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    Fire-induced rock spalling as a mechanism of weathering responsible for flared slope and inselberg development

    Establishing the variables involved in rock weathering and fire behaviour is a key aspect of developing an accurate fire-induced rock spalling hypothesis. We expand on these variables by drawing on field observations and existing findings outlined below.Mechanical weatheringThe physical breakup and removal of rocks of varying hardness and degrees of weathering via mechanical weathering is the primary process that denudes and sculpts uplifted regions of Earth’s surface. Sub-critical cracking describes the slow propagation of microfractures through a rock in low-stress, near-surface conditions as a result of thermal stress, ice wedging, mineral alteration (volumetric expansion) and biomechanical processes such as root growth25. Sheeting is characterised by thick (0.1–1 m) layers of rock peeling off exposed surfaces roughly parallel to the surface topography. There is debate as to whether sheeting is related to gradual unloading and release of stresses near the surface or a combination of other stresses26,27. The physical process of thermal expansion and contraction of rocks over thousands of years is responsible for the thinner, gradual flaking (exfoliation) of rock surfaces, which can be observed all over the surface of inselbergs in central Australia5 and presumably the main process responsible for the slow rates of erosion at the tops of inselbergs14.Fracture propagation is facilitated by the presence of water28, which helps to break chemical bonds leading to more fractured rock at shallow, superficial levels of the crust. Thus, rocks are generally more fractured in the superficial, near-surface environments than at deeper levels. Spontaneous rock-burst events were captured on video during a hot summer of 2014 in California when a granite dome at Twain Harte began explosively exfoliating29. Extreme thermal stresses associated with fire and lightning strikes are acknowledged as mechanisms of critical stress fracturing in rocks but generally considered to be a rare form of rapid and catastrophic mechanical weathering25. Our observations of rock surfaces following wildfires are that fire-related rock spalling is a commonly observed phenomenon wherever high-intensity fire has swept across rocky outcrops (for example, Figs. 5 and 6). We suggest that fire-spalling is a significant driving mechanism of physical weathering in arid, fire-prone environments and has been overlooked as an important agent of geomorphic change and landscape evolution.Fig. 6: Existing and new models of flared slope development using Uluru as an example and a graphical representation of the formula for erosion due to fire-spalling in different fire regimes.a The model of Twidale and Bourne 199822 involving subsurface weathering via shallow groundwaters to form soft regolith or unconsolidated soil that is subsequently removed by erosion and landscape lowering; b a new model of flared slope development via fire-induced rock spalling associated with episodic wildfire events. Note the charcoal on the recently burnt trees is the same height as the flared slope; c inverse correlation relationship between rates of erosion E(t) plotted against fire recurrence interval (t) using the formula E = W.A/t (see https://www.geogebra.org/calculator/uwa68amr). Rock-type and fire temperatures tend to control the thickness of spalled sheets (W) whilst fire intensity and duration are the main controls on the surface area spalled (0–100%). The inverse correlation of rates of fire-spalling erosion with average recurrence intervals (t) results in an increasing rate of weathering with smaller average fire recurrence intervals. Fire recurrence intervals are largely controlled by climatic and vegetation regimes and examples from Figs. 2 and 4 are shown and plotted on the graph according to the fire recurrence interval for that region.Full size imageWildfire temperaturesA detailed study of high-intensity wildfires in eucalypt forests of SW Australia30 revealed that these fires burn at temperatures between 300 °C at the tips of visible flames and up to a maximum of 1100 °C near the flame base, while temperatures of up to 1330 °C were recorded in Canadian crown fires31. Experimental fires conducted in jarrah forests of south-west Western Australia (Project VESTA) reveal that temperature correlates directly with the rate of spread, fire intensity, flame height and surface fuel bulk density30. This single case study measured the average flame-front residence time in eucalypt forest fuels of about 37 s. However, radiant heat and hot winds fanning out in front of the fire have the ability to pre-heat the rock surface and vegetation before and after the arrival of the fire front31 particularly along cliff lines.We report the first documented case of spalling in basalt from Mount Kaputar in northern N.S.W. (Fig. 4d). Basalt is a high-temperature volcanic rock with no quartz content. Fire-spalling was minimal across most of the outcrops and generally consisted of dislodged pyroxene phenocrysts. However, a few basalt outcrops adjacent to nearby fallen burnt logs were intensely scorched and displayed thin (1–4 mm) spalled flakes of basalt indicating that fire-spalling is not restricted entirely to quartz-rich lithologies. In mature eucalypt forests with large, woody fuels, termed ‘down wood’32, fires can burn or smoulder for days, providing prolonged heat required for extensive spalling. Some cliff faces record distinct ghosted impressions of nearby tree trunks with the resultant spalling hollowing out the line and shape of a tree trunk in an otherwise flat, vertical rockface (Fig. 5a—right-hand side). A discarded brown glass bottle adjacent to the basalt spalling had softened and undergone ductile collapse and partially melted. The glass had cooled slowly enough to avoid shattering indicating prolonged heating from the smouldering downward. This glass was collected and placed in a high-temperature oven where it was observed to become soft and malleable at 750 °C and completely collapsed and started melting at 830 °C indicating that this fire sustained ground surface temperatures of between 750 and 830 °C next to the smouldering tree and fallen logs.Fire-induced rock spallingFire is known to accelerate the rock flaking process25,33,34,35,36,37,38 resulting in rock spalling36,39 and shattering38. Conflagration leads to the rapid disintegration of the rock surface due to the differential expansion of the hot rock surface compared with the cooler interior. Fire-spalling can remove between 10 and 100% of the burnt rock surface in sheets between 5 and 50 mm thick37 depending upon rock type and fire intensity. Detailed measurements of post-fire rock spalling after the Esperanza chaparral fire in California revealed that 7–55% of the granodiorite boulder surfaces were spalled to a depth of 11–24 mm33. They found that the thickest spalled sheets occurred around the flanks of the boulders and cautioned that, if sampled for cosmogenic dating, these freshly exposed, spalled surfaces would produce a significant underestimate of exposure age. These figures match our own observations of spalled granite following the fires in Cobargo, Moonbi and Thredbo N.S.W. (Fig. 4) in which granite boulders spalled sheets between 5 and 50 mm thick, while sandstones from the Blue Mountains spalled sheets between 5 and 22 mm thick (Fig. 5).Quartz expands four times more than feldspar and twice as much as hornblende and shows a 3.76% volume expansion when heated from room temperature to 570 °C40. Thus, quartz-rich rocks have a greater expansion potential and are more likely to spall. Experimental studies41 show that rock elasticity reduces significantly at temperatures as low as 200 °C, over a relatively short period of time. Goudie et al.41 postulated that rock outcrops subject to intense fires would have an increased susceptibility to erosion via spalling and weathering. However, these findings have not been applied to broader landscape models or the formation of flared slopes around inselbergs.Fire regimesThe potential rate of erosion due to fire-spalling at the base of inselbergs will be strongly influenced by fire severity and recurrence intervals, which vary greatly across Australia from 1- to 5-year recurrence intervals and 100-year intervals and >10,000 kW m−1 for tall, open forests of the cool, temperate south42. Accurately calculating the fire return period is difficult due to limited historical records but estimates for arid, spinifex-dominated regions such as the Tanami are in the order of every 7–9 years43. Analyses of satellite data between 1998 and 2004 revealed that 27% of arid Australia burnt at least once over that 6-year period44. Figure 1a shows the areas burnt in Australia since 2001. The surface area of the rock affected by spalling depends on the rock-type and severity of the fire. Fire severity is strongly determined by the bulk density45, height and proximity of the adjacent vegetation to rock surfaces and the surrounding slope gradient. All the examples of flared slopes shown in Figs. 1 and 2 reveal a close relationship between the height of the encroaching vegetation and the height of the concavity. Katter Kich, Pildappa Rock and Walga Rock form distinct embayments where the flared slopes are most pronounced, which appear to promote denser, taller vegetation growth and hence greater fuel loading and thus higher fire severity (Fig. 3).The impermeable nature of inselbergs results in rapid and efficient water runoff from the bare-rock surface before draining into adjacent, thin soil profiles. This creates a “roof and gutter” effect around the periphery of many inselbergs which creates permanent water holes and shallow groundwater within easy reach of deep-rooted plants. Inselbergs create important geodiversity within otherwise flat landscapes and thus host important niche ecosystems that add to the overall biodiversity of desert regions46. Accessible groundwater around the fringes of the inselbergs encourages denser, taller vegetation at the interface between bare rock and unconsolidated surficial sediments which in turn increases the fuel load. Inselbergs are prominent topographic features in flat deserts that provide sources of permanent water, abundant