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. Author manuscript; available in PMC: 2019 May 1.
Published in final edited form as: Arch Microbiol. 2018 Jan 15;200(4):623–633. doi: 10.1007/s00203-018-1475-5

Nitrogen-Fixation Activity and the Abundance and Taxonomy of nifH Genes in Agricultural, Pristine, and Urban Prairie Stream Sediments Chronically Exposed to Different Levels of Nitrogen Loading

I R Caton 1,‡, T M Caton 1, M A Schneegurt 1
PMCID: PMC5908754  NIHMSID: NIHMS934871  PMID: 29333588

Abstract

Small streams exert great influences on the retention and attenuation of nitrogen (N) within stream networks. Human land use can lead to increased transport of dissolved inorganic N compounds and downstream eutrophication. Microbial activity in streams is important for maintaining an actively functioning N cycle. Chronically high N loading in streams affects the rates of the central processes of the N cycle by increasing rates of nitrification and denitrification, with biota exhibiting decreased efficiency of N use. The LINXII project measured N-cycle parameters in small streams using 15NO3− tracer release experiments. We concurrently measured N2 fixation rates in six streams of three types (agricultural, pristine, and urban prairie streams) as part of this broader study of major N cycle processes. Nitrogen fixation in streams was significantly negatively correlated with nitrate levels, dissolved inorganic N levels, and denitrification rates. Algal mat and leaf litter samples generally exhibited the highest rates of N2 fixation. The abundance of nifH genes, as measured by real-time PCR, was marginally correlated with N2-fixation rates, but not to other N cycle processes or stream characteristics. The nifH sequences observed were assigned to cyanobacteria, Deltaproteobacteria, Methylococcus, and Rhizobia. Seasonal changes, disturbances, and varying inputs may encourage a diverse, flexible, stable N2-fixing guild. Patchiness in the streams should be considered when assessing the overall impact of N2 fixation, since algal biomass exhibited high rates of N2 fixation.

Keywords: Nitrogen fixation, streams, multirate, real-time PCR, nifH

Introduction

Small headwater streams have great influence on the transport of available N downstream, ultimately contributing to the eutrophication of receiving bodies of water (Dodds and Smith 2016). Spiraling theory suggests that control of N transport and cycling downstream are predominantly in-stream biotic uptake and assimilation, including mineralization, nitrification, and denitrification (Dodds et al. 2002; Webster et al. 2003; Mulholland 2004). Urbanization, cropland fertilization, and high-density livestock operations, among other land uses, can lead to increases over pristine streams in chronic levels of dissolved inorganic nitrogen (DIN) compounds. Nitrification and denitrification rates increase with increases in chronic NO3− levels in streams, essentially increasing N removal, while keeping transport constant (Kemp and Dodds 2002a).

The current report is part of the nationwide Lotic Inter-site Nitrogen eXperiment II (LINX II) field study at the Konza Prairie Biological Station, an LTER in Kansas, that used whole-stream 15NO3− isotope tracer release techniques to measure N cycle processes in nine small streams with varying levels of chronic N loading (O’Brien et al. 2007; Mulholland et al. 2008, 2009; Hall et al. 2009; Knapp et al. 2009; Bernot et al. 2010; Graham et al. 2010; O’Brien and Dodds 2010). The rates of uptake, nitrification, and denitrification were increased 10− to 100-fold in response to chronically high N loading. Denitrification represented only a small portion of the total uptake of NO3−, but was important in the loss of N. A key finding was that the efficiency of NO3− use by biota decreased with increasing N loading. These findings support the Efficiency Loss model of nutrient dynamics and do not fit a 1st-order linear model where N cycling is tied to DIN, but retention efficiency remains constant across streams despite increasing chronic N loading. While saturation was not observed, even in highly loaded streams, acute additions of high levels of NO3− to stream samples demonstrated that uptake can be saturated by short-term loading (Kemp and Dodds 2002b; O’Brien and Dodds 2010). Ambient levels of DIN in streams were low relative to the saturation levels measured by acute NO3− additions. It was suggested that N limitation is severe and likely limits the growth of microbiota (Kemp and Dodds 2002b; Tank and Dodds 2003; Bernot and Dodds 2005; O’Brien and Dodds 2010).

The role of N2 fixation in the N budgets of small streams seems to vary. Some studies have shown substantial contributions of N2 fixation to total N input (Grimm 1987; Howarth et al. 1988a, b; Grimm and Petrone 1997; Arango et al. 2009; Kunza and Hall 2014), while others report little impact of N2 fixation on stream N budgets (Meyer et al. 1981; Triska et al. 1984; Naiman and Melillo 1984; Francis et al. 1985; Marcarelli et al. 2008). Temperature and light conditions are primary controllers of N fixation (Horne and Carmiggelt 1975; Grimm and Petrone 1997). In oligotrophic streams with low DIN, N2 fixation ascends in importance (Marcarelli and Wurtsbaugh 2007; Scott et al. 2009; Lang et al. 2012; Kunza and Hall 2013, 2014). There appears to be interplay between P availability and N2 fixation in streams, with low P levels limiting N2 fixation (Schindler et al. 2008; Scott et al. 2009; Kunza and Hall 2013).

