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Article

Anthropogenic Nitrate Contamination Impacts Nitrous Oxide Emissions and Microbial Communities in the Marchica Lagoon (Morocco)

by
Chahrazade El Hamouti
1,
Antonio Castellano-Hinojosa
2,*,
Youness Mabrouki
3,
Bouchra Chaouni
4,
Hassan Ghazal
5,
Noureddine Boukhatem
6,
Rajaa Chahboune
1 and
Eulogio J. Bedmar
2
1
Life and Health Sciences Laboratory, Faculty of Medicine and Pharmacy, Abdelmalek Essaadi University, Tanger 90000, Morocco
2
Department of Soil Microbiology and Symbiotic Systems, Estación Experimental del Zaidín-CSIC, E-18008 Granada, Spain
3
Conservation and Valorization of Natural Resources Laboratory, Faculty of Sciences Dhar El Mehraz, Sidi Mohammed Ben Abdellah University, Fèz-Atlas 30003, Morocco
4
Laboratory of Plant and Microbial Biotechnology, Biodiversity and Environment, Faculty of Sciences, Mohammed V University, Rabat 10000, Morocco
5
Scientific Department, National Center for Scientific and Technical Research (CNRST), Rabat 10102, Morocco
6
Laboratory of Bioresources, Biotechnology, Ethnopharmacology and Health, Faculty of Sciences, Mohammed First University, Oujda 60000, Morocco
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(5), 4077; https://doi.org/10.3390/su15054077
Submission received: 4 January 2023 / Revised: 9 February 2023 / Accepted: 20 February 2023 / Published: 23 February 2023
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Abstract

:
Lagoon systems are often confined, and their waters are poorly renewed, which makes them vulnerable to pollutants’ accumulation. Here, the impact of different sources of anthropogenic contamination (domestic, urban, industrial, and agricultural) on the nitrate (NO3−) content, emission of the greenhouse gas nitrous oxide (N2O), abundance of total bacterial archaeal, nitrifying, and denitrifying communities, and diversity and composition of bacterial communities in the sediments of the RAMSAR-protected Marchica lagoon (Nador, Morocco) was investigated. Six lake sites differing in NO3− concentration were selected. Wastewater coming from industrial activities results in the greatest concentration of NO3− in sediments and emissions of N2O. Increased carbon to nitrogen content in sites near domestic activities resulted in an increase in the abundance of total bacterial and archaeal communities, as well as nitrification and denitrification genes, but low N2O emissions due to a greater presence of microorganisms involved in N2O production over those able to reduce N2O. Significant differences in bacterial community composition between sites were observed, with the NO3− content being the main driver of these changes. Increased NO3− content in the sampling sites significantly reduced bacterial diversity. Bacterial genera involved in the degradation of organic and inorganic pollutants and nitrous oxide reduction, such as Robiginitalea, Symbiobacterium, Bacillus, Fusibacter, Neptunomonas, Colwellia, and Alteromonas, were the most abundant in the lagoon. The results suggest that the type of anthropogenic contamination directly impacts the nitrate content in the sediments of the Marchica lagoon, which determines variations in nitrous oxide emissions, nitrogen-cycling gene abundances, and bacterial diversity.

1. Introduction

Coastal lagoons are boundary environments of high ecological value located in the transitional zones between land and sea and provide critical supporting ecosystem services, including habitat for birds and fish, nutrient retention and export, flood control, and shoreline stabilization [1,2]. Despite their worldwide contribution to people′s social and economic welfare, increased anthropogenic pressure due to domestic, urban, agricultural, mining, and industrial activities threatens coastal lagoons in terms of water pollution, conservation, and management.
Nitrogen (N) is a key element for life since it is a basic component of proteins, hormones, and nucleic acids. For centuries, scarce amounts of reactive nitrogen species (RNs) accumulated in environmental reservoirs as RN formation was balanced by deep sedimentation and the conversion of RN back to N2 [3,4]. Changes in energy and food production patterns during the 19th and 20th centuries as a result of the industrial and agricultural revolutions have altered the natural functioning of the N-cycle [3,4]. Excess N is considered responsible for the creation of unintended RN, which causes water eutrophication as well as soil and air pollution [5]. Nitrification and denitrification are widely recognized as the dominant RN removal processes during the N cycle [5]. Within this cycle, denitrification is the biological process that reduces NO3− to molecular nitrogen (N2) through the formation of nitrite (NO2−), nitric oxide (NO), and nitrous oxide (N2O) under oxygen (O2)-limited conditions via the enzymes encoded by the napA/narG, nirK/nirS, norB, and nosZ genes, respectively [6,7,8]. Denitrification in sediments has been reported, with particular focus on N2O emissions [9,10,11,12], an anthropogenic greenhouse gas about 300 times as potent as carbon dioxide (CO2) that accounts for about 12% of global greenhouse emissions [13,14].
The lagoon of Marchica is the broadest paralic environment in the northern Mediterranean coast of Morocco (Africa). With about 115 km2, the lagoon is limited by two jetties that communicate it with the Mediterranean Sea and an artificial inlet [15,16] (Figure 1). This inlet was built in 2011, replacing the previous natural small channel and securing water renewal; consequently, the lagoon was transformed from a choked to a leaky lagoon [15,17]. Marchica is the only lagoon ecosystem on the Moroccan Mediterranean coast and was declared a RAMSAR site in 2005 due to its high ecological and environmental importance for the conservation of wetlands. It is considered a very productive area and plays an important socio-economic role. Touristic activities and artisanal fishing are the main economic activities carried out in the lagoon. The internal hydrodynamics of Marchica depend mainly on the marine waters passing through the artificial inlet, the contribution of the Gareb and Bou Areg aquifers, and some other small streams flowing periodically into the lagoon. Geomorphologically, lagoon systems are often confined, and their waters are poorly renewed, which makes them vulnerable to pollutant accumulation [18,19]. Due to the growing number of socio-economic activities in the localities adjacent to the Marchica lagoon, the anthropogenic pressure on it is increasing, with the main causes being the discharge of wastewater and the extraction of minerals, whose residues are kept in the open air. Studies on the metallic trace elements in the lagoon sediments revealed that cadmium (Cd), lead (Pb), copper (Cu), and zinc (Zn) were the most abundant contaminants, most likely coming from the sewage treatment plants of Nador and the runoffs of the industrial areas of Selouane and Kariet Arkmane [20]. Other sources of pollution are the untreated waters from the numerous irrigation streams that carry the solid and liquid residues from the nearby abundant agricultural fields and farming exploitations that empty into the lagoon; this, in turn, has produced considerable increases in nitrate (NO3−) concentration, which has led to eutrophication of the lagoon.
Previous studies have found that NO3− run-off to lakes contributes to eutrophication, increases in the abundance of N-cycling genes and N2O emissions, and changes in the diversity of bacterial communities [21,22,23,24,25]. Although several authors have studied the sedimentology, biology, and geochemistry of the Marchica lagoon [26,27,28], data on the effects produced by anthropogenic NO3− contamination on the activity, abundance, diversity, and composition of microbial communities in the sediments of the lagoon with possible consequences on N2O emissions are not available. This information is important to evaluate the potential consequences of different human disturbance activities releasing NO3− to the lake on microbial communities providing key ecosystem services in the lagoon as well as their sensitivity to different kinds of stress. In addition, the quantification of enzymatic activities related to nitrogen (N), carbon (C), phosphorus (P), and sulfur (S) biogeochemical cycles is often used as an indicator of changes produced in the cycles, including those that stem from anthropogenic disturbances, as they are sensitive to variations in substrate quality and abiotic factors [29].
Therefore, the objective of this study was to elucidate the impact of agricultural, industrial, domestic, and urban discharges on the NO3− content, enzyme activities, N2O production, abundance of nitrifiers and denitrifiers, and the diversity of bacterial communities in the sediments of the Marchica lagoon. Multivariate analyses were used to study the relationships between the origin and content of the NO3− contamination, the N2O gas emissions, and the abundance and diversity of microbial communities. It was hypothesized that the source of anthropogenic contamination would determine different NO3− concentrations in lake sediments, which would differentially impact N2O emissions, N-cycling gene abundances, and microbial diversity and composition.

