Philippa Kaur

Degree of hydrolysisOrganic silages prepared from fat fish (FFS) and lean fish (LFS) had a characteristic tawny brown colour which was accompanied with a strong characteristic salty-fishy odour. At the end of 5 DoF, both FFS and LFS exhibited sluggish liquefaction which increased progressively concomitant with the DoF (Table S1). Liquefaction is an indicator of tissue hydrolysis due to the action of acid. During 35 DoF, the degree of hydrolysis (measured in terms of liquefaction volume) increased progressively with the DoF in both types of ensilages and was relatively higher in LFS compared to FFS on all sampled DoF (Table S1). In general, lipolysis supersedes the proteolysis in all major biochemical processes23. A relatively higher degree of hydrolysis recorded in LFS may be attributed to the presence of a greater proportion of light muscles compared to dark muscles. Relatively greater susceptibility of light muscles to hydrolysis compared to dark muscles might be due to lower lipid content in the former23.Irrespective of fish type, the measured pH values in both types of ensilages (FFS and LFS) were similar (data not shown) and the values showed a progressive increase from 1.0 ± 0.03 (0 DoF) to 6.0 ± 0.03 (35 DoF). Such an increasing trend in pH with the advancement in DoF could be attributable to gradual solubilisation of boney material with the advancement fermentation time24,25,26.Changes in principal biochemical constituentsDuring the 35 DoF, the concentrations of total protein (TP) in both FFS and LFS progressively increased with the DoF and showed significant differences with the advancement of DoF (p  phenylalanine (2.6 ± 0.033)  > serine (2.4 ± 0.033)  > aspartic acid (2.3 ± 0.033)  > alanine (2.1 ± 0.033)  > histidine (1.8 ± 0.033)  > valine (1.6 ± 0.033)  > methionine (1.5 ± 0.033)  > isoleucine (1.5 ± 0.033)  > threonine (1.4 ± 0.033)  > cysteine (0.946 ± 0.033).Figure 1Composition of total amino acids (mg/g) in two types of fish ensilages (FFS—fat fish silage; LFS—lean fish silage) during 35 days of fermentation (DoF). Data are mean ± SD. * p  glutamic acid (4.97 ± 0.033)  > arginine (4.5 ± 0.033)  > phenylalanine (3.38 ± 0.033)  > aspartic acid (2.92 ± 0.033)  > alanine (2.23 ± 0.033)  > methionine (2.19 ± 0.033)  > lysine (1.882 ± 0.033)  > serine (1.881 ± 0.033)  > tyrosine (1.410 ± 0.033)  > glycine (1.219 ± 0.033)  > threonine (0.953 ± 0.033)  > valine (0.945 ± 0.033)  > isoleucine (0.864 ± 0.033)  > histidine (0.417 ± 0.033).A comparative assessment of profiles of TAA in both FSS and LFS during all DoF revealed a similar pattern, albeit with obvious differences in the concentration of few amino acids (Fig. 1). It has been hypothesised that the occurrence of decarboxylation that follows transamination of amino acids as a consequence of increase in pH during fermentation is known to cause a decrement in the concentration of few amino acids, especially valine and isoleucine34. During the present study, the concentrations of histidine, valine, isoleucine, glycine and lysine were significantly higher (p  leucine (3.09 ± 0.003)  > glutamic acid (2.61 ± 0.003)  > alanine (1.83 ± 0.003)  > phenylalanine (1.79 ± 0.003)  > cysteine (1.67 ± 0.003)  > histidine (1.56 ± 0.003)  > aspartic acid (1.54 ± 0.003)  > serine (1.32 ± 0.003)  > lysine (1.16 ± 0.003)  > threonine (1.09 ± 0.003)  > valine (1.07 ± 0.003)  > isoleucine (1.06 ± 0.003) followed by methionine (0.93 ± 0.003)  > tyrosine (0.92 ± 0.003)  > tryptophan (0.72 ± 0.003)  > asparagine (0.57 ± 0.003)  > glutamine (0.15 ± 0.003).Figure 2Composition of free amino acids (mg/g) in two types of fish ensilages (FFS—fat fish silage; LFS—lean fish silage) during 35 days of fermentation (DoF). Data are mean ± SD. * p  More

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Biostimulation of ureolytic communitiesEnrichmentThe native communities of the soils were successfully grown in the enrichment media (NB5U). The cultivated communities after two subcultures were serially diluted (10–2 to 10–6) and were spread with a sterile loop over Nutrient agar plates supplemented with 2% urea. Later, 36 morphologically distinct single colonies were obtained on the urea agar base plates based on visual observation.Isolation, identification, and characterization of the ureolytic isolatesOut of 36 isolated bacteria, six isolates (BS1, BS2, BS3, BS4, LS1, and LS2) were selected after checking for the urease activity test on the urea agar base (UAB) plate. These selected isolates turned the color of the UAB plate from orange to pink within 12 h. The 16 s rRNA sequence revealed the isolates as relatives of Sporosarcina pasteurii (SP). The details of the identified isolates are provided by NCMR (details in Supplementary Table 1). The biochemical characterization (details in Supplementary Table 2) of the isolates