Philippa Kaur

Analysis of COs and LCOs from fungal exudates
The list and sources of the 59 species of fungi and three species of oomycetes (Heterokontophyta) used in the study are presented in Supplementary Data 1–3. The fungal species examined are representatives of each sub-phyla within five phyla (out of eight phyla) of the Kingdom Fungi30. The absence of contaminants in the fungal and oomycete strains was systematically checked by PCR by using the specific primers ITS1F/ITS4 and fD1/rP231,32 (Supplementary Fig. 2). The inoculum type (cells, mycelium, spores, or zoospores), culture media and culture times used for each strain are indicated in Supplementary Data 1–3.
Fungi and oomycetes producing mycelia were pre-cultivated in Petri dishes on the solid media gelled with agar as indicated in Supplementary Data 233,34. Once the mycelium had covered the dish, plugs of the mycelium were transferred to Sylon-coated culture flasks35 or to 6.7 × 11.4 cm flat-bottom PYREX® flasks (Corning, Inc. Corning, NY), or for the Russulales to 25 × 95 mm flat-bottom culture tubes (PhytoTech), respectively, filled with 50 ml or 12 ml of the appropriate liquid medium to produce and collect exudates (Supplementary Data 2). In addition, using a separate experimental method, C. geophilum, G. stellatum, Lepidopterella palustris, Leptosphaeria maculans, S. sclerotiorum, and the species of Amanita, Hebeloma, and Paxillus were pre-cultivated as above but they were inoculated on a cellophane membrane laid on the solid medium. This membrane was used to transfer agar-free mycelium to Petri dishes filled with deionized sterile water or with liquid culture medium in order to produce and collect exudates (Supplementary Data 2).
For the anaerobic Neocallimastigomycetes, Neocallimastix californiae, Piromyces finnis, Anaeromyces robustus, and Caecomyces churrovis, 1 ml of fungal zoospores was used to inoculate 20 ml of modified minimal Medium C in a 60 ml borosilicate serum bottles containing 0.2 g switchgrass while sparging with CO236,37. Fungal cultures were incubated anaerobically 6 days before collecting the exudates.
For fungi (except AM fungi) producing cells, spores, or zoospores, 106 of these propagules were produced and collected according to published methods33,37,38,39,40,41,42,43,44,45,46,47,48. Propagules were inoculated directly in five independent Sylon-coated flasks with 50 ml liquid medium per species. AM cultures were propagated by in vitro mycorrhizal root organ cultures in solid M medium containing Phytagel (Sigma-Aldrich) and collected after solubilization of Phytagel39,49. Exudates from the AM fungal strains were collected from 10,000 spores germinating in 10 ml liquid medium for 10 days.
The various liquid media (broth or water), enriched with exudates, were filtered under sterile conditions through a 0.22 µm Millipore Express® PES membrane (MilliporeSigma, Darmstadt, Germany) prior to being analyzed in the bioassays.
One hundred to 400 ml of culture filtrates, depending on the fungal cultures, were extracted twice with butanol (1 : 1 v/v). The pooled butanol phases were washed with distilled water and evaporated under vacuum. The dry extract was re-dissolved in 4 ml water : acetonitrile (ACN) (1 : 1 v/v) and dried under nitrogen. This crude extract was resuspended in 1 ml of 20% ACN in water and separated on Hypersep C18 (500 mg, 3 ml, Thermo Fisher Scientific) by sequential elution with 3 ml each of 20%, 50%, and 100% ACN in water, respectively. The eluted samples were then dried under nitrogen. Occasionally, for further purification, the 50% eluate was resuspended in 75% ACN in water and separated on Chromabond HILIC (500 mg, 3 ml) by sequential elution with 3 ml each of 100%, 80 and 75% ACN in water. The eluates were then dried under nitrogen.
The presence of LCOs in filtered crude exudates (1× or 10×) or in the butanol fractions of media were assayed by root hair branching in V. sativa, which is induced by nsLCOs50, by root hair branching in M. truncatula accession Jemalong A17, which is induced by sLCOs, and by expression of MtENOD11 using the pENOD11:GUS transcriptional fusion in M. truncatula, which is also induced by (s)LCOs4,51.
The root hair branching assays in V. sativa and M. truncatula used the method of Cope et al.9. Eight young seedlings (3–7 days old) were treated with the fungal exudates, with the same concentration of solvent (negative controls), or with Nod factors purified from Rhizobium leguminosarum biovar viciae or Sinorhizobium meliloti supernatant at a concentration of 10−8 M (positive controls). One milliliter of fungal crude exudates or 40 µl of butanol fractions were applied on each seedling primary root.
The MtENOD11 gene expression assay was performed as in Maillet et al.4. Two kinds of samples were tested: butanol extracts diluted 100 times in water and HILIC column fractions diluted 10 times. Forty microliters of these solutions were applied to the primary root of each seedling for 16 hours. Seven to ten seedlings were tested by sample and compared to mock treatment (0.005% EtOH in water or 5% ACN in water). Plants were stained for 6 h. An arbitrary scale was used to quantify GUS (beta-glucuronidase)-staining (Supplementary Fig. 8).
Standard LCO compounds (non-sulfated C16:0 LCO IV, sulfated C16:0 LCO IV, non-sulfated C18:1 LCO IV, sulfated C18:1 LCO IV) were synthesized at CERMAV (Grenoble, France) and were used at 10−5 M in ACN/water (1/1, v/v) to determine retention times and to optimize HPLC/QTRAP tandem MS detection by MRM4,12. The UltiMate 3000 HPLC system (Dionex Corporation) was equipped with an Acquity C18 reversed-phase column (2.1 × 100 mm, 1.7 µm, Waters Corporation). Samples of 10 µl were injected. The elution was done at a constant flow rate of 450 µl min−1 using solvent A, water:acetic acid (1000 : 1, v-v) and solvent B, ACN, as follows: 30% B for 1 min, followed by a 30–100 % B during 8 min, followed by isocratic elution with 100% B for 2 min. A QTRAP 4500 mass spectrometer (Applied Biosystems, Foster City, USA) equipped with an electrospray ionization source in the positive ion mode was used to analyze samples in the MRM mode or in the EMS–EPI mode (see below). For the MRM mode analyses, from the known substitutions and chitin lengths already described for Nod factor structures, we created a database of all possible combinations of structures, including new ones never described before, with their corresponding precursor proton adduct ion [M + H]+ and product B ions: in total, 76,386 precursor ions, 2,598,159 theoretical combined structures, and 358,473 MRM transitions (Supplementary Data 5). Given that the number of MRM transitions to be selected for each analysis must be reasonably low to ensure proper sensitivity, we have selected the most commonly described Nod-LCOs (corresponding to 990 MRM transitions). This highly sensitive, targeted, analytical approach was suitable for samples containing low concentrations of molecules. For samples with higher concentrations of molecules, full scan EMS–EPI analyses were performed. During EMS analysis, major precursor ions are selected automatically, and, after the collision, EPI analysis accumulates their product ions in the trapping module. From this data set, we selected only the precursor ions containing 3 to 6 GlcNAc. This more comprehensive mode could only be used with P. adelphus, P. involutus, and G. rosea LCO-rich samples.
Short COs were separated and analyzed using the same LC-MS system, equipped with an hypercarb column (5 μm, 2 × 100 mm; Hypercarb, Thermo). Samples of 10 µl were injected. The elution was done at a constant flow rate of 400 µl min−1 using solvent A, water : acetic acid (1000 : 1, v-v) and solvent B, ACN, as follows: 100% A for 1 min, then 100–50% A in 30 min then 50–0% A in 3 min. COs were identified in the MRM mode by monitoring the transitions from precursor proton adduct ion [M + H]+m/z 628 (CO3), 831 (CO4), 1034 (CO5), or 1237 (CO6) generating after collision-induced dissociation (CID) the common product B ion m/z 204, comparatively to standard solutions (10−7 M in water). The capillary voltage was fixed at 4500 V and the source temperature at 400 °C. Fragmentation was performed by CID with nitrogen at a collision energy of 22–54 V; declustering potential was 90–130 V, optimized for each synthetic molecule available. Data processing was performed using Analyst 1.6.1 software (AB Sciex).
Experiments with A. fumigatus
A. fumigatus strain Af293 was grown in standard 90 mm Petri dishes on solid glucose minimal medium (GMM) and placed in the dark at 37 °C for 48 h52. Ten milliliters of 80% Tween 20 (Acros Organics, New Jersey) in sterile MiliQ water were added to the dishes and agitated with a sterile L-shaped cell spreader (Thermo Fisher Scientific, Waltham, MA) to collect spores. The spore suspension was sterilely transferred to a 50 ml polypropylene sterile Falcon® Centrifuge Tubes (Corning, Corning, NY). The spore suspension was homogenized by vortexing at maximum speed, and a 1 : 10 dilution was prepared with sterile MiliQ water, which was used to count spores using a hemocytometer. Afterward, spore suspension was adjusted to 106 spores with 80% Tween 20 in sterile MiliQ water44.
Spores were germinated in GMM liquid broth supplemented with various LCOs, COs, and fatty acids at a final concentration of 10−8 M. All LCOs and COs stock solutions were in 0.005% aqueous ethanol. The LCOs used were as follows: sulfated C16:0 LCO, non-sulfated C16:0 LCO, sulfated C18:1 LCO, and non-sulfated C18:1 LCO. The COs used were CO4, CO5, and CO8 (IsoSep, Tullinge, Sweden). The fatty acids used were palmitic and oleic acids. The negative control for these analyses was 0.005% aqueous ethanol, the solvent in which the LCO and CO stocks were prepared. The spore concentration was adjusted to 106 spores per ml of medium. One milliliter of spore suspension with the treatment of LCOs or COs were distributed into two replicate wells of a sterile Costar® 24 clear wells round, flat-bottom plate (Corning, Corning, New York) and the cells were incubated at 37 °C for 3 h. They were then observed at 1 h intervals over 21 h using a Nikon Ti inverted microscope with a ×40 objective and ten pictures were taken for each well every hour. Over 200 spores were scored for germination in each well. After 12 h of incubation, the length of the germinating apical hypha and the number of secondary branches per apical hypha were scored for over 200 germinated spores per well. Four independent experiments were performed. No differences between experiments were observed. Dose–response experiments were carried out in the same way, except that the spores were treated with a range of concentrations of sulfated C16:0 LCO(s) from 10−6 to 10−13 M.
Spores of A. fumigatus were grown in GMM supplemented with either 10−8 M sulfated C16:0 LCO or 0.005% ethanol as a negative control. The density was adjusted to 106 spores per ml of medium and the cultures were maintained at 37 °C on a New Brunswick Scientific Excella E25 incubator shaker (Eppendorf, Hamburg, Germany) at 250 r.p.m. The spores were collected after 30 and 120 min by filtering the liquid broth through sterile cheesecloth. Spores were completely removed from the cheesecloth with a sterile spatula and placed into 1.5 ml FisherbrandTM Premium Microcentrifuge tubes (Thermo Fisher Scientific, Waltham, MA). Four independent cultures were replicated per treatment and time point. Immediately after spore collection, tubes were placed in liquid nitrogen for 10 min. The spores were ground to a fine powder in liquid nitrogen and transferred into 50 ml centrifuge tubes. Total RNA was extracted by using QIAzol Lysis Reagent (Qiagen, Hilden, Germany) according to the manufacturer’s instructions but with an additional phenol : chloroform : isoamyl alcohol (24 : 1 : 1) extraction step before RNA precipitation. For RNA sequencing (RNA-Seq), total RNAs were further purified by using the RNeasy Mini Kit (Qiagen). RNA samples were digested with DNase and stored at −80 °C for further use. A NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific) was used to quantify and assess the purity of RNA. NanoDrop readings for samples were 112.24–491.44 ng µl−1.
Sixteen libraries of RNA-Seq single-end reads were prepared by using the TruSeq library preparation protocol and sequenced with an HiSeq 2500 sequencing system (Illumina, San Diego, CA). The 16 libraries corresponded to each of the four biological replicates for each of the four treatments. Read quality was assessed with FastQC 0.11.5. Read quality was excellent and adapter sequences were minimal, so reads were not trimmed. Paired-end reads were pseudo-aligned and quantified by using Kallisto 0.42.3 and the reference transcriptome of A. fumigatus Af293 (released 21 December 2012) downloaded from the Joint Genome Institute’s Genome Portal53,54. Bootstrap values were 100. Pairwise transcriptomic comparisons were made by using Sleuth version 0.30.055. We defined transcripts as differentially expressed if they had a false discovery rate (q-value)  More

