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Methane-Derived Carbon in the Benthic Food Web in Stream Impoundments

  • John Gichimu Mbaka ,

    Affiliation Institute for Environmental Sciences, University of Koblenz-Landau, Landau, Rhineland-Palatinate State, Germany

  • Celia Somlai,

    Affiliation Institute for Environmental Sciences, University of Koblenz-Landau, Landau, Rhineland-Palatinate State, Germany

  • Denis Köpfer,

    Affiliation Institute for Environmental Sciences, University of Koblenz-Landau, Landau, Rhineland-Palatinate State, Germany

  • Andreas Maeck,

    Affiliation Institute for Environmental Sciences, University of Koblenz-Landau, Landau, Rhineland-Palatinate State, Germany

  • Andreas Lorke,

    Affiliation Institute for Environmental Sciences, University of Koblenz-Landau, Landau, Rhineland-Palatinate State, Germany

  • Ralf B. Schäfer

    Affiliation Institute for Environmental Sciences, University of Koblenz-Landau, Landau, Rhineland-Palatinate State, Germany

Methane-Derived Carbon in the Benthic Food Web in Stream Impoundments

  • John Gichimu Mbaka, 
  • Celia Somlai, 
  • Denis Köpfer, 
  • Andreas Maeck, 
  • Andreas Lorke, 
  • Ralf B. Schäfer


Methane gas (CH4) has been identified as an important alternative source of carbon and energy in some freshwater food webs. CH4 is oxidized by methane oxidizing bacteria (MOB), and subsequently utilized by chironomid larvae, which may exhibit low δ13C values. This has been shown for chironomid larvae collected from lakes, streams and backwater pools. However, the relationship between CH4 concentrations and δ13C values of chironomid larvae for in-stream impoundments is unknown. CH4 concentrations were measured in eleven in-stream impoundments located in the Queich River catchment area, South-western Germany. Furthermore, the δ13C values of two subfamilies of chironomid larvae (i.e. Chironomini and Tanypodinae) were determined and correlated with CH4 concentrations. Chironomini larvae had lower mean δ13C values (−29.2 to −25.5 ‰), than Tanypodinae larvae (−26.9 to −25.3 ‰). No significant relationships were established between CH4 concentrations and δ13C values of chironomids (p>0.05). Mean δ13C values of chironomid larvae (mean: −26.8‰, range: −29.2‰ to −25.3‰) were similar to those of sedimentary organic matter (SOM) (mean: −28.4‰, range: −29.3‰ to −27.1‰) and tree leaf litter (mean: −29.8 ‰, range: −30.5‰ to −29.1‰). We suggest that CH4 concentration has limited influence on the benthic food web in stream impoundments.


Allochthonous and autochthonous plant organic matter are major sources of carbon and energy for freshwater ecosystems [1]. Recent studies have revealed that also methane, which can be produced by microbial degradation of organic matter under anoxic conditions, can significantly contribute to the carbon budget of freshwater ecosystems [2]. Part of this gas is released to the atmosphere, where it contributes to the pool of green house gases [3], or is oxidized by methane oxidizing bacteria (MOB) [4]. The biogenic methane in MOB can contribute to the biomass of chironomid larvae [5]. Chironomids are one of the most dominant invertebrate groups in the soft sediments in freshwater ecosystems and their larvae feed mainly on algae or allochthonous organic material and associated microroganisms [6]. CH4 derived organic carbon may constitute a crucial source of carbon and energy for chironomids, in comparison to other aquatic invertebrates, because their burrowing habit creates and exposes them to oxyclines at the sediment-water interface, where MOB density and CH4 oxidation rates are usually high [7][10]. For example, chironomid larvae collected from some lakes were sustained (up to 70%) by CH4 derived carbon [11].

These quantitative estimates are based on the stable carbon isotope signature (δ13C) of CH4 which is highly depleted due to carbon isotopic fractionation related to methanogenesis [12]. Additionally, MOB that oxidize CH4 are usually characterized by further depletion in δ13C [13]. Therefore, organisms that consume MOB have lower δ13C values (typically <−40‰; [14]), in comparison to organisms that feed on plant organic matter (−32 to −21 ‰; [15]). Bunn & Boon [16] determined the δ13C values of invertebrates in backwater pools and found Chironominae larvae to have δ13C values (<−35‰) that were lower than for particulate organic matter (−29 to −25 ‰). Kiyashko et al. [18] and Jones & Grey [19] also reported lower (−64 to −55 ‰) δ13C values for some chironomid larvae than for particulate organic matter in lakes. The observed differences between δ13C values of chironomid larvae and potential food resources led to the conclusion that the chironomid larvae might have fed on MOB, which has very low δ13C values. The carbon isotope composition of consumers (e.g. insects) is determined by their diet and usually potrays an enrichment by about 1 ‰, even though the δ13C can deviate from −3 ‰ to +3 ‰ [20]. Given that methane is isotopically very distinct, stable carbon isotopes are particularly useful for tracing methane derived carbon [17].

