H., Dawson, F.H., 1990. Flow-resistance of aquatic weeds. In: Pieterse, A.H., Murphy, K.J. (Eds.), Aquatic Weeds the Ecology and Management of Nuisance Aquatic Vegetation. Oxford Science Publications, Oxford, UK, pp. 74–84. Preston, C.D., Croft, J.M., 2001. Aquatic Plants in Britain and Ireland. Harley Books, Colchester, UK. Riis, T., Sand-Jensen, K., Vestergaard, O., 2000. Plant communities in lowland Danish streams: species composition and environmental factors. Aquat. Bot. 66, 255– 272. Sand-Jensen, K., 1989. Photosynthetic carbon sources of stream macrophytes. J. Exp. Bot. 34, 198–210. Spence, D.H.N., Maberley, S.C., 1985. Occurrence and ecological importance of HCO3—USE among aquatic higher plants. In: Lucas, W.J., Berry, J.A. (Eds.), Inorganic Carbon Uptake by Aquatic Photosynthetic Organisms. American Society of Plant Physiologists, Rockville, MD, USA, pp. 125–143. Spencer, W., Bowes, G., 1990. Ecophysiology of troublesome aquatic weeds. In: Pieterse, A.H., Murphy, K.J. (Eds.), Aquatic Weeds the Ecology and Management of Nuisance Aquatic Vegetation. Oxford Science Publications, Oxford, UK, pp. 39–73. Stevenson, J., Bothwell, M.L., Lowe, R.L., 1996. Algal Ecology. Freshwater Benthic Ecosystems. Academic Press, London, UK. Westlake, D.F., Dawson, F.H., 1982. Thirty years of weed cutting on a chalk-stream. In: Proceedings of the 6th European Weed Research Council Symposium on Aquatic Weeds. pp. 132–140. Wright, J.F., Gunn, R.J.M., Winder, J.M., Wiggers, R., Vowles, K., Clarke, R.T., Harris, I., 2002. A comparison of the macrophyte cover and macroinvertebrate fauna at three sites on the river Kennet in the mid 1970s and late 1990s. Sci. Total Environ. 282–283, 121–142. Zimba, P.V., Hopson, M.S., 1997. Quantification of epiphyte removal efficiency from submersed aquatic plants. Aquat. Bot. 58, 117–173.
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Aquatic Botany journal homepage: www.elsevier.com/locate/aquabot
Eutrophication impacts on a river macrophyte Matthew T. O’Hare a,*, Ralph T. Clarke b, Michael J. Bowes c, Claire Cailes c, Paul Henville c, Nicola Bissett b, Caroline McGahey d, Margaret Neal c a
CEH Edinburgh, Bush Estate, Penicuik, Midlothian EH26 0QB, UK Centre for Conservation Ecology and Environmental Change, Bournemouth University, Christchurch House, Talbot Campus, Poole, Dorset BH12 5BB, UK c CEH Wallingford, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire OX10 8BB, UK d HR Wallingford UK, HR Wallingford Ltd, Howbery Park, Wallingford, Oxfordshire OX10 8BA, UK b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 13 February 2009 Received in revised form 5 November 2009 Accepted 7 November 2009 Available online 17 November 2009
The postulated relationship between eutrophication, enhanced standing macrophyte crop and flow impedance was assessed in 14 rivers across the UK. We sampled the July standing crop of Ranunculus subgenus Batrachium at 14 rivers across England and southern Scotland, at sites where there is a known relationship between standing crop and flow impedance. We relate standing crop to variation in carbon concentrations and to elevated phosphorus concentrations, using regression analysis. Standing crop increased significantly with P availability as soluble reactive phosphorus (filtered SRP) and total phosphorus (TP). Best subsets multiple regression analysis suggests that, based on this sample of sites, there is evidence that macrophyte biomass increases with SRP concentrations and also increases with the amount of carbon as HCO3 for a given concentration of SRP in the water. Thus eutrophication is found to increase the standing crop of a submerged aquatic plant in UK rivers. Current targets for P reduction may not be sufficient and managers should now also recognise that eutrophication can exacerbate flood risk by elevating macrophyte standing crop. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Conveyance Crowfoot Phosphorus Ranunculus penicillatus
1. Introduction Eutrophication alters aquatic plant community structure and standing crop in rivers (Carr and Chambers, 1998; Carr et al., 2003). In the UK and elsewhere a large proportion of rivers are considered to have unnaturally high levels of macronutrients (Heathwaite et al., 1996). Here we address the specific concern that eutrophication may enhance flood risk by increasing macrophyte biomass which in turn physically impedes the flow of water, thereby reducing a river’s capacity to convey water in-channel. Field studies have confirmed that channel conveyance reduces as macrophyte standing crop increases (Hamill, 1983; Pitlo and Dawson, 1990; Champion and Tanner, 2000; Dun, 2006). What remains unconfirmed is the influence of eutrophication on standing crop. Papers that report on this issue present conflicting results, either finding no response to P and N or a decline in species diversity and an increase in biomass (Carr and Chambers, 1998). In UK rivers, water crowfoot species Ranunculus subgenus Batrachium are known to impede flow and hence they are routinely cut to maintain channel capacity in rivers (Westlake and Dawson, 1982; Gurnell and Midgley, 1994; Green, 2005, 2006; O’Hare et al.,