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Dipoides sp. palaeoecology
The Bayesian mixing model indicates that Dipoides sp. consumed both woody plants and freshwater macrophytes in approximately equal proportions (Figs. 6 and 7), although it relied slightly more on freshwater macrophytes. This suggests that Dipoides sp. spent a greater proportion of time feeding in the water than on land.
Figure 7

(a) Proportion versus Source Boxplot generated using SIAR, indicating the relative proportion that moss, woody vegetation, and aquatic macrophytes contributed to the diet of Dipoides sp. at the Beaver Pond site. Darker shaded areas indicate highest probability of source proportion. The Proportion versus Source Boxplots for (b) extant Castor canadensis and (c) late Pleistocene Castoroides have been included for comparison. Note the differences in dietary Source data used to distinguish C. canadensis and Castoroides diet (primarily the sub-division of aquatic plants into categories based on habitat within the water column). b and c from Plint et al.13.

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The distribution of Dipoides sp. δ13Ccol and δ15Ncol is not entirely enclosed within the three primary producer functional groups analyzed (Fig. 6). This is likely the result of the relatively small plant macrofossil sample size. Submerged aquatic macrophytes, for example, are under-represented in the plant macrofossils available for stable isotope analysis. Macrophytes have highly variable δ13C and may have contributed more to Dipoides sp. diet than the mixing model suggests. Submerged macrophytes can be highly enriched in 13C because of physiological differences (primarily the use of 13C-enriched dissolved bicarbonate) or environmental conditions in the water column (i.e. boundary-layer effect)54,55,56. In addition, tree bark is more enriched in 13C than tree foliage57 and may have been a key resource for Dipoides sp.
The results of the dietary mixing model support the interpretation that woody plants were an important contributor to Dipoides sp. diet. It is likely that Dipoides sp. also used shrubs and trees as a source of construction material10,11, but more evidence is needed to confirm this. Similar to extant Castor, Dipoides sp. may have also demonstrated regional differences in diet, where northern and southern populations utilized different resources according to their availability.
Nitrogen content and C/N as indicators of forage quality
Plant macrofossil nitrogen content (N wt%) and C/N are indicators of forage quality and may be used to interpret the relative nutrition of dietary inputs. Plants with high N (wt%) contain more protein and energy—likewise, low N (wt%) correlates with low plant digestibility, high fiber and high lignin compound content58. Beaver Pond plant macrofossil N (wt%) and C/N are highly variable (Table 2, Fig. 5). Although there is considerable variability in C/N ratios depending upon which plant part was analyzed (i.e. seeds versus woody tissue), woody vegetation tends to have higher C/N ratios than macrophytes, and thus tends to be of lower food quality. However, the increased structural tissues in woody plants may have rendered them more effective winter cache foods.
In extremely seasonal environments such as the High Arctic, herbivores must use plant resources in a highly efficient manner. Herbivores must consume the highest quality forage possible during the brief growing season to maximize nutrient and energy gain. High quality forage typically includes young leaves with high nitrogen content, minimal structural (fibrous) tissues, and low defense compound content59,60.
Within the Beaver Pond macrofossil assemblage, pod grass (an emergent macrophyte) and birch have the highest nitrogen content and lowest C/N (Fig. 5). A larger sample set is necessary to confirm this observation; however, current data supports the conclusion that emergent macrophytes and deciduous broadleaf trees were among the more nutritious types of forage available to Dipoides sp. at the Beaver Pond site. It should be noted that forage quality is not the only factor that governs herbivore feeding behaviour. Animals may preferentially target plants with higher biomass to minimize energy expenditure traveling between forage sites or select plants that grow in locations that minimize the risk of predation.
The C/N of high Arctic shrubs decreases over the course of the growing season58. As there is no time-constraint on macrofossil deposition at the Beaver Pond site, variation in C/N may also be due to differences in plant phenological stage at time of incorporation into the peat layer. The incorporation of senescent plants into the peat deposit at the end of each growing season may in part account for the lower than expected macrofossil N (wt%) values reported from this site.
Beaver Pond site flora δ13C and δ15N
The Beaver Pond macrofossil assemblage contains a diverse range of terrestrial and freshwater plant species. The identified plant species in this study concur with previous interpretations that this was an open-forest landscape interspersed with shallow wetlands. Larch trees and cool-climate woody shrubs dominated the forest community. The wetlands supported both vascular macrophytes and dense assemblages of bryophytes.
The macrofossil δ13C are all within the range expected for primary producers utilizing the C3 photosynthetic pathway and accessing either ambient or dissolved atmospheric CO2 as their dominant carbon source. The δ15N of the macrofossils are also within the expected range for a riparian ecosystem in a cool climate biome.
While Dipoides sp. most likely consumed leafy tree branches and woody tissues (cambium), it is worth noting that plant seeds and cone bracts were analyzed in this study due to ease of macrofossil taxonomic identification. Leaf δ13C is typically lower than that of other plant parts61, although there is no clear pattern in intra-plant variation of δ15N.
Moss
Samples of the dominant Beaver Pond site bryophyte, Scorpidium (hooked scorpion moss), have very low δ13C for a primary producer (− 36.6 to − 34.6‰). This pattern is consistent with modern mosses collected from freshwater habitats in Subarctic and Arctic regions13,62,63,64.
Environmental conditions dictate moss δ13C rather than species-specific physiological differences. Peat mosses can grow partially or fully submerged in water. Given that mid-Pliocene atmospheric CO2 concentration levels were similar to modern (~ 400 ppm)15,65,66, moss exposed to the atmosphere would preferentially have used the abundant 12CO2, resulting in low δ13C. Alternatively, low δ13C in peat mosses can also indicate an underwater growing environment rich in 13C-depleted respired CO2 from surrounding plants62.
Moss macrofossil δ15N is relatively high for a photosynthetic organism (mean =  + 4.8‰). This is indicative of either the presence of 15N-enriched sources of bioavailable N (i.e. dissolved nitrates, organic proteins such as urea or amino acids), or increased nutrient availability45,61. Unlike vascular plants, mosses do not uptake compounds through their roots. Rather, they obtain nutrients from wet or dry deposition through their leaves67,68. Today, beaver ponds are considered to be N sinks, with elevated rates of bacterially mediated denitrification69. These bacterial processes result in 15N-enriched products that are readily dissolved and used by plants (including moss) living in an aqueous environment. Decomposition processes also increase plant δ15N over time47 and remineralized organic debris decomposing in wetlands may be particularly 15N-enriched.
Beaver Pond bulk peat samples and moss macrofossils show a similar isotopic pattern (low δ13C and high δ15N), which suggests that hooked scorpion moss contributed substantially to peat biomass accumulation at the Beaver Pond site.
Macrophytes
Beaver Pond macrophyte δ13C fall well within the albeit very wide known range for modern freshwater plants (− 50 to − 11‰, see Osmond et al.70, Keeley and Sandquist54, Mendonça et al.55, and Chappuis et al.56). It is reasonable to assume, however, that the very small sample size in this study hides the potential extent of the carbon isotope variability of macrophytes at the site.
Pod grass and bogbean are classified as emergent macrophytes (they grow rooted in water-logged substrates, but their leaves are exposed to the atmosphere), while pondweed grows entirely submerged. Submerged macrophytes become more enriched in 13C as the dissolved CO2 pool (the dominant carbon source) becomes increasingly limited54.
