Keywords: copepods, nitrogen cycle, oxygen,¹⁵N-stable-isotope labeling, functional gene analysis, molecular community fingerprinting

Study site and organisms

Lake Dagow (53°09'01'N, 13°03'60'E) and Lake Stechlin (53°09'03'N, 13°01'40'E) are located in NE Germany and are connected via a small outflow. Lake Dagow is a shallow (9 m), eutrophic lake that experiences seasonal hypoxia, with the bottom water falling anoxic below a depth of 6 m every year. Lake Stechlin is a deep (69.5 m), oligotrophic lake with no anoxia or hypoxia even at 50 m depth. Three different species of zooplankton that were abundant in any of these two lakes at the time of this study (September 2015) were investigated in laboratory experiments: The small (prosome length 0.5–0.8 mm), omnivorous copepodsEudiaptomus gracilis andE. graciloides from Lake Dagow (Brandl2005; Šorf and Brandl2012) and the large (prosome length 2.5–3.0 mm), carnivorous copepodMegacyclops gigas from Lake Stechlin (Brandl2005).

Sample collection

Eudiaptomus sp. were collected in Lake Dagow just below the water surface by horizontal net tows with a plankton net of 250 µm mesh size and 0.5 m mouth size and carefully transferred to 1-L glass bottles. The net was rinsed between each tow to remove zooplankton carcasses. Surface lake water was collected in 5-L canisters and filtered through 5-µm polycarbonate membranes.Megacyclops gigas was collected in Lake Stechlin at 10–15 m water depth by deploying sediment traps and leaving them in the water for 3 days. LivingM. gigas were abundant in the traps, presumably taking advantage of accumulated food.Megacyclopsgigas was kept in darkness at 20°C in 90-µm filtered, oxygenated surface water from Lake Stechlin. For feeding, mixed zooplankton from Lake Stechlin was added to the storage tank containingM. gigas.

Preparation of copepod carcasses

When returning to the laboratory,Eudiaptomus gracilis andE. graciloides were isolated from the Lake Dagow zooplankton samples, carefully excluding the bottom layer in the collection bottle to avoid transferring already dead specimens. The pooledEudiaptomus sp. were then exposed to 10% acetic acid for a few seconds followed by several immersions in sterile-filtered Lake Dagow water to get rid of residual acid. TheEudiaptomus sp. carcasses were then transferred to beakers with Lake Dagow water collected on the same day. The beakers were put on a shaker table set at slow speed and left in darkness at 20°C overnight, to allow for colonization by the free-living microbial community in the lake water.Megacyclops gigas specimens were killed and preincubated on the day before the incubation experiments by the same procedure.

Experimental schedule

Short-term¹⁵NO₃⁻-incubation experiments were performed with and without copepod carcasses as summarized in Table1. ForEudiaptomus sp., four incubation experiments with three replicates each were designated E1_low, E1_high, E2_low and E2_high in accordance with the different targeted ambient O₂ levels. ForM. gigas, four incubation experiments with five replicates each were designated M1a_low, M1b_low, M2_low, and M2_high. Note that for incubation experiment M1a_low, the copepods were killed just prior to the short-term incubation experiments, whereas for all remaining experiments, the prepared carcasses were preincubated overnight (see previous section). For controls without copepod carcasses, three incubation experiments with five replicates each were designated Ctr_low, Ctr_intermediate, and Ctr_high, in accordance with the different targeted ambient O₂ levels of 0%, 20% and 100% air saturation.

Experimental procedure

Oxygen dynamics and anaerobic N-cycling were studied in short-term incubation experiments. Prior to the incubations, 100Eudiaptomus sp. or 40M. gigas carcasses each were transferred to replicate 30-mL glass bottles. Despite this larger number ofEudiaptomus sp. carcasses, the total biomass was still ca. six times higher inM. gigas incubations. The bottles were equipped with oxygen-sensitive optode patches (SensorSpot, PyroScience, Aachen, Germany) fixed to the inner side of the bottle wall and interrogated from the outside by a FireSting O₂ meter (PyroScience, Aachen, Germany). For reasons of conformity regarding water chemistry and free-living bacterial community, allEudiaptomus sp.,M. gigas, and control incubation experiments were made with 5-µm-filtered Lake Dagow water. The lake water was amended with¹⁵NO₃⁻ (98 atom%¹⁵N, Sigma-Aldrich, U.S.A.) to a final concentration of 5 µM. The background concentration of NO₃⁻ in Lake Dagow water was 1.3 µM. The ambient O₂ level was adjusted by flushing the lake water with O₂ and He using a thermal mass flow controller (Brooks Instrument, Hatfield, USA). The bottles were closed and sealed with gas-tight rubber stoppers without entrapping gas bubbles and then incubated on a plankton wheel in darkness at 20°C. After 0, 1.5, 3, 4.5 and 6 h, the O₂ concentration was measured and a water sample (3 mL) was taken from each bottle through the rubber stopper. At each sampling time point, the water withdrawn from the bottle was replaced with¹⁵NO₃⁻-enriched lake water that had been adjusted to an O₂ concentration that roughly would compensate for the drop in O₂ concentration since the last sampling time point (Stiefet al.2016). The 3-mL water sample was split into two samples: (i) 1.5 mL was transferred to a 3-mL He-flushed, half-evacuated exetainer (Labco, Wycombe, UK) containing 50 µL ZnCl₂ (50% w/v) that was stored at room temperature for later¹⁵N-analyses and (ii) 1.5 mL was transferred to a 2-mL sample tube that was stored at –20°C for later DIN analysis.

