Philippa Kaur

arising from J. Cheng et al. Nature Communications https://doi.org/10.1038/s41467-021-22087-2 (2021)Recently, Cheng J. et al.1 cited and simulated the relative percentage tree cover to interpret the ~3000–4000 years lag between tree cover and East Asian Summer Monsoon (EASM) rainfall. They concluded that vegetation feedback has caused a lagged ecosystem response to EASM rainfall during the Holocene (11.7–0 ka). Here, we question the feasibility of using the relative percentage tree cover to measure vegetation feedback to climate. First, the land cover in northern China includes forests, grasslands, and bare land2. Cheng J. et al.1 did not consider the role of bare land in climate feedback models. Absolute land cover, including forest, grassland, and bare land can accurately reveal feedback to climate3. Second, the biome reconstructions they cited represent changes in vegetation type only, whereas the relationship between vegetation type and vegetation cover is altered by many other factors3,4,5. Third, the paper they cited6 averaged the vegetation types on a millennium scale with an interval of 1000 years, so the view that vegetation has a ~3000–4000 years lag in EASM rainfall is not credible as the lag can be enlarged by data resolution. Therefore, absolute vegetation cover, not relative cover, is a prerequisite for studying ecosystem feedback.Our previous work3 was the first to reconstruct the absolute vegetation cover in northern China based on pollen concentrations in two well-dated sediment cores. Using a random forest method, the vegetation cover at Dali Lake in the forest-steppe transition in northern China was determined for the period from 19,000 cal. yr BP to the present with a resolution of approximately 200 years. Han et al.3 showed that tree cover peaked during the early Holocene and it has gradually declined since the middle Holocene. Pollen percentages are widely used in vegetation reconstruction, but they are challenging to analyze because they can be similar in composition, despite being produced by very different flora7,8. This means they represent the relative fractions of vegetation type and not the absolute vegetation cover (Fig. 1A, B). Han et al.3 suggested that pollen concentration data are suitable for the reconstruction of absolute vegetation cover, particularly in arid and semi-arid regions. Dali Lake represents a typical lake in the semi-arid area of northern China. The random forest model showed that the area had a high tree cover during the early Holocene, which suggests that tree cover was a timely response to Holocene monsoon rainfall and there was no time lag at this specific location. Therefore, the data at Dali Lake challenge the conclusion that tree cover has a ~3000–4000 years lag to EASM rainfall.Fig. 1: Trends in pollen percentage, absolute vegetation cover and fire history during the Holocene at Dali Lake, a typical lake in the semi-arid area of northern China.Changes in the percentages of arboreal and non-arboreal pollen (A)3. Reconstructed absolute tree and grass cover (B)3, with gray, yellow, and green shaded areas indicating the standard deviation of 1000 random forest model results for total cover, grass cover, and tree cover, respectively. Normalized fire activity index in the northern region of eastern monsoonal China (C)10. Z-score of transformed charcoal value showing fire activity trend in the temperate steppe of northern China (D)11.Full size imageMoreover, Cheng J. et al.1 used −17 °C as the threshold for tree and grass transition, but this could be an incorrect citation from Bonan et al.9. In the original text by Bonan et al.9, they showed that both temperate deciduous broadleaved trees and C3 grasses have a tolerance of −17 °C for the coldest month for their survival, but this temperature is not the favored threshold for the shift from grasses to trees. Actually, the trend in absolute vegetation cover was mainly driven by summer temperature, annual precipitation, and fire incidents, which is in line with the vegetation-climate relationships at Dali Lake3. That is, higher monsoon rainfall could increase the competitiveness of trees, while increased fire could increase the competitiveness of grasses as grasses are mostly annual and perennial, and they renew faster than trees after a fire. Between 10,000 and 8000 cal. yr BP, monsoon rainfall peaked and there were relatively few fires, which led to a significant increase in absolute tree cover. Since 6500 cal. yr BP, monsoon rainfall decreased and fire increased, resulting in stronger competition by grasses, which has led to an increased grass cover and reduced tree cover3 (Fig. 1B).The impact of secondary disturbances on vegetation dynamics requires careful consideration, particularly the impact of fires on vegetation cover in semi-arid areas of China, even though vegetation growth is strongly constrained by rainfall in this region. Both the normalized fire index in the northern region of eastern monsoonal China10 and the charcoal value in the temperate steppe of northern China11 show a clear antiphase relationship with the absolute forest cover of the Dali Lake region (Fig. 1B, C, D). However, Cheng J. et al.1 did not discuss fire incidence on vegetation evolution in northern China. Fire has occurred frequently through the Holocene10,12 and it plays an important role in vegetation dynamics based on observational evidence13,14. Particularly, fire is considered as a triggering disturbance that can reduce a forest’s resilience to drought under a drying climate during the mid to late Holocene. For Dali Lake, fire and drying climate has co-driven the evolution of vegetation cover since 6500 cal. yr BP3. Moreover, in northern China, data from Daihai Lake and Hulun Nuur Lake also