flora and fauna and shelter.Grassy plains and savannahs of central Australia are characterised by regular, low-intensity fires with fire recurrence intervals between 1 and 5 years42. However, where these fires encounter inselbergs they move into thicker, taller vegetation regimes with greater fuel loads (Figs. 2 and 3). Inselbergs are topographic highs within relatively flat landscapes and the slight increase in slope gradient around the inselberg will accelerate and intensify an approaching fire front. Steep slopes around the margins of inselbergs possibly act as chimneys, drawing in hot air from the surrounding plains and channelling them upwards. These factors possibly help to draw in fires from the surrounding plains into and around topographically high inselbergs where the intensity is enhanced at the base of inselbergs due to the denser vegetation and greater fuel load.A fire-induced spalling weathering formulaFire-spalling leads to physical weathering (erosion) and disintegration of exposed rock faces36,37 as shown in Figs. 3–5. The degree and extent of spalling on different rock types and at varying temperatures and durations is less well understood and requires further experimental work41 but essentially fire-spalling is a function of fire intensity (temperature), duration and rock type with quartz-rich rocks having a greater propensity to expand and spall40.We developed a simple fire-spalling erosion formula to estimate a long-term rate of fire-induced spalling that broadly considers the net result of fire-spalling in terms of the thickness (width) of the spalled flakes produced by a single fire event, the total surface area as a percentage of the exposed rock face affected by a single fire-spalling event, and the average fire recurrence interval for a given region. Together these variables can give some indication as to the long-term rates of erosion due to fire-spalling at the base of an inselberg or cliff face where there is significant vegetation to fuel a wildfire.The formula for erosion due to fire-spalling.$$E = frac{{W times A}}{t}$$
    (1)
    where, E = rate of erosion due to fire-spalling (mm yr−1), W = average width (thickness) of spalled sheets (mm) for a single fire event. Dependent on rock type (quartz content and texture), rock strength, fire temperature and duration, A = area of rock surface affected by fire-spalling as a percentage (%) of total surface area. Dependent on temperature and duration of the fire, t = average fire recurrence interval (years). Determined from regional, historic fire records or palaeofire records for longer time periods. Dependent on vegetation, climatic regimes and land management practices.Limitations: this equation applies to a near-vertical rock face at ground level which receives uniform heat radiation from a fire that burns right up to the rock face at ground level. The intensity of radiation will vary according to the dynamics of the fire front, fuel loading, vegetation type and slope gradient. Flame height is not critical to the overall rate of retreat of the cliff face because fire-spalling at the base of the cliff will gradually remove material supporting the cliff resulting in over-steepening at the base of the cliff and periodic sheeting and rockfalls as the overhanging cliff face becomes gravitationally unstable. The formula assumes that fire recurrence intervals have remained constant but we know from palaeofire records47,48 that fire intensity and recurrence intervals are largely controlled by long-term climatic variations which affect vegetation types and thus fuel loads. Below, we give two end-member examples of long-term rates of spalling-related erosion for low and high-frequency fire regimes that may apply to temperate and arid environments, respectively.Example 1. Low intensity, irregular fire regime. In this scenario, the average fire against a cliff results in spalling and flaking of ~10 mm sheets off ~20% of the surface area at ground level during a single fire event. Fire recurrence interval is one event every 50 years.$$E = frac{{W times A}}{t} = frac{{10;{mathrm{mm}} times 0.2}}{{50}} = 0.04;{rm{mm}};{rm{yr}}^{ – 1} = 40;{rm{m}};{rm{Ma}}^{ – 1}$$Example 2. High intensity, high-frequency fire regime. In this scenario, the average fire against a cliff results in spalling and flaking of ~20 mm sheets (Fig. 5) off ~80% of the surface area at ground level. Fire recurrence interval is one event every 5 years.$$E = frac{{W times A}}{t} = frac{{20;{mathrm{mm}} times 0.8}}{5} = 3.2;{rm{mm}};{rm{yr}}^{ – 1} = 3200;{rm{m}};{rm{Ma}}^{ – 1}$$In an intensely fire-prone environment such as example 2 above, it may only take about 625 years of fire-induced spalling to weather out a 2 m deep flared slope at the base of a vertical rock face. The point at which undercutting due to fire-spalling would trigger massive sheeting of the unsupported, overhanging rock ledge and subsequent rockfall event is not well constrained but some of the flared slopes around Uluru and Walga Rock are at least 2–3 m deep (Fig. 2h).Sediment production ratesIf rates of erosion due to fire-spalling around the periphery of an inselberg are orders of magnitude greater than those across the top of the inselberg, then this has implications for mechanisms of sediment production in flat, arid environments like Central Australia.Spalling of a 20 mm sheet from a 1 m2 area of granite with a density of 2691 kg m−3 will yield 0.02 m3 (53.82 kg) of rock. A flared slope around an inselberg such as Uluru with a circumference of ~10,000 m and a height of 2 m, would produce 400 m3 (1,076,400 kg) in a single event in which 100% of the 2 m high flared slope was spalled. Obviously, 100% spalling of the entire flared slope would never occur in a single event, so we use the long-term erosion rate based on fire recurrence intervals and average area spalled calculated in Eq. 1. This long-term estimate of sediment production from a single inselberg is compared with quantitative measurements of spalled granite surfaces sampled after the 2019–2020 fires in Cobargo on the south coast of N.S.W., Australia.The formula for sediment production.$$S_{rm{FS}} = P.H.E$$where, SFS = sediment production from fire-spalled rock surface (cubic metres per year), P = perimeter of the inselberg (metres), H = height of the flared slope around the inselberg as determined by vegetation and fire height, E =  rate of erosion due to fire-spalling (Eq. 1).Fire-spalling sediment production around the periphery of an inselberg such as Uluru with a perimeter of roughly 10,000 m and flared slope height of 2 m, would be$$S_{mathrm{FS}}=10,000, {mathrm{m}}times 2, {mathrm{m}} times 0.0032, {mathrm{m}}, {mathrm{yr}}^{-1}=64, {mathrm{m}}^{3}, {mathrm{yr}}^{-1}=172,224, {mathrm{kg}}, {mathrm{yr}}^{-1}$$This can be standardised to give a volume of rock spalled per year per square metre, which is the same as the erosion rate but in cubic metres per year. Given the density of the rock (granite = 2691 kg m−3 and compacted, meta-arkose sandstone (Uluru) are about the same) we can calculate the average mass of rock spalled each year. In the above scenario, it equals 8.61 kg per square metre per year.The rate of background (non-fire related) sediment production (SBA) from erosion of the surface area of an inselberg such as Uluru is equivalent to the surface area (~3,440,000 m2) multiplied by the average denudation rate of ~0.3–0.6 m/Ma (0.0003 mm yr−1) as established from cosmogenic studies.$$S_{mathrm{BA}}=3,440,000, {mathrm{m}}^{2}times 0.0000003, {mathrm{m}}, {mathrm{yr}}^{-1} =, sim! 1, {mathrm{m}}^{3}, {mathrm{yr}}^{-1}=2691, {mathrm{kg}}, {mathrm{yr}}^{-1}$$This equates to only 0.00081 kg per square metre per year. We estimate that fire-spalling on a 2 m high perimeter produces in the order of 64 times more sediment than the erosion of the entire surface of the inselberg due to background (non-fire related) processes.Spalled granite material was collected from two locations following the 2019–2020 fires in the Cobargo region along the south coast of N.S.W. (Fig. 4) to assist in quantifying the amount of rock spalled from a single rock face. Spalled surface area can be estimated simply by measuring the maximum height and width of the spalled surface in the field. We also created a digital surface using photogrammetry MetaShapePro software to calculate a precise surface area of the spalled surface. All of the spalled material was weighed and a standard granite density of 2691 kg m−3 was used to determine total volume. Generally spalling occurs as thin (1–3 cm) sheets but occasionally includes large 20–30 cm thick slabs that substantially add to the overall weight of spalled material. Whilst complete spalling of a 2 cm sheet from one square metre of granite surface will produce 53.82 kg m−2 of rock, our two sites (Cobargo2 and 3A) produced 23.65 kg total (16.89 kg m−2) and 41.60 kg m−2 total (33.55 kg m−2), respectively, indicating an average spalling thickness of 0.63–1.25 cm although the spalled thickness was highly variable with spalling distinctly more prominent along sharp or protruding edges than on flat surfaces. Large logs or tree trunks have the potential to continue burning long after the fire front moves through and their presence near rock surfaces significantly increases the degree of spalling. The most intense spalling was observed at Moonbi Granite near Tamworth in northern N.S.W. where some granite boulders had 100% surface spalling up to 2 m above ground level and not one but several spalled sheets (5–20 cm total thickness) exfoliating off during a single, intense fire creating several hundred kilograms of spalled rock debris on the granite surface facing the fire front (Fig. 4). Likewise, lichen coated granites from Australia’s most elevated alpine regions in the Snowy Mountains (Thredbo) displayed intense spalling but were covered in snow six months later. The fire recurrence interval for these alpine regions is probably in the order of one every 20–100 years thus the effects of fire-spalling are less pronounced than in arid regions and less evident than other forms of fluvial or chemical weathering that dominate in wetter climates. However, the abundant spalled surfaces shown in Fig. 4 reveal that large, intense fires such as the Black Summer fires of 2019–2020 will result in significant erosion and sediment production even in alpine environments. More