We measured N2-fixation rates by acetylene reduction and performed molecular analyses of diazotrophic microbial community structure in the sediments of six prairie streams from the LINXII effort at Konza Prairie. Several N cycle processes also were measured contemporaneously by collaborators in streams with a range of chronic N loads. The abundance and identity of diazotrophs in stream sediments were determined using the nifH gene, which codes for dinitrogenase reductase, a subunit of the nitrogenase complex (Ueda et al. 1995, Zehr et al. 2003).

Materials and Methods

Site Description and Sample Collection

The Flint Hills region of the Great Plains in Northeast Kansas is a tallgrass prairie used primarily for cattle grazing and agriculture (O’Brien et al. 2007). Two streams were selected from each of three main land-use categories, agricultural, pristine, and urban, and their characteristics are given in Table 1. Kings Creek N4D, North Creek, and Campus Creek were sampled in 2003, with the others sampled in 2004. All analyses were performed near the time of sampling.

Table 1.

Stream characteristics taken from O’Brien et al. (2007).

Stream Type Bottom Width (m) Depth (m) PAR (mole m−2 d−1) GPP (g O2 m−2 d−1) Temperature (°C) DO (mg L−1) Location
Campus Creek Urban cobble/sand 2.56 0.08 44.4 0.3   25.5 8.2   39° 13.723′ N, 96° 39.530′ W
Big Blue River Ditcha Urban concrete 2.10 0.05 56.1 11.9 27.1 10.7 39° 11.135′ N, 96° 33.500′ W
North Creek Agric silt 0.77 0.02 43.2 8.0   21.5 8.7   39° 12.741′ N, 96° 35.584′ W
Natalie’s Creek Agricb cobble 1.20 0.04 29.5 0.2   20.4 7.6   39° 13.723′ N, 96° 39.530′ W
Kings Creek N4D Pristine cobble 2.40 0.07 57.4 2.0   13.5 9.8   39° 05.271′ N, 96° 35.067′ W
Kings Creek K2A Pristine cobble 2.50 0.09 22.7 1.77 17.4 10.1 39° 06.008′ N, 96° 34.454′ W
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a

Informally called Wal-Mart Ditch in O’Brien et al. (2007).

b

Mixed land use area at Kansas State University Farms (26% native vegetation, 30% agriculture, and 45% urban)

Sediment samples were collected cleanly at the start, midpoint, and end of each reach (125 to 300 m; O’Brien et al. 2007). Table 2 provides parameters related to stream N-cycle processes that were measured in conjunction with our study. Sediment samples were collected to a depth of 3-5 cm in ~250-ml Mason jars. Leaf litter and algal mat grab samples were collected haphazardly when observed along a reach. Algal mat samples were collected in 10-ml Vacutainer tubes. Samples for N2-fixation assays were transported at ambient temperature and assays were begun in the laboratory within a few hours. Subsamples held for molecular analyses were placed in sterile containers, frozen immediately in the field, transported on dry ice, and stored at −80 °C prior to analysis.

Table 2.

Stream N cycle parameters taken from O’Brien et al. (2007).

Stream NO3-N (μg L−1) NH4+-N (μg L−1) DON (μg L−1) DIN (μg L−1) Nitrification (μg N m−2 s−1) Denitrification (μg N m−2 s−1) NO3-N flux (μg s−1)
Campus Creek 2900.0 7.8 nd 2908.0 7.00 8.8 8552.0
Big Blue River Ditch 277.0 28.3 472 305.3 0.47 44.0 432.6
North Creek 35.0 31.7 111 66.7 0.03 0.0 8.3
Natalie’s Creek 6.0 3.1 156 9.1 0.08 0.6 8.1
Kings Creek N4D 8.6 0.0 196 8.6 0.22 0.2 115.2
Kings Creek K2A 0.9 6.7 85 7.6 0.09 0.0 24.6
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Acetylene Reduction Assays of Nitrogen Fixation

The metal lids of the 250-ml jars used for sampling were fitted with rubber septa and sealed with silicone vacuum grease creating gas-tight vessels, the headspace of which were accessed by syringe. Jars were filled to approximately two-thirds with sediments that was covered in a layer (~1 cm) of stream water. Since nitrogenase is sensitive to oxygen, the jars were not left open to the air after collection and the small amount headspace oxygen was rapidly exhausted by microbes in the samples. Upon return to the laboratory, acetylene gas was injected into the headspace of the jars (to ~10% v/v). Algal samples were assayed in Vacutainer tubes. Samples with 2 to 6 replicates were incubated at room temperature in natural light and measurements were taken 1, 3, 7, and 14 d after collection. The weights of the sediment samples (~200 g) were recorded to express N2 fixation per g sediment. The planar surface of the sediment sample in the Mason jar was similar to the area from which the sample was collected (diameter = 6 cm) and this was used to estimate N2-fixation rates on an areal basis. Similar estimates were made for algal grab samples.