2. Materials and Methods

2.1. Sampling Sites

This study was performed on the Marchica lagoon, locally known as Sebkha Bou-Areg, located near the city of Nador (Morocco), which is why it also receives the name of the Nador lagoon. The lagoon is protected by a northwest-southeast elongated 25 km length and 300–400 m width sandy spit that is only interrupted by an artificial inlet 300 m in width and 6.5 m in depth (Figure 1). In October 2018, following in situ measurement of the NO3− content using a NO3− test kit (CHEMetrics Inc., Midland, VA, USA) of more than 25 sediments randomly taken to a soil depth of 10 cm near the mouth of the different rivers and streams that flow into the lagoon, 6 sampling sites were selected (Figure 1): the Kariat Arkmane stream (S1; 35°06′16.6″ N; 2°44′55.8″ W), an irrigation channel for agricultural fields (S2, 35°07′21.3″ N 2°51′35.9″ W), the Selouane stream (S3, 35°07′54.4″ N; 2°52′57.5″ W), the Caballo stream (S4, 35°09′40.3″ N; 2°54′31.1″ W), the Bouareg stream (S5, 35°08′53.3″ N; 2°54′06.8″ W), and the Tirakaa stream (S6, 35°11′15.6″ N; 2°55′31.6″ W). The selection of the sampling sites was based on the origin and NO3− content of the sediments: sites S1, S4, and S5 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; site S3 those of industrial wastewaters; and site S6 those predominantly of domestic origin from an artisanal fishing port (Figure 1).

2.2. Sediment Physicochemical Properties and Enzymatic Analysis

Sediment samples (4 per sampling site) were collected from the top layer (0–10 cm) within 2 m2 at 3–4 m from the lagoon shore using an Eijkelkamp peat sampler (Aqualab Scientific, Cromer, Australia). Samples were kept separately and maintained at −80 °C until use. The pH and concentrations of NO3−, NO2−, exchangeable NH4+, total carbon, organic carbon, and nitrogen (TC, TOC, and TN, respectively) in sediment samples were determined as described by Gonzalez-Martinez et al. [30] using an ionic chromatograph (Metrohm, Madrid, Spain) equipped with an anion (Metrosep A supp-4-250) and a cation (Metrosep C2-150) column and a TruSpec CN elemental analyzer (LECO, St. Joseph, MI, USA), respectively. Enzymatic activities related to main biogeochemical cycles (urease, acid phosphatase, arylsulphatase, and β-glucosidase) were measured in sediment samples as previously published [31]. The content of moisture in the sediment samples was determined gravimetrically by oven-drying 10 g of the samples at 105 °C for 24 h.

2.3. Nitrous Oxide Emissions

Production of N2O by the sediments was assayed using the procedures described in [32]. Essentially, 25 g of sediments (covered with a 2 cm layer of water from the lagoon) were placed in hermetically sealed 125 mL glass flasks and flushed with He; then, about 10% (12.5 mL) of the atmosphere of the flasks was replaced by acetylene to inhibit N2O reductase activity [33]. Gas samples (5 mL) were taken every 12 h and injected into a gas chromatograph (Hewlett-Packard 5890, Agilent, Santa Clara, CA, USA) to measure N2O fluxes [31]. The concentration of N2O was estimated using the Bunsen coefficient, which considers the N2O dissolved in water [31].

2.4. Extraction of DNA and Quantification of N-Cycling Genes

Total genomic DNA was extracted from 0.5 g of samples using the DNeasy PowerMax Soil Kit (Qiagen, Hilden, Germany). Gel electrophoresis and the Qubit2® ssDNA assay kit (Thermo Fisher Scientific, Waltham, MA, USA) were used to determine the quality and concentration of DNA, respectively. DNA was kept at −80 °C until use.
The quantitative PCR (qPCR) method was used for the estimation of the total abundances of different genes using a Bio-Rad iCycler iQ5 thermocycler (Bio-Rad Laboratories, Hercules, CA, USA) [34]. The total abundance of archaeal (16SA) and bacterial (16SB) communities was assessed using the 16S rRNA gene as a molecular marker. The total abundance of ammonia-oxidizing bacteria (AOB) and archaea (AOA) involved in nitrification was estimated using the amoA gene as a molecular marker. The abundance of the denitrification genes napA, narG, nirK, nirS, and nosZI was also estimated. The primers, PCR reaction mixtures, and PCR thermocycler conditions are shown in Supplementary Table S1. Melting curves analysis and gel electrophoresis were used to check the quality of the qPCR amplifications.

2.5. Amplicon Sequencing and Data Processing

Sites S1, S2, S3, and S4 were selected for the analysis of the bacterial diversity as they represented lagoon effluents of different origins and covered the gradient of NO3− concentrations detected in the lagoon (Table 1). Illumina Miseq technology was used to amplify the bacterial 16S rRNA gene (V3–V4 region) using the 341F and R806 primers [35]. Samples were sequenced at the facilities of the Genomic Unit of the Institute of Parasitology and Biomedicine López-Neyra (IPBLN-CSIC, Granada, Spain). Forward and reverse sequence reads were merged, assembled, and dereplicated into representative amplicon sequence variants (ASVs) using DADA2 [36] as described by [37]. The resulting ASVs were assigned to the SILVA 132 database [38] using QIIME2 v2018.4 [39]. The final dataset for the S1, S2, S3, and S4 sites consisted of 78451, 87956, 79468, and 84565 sequences, respectively. In total, 235, 221, 118, and 159 representative ASVs for the S1, S2, S3, and S4 sites were obtained, respectively. Raw sequences can be found in the NCBI’s Sequence Read Archive under BioProject PRJNA841256.

2.6. Bacterial Diversity

Values of the alpha diversity indices (Shannon, Simpson, and Good’s coverage) were calculated in R using package “Phyloseq” version 1.24.0 [40]. Significant differences in beta diversity between the sites were examined using a Bray–Curtis-based principal coordinate analysis (PCoA) together with a permutational multivariate analysis of variance (PERMANOVA). Venn diagrams were constructed to determine the relationships among ASVs from the different sampling sites using the ‘gplots’ package (version 3.0.1 [41]).

2.7. Statistical Analyses

The R software (http://www.rproject.org/, accessed on 15 October 2022) was used for data analysis (version 4.0.3). The relationships between the sediment physicochemical properties, N2O emissions, and abundance of the targeted genes were assayed using a redundancy analysis (RDA) [42] as described earlier [43]. The correlation between variables was determined using the Pearson correlation coefficient (r). A distance-based Redundancy Analysis (db-RDA) based on Bray–Curtis distances was performed to study differences in the composition of the bacterial community between sites due to variations in the physicochemical properties of the sediments in R using the “vegan” package. The soil parameters controlling changes in the bacterial community were identified via permutation tests (p < 0.01) with the R package vegan. The collinearity of the vectors was tested using the package usdm (version 1.1.15).

3. Results

3.1. Physicochemical Properties of the Sediments

Values of physicochemical properties in the sediments collected at the sampling sites of the Marchica lagoon are shown in Table 1. No significant differences in NH4+ content were detected among sites, but the NO3− concentration was significantly greater in site S3 and site S5 compared to the rest of the sites, with site S1 showing the lowest values. The TN content was significantly lower in site S4 compared to the remaining locations. The TOC content was greatest in site S6, followed by sites S5, S1, S2, S3, and finally S4.

3.2. Enzymatic Activities in the Sediments

The activities of the enzymes urease, acid phosphatase, arylsulphatase, and β-glucosidase differed significantly between sampling sites (Figure 2). The arylsulphatase and β-glucosidase activities were significantly greater in site S1 compared to the rest of the locations which showed no differences in the values of both enzyme activities. The urease activity was significantly lower in site S2 compared to the other sites, and sites S2 and S5 showed the lowest values of acid phosphatase activity (Figure 2).