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    Nitrogen isotope effects can be used to diagnose N transformations in wastewater anammox systems

    Variation in the N isotope effect imparted by ammonium oxidationWhile the ammonium isotope effect, 15ε(NH4+), varies by over 13‰ across all experiments, it exhibits a narrower range for a specific experimental setting with distinct cultivation conditions (mainstream, enrichment, sidestream), it exhibits a broader range across all experiments (Fig. 2). There are a number of possible physiological and experimental conditions that differ among experiments, including reaction rate, temperature, and initial concentration of substrates. As shown in Fig. 6, there is a systematic decrease in 15ε(NH4+) at decreasing initial ammonium concentration, while at the highest ammonium concentrations, the value of 15ε(NH4+) appears to plateau at a value near 32‰, close to the maximum value (32.7 ± 0.7‰) observed by Kobayashi and coworkers in chemostat experiments with enriched cultures19. Typically, the isotope effect imparted into a substrate pool by a kinetic process is set at the first irreversible step; any isotope effects that occur before this point can be expressed, while any that occur after it are concealed37,38. Substrate supply limitations can decrease the reversibility of a given step, and thereby let it modulate the net isotope effect of a multi-step process. This behavior has been proposed to play important roles in controlling the isotopic signatures of microbial sulfate39,40 and nitrate41,42 reduction.Figure 615ε(NH4+) for each individual experiment, compared to the concentration of ammonium at the start of that experiment. Mainstream experiments are plotted in yellow circles, sidestream experiments in blue squares, and enrichment experiments in grey diamonds.Full size imageIn the case of anammox bacteria, this pattern suggests that the relative kinetics of ammonium uptake and oxidation control the observed value of 15ε(NH4+). The typical path of an ammonium molecule through an anammox cell requires crossing several cell membranes to the eventual site of reaction, inside the anammoxosome43,44. When ammonium concentrations are relatively high and ammonium oxidation is not uptake-limited, 15ε(NH4+) is set at the hydrazine synthase (Hzs) enzyme, at which ammonium binds and is subsequently oxidized to hydrazine43. The maximum observed value of 15ε(NH4+) would then be the expression of all isotope effects up to, and including, this bond-breaking step. But if, at relatively low ammonium concentrations in the external medium, the rate of ammonium oxidation is limited by its uptake, then active transport or passive diffusion of ammonium will become the first irreversible step and thereby set the observed value of 15ε(NH4+). Indeed, for assimilatory uptake by a marine bacterium, 15ε(NH4+) has been shown to depend on the external ammonium concentration, varying from 3.8 to 26.5‰ across an ammonium concentration range of 0.3 to 316 mg-N/L, as the first irreversible step changes from active transport at low NH4+ concentrations to diffusion at intermediate concentrations and the enzymatic reaction associated with assimilation at high concentrations18.In the process of NH4+ uptake by anammox bacteria, a number of steps could imaginably impact the isotope effect imparted on the ammonium pool. Prior to oxidation within the anammoxosome, ammonium must cross three membranes to reach the Hzs enzyme44. This is distinct from many other respiratory processes in the N cycle, including aerobic ammonia oxidation, where ammonia is thought to be oxidized in the periplasm45,46. Metagenomic characterization of anammox bacteria in the mainstream system used in these experiments reveals the presence of genes for amt ammonium transporters in these species23, while past studies of Ca. Kuenenia stuttgartiensis shows that anammox bacteria feature a number of genes homologous to those that express AmtB ammonium transporters in other bacteria47,48. These transporters could function to transport ammonium across two membranes, first into the cytoplasm and then into the anammoxosome49. In addition, passive, diffusive influx of ammonium into the cell could play a role, especially at relatively high external ammonium concentrations. Therefore, it is easily imaginable that under different physiological conditions, the observed value of 15ε(NH4+) could reflect (1) free motion of ammonium into the anammoxosome and the full expression of the isotope effect associated with NH4+ oxidation, (2) irreversibility in either of two active transport steps, or (3) irreversibility of diffusive transport of ammonium into the periplasm.We do not know the N isotope effects for ammonium diffusion into the cell and ammonium transport to the anammoxosome. But in analogy to considerations made for the diffusion and active transport of nitrate and active transport into the cells of denitrifying bacteria41, we conclude that it is reasonable to expect the N isotope effects for both passive ammonium diffusion and active transport to be much smaller that the enzyme-level N isotope effect associated with the actual ammonium oxidation. Therefore, when external ammonium is relatively low, and NH4+ transport becomes the rate-limiting step in anaerobic ammonium oxidation, the overall N isotope effect will approach that associated with NH4+ uptake or transport, and will likely be lower than under NH4+-replete conditions, where the full expression of the isotope effect associated with NH4+ oxidation may be expressed. This also supports the observation (Fig. 6) of decreasing 15ε(NH4+) under decreasing ammonium availability.Importantly, in a different microbial setting, e.g., in an oceanic environment, which has anammox bacteria with different (e.g., higher) affinities for ammonium uptake and oxidation, we predict that the same endmember values of 15ε(NH4+) that are seen in these experiments will be observed, but with the relationship between them unfolding at different (e.g., lower) values of ammonium concentration, cell densities, and in turn different cell-specific anammox rates. It is also important to note that the cell-specific anammox rate, not the bulk reaction rate, is the essential parameter for understanding the balance between the different processes at work. Unfortunately, because of the biofilm-dwelling nature of the anammox communities in this study, it is challenging to estimate accurately the number of anammox cells present, and so we were not able to determine the cell-specific anammox rate in our experimental setup. Yet, even at substrate concentrations that are much higher than those typically found in the natural environment, NH4+ uptake can be limiting if the bacterial cell density is high, as is the case in this study.For understanding the role that the balance between ammonium uptake and oxidation may play in controlling 15ε(NH4+), it is useful to compare anammox bacteria to aerobic ammonia oxidizing bacteria (AOB) and archaea (AOA). It is notable that the range of 15ε(NH4+) is similar for anammox bacteria and aerobic ammonia oxidizers; the AOB and AOA express values of 15ε(NH4+) between 14 and 42‰14–17. AOB and AOA perform catabolic ammonia oxidation using the ammonia monooxygenase enzyme. In AOB, this enzyme is located in the periplasm45,46, not in an internal cell structure like the anammoxosome, and so it is unlikely that active transport controls observed isotope effects. Instead, it has been proposed that variations in 15ε(NH4+) for the AOB are related to sequence variations in ammonia monooxygenase16. But recent results from Kobayashi and coworkers suggest that 15ε(NH4+) for anammox bacteria is species-independent; for the three different species tested under similar experimental conditions, the N isotope effects were consistent19. In our experiments, variations in the 15ε(NH4+) values were observed in mainstream and enrichment experiments, where the anammox bacteria population is expected to be similar, which also argues against species dependence. Indeed, the Hzs enzyme seems well conserved across anammox clades50, and, therefore, the ammonium N isotope effect variation observed here cannot be attributed to sequence variations, and is more likely due to the changing experimental conditions (NH4+ concentrations), as discussed above.Irrespective of the explanations for the observed N-isotope effect variability for both ammonium oxidation modes, the overlap in the ranges of values for 15ε(NH4+) for anammox and aerobic ammonia oxidation suggests that in a system that might be either aerobic or anaerobic, the mechanism of ammonium oxidation cannot necessarily be identified based on the ammonium N isotope signature. That is, an enrichment in 15 N associated with ammonium consumption cannot be attributed to ammonia oxidizing bacteria or anammox bacteria based on this measurement alone. Further work to compare the responses of both aerobic ammonia oxidizers and anammox bacteria to changing concentrations and cell-specific reaction rates would be helpful for identifying the overall environmental controls on 15ε(NH4+) under both oxic and anoxic conditions.
    15ε(NO2
    –) reflects a mixture of processesThe parameter 15ε(NO2–) reflects the weighted sum of the isotope effects for the consumption of nitrite by reduction to N2 and by oxidation to nitrate, and so its value depends on these two processes, as well as upon the stoichiometric ratio between them. For considering the physiology of anammox and its role in a biogeochemical N cycling network, it is of limited use, but in a system where the δ15N of nitrite can be readily measured it is valuable to know how to interpret it. It exhibits relatively little variation across the experimental conditions described here, and is also consistent with the result reported by Brunner and coworkers for Ca. K. stuttgartiensis enrichment cultures (Fig. 3)10, but our results differ from 15ε(NO2–) values for other anammox species by Kobayashi and coworkers19. The principal cause of the constancy of 15ε(NO2–) in these experiments is likely the stability of 15ε(NO2––N2) across all experiments, and is discussed in the sections that follow.The N isotope effect associated with the reduction of nitrite by anammox, 15ε(NO2