Nitrogen analyses

Samples for DIN analysis (NO₃⁻, NO₂⁻ and NH₄⁺) were filtered through 0.22-µm membranes prior to analysis. Nitrate plus nitrite concentrations were measured on an NO_x analyzer (42 C, Thermo Fisher Scientific) with the VCl₃ reduction assay (Braman and Hendrix1989). Nitrite was quantified via the Griess reaction using a spectrophotometer (Multiskan GO Microplate Spectrophotometer, Thermo Fisher Scientific) after Garcia-Robledo, Corzo and Papaspyrou (2014). Ammonium was analyzed after Holmeset al. (1999) on a Turner Trilogy Fluorometer (Model 7200-041, Turner Design). The isotopically labeled nitrogen species¹⁵N-N₂ (²⁹N₂ +³⁰N₂),¹⁵NO₂⁻, and¹⁵NH₄⁺ were analyzed on a gas chromatography-isotopic ratio mass spectrometer (GC-IRMS; Thermo Delta V Plus, Thermo Fisher Scientific) (Dalsgaardet al.2012). A subset of the samples was analyzed for N₂O on a gas chromatograph (GC 7890, Agilent Technologies). The samples for¹⁵N₂ and N₂O analysis were withdrawn from the headspace of the 3-mL exetainers, after which¹⁵N-labeled NO₂⁻ and NH₄⁺ were analyzed with the sulfamic acid and the hypobromite assay, respectively (Warembourg1993; McIlvin and Altabet2005). The efficiency of these chemical conversion steps was verified with¹⁵NO₂⁻ and¹⁵NH₄⁺ calibration standards ranging between 0 and 5 µM in concentration.

Rate calculations and statistics

Oxygen consumption and N-turnover rates were calculated from linear regressions of the concentration time series, accounting for any dilution during the sampling process. Production rates of total NH₄⁺ from DNRA, total NO₂⁻ from DNRN and total N₂ from denitrification were calculated from production rates of¹⁵NH₄⁺,¹⁵NO₂⁻ and¹⁵N₂, respectively, and the initial¹⁵NO₃⁻-labeling fraction in the lake water (i.e. 0.79) to account for the¹⁴NO₃⁻ present in the water. Since the N-turnover rates measured in carcass incubations included any activity from the free-living microbial community in the 5-µm-filtered lake water, the N-turnover rates measured in the respective control incubations without carcasses were subtracted to approximate the carcass-associated N-turnover rates. In incubations in which unintended anoxic events occurred (i.e. M1b_low and M2_low), the N-turnover rates were additionally calculated for the hypoxic and anoxic phase separately.

The slope of the regression lines and the mean slopes were analyzed with t-tests to identify rates that were significantly different from zero. The effect of the ambient O₂ level on the turnover rates of O₂, NO₃⁻, NO₂⁻, NH₄⁺, and process rates of DNRN, DNRA, and denitrification inEudiaptomus sp. orM. gigas incubations was tested with ANOVA (one-way), followed by the Tukey post-hoc test. The effect of overnight preincubation on N-turnover rates was analyzed with t-tests. The effect of (i) ambient O₂ level and day of copepod collection inEudiaptomus sp. orM. gigas carcass incubations and of (ii) ambient O₂ level and copepod taxon in the whole sample set was tested with ANOVA (two-way, two-factorial, without interaction), followed by the Tukey post-hoc test on the same variables as above. ANOVA and post-hoc tests were performed in R (R core team, Version 3.2.4).

Bacterial community fingerprinting

To separate the carcasses from the water after the incubations were completed, the content of each incubation bottle was filtered onto 5.0-µm Nuclepore polycarbonate membranes. Membranes were immediately frozen in liquid nitrogen and stored at –80°C until further processing. Biomass from Lake Dagow and Lake Stechlin water was sampled on the day of copepod collection by filtration through 0.22-µm Nuclepore polycarbonate membranes, which were stored like the carcass samples.

DNA from carcasses was extracted with a protocol modified from Nercessianet al. (2005) using chloroform-phenol-isoamyl and zirconium beads with the addition of potassium phosphate buffer. For DNA extractions from water samples, the PowerWater DNA Isolation kit (MO BIO, Carlsbad, USA) was used following the manufacturer's protocol. DNA was quantified with a fluorometer using the Quant-iT Picogreen kit (Invitrogen, Carlsbad, USA), providing average yields of 6.9, 84.5 and 122.2 ng µL⁻¹ from 100Eudiaptomus sp. carcasses, 40M. gigas carcasses, and ∼750 mL lake water, respectively.

For terminal restriction fragment length polymorphism (T-RFLP) analysis (Avaniss-Aghajaniet al.1994; Liuet al.1997) of the bacterial community, the 16S rRNA genes were amplified by PCR using the phosphoramidite fluorochrome 5-carboxy-fluorescein labeled, Bacteria-specific forward primer B27FAM (50-AGRGTTYGATYMTGGCTCAG-30) and the reverse primer U519R (50-GWATTACCGCGGCKGCTG-30). PCR was performed in 50-µL reactions with final amounts of 5–10 ng template, 20 pmol of each primer, 10 nmol dNTPs in equal amounts, 5 µL 10x Taq-buffer with (NH₄)₂SO₄, 1.25 units Taq-polymerase and 125 nmol MgCl₂ (all: Thermo Fisher Scientific). Denaturation at 94°C for 2 min was followed by 32 cycles of 94°C for 20 s, 54°C for 45 s, and 72°C for 45 s, with a final elongation step at 72°C for 5 min. Successful amplification was verified by agarose gel (1.5%) electrophoresis. The ∼500 base pair (bp) PCR product was incubated with 5 U ofBsuRI in buffer R (Thermo Fisher Scientific) at 37°C for 12 hr followed by heat inactivation at 80°C for 20 min. The resulting restriction fragments were purified with the GeneJET PCR purification kit (Thermo Fisher Scientific) and ∼100 ng were sent for fragment length analysis to Uppsala Genome Center (Sweden).

For the analysis of the T-RFLP data, initial fragment sizing was carried out with the software Peak Scanner (Applied Biosystems, Foster City, USA). Noise filtration (factor 1.2 based on peak area), clustering (factor 0.5) and construction of data matrices were performed with the online program T-RFLP analysis EXpedited (http://trex.biohpc.org/). The operational taxonomic unit (OTU) fluorescence was standardized to the total fluorescence of all OTUs in a sample, and matrices of different sample combinations of interest were created including only OTUs present in more than one sample and with a relative abundance of >0.5%. Data matrices were analyzed with R (R core team, version 3.2.4) and the R-package vegan (Oksanenet al.2013), where the dissimilarities between samples and their respective OTUs were calculated and visualized with non-metric multidimensional scaling (NMDS). The function metaMDS was used to find the best fit between Bray–Curtis dissimilarities and ordinations with minimal stress (goodness of fit). The data values were submitted to Wisconsin double standardization. The function found species scores as weighted averages of site scores, but expanded them so that species and site scores had equal variances (Oksanenet al.2013). All NMDS settled for two dimensions and low stress ranging from 0.086 to 0.112.