Although most existing studies on the importance of CH4 derived carbon in freshwater food webs mainly focused on lakes [2], a wide array of anoxic habitats with high potential for CH4 production also exist in rivers and streams [21][23]. Particularly, impoundments increases the residence time of water, promotes accumulation of organic matter and sediment, and have been identified as hot spots of CH4 emissions [24]. Maeck et al. [24] measured CH4 concentrations in riverine and impoundment reaches and found sediment accumulation in dams to be the main source of CH4 emissions. Guérin et al. [25] reported an increase in CH4 emissions at the downstream sides of impoundments as a result of release of water enriched with CH4.

In shallow aquatic systems such as rice paddies and small lakes, CH4 has been shown to be an important source of energy in the benthic food webs [26][28]. In spite of the high abundance of small in-stream ponds in smaller streams [29], the relationship between CH4 concentrations and stable carbon isotope ratios (δ13C) of chironomid larvae in such systems has not been examined. Globally, there exist millions of small impoundments (height <15 m; [30]). Within this study, we assessed (i) CH4 concentrations in stream and pore-water and (ii) the relationship between CH4 concentrations and δ13C values of chironomid larvae in impoundments located in the Queich River catchment area, South-western Germany. We hypothesized that CH4 would have a significant influence on the δ13C of chironomid larvae.


Ethics statement

This study was conducted in the Queich River catchment area (see coordinates below) and was not conducted in an area requiring research permit (e.g. national park) or private land. This study did not involve endangered or protected species.

Study area and sites

The study was conducted in the Queich River catchment area, Rhineland-Palatinate State, South-western Germany. The Queich River (length: 52 km) originates from the Palatinate forest (49o10′6oN 7o50′48oE) and flows (mean discharge: 1.31 m3 s−1; through the upper Rhine Valley to its confluence with the Rhine River in Germersheim (49o13′39oN 8o23′4oE). The catchment (area: 271 km2) is primarily covered by sandstone and is between 100 m and 673 m above sea level. The Rhineland-Palatinate region has dry climate conditions in summer.

Typical for most stream networks in central Europe, 67 small in-stream impoundments ( have been constructed on the main stem and tributaries of the Queich River, South-western Germany, for various purposes such as hydropower generation and flood control. Here, we selected eleven study sites (e.g. Figure S1 in File S1) located from the downstream to the upstream reaches of the Queich River catchment area (Figure 1, Table S1 in File S1). The study sites were located at five different streams. The sampled impoundments were approximately 0.5–2.0 metres deep and had water bypasses that transported water to the downstream reaches.

Figure 1. Locations of the study impoundments in the Queich River catchment area.

Water chemistry and physical characteristics

Field measurements and sampling were conducted between 9th and 24th June, 2013. Data collection was done between 9 a.m. and 4 p.m. Electrical conductivity, temperature, dissolved oxygen concentration and pH of stream water were measured in situ with a WTW Multi 340i/SET (Wissenschaftlich Werkstätten GmbH, Weilheim, Germany). Average water depth was computed from three measurements taken on a transect across the river channel and current speed was estimated by timing a float over a distance of 5 metres [31]. Water discharge was calculated from velocity, width and depth [31]. Water residence time was calculated as follows:

(i)where: T is the water residence time, V is the volume of water stored in the impoundment, and Q is the water discharge [32]. Nitrate and phosphate concentrations in stream water were determined in the laboratory using Macherey-Nagel viscolor kits (Macherey-Nagel, Düren, Germany).