    ––N2), reflects the microbial communityThe N isotope effect associated with the reduction of nitrite to N2 in anammox, 15ε(NO2––N2), is consistent across all three experimental settings (Fig. 5), which is notable when compared to the broad range in 15ε(NO2––N2) observed in previous pure culture experiments with members of the genera Ca. Kuenenia, Ca. Scalindua, Ca. Jettenia, and Ca. Brocadia10,19, as well as in anammox incubation experiments20. This consistancy is also striking in light of the variation of 15ε(NH4+) observed in this study, and suggests that variations in substrate concentrations, reaction rates, or other physiological conditions are not strong controls on 15ε(NO2––N2). Instead, the identity of the anammox bacteria, and in turn its biochemical processing of nitrite, appears to exert control over this isotope effect. In the mainstream system used for these experiments, it has been shown that species in the genus Ca. Brocadia are the principal members of the anammox community present, but that Ca. Kuenenia and Ca. Jettenia are also represented (Table S1)23. Indeed, using the metagenomic characterization of the mainstream system reported by Niederdorfer and coworkers23, as well as the observed values of 15ε(NO2––N2) from previous studies10,19, we calculate an expected value of 15ε(NO2––N2) for the mainstream system of 7.5‰ ± 5.5‰ (1 s.d.). This result is close to, but distinct from, the observed value, and leads to the conclusion that 15ε(NO2––N2) in these systems is the result of a stable mixture of different anammox species, but that the contribution of different species to anammox activity under a specific set of experimental conditions may not directly reflect their cellular abundance. Likewise, although we do not yet know the microbial community composition of the material used in the sidestream experiment, we predict, based on its consistent value for 15ε(NO2––N2), that it is similar to that seen in the mainstream and enrichment settings, and we speculate that this microbial community has been stable over the course of the ~ 5 years between 2014 and 2019.The distinct values of 15ε(NO2––N2) observed for different species can be connected to key variations in the anammox metabolism. Although the canonical anammox mechanism includes the reduction of nitrite to NO by a nitrite reductase enzyme51, genomes of anammox bacteria of the Genus Ca. Brocadia52,53, including 5 of 6 metagenome-assembled genomes for bacteria in the mainstream system used in this study23, typically lack any canonical nitrite reductase in their genomes. Instead, it has been proposed that Ca. Brocadia do not produce NO and instead have hydroxylamine as the intermediate between nitrite and hydrazine52. This hypothesis is supported further by the nature of Hzs, which has two catalytic centers, one of which reduces NO to hydroxylamine, while the second conproportionates hydroxylamine and ammonia to generate hydrazine54; it is possible that Ca. Brocadia can bypass NO entirely and deliver hydroxylamine directly to Hzs.In contrast, Ca. Kuenenia, Ca. Scalindua, and Ca. Jettenia all include a canonical nitrite reductase in their genomes. Indeed, Kobayashi and coworkers19 observed that the offset in 15ε(NO2––N2) between measured values for Ca. Kuenenia and Ca. Scalindua, which have the iron-bearing nitrite reductase NirS, and Ca. Jettenia, which has the copper-bearing nitrite reductase NirK, corresponds to that observed for NirK and NirS in bacterial denitrifiers55. This interpretation is complicated by the observation that the genes for these canonical nitrite reductases are often not expressed49,56 or translated57 under environmental conditions. Nevertheless, the differences in N isotopic discrimination of nitrite among anammox clades appear to correspond to fundamental differences in the conversion of nitrite, but the molecular mechanisms of these steps remain poorly understood.Inverse isotope effect imparted in 15ε(NO2
    ––NO3
    –) by nitrite oxidationA pronounced inverse isotope effect, in which nitrate becomes enriched in 15 N relative to nitrite from which it is produced, was observed in all experimental settings. Such an inverse isotope effect appears to be a signature feature of microbial nitrite oxidation to nitrate, both under oxic and anoxic (i.e., anammox) conditions58,59 In culture-based experiments with nitrite oxidizing bacteria (NOB), 15ε(NO2––NO3–) has been found to vary between − 7.8‰ and − 23.6‰59,60, while anammox bacteria have been shown to express 15ε(NO2––NO3–) values in pure or highly-enriched cultures between − 30 and − 45‰10,19, with values as low as − 78‰ in a wastewater incubation experiment20. In our experiments, we found N isotope effects that cover nearly this whole range (Fig. 4). In both anammox and the NOB, nitrite oxidation is thought to be performed by the enzyme nitrate:nitrite oxidoreductase (Nxr)25,43,59, which is also closely related to bacterial membrane-bound and periplasmic nitrate reductases61,62. The structural details of the Nxr enzyme family are not yet well explored, especially in light of its diverse metabolic roles63, and so it remains unclear what metabolic or microbial processes are responsible for the observed and reported variation in 15ε(NO2––NO3–). At least for anammox bacteria, the inverse kinetic N isotope effect associated with the enzymatic oxidation of nitrite to nitrate may be superposed in part by a relatively large equilibrium N isotope effect between nitrite and nitrate10, perhaps promoted by the reversibility of the enzymatic nitrite oxidation reaction64. It is notable that the most negative end of the observed range for 15ε(NO2––NO3–) in this study approaches the theoretical limit for the isotope effect set by the N isotope equilibrium between nitrite and nitrate, which at 20 °C is – 54.6‰59, and which the NOB have not been observed to approach. This suggests that under the metabolic conditions of anammox, the Nxr enzyme is more likely to catalyze reversible reactions, and so the corresponding N isotope effect is closer to the equilibrium limit, than in aerobic nitrite oxidation. However, the great range observed in 15ε(NO2––NO3–) for anammox makes it difficult to predict a priori how much fractionation anammox will impart on a nitrate pool.On the other hand, observations in this study and elsewhere10,19 (Fig. 4) of values of 15ε(NO2––NO3–) falling near − 30‰ for nitrate generated by anammox match a prediction from water column measurements of N isotope ratios in nitrate and nitrite in the Peru oxygen deficient zone (ODZ)65. The large and variable magnitude of this inverse isotope effect means that even though only ~ 25% of the nitrite oxidized by anammox is converted to nitrate, it can have an outsize effect on nitrate and nitrite pools that can be mistaken for either nitrite oxidation by NOB or nitrite generation by denitrification.Implications for N isotope measurements in natural and engineered environmentsTaken together, the results measured in this study suggest both potential and pitfalls for the application of N isotope measurements to disentangle the systematics of microbial N cycling processes. By its interaction with the nitrate, nitrite, ammonium, and N2 pools, anammox already complicates analysis of the N cycle in any setting where it acts; not only does it impact the stable isotope pools of these molecules, but also its effects on each of these pools can vary greatly depending on physiological or metabolic variables or the identity of the dominant anammox bacteria species. In the context of a wastewater treatment process, measurements of δ15N alone may not be able to directly diagnose what processes are occurring, but when coupled to rate and stoichiometry measurements, may provide insights into the efficiency or limitations of those processes.The removal of 15 N-depleted N by anammox may partly explain the heavy N isotope values ( > 15‰) for nitrate in ODZs that have been formerly attributed to denitrification alone. It remains uncertain, however, what the exact expression of the range of N isotope effects reported here is under natural and variable substrate concentrations. First, as shown here for ammonium, concentration levels will have an effect on the relative kinetics of uptake and oxidation, and in turn on the cell-specific N isotope effect. Second, ammonium concentrations are generally at or below detection in the interior of OMZs, indicating that ammonium supplied by degradation of organic matter may be quantitatively oxidized to N2 by anammox. Under these conditions, the N isotope effect associated with the conversion of ammonium to N2 will be suppressed. Previously published estimates of the overall N isotope effect of dissolved inorganic N (DIN) elimination to N2 in ODZs based on comparing nitrate δ15N values to observed water-column nitrate deficits has inherently included any potential non-fractionating loss of ammonium, and has thus implicitly represented a community N loss isotope effect that depends on the balance between anammox and canonical denitrification. The overall expression on DIN lost by the combined processes of denitrification and anammox in sediments, however, may be completely different. In contrast to nitrate and nitrite66, ammonium is usually not limiting in sediments and its fractional loss to overlying waters allows the N isotope effect of ammonium oxidation to N2 by benthic anammox to be expressed.In both natural and engineered systems where anammox is known to be occurring, measurements of 15ε(NH4+) may be able to diagnose substrate limitations or other physiological limitations. And in the case where ammonium is observed to be consumed by an unknown pathway, it can be expected that isotope effects will fall into a similar range for both aerobic and anaerobic ammonium oxidation; on the other hand, 15ε(NH4+) is of little use for distinguishing ammonium consumption by AOB and anammox. We have also found that despite the great possibility for variation in 15ε(NO2––N2) amongst different anammox species, values of 15ε(NO2––N2) remain relatively stable in a given system that has a stable microbial community, and so this parameter has some potential to be used in monitoring such microbial community stability. Further work is needed to explore how metabolic variation amongst anammox species is related to variations in this parameter, but it appears that subtle changes in the mix of anammox species present, which have no observed effect on anammox rates or stoichiometry can lead to major changes in 15ε(NO2––N2). Finally, this study expands the range of 15ε(NO2––NO3–) for anammox bacteria. On one hand, this result lends further support to the observation that through a strong manifestation of the inverse isotope effect associated with nitrite oxidation, anammox can produce nitrate strongly enriched in 15 N, thereby complicating N mass balances based on tracking the nitrate pool. But we also find that anammox can have 15ε(NO2––NO3–) values much closer to 0‰, falling in the same range as for NOB bacteria, so the contribution of anammox to the δ15N composition of the nitrate pool can in fact vary greatly. Finally, we find that there are no systematic relationships among 15ε(NH4+), 15ε(NO2––N2), 15ε(NO2––NO3–), which is consistent with the conclusion that each of these parameters is controlled at a distinct point in the anammox metabolism. More