3.3. Nitrous Oxide Emission

The emission of N2O from sediments varied significantly among sites (Table 2). N2O emissions were significantly greater at site S3 compared to the rest of the sites. Significantly greater emissions of N2O were detected at site S5 compared to sites S4 and S6. Sites S1 and S2 showed the lowest emissions of N2O.

3.4. Quantification of the Total Communities and N-Cycling Genes

Gene abundances of the targeted genes in the sediments of the sampling sites are presented in Figure 3. The abundance of the 16SB gene was significantly greater in S2 than in the remaining sites. The abundance of the 16SA gene varied widely among sites and was statistically greater in S6 than in the other locations. The total abundance of the amoA AOA gene did not significantly differ among sites, but that of amoA AOB was greater in S6 than in the rest of the locations. The napA, nirK, nirS, and nosZI gene abundances in site S6 were significantly greater compared to the remaining sites, whereas site S1 showed the lowest values. Sites S5 and S6 showed statistically greater abundances of the narG gene compared to the rest of the locations.
A calculated ratio between the total abundance of nitrification and denitrification genes involved in N2O production (amoA AOA + amoA AOB + nirK + nirS) and those involved in N2O reduction (nosZI) showed the values of the ratio were significantly greater in site S3 compared to the remaining sites (Supplementary Table S2). Sites S1 and S2 showed the lowest values of the ratio (Supplementary Table S2).

3.5. Linking Sediment Physicochemical Properties, Gene Abundance, and N2O Emissions

A significant relationship between the sediment physicochemical properties, the abundance of the targeted genes, and the N2O emissions was revealed by the RDA analysis (Monte Carlo test, p = 0.001) (Figure 4). Pearson’s coefficients denoting correlations among variables are presented in supplementary Table S3. The 16SA and 16SB gene abundances displayed opposite ordinations and were positively (r > 0.85) and negatively (r < −0.90) correlated with the content of TN and TOC, respectively. A strong positive correlation was detected between the abundance of each of the nitrification genes and NH4+ concentration (r > 0.87) but both genes negatively correlated with the content of NO3− (r < −0.78). The napA and narG gene abundances were positively correlated (r > 0.80) with NO3− content. N2O emissions correlated positively (r = 0.87) with the nirS gene but negatively with the nosZI gene (r = 0.90). The RDA analysis also showed that samples corresponding to sites S1 and S2 clustered together, while those from sites S3, S4, and S5 formed a different group, and that the samples corresponding to site S6 formed an independent cluster (Figure 4).

3.6. Diversity, Structure, and Composition of the Bacterial Community

A good sequencing effort was achieved as the values of the good coverage index were higher than 92.5%. A significantly greater number of ASVs and values of the Shannon and Simpson indices were observed in sites S1 and S2 compared to sites S3 and S4 (Figure 5a). The values of the alpha diversity indices were significantly lower at site S4 compared to the rest of the sampling sites. The PCoA and PERMANOVA analyses showed significant differences in the composition of the bacterial community between the sites (Figure 5b; p < 0.01). The samples corresponding to sites S1 and S2 clustered together, whereas those of sites S3 and S4 formed two isolated groups, as further shown by the percentage of ASVs being exclusive to each site (Supplementary Figure S1). For example, 39.6% of the total number of ASVs were shared between sites S1 and S2, and 17.0% and 19.4% of the ASVs were exclusive to sites S3 and S4, respectively.
Taxonomy summary plots of the bacterial community at the four different sites at the phylum, order, class, and genus taxonomic levels are presented in Supplementary Figure S2. The bacterial community was dominated by the phyla Actinobacteria (38% of relative abundance) and Bacteroidetes (16% of relative abundance) in site S1 and by Actinobacteria (59% of relative abundance), Bacteroidetes (15% of relative abundance), and Proteobacteria (15% of relative abundance) in site S2. Actinobacteria (26% of relative abundance) and WWE3 (38% of relative abundance) were the most representative phyla in site S3, and Bacteroidetes (49% of relative abundance) in site S4. Robiginitalea was the dominant genera in site S1 with 47% relative abundance. Fusibacter, Robiginitalea, Shewanella, and Symbiobacterium were the most abundant genera in site S2, accounting for 88% of the relative abundance. In site S3, 15% and 25% of the ASVs were affiliated with Robiginitalea and uncultured anaerobic bacteria, respectively. In site S4, the bacterial community was formed by the genera Shewanella, Robiginitalea, Pesudoalteromonas, Neptunomonas, Colwellia, and Bacillus.

3.7. Linking Sediment Physicochemical Properties with Bacterial Diversity

A db-RDA analysis revealed that the physicochemical properties of the sediments drive variations in the bacterial community composition between sites (Figure 6). The proportion of the total variability of the bacterial community attributed to the sediment physicochemical properties variables was 47.2% and was significant (general permutation test, p < 0.001; Figure 6). The content of NO3−-N was the main controller of the variations in the diversity of the bacterial community, as revealed by the length of its vector (Figure 6). The db-RDA analysis also shows that samples corresponding to sites S1 and S2, and those of sites S3 and S4, clustered together.

4. Discussion

Lagoon systems are often confined, and their waters are poorly renewed, which makes them vulnerable to impacts from domestic, urban, industrial, and agricultural anthropogenic activities, particularly in the form of NO3−. This study found that the source of human contamination determines variations of the NO3− content in the sediments of the Marchica lagoon, which directly impact N2O emissions. These alterations were linked to changes in the abundance of N-cycling communities (mainly denitrifiers) and in the diversity and composition of the bacterial community in the sediments of the lagoon. Among anthropogenic activities, wastewater coming from industrial activities resulted in the greatest concentration of NO3− in sediments and emissions of N2O. Increased NO3− content had negative effects on bacterial diversity and altered the composition of the bacterial community. Increased TOC and TN content in sites nearby activities of domestic origin resulted in an increased abundance of total bacterial and archaeal communities and nitrification and denitrification genes but low N2O emissions due to a greater presence of N2O reducers than N2O producers. Other anthropogenic activities, such as those of agriculture precedence and urban wastewaters, had low effects on physicochemical properties, N2O emissions, and microbial communities in the sediments.
The type of anthropogenic activity determined variations in NO3− content (N availability) and TC and TOC (C availability) in the sediments of the Machica lagoon. For example, sites receiving mainly urban (e.g., site S3) and industrial (site S5) wastewater through the streams that flow into the lagoon showed the greatest content of NO3−, whereas those nearby domestic activities from an artisanal fishing port (site S6) had the greatest organic C content. Overall, these results are in agreement with previously published studies showing that human disturbance activity determines variations in N and C availability in lake sediments [44,45]. The NO3− concentration in the sediments of sites S3 and S5, which receive residues from an upstream industrial slaughterhouse and an urban wastewater treatment plant, respectively, was higher than those published by other authors in lakes contaminated with NO3− [27,46,47,48] and those of the Moroccan Standards for Surface Water Quality (2002), thus suggesting potential NO3− contamination in some areas of the Marchica lagoon.
Increased NO3− in the sediments resulted in increases in N2O emissions, which were linked to values of the ratio between N-cycling genes involved in N2O production vs. reduction. For example, the greatest values of the ratio were found at site S3, which had the highest N2O emission and NO3− content. By contrast, N-cycling communities in sites S1 and S2 showed the greatest potential to carry out complete denitrification to N2, as revealed by the lowest N2O emissions and greater abundance of N2O producers over N2O reducers. Taken together, these results show N-cycling communities in the Marchica lagoon have the potential to reduce N2O emissions, but excessive NO3− content from specific anthropogenic activities such as wastewater from industrial and urban origins may favor the abundance of N2O producers over reducers in lake sediments. Other authors found that excess NO3− in lake sediments due to different anthropogenic activities leads to emissions of N2O as a result of increased denitrification [24,49,50]. Although nitrification is often a minor N2O production process in lake sediments due to low oxygen availability [32,51], nitrifiers (mainly AOB) were present in the sediments of the Marchica lagoon. Given the neutral-alkaline pH and the NH4+ content in the sediments, it is possible that AOB became a greater player than AOA for ammonia oxidation and N2O emission by nitrification in the sediments of the Marchica lagoon [52]. Nevertheless, nitrifiers were about 100 times less abundant than denitrifiers in the lake sediments, suggesting that denitrification was the major process contributing to N2O production.
Increased C availability in sediments from nearby activities of domestic origin resulted in increases in the abundance of bacteria, above all in archaeal communities. These results agree with recent findings showing that archaeal communities respond to variations in C content in coastal sediments [53]. There is reported evidence that archaeal species play key roles in sediment C cycling and can actively process organic C, affecting the fate of buried organic C [53,54,55].
The bacterial diversity significantly decreased in sites with greater NO3− content, which was the main abiotic factor determining variations in the composition of the bacterial community in the lagoon. These results agree with those in previous studies showing that NO3− run-off to coastal lakes contributes to changes in the diversity of bacterial communities in sediments [21,22,25]. Among sources of anthropogenic contamination with NO3−, sites receiving mainly wastewater from industrial (S4) and urban (S3) activities had the lowest number of ASVs and values of the Shannon index. Previous studies have linked decreased bacterial diversity to increased NO3− content in lake sediments [21,24,56] and soils [43,57,58]. Despite differences in NO3− content (Table 1) and composition of the bacterial community among sites (Figure 5b), RDA analyses showed that NO3− was the main controller of changes in the abundance of N-cycling genes (Figure 4) and bacterial diversity. Accordingly, it is not the source of anthropogenic contamination but the sediment NO3− content that is the main factor explaining variations in bacterial communities in the Marchica lagoon.
Actinobacteria and Bacteroidetes were the dominant phyla in all four sampling sites, followed by Proteobacteria, all of which are commonly found in sediments of rivers and lagoons [59,60,61]. Bacteroidetes are microorganisms with fast growth rates that become dominant in nutrient-rich conditions, such as in lake sediments contaminated with NO3− [24]. Robiginitalea, a common genus in marine sediments [62], with the ability to reduce N2O to N2 [63], was the dominant taxon in sites S1 and S3. The bacterial community at sites S2 and S4 was dominated by genera containing species capable of reducing NO3− to N2 under oxygen-limiting conditions, such as Fusibacter, Robiginitalea, Shewanella, Bacillus, and Symbiobacterium, thanks to the presence of the nosZ gene in their genomes [64,65,66,67].