The Beaver Pond site pondweed δ13C is relatively low (− 26.5‰) for a submerged macrophyte. This indicates that it grew in an aquatic environment with adequate dissolved CO2. This is in keeping with the interpretation that the Beaver Pond was a fen (near neutral pH, cool water temperature) during the Pliocene. A low δ13C may also indicate high influx of terrestrial organic biomass or mosses (with low δ13C) into the water that subsequently remineralized and contributed to the dissolved inorganic carbon pool.
Environmental conditions strongly influence aquatic plant δ15N. Beaver Pond macrophyte δ15N (range =  + 0.2 to + 2.7‰) indicate interspecific access and use of a variety of different sources of bioavailable N within the water column and substrate. The most likely N sources are microbial-fixed atmospheric N2 (which ranges from –2 to + 2‰), the products of nitrification/denitrification processes (15N-enriched NH4+ or NOx), and remineralized 15N-enriched organic material (either terrestrial or aquatic)71,72,73.
Larch
Larch (the extinct species Larix groenlandii) is the most common vascular plant species in this macrofossil assemblage.
There is an offset of ~ 2‰ between the δ13C of (i) larch shoots/buds (which bear the needles) and cone bracts, and (ii) larch seeds. Larch shoots and cones (δ13C range = ‒25.4 to − 25.1‰; mean = − 25.3‰) are more depleted of 13C than larch seeds (δ13C range = − 23.3 to − 22.7‰, mean = − 23.1‰). This could be indicative of seasonal physiological or environmental conditions experienced by larch trees at the Beaver Pond site. The cones and shoots of extant larch trees begin growing in the early spring and have lower δ13C, whereas their seeds (higher δ13C) do not develop and mature until mid to late summer74.
A number of physiological and environmental conditions could be responsible for this offset between needle/-bearing structures and seeds. Atmospheric vapor pressure deficit (aridity) induces stomatal closure in vascular plants75. This restricts not only the rate of water leaving the needle/tree, but also that of atmospheric CO2 entering it. Stomatal closure reduces CO2 entry and results in less discrimination against 13CO2. High levels of solar irradiance in the summer increase the rate of CO2 assimilation. Plants growing at very high latitudes experience 24-h of daylight during the summer. This creates a greater demand for CO2 to maintain photosynthesis and less discrimination against 13CO2. Both aridity and increased light levels could contribute to why Beaver Pond larch tissues grown late in the summer are more 13C-enriched than those grown in the early spring/the previous fall.
Alternatively, trees can use water and carbon (in the form of sugars) stored during the previous year to promote new growth during the early spring when leaves are absent and light levels are low. Tissues that develop early in the growing season (i.e. needle-bearing buds and shoots) can therefore reflect the δ13C of photosynthetic conditions from the previous growing season76,77. In addition, differences in the macromolecular (lipid, protein, sugar) composition of larch buds/needles versus seeds could account for their offset in δ13C (i.e. lipids are typically more 13C-depleted than proteins).
Larch δ15N (mean =  + 2.7‰) indicate that these conifer trees had access to N sources other than “light” fixed atmospheric N2. Given the proximity of wetlands, the root systems of larch trees may have had access to 15N-enriched dissolved nitrates in the surrounding water-logged soils. Increasing foliar N concentration due to atmospheric N deposition also drives up plant δ15N78,79.
Aridity may also have influenced terrestrial plants growing at the Beaver Pond site. Higher rainfall is inversely correlated with δ15N, where rainier ecosystems tend to produce more 15N-depleted plants80.
Similar to δ13C, there is an offset in δ15N (and N wt%) between larch needle-bearing structures (mean =  + 3.8‰; 0.9%) and larch seeds (mean =  + 2.1‰; 0.3%). This could indicate differences in the macromolecular composition of these different tissue types (where high N content typically indicates higher tissue protein content).
Comparison of Dipoides within Castoridae
The composition of Dipoides sp. diet differs from that of other members of Castoridae that lived in North America during the late Cenozoic. Pliocene High Arctic Dipoides sp. (n = 5), modern subarctic Castor canadensis (n = 4) (Table 1), and late Pleistocene Castoroides ohioensis (n = 11) (Table 1) δ13Ccol and δ15Ncol are compared in Fig. 3. A correction for the Suess effect was first necessary render the δ13C of all three genera comparable. The carbon isotope composition of atmospheric CO2 has changed over time with global climatic conditions. More recently, anthropogenic burning of fossil fuels that has rapidly released CO2 enriched in 12C into the atmosphere46,81. Hence, a correction is needed when comparing δ13C of organic samples from different time periods to account for this isotopic variation in the primary carbon source of photosynthetic organisms at the base of the food web.
Suess effect corrections of + 2.02‰ and − 0.1‰ were applied to the δ13Ccol of modern C. canadensis (collected in 2013 and 2014) and Castoroides (late Pleistocene in age), respectively. These corrections were based on the average δ13C of atmospheric CO2 (δ13CCO2) calculated from Pliocene dual-benthic and planktonic foraminifera proxy records, spanning from ~ 4.1 to 3.8 Ma (average δ13CCO2 = − 6.55‰)76. These foraminifera proxy records are approximately contemporary with the Beaver Pond site. Average δ13CCO2 for 2014 (− 8.57‰) was compiled from the Scripps CO2 monitoring program. Average δ13CCO2 for the late Pleistocene (− 6.45‰) was compiled using ice core data from Schmitt et al.82.
Plants growing during these three different time periods (Pliocene, late Pleistocene, and modern/2014) would reflect the δ13C of contemporary atmospheric CO2. Therefore, changes in δ13CCO2 help explain differences in δ13C between Dipoides sp. and modern C. canadensis. Additional factors, however, are important in explaining the wide range of δ13C and large enrichment in 13C measured for Castoroides.
Dipoides sp. diet composition differs from that of Castoroides (the Pleistocene giant beaver) (Figs. 3 and 7). Castoroides’ high δ13Ccol and δ15Ncol (mean δ13Ccol = − 17.6‰ and mean δ15Ncol =  + 5.8‰) indicate a diet composed predominantly of aquatic (particularly submerged) macrophytes and minimal woody plant material (Table 1)13.
In comparison with Castoroides, both Dipoides sp. and C. canadensis have a relatively small range of δ13Ccol and δ15Ncol (Table 1) (Fig. 3). Dipoides sp. mean δ13Ccol and δ15Ncol are higher than those of modern C. canadensis (Fig. 3). This is attributable to either variation in diet between the two species, or changes in global C and N baselines over geologic time.
Previous mixing model studies predict that extant C. canadensis diet is composed of approximately equal proportions of woody terrestrial plants and aquatic macrophytes13. However, this can vary by latitude and season. For example, extant C. canadensis in the Canadian subarctic vary their winter diet significantly depending on habitat83. It is worth noting that extant C. canadensis does not occur north of 70° latitude and High Arctic Dipoides sp. living at 78° latitude may have employed different dietary strategies.
Dipoides sp. may have relied more heavily than C. canadensis on underwater stores of tree branches to survive the long, dark polar winter. Tree bark is more 13C-enriched than leafy vegetation57 and increased consumption could account for the higher δ13Ccol seen in Dipoides sp. Variation in the quantity and type of macrophytes consumed by each beaver species could also account for this difference (i.e. emergent and floating macrophytes are, on average more 15N-enriched than submerged macrophytes).
Changes in the isotopic composition of the C and N baseline between the Pliocene and the present could also account for the isotopic offset between beaver species. Further investigation of possible changes in the δ15N baseline of flora in terrestrial high latitude environments during the Pliocene would be a valuable avenue of future research.
Dipoides sp. behaviour and evolutionary implications
Evidence from the Beaver Pond site has implications for our understanding of Dipoides sp. ecology. These data also contribute to our understanding of the evolution of behavioural transitions within Castoridae. In particular, how Castor’s distinctive complex of behavioural traits (tree harvesting, underwater food caching, and construction behaviour) may have evolved. A new hypothesis of behavioural evolution in castorids based on evidence from the fossil record (i.e. fossil burrows, cut wood, and stable isotope measurements) and skeletal-dental morphology is mapped onto a simplified phylogenetic tree in Fig. 842,84,85,86,87.
Figure 8

