Verh. Internat. Verein. Limnol. 2008, vol. 30, Part 2, p. 275–278, Stuttgart, April 2008 © by E. Schweizerbart’sche Verlagsbuchhandlung 2008
The effects of flow regulation on food-webs of Boreal Shield Rivers Jérôme Marty, Michael Power and Karen E. Smokorowski
Introduction Alteration of flow regimes is a major threat to the functioning of lotic food-webs and is responsible for a wide range of ecological responses, including biodiversity loss (BUNN & ARTHINGTON 2002), reduction of food-chain length at lower trophic levels (MARKS et al. 2000), or diversion of energy flow from top consumers (WOOTTON et al. 1996). Despite growing recognition of the effects of flow disturbances on biota, quantitative understanding and/or predictive models of biotic responses to altered flow regimes are lacking. Consequently, environmental regulations that help to sustain lotic ecosystem ecological integrity are weakened. Such difficulty may stem from ignoring the complexity of flow as a combination of many variables including magnitude, frequency, timing, duration, or rate of change (ARTHINGTON et al. 2006), which have differing consequences on the biota (POWER et al. 1996). We applied a stable isotope (SI) approach to determine the impacts of a flow perturbation on food-web structure in rivers. The carbon and nitrogen isotopic compositions of organisms (δ13C and δ15N) are useful to characterize main sources of carbon and positions in the food-web because of the consistent fractionation between consumers and diet (FRY & SHERR 1984, FRANCE 1996, VANDER ZANDEN & R ASMUSSEN 2001). In natural streams, the application of SI techniques revealed the importance of flow as a key variable driving the variation in δ13C of primary producers (FINLAY et al. 1999, MCCUTCHAN & LEWIS 2001, TRUDEAU & R ASMUSSEN 2003). The controlling effect of flow at the base of the food-web has been further detected at higher trophic levels based on cross-ecosystem studies showing relationships between the carbon isotopic composition of consumers and basin characteristics such as drainage area (MCNEELY et al. 2006) and geochemistry (JEPSEN & WINEMILLER 2007). Stable isotope techniques have also been successfully applied to study the response of food-web structure to anthropogenic perturbations such as nutrient loading (A NDERSON & CABANA 2006) or contaminant accumulation (CABANA & R ASMUSSEN 1994). Despite the great potential of SI techniques to identify impoundment and flow-related perturbations, they are rarely used to quantify food-web structure in regulated systems. We report on the effect of flow regulation on carbon sources and food-web structure of boreal streams based on a eschweizerbartxxx
large-scale in situ experiment. We related variations in the flow regime to the carbon and nitrogen stable isotope composition of aquatic vegetation, invertebrates, and fish. This study aimed to determine the effects of (1) impoundment and (2) variation in the ramping rate (RR – or rate of change) regime on the food-web of a regulated stream. Key words: food-web, regulated rivers, stable isotopes
Study site The regulated Magpie River (48°0´N; 84°7´W) and the unregulated Batchawana River (47°0´N; 84°3´W) are situated on the north shore of Lake Superior in the Boreal Shield region. They were sampled in spring and summer over a 4-year period. Impoundment effects on the stable isotope composition of organisms were assessed by comparing measurements from control sites (3 sites on BR and 1 upstream site above the dam on the MR) to impacted sites (2 sites below the dam on the MR). Variations in ramping rates were applied at impacted sites, allowing for further identification of the effects of flow variation on the food web. In 2003 and 2004 (before perturbation), restrictions in RR regimes were applied on the MR where RR did not exceed 1 m3·s–1·h–1 from October to November; from November to spring freshet, RRs were increased to 2 m3·s–1·h–1; from spring freshet to October RRs were restricted to 25% of the preceding hourly discharge. This restriction period was followed by 2 years (after perturbation, 2005 and 2006) of unrestricted RR regimes. Analysis of variance (ANOVA) was used to detect significant differences between control and impacted sites and between before and after manipulations.
Methods Aquatic vegetation, macroinvertebrates, and fish were collected at each site following standard sampling methods described in HAUER & LAMBERTI (2006). Samples were kept frozen until they were dried at 50 °C and ground into powder. Carbon and nitrogen stable isotope compositions were determined at the 0368-0770/08/0275 $ 1.00 © 2008 E. Schweizerbartsche Verlagsbuchhandlung, D-70176 Stuttgart
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University of Waterloo-Environmental Isotope Laboratory (uwEILAB) on a Thermo Finnigan Mat Delta Plus Mass Spectrometer, coupled to a Carlo Erba Elemental Analyzer (NA1500). Results are given using the standard δ notation with δ = [(Rsample /R reference) – 1] × 1000, expressed in units per thousand (‰) and R = 13C/12C or 15N/14N (VERARDO et al. 1990). A secondary standard (cellulose) of known relation with the international standard of Pee Dee Belemnite and atmospheric nitrogen were used as reference materials for carbon and nitrogen respectively. Precision on SI measurement was calculated as the standard deviation of a series of repeated sample signatures and was on average 0.11 and 0.08‰ for C and N, respectively.