Bacterial functional marker gene abundances

The bacterial and archaeal 16S rRNA genes as well as the functional marker genesnirS (denitrification) andnrfA (DNRA) were quantified by quantitative PCR (qPCR) in duplicate 25-µL reactions with 5–10 ng template, 25 pmol of each of the respective primers (Table S1, Supporting Information), RealQ Plus 2 × Master Mix (Ampliqon) and 10 µg bovine serum albumin (BSA; final conc. 4 µg µL⁻¹) using a CFX Connect Real-time System (BIO-RAD). Amplification was started with a denaturing step at 95°C for 15 min followed by 40 (16S,nirS) or 32 (nrfA) cycles of denaturing at 95°C for 20 s, annealing for 30 s at primer-specific temperatures (Table S1, Supporting Information) and extension at 72°C for 30 s (16S,nirS) or 45 s (nrfA). The products were analyzed by melting curves from 65°C to 95°C in steps of 0.5°C with 5 s at each step. Standard curves were made from serial 10-fold dilutions of the target genes (10¹–10⁷ copies per µL).

Diversity ofnrfA in copepod carcasses

To assess the diversity ofnrfA, the gene was amplified from copepod carcass samples (M. gigas) by PCR with the corresponding primers (Table S1, Supporting Information). The PCR-product was cloned into the plasmid vector (pCR 4-TOPO) using the TOPO TA Cloning Kit for sequencing (Invitrogen) and One Shot TOP10 Chemical competentE. coli cells were transformed with the ligated plasmids following the manufacturer's instructions. The inserts from 60 clones were amplified by colony PCR using M13 primers and the PCR products were sent for sequence analysis to the Institute of Clinical Molecular Biology (IKMB), Kiel University. Fifty-four clones returned high-quality sequences from which the vector sequences were trimmed off. The resulting, around 237 bp long DNA sequences were translated and phylogenetically analyzed using theNrfA alignment from Welshet al. (2014) in the software package ARB (Ludwiget al.2004). The sequences have been deposited at Genbank under the accession numbersMG806931-MG806984.

Preparation ofnrfA standard for qPCR

In order to be used as standards in the qPCR, twonrfA clones were chosen, grown in LB medium (Miller) with 50 µg mL⁻¹ kanamycin overnight at 37°C and the plasmids extracted with the GeneJet Plasmid Miniprep kit (Thermo Fisher Scientific). ThenrfA gene fragment was amplified with PCR as described above and the DNA concentration of the PCR product was quantified with a Quant-iT Picogreen dsDNA Assay Kit (Molecular Probes by Life Technologies) using a Victor2 1420 Multilabel Counter (Wallac). With this information, the gene copy number was calculated and dilution series of 10¹ to 10⁷ copies were prepared.

Oxygen dynamics

In most experiments, ambient O₂ levels remained relatively stable throughout the incubation (Fig. S1, Supporting Information), in particular during theEudiaptomus sp. carcass incubations and the control incubations without any carcasses (Fig. S1A and C, Supporting Information). During some of the incubations with the much largerM. gigas carcasses, however, strong O₂ consumption caused pronounced drops in the ambient O₂ level (Fig. S1B, Supporting Information). In M1b_low and M2_low, this led to the occurrence of anoxic events in the majority of the replicates, already after 3 h of incubation. In M2_low, the re-injection of oxygenated water during water sampling made the ambient O₂ level fluctuate between 0% and ∼10% air saturation. To account for these anoxic events, carcass-associated anaerobic N-cycling was not only evaluated for the total incubation period, but also separately for the hypoxic and anoxic phases that occurred in M1b_low and M2_low (see below).

Carcass degradation

The carcass-associated O₂ consumption and NH₄⁺ production was used to assess the rate of microbial degradation of the carcass biomass. Oxygen concentration time series were re-constructed from the concentration decreases measured between consecutive sampling time points, while NH₄⁺ concentration time series were measured directly (Fig.1A and B). Across all experiments, the O₂ consumption and NH₄⁺ production rates calculated from the concentration time series were significantly, linearly correlated (R² = 0.894,P < 0.001) (Fig.1C). Assuming a respiratory quotient of 1.0 during carcass degradation, the O₂ consumption rates are numerically equivalent with CO₂ production rates. The slope of the regression line in Fig.1C then corresponds to an average C/N ratio of 6.0 between the CO₂ and NH₄⁺ produced during carcass degradation. This C/N ratio was mainly carried by the higher O₂ consumption and NH₄⁺ production rates during incubation of the largeM. gigas carcasses compared to the much smallerEudiaptomus sp. carcasses (Fig.1C; Table S2, Supporting Information). It needs to be noted that for the two incubation series in which anoxic events occurred (i.e. M1b_low and M2_low), the re-constructed O₂ concentration time series underestimate the actual rate of CO₂ production that may partially be due to anaerobic respiration processes, such as dissimilatory NO₃⁻ reduction or SO₄²⁻ reduction.

Within each copepod taxon and O₂ treatment, sample history had a strong effect on carcass degradation, i.e. the E2- and M2-incubation series showed several times higher rates than the corresponding E1- and M1-incubation series. Furthermore, carcass degradation was stimulated by the high ambient O₂ levels in E1_high and E2_high (but not in M2_high) and by the overnight preincubation in M1b_low (Table S2, Supporting Information).

Nitrogen cycling

Consistent temporal changes in NO₃⁻ concentration indicative of net NO₃⁻ production or consumption were rare (Fig.2A and B). A pronounced decrease in NO₃⁻ concentration was only observed in the low-oxygen experiment M2_low (Fig.2B). Notably, this decrease in NO₃⁻ concentration only started when the first anoxic event occurred. The strongest increases in NO₂⁻ and NH₄⁺ concentration due to DNRN and DNRA activity, respectively, were likewise observed in the low-oxygen experiments E2_low, M1b_low and M2_low (Fig.2C–F). The onset of anoxic events in M1b_low and M2_low further accelerated the increase in NO₂⁻ and NH₄⁺ concentration. In contrast, rather weak increases in N₂ concentration due to denitrification activity were observed in all experiments, and anoxic events did not trigger stronger increases in N₂ concentration (Fig.2G and H). Consistent temporal changes in N₂O concentration were not observed in any of the experiments (data not shown).