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    The first record of exceptionally-preserved spiral coprolites from the Tsagan-Tsab formation (lower cretaceous), Tatal, western Mongolia

    SizesAs from the measurements, all collected coprolites vary in sizes (Table 1). The smallest and complete specimen is IVPP V 27,545 (Fig. 2D–G), and while IVPP V 27,550 (2 V-Z) is multiple time larger. The maximum length for specimen IVPP V 27,544, IVPP V 27,546, IVPP V 27,547 and IVPP V 27,549 have not been determined due to their incompleteness.Table 1 Biometrical and morphological features of spiral coprolites from Tsagan-Tsab Formation (Lower Cretaceous), Tatal, western Mongolia. Paul Rummy, Kazim Halaclar & He Chen.Full size tableSurface adhesion and marksAll specimens contained some degree of bone fragments and rhomboidal-shaped ganoid scales adhered to the coprolite surfaces (Fig. 3). Additionally, all specimens have smooth surfaces with little abrasion. The inner coil lines of specimen IVPP V 27,549 adhered with a matrix of red clay with silt (Fig. 2S–U). Only specimen IVPP V 27,550 has been seen with concentric cracks (Fig. 2V–Z). Bite marks have also been found on specimen IVPP V 27,545, in which these traces were short, parallel, shallow and isolated. They have been formed from 3 furrows of roughly 3.8 mm long and 0.3 mm deep (Fig. 4).InclusionsThrough CT scans and surface observation, we noticed that all specimens contained bone fragments and scales of varying degrees (Fig. 5). We were unable to identify the bones in detail for specimen IVPP V 27,544, IVPP V 27,546, IVPP V 27,547, IVPP V 27,548, IVPP V 27,549 and IVPP V 27,550, as they were excessive in amount and extremely fragmentary. On the contrary, for specimen IVPP V 27,545, we noticed a rather complete bone structure, such as the ribs and a segment of an infraorbital (Fig. 5H–N). SEM photograph from one random point of specimen IVPP V 27,545 yielded results of the existents of pollen grain (Fig. 6C).BoringsSurface borings of invertebrate burrowing can be seen in 2 spiral coprolites, namely IVPP V 27,547 (Fig. 2D–G) and IVPP V 27,550 (Fig. 2V–Z). CT scans revealed that the borings of specimen IVPP V 27,550 did not intrude internally, and it was the same for some of IVPP V 27,547 as well (Fig. 7). Specimens IVPP V 27,546, IVPP V 27,547, IVPP V 27,548 and IVPP V 27,549 are shown to have traces of internal borings (Fig. 5C–F).EDS analysesIn this work, in regards to Tatal’s coprolites, the mineral elements were examined by using EDS and the photos were taken with SEM. Analyses was conducted on 2 specimens (IVPP V 27,546 and IVPP V 27,545) with two sample points for each. All 4 samples showed high peaks of calcium and phosphorus. EDS results of specimen IVPP V 27,546 (Fig. 6A–B) and specimen IVPP V 27,545 (Fig. 6C–D) gave similar atomic compositions. They were mainly composed of Ca, P and O and small peaks that belong to Nb, Si, C, K, Fe and Al. We have also described a potential pollen structure under SEM image (Fig. 6C). This possible pollen structure in specimen IVPP V 27,545 (Fig. 6C) showed different atomic elements from the other EDS results, where it contained high peaks of Na and Cl.Taphonomy inferencesNo signs of abrasion were found on all of the coprolites. Coloration of the coprolites varied, thus, indicating they were buried in different sedimentary conditions. Through the shape of the coprolites, we can deduce that they have indeed spent different amounts of time or phases in water bodies before burial (see above description/discussion). Meanwhile, specimen IVPP V 27,550 showed shallow coil deepness, therefore, this indicates that it was buried rapidly after excretion.Discussion and interpretationThere are several pivotal evidences that corroborate to fecal origins of the Tsagan-Tsab Formation material: (1) basic morphology; (2) general shape and size (3) inclusions of the fecal matter; (4) high calcium and phosphorus content; (5) bioerosional scars; (6) borings and cavities; (7) concentric cracks.The fundamental puzzle in the studies of coprolite is the difficulty in identifying the potential producer, which can be due to their nature and preservation. Also, that includes the methods used to deduce them with their producer, which were done by inferring with various forms of relationship based on stratigraphy and geographical relationships, as well as on neoichnology studies7,23,54,55. Such problems similarly arose in our context as well, and the materials were collected from a stratum that were interpreted as lake deposit margins, thus, suggesting an amphibious or aquatic producer. The paleoenvironment correlates with the findings of pterosaur fossils such as the Noripterus44 or argued as ‘Phobetor’56, and the diets of these pterosaurs were dependable on the lake environment57,58,59,60. Above all, and more importantly, that the shape of the coprolite has to be intact in order to represent the shape of the internal intestine of the producer, whereby, anatomically it can lead to a certain biological aspect and digestive system of the organism. Despite these, there are on-going controversies on the origin of the spiral shaped bromalites in regards to whether or not they signify fossilized feces, or they are the cololite that was formed within the colon6,21,23,61,62.Spiral coprolites are producer of an animal with spiral intestine valves to increase the surface area of absorption, to slow down food movement in the bowel to maximise nutrient absorption, which has a significant strategy in surviving uncertain and harsh environment conditions28,63,64. Referring to past literature, it is generally agreed upon that the spiral shape is the only distinctively coprolite morphology, whereby it has been regarded as a true coprolite and can be correctly associated to the source animal, such as a range of fishes in particular6,22,52. Many primitive bony fishes (except those of teleosts), fresh water sharks (elasmobranches), coelacanths, Saurichthys, sturgeons and lungfishes are known to have the spiral valve intestine51,64,65,66. Also, Price67 suggested that the amphipolar form could have been derived from palaeoniscoids. Additionally, Romer & Parsons68 noted that the spiral valves are secondarily lost in teleost and tetrapods, while Chin69 noted a few teleosteans still possessing them.The spiral coprolites collected for this study are mainly amphipolar in shape and one in scroll. As we know, generally heteropolar spiral coprolite are produced by sharks, which have complex spiral valves62. Therefore, we can exclude those in the family of elasmobranches as the potential producers and this can also be supported by the non-marine geological settings of Tsagan-Tsab Formation. But it is also noteworthy to mention that in previous studies, some workers have conducted observations on sharks that were kept in tanks, and were not been able to find any spiral fecal pellets. The reasons given were that the sharks’ eating habits could have changed due to the tank environment, which would have differed from the natural marine environment. Also, modern day sharks are totally unrelated to the ancient Permian pleuracanth sharks6. Despite these, evidence of spiral fecal pellet can still be observed in some of the present-day fishes, such as the African lungfish Protopterus annectans, the Australian lungfish Neoceratodus forsteri, the long-nosed gar Lepisosteus osseus and the spotted gar Lepisosteus oculatus6,70,71,72. As for scroll coprolites, it is generally known to be produced by animal with longitudinal valves (valvular voluta), whereby the valves naturally rolls in upon itself , in a way that it maximises nutrient absorption8,9,17,18. Gilmore17 in his work mentioned that this type of valve must be primitive than the transverse valve (valvular spiralis), which could be a modification of the previous ones. This form is especially known to sharks of carcharhiniforms73, and it is evident that it could have been associated with sarcopterygian53, as well as anaspid and thelodont agnathans17.In this study, we recognised four new ichnotaxa for all the seven coprolite specimens. Assigning four new ichnotaxa does not conclude that the coprofauna are of four different types of animals. Considering there are two distinct morphologies, which are the amphipolar spiral and scroll, we can deduce that at least two animals can produce these coprolites. But we have to carefully consider that diverse diets at different times for the same animal can often be variable, and soft fecal materials can range disparately after defecation, as well as taphonomy influence74,75. Specimen IVPP V 27,550 is remarkably huge and its producer should be a massive animal since large animals could produce small excrement, but small animals would not be able to produce big excrement52,54. Moreover, since there are no relevant fossils fauna found in the locality, we were unable to exactly identify the specific producer, rather, we deduced with relevant sources. However, we do know that both amphipolar spiral and scroll coprolites can be attributed to certain types of fishes. As of these, we can conclude that the coprolites were produced by fishes in different sizes. Specimen IVPP V 27,545 differs from the rest by its shape and size, which makes prediction even harder, because it could be produced by either large or smaller animals.CT scans revealed that bony inclusions are evident in all of the coprolites (Fig. 5). However, except in specimen IVPP V 27,545, the bones in the rest of the coprolites are fragmentary. Specifically, bones in specimen IVPP V 27,545 are rather unaffected by the acidity of the digestive enzyme and these were evident by the presence of clusters of entire bones in the coprolite (Fig. 3A–C), as contrast to the fragmentary bones in the rests of the coprolites. Furthermore, we identified an infraorbital bone of a fish. CT scans revealed that the infraorbital bone has a sensory canal where it branches off at both ends (Fig. 5M–N). With these, we can indicate that the producer of specimen IVPP V 27,545 poorly masticated the prey and also had a rather low gut digestion for food28,55,76,77,78. Through these results, we can infer the digestive strategies of the producers were in correlation with food intake and digestion process, as discussed in Barrios-de Pedro & Buscalioni77. Specimen IVPP V 27,545 might belong to the first type of digestive strategy, whereby the producer has limited food processing in the mouth and the food stays in the digestive system for a short period of time. This strategy is regarded to be efficient in conditions where food sources are abundant and the nourishment levels are sufficient79. The rest of the coprolites possibly belong to the second digestive strategy, as the bone content is fragmentary. This suggest the producer might have limited mastication with improved digestive assimilation and longer gut time to favour better absorptions of nutrients55,80,81,82,83. The third type of digestive strategy does not imply in our study. It is also noteworthy to mention that the quantity of the inclusions is not correlated to the size of the coprolite, rather, it is dependable on the above-mentioned biological variables28,84.Carnivorous coprolites are normally composed of calcium phosphate and other organic matter, but it is important to be aware that the initial compositions are usually altered during fossilization processes33. Meanwhile, the excretion of herbivores is generally lacking in phosphates and their fossilization are mostly dependable of the mineral enrichment85. Through the morphological shape, the density of bone and scale inclusions on the surface from the CT scans, we can directly assume that these coprolites are inevitably produced by carnivorous organisms. Despite that, we still conducted SEM–EDS tests on two specimens, IVPP V 27,546 and specimen IVPP V 27,545 (Fig. 6), in order to determine its mineral content, and to prove them as a valid coprolite material because we were not able to compare these materials to any attached locality matrix at the time the study. The reason for that was because the specimens were collected almost two decades ago and they were very