The conversion of acetylene to ethylene by nitrogenase is used as a surrogate for N2 fixation (Jensen and Cox 1983). The ethylene content of aliquots (0.2 ml) of the headspace gas from the N2-fixation assays were determined using the method of Reddy et al. (1993) by gas chromatography (Hewlett Packard 6890) with hydrogen flame ionization detection and a microbore DB5 column. Adjustments were made for the trace amount of ethylene found in the acetylene gas and a standard curve was generated by diluting commercial ethylene gas. We use a conversion factor of 3.8 acetylene molecules reduced per one dinitrogen molecule reduced (Jensen and Cox 1983). Theoretical ratios of 3:1 are often applied to N2-fixation assays (Horne and Carmiggelt 1975; Grimm and Petrone 1997; Marcarelli and Wurtsbaugh 2006), but a 4:1 conversion ratio also has been used (Zehr and Montoya 2007; Kunza and Hall 2014).

Bivariate correlation analyses were performed in SPSS Statistics v23 (IBM) to derive Pearson coefficients through pairwise comparisons of measured processes, environmental conditions, stream parameters, and gene abundances. Numerical data were log-transformed for analysis, unless otherwise stated. Pearson correlations of p ≤0.05 were considered to be statistically significant in the 2-tailed analyses routinely performed.

Direct Metagenomic DNA Extraction

DNA was directly extracted from sediment, leaf litter, and algal mat samples using the protocol of Bürgmann et al. (2001) with modifications as followed by Kilmer et al. (2014). Environmental samples (~0.5 g) were processed with a bead-beater and extracted with CTAB buffer, followed by phenol extraction and precipitation with polyethylene glycol before collection by centrifugation, washing, and resuspension in buffer. Purity was assessed spectrophotometrically (Genesys 5) by measuring A260/A280 (DNA to protein) and A260/A230 (DNA to humic acids) ratios.

Gene Counting by Real-time PCR

Real-time PCR was performed (Smart Cycler II; Cepheid Technology) following the manufacturer’s instructions. The reaction mixture contained (per 25 μL-reaction): SYBR Premix EX Taq (2x, TaKara), 12.5 μL; PCR forward and reverse primer (10 μM), 0.5 μL each; template DNA extract (≤400 ng), 2 μL; dH2O, 9.5 μL. The nifH gene primers were UNIFF19F (5′–GCIWTYTAYGGIAARGGIGG–3′) and NifDN (3′–ADNGCCATCATYTCNCC–5′) generating a 464-bp amplicon (Zehr and McReynolds 1989; Ueda et al. 1995; Zehr et al. 1995). Real-time PCR amplification began with 60 s at 95 °C, followed by 45 cycles of 5 s at 95 °C, 30 s at 50 °C, and 15 s at 72 °C, and finally a hold at 72 °C for 60 s. Samples were assayed three to six times to determine typical deviations between different extracts of the same sample and from different amplifications of a single extract. A universal bacterial 16S rRNA gene primer set, EUB338 (5′–ACTCCTACGGGAGGCAGCAG–3′) and EUB518 (5′–ATTACCGCGGCTGG–3′), generated a ~200-bp amplicon with PCR as above with 40 s annealing at 53 °C (Fierer et al. 2005). Negative controls were sterile dH2O and a positive control, Cyanothece sp. str. ATCC 51142 genomic DNA, was used to construct standard curves of gene copy number. The threshold value was 30 fluorescence units and Ct was calculated by the instrument. PCR products were confirmed using 2% agarose gel electrophoresis. Melting curves demonstrated high quality real-time PCR products.

Potential inhibition PCR by contaminants in DNA extracts was assessed using an exogenously added kanamycin-resistance gene from Pseudomonas fluorescens R8 Tn5 pho mutant M1 (Williams and Fletcher 1996) grown in LB media supplemented with 50 μg ml−1 kanamycin, as previously described (Caton et al. 2004b). Real-time PCR reactions (annealing at 63 °C) contained a known quantity of the kanamycin gene, aliquots (2 μl) of extracts, and the primers KanR: 5′–GCTGACGGAATTTATGCCTCTTC–3′; positions 572-594 and KanF: 5′–CACCATGAGTGACGACTGAATCC–3′; positions 224-246. Inhibition of PCR amplification was less than 2%, compared to control reactions with no added extract.