Simplified Castoridae phylogeny showing behavioural reconstructions, including new evidence of woody plant consumption in Dipoides sp. Diagram based on phylogenetic analysis by Rybczynski9, which used a matrix of 88 morphological characters and 38 taxa. The origination of dam building is a minimum age (~ 7–8 Ma), corresponding to the time of divergence of Castor canadensis and C. fiber, inferred from molecular evidence96 and supported by fossil evidence97. Legend: CIRCLE—taxa that burrowed (Dipoides and Castoroides may have burrowed, but direct fossil evidence is currently lacking); WP—taxa with significant woody plant contribution to their diet; NWP—taxa that did not generally consume woody plants (the terrestrial burrowing clade is associated with open plains and unforested habitat, and therefore assumed to have not consumed significant amounts of woody plants); Plio—Pliocene; Q—Quaternary. Age range sources: Castor96,97,103, nowdatabase.org; Steneofiber eseri104; Fossorial clade84,86,94,105; Eutypomys94, Fossilworks.org, nowdatabase.org; Dipoides, including D. tanneri: Fossilworks.org, nowdatabase.org; Castoroides106, Fossilworks.org, nowdatabase.org. Fossil taxa behavioural evidence sources: Steneofiber eseri104; Castoroides13; Dipoides (this study); Fossorial clade90.

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Castoridae is a group of herbivorous rodents comprising roughly two dozen genera. Most fossil castorids fall within two major groups: a clade of fossorial specialists (Palaeocastorinae) and a semiaquatic clade42,84,86,88,89,90. The latter includes Castor and Dipoides. Members of the fossorial clade (~ 7 genera) possess striking specializations such large digging claws, extremely reduced tails, and broad, procumbent incisors for digging. In some cases, specimens have been found within fossil burrows (i.e. Palaeocastor, or “The devil’s corkscrew” burrows discovered in the plains of North America88). The semiaquatic group comprises two subfamilies, Castorinae (~ 6 genera, including Steneofiber and the extant Castor), and Castoroidinae (~ 7 genera, including Dipoides and the giant beaver, Castoroides). The oldest definitive Castorinae in the fossil record is Steneofiber eseri from the early Miocene (France, MN2, ~ 23 Ma). S. eseri shows evidence of living in family groups and swimming specializations91. This, in combination with aDNA evidence12, suggests Castorinae and Castoroidinae are derived from a semiaquatic ancestor in the early Miocene.
Digging behaviour was not just characteristic of the fossorial group and appears within the semiaquatic clade as well. Castor, though not morphologically highly specialized for the task, digs bank burrows and creates extensive canal systems92. In addition, the extinct semiaquatic beaver Steneofiber eseri was found within a burrow91. Considering the phylogenetic distribution of burrowing behaviour within the Castorid tree (Fig. 8), it is likely that the common ancestor of the fossorial and semiaquatic clades also burrowed. Thus, the appearance of burrowing behaviour within Castor and Steneofiber are seen as a retention of a primitive trait9.
If burrowing behaviour in semiaquatic castorids is the primitive condition, it is likely Dipoides burrowed as well, as seen in other semiaquatic rodents today such as Castor, but also Crossomys (earless water rat), Myocastor (nutria), and Ondatra (muskrat)92. It is also possible that Dipoides constructed lodges. Extant Castor and Ondatra are known to construct burrows and lodges, depending on the characteristics of the habitat. Bank burrows are associated with stream environments, whereas lodges are better suited to calmer waters92. Unlike Castor, extant Ondatra construct their push-up lodges using cattails and other fibrous vegetation rather than wood. The abundance of cut wood at the Beaver Pond site11 suggests that Dipoides sp. had the option to incorporate wood into their nesting structures, and possibly built lodges.
Given the occurrence of woodcutting and woody plant consumption within both subfamilies of semiaquatic castorids (represented by Castor and Dipoides in Fig. 8), it seems likely these behaviours appeared in the common ancestor of the semiaquatic group. Woody plant consumption may have preadapted castorids to exploit colder environments that arose during and after the late Miocene. Castor canadensis does not hibernate, but builds and sink rafts of branches and foliage to use as a source of fresh food during the winter months1,93. Dipoides sp. may have also engaged in this behaviour and used underwater caches of branches as a primary food source to survive the consecutive months of darkness during the high latitude winter when plants become dormant. The use of woody plants in this way may have been key to allowing beavers to disperse between North American and Eurasia, which required crossing the Bering Isthmus94, a high latitude landmass. Curiously, given that a diet rich in woody plants appears to be the primitive condition of semiaquatic castorids, the absence of woody plant consumption seen in the Pleistocene giant beaver Castoroides13 must be interpreted here as an evolutionary loss and potentially a leading factor in their extinction (Fig. 8).
Among living mammals, Castor’s dam construction is a unique and highly derived behaviour – an evolutionary puzzle, associated with a set of innate behavioural specializations95. For example, dam construction is well known to be triggered by the sound of running water alone95. The presence of such “hard-wired” behaviours may be associated with the ancient origins of this behaviour. Molecular and fossil occurrence records indicate that the split between Eurasian and North American Castor arose around 7.5 Ma ago96,97, implying that dam building behaviour itself is at least as old.
Definitive fossil evidence for dam building by an extinct beaver is currently lacking. Consequently, dam building behaviour is shown as possibly arising only on the lineage leading to Castor. Hypothetically, dam building may have arisen from beavers collecting branches near their burrow/lodge for feeding purposes and the accumulations of sticks could have dammed streams by happenstance. The effects may have been multifold. A deeper pond is an effective defense mechanism and provides a safe refuge from predators. Raised water levels also create more favourable conditions for underwater food caching of branches in sub-freezing winter conditions because the deeper water would prevent an underwater food cache from being locked in ice. As such, natural selection would have favoured animals that maintained the dam, presumably as an extension of their pre-existing nesting behaviour such as lodge building. In this scenario, the climate cooling that started around 15 Ma ago and continued into the Pleistocene would have provided an interval where behaviours promoting over-wintering survival, such as underwater food caching branches and dam building, would have been increasingly reinforced by natural selection.
It seems unlikely that the common ancestor of all semiaquatic beavers was a dam-builder. Extant Castor is a large powerful rodent weighing 12–25 kg, with some individuals as large as 40 kg92. Its body size is one factor that allows the animal to harvest branches and whole trees to build lodges and maintain dams over multiple years. The Beaver Pond site Dipoides sp. was also a large rodent and was roughly two-thirds the size of an average extant Castor. In contrast, the less-derived semiaquatic beavers, such as the Miocene Eucastor tortus (Castoroidinae) and Steneofiber eseri (Castorinae) were small (~ 1 kg, or less), suggesting that the common ancestor of the semiaquatic lineage was also small bodied. Although the common ancestor of the semiaquatic beaver lineage is inferred to have consumed woody plants (this study), and may have used branches in creating food piles and wood for lodge construction, it would have been too small to have had the capacity to build and maintain dams. As such, if Dipoides sp. did exhibit dam building behaviour, it would be the result of parallel evolution within the Castoroidinae and Castorinae lineages. More