* Corresponding author. Tel.: +44 0131 445 8516; fax: +44 0131 445 3943. E-mail address: [email protected] (M.T. O’Hare). 0304-3770/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.aquabot.2009.11.001
submitted for publication). Their ability to impede flow can be beneficial too as they retain water in groundwater fed rivers during summer providing wetted habitat for other aquatic species (Hearne et al., 1994; Armitage and Cannan, 2000). In general water crowfoots are valued as keystone species of high conservation value and the habitats they form are protected under the European Union Habitats and Species Directive (92/43/EEC; Wright et al., 2002; O’Hare et al., 2007). When managing this group there is therefore a trade-off between conservation and flood management. Recently a conceptual model was proposed to describe the complex interaction between nutrient enrichment and macrophytes in rivers (Hilton et al., 2006). The model proposes that as nutrient load (which is not quantified) increases the biomass of the most competitive macrophytes increases until the macrophytes are out-competed by excessive epiphytic growth. This concept is key for flood risk management as the theory predicts eutrophication initially increases then subsequently decreases standing crop of macrophytes. As epiphytes cannot use nutrients held in the sediment as macrophytes can, they are dependent on the readily available nutrients supplied from the water column, hence rivers with high summer nutrient concentrations are most at risk of epiphytes suppressing macrophyte growth (Hilton et al., 2006). However benthic algae, including epiphytes, have a complex ecology
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exhibiting seasonality and responses to a wide range of parameters such as water flow and light (Biggs, 1995; Stevenson et al., 1996). Natural variation in water chemistry can potentially influence standing crop of submerged macrophytes too but to date no measure of the natural variation has been made in the field and its significance is not known. One important natural chemical variable is the availability and speciation of carbon. For photosynthesis, CO2 is less available to submerged aquatic plants than terrestrial plants (Madsen and Sand-Jensen, 2006). R. pseudofluitans can increase its carbon supply by using bicarbonate, an alternative source of inorganic carbon (Newman and Raven, 1999) Macrophytes that are able to use bicarbonate are considered to have a competitive edge in alkaline waters (Spence and Maberley, 1985). Bicarbonate is the major constituent of alkalinity (Neal, 2001). Ranunculus spp. occupy rivers which cover a range of alkalinity with high alkalinity chalk rivers considered their ideal habitat (Preston and Croft, 2001; JNCC, 2005). Yet there has been no quantitative comparison of standing crop along this range of carbon availability although there is strong evidence for changes in community composition (Riis et al., 2000). In this paper we use field data to quantify the relative influence of eutrophication and carbon availability on the standing crop of Ranunculus penicillatus (Dumort.) Bab. The standing crop of R. penicillatus was measured at sites representative of low to high nutrient and alkalinity concentrations, across England and southern Scotland. We test the hypotheses that the biomass of R. penicillatus will increase with nutrient (P) and carbon availability (HCO3, CO2). We also test to see if epiphyte cover increases with P too and whether or not macrophyte biomass is lower at high epiphyte cover than would be expected for a given concentration of P. 2. Materials and methods 2.1. Sites and sampling strategy Fourteen sites were selected where flow was not influenced by artificial instream structures, so that flow conditions at the sites were as natural as possible. At all sites local habitat conditions suited R. penicillatus and so it was abundant and dominated the submerged macrophyte flora. A detailed list of sites and a map of site locations are shown in Fig. 1. Their hydrological character and the response of flow conveyance to standing crop at these sites is detailed in O’Hare et al. (submitted for publication) and O’Hare et al. (2008). Sites were chosen to have a range of growth conditions and nutrient concentrations. None of the sites had significant riparian shading, which can significantly influence standing crop (Dawson and Kern-Hansen, 1978; Canfield and Hoyer, 1988), had been recently subjected to