suggest that fire has accelerated the decline of forest cover and the transition from forest to grass during the Holocene13,14. Unfortunately, Cheng J. et al.1 did not discuss the effect of fire when citing and interpreting the observation data, as scale-dependent fires could make the transition between forest and grassland and their interactions variable.In summary, we believe there are three flaws in the data interpretation of Cheng J. et al.1. (1) They contradict the observed evolution of absolute tree cover at Dali Lake in northern China, which is representative of the marginal area of EASM. Relative percentage tree cover cannot accurately reflect a forest’s response and feedback to past climate change. (2) Both temperate deciduous broadleaved trees and C3 grasses have a tolerance of −17 °C for the coldest month for their survival. Thus, −17 °C is not a correct threshold for the shift from grasses to trees. (3) They contradict the ecological theories of secondary disturbance on vegetation dynamics. Fire and other secondary disturbances may be crucial to the transition between forest and grassland. Interpretations of vegetation feedback might be biased if these important factors are not fully considered. Based on the evidence, their conclusion that vegetation feedback causes lagged ecosystem response to EASM rainfall during the Holocene could be problematic. More

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Our findings indicated that mine water had a certain inhibitory effect on ryegrass seed germination, and the intensity of this inhibitory effect increased with increased mine water proportion. These effects were mainly reflected as changes in germination potential. Concretely, irrigation with mine water prolonged the germination of ryegrass seeds but had no significant effect on germination rate. Min Zhu et al. found that recycled water inhibited the seed germination of turfgrass, and this effect became more notorious when the concentration of reclaimed water increased. This was likely because the water contained salt ions, heavy metal ions, and E. coli, all of which are known to affect seed germination22. The mine water was taken from the Laohutai mining area, where the water composition and quality are good. Therefore, mine water did not significantly affect seed germination and the seeds maybe germinate normally if given sufficient time.The physiological and photosynthetic characteristics of ryegrass were impacted by the mine water, and the intensity of inhibition increased with higher mine water proportions. When the ratio of mine water to clean water reached a certain proportion (1:2, A1 and B1), the physiological and growth characteristics of ryegrass were improved to a certain extent. When only mine water was used for irrigation, the indices were significantly suppressed. In contrast, mixing clear water with mine water for irrigation promoted the physiological characteristics of the plants, as well as photosynthesis. This was likely because the mineral content of mine water is higher. However, mine water not only contains elements needed for plant growth but also some elements and ions that have inhibitory effects on plant growth. Therefore, the quality of ryegrass growth were suppressed when irrigating only with mine water. In contrast, after mixing the mine water with clean water, the concentrations of certain substances that produce adverse effects are diluted, and the mixed irrigation water promoted ryegrass growth in appropriate proportion.A certain concentration of heavy metal elements will affect the absorption of essential elements by plants and produce antagonism, and high concentration can directly lead to plant death. Heavy metal stress affects chlorophyll content through two aspects: Heavy metal destroys enzymes needed for chlorophyll synthesis, affects plant chlorophyll synthesis, and then inhibits plant photosynthesis23. The second is the destruction of chloroplast structure and cell membrane24,25,26. In the treatment of high concentrations of heavy metals, the chlorophyll content of plants is significantly reduced due to the inhibition of chlorophylase or aminolevulinic acid dehydrase, thus inhibiting plant photosynthesis27. The heavy metal threat forcing stimulates the formation of reactive oxygen species that convert fatty acids into toxic lipid peroxides, which damage to plant cells28,29,30. Heavy metal stress can induce a lot of activity in plants sexual oxygen and inhibit the normal metabolism of plants, causing membrane lipid peroxidation and increased plasma membrane permeability31, 32. Low concentration of heavy metal stress will stimulate the protective mechanism of plants, so low concentration of stimulation will not damage plants, on the contrary, may help plant growth. Heavy metal stress causes water loss in plants, and a certain amount of proline can be produced to regulate the water balance of plant cells and reduce the damage degree of plant cells33. SOD, POD and CATT are important antioxidant enzymes in plants, which can scavenge excessive free radicals. The synergistic action of three enzymes can protect plants from free radical damage. When the concentration of heavy metals was low, the activity of protective enzymes increased under the induction of reactive oxygen radicals. However, with the increase of stress degree, the activities of SOD, POD and CAT decreased, which eventually led to the persecution of plant cells34. These conclusions are consistent with the results of this paper. When mine water was mixed with clear water at a ratio of 1:2, heavy metal stress stimulated the protective mechanism of ryegrass most appropriately, and improved plant quality and resistance. On the contrary, when the proportion of mine water increased, the