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Study species and site
Odontotermes obesus is a fungus-farming termite species21 which makes cathedral-shaped, buttressed mounds9. It is widely distributed in India21 with mounds of several meters in height9. The study was conducted at the Indian Institute of Science Campus in Bangalore, India, which has a residual red soil formed from weathering of gneissic bedrock22. The soil is classified as inorganic clay of low plasticity and contains kaolinite and montmorillonite as dominant clay minerals, and quartz, mica and feldspar as non-clay mineral fractions22. It contains 43%, 34% and 23% of sand, silt and clay-sized fractions respectively22. For all analysis presented in this paper, the outermost region of termite mounds with surface conduits directly in contact with the atmosphere was considered as the buttress and the innermost region farthest away from the mound exterior was considered as the mound core. This was determined visually on a case to case basis based on the architecture of individual termite mounds (see Supplementary Fig. S1 online).
Strength of termite mound regions
To understand the scaling of strength with dimensions of mound samples, termite mound slices used by Kandasami et al.11 were obtained and samples were cored out with diameters 2 cm, 2.5 cm and 3.5 cm and standard aspect ratio of 223. These were tested under unconfined compression in a micro Universal Testing Machine (micro UTM) at a displacement of 1 mm/min. The unconfined compressive stress (UCS) for these samples were not significantly different (see Supplementary Fig. S2 online) and were similar to values in Kandasami et al.11 with samples of 6 cm × 3 cm (height: diameter) suggesting no effect of specimen dimension in strength testing; samples of small dimensions could therefore be used for further experiments. This validation was essential since it was not possible to get samples of 6 cm × 3 cm (height: diameter) dimensions from the buttress of the mound due to presence of pits in the mound walls (see Supplementary Fig. S1 online). Samples of 2 cm × 1 cm (height:diameter) were cored out from the core and buttress of the horizontal slices mentioned above. Depending on the availability of samples without channels/tunnels made by termites, 3 to 8 samples were cored out from each location, weighed and their densities were calculated. These samples acted as technical replicates. Samples were oven dried at 50 °C overnight since the mound slices from which they were derived had been stored under laboratory conditions. Samples were then tested under unconfined compression at 1 mm/min displacement and peak compressive stress recorded.
In order to obtain biological replicates, a drill was attached to a sampling tube (see Supplementary Fig. S3 online), and soil samples were obtained from the core and buttress of occupied mounds (N = 6 mounds). Drilling was carried out at 90 cm and 120 cm from the base (see Supplementary Fig. S3 online). Termites repaired the drilled section within 24 h. This method of sample collection, therefore, ensured minimal damage to the mounds. Samples were carefully transported in zip lock bags to minimise moisture loss, were cored to the dimensions 2 cm × 1 cm (height:diameter), were tested under unconfined compression at 1 mm/min displacement and the peak compressive stress was recorded. The in situ moisture content of soil from the core of the occupied mounds was 6–10% and that for the buttress was 0–4%. Some moisture loss was observed during sample testing, which was attributable to moisture loss occurring during sampling and testing.
Brazilian test for tensile strength of mound soil
To determine the tensile strength of termite mound soil, we performed a set of Brazilian or diametral compression tests wherein a disc of diameter 13.70 mm and thickness 6.60 mm24 was subjected to compression (displacement rate = 1 mm/min) under displacement–controlled loading along its diametral plane. Due to the compression load, a tensile stress state develops in the specimen normal to the compressed diameter with peak values near the centre of the specimen (see details in Supplementary, see Supplementary Fig. S4 online). To avoid local failure at compressed ends due to stress concentration, a cushion arc subtending an angle 2α (12°) at the centre of the disc is used to distribute the load uniformly25. With increase in axial displacement, the axial load increases to a peak where a crack initiates near the centre of the specimen and propagates towards the compressed ends instantly. The tensile strength corresponding to this peak load is calculated using σt = 2P/πDt where P is the peak compression load at failure or first drop in the load displacement curve, t is the thickness of the disc and D is the diameter of the disc26.
The tensile strength was estimated for samples extracted from different cross-sections at varying heights. For each cross section of the mound, several tests were performed (slice A2: n for buttress = 3, n for core = 3; slice A4: n for buttress = 2, n for core = 3; slice A7: n for buttress = 1, n for core = 3). The strength among these tests did not vary significantly (see “Results”).
Stability analysis of termite mounds
Slope stability analysis was performed on termite mounds to examine the effect of varying soil density and strength along the radial direction. Two geometrical models, triangular and trapezoidal, of the slope were used in this analysis (see Supplementary Fig. S5 online). The finite element method was used to perform slope stability analysis using a strength reduction factor. The advantage of using finite element-based slope stability analysis is that it does not require any à priori assumption of the failure surface27,28. The termite mound slope was modelled as an axisymmetric domain with an isotropic, homogeneous, linear elastic perfectly plastic Mohr–Coulomb material. The axisymmetric domains were discretized with six noded triangular elements with reduced integration to obtain the global stiffness matrix (see Supplementary Fig. S5 online). Discretization is a prerequisite for performing slope stability analysis using the finite element method. The termite mound was discretized into triangular elements, force balance was performed on each element and the results obtained from individual elements were integrated to obtain the overall slope stability of the mound. The bases of these domains were kept fixed for finite element analysis (soil below the termite mound was not considered). The finite element simulations were performed in Plaxis 2D software. As observed from uniaxial compression test data and density calculations, the strength and density of the mound soil varied in radial directions; to accommodate this variation four sets of model parameters were used (Table S1) for outer buttress, inner buttress, outer core, and inner core (see Supplementary Fig. S5 online). The parameters for inner core and outer buttress were the average of their values along the height of the specimen. For outer core and inner buttress, density and cohesion were linearly interpolated between the inner core and outer buttress. The tensile strength was considered to be constant throughout the domain as obtained in our Brazilian test results using samples from the abandoned mound. Since the soil density is comparable between occupied and abandoned mounds and the cementation is also expected to be the same, the tensile strength is expected to be similar between occupied and abandoned mounds.
Cohesive strength (c) for slope stability analysis is half of the average uniaxial compressive strength. Friction (ϕ) and dilation (ψ) angle were set to zero as the termite soil is predominantly clayey. The parameters used for slope stability analysis are provided in Table S1 online.
In the strength reduction factor method, strength parameters were continuously reduced until slope failure occurred. This method involves the reduction of strength by a strength reduction factor in a step-by-step procedure. The factor of safety corresponds to a stable strength reduction factor over a number of successive steps given that the slope failure is achieved in these steps28. A slope failure is identified by a contiguous surface/curve at the plastic limit (or pre-identified failure shear strain) whose end points lie at the boundary of the slope. The strength reduction factor at failure is approximately equal to the factor of safety as defined in limit equilibrium methods29,30.
Porosity distribution from computed tomography
X-ray computed tomography (XCT) was performed on samples (of diameter ~ 1.3 mm, aspect ratio of one) extracted from buttress and core at different heights for analysing the distribution of pores within mound soil. From the reconstructed XCT data, the scanned volume was segmented into two phases, air voids and termite mound soil, using thresholds corresponding to air–soil gray-level intensity cutoff. A typical slice of scanned volume data is presented in Fig. S6 (see Supplementary Fig. S6 online) along with a binarized image corresponding to air–soil gray level intensity cutoff. In order to obtain the distribution of porosity from the binarized volume data, a probing cube of 101 voxels (~ 1.3 mm) was traversed along all the interior voxels within the specimen with the cube residing completely in the specimen. The size of the pores within the cube is estimated as

$$Pore;Size = sqrt[3]{Total ;number;of;voxels;in;the;cube – voxels;occupied;by;soil;in;the;cube}$$