NifH Clone Libraries and Cladistics

NifH clone libraries were generated using a TOPO-TA blue-white cloning system in E. coli (Invitrogen). Ten separate amplicon populations were purified by band excision from a 2% agarose gels and pooled for each sample. Clones (~200) were randomly collected and inoculated into 96-well plates. Plasmid isolation and insert sequencing was performed by a commercial vendor (Agencourt) using the UNIFF19F/NifDN primer set. Sequences were trimmed to remove remaining vector regions, leaving reads of 191-278 bp for analysis. The 125 reliable sequences obtained were too short for inclusion as a group in GenBank, but are available from the permanent SOAR repository at Wichita State University (https://soar.wichita.edu/handle/10057/14382).

Sequences were aligned using Clustal-W and trimmed in MacClade v4.08 (Sinauer Associates). Contextual 16S rRNA gene sequences were identified in GenBank using BLAST or by comparison to relevant literature (Ueda et al. 1995). Sequences were trimmed to equal lengths and positions with gaps and ambiguous bases were ignored, giving 191 positions for analysis. PAUP 4.0 b10 generated phylogenetic trees using distance analysis with Jukes-Cantor rules and the neighbor-joining algorithm. The tree was rooted using the sequence from Methanocaldococcus jannaschii as the functional outgroup. The diversity of nifH genes and species assignments between and within the three stream types were compared using MEGA7 (Kumar et al. 2016), the Biodiversity Assessment Tools (BAT) package function beta.multi within R (Cardoso et al. 2014), and log-likelihood ratio tests using the G statistic and two-sample ranking with the Wilcoxon-Mann-Whitney test (Zar 2009).

Results

Rates of Nitrogen Fixation

The results of N2 fixation assays are presented in Table 3 for stream sediment samples taken from three locations along each of six prairie stream reaches. The highest rates of N2 fixation in stream sediments were observed at locations on two reaches of Kings Creek, the least impacted stream, having the lowest nitrate levels in our study (Table 3). Although it is considered an agricultural stream, Natalie’s Creek had nitrate levels as low as the pristine stream Kings Creek at the time of sampling; however, it did not exhibit high N2-fixation rates in sediments. The North Creek agricultural stream sediment had somewhat elevated nitrate levels and a high rate of N2 fixation was observed in some sediment samples. The lowest rates of N2 fixation were observed in the urban stream sediments and these corresponded to the greatest chronic nitrate loads. It should be noted that acetylene reduction assays are surrogates for N fixation and a common conversion factor (3.8) was used here for calculations (Jensen and Cox 1983). While this allows for comparison within these data, actual values for N fixation would be altered if this ratio were to differ substantially between samples. Stable isotope methods would give a direct measure of N fixation activity that could be used to determine if any samples deviated from the common ratio used for conversion, however, the accepted range is 3 to 4 (Horne and Carmiggelt 1975; Zehr and Montoya 2007).

Table 3.

Gene abundances by real-time PCR and rates of N2 fixation by acetylene reduction in sediments along reaches (upstream start to downstream end) of impacted and unimpacted prairie streams. The abundance of bacteria are based on 16S rRNA gene sequences.

Site nifH (# g−1) Bacteria (# g−1) N2 fixation (fmol g−1 h−1)
Kings Creek N4D (pristine)
 Start 8.0 × 104 3.7 × 109 18.6
 Middle 5.0 × 106 1.4 × 1011 ND
 End 3.2 × 105 1.7 × 1011 13.3
Kings Creek K2A (pristine)
 Start 2.0 × 104 2.5 × 1011 2.9
 Middle 4.6 × 104 3.6 × 109 3.2
 End 2.0 × 106 9.8 × 1010 78.1
North Creek (agricultural)
 Start 1.2 × 102 7.1 × 1010 6.2
 Middle 1.2 × 102 5.5 × 106 6.2
 End 3.0 × 102 2.4 × 108 14.8
Natalie’s Creek (agricultural)
 Start 2.0 × 102 4.3 × 1010 2.1
 Middle 2.0 × 102 5.0 × 107 2.3
 End 3.1 × 106 6.0 × 1010 5.6
Big Blue River Ditch (urban)
 Start 2.0 × 102 1.1 × 1010 2.3
 Middle 2.0 × 102 4.0 × 109 2.6
 End 2.0 × 102 3.9 × 109 3.0
Campus Creek (urban)
 Start 4.0 × 103 5.0 × 109 1.9
 Middle 2.5 × 104 2.2 × 1010 1.5
 End 2.2 × 105 3.3 × 1010 1.5
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The rates of N2 fixation across our six prairie streams varied between 1.6 and 28.0 fmol g−1 h−1. The highest rates were observed in pristine prairie streams and the lowest rates were observed in urban stream sediments (Fig. 1). Log-transformed rates and concentrations (n = 6, fd = 4) were used for statistical analyses using Pearson correlations. N2-fixation rates were significantly negatively correlated (r = −0.811, p = 0.050) with the extent of chronic N loading of the streams, as measured by NO3− levels in sediments. In a similar fashion, DIN levels in the streams were negatively correlated with N2-fixation activity in sediments, with marginal statistical significance (r = −0.745, p = 0.089) (Fig. 2). This is expected since nearly all of the DIN was due to NO3− (Table 2), with NO3− and DIN levels significantly positively correlated (r = 0.969, p = 0.001). Rates of N2 fixation were not correlated with NH4-N (r = −0.181, p = 0.731) or with DON (r = 0.691, p = 0.196).