physiological characteristics and quality of ryegrass plants were inhibited to different degrees.Precious Nneka Amori et al. studied physiological traits of leaves and Silverbeet using treated wastewater, the results show that the biomass of plants watered with only the treated wastewater were more than 50% higher than the yield in tap water control and plants exhibited high degree of root foraging1. Libutti et al. irrigated tomato and broccoli with purified agro-industrial effluent and reported that yield and quality traits of agricultural products were not affected35. Radish was grown using a reclaimed synthetic textile wastewater treated in an anoxic-aerobic photobioreactor, and the dry weight, leaf number and leaf area of plant harvest were 49, 19.2 and 62% higher than the growth performance in freshwater irrigation36. FU et al. studied four native Chenopodiaceae plants of Halogeton glomeratus, Kochia scoparia, Suaeda glauca and Chenopodium glaucum in Jinchang area northwest China, from their changes of net photosynthetic rate (Pn), Stomatal conductance (Gs), transpiration rate (Tr). chlorophyll content (Chl), malondialdehyde (MDA), soluble protein (SP), proline (Pro) and antioxidant enzymes activity under the treatment of farmland soil (T1) and sedendary soil mixed with tailing (1:1, T2), they concluded that under T2 treatment, Pn, Gs, and Tr of Halogeton glomeratus and Kochia scoparia were decreased , the other six indexes were increased significantly. Gs, Tr, MDA, Pro, and SOD increased, yet CAT, Chl and Pn of Suaeda glauca decreased significantly, respectively. Pn, Gs, and Tr of Chenopodium glaucum decreased significantly, while SP, POD increased significantly37. Our results also indicated that mine water irrigation had significant effects on soil characteristics. At higher mine water ratios, the soil conductivity increased exponentially, the pH decreased gradually, the content of K+, Na+, Ca2+ and Mg2+ increased, and the content of N, P and K also increased gradually. In contrast, the clean water and mine water mixture had little effect on the soil properties. This was because the salt and metal ions in mine water migrate to the soil during the irrigation process, which significantly changes the soil properties. As a result, the concentration of salt in the soil increased and soil acidity also increased. After mixing with clean water, the concentration of salt decreases, and the influence on the soil matrix weakened. These results also indicated that the growth, physiological, and photosynthetic effects of ryegrass in the pot experiments were better than those in soilless culture, because there were many other organic materials and inorganic ions in soil that could promote growth, whereas the plants in the hydroponic system lacked other nutrients that benefit plant growth. Many existing studies have shown that mine drainage or other wastewater can improve the quality and yield of one or more kinds of plants to different degrees after certain treatment, but some studies also show that the reclaimed water used for irrigation will cause harm to plants, soil and even human health.Jinfang Yang et al. reported that long-term irrigation with mine water significantly reduced the soil respiration rate and soil enzyme activity. Mine water irrigation also significantly inhibited wheat plant height, leaf area, chlorophyll content, and photosynthetic rate, and wheat production was also markedly reduced38. Jianjun Cha found that acidic mining waste water can reduce the pH of the soil profile and increase its electrical conductivity39. Junhao Qin et al. found that if treated mine water is used as an irrigation water source, acidic substances may still be introduced into the soil. This inhibits plant growth and may also enhance leaching of some trace elements in the soil to shallow aquifers, resulting in groundwater pollution40, 41. The results of this study are consistent with the above conclusions, that is, directly irrigating with mine water can significantly inhibit plant growth and photosynthesis, thus affecting the quality of ryegrass plants. MA et al. studied the effects of irrigation with mine wastewater on the physiological characters and heavy metals accumulation of winter wheat. It shows that irrigation with mine wastewater had negative effects on the winter wheat growth and grain yield. At anthesis stage, the leaf area, dry mass per stem, root activity and net photosynthetic rate of winter wheat in treatments were significantly lower and the plant height and leaf chlorophyll content was decreased. In addition, the heavy metals (Cr, Pb, Cu and Zn) contents in the grain of winter wheat under mine wastewater irrigation were significantly higher than those in control, it suggested that the irrigation with mine water could result in the heavy metals accumulation in wheat grain42. A large number of studies have shown that direct use of mine water for irrigation will have a negative impact on soil and plants, but this study found that after a certain processing of mine water (mine water was mixed with clear water in a ratio of 1:2) used for irrigation does not significantly alter soil properties, but can increase plant yield and quality, it will be meaningful to mine water reuse, soil utilization around the mining area and the agriculture.The conclusions of this study are based on mine water from Fushun mining area in Northeast China, but the effects of mine water on plants from other mining areas are uncertain. At the same time, ryegrass, a cold-season turfgrass, is only selected in this study. If it is other kinds of plants, how they respond to mine water irrigation needs further study. What are the effects of mine water irrigation on plants other than ryegrass that need further