revealed that all the isolates are Gram-positive. All the isolates were rod-shaped, endospore-forming, urease, and oxidase positive. All the isolates were not able to utilize the Lysine and ONPG, contrary to SP.Further investigation of the isolated sequence was done via the NCBI database. The sequences were submitted to the GenBank database of the NCBI (National Center for Biotechnology Information) under the accession number MW024144 to MW024149. The BLAST analysis suggested that these strains are close relatives and indicate the possibility of being novel strains of the Sporosarcina family. We found that the isolate BS1 and BS2 had 96.62% (coverage 100%) and 96.22% (coverage 99%) identity with Sporosarcina siberinisis (NCBI accession number NR 134188). BS3 had 98.8% identity (coverage 97%) with Sporosarcina pasteurii (NCBI accession number NR 104923). BS4 and LS1 had 97.4% (coverage 99%) and 97.37% identity (coverage 100%) with Sporosarcina soli (NCBI accession number NR 043527). Contrarily, LS2 was found to be related to the Pseudogracilibacillus family. LS2 was observed to be closely related to Pseudogracilibacillus auburnensis P-207 with 97.06% identity (96% coverage). Based on these findings, the Phylogenetic tree was constructed with bootstrap (1000 replicates) considering the reference sequences obtained from the BLAST analysis, as shown in Fig. 3. The threshold criteria to differentiate two species is defined as 98.65% similarity score with the reference culture from databank40, while another study has suggested that in case of similarity index is  > 99%, the unknown isolate should be assigned to a species, and if the unknown isolates have similarity score between 95 to 99% to a reference sequence, the isolate should be assigned to the genus41. However, further investigation is suggested to conclude if the reported strains are novel or merely mutants of the reference strains of the databank. Similar observations were made at Graddy et al.22, where the majority of the isolated strains (47 out of 57) from bio-stimulation soil tanks were found to be strains of the Sporosarcina genus. It is worth noting that the soil enrichment media for stimulation was rich in urea, similar to Gomez et al.42 and Graddy et al.22, which is conditional stress for selective stimulation of ureolytic microorganisms. Moreover, the isolated strains were screened based on morphology and qualitative urease activity.Figure 3Neighbor-joining phylogenetic tree based on the 16S rRNA sequence of the isolates and reference sequence from the GenBank database (NCBI).Full size imageEvaluation of biocementation potential of the isolated strainsGrowth and pHThe various parameters of the biocementation potential of the isolated strains in comparison with Sporosarcina pasteurii (SP) have been plotted in Fig. 4. The growth characteristics of the isolates in NBU media and pH during growth have been represented in Fig. 4a and b. The initial pH of the growth media is kept at 7.5. It was observed that the pH of the growth media rises to 9.5 within 24 h of growth, indicating that these strains favor an alkaline environment to grow similar to SP43. All the isolates start growing when the pH of the media rises to 8.5 or above. Isolate LS2 was observed to have slower growth when compared with other isolates. This can be explained as LS2 belongs to different genera (Pseudogracilibacillus).Figure 4(a) Growth characteristics, (b) pH, (c) specific urease activity, (d) calcium utilization rate, and (e) carbonate precipitation rate of the isolates and consortia.Full size imageSpecific urease activityThe specific urease activities of the isolates were found to be comparable with SP (shown in Fig. 4c). Based on the provided NBU media and growth condition, the specific urease activity of SP is found to be 173.44 mM urea hydrolyzed h−1 (OD600)−1, which is around 2.9 mM urea hydrolyzed min−1 (OD600)−1. The specific urease activity of the isolate BS3 was observed to be maximum as 186.6 mM urea hydrolyzed h−1 (OD600)−1 during a growth period of 24 h and pH  > 9. Consortia also demonstrated significant urease activity as 160 mM urea hydrolyzed h−1 (OD600)−1 at a growth period of 48 h. The maximum ureolytic activity in BS1 was observed after 72 h of growth with a value of 106.67 mM urea hydrolyzed h−1 (OD600)−1. Maximum specific urease activity of the isolate BS2, BS4, and LS1 was observed to be 160.2, 120, and 173.4 mM urea hydrolyzed h−1 (OD600)−1 respectively after a growth duration of 48 h. LS2 demonstrated the maximum specific urease activity of 146.4 mM urea hydrolyzed h−1 (OD600)−1. The observed order of specific urease activity at 24 h of growth period is BS3  > SP  > Consortia  > LS1  > BS2  > BS4  > LS2  > BS1. As the urease activity of the strains depends on the growth media, urea content, and environmental conditions