weed maintenance or showed any signs of grazing by waterfowl. Six sites were excluded (leaving the 14 sites used) when severe flooding reduced standing crop. All sites had a maximum water depth of 1 m or less and ranged in width from 2 to 13 m. Experience suggested that a completely random selection of sites in the UK produces a noisy data matrix where alkalinity (and HCO3) and phosphorus concentrations are highly correlated (Dawson et al., 1999). This reflects the fact that the largest inputs of phosphorus from urban areas and intensively farmed land are most often found in southern England, on limestone and chalk bedrock which produce hard, alkaline water. Here we selected sites so the two parameters would not correlate strongly with one another by using stratified random sampling. We created a 2 by 2 search matrix of high versus low alkalinity, as well as high versus low phosphorus, and randomly selected sites to match each of the four combinations in the matrix. Two matrices were used one for the south of England and a second for northern England and
Fig. 1. Site sampling locations, latitude, longitude, with sampling date: 1, R. Allen, 508480 18.746300 , 18590 14.804000 , 2nd August 2007; 2, R. Aln, 558250 1.470000 , 18480 48.864000 , 11th July 2007; 3, R. Avon (Wiltshire), 518150 44.943600 , 18470 52.339500 , 12th July 2007; 4, R. Axe, 508450 48.661100 , 3810 55.836900 , 9th July 2007; 5, R. Biggar, 558370 14.647600 , 38310 16.241800 , 10th July 2007; 6, R. Bourne, 51840 45.886200 , 18460 33.911200 , 31st July 2007; 7, R. Darent 518220 58.948500 , 08130 33.213100 , 26th July 2007; 8, R. Dunn, 518250 2.160700 , 18310 41.813400 , 17th July 2007; 9, East Burn Beck Tributary, 538 590 43.140600 , 08260 27.600100 , 17th July 2007; 10, Great Stour Side Stream, 518170 15.557400 , 1850 6.039700 , 25th July 2007; 11, R. Hooke, 508460 35.602100 , 28340 32.771900 , 5th July 2007; 12, R. Isle, 508580 26.426900 , 28550 1.899100 , 18th July 2007; 13, R. Rye, 548130 4.808400 , 1800 55.497900 , 24th July 2007; 14, R. Wellow, 518180 36.888000 , 28220 57.223800 , 24th July 2007.
southern Scotland. In reality not all squares could be completely filled despite visiting over 600 possible sites because most were partially shaded and high alkalinity sites were rare in the north. All sites were sampled in July and early August 2007. Two teams worked in parallel, one in the north of the survey zone and one in the south. Members of the two teams trained together in the methods used and agreed common routines to ensure all methods
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were carried out in the same way. Plants were identified in the field and were referable to R. penicillatus. 2.2. Macrophyte biomass Plant biomass was sampled using a 0.1 m internal diameter corer (sample area 0.0078 m2). Five replicate samples were taken. The method was adapted to take account of the growth form of R. penicillatus. Biomass is often only collected from within the corer area, but this provides a gross under estimate of the biomass produced from that area of bed. As the plant stand develops during the growing season long stems with capillary leaves grow downstream. To get a clear picture of growth up to the sampling date, each biomass sample was taken at the main point of rooting, normally found at the upstream end of the plant where growth had begun in the spring, and all material arising within the corer area was harvested. On occasion this necessitated uprooting the stems where they had started to root downstream. Plants were cleaned and any roots were removed. The plants were then dried to constant weight at 60 8C and dry weight was measured. Macrophyte biomass is therefore presented as kg DW m2 initial growing area. Macrophyte biomass was chosen in part because it has been demonstrated to influence flow conveyance. It is positively correlated with other biotic metrics which influence conveyance such as plant cover and on its own and in combination with other biotic parameters it is a predictor of Manning’s n roughness value (O’Hare et al., submitted for publication). 2.3. Epiphyte cover Epiphyte cover was measured by taking a section of leaf and stem (each 10 cm long) from 5 plants. The plants differed from those sampled for biomass. Epiphytes were removed from the sections, using a technique from Zimba and Hopson (1997). Samples were shaken vigorously in a bag filled with 500 ml of water for 2 min. The water sample was filtered through preweighed and dried GF/C 0.45 mm filter paper. The material collected on the filter paper was then dried to constant weight at 60 8C and its dry weight measured. The 0.1 m pieces of macrophyte stem were similarly dried and weighed. Epiphyte cover is reported as g DW g1 DW of macrophyte. Samples were always taken from the outside and upper side of stands.