study. Moreover, this study was only a short-term experiment, and the effects of mine water on the properties of the soil matrix cannot be generalized. Indoor experiments can be regularly watered to maintain moisture, indoor temperature is relatively fixed, while the natural environment is a lot of uncertainty and uncontrollable. Would the results of a small-scale pot experiment in a controlled environment be different if it were applied to a field where there are many uncertainties about soil properties and atmospheric conditions? Long-term field experiments must also be conducted to confirm our findings in more realistic conditions. The use of mine water resources not only has environmental and social benefits but could also bring economic benefits43. This study demonstrated that mine water can be used in ecological restoration and agricultural irrigation in mining areas, and is therefore of great significance to environmental restoration. More

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The current study is the first to directly compare the differences in eukaryotic community diversity by metabarcoding eRNA and eDNA from an estuarine benthic ecosystem. This is also the first study to compare the diversity of environmental RNA and DNA using two of the most common loci examined in metabarcoding applications: COI and 18S. Only a handful of studies have used eRNA to assess diversity through metabarcoding and have demonstrated some differences in detected diversity between eRNA and eDNA in metabarcoding19,29,38. Environmental DNA has many useful applications, but one of the downfalls of DNA is that it can be detected long after an organism has inhabited an area, such as from dead organisms and even significant distances away from the source1. While the persistence of eDNA may be useful in detecting the presence of endangered, rare, or invasive species in marine systems, the persistence of eDNA, such as legacy DNA, may skew the accurate representation of community structure immediately after a disturbance event or during the exact moment of sampling21. Environmental RNA proves to be a useful tool because it is far less persistent in marine environments2,27. In the current study, RNA provides a snapshot of living organisms present in the mesocosms at the time of sampling, compared to DNA which detects past and present organisms in the sample.Benthic ecosystems often have high biodiversity because they are dynamic environments with various substrates favorable for hosting communities39. To date, there is no one loci and associated primer pair that will effectively detect all eukaryotic organisms, and in particular metazoans, so it is beneficial to use multiple loci when looking for a variety of taxa6. Previous marine eDNA studies have demonstrated the preferred method of using two loci to achieve comprehensive metabarcoding for taxonomically diverse environments5,30,40. The current study further demonstrates the need to use at least two different loci for targeted PCR and sequencing to truly capture the wide diversity in rich systems, such as the top oxygenated layer of the marine benthos. Our results demonstrate the types of organisms detected using the 18S loci vary widely from the organisms detected by COI. The 18S loci also detected a higher number of organisms than using the COI loci. The 18S allowed greater detection of metazoans whereas COI was useful in the detection of Oomycota (i.e., a eukaryotic microorganism that resembles fungi) protozoa. Protozoa are often food sources for meiofauna41; therefore, using COI for protozoan detection and 18S for metazoan detection showcases multiple trophic levels present in the mesocosms of the current study. Utilizing multiple loci not only broadens taxonomic diversity detection but can also highlight multiple trophic levels for understanding food webs originating in benthic environments15.A study evaluating arctic benthic diversity similarly found that COI detected fewer taxa than 18S using eDNA metabarcoding, and there was only ~ 40% taxa overlap between markers at the class level42. In the current study, the COI marker using both nucleic acid templates yielded a higher percentage of unassigned taxa after filtering for presence in the majority of mesocosms compared to 18S. A possible explanation for the low metazoan detection by COI may be that the unassigned taxa are metazoans rather than more SAR organisms. Additionally, singly detected metazoans were filtered out of the analysis if they were not detected in at least 4 mesocosms. For example, one type of amphipod was detected in only 3 mesocosm by RNA using the COI marker, but was not detected in any mesocosms using DNA. Therefore, the amphipod observation was excluded from the COI results in Fig. 3 and Table S3 because it was not found in at least 4 mesocosms.Overall, RNA provides a broader assessment of benthic community structure than DNA, particularly when using two loci/ markers for sequencing. In the current study, we used nuclear 18S ribosomal RNA and DNA and mitochondrial COI RNA and DNA sequences as markers for metabarcoding. The number of copies of ribosomal RNA per cell is higher than the copies of ribosomal DNA, and the ratio of RNA: DNA is higher in single-cell organisms, such as protists43. The higher number of unique ASVs detected using eRNA is likely attributed to the higher number of RNA copies of each marker in small, single-cell organisms successfully amplified during PCR, therefore making rare organisms easier to detect. The DNA of highly abundant or higher biomass organisms may “drown out” (i.e., mask) the sequences from lower abundance and biomass organisms during PCR amplification, thus resulting in lower detected α-diversity. The increased detection of ciliates and protozoa