CH4 concentrations

Concentrations of dissolved CH4 in stream and pore-water were measured at the impoundments. Water samples were collected from each study impoundment using 20 mL serum bottles. The samples for stream water CH4 analysis were collected by filling water to the sample bottles from the bottom to top, and overflowing the sample bottles several times over. Three bottles were completely filled with water at each sampling site and several drops (250 µL) of mercuric chloride were added to each bottle as preservative [33]. The bottles were capped and sealed and transported to the laboratory. A headspace was prepared by replacing 10% of the bottle (i.e. 2 mL) with nitrogen gas. To generate the headspace, each sample bottle was held upside down and a 20 gauge needle was inserted through the septum. Then 2 mL nitrogen gas was added to each bottle using a syringe, while the replaced water sample escaped through the needle. The samples were manually shaken, for 1 minute, to equilibrate the gas between the headspace and the water [34]. The samples were analyzed using a CH4 analyser (Los Gatos Research Inc., Mountain view, CA, U.S.A.). A closed loop was created between the gas inlet and outlet of the analyser. A gas tight syringe was then used to inject 0.5 mL gas sample into the closed loop. The CH4 concentrations were averaged over 30 seconds before and after gas injection. Concentration of the injected gas was computed as:(ii)where: csample is the mol fraction of the sampled gas in parts per million, ΔcLosGatos is the change in mole fraction before and after gas sample injection, VLosGatos = 92.5 mL and VInjection = 0.5 mL.

Sediment samples for pore-water CH4 analysis were obtained at the impoundments, where fine sediment accumulated. Pore-water CH4 concentrations were assessed from sediment cores (1 core per site). Cores were taken at location of soft sediment using a piston corer and analyzed for porosity, carbon:nitrogen (C:N) ratio, total organic carbon (TOC) content and pore-water CH4 concentration. Cut-off syringes (3 mL) were used to extract sediment sub-samples which were immediately placed into crimp capped 20 mL vials containing 3 mL of 2.5% NaCl solution for conservation of the CH4. Pore-water was sampled in the cores from the homogenized upper (0–10 cm) sediment layer, where chironomid larvae are found [35]. The pore-water CH4 samples were measured as described for water samples. For C:N ratio, TOC and porosity, three sediment sub-samples were extracted from the cores (0–10 cm) and placed into glass tubes before analysis in the laboratory.

Chironomid sampling and processing

Chironomid samples were collected from the deepest point in each impoundment using an Ekman grab sampler (Hydro-Bios, Kiel, Germany). Sediments were sieved by passing them through two metal sieves (mesh size: 500 µm and 2 mm). Materials such as stones and large pieces of organic matter (>5 cm) were removed and chironomid larvae were picked from a sorting tray using forceps and placed into 500 mL sample bottles containing river water. In some sites only few chironomids (<5 chironomids) were found. The chironomid samples were transported to the laboratory and transferred to sample bottles containing clean tap water for 24 hours to allow gut clearance. Faecal materials were periodically removed to prevent ingestion by chironomids [36]. Chironomids were sorted by tribe and subfamily [37][40] and size (instar) [41], [42] under a dissecting microscope (magnification: x 40-100). Chironomids of the same tribe, subfamily and size were pooled to obtain sufficient mass (0.5–1 mg) for isotope analysis [43]. Sorting of chironomids by size was done to detect the potential effect of body size on the isotopic signal as demonstrated by Grey et al. [44]. In most cases the limited number of specimens excluded replicate analyses. Therefore, we collected individuals from a site with a high abundance of chironomids to exemplarily determine the δ13C variability from 9 replicates. Second instar larvae were discarded as they were too small for identification and their mass was insufficient for isotope analysis. Before isotope analysis, chironomids were placed into glass tubes, oven dried at 60°C for 24 hours and subsequently stored in a desiccator.

Stable isotope, TOC and C:N analyses

Three replicate sediment samples, from each site were analysed, for δ13C of sedimentary organic matter (SOM), TOC and C:N ratios. They were rinsed with a 2.5% HCL solution for four hours to remove carbonates [45], rinsed three times with demineralised water, oven dried at 60°C for 24 hours and ground using a mortar and pestle. Leaves, for analysis of δ13C of potential allochthonous food resources, were collected from trees near the impoundments, washed with demineralised water, rinsed, oven dried and ground before analysis.

Sediment samples for C:N ratios and TOC were weighed into tin cups (15–20 g) and analysed using a Vario Microcube elemental analyser (Elementar Analysensysteme, Hanau, Germany). The chironomid, SOM and leaf litter samples for stable isotope analysis were also weighed (approximately 0.5–1.0 mg for chironomids and 5–20 mg for SOM and leaf litter) into tin cups before their combustion in an isotope ratio mass spectrometer (ThermoScientific, Bremen, Germany). Stable isotope ratios were expressed in per mille (‰).

Statistical analysis

Relations between variables were tested using Spearman's rank correlation test [46]. Comparisons of CH4 concentrations in pore and stream water, and between δ13C values of chironomids, and leaf litter and SOM were done using paired t-test. A value of p<0.05 was considered as statistically significant. Homogeneity of variances was examined with Bartlett's test and data were square root transformed to improve normality. Statistical analyses were done using the R statistical package [47] and all data are provided in File S1.


