Ecology

Chemicals and reagents
Sodium chloride (S3014), potassium chloride (P9541), sodium phosphate dibasic (S3264), potassium phosphate monobasic (P9791), potassium bicarbonate (12602), ammonium chloride (A9434), ethylene diamine tetra acetic acid di-sodium salt (E6635), bovine serum albumin (BSA) (5482), absolute ethanol (100983), methanol (34860) were purchased from Sigma–Aldrich, St. Louis, MO, United States. CD 34, Sca 1, and CBA Flex Set which contains IL-3 (558346), IL-6 (558301), TNFα (558299), IFN γ (562233), G-CSF (560152), GM-CSF (558347), IL-1α (560157), IL-1β (560232), Mouse/Rat Soluble Protein Master Buffer Kit (558266) were procured from BD Biosciences, United States. May-Grunwalds Stain (S039) and Giemsa Stain Solution (TCL083) were procured from Hi-Media India.
1 L 1X PBS (8 g of sodium chloride, 0.2 g of potassium chloride, 1.44 g of sodium phosphate dibasic, 0.25 g of potassium phosphate monobasic to 1 L at pH 7.4), 1 L 1X RBC lysis buffer (1 g of potassium bicarbonate, 8 g of ammonium chloride and 0.03 g of di-sodium EDTA), 1% BSA in PBS, 70% ethanol in PBS, and may-grunwald-giemsa stain mixed in 3:1 ratio were prepared in the laboratory.
Animals and groupings
Pathogen free Strain ‘A’ male mice weighing 25.0–30.0 gm were received from Institute of Nuclear Medicine and Allied Science (INMAS) experimental animal facility at the age of 9 weeks, which is equivalent to young adult humans. Six mice per cage were housed under 25 ± 3 °C temperature and relative humidity of 30–70% in 12 h light/dark cycle with standard food and water. The study design strictly adhered to the guidelines approved by Institutional Animal Care and Use Committee (IACUC) of our institute, Institute of Nuclear Medicine and Allied Sciences (INMAS), Defence Research and Development Organization (DRDO), Delhi, India (Institute Animals Ethics Committee number: INM/IAEC/2019/01).
After 1 week of acclimatization under ambient conditions, mice were grouped for the survival assay according to localized gamma radiation dose i.e. 7, 9, 10, 12, 15, 17 and 19 Gy. Eighteen animals were assigned in each group for this assay.
For all other parameters mice were divided into two groups with six animals in each. Group 1, consisted of untreated or sham irradiated animals. Group 2 was exposed to 15 Gy localized irradiation. Mice were sacrificed at different time points (1, 2, 4, 7, 10, 15, 20, 25, and 30 days) post treatment. Hematopoietic stem cell marker CD 34 and Sca1 were measured on 1, 4, 7, and 10th day post-irradiation.
Irradiation
A Cobalt-60 teletherapy (Model: Bhabhatron-II, Panacea Medical Technologies Pvt Ltd, India) machine was used to irradiate the hinds of the three mice at a time (Fig. 1). The cobalt-60 beam was calibrated following IAEA TRS-398 protocol, with measurement done in water phantom (30 cm × 30 cm × 30 cm), for a field size 10 cm × 10 cm at source to surface distance (SSD) of 80 cm. A Farmer type, 0.6 cc volume, ionization chamber was utilised and the same was recently calibrated for absorbed dose to water (NDW) at Secondary Standard Dosimetry Laboratory (SSDL) of India. The measured absorbed dose rate (water, 10 cm × 10 cm, 80 SSD, Dmax) was 1.39 Gy/min.
Figure 1

Representative image of animal exposure with γ-rays in a field size of 2 cm × 35 cm.