using eRNA are consistent with other recent eRNA metabarcoding results that found higher ciliate and protozoan diversity compared to eDNA using the same Uni18S primers19. Positive correlations between organism biomass and sequence copy numbers have been demonstrated for DNA metabarcoding conducted on invertebrate species44. In the current study, RNA allowed for the detected of both larger meiofauna and smaller microfauna, which is optimal for assessing true biodiversity with molecular assays. Chaetonotida, a type of gastrotrich, was the only taxa detected in 4 of the mesocosms using DNA that was not found with RNA. It is possible the chaetonotida may have died during the experiment due to sensitivities to new environmental conditions, and therefore were not detected with RNA. The temperature of the flowing seawater in the mesocosms was approximately 18 °C, and many marine chaetonotida prefer 23–28 °C and high organic matter substrate45.Previous studies have compared the accuracy of conventional morphological identification to molecular metabarcoding methods for assessing biodiversity. In estuarine-specific studies, metabarcoding methods are able to detect the majority of taxa identified with traditional methods and often detected higher species richness, or higher numbers of unique organisms, that was not found conventionally10,46,47. The limiting factor for higher resolution of taxonomic identification is the availability of species-specific sequences in barcoding databases48. However, barcoding databases are becoming more robust as an increasing number of researchers contribute high quality sequencing data to databases7. Therefore, eRNA metabarcoding techniques perform similarly to conventional morphological methods, and may even uncover higher biodiversity in systems like estuaries where meiofauna have been historically understudied and identified.Although eRNA α-diversity is higher compared to eDNA, there is some overlap between ASVs detected with eRNA and eDNA. The higher percentage of overlap between eDNA and eRNA ASVs is predominantly seen in the ASVs detected in all 7 of the mesocosms. The increased overlap in ASVs detected in all 7 mesocosms compared to the relatively lower overlap of ASVs found in only 1 of the 7 mesocosms is due to the filtering of random organisms found in only 1 mesocosm. Detection of a unique organism in a single mesocosm is likely not representative of the sample community and filters potential artifacts that may be introduced during cDNA synthesis from eRNA. However, all uniquely identified ASVs are used in the β-diversity analysis, so the higher number of unique ASVs detected from eRNA are likely driving the significant differences observed between eRNA and eDNA β-diversity. It is possible that using eRNA could increase the statistical power of a study design compared to eDNA because eRNA detects a higher number of ASVs. It is unlikely that a higher number of RNA ASVs could be due to splice variants contributing to unique sequences because the amplified regions of both markers do not contain introns. Therefore, no splicing of transcripts would be expected. Thus, the detected DNA ASVs are from living organisms in the mesocosms and the higher diversity of ASVs detected from RNA demonstrate that RNA is a more suitable option for assessing diversity of living organisms.It is evident that the mesocosms in the current study were rich with meio- and microfauna due to the number of unique organisms and broad diversity of different taxa. It is likely that collecting samples for nucleic acid extraction directly from the field site may result in higher diversity because there is no mechanical disturbance during the laboratory acclimation period and the presence of other organisms in the system, such as fish, macroinvertebrates, or birds. eDNA molecular abundance in samples has been shown to correlate to actual organismal abundance in laboratory environments, but the same correlation is not as apparent in field samples, which is likely due to a variety of collection and processing methods49. eRNA may be the better nucleic acid template for field collection once flash frozen, especially for the detection of protozoans. Future studies will compare the diversity of eukaryotic communities detected using eDNA and eRNA collected directly from the field rather than from sediment core mesocosms. Repeated sampling from a field site may help reduce transient eRNA detection when establishing accurate baseline community composition in field-based biomonitoring studies.Recently, meiofaunal organisms and communities are being explored as bioindicators, which are organisms whose presence are indicators for environmental stress and pollution17. For example, lower meiofaunal diversity and abundance is associated with higher pollution in harbors, and the presence of some genera of nematodes are correlated with higher concentrations of polycyclic aromatic hydrocarbons because they are more tolerant to pollution50. A previous study that used field-collected mesocosms from the same location as our current study found similar phyla detected with a metabarcoding approach; the majority of the sequences detected in benthic communities were from nematodes, arthropods, and the microfaunal SAR clade10. Similarly, the majority of the ASVs detected from the current study also corresponded with nematodes, arthropods, and the SAR clade, as well as other commonly detected meiobenthic organisms, such as polychaetes and Homalorhagida (i.e., mud dragons). A recent study exposed a benthic foraminiferal community to chromium, and found that eRNA metabarcoding was more robust for detecting changes in diversity at lower chromium concentrations compared to eDNA51. The eRNA metabarcoding method used in the