5. Conclusions

This study is of important environmental interest as it shows that the NO3− content coming from different anthropogenic activities in the streams that flow into the Marchica lagoon directly impacts physicochemical properties, N2O emissions, N-cycling gene abundances, and bacterial diversity. Among anthropogenic activities, wastewater from industrial activities results in the greatest concentration of NO3− in sediments and, therefore, emissions of N2O. Human activities that increase TOC and TN, such as those of domestic origin, result in a higher abundance of total communities and N-cycling genes but low N2O emissions. Lake sites showing lower N2O emissions were linked to a greater abundance of N2O reducers than N2O producers. Increased NO3− content determined decreases in bacterial diversity and changes in the composition of the bacterial community in the lagoon. The results of this work should facilitate expanded studies aimed at the preservation of the Marchica lagoon from undesirable effects due to anthropogenic contamination, and assist in management decisions by the corresponding authorities.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su15054077/s1, References [68,69,70,71,72,73,74,75,76,77] are cited in the Supplementary Materials.

Author Contributions

Conceptualization, C.E.H., A.C.-H., R.C. and E.J.B.; data curation, C.E.H., Y.M., B.C., H.G., N.B. and R.C.; funding acquisition, C.E.H. and E.J.B.; investigation, C.E.H. and A.C.-H.; methodology, C.E.H., A.C.-H. and E.J.B.; writing—original draft, C.E.H. and A.C.-H.; writing—review and editing, R.C. and E.J.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