well-kept in the archives throughout these years. As predicted, all 4 samples gave higher content of Ca and P, thus, there is no doubt that they are indeed fossilized fecal materials. Also, in regards to the SEM–EDS on specimen IVPP V 27,545 (Fig. 6C–D), when randomly pointed to a particular structure, it yielded unusual results from the rest, in which the EDS peaks are composed of Na and Cl. At the same time, the SEM image potentially showed a pollen grain like structure. Hollocher and Hollocher86 documented a pollen image by using SEM, which brings our potential pollen image (Fig. 6C) dimensionally compatible with their sample. Although specimen IVPP V 27,545 is produced by an unidentified carnivorous vertebrate, it is common for carnivore coprolites to have plant remains within them. Also, it is known that spores and pollens are exceptionally well preserved within the encasement of calcium phosphate, which inhibits sporopollenin degradation87. Various reasons can be inferred for the presence of the pollen in specimen IVPP V 27,545, to which it could either be by accident or by preying on an herbivorous animal. Furthermore, it could also be through the adhesion on the excrement when the fecal is still fresh88. Pollens are in fact valuable information provider for paleoenvironment reconstruction, as well as for understanding the vegetation state of a particular era87,89,90,91,92. Hence, further palynology analyses are needed for future work.EDS mineral composition and coprolite coloration can be correlated to a certain degree, in which it could also explain depositional origin27. Most of the Tatal’s coprolites are pink-whitish in color, which is highly associated with the presence of calcium through its carnivorous diets93,94,95,96. The dark colors can also be due to the presence of iron or it could also be due to complete phosphatisation23,27. However, a large part of the colorations was influenced by diagenesis27,28.Traces of burrows are evident on the surface of specimen IVPP V 27,547 and IVPP V 27,550, but CT scans revealed internal traces burrowing did occur in specimen IVPP V 27,546, IVPP V 27,547, IVPP V 27,548 and IVPP V 27,549 (Fig. 5). Since not all possible burrows were dug-in, we gave the term ‘pseudo-burrow’ on those burrows that were abandoned in the early stages. For example, on all of the burrow traces in specimen IVPP V 27,547, only one traces showed burrowing holes, while the rest did not form a hole. While those specimens with internals, but without any traces on the outer surface, this can be explained by taphonomy processes, whereby the outer surface is covered with sedimentary and non-differentiable. It was reported in Tapanila et al.97, that marine bivalves are potential makers of the burrows in coprolites by expanding the diameter of the hole as they dig in, although Milàn, Rasmussen & Bonde98, reported a contradictory example, where the holes were indeed constant in diameter. In our study, we couldn’t determine if the holes were constantly in diameter or not. Numerous tiny holes were visible on all of the coprolites surface, as well as within it, and these were most probably caused by gases within the fecal matters. These holes can be called as microvoids or ‘degassing holes’, which contain gases trapped during digestion74,99,100. Microvoids are quickly filled with water when fecal matter is excreted from the animal body, thus making the fecal becoming heavy and sinking to the lake floor74.A series of three parallel furrows or bioerosional scars were evident on the surface of specimen IVPP V 27,545 (Fig. 3). Those lines only occurred once without any repetition on the rest of the surface. The information from these furrows were insufficient to deduce any potential biters, as widely discussed in the work of Godfrey & Palmer101, Godfrey & Smith102, Dentzien-Dias et al.103, and Collareta et al.104. On the other hand, deducing from the dented surface on the bitten marks, we predicted that the marks were most probably made by the biting pressures from the fish mandibles, which may indicate coprophagous behavior. The biting could have happened on the lake floor just before sedimentary deposition. Since the bitten marks are on the surface, this probably suggests unintentional scavenging and was eventually aborted during food search.In general, coprolites can be transported from the original place through various modes25 and this can be evident by the traces of abrasion51,65. However, in Tatal’s coprolites, there were little or almost no marks of abrasion. Yet again, this supports our hypothesis that these coprolites were excrements in shallow waters, such as in the lake banks with little turbulence and current, where the fecal matter was dropped in-situ after excrement. As stated in previous literature105,106, radial and concentric cracks are also evident on the surface of specimen IVPP V 27,550, therefore, these indicate that the coprolite was excreted on a very shallow environment where the water body was vastly evaporated and left for subaerial exposure before embedment. This phenomenon caused the coprolite to dehydrate through the cracking, and shrinking occurred in a low magnitude process while retaining its overall shape27,54,107. Previous authors have also discussed that the cracks could possibly be due to synaeresis under certain conditions27,54,108.It has been frequently reported in records that almost all spiral coprolite fossilization from various Phenerozoic ages have occurred in low-energy shallow marine environments54. Feces that are being excreted in this humid environment have a higher chance of preservation due to the rapid burial, as well as on the acidity level of the water bodies5,7,109,110,111. There are also several crucial factors that are involved in fecal fossilization. Among them, one of the most important criteria includes the content and composition of the fecal matter, and those of carnivorous diets tend to form coprolites than those who consumed an herbivorous diet75. As mentioned in Dentzien-Dias et al.111, there are three main stages involved in a coprolite taphonomy history, which include stages before final burial, after the final burial and after exposure. In accordance to this, we introduced the usage of phases to discuss the spiral coprolites morphologies in this study (see material and methods). The phase concept of spiral coprolites disentanglement has been widely discussed in early days by various workers6,22,70. Coprolite specimen IVPP V 27,544 and IVPP V 27,547 are considered as Phase 1, as the coils are not deep, and this can be explained as during excrement, there’s a mucosal membrane covering the surface of the fecal matter and embedment occurring rapidly, thus retaining most of its surface structure. Although there are signs of disentanglement, we predict that the uncoiling on the surface was not by natural processes, but has been caused by a breakage after on. Both of these two coprolites could have been large in actual size. Similar explanations can be given to specimens IVPP V 27,548 and IVPP V 27,550, whereby the coils are shallow, thus, classifying them as to had occurred in Phase 1. We classify specimen IVPP V 27,546 and IVPP V 27,549 as Phase 2, in which the spaces between the coils of IVPP V 27,546 were slightly separated and in IVPP V 27,549, they were strongly separated. Both of these specimens could have spent more time in water bodies before burial. Specimen IVPP V 27,545 does not provide any external information in regards of phases approach because of its non-spiral morphology. While it is also worthwhile to mention that none of them have spent sufficient time in the water bodies in order to possess the Phase 3 structure. Through these, we can also conclude that smaller coprolites are much complete while bigger coprolites tend to easily break-off. However, having mentioned that, the preservation of specimen IVPP V 27,550 is indeed valuable.Through the above morphological points, we predict that the amphipolar spiral coprolites could have belonged to groups of either prehistoric lungfishes or Acipenseriformes (sturgeon and paddlefish). Another aim of this work is to portray the existence of possible prey-predation relationships from the collected coprolites. In order to narrow down the identity of the potential producer and possibly the prey, we looked into some related fauna list from past literature. Geological settings have indicated that the Lower Cretaceous Tsagan-Tsab formation is not only recorded in the area of Tatal, but also in other regions of Mongolia as well36. There are two possibilities on the deduced prey and predator, they are either of Asipenceriformes—Lycopteriformes relationship or Asipenceriformes—Pholidophoriformes relationship. We suggest Pholidophoriformes as a much potential prey than the Lycopteriformes in the Tsagan-Tsab Formation, and the reasons will be explained thoroughly. As for the producer, we knew that Asipenceriformes are largely known from the Lycoptera-Peipiaosteus (Asipenceriformes) Fauna or the “Jehol Fauna”, as these assemblages of fishes were not only abundant in the Lower Cretaceous Yixian Formation of northeastern China, but also widely distributed over the region of eastern Siberia, Mongolia, northern China and northern Korea112. It is also noteworthy to mention that the Tsagan-Tsab formations and the Yixian formation were similar in geological age. In the same context, Jakolev35 described Stichopterus popovi (Asipenceriformes) and recorded amphipolar spiral coprolites from the Aptian lacustrine of Gurvan-Eren Formation of Mongolia , a locality that is close to Tatal. Although there are differences in the geological period of Tsagan-Tsab and Gurvan-Eren Formation, it is highly possible that Asipenceriformes existed in these areas. Furthermore, Asipenceriformes are shown to have spiral valves113, and this can be further proven with the work of Capasso64 on Peipiaosteus pani, thus, contributing to the morphology of the spiral coprolites. With these, we strongly suggest that the amphipolar spiral coprolites of Tsagan-Tsab Formation and for Gurvan-Eren Formation to belong to Asipenceriformes. As for prey, we know from existing literature that there is a close relationship between Asipenceriformes and Lycoptera, as evident in the name Lycoptera-Peipiaosteus Fauna. Yondon et al.36 reported Lycoptera middendorfii, a form of small freshwater Teleost fish from the Eastern Gobi—Tsagan-Tsab formation. But, it was clearly mentioned that Bon-Tsagan/Bon-Chagan (Fig. 1) is the westernmost locality of Lycoptera in Mongolia114. Another fact that was taken into account for the possible prey is the shape of the scales found in the inclusions, whereby Lycoptera are known for their cycloid shaped scales, while the ones in our specimens are more towards rhomboidal-shaped ganoid scales. These facts crucially eliminate the possibilities of Lycoptera for the Tsagan-Tsab fauna. With this, we further examined Jakolev35′s works and discovered the species that he described, Gurvanichthys mongoliensis (Pholidophoriformes) from the Gurvan-Eren Formation has rhomboidal-shaped ganoid scales. The size, shape of the scale and the nature of this fish fits well as a prey for the Stichopterus popovi (Asipenceriformes). Through these interpretations, we can possibly infer that the spiral coprolites in our study might have belonged to Asipenceriformes and Pholidophoriformes as the prey, which could further affirm the occurrence of prey-predator inter-relationship in the Lower Cretaceous of Tsagan-Tsab Formation.As for the sole scroll coprolite in this study, we do not intend to further deduce any detailed possibilities. Based on other works, chondricthyans origins or a sarcopterygian for scroll coprolites were suggested18,53,but such deduction is difficult to be purported in our studies as there is a lack of such fossil materials in the locality and surrounding localities. The chances of the underived producer to be a sarcopterygian is much higher than to be a chondricthyan, mainly due to its geological settings. The discovery of the single scroll coprolite can be a window opening to many paleontological questions for Tsagan-Tsab Formation. More