such as pH and Temperature44, we considered the conditions at the riverbank at the time of isolation, and the pH and temperature of the growth media were set at 7.5 and 37 degrees Celsius. The specific urease measured by the electrical conductivity method is reported to be between 3 to 9.7 mM urea hydrolyzed min−1 (OD600)−1 in yeast-extract urea media at pH 7 and temperature 30 degrees Celsius43. It is reported around 5 mM urea hydrolyzed min−1 (OD600)−1 in the nutrient broth urea (2%) media at a temperature of 25 degrees Celsius44. The comparative analysis of the urease activity (measured by electrical conductivity method) was done considering SP as positive control in this study. The maximum specific urease activities of all isolates were found to be in a range of 106.67 to 186.67 mM urea hydrolyzed h−1 (OD600)−1 (1.78 to 3.11 mM urea hydrolyzed min−1 OD600–1), which indicates that all of the isolated strains are capable of biocementation43,45.Calcium utilization and carbonate precipitation potentialIt was experimentally observed that the depletion of the supplemented soluble calcium in the precipitation media (PM) was corresponding to the ureolytic activities of the isolated strains. Within 48 h of introducing 1% bacteria (OD600 = 1) in the precipitation media, the soluble calcium chloride (50 mM) was utilized to precipitate carbonate crystals, as illustrated in Fig. 4d. Within 12 h of the inoculation period, BS3 was able to utilize 75% of the supplied calcium, while SP was able to utilize only 62.5% of the soluble calcium. The order of the calcium utilization potential in the isolates was observed as BS3 ≥ LS2  > L.S.1  > Consortia  > SP  > BS4  > BS2  > BS1 during the inoculation period. Contrarily, LS2, despite being a comparatively slow urease-producing bacteria, was able to utilize calcium ions at par with other isolates. Negligible changes were observed in the soluble calcium concentration of the control group eliminating the possibility of abiotic precipitation.The carbonate precipitation rate for each isolate (1% at OD600 = 1) for the 50 mM cementation media is plotted in Fig. 4e. The isolate BS3 with maximum ureolytic activity (specific urease activity 186.6 mM urea hydrolyzed min−1 OD600–1) precipitated the highest carbonate crystals after 96 h of the incubation period. BS3 precipitated 438 mg/100 ml of carbonate crystals, which is around 87.66% precipitation from the total supplied CaCl2, while precipitation with SP was quantified as 389 mg/100 ml (78%). The precipitation in consortia was observed to be 407 mg/100 ml (81%), which is slightly higher than SP. Precipitation in other isolates was found to be significantly lower than isolate BS3. Isolate BS1and BS2 precipitated 334 mg/100 ml (67%) and 343 mg/100 ml (69%) of carbonate crystals respectively, whereas isolate LS1 and LS2 precipitated around 357 mg/100 (71%) ml of carbonate crystals each. Isolate BS4 precipitated minimum carbonate crystals 292 mg/100 ml (58%). No precipitation was observed in the negative control set. Low concentrations of bacterial cells (1%) were considered in this experiment to slow down the urea hydrolysis in order to differentiate the calcium utilization potential of the isolated strains. This approach was modified from Dhami et al.46, and our results show agreement with their finding where 1% of SP cells depletes the 25 mM of CaCl2 within 24 h. It was observed that all the isolates took approximately 48 h to deplete the 50 mM CaCl2. The depletion of soluble calcium concentration was rapid in the initial 24 h in all the isolates. After 48 h, the residual soluble calcium was observed to be in the range of 2.5–5 mM in all the isolates (except BS1 and BS2), which might be due to loss of super-saturation caused by the unavailability of nutrient for bacterial cells to continue urea hydrolysis in the precipitation media13,43,47. The mineralogy of precipitated carbonate polymorphs (calcite, aragonite, vaterite) and the residual calcium are also influenced by pH, temperature, saturation index, dissolved organic carbon concentration, and the Ca2+ /CO32−ratio along with the presence of metabolites in the precipitation media13,47,48. As maximum precipitation was recovered with the isolate BS3, the isolate BS3 was selected for further investigation on soil improvement.Microstructure analysis of the precipitatesThe FESEM images of the carbonate crystal precipitated from BS3 were investigated further. The shape of the precipitated crystals was observed to be rhombohedral and trigonal (Fig. 5a). The average size of the crystals was observed in a range of 25 to 50 microns. The entrapped bacteria and rod-shaped bacterial imprints were identified (Fig. 5b), indicating that the bacteria acted as a nucleation site14. The smaller crystals were observed to coagulate in layers to develop larger