Porosity of all interior voxels was determined and frequencies of pore sizes were plotted for core and buttress of slices A2, A4 and A7 (Fig. 4). A total of 18 samples were scanned for this analysis (3 samples each for core and buttress within each slice). The pore sizes were divided into 1,000 bins between 0 and 1 mm for plotting. Any attempt towards reduction in the number of bins (say 500, 250, 200, 125, 100, 50, … bins) led to loss of information and statistical significance between core and buttress (see “Statistical analysis”).
We also calculate the porosity of the whole specimen by the following relation

$${text{Air}};{text{space}};{text{ratio}};left( {{text{porosity}}} right) = frac{number;of;voxels;in ;pores}{{total ;number;of;voxels;in ;a;sample}}$$

The porosity measurements for buttress and core at different cross sections are listed in Table 1.
Air permeability of mound soil
To understand the functional significance of the differences in density and strength on the gaseous permeability of termite mound samples, one sample each from the core and buttress at different heights from the abandoned mound was examined (see Supplementary Fig. S1 online). Samples were also obtained from the core and buttress of six occupied mounds by drilling at 0.9 and 1.2 m heights from the base of the mounds. Samples of dimensions 2 cm × 1 cm (height:diameter) were cored and inserted inside custom-made glass T-tubes. The samples were sealed inside the tubes with a commercial adhesive. The adhesive was allowed to dry and harden for 24 h before permeability testing. To ensure that all air flow can be attributed to the permeability of the mound samples alone, it was confirmed that the adhesive itself is impermeable to air in the range of air pressures tested. The set-up used for testing the permeability of termite mound soil was modified from King et al.4. The glass T-tubes with the samples were attached to a source of synthetic air (80% N2, 20% O2, 0% RH) and the flow rate was regulated using mass flow controllers Alicat MFC-100 and Alicat MFC-500 in the range 10–100 sccm (standard cubic centimetres per minute) and 100–500 sccm, respectively. The corresponding pressure was measured using a custom-made 14,000 Pa MEMS (micro-electronic measurement sensor) pressure transducer (0.28% full scale error) (see Supplementary Fig. S7 online). Air flow velocity vs. pressure graphs were plotted for samples from occupied and abandoned mounds. The pressures recorded in our experiment fell beyond the full scale error suggesting that they are not due to measurement error and thus reflect a real phenomenon.
Statistical analysis
We analysed the data using the software package R version 3.3.3 (2017-03-06). Data were tested for normality using the Shapiro–Wilk test. For the data on the scaling of strength in termite mound soil, Mann–Whitney U tests were performed followed by Bonferroni corrections. For the unconfined compressive strength data obtained from the abandoned mound, no significant interactions were found; therefore, a type II analysis of variance (ANOVA)31 was performed using the model: Compressive Strength ~ Height + Region  by employing the Anova function in the car package where Compressive Strength denotes peak compressive strength for each sample, Height refers to distance of each slice of the termite mound from the base (A2–A7; Fig. 1 and see Supplementary Fig. S1 online), and Region denotes the region within a slice (core vs. buttress; see Supplementary Fig. S1 online). For compressive strength data from the occupied mound, unpaired t tests were performed to check for differences between core and buttress at 90 cm and 120 cm from the base of the mound. Type II analysis of variance (ANOVA) was performed using the model: Tensile Strength ~ Height + Region by employing the Anova function in the car package where Tensile Strength denotes the tensile strength for each sample (see details in “Methods” and Supplementary; see Supplementary Fig. S4 online), Height refers to distance of each slice of the termite mound from the base (A2, A4, A7; see Supplementary Fig. S1 online), and Region denotes the region within a slice (core vs. buttress; see Supplementary Fig. S1 online). Data for porosity distribution in termite mound wall were analysed using a Kolmogorov–Smirnov (KS) test. Pore size distribution of core and buttress were compared for slices A2, A4 and A7 individually. The actual pore size values were compared using unpaired Mann–Whitney U tests for slices A2, A4 and A7 individually. Since the sample sizes in all these cases were very large, random subsamples were also taken and were subjected to unpaired Mann–Whitney U tests; results showed that the difference between core and buttress remained significant even when the sample was reduced to 1/128th of its original size (only results from original sample size and reduction to 1/128th of sample sizes are shown). Any further reduction would not have provided a representative sample. More

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DOC changes under photocatalytic degradation
The changes in DOC during photocatalysis are illustrated in Figs. 1–2 and Table S1. DOC removal after 180-min irradiation varied from 16.76 to 60.88% depending on the experimental conditions. All observed degradation trends followed a pseudo-first-order kinetic model (R2 = 0.96–1.00), which has also been reported in other studies to describe the photodegradation of DOM15,16,17. The effects of ZnO dosage, pH level, and presence of inorganic anions on the degradation of DOM are described in detail in the following sub-sections.
Figure 1

Effect of ZnO dosage and pH on DOC removal for photocatalytic degradation of DOM: (a) degradation curves, (b) removal %, and (c) degradation rates.

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Figure 2

Effect of inorganic anions on DOC removal for photocatalytic degradation of DOM with 0.2 g/L ZnO at pH 7: (a) degradation curves, (b) removal %, and (c) degradation rates.

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Effect of ZnO dosage
The relationship between ZnO dosage and DOC degradation is presented in Fig. 1 and Table S1. When ZnO dosage increased from 0.1 to 0.3 g/L, DOC removal and apparent degradation rate (kapp) were ∆ 21.42% and 2.49-fold higher at pH 4, ∆ 29.64% and 2.53-fold higher at pH 7, and ∆ 27.62% and 2.28-fold higher at pH 10, respectively. It is assumed that more active sites become available with increasing ZnO dosage, thus facilitating the generation of OH and consequently greater DOC removal and a higher degradation rate.
Effect of pH
As illustrated in Fig. 1 and Table S1, DOC removal and kapp were highest at a pH of 7 for all ZnO dosage levels. This observation could be explained by the ionization of DOM and the zeta potential (ZP) of ZnO at different pH levels. The acidic functional groups (e.g., –COOH and –OHphenolic) in HA molecules would become more ionized as the aqueous pH increases because pKa,-COOH and pKa,-OH have been reported to be 4.7 and 12.5, respectively (Eqs. 2)20:

$${text{HOOC}} cdots -{text{HA}}- cdots {text{OH}} to^{ – } {text{OOC}} cdots- {text{HA}} – cdots {text{O}}^{ – } , + , 2{text{H}}^{ + }$$
(2)

HAs are negatively charged over a wide pH range (2.0–10.7) 21, while the ZP of ZnO is positive at a pH range of 6.7–9.3 and negative otherwise (the pHZPC of ZnO = 9.0 ± 0.3) 22. Thus, at pH 7, where the dominant charges of ZnO and HA oppose each other, the electrostatic attraction between HA molecules and the ZnO surface would lead to the more rapid exposure of the HAs to reactive species (especially ·OH), resulting in the maximum DOC removal and photodegradation rate. On the other hand, at a pH of 4 and 10, both the HAs and ZnO are negatively charged, thus the repulsive force between the HA molecules and the ZnO surface would be strong. Therefore, there would be limited opportunities for the HA molecules to contact with reactive species near the ZnO surface, reducing removal and kapp.
In addition, it was found in the present study that DOC removal was always higher at pH 10 than at pH 4 for the same ZnO dosage. It has been reported that ZnO aggregation occurs at pH 4 (pHZPC of ZnO = 9.0 ± 0.3)22, which would slow the mass transport rate and consequently reduce the active surface area of ZnO. In addition, acidic conditions (i.e., less OH−) are less favorable for the formation of ·OH via the hole oxidation of OH−, lowering the efficiency of the attack of ·OH on DOM and the photocatalytic oxidation rate15, 16. These two reasons lead to lower total DOC removal and a lower photodegradation rate at a pH of 4.
Effect of inorganic anions
Figure 2 and Table S1 show the effects of inorganic ions on DOC removal. When fitting a pseudo-first-order kinetics model (R2 = 0.96–0.99), the presence of Cl−, SO42−, and HCO3− anions inhibited DOC removal. This occurred possibly because of two reasons. First, the ZnO surface is positively charged at pH 7, and the anions can be easily adsorbed onto the positively charged surface of the catalyst by electrostatic attraction, leading to the competitive adsorption. Second, the anions acted as free radical scavengers by reducing the availability of positive holes and by competitively reacting with ·OH6, 23,24,25, as given by the following reactions (Eq. 3–10) (Table S2):