We acknowledge the support of Junta de Andalucía to group BIO275. We thank Soumiya Essayeh and Soufian El Barkany from the Polydisciplinary Faculty of Nador, and Mohamed First University, for providing the facilities during the sampling days.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Pérez-Ruzafa, A.; Campillo, S.; Fernández-Palacios, J.M.; García-Lacunza, A.; García-Oliva, M.; Ibañez, H.; Navarro-Martínez, P.C.; Pérez-Marcos, M.; Pérez-Ruzafa, I.M.; Quispe-Becerra, J.I.; et al. Long-Term Dynamic in Nutrients, Chlorophyll a, and Water Quality Parameters in a Coastal Lagoon During a Process of Eutrophication for Decades, a Sudden Break and a Relatively Rapid Recovery. Front. Mar. Sci. 2019, 6, 26. [Google Scholar] [CrossRef] [Green Version]
  2. Pérez-Ruzafa, A.; Marcos, C.; Pérez-Ruzafa, I.M.; Pérez-Marcos, M. Coastal lagoons: “transitional ecosystems” between transitional and coastal waters. J. Coast. Conserv. 2011, 15, 369–392. [Google Scholar] [CrossRef]
  3. Galloway, J.N.; Leach, A.M.; Bleeker, A.; Erisman, J.W. A chronology of human understanding of the nitrogen cycle. Philos. Trans. R. Soc. B Biol. Sci. 2013, 368, 20130120. [Google Scholar] [CrossRef] [Green Version]
  4. Erisman, J.W.; Galloway, J.N.; Dice, N.B.; Sutton, M.A.; Bleeker, A.; Grizzetti, B.; Leach, A.M.; de Vries, W. Nitrogen: Too Much of a Vital Resource: Science Brief; WWF: Zeist, The Netherlands, 2015. [Google Scholar]
  5. López-Aizpún, M.; Castellano-Hinojosa, A.; González-López, J.; Bedmar, E.J.; Loick, N.; Barrat, H.; Ma, Y.; Chadwick, D.; Cardenas, L.M. Nitrogen Cycle in Agriculture: Biotic and Abiotic Factors Regulating Nitrogen Losses, in Nitrogen Cycle; CRC Press: Boca Raton, FL, USA, 2021; pp. 34–59. [Google Scholar] [CrossRef]
  6. Bueno, E.; Mesa, S.; Bedmar, E.J.; Richardson, D.J.; Delgado, M.J.; Schut, G.J.; Zadvornyy, O.; Wu, C.-H.; Peters, J.W.; Boyd, E.S.; et al. Bacterial Adaptation of Respiration from Oxic to Microoxic and Anoxic Conditions: Redox Control. Antioxid. Redox Signal. 2012, 16, 819–852. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Kuypers, M.M.M.; Marchant, H.K.; Kartal, B. The microbial nitrogen-cycling network. Nat. Rev. Microbiol. 2018, 16, 263–276. [Google Scholar] [CrossRef]
  8. Liu, H.; Li, Y.; Pan, B.; Zheng, X.; Yu, J.; Ding, H.; Zhang, Y. Pathways of soil N2O uptake, consumption, and its driving factors: A review. Environ. Sci. Pollut. Res. 2022, 29, 30850–30864. [Google Scholar] [CrossRef] [PubMed]
  9. Liu, W.; Wang, Z.; Zhang, Q.; Cheng, X.; Lu, J.; Liu, G. Sediment denitrification and nitrous oxide production in Chinese plateau lakes with varying watershed land uses. Biogeochemistry 2015, 123, 379–390. [Google Scholar] [CrossRef]
  10. Liu, W.; Yao, L.; Jiang, X.; Guo, L.; Cheng, X.; Liu, G. Sediment denitrification in Yangtze lakes is mainly influenced by environmental conditions but not biological communities. Sci. Total Environ. 2018, 616, 978–987. [Google Scholar] [CrossRef]
  11. Correa-Galeote, D.; Tortosa, G.; Moreno, S.; Bru, D.; Philippot, L.; Bedmar, E.J. Spatio-Temporal Variations in the Abundance and Structure of Denitrifier Communities in Sediments Differing in Nitrate Content. Curr. Issues Mol. Biol. 2017, 24, 71–102. [Google Scholar] [CrossRef]
  12. Chang, Y.; Yin, G.; Hou, L.; Liu, M.; Zheng, Y.; Han, P.; Dong, H.; Liang, X.; Gao, D.; Liu, C. Nitrogen removal processes coupled with nitrification in coastal sediments off the north East China Sea. J. Soils Sediments 2021, 21, 3289–3299. [Google Scholar] [CrossRef]
  13. Ravishankara, A.R.; Daniel, J.S.; Portmann, R.W. Nitrous Oxide (N2O): The Dominant Ozone-Depleting Substance Emitted in the 21st Century. Science 2009, 326, 123–125. [Google Scholar] [CrossRef] [Green Version]
  14. Hergoualc’h, K.; Akiyama, H.; Bernoux, M.; Chirinda, N.; Prado, A.D.; Kasimir, Å.; MacDonald, J.D.; Ogle, S.M.; Regina, K.; Weerden, T.J. IPCC N2O Emissions from Managed Soils, and CO2 Emissions from Lime and Urea Application. In Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories Prepared by the National Greenhouse Gas Inventories Programme IGES; Intergovernmental Panel on Climate Change: Hayama, Japan, 2019. [Google Scholar]
  15. Karim, H.; Ahmed, D.; Mohammed, I.; Benyounes, D. Circulation marine de la lagune de Nador (Maroc) par modélisation hydrodynamique. Eur. Sci. J. 2015, 11, 418–428. [Google Scholar]
  16. Selfati, M.; El Ouamari, N.; Franco, A.; Lenfant, P.; Lecaillon, G.; Mesfioui, A.; Boissery, P.; Bazairi, H. Fish assemblages of the Marchica lagoon (Mediterranean, Morocco): Spatial patterns and environmental drivers. Reg. Stud. Mar. Sci. 2019, 32, 100896. [Google Scholar] [CrossRef]
  17. Umgiesser, G.; Ferrarin, C.; Cucco, A.; De Pascalis, F.; Bellafiore, D.; Ghezzo, M.; Bajo, M. Comparative hydrodynamics of 10 Mediterranean lagoons by means of numerical modeling. J. Geophys. Res. Ocean. 2014, 119, 2212–2226. [Google Scholar] [CrossRef]
  18. Coelho, S.; Pérez-Ruzafa, A.; Gamito, S. Phytoplankton community dynamics in an intermittently open hypereutrophic coastal lagoon in southern Portugal. Estuar. Coast. Shelf Sci. 2015, 167, 102–112. [Google Scholar] [CrossRef]
  19. Scanes, P.; Ferguson, A.; Potts, J. Estuary form and function: Implications for palaeoecological studies, in Applications of paleoenvironmental techniques in estuarine studies. Springer 2017, 20, 9–44. [Google Scholar] [CrossRef]
  20. Oujidi, B.; El Bouch, M.; Tahri, M.; Layachi, M.; Boutoumit, S.; Bouchnan, R.; Ouahidi, H.; Bounakhla, M.; El Ouamari, N.; Maanan, M.; et al. Seasonal and Spatial Patterns of Ecotoxicological Indices of Trace Elements in Superficial Sediments of the Marchica Lagoon Following Restoration Actions during the Last Decade. Diversity 2021, 13, 51. [Google Scholar] [CrossRef]
  21. Scofield, V.; Jacques, S.; Guimarães, J.R.D.; Farjalla, V.F. Potential changes in bacterial metabolism associated with increased water temperature and nutrient inputs in tropical humic lagoons. Front. Microbiol. 2015, 6, 310. [Google Scholar] [CrossRef] [Green Version]
  22. Highton, M.P.; Roosa, S.; Crawshaw, J.; Schallenberg, M.; Morales, S.E. Physical Factors Correlate to Microbial Community Structure and Nitrogen Cycling Gene Abundance in a Nitrate Fed Eutrophic Lagoon. Front. Microbiol. 2016, 7, 1691. [Google Scholar] [CrossRef] [Green Version]
  23. Wang, W.; Liu, W.; Wu, D.; Wang, X.; Zhu, G. Differentiation of nitrogen and microbial community in the littoral and limnetic sediments of a large shallow eutrophic lake (Chaohu Lake, China). J. Soils Sediments 2019, 19, 1005–1016. [Google Scholar] [CrossRef]
  24. Li, Y.; Sun, Y.; Zhang, H.; Wang, L.; Zhang, W.; Niu, L.; Wang, P.; Wang, C. The responses of bacterial community and N2O emission to nitrogen input in lake sediment: Estrogen as a co-pollutant. Environ. Res. 2019, 179, 108769. [Google Scholar] [CrossRef]
  25. Zhu, W.; Liu, J.; Li, Q.; Gu, P.; Gu, X.; Wu, L.; Gao, Y.; Shan, J.; Zheng, Z.; Zhang, W. Effects of Nutrient Levels on Microbial Diversity in Sediments of a Eutrophic Shallow Lake. Front. Ecol. Evol. 2022, 10, 412. [Google Scholar] [CrossRef]
  26. Raji, O.; Dezileau, L.; Von Grafenstein, U.; Niazi, S.; Snoussi, M.; Martinez, P. Extreme sea events during the last millennium in the northeast of Morocco. Nat. Hazards Earth Syst. Sci. 2015, 15, 203–211. [Google Scholar] [CrossRef] [Green Version]
  27. Mohamed, N.; Driss, N.; Nadia, B.; Roberto, P.; Abdeljaouad, L.; Nor-Dine, R. Characterization of the New Status of Nador Lagoon (Morocco) after the Implementation of the Management Plan. J. Mar. Sci. Eng. 2017, 5, 7. [Google Scholar] [CrossRef] [Green Version]