Full size image

The localized bone marrow irradiation was done using single Posteroanterior (PA) beam with 2 cm × 35 cm field size at 80 cm SSD opened through secondary collimators of the machine. The 5 mm thick acrylic re-strainers were used to immobilize each mouse which also provides the build-up thickness for the irradiation. The dose prescription point was the surface of the hinds i.e. 5 mm below the surface of the re-strainer. The whole irradiation platform was placed on 5 cm thick acrylic slab to provide sufficient back scatter and all the air gaps between the three mice were filled with tissue equivalent gel bolus or wet cotton to compensate for missing side scatter. The prescription doses were absorbed dose to water and not corrected for any tissue heterogeneity.
The absolute and relative dosimetry of collimated field (2 cm × 35 cm) were performed using pin point (0.04 cc volume) ionization chamber and EBT3 (ISP, Wayne, USA) Gafchromic dosimetry films in solid water phantom. The response of the pin point chamber and EBT3 films was calibrated against the SSDL calibrated ionization chamber in solid water phantom at the depth of 5 cm and field size 10 cm × 10 cm in the same beam quality (i.e. cobalt-60). The film scanning was performed using Epson 10000XL flatbed scanner as per the manufacturers scanning protocol. The beam profiles were obtained from the scanned films and the full width at half maximum (FWHM) in transverse direction was 1.78 cm for the opening of 2.0 cm. The dose uniformity was better than 4% in central 80% of the field. The absolute dose rate (dose to water, dmax, 2 cm × 35 cm, SSD 80 cm) measured at the centre of the field was 1 Gy/min. The overall uncertainty in dose calculations is 6.5% with enhancement or coverage factor (k = 2) at 95% confidence. The main body of the mice was covered with 15 mm lead to prevent any scatter radiation reaching at other body parts of the animal. The surface dose reaching at the shielded body parts of the mice was measured using 0.4 cc ionisation chamber. The measured mean surface dose was 0.024 ± 0.014% of the open field dose. This dose is negligible and considered to be acceptable.
Survival assay in mice
For survival assay, 18 mice from each experimental group i.e. 7, 9, 10, 12, 15, 17 and 19 Gy, were irradiated at a fixed dose rate of 1 Gy/min. Groups were inspected daily for their morbidity and mortality status for a total duration of 30 days. All the surviving mice were euthanized humanely using intra-peritoneal injection (i.p.) with dexmedetomidine (0.3 mg/kg) in combination with ketamine (190 mg/kg) at the completion of the observation period.
Validation of hematopoietic syndrome model
The model of hematopoietic syndrome was validated with localized radiation of 15 Gy as this was the maximum dose at which all the animals survived as observed in the survival results. Mice were euthanized using intra-peritoneal injection (i.p.) with dexmedetomidine (0.3 mg/kg) in combination with ketamine (190 mg/kg) at 1, 2, 4, 7, 10, 15, 20, 25, and 30th day time points. Further analysis such as organ weight, cell counting, and serum cytokines measurement assays were conducted on various organs such as femur bone, spleen, thymus, lungs, kidneys (L), kidneys (R), liver and heart and blood at above mentioned time points. Hematopoietic stem cell markers (CD 34 and Sca 1) were measured in bone marrow cells of mice at 1, 4, 7, and 10th day time points.
Body and organ weights
The control and 15 Gy locally irradiated group animals were sacrificed at 1, 4, 7, 10, 15, 20, 25, and 30th day time points. The organs (spleen, thymus, lungs, kidneys (L), kidneys (R), liver and heart) were dissected out and weighed individually. Relative organ weight was calculated as the ratio between organ weight and body weight.
Haematology
The blood samples were collected from untreated and 15 Gy localized radiation group at 1, 4, 7, 10, 15, 20, 25, and 30th day time points in EDTA vial by cardiac puncture. 20 µl of collected blood from each experimental animal was taken for haematology and analysed using Nihon Kohden Celltac α, Tokyo, Japan, a fully automatic 3 part haematology analyzer.
Bone marrow cell counting
Total bone marrow cells were flushed out at 1, 4, 7, 10, 15, 20, 25 and 30th day points in 1 ml PBS from both femurs of the untreated mice and 15 Gy localized radiation group. The PBS containing cells was centrifuged at 2000 rpm for 8 min and the supernatant was discarded. The cells were washed with 1 ml PBS and the cell pellet was re-suspended in 1 ml of PBS. The re-suspended sample was diluted as required. The cells were then counted using improved Neubauer chamber under Olympus BX-63 microscope.
Bone marrow smears study
Bone marrow cells collected at 1, 4, 7, 10, 15, 20, 25, and 30th day post-irradiation from different treatment groups were centrifuged at 2000 rpm for 8 min and re-suspended in 50 μl of Fetal Bovine Serum (FBS). A small drop of cells suspension was dropped on a clean microscopic slide and then smeared thinly over an area of 2–3 cm by pulling another glass slide held at a 45° angle. Cells were fixed with methanol and stained with may-grunwald-giemsa. Slides were then analysed using Olympus BX-63 microscope.
Splenocytes and thymocytes counts
The organs excised at 1, 4, 7, 10, 15, 20, 25, and 30th day time-points were cleaned in chilled PBS. Using sterile-chilled frosted slides both the thymus and spleen were minced into a cell suspension and which was further centrifuged at 2000 rpm for 8 min. After centrifugation the supernatant was discarded. The RBCs were lysed using RBC lysis buffer and the cells were washed with 1 ml PBS. The cells were then counted using improved Neubauer chamber under Olympus BX-63 microscope.
Measurement of hematopoietic stem cell marker CD 34 and Sca1
Bone marrow cells were isolated from both the femurs from various treatment groups at different time points. Cell were washed with chilled PBS and fixed with 70% chilled ethanol and stored overnight at – 20 °C. Following day, five million cells were blocked with 1% BSA-PBS and stained with CD 34 and Sca 1 cell-surface markers for 20 min at room temperature. 10,000 cells from each sample were analyzed using FACS LSR II (BD Biosciences, San Jose, CA) and results were visualized by the BD FACSDiva V7 software (BD Biosciences, San Jose, CA).
Cytokines expression changes
Mice blood samples were collected in BD serum separation tube at different time-points post treatment (1, 4, 7, 10, 15, 25, and 30 days) via. cardiac puncture from different treatment groups. Samples were incubated at room temperature for 2 h and after incubation centrifuged at 6000g for 15 min. Serum was separated and stored at − 80 °C until analysis. The Levels of IL-3, IL-6, TNFα, IFN γ, G-CSF, GM-CSF, IL-1α,and IL-1β cytokines in mice serum were determined by using respective BD Cytometric Bead Array (CBA) Flex Set (BD Biosciences, USA) on dual laser flow analyzer (LSR-II, Becton Dickinson Biosciences, USA) according to manufacturer’s instructions. Results were analysed using FCAP Array V3 software (BD Biosciences, San Jose, CA).
Statistical analysis
All values obtained in our results are represented as mean ± SD of three independent replicates. The 30 day survival data was plotted using Kaplan–Meier analysis. The difference between the experimental groups was evaluated by one-way analysis of variance, with Newman–Keuls multiple comparison test (V, 8.01; GraphPad Prism, San Diego, CA, USA). The comparisons were made among the untreated and 15 Gy locally irradiated groups for all experimental parameters except the survival study. A value of p  More