Water chemistry and physical characteristics

Water residence time varied from 0.5 to 6.0 minutes. Nutrient concentrations in stream water ranged from 3.5 to 5.0 mg NO3 L−1, and from 0.1 to 0.3 mg PO4 L−1. Water temperature ranged from 10.2 to 18.6°C, whereas electrical conductivity, dissolved oxygen concentrations and water discharge ranged from 61 to 380 µS cm−1, 8.5 to 11.9 mg L−1 and 0.2 to 7.8 m3 s−1 (Table S1 in File S1).

Methane gas concentrations

Average values of dissolved CH4 concentrations in stream water ranged from 0.07 µmol L−1 at Site 6 to 0.7 µmol L−1 at Site 10 (Table 1). Pore-water CH4 concentrations ranged from 0.3 µmol L−1 at Site 7 to 1657.5 µmol L−1 at Site 9, and were statistically significantly (t-value  = 3.1, p = 0.005) higher than the stream water CH4 concentrations. Some pore-water CH4 measurements at sites 3 and 6 differed greatly from the other measurements, either due to disturbance during sampling or gas leakage during analysis, and were therefore taken to be unreliable and excluded from further analysis.

Table 1. Average CH4 concentrations (µmol L−1) and bulk sediment characteristics (TOC, C:N ratio, porosity and δ13C) of samples from the studied impoundments (in parentheses are standard errors, ±SE (when applicable).

δ13C of SOM and leaf litter, C:N ratios and TOC

δ13C values of SOM ranged from −29.3‰ at site 7 to −27.1‰ at site 3 (Table 1), whereas δ13C values of leaf litter ranged from −30.5 ‰ to −29.1‰. C:N ratios of sediment and the TOC ranged from 12.0 at site 3 to 23.2 at site 2, and from 0.2% at site 3 to 3.1% at site 2, respectively (Table 1).

δ13C of chironomids

The chironomids were identified as Chironomini, Tanypodinae and Chironomus sp. Chironomus sp. were only found at site 10 and were not analyzed because they did not provide an adequate pooled mass for isotope analysis. The lowest δ13C value, −29.2 ‰, was measured in a third instar Chironomini larvae collected from site 8, whereas the highest δ13C values, −25.3 ‰, were measured in third instar Tanypodinae larvae collected from Sites 9 and 11 (Table S2 in File S1). Generally, the highest mean δ13C values were measured in third (−25.3±0.01‰) and fourth (−26.3±0.14 ‰) instar Tanypodinae, whereas slightly lower mean δ13C values were measured in fourth (−27.2±0.16 ‰) and third (−26.9±0.25 ‰) instar Chironomini. δ13C values did not differ significantly between third and fourth instar Chironomini larvae (t-value  = 1.4, p = 0.17). The analysis of 9 replicates of fourth instar Chironomini larvae from site 4 had a standard deviation as low as 0.19 ‰ for δ13C (Table S2 in File S1). No significant correlations were observed between CH4 concentrations and δ13C values of chironomids (Figure 2, Table 2). However, δ13C values of chironomid larvae were significantly correlated to those of the SOM and to each other within site (p<0.05) (Table 2). Mean δ13C of chironomid larvae (−26.8 ‰) was more similar to that of the SOM (−28.4 ‰) than leaf litter (−29.8 ‰) and there were significant differences (p<0.05) between δ13C values of chironomids, and SOM and leaf litter.

Figure 2. Relationships between pore-water CH4 concentrations and δ13C values.

TNP 4th, CMI 3rd, CMI 4th and SOM stands for Tanypodinae fourth generation, Chironomini third and fourth generation, and sedimentary organic matter, respectively.

Table 2. Correlations (rho-values) between δ13C values, C:N ratio of bulk sediment, water residence time (min) and CH4 concentrations (*p<0.05).


Methane gas concentrations

CH4 concentrations measured in this study are comparable to those measured in other aquatic ecosystems [48][50]. Pore-water CH4 concentrations showed a highly variable pattern among the impoundments (Table 1). These differences can be attributed to heterogeneity in the distribution of sedimentary organic materials within the impoundments. Sanders et al. [51] found pore-water CH4 concentrations to be influenced by sediment heterogeneity. The authors reported that enhanced retention of sediment by macrophytes (Ranunculus penicillatus) increased pore-water CH4 production in streams. Significantly higher mean CH4 concentrations were recorded in pore than stream water. This can be explained by the fact that CH4 is usually produced in sediments, where anoxic conditions are likely to develop, whereas the stream water is rather well oxygenated (Table S1 in File S1) [21].