  28. Oujidi, B.; Tahri, M.; Layachi, M.; Abid, A.; Bouchnan, R.; Selfati, M.; Bounakhla, M.; El Bouch, M.; Maanan, M.; Bazairi, H.; et al. Effects of the watershed on the seasonal variation of the surface water quality of a post-restoration coastal wetland: The case of the Nador lagoon (Mediterranean sea, Morocco). Reg. Stud. Mar. Sci. 2020, 35, 101127. [Google Scholar] [CrossRef]
  29. Lee, S.-A.; Lee, J.; Han, Y.; Kim, G. Biogeochemical alteration and fluxes of dissolved organic matter and nutrients in coastal bays. Estuar. Coast. Shelf Sci. 2020, 245, 106992. [Google Scholar] [CrossRef]
  30. Gonzalez-Martinez, A.; Rodriguez-Sanchez, A.; Garcia-Ruiz, M.J.; Palazon, B.M.; Cortes-Lorenzo, C.; Osorio, F.; Vahala, R. Performance and bacterial community dynamics of a CANON bioreactor acclimated from high to low operational temperatures. Chem. Eng. J. 2016, 287, 557–567. [Google Scholar] [CrossRef]
  31. Tortosa, G.; Correa, D.; Sánchez-Raya, A.J.; Delgado, A.; Sánchez-Monedero, M.A.; Bedmar, E.J. Effects of nitrate contamination and seasonal variation on the denitrification and greenhouse gas production in La Rocina Stream (Doñana National Park, SW Spain). Ecol. Eng. 2011, 37, 539–548. [Google Scholar] [CrossRef] [Green Version]
  32. Castellano-Hinojosa, A.; Correa-Galeote, D.; Carrillo, P.; Bedmar, E.J.; Medina-Sánchez, J.M. Denitrification and Biodiversity of Denitrifiers in a High-Mountain Mediterranean Lake. Front. Microbiol. 2017, 8, 1911. [Google Scholar] [CrossRef] [Green Version]
  33. Yoshinari, T.; Knowles, R. Acetylene inhibition of nitrous oxide reduction by denitrifying bacteria. Biochem. Biophys. Res. Commun. 1976, 69, 705–710. [Google Scholar] [CrossRef]
  34. Correa-Galeote, D.; Tortosa, G.; Bedmar, E.J. Quantification of functional microbial nitrogen cycle genes in environmental samples. In Metagenomics of the Microbial Nitrogen Cycle: Theory, Methods and Applications; Caister Academic Press: Norwich, UK, 2014; pp. 65–85. [Google Scholar]
  35. Takahashi, S.; Tomita, J.; Nishioka, K.; Hisada, T.; Nishijima, M. Development of a Prokaryotic Universal Primer for Simultaneous Analysis of Bacteria and Archaea Using Next-Generation Sequencing. PLoS ONE 2014, 9, e105592. [Google Scholar] [CrossRef] [Green Version]
  36. Callahan, B.J.; McMurdie, P.J.; Rosen, M.J.; Han, A.W.; Johnson, A.J.A.; Holmes, S.P. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 2016, 13, 581–583. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Castellano-Hinojosa, A.; Strauss, S.L. Insights into the taxonomic and functional characterization of agricultural crop core rhizobiomes and their potential microbial drivers. Sci. Rep. 2021, 11, 10068. [Google Scholar] [CrossRef]
  38. Quast, C.; Pruesse, E.; Yilmaz, P.; Gerken, J.; Schweer, T.; Yarza, P.; Peplies, J.; Glöckner, F.O. The SILVA Ribosomal RNA Gene Database Project: Improved Data Processing and Web-Based Tools. Nucleic Acids Res. 2013, 41, D590–D596. [Google Scholar] [CrossRef] [PubMed]
  39. Bolyen, E.; Rideout, J.R.; Dillon, M.R.; Bokulich, N.A.; Abnet, C.; Al-Ghalith, G.A.; Alexander, H.; Alm, E.J.; Arumugam, M.; Asnicar, F. QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science. PeerJ Prepr. 2018, 6, e27295v1. [Google Scholar] [CrossRef]
  40. McMurdie, P.J.; Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 2013, 8, e61217. [Google Scholar] [CrossRef] [Green Version]
  41. Warnes, M.G.R.; Bolker, B.; Bonebakker, L.; Gentleman, R.; Huber, W. Package ‘gplots’. Various R Programming Tools for Plotting Data. 2016. Available online: https://cran.microsoft.com/snapshot/2016-03-30/web/packages/gplots/gplots.pdf (accessed on 15 October 2022).
  42. Lepš, J.; Šmilauer, P. Multivariate Analysis of Ecological Data Using CANOCO; Cambridge University Press: Cambridge, UK, 2003. [Google Scholar]
  43. Castellano-Hinojosa, A.; Correa-Galeote, D.; González-López, J.; Bedmar, E.J. Effect of nitrogen fertilisers on nitrous oxide emission, nitrifier and denitrifier abundance and bacterial diversity in closed ecological systems. Appl. Soil Ecol. 2020, 145, 103380. [Google Scholar] [CrossRef]
  44. Chen, N.; Wu, J.; Zhou, X.; Chen, Z.; Lu, T. Riverine N2O production, emissions and export from a region dominated by agriculture in Southeast Asia (Jiulong River). Agric. Ecosyst. Environ. 2015, 208, 37–47. [Google Scholar] [CrossRef]
  45. Lin, J.; Chen, N.; Yuan, X.; Tian, Q.; Hu, A.; Zheng, Y. Impacts of human disturbance on the biogeochemical nitrogen cycle in a subtropical river system revealed by nitrifier and denitrifier genes. Sci. Total. Environ. 2020, 746, 141139. [Google Scholar] [CrossRef]
  46. Ruiz, F.; Abad, M.; Olías, M.; Galán, E.; González, I.; Aguilá, E.; Hamoumi, N.; Pulido, I.; Cantano, M. The present environmental scenario of the Nador Lagoon (Morocco). Environ. Res. 2006, 102, 215–229. [Google Scholar] [CrossRef]
  47. Aknaf, A.; Akodad, M.; Moumen, A.; Chekroun, K.B.; Elhamouti, C.; Bailal, A.; Baghour, M. Impact of the new pass on the eutrophication of the lagoon Marchica: Study of the two sites Bou Areg and Mohandis. J. Mater. Environ. Sci. 2015, 6, 2939–2943. [Google Scholar]
  48. Mostarih, M.M.M.; Madani, F.E.; Ali, H.S. Evaluation physico-chimique de la qualité de l’eau de la lagune de Nador-Nord du Maroc oriental après l’ouverture de la nouvelle passe. J. Mater. Environ. Sci. 2016, 7, 4795–5809. [Google Scholar]
  49. Zhang, H.-H.; He, P.-J.; Shao, L.-M. Ammonia volatilization, N2O and CO2 emissions from landfill leachate-irrigated soils. Waste Manag. 2010, 30, 119–124. [Google Scholar] [CrossRef] [PubMed]
  50. Yao, X.; Zhang, L.; Zhang, Y.; Xu, H.; Jiang, X. Denitrification occurring on suspended sediment in a large, shallow, subtropical lake (Poyang Lake, China). Environ. Pollut. 2016, 219, 501–511. [Google Scholar] [CrossRef]
  51. Palacin-Lizarbe, C.; Camarero, L.; Hallin, S.; Jones, C.M.; Cáliz, J.; Casamayor, E.O.; Catalan, J. The DNRA-Denitrification Dichotomy Differentiates Nitrogen Transformation Pathways in Mountain Lake Benthic Habitats. Front. Microbiol. 2019, 10, 1229. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Hink, L.; Gubry-Rangin, C.; Nicol, G.W.; Prosser, J.I. The consequences of niche and physiological differentiation of archaeal and bacterial ammonia oxidisers for nitrous oxide emissions. ISME J. 2018, 12, 1084–1093. [Google Scholar] [CrossRef] [Green Version]
  53. Liu, J.; Zhu, S.; Liu, X.; Yao, P.; Ge, T.; Zhang, X.-H. Spatiotemporal dynamics of the archaeal community in coastal sediments: Assembly process and co-occurrence relationship. ISME J. 2020, 14, 1463–1478. [Google Scholar] [CrossRef] [Green Version]
  54. Hug, L.A.; Castelle, C.J.; Wrighton, K.C.; Thomas, B.C.; Sharon, I.; Frischkorn, K.R.; Williams, K.H.; Tringe, S.G.; Banfield, J.F. Community genomic analyses constrain the distribution of metabolic traits across the Chloroflexi phylum and indicate roles in sediment carbon cycling. Microbiome 2013, 1, 22. [Google Scholar] [CrossRef] [Green Version]
  55. Castelle, C.J.; Wrighton, K.C.; Thomas, B.C.; Hug, L.A.; Brown, C.T.; Wilkins, M.J.; Frischkorn, K.R.; Tringe, S.G.; Singh, A.; Markillie, L.M.; et al. Genomic Expansion of Domain Archaea Highlights Roles for Organisms from New Phyla in Anaerobic Carbon Cycling. Curr. Biol. 2015, 25, 690–701. [Google Scholar] [CrossRef] [Green Version]
  56. Baxter, A.M.; Johnson, L.; Edgerton, J.; Royer, T.; Leff, L.G. Structure and function of denitrifying bacterial assemblages in low-order Indiana streams. Freshw. Sci. 2012, 31, 304–317. [Google Scholar] [CrossRef]