current study detected meiofaunal taxa typical of marine or estuarine environments. Therefore, eRNA metabarcoding may be useful for efficiently identifying bioindicator species or taxa impacted by exposures to different contaminants and environmental stressors to aid with management of aquatic systems. Another advantage of eRNA is that RNA provides functional information about how organisms response to stress through altered transcription of activated pathways. eRNA will likely be a more powerful tool than eDNA because it allows for the detection of both bioindicator species and, in the future with increase development of genetic databases, environmental detection of biomarkers of stress through increased transcription of response genes.Many academic researchers are adopting molecular methods using High Throughput Sequencing as the future of biomonitoring surveys; however, few regulatory and environmental management organizations/ agencies have adopted metabarcoding into their routine biomonitoring practices for regulatory purposes. In marine benthic communities, metabarcoding provides a comprehensive assessment of diversity and is useful for detecting a broader array of organisms in biomonitoring surveys especially when using two markers47. eDNA is also useful for monitoring discrete communities (i.e., benthic versus pelagic)52, so it is possible that using eRNA could provide vital information about living organisms in specific environments compared to eDNA. Metabarcoding sequencing and bioinformatic approaches for benthic environments vary among studies, thus requiring some standardization between methods to further advance the use of metabarcoding in conservation and regulatory applications30,53.Like eDNA, some advancements must be made with eRNA to be used as a quantitative tool in molecular ecology. Validation of eDNA metabarcoding for assessing relative abundance of species is rapidly progressing by correlating laboratory studies of DNA shedding with field experiments1,54. Similar validation techniques can be used to develop eRNA metabarcoding as a quantitative or semi-quantitative method. There is growing interest in optimizing eRNA extraction protocols from different types of environmental media to standardize the use of eRNA in downstream molecular applications55. Thus, standardizing eRNA protocols will help with integration into environmental management toolkits for regulatory purposes.RNA poses unique barcoding challenges compared to DNA because the number of RNA transcripts from a gene are not always present in the same proportion compared to the gene copy number per genome (i.e., one DNA copy per cell), especially for differentially expressed genes. However, one possible way to work around this issue is to utilize constitutively expressed marker loci where transcription is generally stable and unaffected by environmental stressors, such as those used as reference genes for quantitative real-time PCR49. Fortunately, many loci chosen for metabarcoding purposes fit this criterium; the transcription of 18S and COI remain steady within the cell regardless of environmental stress.Collecting sediment cores from the environment and bringing them into controlled laboratory settings for community analysis through eRNA metabarcoding is a powerful tool that opens opportunities for this method to be used in a broad range of fields. For instance, field-collected mesocosms could be used in controlled settings to investigate the effects of individual or mixtures of toxicants on entire community and population-level outcomes. Marine sediments are often the ultimate sink for environmental contaminants, such as organic pollutants , heavy metals56, and plastic particles57, yet few studies investigate actual community-level changes in contaminant exposures. Marine benthic environments have high biodiversity, but the breadth of diversity in micro- and meiofaunal organisms is often understudied because traditional morphological methods are immensely time consuming. Sediment core mesocosms could also be used to understand the effects of global climate change stressors, such as fluctuating temperatures, surface water salinity and pH, on communities as well as conventional and emerging contaminants in combination with climate change stressors. Additionally, this method could also be used to understand how communities respond to a significant disturbance event or smaller series of stressors, which are often difficult to measure in environmental settings32,58. In these applications, eRNA is favorable for constructing community composition at a specific moment of the experiment to better regulate anthropogenic causes of environmental stress. More

Electrohydrogenesis effluent as a potential biofertilizerTo characterize the electrohydrogenesis left-over residues as potential biofertilizers, the sample from the operating reactors was performed a 16S rRNA sequencing test, and interestingly, the results revealed that the bio-electrohydrogenesis effluent was enriched with various microorganisms including plant growth-promoting microbes that display biofertilizer-like features. Among the well-known plant-promoting bacterial genera observed in DF-MEC residues included Azospirillum, Mycobacterium, Chryseobacterium, Paenibacillus, Rhizobacter, Pseudomonas, Achromobacter, Bradyrhizobium, Actinomyces, Sphingomonas, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, Gordonia, Rhodococcus, Bacillus, Methylobacterium-Methylorubrum, Microbacterium, Flavobacterium, Devosia, Acinetobacter, Mesorhizobium, Enterobacter, Aeromonas, Beijerinckia, etc.24,25,26 (Fig. 2). Lots of investigations working on the feasibility of using biofertilizers other than chemical fertilizers have revealed that those aforementioned microbes play