Aquatic ecosystems serve as reservoirs of terrestrial and anthropogenic-C accumulation. Carbon enrichment interacts with site-specific conditions, including occurrence of other contaminants. Thus, the rate of decomposition vis-à-vis CO2 emission varies subject to the nature of C-source and site-specific conditions, for instance presence of other contaminants. Anthropogenic input of carbon is often accompanied by a large supply of nutrient and non-nutrient contaminants (Smith and Schindler 2009). Thus, the fate of carbon in such water bodies can be strongly influenced by the interaction of multiple pollutants. For instance, nutrient supply, chiefly N and P, can gear-up autochthonous C- build-up and decomposition, whereas metal enrichment can provide countervailing effect. Thus, the complex interactions, especially those pertaining to countervailing effect deserve scaled-up studies from a climate change perspective; and for understanding ecosystem level effects of heavy metal pollution. Land-water interface (LWI) of large rivers provides heterogeneous habitats with imprints of riverine metabolism (Jaiswal and Pandey 2019). Here, we consider LWI to study C-metabolism and CO2 emission as regulated by C- enrichment and metal-driven countervailing effects. This has concern because sewage sources alone add 110 Gg of TOC, 13.28 Gg DIN and 5.29 Gg of DRP annually into the Ganga River. In addition, the basin receives about 1.81 Tg, 2.77 Tg and 0.13 Tg of TOC, TIN, and P, respectively, through atmospheric deposition annually (Singh and Pandey 2018).
The CO2 emission reported here was significantly lower than those reported for a freshwater marsh (1456.60 ± 593.31 mg m-2 hr-1) and a brackish water marsh (1435.23 ± 689.71 mg m-2 hr-1) in the Min River estuary, Southeastern China (Hu et al. 2017). Sediment with favorable conditions tends to be substrate limited, and show high in situ activities and low organic matter accumulation. In contrast, sediments with stress conditions, are activity limited, and show low in situ activities, promoting carbon storage (Sinsabaugh 2010). Also, the enzyme activity limited systems contribute to organic matter accumulation (Freeman et al. 2001; 2004). Earlier research shows that carbon quality and particle size distribution is an important regulator of microbial biomass distribution (Sinsabaugh and Findlay 1995). Small particle size support high concentration of TOC and TN, with concentrations generally high in clay, although the C:N ratio declines with diminishing particle size (Stemmer et al. 1998). The downstream sites- Sngm and Asdr, are rich in WSOC, TOC and TN concentrations and also have high percentage of clay and silt at mouth of the drain. High substrate availability coupled with high percentage of silt and clay may invite the colonization of a large microbial population and create a suitable room for high microbial/enzyme activities that trigger CO2 emission.
Here we identified, in addition to other variables, two major determinants-chemical recalcitrance and heavy metal enrichment, to address changes in microbial extracellular enzyme (EE) activities vis-à-vis CO2 emission along the river gradient. Microbial EEs mediate decomposition and mineralization of organic matter (OM), and terrestrially-derived OM often shows recalcitrance to degradation (Sinsabaugh 2010; Ward et al. 2013). Terrestrially derived OM, rich in leaf litter, are generally poor in N content (high C:N ratio) and are poorly decomposable relative to autochthonous C. Lignin and cellulose constitutes the most abundant C fractions on land (Boerjan et al. 2003). Lignin accounts about 30% of organic-C in the terrestrial C reservoir (Boerjan et al. 2003), and ̴55% of land sequestered lignin is degraded in the river continuum (Malhi et al. 2008; Bose et al. 2009; Houghton et al. 2001). Roughly 80 Tg C in the Amazon terrestrial biosphere is fixed as lignin each year (Mayorga et al. 2005; Ward et al. 2013). Sites with chemical recalcitrance-measured in terms of phenol/phenol oxidase activity-a signature of terrestrially-derived OC; and those rich in metal pollutants showed mismatch in CO2 emission rates and C-inputs. Phenol oxidase is one of the key enzymes able to degrade recalcitrant phenolic materials such as lignin (McLatchey and Reddy 1998). Phenolic materials are highly inhibitory to enzymes and their lower abundance at some sites allowed higher hydrolase activities. Sites- Stmh and Adpr, with high amount of terrestrially derived organic matter showed highest phenol concentration and high C:N ratio and CO2 emission rates were not comparable to C inputs. The downstream sites- Sngm and Rjht, with easily utilizable soft carbon, added from sewage for instance, showed less activity of phenol oxidase, but high activity of β-D-glucosidase. Sites with high concentration of Chl a, (high autochthonous organic C) did show low phenol oxidase activity and high activity of β-D-glucosidase. The C:N ratio, a proxy of decomposability (Datry et al. 2018), was recorded lowest at highly productive site (Sngm). At the mouth of both the point sources (Asdr; Rmdr), the phenol oxidase activity was found to be the lowest which increased with upstream and downstream trajectories. Pandey and Yadav 2017 reported very low levels of DO close to the mouth of Assi drain. Thus, low amount of land-derived OC coupled with oxygen deficiency could decrease phenol oxidase activity, whereas the activity of hydrolases remained relatively higher even in an anaerobic environment (Lee et al. 1999). We also tested alkaline phosphatase (AP), an ectoenzyme of microbial origin, used as a measure of P status in soil and sediment (Sayler et al. 1979; Johnson et al. 1998; Sinsabaugh et al. 2009). The AP showed a trend similar to phenol oxidase, whereas sediment-SRP showed an opposite trend in the main stem as well as along point sources. Also, the sites with low productivity have high AP and phenol oxidase activities. Overall, these two enzymes can be used as an indicator of less polluted and low CO2 emission sites; whereas, high activities of other enzymes indicate sites acting as a hot spot of CO2 emission.