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    Evaluating sediment and water sampling methods for the estimation of deep-sea biodiversity using environmental DNA

    High-throughput sequencing resultsA total of 26 million COI reads, 19 million raw 18S V1-V2 reads,, 14 million 18S V4 reads, and 17 million 16S V4–V5 reads were obtained from three Illumina HiSeq runs of amplicon libraries built from pooled triplicate PCRs of 22 environmental samples, 2 extraction blanks, and 4–6 PCR blanks (Supplementary Table S4 online). The in situ pump yielded less raw reads for COI and 16S (Supplementary Fig. S1 online, F = 4.02–14.4, p = 0.0003–0.03), while more raw reads were recovered from both water sampling methods with 18S V4 (F = 6.5, p = 0.007). Water samples generally yielded fewer raw clusters (F = 5.1–35.1, p = 3.2 × 10−6–0.02), except for 18S V4 where numbers were comparable across sample types (Supplementary Fig. S1 online).Bioinformatic processing (quality filtering, error correction, chimera removal, and clustering for metazoans) reduced read numbers to 20 million for COI, 12 million for 18S V1–V2, 11 million for 18S V4, and 10 million for 16S V4–V5, resulting in 10,351 and 17,608 raw OTUs for COI and 18S V1–V2 respectively; 35,538 raw 18S V4 ASVs, and 62,646 raw 16S ASVs (Supplementary Table S4 online). For eukaryote markers, 17–55% of the raw reads remained in PCR blanks after bioinformatic processing, while 50–75% remained in extraction blanks and 52–87% in true samples. In contrast, with 16S, these values were at 87% for PCR blanks, 67% for extraction blanks, and 29–73% for true samples. Thus, negative control samples accounted for 7–13% of bioinformatically processed reads with eukaryotes, compared to 27% with prokaryotes. The vast majority of 16S reads generated by negative controls belonged to a common contaminant of Phusion polymerase kits, which is well amplified in low concentration samples such as negative controls. These reads however accounted for  20 µm size class, and the sampling box targeting both the 2–20 µm and the 0.2–2 µm size classes, detected different community assemblages. For protists, the in situ pump detected higher proportions of ASVs for Bacillariophyta, Ciliophora, Labyrinthulea, or Phaeodarea, while the sampling box detected more cryptophytes, haptophytes, MAST, and telonemians (Fig. 3 18S V4). For prokaryotes, the sampling box detected more diversity in the Alphaproteobacteria, Chloroflexi, or Marinimicrobia (Fig. 3 16S V4–V5). More