Figure 1.

Figure 1

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Correlation (r2 = 0.66) between the rates of N2 fixation and chronic nitrate loading in six small prairie streams. Nitrate levels are taken from O’Brien et al. (2007).

Figure 2.

Figure 2

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Correlation (r2 = 0.56) between the rates of N2 fixation and DIN levels in six small prairie streams. DIN levels are taken from O’Brien et al. (2007).

Overall rates of denitrification were low and varied from undetectable to 44.0 μg N m−2 s−1 (Fig. 3). Denitrification rates in sediments were significantly negatively correlated with N2-fixation activity (r = −0.809, p = 0.050). The rates of nitrification were not significantly correlated to the rates of N2 fixation (r = −0.616, p = 0.193), nor were NO3− fluxes (r = −0.548, p = 0.260).

Figure 3.

Figure 3

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Correlation (r2 = 0.65) between the rates of N2 fixation and denitrification in six small prairie streams. Denitrification rates are taken from O’Brien et al. (2007).

Significant correlations were not observed between N2-fixation rates and PAR (r = −0.334, p = 0.517) or GPP (r = 0.331, p = 0.522). No significant correlation (r = 0.446, p = 0.376) was found between N2-fixation rates and DO either. The width (r = 0.047, p = 0.929) or depth (r = 0.125, p = 0.814) of the streams did not significantly correlate with N2-fixation rates. A marginally significant negative correlation (r = −0.799, p = 0.057) was observed between temperature and N2-fixation rates across our six streams. Stream type significantly correlated (r = 0.923, p = 0.009) with N2-fixation rates as expected, since the streams had different levels of chronic N loading.

In addition to regular sediment sampling along each reach, targeted grab samples were taken of leaf litter and algal mats along these reaches (Table 4). Rates of N2 fixation in these targeted grab samples were generally higher than in sediment samples. Leaf litter samples from Kings Creek exhibited high rates of N2 fixation in the N4D reach. Natalie’s Creek had algal mats along its banks and these exhibited very high rates of N2 fixation. Similarly, the algal materials from the Big Blue River Ditch also exhibited high rates of N2 fixation. The Big Blue River Ditch is canalized in this region and the algal samples were taken from depressions in the concrete and from algal streamers.

Table 4.

Gene abundances by real-time PCR and rates of N2 fixation by acetylene reduction in leaf litter and algal mat samples along reaches (upstream start to downstream end) of impacted and unimpacted prairie streams. The abundance of bacteria is based on 16S rRNA gene sequences.

Site nifH (# g−1) Bacteria (# g−1) N2 Fixation (fmol g−1 h−1)
Kings Creek N4D
 Start leaves 2.5 × 106 3.4 × 1010 81.9
 End leaves 3.4 × 106 5.8 × 1010 63.3
Kings Creek K2A
 Middle Leaves 6.0 × 104 1.0 × 1010 9.2
Natalie’s Creek
 Middle algae 6.8 × 104 nd 112.8
 End algae 2.4 × 106 nd 82.8
Big Blue River Ditch
 Start algae 2.0 × 102 nd 93.5
 Middle algae 7.6 × 106 4.0 × 1012 62.7
 End algae 2.0 × 102 nd 69.7
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Levels of NifH Genes

Direct DNA extracts were made from field-frozen sediment samples taken at the same locations as those assayed for N2-fixation activity. The greatest overall abundance of nifH genes was observed in the sediments from Kings Creek, with all samples above 104 copies g−1 (Table 3). Campus Creek, an urban stream, had relatively high nifH abundance overall. One sample from Natalie’s Creek also showed high nifH abundance. The abundance of bacterial 16S rRNA genes varied from 108 to 1011 copies g−1 sediment. There was a significant correlation (r = 0.941, p = 0.005) between stream type and bacterial 16S rRNA gene abundance, but there was not a significant correlation (r = 0.588, p = 0.219) between stream type and nifH gene abundance. Chronic NO3− loads were marginally correlated with bacterial 16S rRNA gene abundance (r = 0.756, p = 0.082), while nifH gene abundance was not (r = 0.472, p = 0.345).