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the phosphomolybdenum blue method of Murphy and Riley (1962). The level of detection was 7 mg l1. Ammonium was determined by automated colorimetry using a Seal Autoanalyser III and a method based on the Berthelot reaction. TP concentration was determined by acid-persulphate digestion and analysis by colourimetry using a Unicam SP1800 spectrophotometer and the phosphomolybdenum blue method (Eisenreich et al., 1975). 2.5. Data analysis Data were tested for normality and relationships tested using regression analysis. The statistical analyses are based on the 14 study sites for which all predictor variables were measured to give consistency in the variation in biomass and sites analysed in all of the multiple and best subsets regressions. Analysis was carried out using Minitab version 15.1 (Systat software, 2006). The relationship between the macrophyte biomass and the individual potential predictor variables was assessed by parametric Pearson’s correlation. Spearman rank correlations were also determined to assess the strength of any non-linear but monotonic relationship between biomass and water chemistry or epiphyte cover and to avoid undue impact of outliers on the estimate of strength of relationship. Best subsets multiple regression (based on Minitab BREG procedure) was then used to assess the joint relationship of two or more predictors with macrophyte biomass at a site. Various alternative forms of best subset regression equations are reported to allow for inter-correlations of predictor variables on their partial regression significance. To allow for the effect of the relative small sample size on inflating true degrees of fit, adjusted R2 (R2adj) are given for each multiple regression. 3. Results All sites were wadeable (mean depth circa 0.48 m) at base flow and ranged in width from 2 to 13 m. All sites had either cobble/ gravel or sand river bed substrates with surface water gradients of circa 1 in 100. Cross-section water velocity ranged from 0.13 to 0.71 m s1. Alkalinity ranged from 1353 to 5033 mequiv. l1, pH from 7.4 to 8.1 and HCO3 ranged from 92 to 98% of total carbon. SRP concentration ranged from the level of detection 7 mg l1 to 319 mg l1. TP ranged from 33 mg l1 to 473 mg l1. R. penicillatus biomass ranged from 3.3 to 121 kg DW m2 initial sample area. 3.1. Primary correlates of standing crop
2.4. Water chemistry In the field, three water samples were taken. The first sample was filtered through a 0.45 mm cellulose nitrate filter and analysed for soluble reactive phosphorus (SRP). The SRP fraction is equivalent to the bioavailable inorganic phosphorus fraction (Nurnberg and Peters, 1984). A second sample was taken and placed in a bottle pretreated with 0.45 g of Potassium persulphate and later analysed for total phosphorus (TP). The final sample was taken by filling a glass bottle to the brim to prevent contamination by air. This sample was later used to measure pH and alkalinity. The samples were taken mid-afternoon and from water adjacent to plants, i.e. not from within the centre of stands. All water samples were insulated and mailed to the laboratory where they were analysed on arrival. Normally samples arrived by the morning after sampling. In the laboratory, pH was measured using a Radiometer PHM210 pH meter. Alkalinity was determined by an acidometric Gran titration (Mackereth et al., 1978). The carbon fractions (CO2 and HCO3) were calculated from alkalinity and pH (Mackereth et al., 1978). SRP concentration was determined by automated colorimetry using a Seal Autoanalyser III and a method based on
To test the hypothesis that standing crop will increase with nutrient and carbon availability we examined the influence on standing crop of the natural drivers of plant growth, HCO3 and CO2 and the influence of the eutrophication drivers, SRP and TP. Because our study sites were carefully chosen using a stratified random selection from a two-way stratification of sites based on phosphorus level (low/high) and alkalinity level (low/high HCO3), then, in our dataset, neither TP or SRP were significantly correlated with either carbon as HCO3 or as CO2 (all correlation p > 0.05; Table 1). Thus any effects of phosphorus (in either form) on macrophyte biomass will be largely uncorrelated and unconfounded with any effects of carbon levels (in either form). The two forms of carbon, CO2 and HCO3, have a moderate correlation but it is not quite statistically significant (r = 0.48, p = 0.081). However, the correlation between SRP and TP amongst our study sites is very high (r = 0.97, p < 0.001), making it potentially difficult to differentiate their relationship with macrophyte biomass. Both forms of phosphorus have significant Pearson correlations (r) with macrophyte biomass, the correlation of biomass with SRP and TP are respectively; r = 0.71, p = 0.004 and r = 0.62, p = 0.018. However, although the relationships between biomass and each
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Table 1 Pearson correlations of macrophyte biomass, soluble reactive phosphorus (SRP), total phosphorus (TP), carbon as CO2 and as HCO3, and epiphyte cover.