General trends for the rates of carcass-associated anaerobic N-cycling were that (i) DNRA and DNRN showed higher rates than denitrification, (ii) the largerM. gigas carcasses hosted higher carcass-specific rates than the smallerEudiaptomus sp. carcasses, and (iii) anaerobic N-cycling was more intense at low ambient O₂ levels (Fig.3; Tables S2–S4, Supporting Information). Additionally, the only significant correlation between rates of the three anaerobic N-cycle pathways was observed between DNRA and DNRN (R² = 0.514,P < 0.0001, n = 30). Rates of DNRA, DNRN and denitrification were significantly different from zero in most, but not all of the low-oxygen experiments (Table S2, Supporting Information). In contrast, rates of these anaerobic N-pathways were not significantly different from zero in the high-oxygen experiments, except the significant DNRN rate in M2_high. Consequently, the ambient O₂ level had in most cases a statistically significant effect on the rates of carcass-associated anaerobic N-pathways (Table S4, Supporting Information). This regulatory role of the ambient O₂ level was further substantiated in the two low-oxygen experiments M1b_low and M2_low in which anoxic events occurred repeatedly. The rates of DNRA (in M2_low) and DNRN (in M1b_low and M2_low), but not denitrification, increased significantly following the onset of anoxic events (Student's t-test:P < 0.05).

The rates of carcass-associated anaerobic N-pathways were also influenced by sample history and sample treatment. The day of copepod collection in the lake had a significant effect on DNRA and DNRN rates in each of the twoEudiaptomus sp. incubation series and on DNRA, DNRN and denitrification rates in each of the twoM. gigas incubation series (Table S4, Supporting Information). Additionally, the overnight preincubation of carcasses in M1b_low increased the rates of NO₃⁻ consumption and DNRN, but not DNRA and denitrification, significantly (Student's t-test:P < 0.05).

Bacterial community composition

UsingBsuRI, 134 OTUs were detected in the complete sample set. Table S5 (Supporting Information) shows how many OTUs were associated with copepods in each of the different incubation experiments and how many were present in thein situ water of the two lakes. When subjected to non-metric two-dimensional scaling, the carcass-associated bacterial communities ofEudiaptomus sp. andM. gigas clustered separately, as did the free-living communities from Lake Dagow and Lake Stechlin (Fig.4A), indicating that both copepod taxon and lake type drove composition of the total bacterial communities. The carcass-associated communities further clustered into four groups according to day of copepod collection, but not into high- and low-oxygen incubations (Fig.4B), indicating that sample history was more important for shaping the total bacterial communities than the short-term exposure to different O₂ levels. M1a_low and M1b_low communities were dissimilar (despite the same day of copepod collection), indicating that the carcass-associated bacterial community changed during the overnight preincubation (Fig.4B).

Bacterial gene abundance

The abundance of carcass-associated bacterial 16S rRNA genes varied between 3.8 × 10⁶ and 1.6 × 10⁸ per carcass (Fig.5A). Across all experiments, 16S rDNA abundance was significantly correlated with the carcass-specific O₂ consumption rate (Spearman: R² = 0.627,P < 0.001). The relative abundance of carcass-associatednrfA genes varied between 9.9 × 10⁻³ and 4.2 × 10⁻¹ per 16S rDNA copy and was 90 ± 20 times higher than in lake water (Mean ± SE, n = 29) (Fig.5B). The relativenrfA abundance was significantly, linearly correlated with the carcass-specific DNRA rate (R² = 0.168,P = 0.034) and O₂ consumption rate (R² = 0.769,P < 0.001). The relative abundance of carcass-associatednirS genes varied between 5.4 × 10⁻⁴ and 8.1 × 10⁻³ per 16S rDNA copy and was 178 ± 35 times higher than in lake water (Fig.5C). The relativenirS abundance was negatively correlated with the carcass-specific denitrification rate (R² = 0.355,P = 0.001) and O₂ consumption rate (R² = 0.389,P < 0.001). Across all copepod taxa, the relativenrfA abundance was ∼20–400 times higher than the relativenirS abundance. Archaea were, based on the quantification of their 16S rRNA gene, not present or extremely low in abundance in both lake water and on carcasses.

NrfA diversity

The 54NrfA sequences retrieved clustered into 15 unique sequences, and phylogenetic analysis revealed their high similarity to sequences belonging toNrfA of clade A that has been defined by Welshet al. (2014) (Fig. S2, Supporting Information). More specifically, they all fell into a sub-cluster of sequences originating from theAeromonas speciesA. veronii,A. salmonicida subsp.salmonicida, andA. caviae, which show a relatively small phylogenetic distance to the other sequences of cluster A (Fig. S2, Supporting Information).

Pathways of carcass-associated anaerobic N-cycling

The dominant anaerobic N-cycle pathways associated with carcasses of bothEudiaptomus sp. andMegacyclops gigas were DNRA and the tightly correlated DNRN. In contrast, only very low rates of denitrification were measured and exclusively on the largerM. gigas carcasses. Anammox was ruled out as an important carcass-associated anaerobic N-cycle pathway because³⁰N₂ rather than²⁹N₂ was the main isotopic form of N₂ produced. Generally, only 1%–4% of the total dissolved¹⁵N-labeled compounds produced from the added¹⁵NO₃⁻ were in the form of N₂, which would contribute to pelagic fixed-nitrogen loss. The majority of¹⁵N-labeled compounds, however, were released as NH₄⁺ and NO₂⁻ into the surrounding water where they can be used by free-living bacteria and microalgae for N-assimilation and nitrification. Consequently, our study on copepod carcassess revealed a rather low potential for a direct contribution to fixed-nitrogen loss at the ecosystem level.

Gludet al. (2015) studied denitrification in carcasses of the large marine copepodCalanus finmarchicus (prosome length ∼2.6 mm) and measured carcass-specific N₂ production rates under anoxic conditions that were two orders of magnitude higher than the rates measured in the present study. Likewise, significantly higher denitrification rates were measured in relatively small copepod carcasses (prosome length ≤0.5 mm) from a tropical oxygen minimum zone (Stiefet al.2017). The unexpectedly high denitrification rates in the latter study might be explained by the use of¹⁵NO₂⁻ instead of¹⁵NO₃⁻, if DNRN was rate-limiting for carcass-associated denitrification. It might, however, also be a specific trait of the three studied lake copepod species that carcass-specific denitrification rates were lower than in all tested marine copepod species. For tropical marine copepods and ostracods, DNRA was also identified as an important carcass-associated N-pathway with rates ∼10–25 times higher than denitrification rates under anoxic conditions (Stiefet al.2017).