calcite crystals. The entrapped bacteria were noticed on the grown and coagulated calcite crystal in Fig. 5c. After taking the FESEM image (Fig. 5a) of the precipitate, EDX analysis was conducted, and the elemental composition suggested an abundance of calcium, carbon, and oxygen, which indicates the presence of calcium carbonate crystals (Supplementary Fig. 1). XRD analysis was conducted to confirm the mineralogy of the precipitates, and the majority of the observed peaks of the XRD plot belonged to calcite, which is consistent with the observation of rhombohedral crystal shapes in the FESEM image. The XRD analysis also suggested an insignificant presence of aragonite in the precipitates.Figure 5FESEM images of the calcite precipitated from BS3 (a) Coagulated crystals (b) Bacterial imprints, (c) Entrapped bacteria on the precipitates.Full size imageApplication of native communities on riverbank soil and its influence on soil strengthNeedle penetration resistance of treated soilThe average NPI (N/mm) for different cases has been shown in Fig. 6a. No notable resistance was observed in the loose untreated sand (control) against the needle penetration. With one bio cementation cycle treatment, the consortia-treated soil sample (Consortia-BC1) demonstrated a higher value of NPI (5.15 N/mm) than SP-BC1 (4.19 N/mm) and BS3-BC1 (4.64 N/mm). The increase in the biocementation cycle treatment significantly improved the needle penetration resistance. Sample BS3-BC2 showed 116% improvement with the NPI value of 10.03 N/mm when compared to one cycle treated sample BS3-BC1. A similar trend was observed in the sample BS3-BC3 (NPI = 16.12 N/mm), which showed around 347% improvement in NPI when compared to sample BS3-BC1. From the needle penetration test, it was evident that the penetration resistance of treated soil improves significantly with the increased level of biocementation cycles, indirectly indicating an improvement in the soil erodibility resilience. Since non-uniformity is one of the undesired traits of MICP, a contour was plotted corresponding to the 25 points NPI, as shown in Fig. 6b. The contrasting color difference in the contours of the samples BS3-BC1, BS3-BC2, and BS-BC3 clearly demonstrates the stark difference in the strength of treated samples. The non-uniformity in the strength of treated soil crust of sample BS3-BC2 and BS3-BC3 can also be realized with the contrasting color gradient of the NPI contours.Figure 6Comparison of the Needle penetration resistance (N/mm) of the treated soil specimen (a) average values and (b) the contours.Full size imageSince the rate of penetration has an insignificant influence on the test results, the needle penetration test is recommended by the International Society of Rock Mechanics (ISRM) for quick, non-destructive testing of the strength of the stabilized soils and soft rocks49. As a large number of tests can be conducted due to the small diameter of the needle without destroying the sample, the needle penetration test is a better alternative to evaluate the local grain bonding in the biocemented soil than bulk strength properties like unconfined compressive strength and calcite content. Another rationale for choosing needle penetration test over conventional soil strength evaluation tests was that a pocket type penetrometer could be developed with the configuration in the present study for non-destructive monitoring of the soil strength improvement with biocementation application in the field. The response of the needle penetration resistance in terms of nominal strain (ratio of penetration to rod diameter) also indicated that the measured responses are independent of needle diameter for a small range, i.e., 1 to 3 mm49,50. A portable penetrometer of Maruto. Co. ltd. (needle maximum diameter 0.84 mm at 12 mm from the tip) have been correlated with high confidence value to conventional physicochemical parameters such as unconfined compressive strength (UCS), elasticity modulus, and elastic wave velocity in several studies50. In our setup, we have utilized a similar configuration chenille 22 needle with (maximum diameter 0.86 mm at 9 mm from the tip) and a penetration rate of 15 mm/minute for measuring the strength properties of cemented soil. Adopting the UCS and NPI correlation suggested by Ulusay et al.51, the UCS of samples BS3-BC1, BS3-BC2, and BS3-BC3 are around 1.67 MPa, 3.4 Mpa, and 5.3 Mpa.It is worth noting that in the needle penetration resistance tests, the boundary of the Petri dish can influence the test results. Therefore, trials were conducted and based on the findings, all penetrations were conducted at points at least five times the diameter of the needle away from the boundary to negate the influence of boundary conditions. The maximum penetration was conducted only up to 50% of the depth of prepared biocemented