a major role in providing the required nutrients for enhanced crop yield.Figure 2The abundance of the Plant growth-promoting bacteria (genus level) detected from the DF-MEC digestate (%).Full size imageNitrogen-fixing microorganismsThe detected nitrogen-fixing microorganisms from the electrohydrogenesis effluent include Azospirillum sp. (0.11 ± 0.02%), rhizobia (Rhizobium (0.058 ± 0.02%), Bradyrhizobium (0.11 ± 0.04%), and Mesorhizobium (0.1 ± 0.03%)), and Beijerinckia (0.08 ± 0.03%) (Fig. 2) and were repeatedly reported for their superior contribution to the plants’ nitrogen requirements through biological nitrogen fixation, which is an important component of sustainable agriculture25. Although the atmosphere counts about 78% N2, it couldn’t be used by plants in its natural state. Prior to getting used by plants, it needs to be converted to ammonia, which is the readily assimilable form of nitrogen by plants/or crops via a biological nitrogen fixation mechanism25. The biological Nitrogen fixation mechanism is summarized in Fig. 3.Figure 3Mechanism of nitrogen fixation bio-catalyzed by nitrogenase enzyme. The plant growth-promoting bacteria produce nitrogenase which is a complex enzyme consisting of dinitrogenase reductase and dinitrogenase. This complex enzyme plays a major role in molecular N2 fixation. Dinitrogenase reductase provides electrons and dinitrogenase uses those electrons to reduce N2 to NH3. However, oxygen is a potential threat to this process since it has the ability to get bound to the enzyme complex and make it inactive and consequently inhibit the process. Interestingly, bacterial leghemoglobin has a strong affinity for O2 and thus gets bound to free oxygen more strongly and effectively to suppress the available oxygen effects on the whole process of nitrogen fixation.Full size imagePhosphate-solubilizing microorganismsFurthermore, various phosphate-solubilizing and mineralizing strains were also found in bioelectrohydrogenesis residues collected from our DF-MEC integrated reactors. Among those microorganisms with the ability to solubilize/metabolize the insoluble inorganic phosphorus, the dominant bacterial genera included Pseudomonas (0.65 ± 0.15%), Bacillus (0.44 ± 0.11%), Rhodococcus (0.04 ± 0.009%), Rhizobium (0.05 ± 0.02%), Microbacterium sp. (0.04 ± 0.01%), Achromobacter (0.16 ± 0.07%), and Flavobacterium (0.058 ± 0.014%) (Fig. 2). Though enormous amounts of phosphorus are available in the soil, its high portion never contributes to plant growth in its primitive state, unless it is bio-transformed into absorbable forms including monobasic and dibasic. Microbial phosphate solubilizing mechanisms are well described in Fig. 4.Figure 4Inorganic phosphorus solubilization by phosphate-solubilizing rhizobacteria. A bacterium solubilizes inorganic phosphorus through the action of low molecular weight organic acids such as gluconic and citric acids. The hydroxyl (OH) and carboxyl (COOH) groups of these acids chelate the cations bound to phosphate and thus convert insoluble phosphorus into a soluble organic form. The mineralization of soluble phosphorus occurs by synthesizing different phosphatases which catalyze the hydrolysis process. When plants incorporate these solubilized and mineralized phosphorus molecules, eventually, overall plant growth and crop yield significantly increase.Full size imagePhytohormone-producing microorganismsIn this current work, the electrohydrogenesis effluent also contained bacterial genera such as Mycobacterium (0.77 ± 0.18%), Allorhizobium (0.05 ± 0.02%), Pararhizobium (0.05 ± 0.02%), Paenibacillus (1.18 ± 0.24%), Bradyrhizobium (0.11 ± 0.04%), Rhizobium (0.05 ± 0.02%), Acinetobacter (0.14 ± 0.02%), and Azospirillum (0.11 ± 0.025%) (Fig. 2) that have the ability to synthesize indole-3-acetic acid/indole acetic acid (IAA) through indole-3-pyruvic acid and indole-3-acetic aldehyde25. IAA is a well-known type of phytohormone that enhances plant/crop growth. Particularly, Azospirillum sp., also produce various phytohormones namely cytokinins, gibberellins, ethylene, abscisic acid and salicylic acid, auxins, vitamins such as niacin, pantothenic acid, and thiamine. The conceptional model delineating the positive effects of inoculation with Azospirillum sp. a phytohormones-producer plant growth-promoting rhizobacteria and its detailed functions on plant growth are summarized and illustrated in Fig. S1. Therefore, the existence of those rhizobacteria in the bioelectrohydrogenesis residues further implies the suitability of considering the DF-MEC left-over residues as potential biofertilizers.Heavy metals-bioremediating microorganismsSome other bacterial genera with the ability to bioremediate the heavy metal toxicity were also found within the bioelectrohydrogenesis left-over residues as well. Among the detected plant growth-promoting bacterial genera; Rhizobium (0.058 ± 0.023%), Mesorhizobium (0.1 ± 0.026%), Bradyrhizobium (0.11 ± 0.04%), Pseudomonas (0.65 ± 0.15%), and Achromobacter (0.16 ± 0.077%) were reported for their key contribution to alleviate the toxicity of the heavy metals via bioremediation process and improve the soil quality for a relief plant development26 (Fig. 2). Other detected heavy metals-bioremediating microorganisms’ species were Chryseobacterium sp. (0.08 ± 0.007%), Azospirillum (0.11 ± 0.02%), Bacillus (0.44 ± 0.11%), Enterobacter (8.57 ± 0.9%), Gordonia (0.06 ± 0.02%), Paenibacillus (1.18 ± 0.24%), Pseudomonas (0.65 ± 0.15%), and Actinomycetes (0.36 ± 0.05%) that either use microbial siderophores or enzymatic biodegradation process.Electrohydrogenesis left-over residues as a potential source of essential elements for plant growthAs aforementioned in “Materials and methods” section, the electrohydrogenesis left-over residues