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Leaf profitability
We calculated the economic profitability of leaves and analysed the patterns in relation to leaf size, environment and durability (longevity). There was wide variation in leaf profitability with a mean value (± SD) of 3.4 ± 3.5% day−1 and 5th/95th percentile range of 0.29–10.3% day−1. There are no previous studies reporting leaf profitability values for direct comparison, but they can be re-calculated based on published values for leaf payback time. For example, Williams et al.21 reported payback time values in several Piper species from a Mexican rainforest, corresponding to leaf profitability values between 0.01 and 33% day−1. Poorter et al.23 calculated payback times corresponding to leaf profitability values of 1.25–50% day−1 , depending on species type, light environment, and growth conditions (very high values were observed for seedlings grown under non-limiting, hydroponic conditions). The mean values of our study are lower, but in line with values calculated from payback time of Kikuzawa and Lechowicz25 (2.2 ± 2% day−1), because they consider the mean labour time and the favourable period length, as we also applied in our calculations (see “Methods” and Supplementary File S2 online).
One factor that could influence profitability is the size of a production unit. For example, a large leaf may imply a higher cost required for structural support; therefore, the changes in profitability will depend on how gains and expenses vary with size. As it turned out, we found that leaf profitability was positively related to leaf size (Fig. 2A), but the percentage of variance explained was not especially high (R2 = 0.07, P  More

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Impact of glacial retreat on the benthic ecosystem
Most enriched POM δ13C concentration in the inner cove location (B2) indicates a potential melt-water input near the glacier (Table S2). The δ13C signature of diatoms showed a similar spatial concentration gradient along the cove, but was slightly more enriched than POM δ13C. This signature of freshwater influence has also been detected in other Antarctic regions. For example, the enriched δ13C of POM and diatoms in Potter Cove was recently reported16. In the enclosed environment beneath glaciers, δ13C might be enriched due to increased HCO3− utilization and production of organic materials17. The POM and diatom δ15N concentrations showed the lack of parallel gradients over the study area. The POM δ15N, especially phytoplankton values, is affected by their nutrient sources. Snow melt-water input occasionally appears from the local creeks throughout the Marian Cove, and the melt-water is associated with the nutrient input as well. Thus, the POM and diatom δ15N concentrations seemed to reflect the melt-water input throughout the cove.
The coastline of the inner locations (B1–B2;  More