SRP TP CO2 HCO3 Epiphyte cover * ** ***
Biomass
SRP
TP
CO2
HCO3
0.71** 0.62* 0.29 0.56* 0.22
0.97*** 0.01 0.21 0.19
0.07 0.22 0.22
0.48 0.39
0.13
Denote correlations significance at p < 0.05 (n = 14 sites. Denote correlations significance at p < 0.01 (n = 14 sites). Denote correlations significance at p < 0.001 (n = 14 sites).
form of phosphorus were monotonic, the corresponding Spearman rank correlation (rS) was statistically significant for SRP (rS = 0.65, p < 0.02) but not for TP (rS = 0.47, p > 0.05) (Fig. 2). The Pearson correlations between biomass and the two phosphorus variables were not improved by log transforming either SRP (r = 0.70) or TP (r = 0.56) and were poorer when working with log biomass or using log–log relationships.
macrophyte biomass increases with SRP concentrations and also increases with the amount of carbon as HCO3 for a given concentration of SRP in the water. The practical strength of this partial relationship with carbon as HCO3 is shown in a double-residual plot (Fig. 3) where the residuals of biomass regressed on SRP are plotted against the residuals of HCO3 regressed on SRP; the correlation between these two sets of residuals is 0.59, which with the correct 11 degrees of freedom has a p value of 0.033. 3.3. The role of epiphytes As theory predicts epiphytes will out compete macrophytes at high P concentrations, we wished to see if there is a decrease in macrophyte biomass with increasing epiphyte cover. Across the 14 sites examined a Pearson correlation between macrophyte biomass and epiphyte cover was not significant and there was no significant trend found when Lowess regression fits were applied (Fig. 2). Epiphyte cover was not significantly correlated with either TP or SRP across the 14 sites (Table 1 and Fig. 2). 4. Discussion
3.2. Can eutrophication and natural drivers work in concert to influence standing crop? To answer this question we first tested the ability of combinations of drivers to predict macrophyte biomass using best subsets multiple regression analysis. This analysis showed that the only multiple regression, involving two or more predictor variables, in which the individual partial regression coefficients of all variables were statistically significant (i.e. p < 0.05) was that involving SRP (p = 0.004) and HCO3 (p = 0.033) (Table 2). This suggests that, based on this sample of sites, there is evidence that
Our primary hypothesis that Batrachian macrophyte biomass would increase with nutrient (P) availability was supported. Anthropogenically elevated concentrations of phosphorus had a more significant influence on biomass than the natural variation in bicarbonate availability. The secondary hypothesis that at high nutrient concentrations epiphytes growth can reduce macrophyte biomass was not supported in the present data (but see Ko¨hler et al., in press). The increase in macrophyte biomass with increasing P is in agreement with observations of increased macrophyte growth
Fig. 2. Bivariate plots of macrophyte biomass, soluble reactive phosphorus (SRP), total phosphorus (TP), carbon as CO2 and as HCO3, and epiphyte cover; lines from Lowess regression fits; rS = Spearman rank correlations of variables with biomass, and * denotes significance at p < 0.05 (n = 14 sites). Biomass units are per initial sample area, kg DW m2.