contained diverse microbial communities that degraded the MEC substrate and generate biogas and inorganic compounds. Moreover, it has been reported that those inorganic nutrients are generally available in fermentation effluent in readily plant-utilizable formats owing to substrate mineralization27. Beside detecting various plant growth-promoting microorganisms in the electrohydrogenesis effluent, a larger number of mineral elements essential for promoted growth and development of crop plants were also investigated and analyzed from the residues. The detected primary and secondary macro-elements’ concentrations in the residues were arranged in decreasing order as follows P  > S  > Na  > K  > N  > Ca  > Mg. Interestingly the findings show that the residues abundantly contained Phosphorus (2.766 × 103 mg/L), Nitrogen (274 mg/L), Potassium (282 mg/L), Calcium (17.66 mg/L), Magnesium (16.3 mg/L), Sulfur (1.225 × 103 mg/L), and Sodium (294.3 mg/L) which are well known as macro-nutrients needed in larger amounts for enhanced plant/ crop growth (Fig. 5).Figure 5Macro-, and micronutrients detected from the bio-electrohydrogenesis left-over residues (mg/L).Full size imageMoreover, small amounts of the microelements including Ni, Pb, Zn, Cu, Cr, Hg, Cd were also found in the electrohydrogenesis residues, and consistently these elements are generally required in small quantities for the development of plants (Fig. 5), otherwise, their high concentrations are toxic for the plant cells thus suppress or inhibit plant growth. The detected concentrations for the main microelements in this current research ranged only from 0.36 to 9.6 × 10–5 mg/L and were all reported to play fundamental roles in plant metabolic reactions.Cultivation of the leguminous crops using electrohydrogenesis left-over residues as fertilizerAfter evaluating the plant-growth promoting bacterial communities and the macro- and micronutrients required for plant/crop growth in the electrohydrogenesis left-over residues, the latter was directly used as fertilizer to grow three different plant species including tomato, chili, and brinjal as afore-described in the “Materials and methods” section. To access the potentials of the electrohydrogenesis effluent as fertilizer, the plants grown in the soil amended with the effluent (Soil + Effluent), were directly compared with their corresponding control plants (Soil + water). The results indicated that at the end of 1st month, the plants with effluent grew faster and generated a good amount of branching than the control plants (see Fig. 6), possibly due to the availability of both microbial species with bio-fertilizing aspects and micro-and macronutrients in the effluent.Figure 6Analysis of the plant growth at the end of the 1st month of cultivation. (a) Tomato in soil with effluent, and its control without effluent (b); (c) Chilli grown in soil with effluent, and its control without effluent (d); and (e) brinjal grown in soil with effluent, and its corresponding control grown without effluent (f) (after 2 months).Full size imageFor instance, tomato (Solanum lycopersicum L.) and chilli (Capsicum annuum L.) height in soil + electrohydrogenesis effluent was ~ 36.9 ± 2.1 cm and ~ 32.6 ± 0.8 cm respectively which was ~ 2.03 and ~ 1.2 times the height of their corresponding plant species in the control protocol, respectively (see Fig. 7). However, the brinjal species (Solanum melongena L.) didn’t show any remarkable height differences in both protocols after a month of cultivation (data not shown), probably due to their low adaptative characteristics to the new environment. However, after the 2nd month, the brinjal height in soil + effluent became 2.7 times that of the brinjal control cultivated without effluent (see Fig. 6e,f). Moreover, both the number of the plants’ leaves and their length in plants cultivated in soil + effluent, were remarkably higher than in plants grown without the supply of the effluent.Figure 7Daily plant growth analysis within one month of cultivation. (a) Tomato growth monitoring, (b) Chili growth analysis.Full size imageAt the end of the 3rd month, the plants in soil + electrohydrogenesis effluent generated more fruit with big size than the control plants (see Fig. 8), but the tomato (Solanum lycopersicum L.) didn’t generate fruits in both protocols at that time probably due to the high weather temperature that inhibitory affected its continuous growth, as previously reported that tomato species are generally so sensitive to temperature change28,29. The final yield was evaluated in terms of the size and number of fruits per cultivated plant. Chili cultivated in soil with MEC effluent generated 3 fruits/plant and its corresponding control without effluent produced only 1 fruit/plant. The chili fruit size in soil + effluent was 16 cm, approximately 18.7% higher than its corresponding control. Moreover, at the time of collecting data, the brinjal plant cultivated in soil with MEC effluent generated brinjal fruits whereas its corresponding cultivated without electrohydrogenesis effluent started flowering (see Fig. 8). These further indicate the significant contribution of the electrohydrogenesis effluent in speeding up the plant growth. Herein, the electrohydrogenesis left-over residues have notably improved the soil quality and significantly promoted the plants’ phenology characterized by plant growth, the generation of new leaves, flowering, and the production of fruits.Figure 8Analysis of plant growth characterized by the flowering and fruiting process at the end of the 3 months. (a) Chili grown in soil with effluent, and its control without effluent (b); (c) brinjal grown in soil with effluent and its corresponding control grown without effluent (d).Full size image More