Significant DNRN activities have also been reported for sinking algae aggregates and were explained by the lack of any NO₃⁻ limitation in the pelagic zone and inside the aggregates (Stiefet al.2016; Lundgaardet al.2017). Similarly, NO₂⁻ production was observed in activated sludge in which NO₃⁻ diffused to the very center of the individual sludge flocs (Schrammet al.1999). In contrast, diffusional NO₃⁻ limitation in sediments favors N₂ and NH₄⁺ over NO₂⁻ production (Stiefet al.2010; Devol2015). The carcasses from this study are not expected to have experienced such diffusional NO₃⁻ limitation because of their relatively small size and low NO₃⁻ consumption rates. The carcass-associated DNRN rates were significantly correlated with the DNRA rates, but not with the denitrification rates. Additionally, both DNRN and DNRA, but not denitrification, were boosted by the onset of anoxic conditions during incubation. Given these similarities, it might be speculated that the two pathways were mediated by the same microorganisms (i.e. DNRA bacteria) carrying out the sequential DNRA pathway either completely or partially. However, it cannot be excluded that true DNRN bacteria that do not possess the enzymes for NO₂⁻ reduction to NH₄⁺ or N₂ were responding to the change in ambient O₂ levels in the same way and at similar rates as DNRA bacteria.

DNRA activities associated with the carcasses of the lake copepods studied here were in a similar range as reported for small marine copepods (Stiefet al.2017). The high relative importance of this N-cycle pathway on both freshwater and marine copepods is likely explained by the unique microenvironments and substrates that sinking zooplankton carcasses provide to DNRA bacteria. Anoxia and the copious supply of electron donors inside the gut of living copepods (Tanget al.2011) may favor the growth and persistence of enteric bacteria many of which are capable of DNRA (Cole1996; Tiso and Schechter2015). Additionally, the exoskeleton of copepods is commonly colonized byVibrio spp. that degrade chitinous compounds (Montanariet al.1999; Tang, Turk and Grossart2010; Shoemaker and Moisander2015), and manyVibrio spp. and related bacterial genera possess the genes necessary for DNRA (Bonin1996; Rusch and Gaidos2013; Kraftet al.2014).

The dominance of DNRA relative to denitrification was supported by the higher relative abundance of the functional marker genenrfA thannirS. For the smallerEudiaptomus sp. carcasses,nrfA was on average 18-fold more abundant thannirS, while the rates of DNRA were 8-fold higher than that of denitrification. For the largerM. gigas carcasses, however,nrfA was on average 462-fold more abundant thannirS, while the rates of DNRA were 40-fold higher than that of denitrification. The discrepancies between gene abundance and rates and between different zooplankton taxa hint to differences at the level of gene transcription and/or differences in the regulation of enzyme activities by microenvironmental conditions or substrate supply related to zooplankton taxon. The phylogenetic analysis of thenrfA sequences indicated a high specificity of the used primer set as onlynrfA sequences were retrieved. On the nucleotide level, the most different clones were still 94.5% identical, indicating that either a fairly low diverse community ofnrfA-containing bacteria was present or that the primers did not amplify allnrfA genes. This suggests that thenrfA abundances determined by qPCR are rather under- than overestimates. Interestingly, thenrfA sequences were closely related toAeromonas species that have previously been found onAcartia tonsa (Tanget al.2009a) and notVibrio spp. that are reported for diverse copepod species (Montanariet al.1999; Tang, Turk and Grossart2010; Shoemaker and Moisander2015). However, the single sample from which thenrfA PCR amplicon was verified might not be representative for all samples and it can be expected that in a more comprehensive study a larger diversity ofnrfA associated with copepods in lakes would be revealed.

Oxygen controls on carcass-associated nitrogen cycling

Anaerobic N-cycling associated with the carcasses ofEudiaptomus sp. andM. gigas was evident even at high ambient O₂ levels, but then the rates were very low compared to the copepod carcasses and algae aggregates investigated in other studies (Gludet al.2015; Klawonnet al.2015; Stiefet al.2016; Stiefet al.2017). Hypoxic and anoxic incubation conditions stimulated carcass-associated anaerobic N-cycling strongly. Therefore, we assume that the extent of internal O₂ depletion in the studied copepod carcasses was insufficient to allow substantial anaerobic N-cycling at high ambient O₂ levels. This could be due to lack of O₂ diffusion limitation in the relatively small carcasses and/or the low volume-specific O₂ consumption rates during microbial carcass degradation (Schrammet al.1999; Stief and Eller2006). The internal O₂ levels of the carcasses studied here are not known, butin situ O₂ measurements in carcasses of the marine copepodCalanus finmarchicus revealed internal anoxia (Gludet al.2015). Even in this relatively large species though, the rates of anaerobic N-cycling (as denitrification) increased strongly with decreasing ambient O₂ level, suggesting a successive expansion of the anoxic center.

The immediate control of anaerobic N-cycling by the ambient O₂ level was observable in carcass incubations during which several anoxic events occurred unintendedly. The carcass-associated microbial communities responded quickly to the onset of anoxic conditions by up-regulating the anaerobic N-cycle pathways DNRA and DNRN, but not denitrification. The latter observation might be due to a low potential for denitrification in the microbial communities colonizing the carcasses, which is consistent with the ∼20–400 times lower relative abundance of thenirS gene compared to thenrfA gene.