$${text{Cl}}^{ – } + {text{h}}_{{{text{VB}}}}^{ + } to {text{ Cl}}^{ cdot }$$
(3)

$${text{Cl}}^{ – } + { }^{ cdot } {text{OH}} to {text{ HOCl}}^{ cdot – } ;;;;;;;;;{ }left( {k = 4.3 times 10^{9} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(4)

$${text{HOCl}}^{ cdot – } to {text{Cl}}^{ – } + { }^{ cdot } {text{OH }};;;;;;;; left( {k = 6.1 times 10^{9} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(5)

$${text{SO}}_{4}^{2 – } + {text{ h}}_{{{text{VB}}}}^{ + } { } to {text{ SO}}_{4}^{ cdot – }$$
(6)

$${text{SO}}_{4}^{2 – } +^{ cdot } {text{OH}} to {text{ SO}}_{4}^{ cdot – } + {text{ OH}}^{ – } { }left( {k = 1.18 times 10^{6} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(7)

$${text{HCO}}_{3}^{ – } + {text{h}}_{{{text{VB}}}}^{ + } to {text{CO}}_{3}^{ cdot – } + {text{ H}}_{2} {text{O}}$$
(8)

$${text{HCO}}_{3}^{ – } +^{ cdot } {text{OH}} to {text{ CO}}_{3}^{ cdot – } + {text{ H}}_{2} {text{O }}left( {k = 8.5 times 10^{6} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(9)

The strength of the inhibition effect followed the order of HCO3−  > SO42−  > Cl−  > no ions, possibly because HCO3− had the strongest capturing effect on ·OH (k = 8.5 × 106)25. The HCO3− quenched the ({h}_{VB}^{+}), which prevented the generation of ·OH (i.e., it inhibited the ({h}_{VB}^{+}) + H2O → ·OH + H+ reaction) and may, in turn, have led to the formation of ({CO}_{3}^{cdot-}) via the oxidation of ({HCO}_{3}^{cdot-}) by ({h}_{VB}^{+}) (Eq. 8), with a lower reactivity (E° = 1.78 V) than ·OH26. ({CO}_{3}^{cdot-}) has a weaker oxidative ability than ·OH and rarely reacts with organic matter, thus decreasing the reaction rate significantly6. In addition, HCO3- anions form a strong combination on the surface of the catalyst and can significantly inhibit the adsorption of HAs on the catalyst due to the weak absorption competition between HCO3− and HAs6.
Change in UV254
The degradation process as measured using UV254 is summarized in Figs. S2, S3 and Table S1. All photodegradation rates fit a pseudo-first-order kinetics model (R2 = 0.93–1.00), and there was a strong correlation between UV254 and DOC (R2 = 0.92–0.98), suggesting that chromophoric DOM accounted for the most significant proportion of DOC removal16. The effects of ZnO dosage, pH level (Fig. S2), and the presence of inorganic anions (Fig. S3) on UV254 removal and photodegradation rate were analogous to those described in the previous section. The highest in UV254 removal was 96.54% after 180 min of irradiation with a ZnO dosage of 0.3 g/L, a pH of 7, and no additional inorganic anions.
Total removal and the photodegradation rate calculated based on UV254 were much higher than those calculated using DOC concentration under all experimental conditions, which may be because the terminal functional groups of the aromatic compounds (e.g., hydroxyl and carboxyl) reinforced the adoption affinity of the surface of the catalyst particles15,16,17 and/or some of the DOM chromophores were partially transformed into non-UV-absorbing compounds (e.g., low-molecular-weight organic acids, alcohols, etc.) in the photochemical reaction13, 24.
The rapid reduction in UV254 with irradiation time (Fig. S2) suggests that the DOM chromophores, which mostly consisted of large aromatic rings, might have been rapidly broken down into smaller non-aromatic structures12, 25. The UV/Vis absorption spectra of DOM showed, as expected, rapid decrease with reaction time, and the remained absorption in UV range, even after 180-min irradiation implies the necessity of experimental optimizations (such as reaction time, power of light source, dosage of catalyst, etc.) for complete mineralization.
Change in SUVA254
Figure 3 presents the changes in SUVA254 during irradiation. Initially, the SUVA254 values were all higher than 4, ranging from 4.37 to 4.98, indicating that the organic matter was primarily composed of hydrophobic compounds with high molecular weights (HMWs)9, 26. There was a substantial reduction in SUVA254 (over 90% of initial values) after 180 min of irradiation in most of the samples except for two (pH 4 and pH 10 with 0.1 g/L ZnO). This was because of the preferential removal of aromatic chromophores over aliphatic moieties, followed by the transition of the DOM to non- or less-UV-absorbing substances28. This reduction in SUVA254 also indicates that HMW DOM was rapidly decomposed into organic compounds of lower molecular weight (LMW), which is supported by the lower DOC removal values compared to UV254-measured removal for the same reaction time27. A strong linear correlation (R2 = 0.92–0.98) was found between SUVA254 and DOC, and similar effects of ZnO dosage, pH level, and the presence of inorganic anions were observed.
Figure 3

Changes of SUVA254 of DOM during photocatalysis under different ZnO dosages and pHs: (a) SUVA254 and (b) a total reduction (%).

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Change in EEMs
The changes in the EEMs of the DOM over 180 min of irradiation under optimal conditions (0.2 g/L ZnO and pH 7) are presented in Fig. S4. It was observed that the broad and strong peak at emission wavelengths above ~ 350 nm, commonly referred to as the humic-like peak, decreased significantly with increasing irradiation time. After 180 min, the fluorescence intensity for the measured wavelengths was almost zero, with no clear peaks.
The lower fluorescence intensity in the EEM plots of the DOM was likely due to the preferential photocatalytic degradation of the HMW fraction27, which led to an increase in the LMW fraction. This was supported by size-exclusion chromatography using DOC and UV254 detection, which also observed a reduction in fluorescence intensity with lower molecular weights based on the synchronous scan spectra of Aldrich HA fractions obtained with ultrafiltration after photocatalysis27. Moreover, the photocatalytic degradation of the HMW compounds in the DOM was similar to the previously reported photocatalytic degradation of NOM from a bog lake29. The photocatalytic degradation of DOM followed a similar sequence to other oxidation processes, such as the chlorination of NOM30 and the photocatalytic degradation of commercial HA using TiO2 and a solar UV-light simulator27.
Behavior of the components during photocatalysis
EEM-PARAFAC components
Using 125 EEM samples from 25 experiments, two components (C1 and C2) were identified using PARAFAC modeling (Fig. S5 and Table S3). It was considered reasonable to extract two fluorophores from the samples because Sigma-Aldrich HA is known to be pedogenic with quite uniform sources31. C1 produced a maximum peak at an Ex/Em of 261 nm/ ≥ 500 nm, exhibiting a broad excitation spectrum and gradual emission above 350 nm, while C2 peaked at an Ex/Em of  pH 10  > pH 4 with 0.1 g/L ZnO and the order pH 10  > pH 7  > pH 4 with 0.2 g/L ZnO. With a ZnO dosage of 0.3 g/L, total removal followed the order pH 10  > pH 7  > pH 4, while the photodegradation rate followed the order pH 7  > pH 4  > pH 10 (Fig. 4). A difference from previous results was also observed for the addition of inorganic anions. In the presence of inorganic anions, total Fmax removal and the photodegradation rate followed the order Cl−  > no anions  > SO42−  > HCO3−. The highest total Fmax removal was 99.36% after 180 min irradiation at a ZnO dosage of 0.3 g/L and a pH of 10, with no additional inorganic anions (Fig. 5).
Because the degradation behavior of both PARAFAC components followed a first-order exponential decay process, their photocatalytic degradation and kinetic rates could be directly compared. Total Fmax removal and the photodegradation rate of C1 were higher than those of C2, which can be explained by the excitation and emission wavelengths of each component. Although both C1 and C2 were both identified as terrestrial humic-like organic matter, C1 represents a combination of peak A and peak C, exhibiting longer excitation and emission wavelengths than C2. With peaks at longer wavelengths, C1 may be associated with the structural condensation and polymerization of DOM15, 32. Indeed, more pronounced fluorescence at longer emission wavelengths in the EEMs of larger sized and/or more hydrophobic DOM fractions has been previously reported33. Therefore, the results indicate the preferential adsorption of more hydrophobic and larger DOM molecules onto minerals and/or nanoparticles, which has also been reported in previous studies15, 34. In addition, because C2 has shorter excitation wavelengths than C1, it would be less excited by visible light than C1.
Total DOM removal and photodegradation rates calculated using DOC, UV254, and the PARAFAC components were also compared (Fig. 6). It was interesting to observe that the total removal and photodegradation rates calculated using the Fmax of the two PARAFAC components were higher than those calculated using DOC and UV254. In particular, under optimal conditions (0.2 g/L ZnO, pH 7, and no inorganic anions), the total removal of C1 (100%) and C2 (98.97%) was observed to be higher than total UV254 removal (95.54%) and much higher than total DOC removal (43.04%), while the photodegradation rate of C1 was 11.27-fold and 8.55-fold higher than the photodegradation rates calculated with DOC and UV254, respectively. Similarly, the photodegradation rate of C2 was 1.90-fold and 1.44-fold higher than the photodegradation rates calculated with DOC and UV254, respectively. The more rapid degradation of fluorescence components compared to UV-absorbing moieties (i.e., UV254) could be explained by the fluorescence arising from the π*–π transitions in DOM molecules and its rapid extinction under UV irradiation15, 16.
Figure 6