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Table 2 Best subsets multiple regression equations of macrophyte biomass and a range of habitat variables with, for each variable, its partial regression coefficient, standard error of coefficient and partial significance p values in brackets. Overall adjusted R2 (R2adj) of the full regression is in the last column. Analysis
Variable(s)
Intercept
Bivariate
SRP TP
244 82 196 110
CO2
167 259
SRP
HCO3 Epiphyte cover Multiple subsets
SRP + CO2
R2adj
Partial regression coefficient TP
CO2
HCO3
Epiphyte cover
2.45 0.69 (0.004)
47% 33%
1.52 0.55 (0.018) 2537 2394 (0.310)
194 277
1% 178 77 (0.039)
341 139
25% 1485 1882 (0.445)
6 188
2.43 0.66 (0.004)
SRP + HCO3
208 197
2.14 0.60 (0.004)
SRP + epiphyte cover TP + HCO3
214 111 260 230
2.39 0.73 (0.008)
SRP + HCO3 + epiphyte cover
219 210
2.11 0.63 (0.008)
2455 1678 (0.172)
resulting from effluent discharge in the River Tees, England, the Great Stour, England the Bow River, Alberta and the South Saskatchewan River, Alberta (Butcher, 1933; Fox et al., 1989; Chambers et al., 1991; Carr and Chambers, 1998). Laboratory experiments and field studies conclude that species which dominate in high alkalinity waters do so because they can use bicarbonate as a carbon source, and that high alkalinity waters are likely to support bicarbonate users (Spence and Maberley, 1985; Sand-Jensen, 1989; Madsen and Sand-Jensen, 2006). For a number of species there is evidence that photosynthetic performance is enhanced when bicarbonate is more available (Kahara and Vermaat, 2003). Our findings add weight to these arguments by showing the biomass of R. penicillatus increases with bicarbonate for a given level of SRP across sites. In English rivers it is common for P and N to positively correlate and hence N may increase with P availability at our sites (Bowes et al., 2005). Carr and Chambers (1998) observed that sediment P and N worked in concert to increase macrophyte biomass in rivers with primary limitation by P and secondary limitation by N. If our sites function in a similar manner then this would explain why we did not observe saturation in the macrophyte standing crop response to summer P concentrations.
51% 136 56 (0.033)
1.28 0.50 (0.025)
0%
141 65 (0.052) 134 58 (0.044)
62% 596 1430 (0.685)
43% 49%
328 1218 (0.793)
59%
4.1. Conceptual model revised The conceptual model of river eutrophication (Hilton et al., 2006) contains an inherent assumption that epiphytes do not compete successfully against macrophytes until P concentrations are very high at which stage the macrophytes are rapidly outcompeted and disappear. Macrophytes were not competitively excluded from any of our sites, even those with high P concentrations. This may, in part, be due to the ability of Ranunculus plants to produce more standing crop at higher P, i.e. if their growth rate is faster at higher P then they can compete more effectively with epiphytes than previously believed. Detailed analysis of macrophyte–epiphyte interactions in the River Spree, Germany, suggests that macrophyte growth may not be limited by epiphytes at unshaded sites (Ko¨hler et al., in press). As our study sites were not shaded, conditions may have suited R. penicillatus well and epiphytes may not have limited growth. All study reaches were relatively fast flowing for the rivers concerned too. To successfully exclude macrophytes by shading or by reducing gas flux (carbon and oxygen) to the leaf, epiphytes must reduce light or carbon reaching the plants to a level below that needed for photosynthesis, i.e. the compensation point when carbon fixation matches carbon loss through respiration (Spencer and Bowes, 1990). It is notable that R. penicillatus is quite resistant to light reduction, continuing to grow, albeit very weakly, at circa 20% normal incident light (Dawson and Kern-Hansen, 1978). Where factors other than nutrients (e.g. herbivory or scour) reduce epiphyte cover, as may have happened at our sites, macrophytes may persist all along the P gradient. Although this study was strengthened by the use of a stratified sampling design it was weakened by the small number of sites used and the exclusion of some parameters such as N. 4.2. Recommendations for river management
Fig. 3. Double-residual relationships between R. penicillatus standing crop biomass and carbon as HCO3 adjusted for SRP concentration at a site based on the residuals from their separate linear regression relationships with SRP concentration.