Results and discussion A significant difference in the δ13C of all organisms was observed between control and impacted sites (Fig. 1, top panel), with a 3‰ depletion for organisms situated below the dam compared to control sites. The mean value reported for aquatic vegetation was similar to that of other
Fig. 1. Top panels represent the mean (± S. E.) δ13C (left) and δ15N (right) (‰) in unperturbed (Control) and perturbed (Impacted) sites, under ramping rate restrictions (Before) and with unrestricted ramping (After). Bars not connected by the same letter are significantly different (ANOVA, p < 0.05). The bottom panel represents the mean (± S. E.) δ15N (‰) of 4 trophic levels in impacted sites before (solid black) and after (hatched) ramping rate manipulation. Significant differences before and after ramping rates restrictions are indicated by an asterisk (t-test, * = p < 0.05).
levels of the food-web (ANOVA, p > 0.05), indicating that autochthonous production was the main carbon source fuelling the entire food web in these systems. The difference in δ13C between control and impacted sites was therefore related to factors that control δ13C of algae, such as the concentration and δ13C of inorganic carbon, algal fractionation, and growth rate (FINLAY 2004). In regulated systems, the concentration and δ13C of inorganic carbon are likely influenced by carbon cycling occurring upstream in the reservoir, which may be responsible for lighter DIC signatures and higher DIC concentrations that result from carbon recycling and methane oxidation (LENNON et al. 2006). In addition, higher mean flow in regulated systems may have reduced the thickness of the algal boundary layer, thereby shifting δ13C of algae toward lighter values (FINLAY et al. 1999). Mean δ13C signatures measured before and after RR manipulation were similar (Fig. 1, top panel), indicating that RR restrictions had no effect on baseline carbon signatures and did not modify the source of carbon fuelling the food web of these systems.
J. Marty et al., Effects of flow regulation
Similar to carbon SI composition, impoundment was responsible for a significant enrichment of 2.9‰ in δ15N measured for the overall food web at impacted sites compared to control sites (Fig. 1, top panel). A hypothesis supporting such a difference may involve the loading of nitrogen compounds with different signatures or nitrogen transformation processes occurring in a given system. JONES (2004) found higher baseline δ15N signatures in nutrient-limited lakes in which isotopic fractionation was reduced. Similar trends might be expected at our impacted sites influenced by the upstream reservoir. Although only significant at the base of the food web, the unrestricted RR flow regime was also responsible for higher δ15N values. The difference in δ15N under restricted and unrestricted RR conditions differed among organisms and ranged from 1.4 to 0.5‰, with decreasing values from the base to the top of the food web (Fig. 1 bottom panel). Several processes may be involved in raising δ15N values at the base of the food web, such as (1) microbial transformation of organic N to inorganic N, (2) algal and bacterial nitrogen uptake, and (3) nitrification/denitrification (HAMILTON et al. 2001). To our knowledge, little is known about the hydrological effects of ramping rate variations on lotic systems, and this study provides evidence that the complexity of flow must be considered when identifying the effects of perturbations in regulated systems. eschweizerbartxxx
Conclusions This study indicated that stable isotope analysis can be successfully applied to track effects of flow variation on the foodweb structure of regulated systems. Variations in δ13C and δ15N indicate that disruptions in carbon and nitrogen cycling due to impoundment and flow regulation are observed in the downstream food web. Furthermore, we found that the ramping rate regime influences the δ15N composition of organisms at the base of food web, with limited effects on higher trophic levels. Although beyond the scope of this study, relating δ15N variations to physical and chemical variables will be useful to precisely determine the effects of flow disruptions on lotic foodwebs.
Acknowledgements This work was conducted as part of the Magpie River Ramping Rate Study supported by the Ontario Centre of Excellence, the University of Waterloo, Fisheries and Oceans Canada, Brookfield Power Ltd., and the Ontario Ministry of Natural Resources. Technical assistance from Tobin Waterworth, Lisa Voigt and Marla Thibodeau was much appreciated.
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Authors’ address: Jérôme Marty and Michael Power, Biology Department, University of Waterloo, 200 University Av. West, Waterloo, ON, Canada, N2L 3G1. Corresp. author: J. Marty,
[email protected] Karen E. Smokorowski, Fisheries and Oceans Canada, Great Lakes Laboratory for Fisheries and Aquatic Sciences, 1 Canal Drive, Sault Ste. Marie, ON, Canada P6A 6W4
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