soil samples in the Petri dishes to avoid inference from the bottom of the Petri dish.Erodibility test in the hydraulic flumeTo investigate the influence of hydraulic current on different levels of biocementation, all the treated samples were exposed to hydraulic current gradually varying from gentle flow (0.06 m/s) to five times the critical velocity (0.75 m/s) in a 45-min duration test and soil mass loss percentage by the initial dry mass of the treated sample is presented as a measure of soil erodibility in Fig. 7. As expected, with an increase of biocementation cycles, i.e., calcite content, the soil erodibility reduced substantially. The initial dry weight of the samples control, BC1, BC2, and BC3, were measured as 398, 403, 406, and 410 g, respectively. Approximately 7.3% of calcite content resulted in a drastic reduction in erodibility (12% mass loss), while 56% soil mass loss was recorded for control (untreated sand). One biocementation cycle treatment (sample BS3-BC1) produced an average of 2.5% of calcite, reducing the soil loss to 31%. Sample BS3-BC2 with 4.93% calcite content resulted in 22% soil mass loss during the hydraulic flume test. It is worth noting that higher precipitation in the soil pores may hinder the flow of water in the soil matrix and increase the pore water pressure resulting in catastrophic failures. However, the MICP technique is reported to be a great tool to improve soil strength, maintaining an adequate hydraulic conductivity to prevent the build-up of the excess pore water pressure11. Theoretically, the percentage pore volume filled with precipitates for samples BS3-BC1, BS3-BC2, and BS3-BC3 considering the observed calcite contents and pore volume (100 ml) is around 3.7, 7.14, and 11.08%. The influence of pore water pressure on erodibility has not been established in the present study, and it certainly is one of the exciting parameters to consider for future studies.Figure 7Weight of the eroded soil (%) after the hydraulic flume test.Full size imageFrom the visual observation of the soil specimen after the flume test, it was evident that the soil particles start bonding with an increased level of bio cementation. A tough crust was formed on the top of BS3-BC2 and BS3-BC3 the samples, which got eroded with the fluvial current. Insignificant aggregation was observed in the sample BS3-BC1. However, with two and three cycles of biocementation treatment (BS3-BC2 and BS3-BC3), the biocemented soil particles (BCS) were evidently noticed (photos are shown in Supplementary Fig. 4).Clarà Saracho et al.27 addressed the erosion due to tangential flow (similar to river current) by treating the soil specimen with ten pore volume of low concentration of cementation media (0.02 M to 0.1 M) by injection strategy and tested the specimen in the flow velocity ranging from 0.035 to 0.185 m/sec for 120 min in a modified erosion function apparatus (EFA). The study concluded that the treatment with 0.08 M cementation media (calcite content varying from 1.2 to 4%) resulted in negligible erosion in the stated test conditions, and with the increase in MICP treatment, a shift in the erosion mode from particulate mode to block failure was observed indicating that with the increase in calcite content and needle penetration resistance, there might be a threshold for biocemented soil, where the soil erosion might be catastrophic due to block failure. However, in this study, a consistent decrease in soil erodibility is observed with the increase in needle penetration resistance. We found that 7.3% of calcite content was required to control the soil erodibility substantially in the test flow range (0.06 m/s to 0.75 m/s). A similar trend was observed by Kou et al.52 and Chung et al.53, where consistent reduction in wave-induced erosion and rainfall-induced erosion was observed with an increase in needle penetration resistance for biocemented fine sand treated with the exogenous bacteria.Another aspect to note in the context of the applied treatment is the produced ammonia which can be toxic for riparian flora and fauna15. From stochiometric calculations, for each biocementation cycle, the produced ammonia is evaluated as 8.5 kg per metric ton of soil treated, and for the best performing treatment approach, i.e., BS3-BC3, the ammonia generated is evaluated as 2.63% by weight of the retained soil. The acceptable limit of ammonia in the surface water was recommended as 17 mg per liter for acute exposure and 1.9 mg/l for chronic exposure for protecting the aquatic life in the freshwater as per the environmental protection agency54. With the MICP technique, the threat of produced ammonia crossing the maximum acceptable quantity is highly plausible; however, for the field application, the ammonia generated can be reduced by reducing the quantity of reagents and increasing