We further tested, whether heavy metal enrichment was able to reduce EEs activities and CO2 emission in the main stem and source orientated sites. The countervailing effect of heavy metals at Rjht and Rmdr reduced CO2 emission. The NMDS separated microbial biomass, EE activity, Chl a biomass and CO2 emission in one group between the Sngm and Rmna (Fig. 7). Asdr also showed the similar pattern (Fig. 8), whereas Rmdr the NMDS showed that the microbial activity maximum at the downstream sites (Fig. 9).The granulometry and organic matter content affect the distribution of heavy metal (Farkas et al. 2009). Fine grained sediments tend to have relatively higher metal contents due in part to high specific surface of particles (Rubio et al. 2000). Positive correlations among metals, organic substrate and sediment particle size validate this concept. A higher proportion of fine sized particles lead easy transportation of the sediment downstream (Bartoli et al. 2012). Accordingly, the river sites down the industrial- and the urban areas were significantly more polluted than upstream sites. The Rjht and Rmdr Sites showed carbon storage in bed sediment. Despite high substrate availability, there were relatively lower in situ microbial/enzymetic activities. Many investigators have reported that heavy metal stressors can induce change in the microbial biomass and activity (Khas et al. 1998; Jaiswal and Pandey 2018). The microorganisms release extracellular enzymes (EEs) to activate the lysis of organic matter (Romaní et al. 2004). The EEs are produced as a result of cellular metabolism influenced by carbon and nutrient availability. The EEs are highly sensitive towards toxicants, including heavy metals, and respond sharply to even after small changes in sediment quality (Pandey and Yadav 2017; Jaiswal and Pandey 2018; Verma and Pandey 2019). The Rjht Site at the main river stem and the sites located downstream of Rmdr showed high concentrations of total heavy metals, nutrients, TOC and high C:N ratios. Despite high TOC, an important resource/ substrate for microbial activity, reduced microbial biomass and enzyme activity at these sites indicated that, when metal concentrations exceed certain level (here, ∑THM > 337.4 µg g-1), the carbon favored microbial activity declines (Jaiswal and Pandey 2019).
Nutrient supply stimulates microbial activity and decomposition of organic matter, and under appropriate temperature and water conditions, leads to high respiration and CO2 emission (Liu et al. 2009). We found significant positive correlations between C availability and CO2 emission at Asdr. However, at metal rich locations, this relationship implied up to certain levels only. As the concentration of metal increased, this relationship gone weaker. It seems that the microbial activities, and consequently the CO2 release at LWI, are constrained by high concentration of toxic metals. Previous studies support these observations (Jaiswal and Pandey 2019). At Rmdr, the CO2 emission was found to be low at drain mouth followed by an increasing trend indicating that metal stressors inhibit enzyme activities, and thereby , the emission of CO2. At Asdr, the enzyme activities and emission of CO2 showed a response almost synchronous to changes in the concentration of organic carbon. The C rich sites, characterized by faster rates of CO2 emission, did show high activity of FDAase and β-D-glucosidase. The FDAase is used as a proxy of total microbial activity and organic matter turnover (Schnurere and Rosswall 1982), whereas the β-D-glucosidase is responsible for the hydrolysis of glycosidic bonds and used as marker of C acquisition (Sinsabaugh et al. 2009). The metal concentrations at Asdr did not appear high enough to induce inhibitory effects. On the contrary, the Rmdr Sites showed metal concentrations high enough to suppress enzyme activities, and consequently, the CO2 emission. The carbon as a substrate stimulates EE activity while metal stressors can suppress it. However, under high concentrations of C and metals, the inhibition by the latter might counterbalance the substrate (carbon and nutrient)-driven stimulatory effects (Jaiswal and Pandey 2018). The dynamic fit model (Fig. 4) showed that total metal concentration above 337.4 μg g-1 induce adverse effects on CO2 emission. In all the three subsets of studies, PCA separated metals opposite to CO2 emission and microbial/enzyme activities. The NMDS yielded almost similar results. The Asdr Site showed low level of total heavy metal (ΣTHM < 337.4 µg g-1), with microbial activities relatively higher and consequently the excess supply of C could assume importance triggering CO2 emission. Previous studies have shown a marked decrease in Cmic and enzymes activities in metal polluted soils and sediments (Abaye et al. 2005; Li et al. 2009). We found significant positive relationships between qCO2 and metal concentrations. Earlier studies show that Cmic declines and qCO2 increases as metal concentration increases (Liu et al. 2012). Metal-associated changes in C-utilization have been considered as a microbial response to stressors and are used as an indicator of metal pollution (Brookes 1995). Overall, the patterns of CO2 emission shown here demonstrate that the distribution of co-occurrence of metal and C-sources ultimately regulate the pattern of carbon sequestration in the Ganga River. Similar spatial trajectories can be expected for other human-impacted rivers suggesting the need of caution for regional C-budgeting and modeling.