There was not a direct correlation between nifH gene abundance and N2-fixation rates (r = 0.295, p = 0.570) when comparing six stream averages or when comparing data for each reach (n = 17, r = 0.381, p = 0.131). The abundance of bacterial 16S rRNA genes was positively correlated (r = 0.830, p = 0.041) with N2-fixation rates, while nifH gene abundance was only marginally correlated (r = 0.704, p = 0.118) with N2-fixation rates. No significant correlations were found between nifH or bacterial 16S rRNA gene abundances with DON, DIN, width, depth, PAR, GPP, DO, nitrate flux, denitrification, or nitrification. NH4-N negatively correlates (r = 0.970, p = 0.006) with nifH gene abundance, but not bacterial 16S rRNA gene abundance (r = 0.485, p = 0.407). There was a significant negative correlation between stream temperature and both nifH gene abundance (r = 0.869, p = 0.025) and bacterial 16S rRNA gene abundance (r = 0.899, p = 0.015).

Targeted grab samples of leaf litter and algal mats mainly gave high abundances of nifH genes (Table 4), similar to the highest values obtained from sediment samples. Small sample size from the canalized concrete bed of Big Blue River Ditch may have led to the low values obtained from two small samples there. No significant correlations were observed between N2-fixation rates, stream type, and nifH gene abundance for the grab samples. While the highest rates of N2 fixation generally were observed in grab samples, this was not correlated with nifH gene abundances.

NifH Gene Clone Libraries

Clone libraries were made from pooled PCR amplicons derived from metagenomic extracts of stream sediment samples. Clones of nifH genes from each of these libraries (125 total clones sequenced) were compared, along with contextual sequences, to generate the summary phylogenetic tree shown in Fig. 4. A complete tree is presented in supporting materials (Fig. S1). NifH genes from members of the Deltaproteobacteria were detected in the sediments of all three stream types, as were nifH genes from Bradyrhizobium, Methylomonas, Rhizobium, and Sinorhizobium. Cyanobacterial nifH sequences were observed in the agricultural and urban streams, although sediments and not algal mats were sampled. Quite a number of groups of nifH sequences that only cluster with sequences from uncultured organisms were observed in each of the streams. These include clones from grass, oil field, and rice soils, Mangrove rhizosphere, and marine environments. The larger cluster near Bradyrhizobium japonicum did not have strong matches to known sequences. No sequences related to Archaea, Azotobacter, Chlorobium, Klebsiella, or Rhodobacter were detected.

Figure 4.

Figure 4

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Dendrogram showing the taxonomic relationships between nifH genes amplified from small prairie streams and contextual nifH gene sequences from GenBank.

Taxonomic assignments were made from nifH sequences and compared across streams, showing obvious differences in guild composition. For example, Methylococcus sequences were only observed in the agricultural stream and sequences related to an uncultured Mangrove soil nifH were found in high abundance only in the urban stream. When isolates are binned at higher taxonomic levels (Cyanobacteria, Deltaproteobacteria, Others, Rhizobia, and Unknowns) the G statistic can be applied. Diazotroph communities among streams significantly differed by stream type by this measure (fd = 4, p <0.001). Whether binning nifH taxons by clade or higher levels, Wilcoxon rank sum analysis supported the hypothesis that diazotroph guild composition varies significantly with stream type (n = 5 to 14, p <0.01 to <0.001). When nifH sequences were examined directly, without assigning taxon and making common evolutionary assumptions (Jukes-Cantor rules), the results were quite different (Table 5). Within-group and between-group mean genetic distances were similar and generally high (>1). Net between group mean distances were low, taken together, indicating that diversity within each group was similar to diversity between the groups. This was supported by beta diversity analyses using Jaccard coefficients where values were consistently high (approaching 1) and were insensitive to randomization between groups. The coefficient of differentiation was very low (0.089 on a scale of 0 to 1), suggesting that the populations of nifH genes among the streams have similarities because there is substantial gene flow between these communities.

Table 5.

Calculated genetic differences within and between nifH clone libraries from streams with different levels of chronic N loading.