the period of applications. It is to be noted that the produced ammonia will also be subjected to dilution in the river stream. The average discharge of the Brahmaputra river is around 19.8 megaliters per second in the Assam valley33. Therefore, the area of the riverbank to be biocemented must be decided judiciously with the context of the produced ammonia quantity and its possible dilution to non-toxic levels.Microstructure and mineralogical analysis of the biocemented samplesTo investigate the influence of different biocementation levels on the erodibility of the treated sand grains, FESEM imaging was conducted for light biocemented samples (BS3-BC1) and heavy biocemented samples (BS3-BC3). While precipitated crystals were observed to be growing on the grooves of sand grains in the light biocemented sample (BS3-BC1), bridging of sand grains with rhombohedral crystals was observed in the heavy biocemented sample (BS3-BC3), as shown in Fig. 8. The effective calcium carbonate bridging between sand grains increases the frictional and cohesive property of sand grains55,56, leading to a substantial reduction in the erodibility of the soil. Bacterial imprints were observed in both cases, suggesting the precipitation to be biodgenic14. Further EDX analysis on a bridged sand grain (Supplementary Fig. 5) suggested an abundance of silicon and oxygen on the sand grains with a trace amount of chlorine and calcium. This indicates the presence of residual calcium chloride on silica grains. The EDX analysis on the grain bridge indicated the presence of calcium, carbon, and oxygen, suggesting CaCO3 precipitation. XRD analysis on treated and untreated sand confirmed the precipitation of calcite. Most of the peaks correspond to quartz (silica). In the biocemented sand sample, a visible peak of calcite was observed at around 29 degrees of 2Ɵ (Details in Supplementary Fig. 6). Therefore, the incorporation of microbial calcite as a binding agent for loose grain silica soil was found to reduce the soil erodibility.Figure 8FESEM images of the treated sand grains (a). Calcite crystal growing on the sand grains on BS3- BC1 sample (b). Calcite bridging in BS3-BC3 samples.Full size image More

Our study uniquely points to differences among scientific disciplines in data availability as published along with the article and upon request from the authors. We demonstrate that in several disciplines such as forestry, materials for energy and catalysis and psychology, critical data are still unavailable for re-analysis or meta-analysis for more than half of the papers published in Nature and Science in the last decade. These overall figures roughly match those reported for other journals in various research fields8,11,13,22, but exceed the lowest reported values of around 10% available data13,23,24. Fortunately, data availability tends to improve, albeit slowly, in nearly all disciplines (Figs. 3, 7), which confirms recent implications from psychological and ecological journals13,31. Furthermore, the reverse trend we observed in microbiology corroborates the declining metagenomics sequence data availability22. Typically, such large DNA sequence data sets are used to publish tens of articles over many years by the teams producing these data; hence releasing both raw data and datasets may jeopardise their expectations of priority publishing. The weak discipline-specific differences among Nature and Science (Fig. 2) may be related to how certain subject editors implemented and enforced stringent data sharing policies.After rigorous attempts to contact the authors, data availability increased by one third on average across disciplines, with full and at least partial availability reaching 70% and 83%, respectively. These figures are in the top end of studies conducted thus far8,22 and indicate the relatively superior overall data availability in Science and Nature compared with other journals. However, the relative rates of data retrieval upon request, decline sharing data and ignoring the requests were on par with studies covering other journals and specific research fields10,12,25,26,28. Across 20 years, we identified the overall loss of data at an estimated rate of 3.5% and 5.9% for initially available data and data effectively available upon request, respectively. This rate of data decay is much less than 17% year−1 previously reported in plant and animal sciences based on a comparable approach24.While the majority of data are eventually available, it is alarming that less than a half of the data clearly stated to be available upon request could be effectively obtained from the authors. Although there may be objective reasons such as force majeure, these results suggest that many authors declaring data availability upon contacting may have abused the publishers’ or funders’ policy that allows statements