Relationship between δ13C of chironomids and methane gas

Few studies examined CH4 as a source of carbon and energy for stream invertebrates (e.g. [52]). In these studies, mean δ13C values of invertebrates supported by CH4 derived carbon were lower (<−40 ‰) than those of potential photoautotrophic food resources, indicating ingestion and assimilation of MOB, which had oxidized isotopically light CH4. This was also demonstrated for lake invertebrates [7], [43], [53], where significant negative relationships between CH4 concentrations and δ13C values of some invertebates indicated ingestion and assimilation of MOB.

Mean δ13C of chironomid larvae ranged from −27.2 (fourth instar Chironomini) to −25.3 ‰ (fourth instar Tanypodinae). The mean δ13C values of potential food resources ranged from −28.4 (SOM) to −29.8 ‰ (leaf litter) and were significantly correlated to those of the chironomids. The similarity of δ13C of Chironomini larvae and SOM can be attributed to the fact that Chironomini larvae are either filterers or gathering-collectors, feeding on fine particulate organic matter in aquatic systems [54]. In comparison to Chironomini, Tanypodinae utilize different types of food (e.g. detritus, oligochaetes, diatoms; [55]) and their δ13C values may be difficult to interpret when compared with the other chironomids. The differences between the δ13C values of chironomids, SOM and leaf litter were within the reported range (±3 ‰) of δ13C values for consumers and their food resources [20].

In the current study, no significant relationships were established between CH4 concentrations in stream and pore-water and δ13C values of chironomid larvae. In the UK, Trimmer et al. [52] found river water to have higher mean (0.16 µmol L−1) CH4 concentrations than pore-water (0.07 µmol L−1). Highly depleted mean δ13C values (<−42 ‰) of Trichoptera larvae (Agapetus fuscipes), relative to those of potential food sources (−38 ‰), were only measured in areas with low pore-water CH4 concentrations. In comparison to Trimmer et al., we recorded higher mean CH4 concentrations in stream and pore-water and the mean δ13C values of chironomid larvae were not low. The type of food consumed by chironomids and presence of MOB influence the δ13C values of chironomid larvae. The short water residence times and the shallow nature of the studied impoundments could have enhanced water turn over rates, mixing of the entire water column and supply of organic matter or periphyton into the benthic zone. Thus, in the case of chironomid larvae feeding on sedimenting organic matter, we would anticipate their δ13C to be similar to that of their food resources. Mixing of the water column may also increase oxygen concentration and CH4 oxidation rates, and reduce CH4 production and the biomass of MOB available to chironomids [9]. For example, Eller et al. [9] recorded two fold higher MOB density in the anoxic waters (0.1 mg L−1 O2) of a stratified lake than in the well mixed and oxygenated waters (9 mg L−1 O2) of a polymictic lake. Additionally, the contribution of MOB to chironomid larvae biomass was higher in the anoxic than oxygenated waters. Jones et al. [11] found that the contribution of MOB to the chironomid larvae biomass was highest at sites with low dissolved oxygen content (2–4 mg L−1). Within the above mentioned studies, the isotopic values of chironomids were more similar to those of the SOM, when they were collected from sediments overlaid by well oxygenated waters. Use of MOB was particularly pronounced under hypoxia or post mixing following on from stratification.

δ13C values of chironomid larvae (mean  =  ∼−27 ‰; −29 to −25 ‰) were similar to those of SOM (mean  =  ∼−28 ‰; −29 to −27 ‰) and leaf litter (mean  =  ∼−29 ‰; −30 to −29 ‰). Additionally, δ13C values of chironomid larvae were significantly correlated to each other. Given that the δ13C values varied little between consumers and their food sources [56], the chironomid larvae collected from the sampled impoundments most likely obtained their carbon through ingestion and assimilation of SOM or allochthonous leaf litter. Other studies using stable carbon isotope analysis also demonstrated SOM and allochthonous plant organic matter as significant sources of carbon and energy for freshwater invertebrates [57]. The C:N ratio can be used to determine the source of organic matter in aquatic ecosystems because autochthonous organic matter generally has lower C:N ratios (e.g. algae: 4–10; [58]) than allochthonous organic matter. The measured C:N ratios (12.0–23.2) of sediments indicated elevated proportions of allochthonous organic matter.