Within Group Mean Genetic Distance:
Campus Creek (urban) 0.832
Kings Creek N4D (pristine) 1.138
North Creek (agricultural) 1.092
Between Group Mean Genetic Distance:
Kings Creek N4D vs. Campus Creek 1.169
Kings Creek N4D vs. North Creek 1.145
North Creek vs. Campus Creek 1.060
Net Between Group Mean Genetic Distance:
Kings Creek N4D vs. Campus Creek 0.184
Kings Creek N4D vs. North Creek 0.030
North Creek vs. Campus Creek 0.098
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Discussion

The overall rates of N2 fixation observed for prairie stream sediments in the current report are of the same magnitude as fixation rates from previous studies of small streams (Horne and Carmiggelt 1975; Leland and Carter 1985; Francis et al. 1985, Marcarelli and Wurtsbaugh 2007). The metanalysis of Marcarelli et al. (2008) reported that the mean N2-fixation rate among 22 streams was approximately 1 μmol N fixed m−2 h−1, with a high of 30 μmol N fixed m−2 h−1. Nitrogen-fixation activity in the stream sediments of our study ranged from about 0.1 to 3.0 μmol N fixed m−2 h−1. Rates of N2 fixation were higher in grab samples suggesting that leaf litter and algal biofilms are important contributors to whole-stream N2-fixation activity.

There was a significant correlation between N2-fixation rates and levels of chronic N loading in these small streams (as NO3− or DIN). It is well known that nitrate can inhibit N2-fixation activity and this also has been observed in streams (Capone and Carpenter 1982; Grimm 1994). However, in brackish marshes, N2 fixation proceeded even with the addition of fixed N compounds (Piceno and Lovell 2000). Controls on the rate of N2 fixation appear more complicated than simply a response to NO3− levels. Temperature was found to be correlated with N2-fixation rates in our streams, as observed previously (Horne and Carmiggelt 1975; Grimm and Petrone 1997). Light and productivity (PAR and GPP) however were not correlated with N2-fixation rates. Phosphorus levels were not measured as part of the LINXII project. Denitrification rates were significantly correlated with N2-fixation rates. This was expected since denitrification rates also appear to vary with nitrate levels (Marcarelli and Wurtsbaugh 2006, 2007), although this correlation was not strong in the current study (r = 0.695, p = 0.126).

The rates of NO3− uptake in our streams ranged from 0.24 to 15.4 mg N m−2 h−1, in North Creek and Campus Creek, respectively (O’Brien et al. 2007). Highly impacted urban streams exhibited uptake rates of >5 mg N m−2 h−1, while pristine and agricultural streams exhibited uptake rates of ≤1 mg N m−2 h−1. While NO3− uptake rates were higher than N2-fixation rates for all streams, those with lower uptake rates tended to have higher fixation rates (r = 0.685, p = 0.133). For the pristine prairie stream Kings K2A, the rate of N2 fixation is about 15% of the NO3− uptake rate (on an areal basis). This suggests that N2 fixation can be a significant contributor to stream N budgets. However, for our other pristine prairie stream Kings N4D, the N2-fixation rate was only 2% of the NO3− uptake rate. None of the other streams had N2-fixation rates that were more than 6% of their NO3− uptake rates, with the Big Blue Ditch value being only 0.02%. Taken together, this suggests that the impact of N2 fixation to the N budget of small streams is variable. While N2 fixation may be a substantial contributor in streams with low chronic N loads, this does not appear to be consistent, and N2 fixation does not seem to be a substantial contributor to N budgets in small streams with higher chronic N loads. This is in agreement with previous studies, both in terms of the variability observed across streams, but also in concluding that N2 fixation can be important in certain oligotrophic streams and perhaps only at certain times (Marcarelli and Wurtsbaugh 2007; Marcarelli et al. 2008; Scott et al. 2009; Lang et al. 2012; Kunza and Hall 2013, 2014).

Patchiness is a key feature of small streams, in terms of leaf litter and algal mat distributions, and this reflects differences in N2-fixation rates across stream compartments. The highest rates of N2 fixation are often associated with patches of leaf litter and algal mats, and the current study agrees (Henry and Fisher 2003; Marcarelli et al. 2008). Targeted grab samples in our study exhibited the highest rates of N2 fixation, substantially higher than equivalent amounts of sediments. To better understand the role of N2 fixation in stream N budgets, coverage estimates for algal mats and leaf litter are needed, but this was not done rigorously in the current study. No significant correlations were observed between N2-fixation rates and estimates of fine benthic organic matter or ash-free dry mass (g dry mass m−2) of leaves, wood, and epilithon (estimates from O’Brien et al. 2007). Samples of algal mats exhibited N2-fixation rates some 30-fold greater than in the bottom sediments. Thus, even if only 3% of a basin was covered with algal mats, their contribution to N2 fixation might equal that of the remaining 97% of the basin comprised of sediments.