of data availability upon request as the only means of data sharing. We find that this infringes research ethics and disables fair competition among research groups. Researchers hiding their own data may be in a power position compared with fair players in situations of big data analysis, when they can access all data (including their own), while others have more limited opportunities. Data sharing is also important for securing a possibility to re-analyse and re-interpret unexpected results9,32 and detect scientific misconduct25,33. More rigorous control of data release would prevent manuscripts with serious issues in sampling design or analytical procedures from being prepared, reviewed and eventually accepted for publication.Our study uniquely recorded the authors’ concerns and specific requests when negotiating data sharing. Concerns and hesitations about data sharing are understandable because of potential drawbacks and misunderstandings related to data interpretation and priority of publishing17,34 that may outweigh the benefits of recognition and passive participation in broader meta-studies. Nearly one quarter of researchers expressed various concerns or had specific requests depending on the discipline, especially about the specific objectives of our study. Previous studies with questionnaires about hypothetical data sharing unrelated to actual data sharing reveal that financial interests, priority of additional publishing and fear of challenging the interpretations after data re-analysis constitute the authors’ major concerns12,35,36. Another study indicated that two thirds of researchers sharing biomedical data expected to be invited as co-authors upon use of their data37 although this does not fulfil the authorship criteria6,38. At least partly related to these issues, the reasons for declining data sharing differed among disciplines: while social scientists usually referred to the loss of data, psychologists most commonly pointed out ethical/legal issues. Recently published data were, however, more commonly declined due to ethical/legal issues, which indicates rising concerns about data protection and potential misuse. Although we offered a possibility to share anonymised data sets, such trimmed data sets were never obtained from the authors, suggesting that ethical issues were not the only reason for data decline. Because research fields strongly differed in the frequency of no response to data requests, most unanswered requests can be considered declines that avoid official replies, which may harm the authors’ reputation.Because we did not sample randomly across journals, our interpretations are limited to the journals Nature and Science. Our study across disciplines did not account for the particular academic editor, which may have partly contributed to the differences among research fields and journals. Not all combinations of disciplines, journals and time periods received the intended 25 replicate articles because of the poor representation of certain research fields in the 2000–2009 period. This may have reduced our ability to detect statistically significant differences among the disciplines. We also obtained estimates for the final data availability for seven out of nine disciplines. Although we excluded the remaining two disciplines from comparisons of initial and final data availability, it may have slightly altered the overall estimates. The process of screening the potentially relevant articles chronologically backwards resulted in overrepresentation of more recent articles in certain relatively popular disciplines, which may have biased comparisons across disciplines. However, the paucity of residual year effect and year x discipline interaction in overall models and residual time effect in separate analyses within research fields indicate a minimal bias (Figure S1).We recorded the concerns and requests of authors that had issues with initial data sharing. Therefore, these responses may be relatively more sceptic than the opinions of the majority of the scientific community publishing in these journals. It is likely that the authors who did not respond may have concerns and reasons for declining similar to those who refused data sharing.Our experience shows that receiving data typically required long email exchanges with the authors, contacting other referred authors or sending a reminder. Obtaining data took on average 15 days, representing a substantial effort to both parties39. This could have been easily avoided by releasing data upon article acceptance. On the other hand, we received tips for analysis, caution against potential pitfalls and the authors’ informed consent upon contacting. According to our experience, more than two thirds of the authors need to be contacted for retrieving important metadata, variance estimates or