Although the δ13C values of chironomid larvae did not indicate utilization of methane derived carbon, other invertebrates could have used it as a source of energy. For example, Kohzu et al. [59] found coleopterans collected from backwater pools to have lower mean (−40 to −67 ‰) δ13C values than the other invertebrates (e.g. chironomids; −36 ‰), suggesting increased utilization of methane derived carbon. In summary, this study reveals that methane derived carbon did not contribute substantially to chironomid larval biomass in small impoundments, rather that allochthonous organic matter was the main source of energy. Future studies assessing the role of methane derived carbon in stream impoundments should include MOB community characterization, CH4 oxidation rates and fluxes, and δ13C values of other invertebrates.

Supporting Information

File S1.

Supporting figure and tables. Figure S1, Example of a weir that impounded the studied rivers. The white arrow shows the direction of water movement. Table S1, Location and environmental characteristics recorded from the studied impoundments. Table S2, δ13C values (‰) of chironomid larvae from the studied impoundments. For each of the impoundments, between 1 and 9 replicates (n) were made from pooled samples.



We thank Vivian Rhee, Sebastian Geissler, Zeyad Alshboul and Anne König for invaluable practical assistance in the field. We also thank Markus Kurtz for C:N and TOC analyses and Andreas Hirsch for stable isotope analysis.

Author Contributions

Conceived and designed the experiments: JGM RS AL. Performed the experiments: JGM CS AM DK. Analyzed the data: JGM RS. Contributed reagents/materials/analysis tools: RBS AL. Wrote the paper: JGM RBS AL AM CS.