Effects of carcass preincubation

Generally, the microbial degradation of zooplankton carcasses is to a large extent driven by bacteria and fungi from the surrounding water that colonize the carcasses within the first day after death (Tang, Hutalle and Grossart2006; Tanget al.2009b; Bickel and Tang2010). Thus, much of the bacterial colonization of the copepod carcasses studied here may have occurred during the overnight preincubation. In fact, the carcass-specific bacterial 16S rRNA gene abundance was on average 1.8-fold higher on preincubated than on non-preincubatedM. gigas carcasses, but statistical significance was narrowly missed (P = 0.053). In contrast, the rates of O₂ and NO₃⁻ consumption, NH₄⁺ production, DNRN, and denitrification were all significantly enhanced by the overnight preincubation ofM. gigas carcasses. An exception to this was the DNRA rate that did not increase during the overnight preincubation, even though the absolutenrfA abundance increased on average as much as 4.5-fold (P = 0.011). This apparent discrepancy is solved by realizing that DNRA was the only anaerobic N-cycle pathway that showed a high rate also in the non-preincubatedM. gigas carcasses. Thus, in particular for DNRA, the bacterial populations and suitable microenvironmental conditions were already established on the living copepods.

Microbial community composition

As distinctive microsites in the pelagic zone, copepods and their carcasses host microbial communities that are dissimilar to free-living microbial communities, which was also true for the lake copepods studied here (Tanget al.2009a; Dziallaset al.2013; Bickel, Tang and Grossart2014; Shoemaker and Moisander2015; Moisander, Sexton and Daley2015). The differences in microbial community composition betweenEudiaptomus sp. andM. gigas carcasses were likely explained by those bacterial groups that were already associated with the live copepods, e.g. due to different feeding strategies of the two species (Brandl2005; Tanget al.2009a). The varying amounts and composition of the food remains in the gut may explain why the same copepod species hosted dissimilar microbial communities (Tanget al.2009a) between different copepod collection days. The overnight preincubation led to a further shift in microbial community composition (and an increase in bacterial abundance; see above), whereas the short-term incubation at different ambient O₂ levels did neither cause shifts in microbial community composition, nor changes in bacterial abundance.

Ecological implications

Microbial carcass degradation and carcass-associated anaerobic N-cycling release DIN into the surrounding water where it can be processed by other microorganisms and thereby influence pelagic N-cycling. For the lake copepods studied here, the main products of carcass-associated anaerobic N-cycling were NH₄⁺ and NO₂⁻, while N₂ only played a minor role. Additionally, it cannot be ruled out that the carcasses of the lake copepods studied here hosted nitrification activity (i.e. promoting NO₂⁻ and NO₃⁻ release into the surrounding water) as shown for the large Arctic marine copepodCalanus hyperboreus (Stiefet al.2018). Ammonium is released through carcass degradation and carcass-associated DNRA. However, DNRA made up only ∼2.5% of the NH₄⁺ production by carcass degradation. Under the hypoxic or anoxic conditions in the hypolimnion of lakes, this fraction would increase to ∼10%–30%. This raises the question where in a stratified lake the copepod-derived NH₄⁺ would make a difference. During periods of stratification, vertical NH₄⁺ concentration profiles typically exhibit very low concentrations in the epilimnion and high concentrations in the hypolimnion (Sand-Jensen and Lindegaard2004; Schubertet al.2006; Hamersleyet al.2009). Thus, copepod-derived NH₄⁺ is more likely to fuel epilimnetic primary production and nitrification activity (Priddleet al.1997; Lehetteet al.2012) than hypolimnetic anammox activity (Schubertet al.2006; Hamersleyet al.2009).

Nitrite release through carcass-associated DNRN was of similar quantitative importance and showed the same response to low-oxygen conditions as carcass-associated DNRA. Vertical NO₂⁻ profiles in lakes rarely exhibit concentrations >0.3 µM throughout the water column (Sand-Jensen and Lindegaard2004; Schubertet al.2006; Hamersleyet al.2009) and thus copepod-derived NO₂⁻ may relieve NO₂⁻ limitation of the second step of nitrification in the oxic epilimnion and denitrification and anammox activity in the anoxic hypolimnion of lakes. A rough quantitative estimate on the latter effect can be based on the copepod abundance in Lake Dagow of 1.8 individuals L⁻¹ of which 8% are dead (Bickel, Tang and Grossart2009), the DNRN rate ofM. gigas carcasses of 1140 pmol carcass⁻¹ h⁻¹ measured under anoxic conditions, and the hypolimnetic anammox rates reported for two lakes (i.e. 0.6–21 nM N₂ h⁻¹ in a temperate lake (Hamersleyet al.2009) and ∼10 nM N₂ h⁻¹ in a tropical lake (Schubertet al.2006)). For these two scenarios, copepod-carcass-derived NO₂⁻ would make up 0.4%–13.9% and 0.8% of the hypolimnetic anammox rate, respectively, which constitutes an indirect contribution to overall fixed-nitrogen loss by sinking copepod carcasses. In an anoxic hypolimnion, denitrification rates can be ∼20 times higher than anammox rates (Wenket al.2014) and thus the relative copepod contribution to hypolimnetic denitrification would even be lower than to anammox.

Such extrapolations might still overestimate the true copepod contribution to pelagic N-cycling because of the seasonally restricted occurrence of hypolimnetic anoxia and the small volume of the hypolimnion relative to the total lake volume. Additionally, in many lakes, benthic fixed-nitrogen loss is more important than pelagic fixed-nitrogen loss (e.g. Wenket al.2014) and thus the possible contribution by sinking copepod carcasses to fixed-nitrogen loss is probably small for the overall N-budget of lakes. However, the extrapolation might also underestimate the copepod contribution because much higher relative carcass abundances of up to 40% have been observed in other lakes (Bickel, Tang and Grossart2009; Elliott and Tang2009; Tanget al.2014). Finally, also the carcasses of other abundant lake zooplankton, such as cladocerans (Bickel, Tang and Grossart2009), might contribute to lacustrine fixed-nitrogen loss.