Nutrient, FOM, and physiochemical contents of the fecal manures
For the three main fertility nutrients (N, P and K) in the fecal manures (Table 1a) the E manure contained the highest N level at 80 µg/g, 16-fold more than the other samples. In addition, it had a high P level of 100 µg/g (along with PC1 and PC3) compared with an average of 34.66 µg/g for the others, and a moderate K level of 150 µg/g (others ranged from 125.00 to 350.00 µg/g. The FOM content ranged from 1.00 to 1.50% for all the animal manures (Table 1a). For the general physiochemical properties, chicken manures showed a relatively high salinity (Table 1b: 3.52 ± 0.28 to 4.01 ± 0.64 ppt), and these ionic salts caused a high conductivity (11.27 ± 0.69 to 12.79 ± 0.08 mS/cm) and high water saturation (73.29 ± 0.40 to 80.56 ± 3.17 mS/cm), giving less available water for plant roots. A moderate level of salinity, conductivity and water content, such as those in E, are generally preferred for farming soil. The water content of the manure was lowest in G2, goats fed with P. purpureum (23.75 ± 3.07%), but increased two-fold in G1 goats fed with D. eriantha (49.35 ± 6.08%), suggesting a different type of grass feed might confer different fecal liquid and dry contents, or the chemical composition influenced the water activity in the goat’s gut. The R manure also had a low water content (41.53 ± 5.57%).
Table 1 Characteristics of (a) NPK and FOM, and (b) physiochemical levels of the different animal fecal manures.
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The visual observation of each manure was in accord with the reported water content, with a dry and hard texture (insufficient moisture) for G1, G2, and R manures, and a wet texture for the chicken, cattle, pig, and buffalo manures. Too much water in the soil can adversely affect aeration, where the plant’s roots receive insufficient oxygen and rot. Moreover, most plants prefer a slightly acidic soil pH of 6.2–6.8, which was found in the R, MB and E composts (Table 1b). The manure pH can change through reactions such as organic matter decomposition that affects the availabilities of NPK39.
From the overall comparison of the NPK nutrients and physiochemical properties, the fecal manures from the Phuparn chicken species might be less suitable as a fertilizer because of the poor N level, and high level of salts and conductivity. Indeed, the manures from most species contained a low N level, and those from goat and rabbit also had a relatively low water content (insufficient water for a plant to absorb nutrients from the soil through the roots, to the trunk, leaves and fruits). A moderate water content in the manure was appropriate. But of course, a somewhat low water level could be adjusted by adding water. The biophysiochemical quality analyses of the manures suggested that the E manure would be appropriate as a fertilizer because of the enhanced NPK levels, low salinity, low conductivity, slightly acidic-neutral pH, and a moderate water content (Table 1b).
Quantification of total bacteria in the fecal manures
The total number of bacteria in copies/g DW fecal manure was derived from the 16S rRNA gene qPCR. Figure 1a showed the data were consistent between independent triplicate samples, and that the E and R manures had the lowest bacterial counts (at 2.1 × 109 and 2.5 × 109 copies/g DW, respectively). The other animal fecal manures contained more than 5 × 109 copies/g DW, and the greatest bacterial load was found in PC2 and MB at 2.6 × 1010 and 1.9 × 1010 copies/g DW, respectively, while PC1 and PC3 had a significantly lower level (p  98% of the sequencing coverage of taxonomic compositions at the genus and species levels, respectively (Table 2). The average Good’s coverage indices were 99.54% and 99.43% for the genus and species levels, respectively (Supplemental Table 1). This was consistent with the plateau rarefaction curves, showing the frequencies of OTUs become constant despite increasing sequencing reads, meaning a sufficient sequencing coverage was obtained (Supplemental Fig. 1).
Table 2 Good’s coverage indices (estimated sequencing coverage) and alpha diversity indices of bacterial taxonomic profiles by 16S rRNA gene sequences at the (a) genus and (b) species levels.
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Combining the count of total 16S rRNA gene copies with the OTU percent compositions gave the quantitative number of copies of each OTU in a community. These quantitative microbiota data were then used to compute the alpha and beta diversity measurements. The alpha diversity revealed that the microbiota of E had the relatively most diverse OTUs at both the genus and species levels (Chao richness, Fig. 2a,c), regardless of having the lowest total bacterial count (Fig. 1). The low total bacterial abundance but high diversity in E underlined that the various OTUs of bacteria in E might be present in small numbers when compared to the copy numbers of OTUs in the other animal manures. Note that the alpha diversity obtained by considering the distribution of general OTUs among the different animal manures were similar (Shannon diversity, Fig. 2b,d).
Figure 2