  1. 1. Meili M (1992) Sources, concentrations and characteristics of organic matter in softwater lakes and streams of the Swedish forest region. Hydrobiologia 229: 23–41.
  2. 2. Jones RI, Grey J (2011) Biogenic methane in freshwater food webs. Freshwater Biol 56: 213–229.
  3. 3. Bastviken D, Tranvik LJ, Downing JA, Crill PM, Enrich-Prast A (2011) Freshwater methane emissions offset the continental carbon sink. Science 331: 50.
  4. 4. Kajan R, Frenzel P (1999) The effect of chironomid larvae on production, oxidation and fluxes of methane in a flooded rice soil. FEMS Microbiol Ecol 28: 121–129.
  5. 5. Kiyashko SI (2001) Contribution of methanotrophs to freshwater macroinvertebrates: evidence from stable isotope ratios. Aquat Microb Ecol 24: 203–207.
  6. 6. Berg H (1995) Larval food and feeding behaviour. In: Armitage, P.D., Cranston, P.S. & Pinder, L.C.V. (eds), The Chironomidae: biology and ecology of non biting midges. Chapman& Hall, London. pp 136–168.
  7. 7. Deines P, Grey J (2006) Site-specific methane production and subsequent midge mediation within Esthwaite Water, UK. Arch Hydrobiol 167: 317–334.
  8. 8. Sanseverino AM, Bastviken D, Sundh I, Pickova J, Enrich-Prast A (2012) Methane carbon supports aquatic food webs to the fish level. PLoS ONE 7: e42723–e42723.
  9. 9. Eller G, Deines P, Grey J, Richnow H, Krager M (2005) Methane cycling in lake sediments and its influence on chironomid larval δ13C. FEMS Microbiol Ecol 54: 339–350.
  10. 10. Yasuno N, Shikano S, Shimada T, Shindo K, Kikuchi E (2013) Comparison of the exploitation of methane-derived carbon by tubicolous and non-tubicolous chironomid larvae in a temperate eutrophic lake. Limnology 14: 239–246.
  11. 11. Jones RI, Carter CE, Kelly A, Ward S, Kelly DJ, et al. (2008) Widespread contribution of methane-cycle bacteria to the diets of lake profundal chironomid larvae. Ecology 89: 857–864.
  12. 12. Teh YA, Silver WL, Conrad ME, Borglin SE, Carlson CM (2006) Carbon isotope fractionation by methane-oxidizing bacteria in tropical rain forest soils. J Geophys Res-Biogeo 111: G2.
  13. 13. Summons RE, Jahnke LL, Roksandic Z (1994) Carbon isotopic fractionation in lipids from methanotrophic bacteria: relevance for interpretation of the geochemical record of biomarkers. Geochim Cosmochim Acta 58: 2853–2863.
  14. 14. Zemskaya TI, Sitnikova TY, Kiyashko SI, Kalmychkov GV, Pogodaeva TV, et al. (2012) Faunal communities at sites of gas-and oil-bearing fluids in Lake Baikal. Geo-Marine Lett 32: 437–451.
  15. 15. Hershey A, Binkley E, Fortino K, Keyse M, Medvedeff C, et al. (2010) Use of allochthonous and autochthonous carbon sources by Chironomus in arctic lakes. Verh Internat Verein Limnol 30: 1321–1325.
  16. 16. Bunn SE, Boon PI (1993) What sources of organic carbon drive food webs in billabongs? A study based on stable isotope analysis. Oecologia 96: 85–94.
  17. 17. Zanden MJV, Rasmussen JB (1999) Primary consumer δ13C and δ15N and the trophic position of aquatic consumers. Ecology 80: 1395–1404.
  18. 18. Kiyashko S, Narita T, Wada E (2001) Contribution of methanotrophs to freshwater macroinvertebrates: evidence from stable isotope ratios. Aquat Microb Ecol 24: 203–207.
  19. 19. Jones RI, Grey J (2004) Stable isotope analysis of chironomid larvae from some Finnish forest lakes indicates dietary contribution from biogenic methane. Boreal Environ Res 9: 17–24.
  20. 20. DeNiro MJ, Epstein S (1978) Influence of diet on the distribution of carbon isotopes in animals. Geochim Cosmochim Acta 42: 495–506.
  21. 21. Trimmer M, Maanoja S, Hildrew AG, Pretty JL, Grey J (2010) Potential carbon fixation via methane oxidation in well-oxygenated riverbed gravels. Limnol Oceanogr 55: 560–568.
  22. 22. Shelley F, Grey J, Trimmer M (2014) Widespread methanotrophic primary production in lowland chalk rivers. Proc R Soc Lond B: Biol Sci 281: 20132854.
  23. 23. Crawford JT, Stanley EH, Spawn SA, Finlay JC, Loken LC, et al.. (2014) Ebullitive methane emissions from oxygenated wetland streams. Glob Change Biol Doi:10.1111/gcb.12614.
  24. 24. Maeck A, DelSontro T, McGinnis DF, Fischer H, Flury S, et al. (2013) Sediment trapping by dams creates methane emission hot spots. Environ Sci Technol 47: 8130–8137.
  25. 25. Guérin F, Abril G, Richard S, Burban B, Reynouard C, et al.. (2006) Methane and carbon dioxide emissions from tropical reservoirs: significance of downstream rivers. Geophys Res Lett 33..
  26. 26. Jones RI, Grey J (2004) Stable isotope analysis of chironomid larvae from some Finnish forest lakes indicates dietary contribution from biogenic methane. Boreal Environmen Res 9: 17–24.
  27. 27. Khalil M, Shearer MJ, Rasmussen R, Duan C, Ren L (2008) Production, oxidation, and emissions of methane from rice fields in China. J Geophys Res-Biogeo 113: G00A04.
  28. 28. Minami K, Neue HU (1994) Rice paddies as a methane source. Climate Change 27: 13–26.
  29. 29. Van Looy K, Tormos T, Souchon Y (2014) Disentangling dam impacts in river networks. Ecol Ind 37: 10–20.
  30. 30. WCD (2000) Dams and development. A new framework for decision making, World commision on Dams. Earthscan publications ltd. London Sterling, VA. 399 pages.