Changes in DOC, UV254, and two EEM-PARAFAC components during photocatalytic degradation of DOM with 0.2 g/L ZnO at pH 7 under artificial sunlight: (a) degradation curves and (b) removal % and degradation rates.

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The proposed reaction mechanism for the ZnO-assisted photocatalytic degradation of DOM under artificial sunlight is presented in Fig. S6. When ZnO is irradiated with artificial light containing photonic energy (hv), valence band hole (({h}_{VB}^{+})) and conduction band electron (({e}_{CB}^{-})) pairs are produced, as given in Eq. (10)11. The ({h}_{VB}^{+}) reacts with H2O and hydroxide ions to yield ·OH (Eqs. 12 and 13)7,8,9. The reduction of dissolved or adsorbed O2 to ({O}_{2}^{cdot-}) by ({e}_{CB}^{_}) is depicted in Eq. (14)7,8,9. The ({O}_{2}^{cdot-}) is converted to H2O2 via disproportionation with protons (Eq. 15) or forms ({HO}_{2}^{cdot}) via protonation, which has a short lifetime due to the rapid reaction with ({O}_{2}^{cdot-}) or ({HO}_{2}^{cdot}) to form the more stable H2O2 (Eqs. 16 and 17)7,8,9, 35. The one-electron reduction of H2O2 produces ·OH (Eq. 19), while H2O2 can also react with ({O}_{2}^{cdot-}) to form ·OH (Eqs. 20 and 21)7,8,9. The generated ·OH is a powerful oxidizing agent that can attack DOM at or near the ZnO surface (Eq. 23). The reaction of ·OH with HAs (as a representative form of DOM) results in the release of LMW acids, amino acids, and ammonia36. The ({O}_{2}^{cdot-}) can also oxidize the DOM molecules (Eq. 24)16. Moreover, upon absorbing light, DOM can act as a photosensitizer in the generation of reactive species such as singlet oxygen (1O2), ·OH, and triplet DOM states (3DOM*), as given in Eqs. (25–28)37. 3DOM* is a potent oxidant of many aquatic contaminants that react with target organic substances directly through electron and energy transfer mechanisms to generate reactive oxygen species such as 1O2, ·OH, and H2O237, thus significantly influencing on the degradation of various fluorophores.

$$ZnO+hv to {h}_{VB}^{+}+{e}_{CB}^{-}$$
(10)

$${H}_{2}Oto {OH}^{-}+{H}^{+}$$
(11)

$${text{h}}_{{{text{VB}}}}^{ + } + {text{ H}}_{2} {text{O}} to { }^{ cdot } {text{OH }} + {text{ H}}^{ + }$$
(12)

$${text{h}}_{{{text{VB}}}}^{ + } + {text{ OH}}^{ – } to { }^{ cdot } {text{OH}}$$
(13)

$${text{e}}_{{{text{CB}}}}^{_} + {text{ O}}_{2} { } to {text{ O}}_{2}^{ cdot – }$$
(14)

$${text{O}}_{2}^{ cdot – } + 2{text{H}}^{ + } + {text{e}}_{{{text{CB}}}}^{_} { } to {text{H}}_{2} {text{O}}_{2}$$
(15)

$${text{O}}_{2}^{ cdot – } + {text{H}}^{ + } to {text{HO}}_{2}^{ cdot } ;;;;;;left( {k = 2.1 times 10^{10} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(16)

$${text{HO}}_{2}^{ cdot } + {text{HO}}_{2}^{ cdot } to {text{H}}_{2} {text{O}}_{2} + {text{O}}_{2} ;;;;;;;;left( {k = 8.3 times 10^{5} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(17)

$$^{ cdot } {text{OH }} +^{ cdot } {text{OH}} to {text{H}}_{2} {text{O}}_{2} ;;;;;;;;;;;;left( {k = 5.5 times 10^{9} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(18)

$${text{H}}_{2} {text{O}}_{2} + {text{H}}^{ + } + {text{e}}_{{{text{CB}}}}^{_} to { }^{ cdot } {text{OH }} + {text{ H}}_{{2}} {text{O}}$$
(19)

$${text{H}}_{2} {text{O}}_{2} + {text{O}}_{2}^{ cdot – } to {text{OH}}^{ – } + {text{O}}_{2} + ^{ cdot } {text{OH}} ;;;;;;;left( {k = 0.13{text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(20)

$${text{H}}_{2} {text{O}}_{2} + {text{hv}} to {2}^{ cdot } {text{OH}}$$
(21)

$${text{H}}_{2} {text{O}}_{2} +^{ cdot } {text{OH}} to {text{H}}_{{2}} {text{O}};;;;;;;left( {k = 2.7 times 10^{7} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(22)

$${text{DOM }} +^{ cdot } {text{OH}} to {text{CO}}_{{2}} + {text{ H}}_{{2}} {text{O }} + {text{ Products}};;;;;;;;left( {k = 1.7 times 10^{8} {text{ Mc}}^{ – 1} {text{s}}^{ – 1} } right)$$
(23)

$${text{DOM }} + {text{O}}_{2}^{ cdot – } to {text{CO}}_{2} + {text{ H}}_{{2}} {text{O }} + {text{ Products}}$$
(24)

$${text{DOM }} + {text{ hv}} to^{{1}} {text{DOM}}^{*} to^{{3}} {text{DOM}}^{*}$$
(25)

$$^{{3}} {text{DOM}}^{*} + {text{ O}}_{{2}} to^{{1}} {text{DOM }} +^{{1}} {text{O}}_{{2}}$$
(26)

$${text{DOM}} + {text{ O}}_{2}^{ cdot – } to {text{DOM}}^{ cdot – } + {text{O}}_{2}$$
(27)

$$2{text{O}}_{2}^{ cdot – } + 2{text{H}}^{ + } { } to {text{ H}}_{2} {text{O}}_{2} + {text{ O}}_{2} ;;;;;;;;;;left( {k = 4.0 times 10^{4} {text{ M}}^{ – 1} {text{s}}^{ – 1} } right)$$
(28)

The effects of photolysis, adsorption, and photocatalysis on the degradation of DOM was also assessed. Figure 7 compares the results for total removal and the degradation rate for these three processes. The total DOM removal and degradation rate calculated with DOC are illustrated in Fig. 7a. After 180-min irradiation, total DOM removal was 2.92% for photolysis, 10.15% for adsorption, and 43.04% for photocatalysis. The photocatalytic rate was 18.6-fold and 5.5-fold higher than that for photolysis and adsorption. The DOM removal and degradation rate calculated with UV254 (Fig. 7b) also revealed that photocatalysis was more effective than the other two processes. Specifically, total DOM removal was 4.03% for photolysis, 19.46% for adsorption, and 95.45% for photocatalysis, while the degradation rate was 93.6-fold and 17.0-fold higher than that of photolysis and adsorption, respectively. Based on these results, we can conclude that adsorption by ZnO only and photolysis only play a minor role in DOM removal, while the synergistic effects of photocatalysis are vital to this process.
Figure 7

Comparison of photolysis, photocatalysis and adsorption of DOM with 0.2 g/L ZnO at pH 7: (a) DOC concentrations and (b) UV254 values.

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