Alpha diversity measurements of OTU compositions at (a,b) genus and (c,d) species levels, by richness (Chao) and evenness (Shannon). Box plot with bar representing the mean from three sequencing replicates, and asterisk (*) indicates a statistically significant difference by one-way ANOVA at p  1% abundance). In (b), the OTUs where Mothur could not identify the genus name were denoted by small letters (p_ abbreviates phylum; o_, order; and f_, family) to the deepest taxonomic names that could be identified.

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Relative frequencies of plant symbiotic and pathogenic bacterial genera
Plant symbiosis and pathogenic bacteria were analysed across the different animal manures. Manures PC1-3, G1, G2 and CC demonstrated generally abundant symbiotic bacteria comprised of the genera Pseudomonas, Bacillus, Arthrobacter, Flavobacterium, Alcaligenes and Streptomyces (Fig. 4a). For examples, PC2 contained abundant Alcaligenes (1.16 × 1010 cells/g DW), Pseudomonas (3.35 × 109), Flavobacterium (2.82 × 108) and Arthrobacter (3.8 × 108). Streptomyces was only found in G1, G2 and E in moderate numbers (5.9–29.0 × 106 cells/g DW).
Figure 4

Comparative number of bacterial genera categorized as plant (a) symbiotic or (b) pathogenic genera across the different animal manures. Data represented mean ± S.D. List of bacteria categorized as plant symbionts and pathogens were downloaded from the Virulence Factor Database (VFDB).

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For the plant pathogenic bacteria, high levels were found in the manures that also contained high levels of plant symbiosis bacteria (PC1-3, G1, G2 and CC), except for E, plus the other manures, such as S, D and MB. The E had none of VFDB-listed plant pathogens. Thus, all manures except for E contained plant pathogenic bacteria, and these were from Escherichia, Shigella, Enterococcus, Clostridium, Acinetobacter, Treponema, Staphylococcus and Bacteroides (Fig. 4b). This finding correlated with the percent abundance of genera (Fig. 3b) where, examples, Treponema were relatively high in PCO and PC3 at 2.03 × 108 and 1.31 × 108 cells/g DW, respectively. Escherichia were relatively low in R and DC at 1.15 × 105 and 2.06 × 105 cells/g DW, respectively. In contrast, only E did not contain any VFDB-listed plant pathogenic bacteria suggesting that E offers a plant pathogen-free organic fertilizer.
Relationship among bacterial communities, and statistical correlation with the biophysiochemical properties
The NMDS demonstrated both the reproducibility of the data between the independent triplicate samples, except for R and PCO. The larger variation in bacterial communities were found generally between the manures from different animal species, while the minor variation in bacterial communities were found between the breeds, or the feeding diets. For examples, the variation in quantitative microbiota profiles between G1, G2 and E, compared with PC1-3 (p = 0.085) and MB (p = 0.59) (Supplemental Fig. 2). Indeed, the quantitative microbiota structures belonging to the six animal manures that had all the VFDB’s categorized plant pathogens (PC, S, R, D and MB, except PCO) were rather distant from E (p = 0.101, 0.052, 0.089, 0.104 and 0.099, respectively).
Seven parameters (NPK and four physiochemical properties) were analyzed for possible Pearson’s correlation with any of the quantitative microbiota structures. The N level was strongly correlated (p = 0.01) to the structures and in the same direction of the E (Fig. 5). The percent water, salinity and conductivity characteristics were significant and associated in the direction opposite to E, and also to the G1, G2 and PCO microbiota structures. On the other hand, the PC1, PC2 and MB microbiota structures were strongly associated with the water content, salinity and conductivity. These parameters are suggested to be important in controlling the diversity of microbiota structures.
Figure 5

Relationship among bacterial communities via NMDS constructed from thetayc distance coefficients among quantitative microbiota (stress value = 0.15, R2 = 0.86), and Pearson’s correlation with nutrients and physiochemical properties (AMOVA, p  More