The Environment Agency of England and Wales has set an annual mean target of 100 mg l1 SRP for rivers (Mainstone and Parr, 2002). To attain this concentration requires substantial changes to water treatment facilities and diffuse pollution sources (Kronvang et al., 2009). Currently tertiary treatment is being put in place across the UK at sewage treatment works with the aim of reducing P loading. We know that the ability of macrophytes to impede flow is directly related to their biomass so we can expect
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less flow impedance in the future as P levels drop. In chalk stream systems this has significant implications for biodiversity and flood management. The contribution to flood risk by excess weed growth is likely to be reduced. Acknowledgements This work was partly funded by the Environment Agency of England and Wales through the Aquatic Plant Management Group. Kathryn Hutchinson, Pete Scarlett and Will Beaumont took part in the site search. An anonymous reviewer of an earlier draft provided useful comment. References Armitage, P.D., Cannan, C.E., 2000. Annual changes in the summer patterns of mesohabitat distribution and associated faunal assemblages. Hydrol. Process 14, 3161–3179. Biggs, B.J.F., 1995. The contribution of flood disturbance, catchment geology and land-use to the habitat template of periphyton in stream ecosystems. Freshwater Biol. 33, 419–438. Bowes, M.J., Hilton, J., Irons, G.P., Hornby, D.D., 2005. The relative contribution of sewage and diffuse phosphorus sources in the River Avon catchment, southern England: implications for nutrient management. Sci. Total Environ. 344 (1–3), 67–81. Butcher, R.W., 1933. Studies on the ecology of rivers. I. On the distribution of macrophytic vegetation in the rivers of Britain. J. Ecol. 21, 58–91. Canfield, D.E., Hoyer, M.V., 1988. Influence of nutrient enrichment and light availability on the abundance of aquatic macrophytes in Florida streams. Can. J. Fish Aquat. Sci. 45, 1467–1472. Carr, G.M., Chambers, P.A., 1998. Macrophyte growth and sediment phosphorus and nitrogen in a Canadian prairie river. Freshwater Biol. 39, 525–536. Carr, M.G., Bod, S.A.E., Duthie, H.C., Taylor, W.D., 2003. Macrophyte biomass and water quality in Ontario rivers. J. N Am. Benthol. Soc. 22, 182–193. Chambers, P.A., Prepas, E.E., Hamilton, H.R., Bothwell, M.L., 1991. Current velocity and its effect on aquatic macrophytes in flowing waters. Ecol. Appl. 1, 249–257. Champion, P.D., Tanner, C.C., 2000. Seasonality of macrophytes and interaction with flow in a New Zealand lowland stream. Hydrobiologia 441, 1–12. Dawson, F.H., Newman, J.R., Gravelle, M.J., Rouen, K.J., Henville, P., 1999. Assessment of the trophic status of rivers using macrophytes: evaluation of the Mean Trophic Rank. Environment Agency (R.D. Technical Report E39) 179. Dawson, F.H., Kern-Hansen, U., 1978. Aquatic weed management in natural streams; the effect of shade by marginal vegetation. Verh. Int. Ver. Limnol. 20, 1429–1434. Dun, R.W., 2006. Reducing uncertainty in the hydraulic analysis of canals. Water Manage. 159 WM4 211–WM4 224. Eisenreich, S.J., Bannerman, R.T., Armstrong, D.E., 1975. A simplified phosphorus analytical technique. Environ. Lett. 9, 45–53. Fox, I., Malati, M.A., Perry, R., 1989. The adsorption and release of phosphate from sediments of a river receiving sewage effluent. Water Res. 23, 725–732. Green, J.C., 2005. Velocity and turbulence distribution around lotic macrophytes. Aquat. Ecol. 39, 1–10. Green, J.C., 2006. Effect of macrophyte spatial variability on channel resistance. Adv. Water Resour. 29, 426–438. Gurnell, A.M., Midgley, P., 1994. Aquatic weed growth and flow resistance: influence on the relationship between discharge and stage over a 25 year river gauging station record. Hydrol. Process 8, 63–73. Hamill, L., 1983. Some observations on the time of travel of waves in the River Skerne, England, and the effect of aquatic vegetation. J. Hydrol. 66, 291–304. Hearne, J., Jonhson, I., Armitage, P., 1994. Determination of ecologically acceptable flows in rivers with seasonal changes in the density of macrophyte. Regul. Riv. 9, 117–184. Hilton, J., O’Hare, M.T., Bowes, M.J., Jones, J.I., 2006. How green is my river? A new paradigm of eutrophication in rivers. Sci. Total Environ. 365, 66–83. Heathwaite, A.L., Johnes, P.J., Peters, N.E., 1996. Trends in nutrients. Hydrol. Process 10 (2), 263–293.