1. Avaniss-Aghajani E, Jones K, Chapman D et al. A molecular technique for identification of bacteria using small-subunit ribosomal RNA sequences. BioTechniques. 1994;17:144–6. [PubMed] [Google Scholar]
2. Bickel SL, Tang KW, Grossart HP. Use of aniline blue to distinguish live and dead crustacean zooplankton composition in freshwaters. Freshw Biol. 2009;54:971–81. [Google Scholar]
3. Bickel SL, Tang KW. Microbial decomposition of proteins and lipids in copepod versus rotifer carcasses. Mar Biol. 2010;157:1613–24. [Google Scholar]
4. Bickel SL, Tang KW, Grossart HP. Structure and function of zooplankton-associated bacterial communities in a temperate estuary change more with time than with zooplankton species. Aquat Microb Ecol. 2014;72:1–15. [Google Scholar]
5. Bonin P.Anaerobic nitrate reduction to ammonium in two strains isolated from coastal marine sediment: a dissimilatory pathway. FEMS Microbiol Ecol. 1996;19:27–38. [Google Scholar]
6. Braman RS, Hendrix SA. Nanogram nitrite and nitrate determination in environmental and biological materials by vanadium(III) reduction with chemiluminescence detection. Anal Chem. 1989;61:2715–8. [DOI] [PubMed] [Google Scholar]
7. Brandl Z.Freshwater copepods and rotifers: predators and their prey. Hydrobiologia. 2005;546:475–89. [Google Scholar]
8. Cole J.Nitrate reduction to ammonia by enteric bacteria: Redundancy, or a strategy for survival during oxygen starvation?. FEMS Microbiol Letts. 1996;136:1–11. [DOI] [PubMed] [Google Scholar]
9. Dalsgaard T, Thamdrup B, Farias L et al. Anammox and denitrification in the oxygen minimum zone of the eastern South Pacific. Limnol Oceanogr. 2012;57:1331–46. [Google Scholar]
10. Devol AH.Denitrification, anammox, and N₂ production in marine sediments. Annu Rev Mar Sci. 2015;7:403–23. [DOI] [PubMed] [Google Scholar]
11. Dubovskaya OP, Gladyshev MI, Gubanov VG et al. Study of non-consumptive mortality of crustacean zooplankton in a Siberian reservoir using staining for live/dead sorting and sediment traps. Hydrobiologia. 2003;504:223–7. [Google Scholar]
12. Dziallas C, Grossart HP, Tang KW et al. Distinct communities of free-living and copepod-associated microorganisms along a salinity gradient in Godthabsfjord, West Greenland. Arct Antarct Alp Res. 2013;45:471–80. [Google Scholar]
13. Elliott DT, Tang KW. Simple staining method for differentiating live and dead marine zooplankton in field samples. Limnol Oceanogr Methods. 2009;7:585–94. [Google Scholar]
14. Garcia-Robledo E, Corzo A, Papaspyrou S. A fast and direct spectrophotometric method for the sequential determination of nitrate and nitrite at low concentrations in small volumes. Mar Chem. 2014;162:30–6. [Google Scholar]
15. Glud RN, Grossart HP, Larsen M et al. Copepod carcasses as microbial hot spots for pelagic denitrification. Limnol Oceanogr. 2015;60:2026–36. [Google Scholar]
16. Gorham E, Boyce FM. Influence of lake surface-area and depth upon thermal stratification and the depth of the summer thermocline. J Great Lakes Res. 1989;15:233–45. [Google Scholar]
17. Hamersley MR, Woebken D, Boehrer B et al. Water column anammox and denitrification in a temperate permanently stratified lake (Lake Rassnitzer, Germany). Syst Appl Microbiol. 2009;32:571–82. [DOI] [PubMed] [Google Scholar]
18. Holmes RM, Aminot A, Kerouel R et al. A simple and precise method for measuring ammonium in marine and freshwater ecosystems. Can J Fish Aquat Sci. 1999;56:1801–8. [Google Scholar]
19. Kamp A, Stief P, Bristow LA et al. Intracellular nitrate of marine diatoms as a driver of anaerobic nitrogen cycling in sinking aggregates. Front Microbiol. 2016;7:Art.1669. [DOI] [PMC free article] [PubMed] [Google Scholar]
20. Kirillin G, Grossart HP, Tang KW. Modeling sinking rate of zooplankton carcasses: effects of stratification and mixing. Limnol Oceanogr. 2012;57:881–94. [Google Scholar]
21. Klawonn I, Bonaglia S, Brüchert V et al. Aerobic and anaerobic nitrogen transformation processes in N₂-fixing cyanobacterial aggregates. ISME J. 2015;9:1456–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
22. Kraft B, Tegetmeyer HE, Sharma R et al. The environmental controls that govern the end product of bacterial nitrate respiration. Science. 2014;345:676–9. [DOI] [PubMed] [Google Scholar]
23. Lehette P, Tovar-Sanchez A, Duarte CM et al. Krill excretion and its effect on primary production. Mar Ecol Prog Ser. 2012;459:29–38. [Google Scholar]
24. Liu WT, Marsh TL, Cheng H et al. Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA. Appl Environ Microbiol. 1997;63:4516–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
25. Ludwig W, Strunk O, Westram R et al. ARB: a software environment for sequence data. Nucleic Acids Res. 2004;32:1363–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
26. Lundgaard ASB, Treusch AH, Stief P et al. Nitrogen cycling and bacterial community structure of sinking and aging diatom aggregates. Aquat Microb Ecol. 2017;79:85–99. [Google Scholar]
27. McIlvin MR, Altabet MA. Chemical conversion of nitrate and nitrite to nitrous oxide for nitrogen and oxygen isotopic analysis in freshwater and seawater. Anal Chem. 2005;77:5589–95. [DOI] [PubMed] [Google Scholar]
28. Moisander PH, Sexton AD, Daley MC. Stable associations masked by temporal variability in the marine copepod microbiome. PLoS One. 2015;10:Art.e0138967. [DOI] [PMC free article] [PubMed] [Google Scholar]
29. Montanari MP, Pruzzo C, Pane L et al. Vibrios associated with plankton in a coastal zone of the Adriatic Sea (Italy). FEMS Microbiol Ecol. 1999;29:241–7. [Google Scholar]
30. Nercessian O, Noyes E, Kalyuzhnaya MG et al. Bacterial populations active in metabolism of C-1 compounds in the sediment of Lake Washington, a freshwater lake. Appl Environ Microbiol. 2005;71:6885–99. [DOI] [PMC free article] [PubMed] [Google Scholar]