At Kings Creek N4D, patches of leaf litter were found to have N2-fixation rates that were 4-fold greater than the sediments of this reach. This stream has a cobbled bottom with limited areas of sediment. Seasonal factors and scouring events will have a role in determining the balance between fixation in sediments and leaf litter in streams like Kings Creek. Finally, the concrete basin of Big Blue River Ditch had remarkably productive patches. N2-fixation activity was high in algal communities within depressions and grooves in the concrete and in algal streamers attached to the bottom. The patchiness of organisms actively fixing N make whole-stream assessments more difficult especially since the patches are often transient and subject to changes in stream flow, seasons, and nutrient inputs.

The contribution of N2 fixation to stream N budgets may be more significant in specific patches of streams or in certain streams. Diazotrophs may have a selective advantage in streams with low N loading. The same may be true for microniches where fixed N could be locally limiting, even in bulk sediments that do not appear to be N-limited. Channeling of fixed N compounds from cyanobacteria to attendant bacterial communities is well known (Scott and Marcarelli 2012). The coupling of diazotrophs to symbiotic bacteria (and fungi) can affect microbial community structure more broadly and may influence stream geochemical processes beyond N2 fixation and assimilation (Tank and Dodds 2003; O’Brien et al. 2007).

While correlations emerged between the rates of N cycle processes in our study, few statistically significant correlations were observed between process-level measurements and the abundance of nifH genes, with the exception of temperature and NH4-N levels. There was a strong positive correlation of temperature with both nifH and bacterial 16S rRNA gene abundance. The abundance of nifH genes was not significantly correlated with N2-fixation rates. An explanation for the weakness of the correlation between nifH gene abundance and N2-fixation rates is that nifH gene copy number simply does not reflect the activity of the gene. Examination of nifH transcripts would provide more insight. Diazotrophs are known with more than one copy of their nifH genes, which could skew ratios (Ueda et al. 1995; Zehr et al. 1997). Seasonal changes, disturbances, and changing inputs may encourage a flexible stable guild. It also is possible that the N pollution in these streams has not persisted for long enough to change the abundance and distribution of microbes in the N2-fixing guild. While the abundance of bacterial 16S rRNA genes significantly correlated with stream type, the abundance of nifH genes did not. Further, there were no significant correlations between the abundance of nifH genes and levels of chronic nitrate loading.

We recovered a number of nifH gene sequences from sediment clone libraries that mainly clustered with oligotrophic taxa associated with diazotrophy in soils. There were sequences from Deltaproteobacteria in all stream types for instance. A variety of Rhizobia were detected, but no sequences from Azotobacter or Klebsiella. While the nifH primers were capable of amplifying genes from Archaea, Chlorobium, Rhodobacter and these others, no corresponding sequences were detected. Cyanobacterial nifH gene sequences were recovered from sediments and would presumably be abundant in diazotrophic algal mats. Biodiversity estimates based on nifH sequence libraries indicated that there were similar diazotroph guilds across stream type, maintained by substantial gene flow between communities. However, there are significant differences between the diazotroph guilds among stream types when taxa are examined. There are likely to be other microbial contributors to N2 fixation in stream sediments, which could be uncovered with more robust sequencing campaigns.

Supplementary Material

Figure S1. Complete dendrogram showing the taxonomic relationships between nifH genes amplified from small prairie streams and contextual nifH gene sequences from GenBank.

Acknowledgments

The authors appreciate the support of members of the broader project, Walter Dodds, David Graham, Charles Knapp, and their teams. We thank Sarah Castro, Daniel Gutzmer, Brooke Landon, Brandon Litzner, Christopher Rogers, Monica Rueda, Leland Russell, Lisa Witte, and Eyyub Yunus for technical support. Preliminary reports of this work have been presented previously and abstracted (Caton et al. 2004a; Santos-Caton and Schneegurt 2006; Caton and Schneegurt 2007, 2012). An award from Kansas National Science Foundation (NSF) Experimental Program to Stimulate Collaborative Research (EPSCoR) in Ecological Genomics (EPS 0236913) supported this work. Additional student support was from Kansas Institutional Development Award (IDeA) Networks of Biomedical Research Excellence (KINBRE) of the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH) (P20 GM103418) and NSF Graduate STEM Students in K-12 Education (GK-12; DGE 0537844). The content is solely the responsibility of the authors and does not necessarily represent the official views of KINBRE, KS NSF EPSCoR, NIGMS, NIH, or NSF.

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Supplementary Materials

Figure S1. Complete dendrogram showing the taxonomic relationships between nifH genes amplified from small prairie streams and contextual nifH gene sequences from GenBank.

NIHMS934871-supplement-Figure_S1.pdf (634.9KB, pdf)

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