  57. Wang, C.; Liu, D.; Bai, E. Decreasing soil microbial diversity is associated with decreasing microbial biomass under nitrogen addition. Soil Biol. Biochem. 2018, 120, 126–133. [Google Scholar] [CrossRef]
  58. Castellano-Hinojosa, A.; Strauss, S.L.; González-López, J.; Bedmar, E.J. Changes in the diversity and predicted functional composition of the bulk and rhizosphere soil bacterial microbiomes of tomato and common bean after inorganic N-fertilization. Rhizosphere 2021, 18, 100362. [Google Scholar] [CrossRef]
  59. Pavloudi, C.; Oulas, A.; Vasileiadou, K.; Sarropoulou, E.; Kotoulas, G.; Arvanitidis, C. Salinity is the major factor influencing the sediment bacterial communities in a Mediterranean lagoonal complex (Amvrakikos Gulf, Ionian Sea). Mar. Genom. 2016, 28, 71–81. [Google Scholar] [CrossRef] [PubMed]
  60. Ben Salem, F.; Ben Said, O.; Cravo-Laureau, C.; Mahmoudi, E.; Bru, N.; Monperrus, M.; Duran, R. Bacterial community assemblages in sediments under high anthropogenic pressure at Ichkeul Lake/Bizerte Lagoon hydrological system, Tunisia. Environ. Pollut. 2019, 252, 644–656. [Google Scholar] [CrossRef] [PubMed]
  61. Bourhane, Z.; Lanzén, A.; Cagnon, C.; Ben Said, O.; Mahmoudi, E.; Coulon, F.; Atai, E.; Borja, A.; Cravo-Laureau, C.; Duran, R. Microbial diversity alteration reveals biomarkers of contamination in soil-river-lake continuum. J. Hazard. Mater. 2022, 421, 126789. [Google Scholar] [CrossRef] [PubMed]
  62. Manh, H.D.; Matsuo, Y.; Katsuta, A.; Matsuda, S.; Shizuri, Y.; Kasai, H. Robiginitalea myxolifaciens sp. nov., a novel myxol-producing bacterium isolated from marine sediment, and emended description of the genus Robiginitalea. Int. J. Syst. Evol. Microbiol. 2008, 58, 1660–1664. [Google Scholar] [CrossRef] [PubMed]
  63. Jung, J.; Choi, S.; Jung, H.; Scow, K.M.; Park, W. Primers for amplification of nitrous oxide reductase genes associated with Firmicutes and Bacteroidetes in organic-compound-rich soils. Microbiology 2013, 159, 307–315. [Google Scholar] [CrossRef] [Green Version]
  64. Cho, J.-C.; Giovannoni, S.J. Robiginitalea biformata gen. nov., sp. nov., a novel marine bacterium in the family Flavobacteriaceae with a higher G+C content. Int. J. Syst. Evol. Microbiol. 2004, 54, 1101–1106. [Google Scholar] [CrossRef] [Green Version]
  65. Sanford, R.A.; Wagner, D.D.; Wu, Q.; Chee-Sanford, J.C.; Thomas, S.H.; Cruz-García, C.; Rodríguez, G.; Massol-Deyá, A.; Krishnani, K.K.; Ritalahti, K.M.; et al. Unexpected nondenitrifier nitrous oxide reductase gene diversity and abundance in soils. Proc. Natl. Acad. Sci. USA 2012, 109, 19709–19714. [Google Scholar] [CrossRef] [Green Version]
  66. Mania, D.; Heylen, K.; van Spanning, R.J.M.; Frostegård, Å. The nitrate-ammonifying and nosZ-carrying bacterium Bacillus vireti is a potent source and sink for nitric and nitrous oxide under high nitrate conditions. Environ. Microbiol. 2014, 16, 3196–3210. [Google Scholar] [CrossRef]
  67. Van Grinsven, S.; Damsté, J.S.S.; Villanueva, L. Assessing the Effect of Humic Substances and Fe(III) as Potential Electron Acceptors for Anaerobic Methane Oxidation in a Marine Anoxic System. Microorganisms 2020, 8, 1288. [Google Scholar] [CrossRef]
  68. Muyzer, G.; De Waal, E.C.; Uitterlinden, A.G. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 1993, 59, 695–700. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Ochsenreiter, T.; Selezi, D.; Quaiser, A.; Bonch-Osmolovskaya, L.; Schleper, C. Diversity and abundance of Crenarchaeota in terrestrial habitats studied by 16S RNA surveys and real time PCR. Environ. Microbiol. 2003, 5, 787–797. [Google Scholar] [CrossRef] [PubMed]
  70. Rotthauwe, J.H.; Witzel, K.P.; Liesack, W. The ammonia monooxygenase structural gene amoA as a functional marker: Molecular fine-scale analysis of natural ammonia-oxidizing populations. Appl. Environ. Microbiol. 1997, 63, 4704–4712. [Google Scholar] [CrossRef] [Green Version]
  71. Tourna, M.; Freitag, T.E.; Nicol, G.W.; Prosser, J.I. Growth, activity and temperature responses of ammonia-oxidizing archaea and bacteria in soil microcosms. Environ. Microbiol. 2008, 10, 1357–1364. [Google Scholar] [CrossRef]
  72. Bru, D.; Sarr, A.; Philippot, L. Relative abundance of the membrane bound and periplasmic nitrate reductase. Appl. Environ. Microbiol. 2007, 73, 5971–5974. [Google Scholar] [CrossRef] [Green Version]
  73. Henry, S.; Baudouin, E.; López-Gutiérrez, J.C.; Martin-Laurent, F.; Brauman, A.; Philippot, L. Quantification of denitrifying bacteria in soils by nirK gene targeted real-time PCR. J. Microbiol. Methods. 2004, 59, 327–335. [Google Scholar] [CrossRef] [PubMed]
  74. Throbäck, I.N.; Enwall, K.; Jarvis, Å.; Hallin, S. Reassessing PCR primers targeting nirS, nirK and nosZ genes for community surveys of denitrifying bacteria with DGGE. FEMS Microbiol. Ecol. 2004, 49, 401–417. [Google Scholar] [CrossRef]
  75. Braker, G.; Tiedje, J.M. Nitric oxide reductase (norB) genes from pure cultures and environmental samples. Appl. Environ. Microbiol. 2003, 69, 3476–3483. [Google Scholar] [CrossRef] [Green Version]
  76. Henry, S.; Bru, D.; Stres, B.; Hallet, S.; Philippot, L. Quantitative detection of the nosZ gene, encoding nitrous oxide reductase, and comparison of the abundances of 16S rRNA, narG, nirK, and nosZ genes in soils. Appl. Environ. Microbiol. 2006, 72, 5181–5189. [Google Scholar] [CrossRef] [Green Version]
  77. Jones, C.M.; Graf, D.R.H.; Bru, D.; Philippot, L.; Hallin, S. The unaccounted yet abundant nitrous oxide-reducing microbial community: A potential nitrous oxide sink. ISME J. 2013, 7, 417–426. [Google Scholar] [CrossRef] [PubMed] [Green Version]
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Figure 1. Geographical situation of the Marchica lagoon (Nador, Morocco). S1–S6 represent the locations of the sampling sites where the sediments were collected. Sites S1, S4, and S5 receive mainly urban wastewaters; S2 collects waters of agricultural precedence; S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin. The map was generated using Google Maps.
Figure 1. Geographical situation of the Marchica lagoon (Nador, Morocco). S1–S6 represent the locations of the sampling sites where the sediments were collected. Sites S1, S4, and S5 receive mainly urban wastewaters; S2 collects waters of agricultural precedence; S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin. The map was generated using Google Maps.
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Figure 2. Urease (A), acid phosphatase (B), arylsulphatase (C), and β-glucosidase (D) activities in sediments of the Marchica lagoon. Sites S1, S4, and S5 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; site S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin. Different letters above the bars denote statistical differences according to the Kruskal–Wallis and Conover-Iman tests (n = 4; p < 0.05). Values are expressed as means with standard errors.
Figure 2. Urease (A), acid phosphatase (B), arylsulphatase (C), and β-glucosidase (D) activities in sediments of the Marchica lagoon. Sites S1, S4, and S5 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; site S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin. Different letters above the bars denote statistical differences according to the Kruskal–Wallis and Conover-Iman tests (n = 4; p < 0.05). Values are expressed as means with standard errors.