JNCC, 2005. Common Standards Monitoring Guidance for Rivers. Joint Nature Conservancy Council, Peterborough. Kahara, S.N., Vermaat, J.E., 2003. The effect of alkalinity on photosynthesis-light curves and inorganic carbon extraction capacity of freshwater macrophytes. Aquat. Bot. 75 (3), 217–228. Ko¨hler, J., Hachoł, J., Hilt, S., in press. Regulation of submersed macrophyte biomass in a temperate lowland river: interactions between shading by bank vegetation, epiphyton and water turbidity. Aquat. Bot. doi:10.1016/j.aquabot.2009.10.018. Kronvang, B., Rubaek, G.H., Heckrath, G., 2009. International phosphorus workshop: diffuse phosphorus loss to surface water bodies-risk assessment, mitigation options, and ecological effects in River Basins. J. Environ. Qual. 38 (5), 1924– 1929. Mackereth, F.J.H., Heron, J., Talling, J.F., 1978. Water Analysis: Some Revised Methods for Limnologists. Freshwater Biological Association Scientific Publications No. 36, Titus Wilson, Windemere. Madsen, T.V., Sand-Jensen, K., 2006. Aquatic plants. In: Sand-Jensen, K., Freiberg, N., Murphy, J. (Eds.), Running Waters, Historical Development and Restoration of Lowland Danish Streams. National Environmental Research Institute, Denmark, pp. 67–74. Mainstone, C.P., Parr, W., 2002. Phosphorus in rivers—ecology and management. Sci. Total Environ. 282, 25–47. Murphy, J., Riley, J.P., 1962. A modified single solution method for the determination of phosphorus in natural waters. Anal. Chim. Acta 12, 31–36. Neal, C., 2001. Alkalinity measurements within natural waters: towards a standardised approach. Sci. Total Environ. 265, 110–115. Newman, J.R., Raven, J.A., 1999. CO2 is the main inorganic species entering photosynthetically active leaf protoplasts of the freshwater macrophyte Ranunculus penicillatus spp. pseudofluitans. Plant Cell Environ. 22, 1019–1026. Nurnberg, G., Peters, R.H., 1984. Biological availability of soluble reactive phosphorus in anoxic and oxic fresh-waters. Can. J. Fish Aquat. Sci. 41, 757–765. O’Hare, M.T, Bissett, N., Cailes, C., Henville, P., Scarlett, P., McGahey, C., submitted for publication. Variability in roughness measurements for vegetated rivers near base flow, in England and Scotland. O’Hare, M.T., Stillman, R.A., Mc Donnell, J., Wood, L., 2007. The effects of mute swan grazing on a keystone macrophyte. Freshwater Biol. 52, 2463–2475. O’Hare, M.T., Cailes, C., Henville, P., Bissett, N., Neal, M., Scarlett, P., 2008. Manning’s n values for vegetated river channels in the UK. National Snapshot Study. (Regional differences in growth patterns within species and implications for uncertainty in conveyance estimation). An Aquatic Plant Management Group Report, Centre for Ecology and Hydrology, UK. Pitlo, R.H., Dawson, F.H., 1990. Flow-resistance of aquatic weeds. In: Pieterse, A.H., Murphy, K.J. (Eds.), Aquatic Weeds the Ecology and Management of Nuisance Aquatic Vegetation. Oxford Science Publications, Oxford, UK, pp. 74–84. Preston, C.D., Croft, J.M., 2001. Aquatic Plants in Britain and Ireland. Harley Books, Colchester, UK. Riis, T., Sand-Jensen, K., Vestergaard, O., 2000. Plant communities in lowland Danish streams: species composition and environmental factors. Aquat. Bot. 66, 255– 272. Sand-Jensen, K., 1989. Photosynthetic carbon sources of stream macrophytes. J. Exp. Bot. 34, 198–210. Spence, D.H.N., Maberley, S.C., 1985. Occurrence and ecological importance of HCO3—USE among aquatic higher plants. In: Lucas, W.J., Berry, J.A. (Eds.), Inorganic Carbon Uptake by Aquatic Photosynthetic Organisms. American Society of Plant Physiologists, Rockville, MD, USA, pp. 125–143. Spencer, W., Bowes, G., 1990. Ecophysiology of troublesome aquatic weeds. In: Pieterse, A.H., Murphy, K.J. (Eds.), Aquatic Weeds the Ecology and Management of Nuisance Aquatic Vegetation. Oxford Science Publications, Oxford, UK, pp. 39–73. Stevenson, J., Bothwell, M.L., Lowe, R.L., 1996. Algal Ecology. Freshwater Benthic Ecosystems. Academic Press, London, UK. Westlake, D.F., Dawson, F.H., 1982. Thirty years of weed cutting on a chalk-stream. In: Proceedings of the 6th European Weed Research Council Symposium on Aquatic Weeds. pp. 132–140. Wright, J.F., Gunn, R.J.M., Winder, J.M., Wiggers, R., Vowles, K., Clarke, R.T., Harris, I., 2002. A comparison of the macrophyte cover and macroinvertebrate fauna at three sites on the river Kennet in the mid 1970s and late 1990s. Sci. Total Environ. 282–283, 121–142. Zimba, P.V., Hopson, M.S., 1997. Quantification of epiphyte removal efficiency from submersed aquatic plants. Aquat. Bot. 58, 117–173.