  31. 31. Gordon ND, McMahon TA, Finlayson BL (1994) Stream hydrology, an introduction for ecologists. Wiley, New York. 526 pages.
  32. 32. Rueda F, Moreno-Ostos E, Armengol J (2006) The residence time of river water in reservoirs. Ecol model 191: 260–274.
  33. 33. Christian JR, Karl DM (1995) Measuring bacterial ectoenzyme activities in marine waters using mercuric chloride as a preservative and a control. Mar Ecol Prog Ser 123: 217–224.
  34. 34. Baird AJ, Stamp I, Heppell CM, Green SM (2010) CH4 flux from peatlands: a new measurement method. Ecohydrol 3: 360–367.
  35. 35. Deines P, Grey J, Richnow H-H, Eller G (2007) Linking larval chironomids to methane: seasonal variation of the microbial methane cycle and chironomid δ13C. Aquat Microb Ecol 46: 273–282.
  36. 36. Feuchtmayr H, Grey J (2003) Effect of preparation and preservation procedures on carbon and nitrogen stable isotope determinations from zooplankton. Rapid Commun Mass Spectrom 17: 2605–2610.
  37. 37. Ashe P, O'Connor JP (2009) A world catalogue of chironomidae (Diptera). Part 1. Buchonomyiinae, chilenomyiinae, Podominae, Aphoratemiinae, Tanypodinae, Usambaromyiinae, Dimesinae, Prodiamesinae and Telmatogetominae. Irish Biogeographical Society & National Museum of Ireland, Dublin, 445 pages.
  38. 38. Orendt C, Dettinger-klemm A, Spies M (2012) Chironomidae larvae in brakish waters of Germany and adjacent areas. Federal Environment Agency, Berlin, 214 pages.
  39. 39. Orendt C, Spies M (2012) Chironomini (Diptera: Chironomidae). Keys to Central European larvae using mainly macroscopic characters. 2nd revised edition, 64 pages.
  40. 40. Orendt C, Spies M (2012) Chironomus (Meigen). Key to the larvae of importance to biological water analysis in Germany and adjacent areas. 2nd revised edition, 24 pages.
  41. 41. Dillon PM (1985) Chironomid larval size and case presence influence capture success achieved by dragonfly larvae. Freshwat Biol 4: 22–29.
  42. 42. Frouz J, Ali A, Lobinske RJ (2002) Suitability of morphological parameters for instar determination of pestiferous midges Chironomus crassicaudatus and Glyptotendipes paripes (Diptera: Chironomidae) under laboratory conditions. J Am Mosq Control 18: 222–227.
  43. 43. van Hardenbroek M, Lotter AF, Bastviken D, Duc NT, Heiri O (2012) Relationship between δ13C of chironomid remains and methane flux in Swedish lakes. Freshw Biol 57: 166–177.
  44. 44. Grey J, Kelly A, Jones RI (2004) High intraspecific variability in carbon and nitrogen stable isotope ratios of lake chironomid larvae. Limnol Oceanogr 49: 239–244.
  45. 45. Kelly A, Jones RI, Grey J (2004) Stable isotope analysis provides fresh insights into dietary separation between Chironomus anthracinus and C. plumosus. JNABS 23: 287–296.
  46. 46. Hauke J, Kossowski T (2011) Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data. Quaestiones Geographicae 30: 87–93.
  47. 47. R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, Available: Accessed 2014 Jan 6.
  48. 48. Bastviken D, Santoro AL, Marotta H, Pinho LQ, Calheiros DF, et al. (2010) Methane emissions from Pantanal, South America, during the low water season: toward more comprehensive sampling. Environ Sci Technol 44: 5450–5455.
  49. 49. Deborde J, Anschutz P, Guérin F, Poirier D, Marty D, et al. (2010) Methane sources, sinks and fluxes in a temperate tidal Lagoon: The Arcachon lagoon (SW France). Estuar Coast Shelf S 89: 256–266.
  50. 50. Hofmann H, Federwisch L, Peeters F (2010) Wave-induced release of methane: Littoral zones as a source of methane in lakes. Limnol Oceanogr 55: 1990–2000.
  51. 51. Sanders I, Heppell C, Cotton J, Wharton G, Hildrew A, et al. (2007) Emission of methane from chalk streams has potential implications for agricultural practices. Freshw Biol 52: 1176–1186.
  52. 52. Trimmer M, Hildrew AG, Jackson MC, Pretty JL, Grey J (2009) Evidence for the role of methane-derived carbon in a free-flowing, lowland river food web. Limnol Oceanogr 54: 1541.
  53. 53. van Hardenbroek M, Heiri O, Parmentier FJW, Bastviken D, Ilyashuk BP, et al. (2013) Evidence for past variations in methane availability in a Siberian thermokarst lake based onδ13C of chitinous invertebrate remains. Quat Sci Rev 66: 74–84.
  54. 54. Armitage PD, Cranston P, Pinder L (1995) The Chironomidae: biology and ecology of non-biting midges. Chapman and Hall, London. 572 pages.
  55. 55. Baker A, McLachlan A (1979) Food preferences of Tanypodinae larvae (Diptera: Chironomidae). Hydrobiol 62: 283–288.
  56. 56. Peterson BJ, Fry B (1987) Stable Isotopes in Ecosystem Studies. Annu Rev Ecol Evol Syst 18: 293–320.
  57. 57. Fuentes N, Güde H, Straile D (2013) Importance of allochthonous matter for profundal macrozoobenthic communities in a deep oligotrophic lake. Int Rev Hydrobiol 98: 1–13.
  58. 58. Meyers PA (1994) Preservation of elemental and isotopic source identification of sedimentary organic matter. Chem Geol 114: 289–302.
  59. 59. Kohzu A, Kato C, Iwata T, Kishi D, Murakami M, et al. (2004) Stream food web fueled by methane-derived carbon. Aquat Microb Ecol 36: 189–194.