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Figure 3. Total abundance of bacterial (16SB) (A), archaeal (16SA) (B), 16S rRNA, amoA AOB (C), amoA AOA (D), napA (E), narG (F), nirK (G), nirS (H), and nosZI (I) genes in the sediments of the Marchica lagoon. Different letters above the bars denote statistical differences according to the Kruskal–Wallis and Conover-Iman tests (n = 4; p < 0.05). Sites S1, S4, and S5 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; site S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin. Values are expressed as means with standard errors.
Figure 3. Total abundance of bacterial (16SB) (A), archaeal (16SA) (B), 16S rRNA, amoA AOB (C), amoA AOA (D), napA (E), narG (F), nirK (G), nirS (H), and nosZI (I) genes in the sediments of the Marchica lagoon. Different letters above the bars denote statistical differences according to the Kruskal–Wallis and Conover-Iman tests (n = 4; p < 0.05). Sites S1, S4, and S5 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; site S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin. Values are expressed as means with standard errors.
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Figure 4. Redundancy analysis (RDA, triplot) including the total abundance of the 16SB, 16SA, amoA AOB, amoA AOA, napA, narG, nirK, nirS, and nosZI genes, the sediment physicochemical properties NH4+, NO3−, TN (total nitrogen), TC (total carbon), and TOC (total organic carbon), and N2O emissions in sediments of the Marchica lagoon. Sites S1, S4, and S5 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; site S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin.
Figure 4. Redundancy analysis (RDA, triplot) including the total abundance of the 16SB, 16SA, amoA AOB, amoA AOA, napA, narG, nirK, nirS, and nosZI genes, the sediment physicochemical properties NH4+, NO3−, TN (total nitrogen), TC (total carbon), and TOC (total organic carbon), and N2O emissions in sediments of the Marchica lagoon. Sites S1, S4, and S5 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; site S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin.
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Figure 5. (A) Number of observed ASVs and values of the Shannon and inverse Simpson diversity indices of the bacterial community in sediments of the Marchica lagoon. Different letters above the bars indicate significant differences between treatments (Tukey′s HSD, p < 0.05). Values are expressed as the mean with a standard error. (B) Principal coordinates analysis (PCoA) plots on Bray–Curtis distances for the bacterial community. Differences in community composition between sites were tested by PERMANOVA analysis, and p values < 0.01 were considered significant. Sites S1 and S4 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; and site S3 those of industrial wastewaters.
Figure 5. (A) Number of observed ASVs and values of the Shannon and inverse Simpson diversity indices of the bacterial community in sediments of the Marchica lagoon. Different letters above the bars indicate significant differences between treatments (Tukey′s HSD, p < 0.05). Values are expressed as the mean with a standard error. (B) Principal coordinates analysis (PCoA) plots on Bray–Curtis distances for the bacterial community. Differences in community composition between sites were tested by PERMANOVA analysis, and p values < 0.01 were considered significant. Sites S1 and S4 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; and site S3 those of industrial wastewaters.
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Figure 6. A distance-based Redundancy Analysis (db-RDA) analysis of the bacterial community based on Bray–Curtis distances and the sediment physicochemical properties (NH4+, NO3−, TN, TC, and TOC). The correlation of the canonical axes with the explanatory matrix of the physicochemical properties of the sediment was determined by the general permutation test (p < 0.001). Sites S1 and S4 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; and site S3 those of industrial wastewaters.
Figure 6. A distance-based Redundancy Analysis (db-RDA) analysis of the bacterial community based on Bray–Curtis distances and the sediment physicochemical properties (NH4+, NO3−, TN, TC, and TOC). The correlation of the canonical axes with the explanatory matrix of the physicochemical properties of the sediment was determined by the general permutation test (p < 0.001). Sites S1 and S4 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; and site S3 those of industrial wastewaters.
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Table
Table 1. Values of pH and content of ammonium (NH4+), nitrate (NO3−), total carbon (TC), total nitrogen (TN), and total organic carbon (TOC) in the sediments of the Marchica lagoon.
Table 1. Values of pH and content of ammonium (NH4+), nitrate (NO3−), total carbon (TC), total nitrogen (TN), and total organic carbon (TOC) in the sediments of the Marchica lagoon.
SitepHNH4+ (mg/L)NO3− (mg/L)TN (mg/g)TC (mg/g)TOC (mg/L)
S18.012.53 ± 0.93 a4.43 ± 1.46 e0.44 ± 0.17 c24.00 ± 2.95 a3.48 ± 0.76 c
S27.162.60 ± 1.20 a10.07 ± 1.15 d0.37 ± 0.12 c17.00 ± 6.19 a3.47 ± 1.17 c
S37.202.73 ± 2.17 a41.87 ± 9.02 a0.30 ± 0.09 c18.20 ± 3.69 a3.29 ± 1.28 c
S47.513.63 ± 1.62 a23.17 ± 1.74 b0.11 ± 0.02 d8.17 ± 1.12 b1.07 ± 0.13 d
S57.082.73 ± 0.86 a45.90 ± 6.56 a1.21 ± 0.30 b19.57 ± 3.55 a10.85 ± 1.16 b
S67.174.20 ± 1.93 a18.40 ± 1.85 c1.87 ± 0.16 a19.63 ± 2.75 a16.27 ± 2.84 a
Note: Sites S1, S4, and S5 receive mainly urban wastewaters; S2 collects waters of agricultural precedence; S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin. For each soil column, values followed by the same letter are not statistically different according to the Kruskal–Wallis and Conover-Iman tests (n = 4; p < 0.05). Values are expressed as means with standard errors.
Table
Table 2. Nitrous oxide (N2O) emissions by sediments of the Marchica lagoon. The values represent the mean ± standard error of six replicates.
Table 2. Nitrous oxide (N2O) emissions by sediments of the Marchica lagoon. The values represent the mean ± standard error of six replicates.
SiteNmol N2O/g Dry Sediment × h
S15.3 ± 1.9 d
S27.7 ± 1.7 d
S362.1 ± 4.8 a
S411.4 ± 2.6 c
S528.3 ± 2.4 b
S611.6 ± 2.1 c
Note: Sites S1, S4, and S5 receive mainly urban wastewaters; site S2 collects waters of agricultural precedence; site S3 those of industrial wastewaters; and those of site S6 are predominantly of domestic origin. Values followed by the same lowercase are not statistically different according to the Kruskal–Wallis and Conover-Iman tests (n = 4; p < 0.05). Values are expressed as means with standard errors.
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El Hamouti, C.; Castellano-Hinojosa, A.; Mabrouki, Y.; Chaouni, B.; Ghazal, H.; Boukhatem, N.; Chahboune, R.; Bedmar, E.J. Anthropogenic Nitrate Contamination Impacts Nitrous Oxide Emissions and Microbial Communities in the Marchica Lagoon (Morocco). Sustainability 2023, 15, 4077. https://doi.org/10.3390/su15054077

AMA Style

El Hamouti C, Castellano-Hinojosa A, Mabrouki Y, Chaouni B, Ghazal H, Boukhatem N, Chahboune R, Bedmar EJ. Anthropogenic Nitrate Contamination Impacts Nitrous Oxide Emissions and Microbial Communities in the Marchica Lagoon (Morocco). Sustainability. 2023; 15(5):4077. https://doi.org/10.3390/su15054077

Chicago/Turabian Style

El Hamouti, Chahrazade, Antonio Castellano-Hinojosa, Youness Mabrouki, Bouchra Chaouni, Hassan Ghazal, Noureddine Boukhatem, Rajaa Chahboune, and Eulogio J. Bedmar. 2023. "Anthropogenic Nitrate Contamination Impacts Nitrous Oxide Emissions and Microbial Communities in the Marchica Lagoon (Morocco)" Sustainability 15, no. 5: 4077. https://doi.org/10.3390/su15054077

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