31. Oksanen J, Blanchet FG, Kindt R et al. Multivariate analysis of ecological communities in R: vegan tutorial. R package version 1.72013.
32. Ploug H, Bergkvist J. Oxygen diffusion limitation and ammonium production within sinking diatom aggregates under hypoxic and anoxic conditions. Mar Chem. 2015;176:142–9. [Google Scholar]
33. Priddle J, Whitehouse MJ, Atkinson A et al. Diurnal changes in near-surface ammonium concentration—interplay between zooplankton and phytoplankton. J Plankton Res. 1997;19:1305–30. [Google Scholar]
34. Rusch A, Gaidos E. Nitrogen-cycling bacteria and archaea in the carbonate sediment of a coral reef. Geobiology. 2013;11:472–84. [DOI] [PubMed] [Google Scholar]
35. Sand-Jensen K, Lindegaard C. Ferskvandsøkologi. København: Gyldendal, 2004. [Google Scholar]
36. Scavotto RE, Dziallas C, Bentzon-Tilia M et al. Nitrogen-fixing bacteria associated with copepods in coastal waters of the North Atlantic Ocean. Environ Microbiol. 2015;17:3754–65. [DOI] [PubMed] [Google Scholar]
37. Schramm A, Santegoeds CM, Nielsen HK et al. On the occurrence of anoxic microniches, denitrification, and sulfate reduction in aerated activated sludge. Appl Environ Microbiol. 1999;65:4189–96. [DOI] [PMC free article] [PubMed] [Google Scholar]
38. Schubert CJ, Durisch-Kaiser E, Wehrli B et al. Anaerobic ammonium oxidation in a tropical freshwater system (Lake Tanganyika). Environ Microbiol. 2006;8:1857–63. [DOI] [PubMed] [Google Scholar]
39. Shoemaker KM, Moisander PH. Microbial diversity associated with copepods in the North Atlantic subtropical gyre. FEMS Microbiol Ecol. 2015;91:fiv064. [DOI] [PubMed] [Google Scholar]
40. Sorf M, Brandl Z. The rotifer contribution to the diet ofEudiaptomus gracilis (G. O. Sars, 1863) (Copepoda, Calanoida). Crustaceana. 2012;85:1421–9. [Google Scholar]
41. Stief P, Eller G. The gut microenvironment of sediment-dwellingChironomus plumosus larvae as characterised with O₂, pH, and redox microsensors. J Comp Physiol B. 2006;176:673–83. [DOI] [PubMed] [Google Scholar]
42. Stief P, Behrendt A, Lavik G et al. Combined gel probe and isotope labeling technique for measuring dissimilatory nitrate reduction to ammonium in sediments at millimeter-level resolution. Appl Environ Microbiol. 2010;76:6239–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
43. Stief P, Kamp A, Thamdrup B et al. Anaerobic nitrogen turnover by sinking diatom aggregates at varying ambient oxygen levels. Front Microbiol. 2016;7:Art.98. [DOI] [PMC free article] [PubMed] [Google Scholar]
44. Stief P, Lundgaard ASB, Morales-Ramirez A et al. Fixed-nitrogen loss associated with sinking zooplankton carcasses in a coastal oxygen minimum zone (Golfo Dulce, Costa Rica). Front Mar Sci. 2017;4:Art.152. [Google Scholar]
45. Stief P, Lundgaard ASB, Nielsen TG et al. Feeding-related controls on microbial nitrogen cycling associated with the Arctic marine copepodCalanus hyperboreus. Mar Ecol Prog Ser, 2018, DOI: 10.3354/meps12700. [DOI] [Google Scholar]
46. Tang KW, Hutalle KML, Grossart HP. Microbial abundance, composition, and enzymatic activity during decomposition of copepod carcasses. Aquat Microb Ecol. 2006;45:219–27. [Google Scholar]
47. Tang KW, Dziallas C, Hutalle-Schmelzer K et al. Effects of food on bacterial community composition associated with the copepodAcartia tonsa Dana. Biol Lett. 2009a;5:549–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
48. Tang KW, Bickel SL, Dziallas C et al. Microbial activities accompanying decomposition of cladoceran and copepod carcasses under different environmental conditions. Aquat Microb Ecol. 2009b;57:89–100. [Google Scholar]
49. Tang KW, Turk V, Grossart HP. Linkage between crustacean zooplankton and aquatic bacteria. Aquat Microb Ecol. 2010;61:261–77. [Google Scholar]
50. Tang KW, Glud RN, Glud A et al. Copepod guts as biogeochemical hotspots in the sea: evidence from microelectrode profiling ofCalanus spp. Limnol Oceanogr. 2011;56:666–72. [Google Scholar]
51. Tang KW, Gladyshev MI, Dubovskaya OP et al. Zooplankton carcasses and non-predatory mortality in freshwater and inland sea environments. J Plankton Res. 2014;36:597–612. [Google Scholar]
52. Thamdrup B.New pathways and processes in the global nitrogen cycle. Ann Rev Ecol Evol Syst. 2012;43:407–28. [Google Scholar]
53. Tian W, Zhang HY, Zhao L et al. The relationship between phytoplankton evenness and copepod abundance in Lake Nansihu, China. Int J Environ Res Public Health. 2016;13:1–15., Art.E855 [DOI] [PMC free article] [PubMed] [Google Scholar]
54. Tiso M, Schechter AN. Nitrate reduction to nitrite, nitric oxide and ammonia by gut bacteria under physiological conditions. PLoS One. 2015;10:Art.e0119712. [DOI] [PMC free article] [PubMed] [Google Scholar]
55. Warembourg FR.Nitrogen fixation in soil and plant systems. In: Knowles R, Blackburn TH (eds). Nitrogen Isotope Techniques. New York, NY: Academic Press, 1993;157–80. [Google Scholar]
56. Welsh A, Chee-Sanford JC, Connor LM et al. Refined NrfA phylogeny improves PCR-basednrfA gene detection. Appl Environ Microbiol. 2014;80:2110–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
57. Wenk CB, Zopfi J, Gardner WS et al. Partitioning between benthic and pelagic nitrate reduction in the Lake Lugano south basin. Limnol Oceanogr. 2014;59:1421–33. [Google Scholar]
58. Xu Z, Xu YJ. Determination of trophic state changes with diel dissolved oxygen: a case study in a shallow lake. Wat Environ Res. 2015;87:1970–9. [DOI] [PubMed] [Google Scholar]
59. Zehr JP, Mellon MT, Zani S. New nitrogen-fixing microorganisms detected in oligotrophic oceans by amplification of nitrogenase (nifH) genes. Appl Environ Microbiol. 1998;64:3444–50. [DOI] [PMC free article] [PubMed] [Google Scholar]

Supplementary Materials