specifying methods for meta-analyses40. Thus, contacting the authors may be commonly required to fill gaps in the data, but such extra specifications are easier to provide compared with searching and converting old datasets into a universally understandable format.Due to various concerns and tedious data re-formatting and uploading, the authors should be better motivated for data sharing41. Data formatting and releasing certainly benefits from clear instructions and support from funders, institutions and publishers. In certain cases, public recognition such as badges of open data for articles following the best data sharing practices and increasing numbers of citations may promote data release by an order of magnitude42. Citable data papers are certainly another way forward43,44, because these provide access to a well-organised dataset and add to the authors’ publication record. Encouraging enlisting published data sets with download and citation metrics in grant and job applications alongside with other bibliometric indicators should promote data sharing. Relating released data in publicly available research accounts such as ORCID, ResearcherID and Google Scholar would benefit both authors, other researchers and evaluators. To account for many authors’ fear of data theft17 and to prioritise the publishing options of data owners, setting a reasonable embargo period for third-party publishing may be needed in specific cases such as immediate data release following data generation45 and dissertations.All funders, research institutions, researchers, editors and publishers should collectively contribute to turn data sharing into a win-win situation for all parties and the scientific endeavour in general. Funding agencies may have a key role here due to the lack of conflicting interests and a possibility of exclusive allocation to depositing and publishing huge data files46. Funders have efficient enforcing mechanisms during reports periods, with an option to refuse extensions or approving forthcoming grant applications. We advocate that funders should include published data sets, if relevant, as an evaluation criterion besides other bibliometric information. Research institutions may follow the same principles when issuing institutional grants and employing research staff. Institutions should also insist their employees on following open data policies45.Academic publishers also have a major role in shaping data sharing policies. Although deposition and maintenance of data incur extra costs to commercial publishers, they should promote data deposition in their servers or public repositories. An option is to hire specific data editors for evaluating data availability in supplementary materials or online repositories and refusing final publishing before the data are fully available in a relevant format47. For efficient handling, clear instructions and a machine-readable data availability statement option (with a QR code or link to the data) should be provided. In non-open access journals, the data should be accessible free of charge or at reduced price to unsubscribed users. Creating specific data journals or ‘data paper’ formats may promote publishing and sharing data that would otherwise pile up in the drawer because of disappointing results or the lack of time for preparing a regular article. The leading scientometrics platforms Clarivate Analytics, Google Scholar and Scopus should index data journals equally with regular journals to motivate researchers publishing their data. There should be a possibility of article withdrawal by the publisher, if the data availability statements are incorrect or the data have been removed post-acceptance30. Much of the workload should stay on the editors who are paid by the supporting association, institution or publisher in most cases. The editors should grant the referees access to these data during the reviewing process48, requesting them a second opinion about data availability and reasons for declining to do so. Similar stringent data sharing policies are increasingly implemented by various journals26,30,47.In conclusion, data availability in top scientific journals differs strongly by discipline, but it is improving in most research fields. As our study exemplifies, the ‘data availability upon request’ model is insufficient to ensure access to datasets and other critical materials. Considering the overall data availability patterns, authors’ concerns and reasons for declining data sharing, we advocate that (a) data releasing costs ought to be covered by funders; (b) shared data and the associated bibliometric records should be included in the evaluation of job and grant applications; and (c) data sharing enforcement should be led by both funding agencies and academic publishers. More

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