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    Angiosperm pollinivory in a Cretaceous beetle

    1.Power, A. G. Ecosystem services and agriculture: tradeoffs and synergies. Phil. Trans. R. Soc. B 365, 2959–2971 (2010).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    2.Huang, D.-Y. et al. New fossil insect order Permopsocida elucidates major radiation and evolution of suction feeding in hemimetabolous insects (Hexapoda: Acercaria). Sci. Rep. 6, 23004 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    3.Grimaldi, D. A., Peñalver, E., Barrón, E., Herhold, H. W. & Engel, M. S. Direct evidence for eudicot pollen-feeding in a Cretaceous stinging wasp (Angiospermae; Hymenoptera, Aculeata) preserved in Burmese amber. Commun. Biol. 2, 408 (2019).4.Bao, T., Wang, B., Li, J. & Dilcher, D. Pollination of Cretaceous flowers. Proc. Natl Acad. Sci. USA 116, 24707–24711 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    5.Peris, D. et al. Generalist pollen-feeding beetles during the mid-Cretaceous. iScience 23, 100913 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    6.Ahrens, D., Schwarzer, J. & Vogler, A. P. The evolution of scarab beetles tracks the sequential rise of angiosperms and mammals. Proc. R. Soc. B 281, 20141470 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    7.Farrell, B. D. ‘Inordinate fondness’ explained: why are there so many beetles? Science 281, 555–559 (1998).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    8.Faegri, K. & van der Pijl, L. The Principles of Pollination Ecology (Pergamon, 1979).9.Poinar, G., Lambert, J. B. & Wu, Y. Araucarian source of fossiliferous Burmese amber: spectroscopic and anatomical evidence. J. Bot. Res. Inst. Tex. 1, 449–455 (2007).
    Google Scholar 
    10.Davies, E. H. Palynological Analysis and Age Assignments of Two Burmese Amber Sample Sets (Branta Biostratigraphy for Leeward Capital, 2001).11.Barrón, E. et al. Palynology of Aptian and upper Albian (lower Cretaceous) amber-bearing outcrops of the southern margin of the Basque-Cantabrian basin (northern Spain). Cretac. Res. 52, 292–312 (2015).Article 

    Google Scholar 
    12.Azar, D., Dejax, J. & Masure, E. Palynological analysis of amber-bearing clay from the lower Cretaceous of central Lebanon. Acta Geol. Sin. Engl. Ed. 85, 942–949 (2011).Article 

    Google Scholar 
    13.Barrón, E., Comas-Rengifo, M. J. & Elorza, L. Contribuciones al estudio palinológico del Cretácico Inferior de la Cuenca Vasco-Cantábrica: los afloramientos ambarigenos de Peñacerrada (España). Coloq. Paleontol. 52, 135–156 (2001).
    Google Scholar 
    14.Cai, C. et al. Basal polyphagan beetles in mid-Cretaceous amber from Myanmar: biogeographic implications and long-term morphological stasis. Proc. R. Soc. B 286, 20182175 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    15.Mao, Y. Y. et al. Various amberground marine animals on Burmese amber with discussions on its age. Palaeoentomology 1, 91–103 (2018).Article 

    Google Scholar 
    16.Shi, G. et al. Age constraint on Burmese amber based on U–Pb dating of zircons. Cretac. Res. 37, 155–163 (2012).Article 

    Google Scholar 
    17.Yu, T. et al. An ammonite trapped in Burmese amber. Proc. Natl Acad. Sci. USA 116, 11345–11350 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    18.Jelínek, J. & Cline, A. R. in Handbook of Zoology, Arthropoda: Insecta, Coleoptera, Beetles Morphology and Systematics (eds Leschen, R. A. B. et al.) Vol. 2 386–390 (Walter De Gruyter, 2010).19.Hisamatsu, S. A review of the Japanese Kateretidae fauna (Coleoptera: Cucujoidea). Acta Entomol. Musei Natl Pragae 36, 551–585 (2011).
    Google Scholar 
    20.Peris, D. & Jelínek, J. Atypical short elytra in Cretaceous short-winged flower beetles (Coleoptera: Kateretidae). Palaeoentomology 2, 505–514 (2019).Article 

    Google Scholar 
    21.Peris, D. & Jelínek, J. Syninclusions of two new species of short-winged flower beetle (Coleoptera: Kateretidae) in mid-Cretaceous Kachin amber (Myanmar). Cretac. Res. 106, 104264 (2020).Article 

    Google Scholar 
    22.Poinar, G. & Brown, A. E. Furcalabratum burmanicum gen. et sp. nov., a short-winged flower beetle (Coleoptera: Kateretidae) in mid-Cretaceous Myanmar amber. Cretac. Res. 84, 240–244 (2018).Article 

    Google Scholar 
    23.Kirejtshuk, A. G. New species of nitidulid beetles (Coleoptera, Nitidulidae) of the Australian region. Entomol. Obozr. 65, 559–573 (1986).
    Google Scholar 
    24.Timerman, D., Greene, D. F., Ackerman, J. D., Kevan, P. G. & Nardone, E. Pollen aggregation in relation to pollination vector. Int. J. Plant Sci. 175, 681–687 (2014).Article 

    Google Scholar 
    25.Thomson, P. W. & Pflug, H. D. Pollen und sporen des mitteleuropäischen Tertiärs. Palaeontogr. Abt. B 94, 1–138 (1953).
    Google Scholar 
    26.Tekleva, M. V. & Maslova, N. P. A diverse pollen assemblage found on Friisicarpus infructescences (Platanaceae) from the Cenomanian–Turonian of Kazakhstan. Cretac. Res. 57, 131–141 (2016).Article 

    Google Scholar 
    27.Takahashi, K. Upper Cretaceous and lower Paleogene microfloras of Japan. Rev. Palaeobot. Palynol. 5, 227–234 (1967).Article 

    Google Scholar 
    28.Nadel, H., Peña, J. E. & Peña, J. E. Identity, behavior, and efficacy of nitidulid beetles (Coleoptera: Nitidulidae) pollinating commercial Annona species in Florida. Environ. Entomol. 23, 878–886 (1994).Article 

    Google Scholar 
    29.Sakai, S. A review of brood-site pollination mutualism: plants providing breeding sites for their pollinators. J. Plant Res. 115, 0161–0168 (2002).Article 

    Google Scholar 
    30.Williams, G. & Adam, P. A review of rainforest pollination and plant–pollinator interactions with particular reference to Australian subtropical rainforests. Aust. Zool. 29, 177–212 (1994).Article 

    Google Scholar 
    31.Klavins, S. D., Kellogg, D. W., Krings, M., Taylor, E. L. & Taylor, T. N. Coprolites in a Middle Triassic cycad pollen cone: evidence for insect pollination in early cycads? Evol. Ecol. Res. 7, 479–488 (2005).
    Google Scholar 
    32.Chadwick, C. E., Stevenson, D. W. & Norstog, K. J. The roles of Tranes lyterioides and T. sparsus Boh. (Col., Curculiodidae) in the pollination of Macrozamia communis (Zamiaceae). In The Biology, Structure, and Systematics of the Cycadales: Proc. CYCAD 90, the 2nd International Conference on Cycad Biology (eds. Stevenson, D. W. & Norstog, K. J.) 77–88 (Palm & Cycad Societies of Australia, 1993).33.Post, D. C., Page, R. E. & Erickson, E. H. Honeybee (Apis mellifera L.) queen feces: source of a pheromone that repels worker bees. J. Chem. Ecol. 13, 583–591 (1987).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.Weiss, H. B. & Boyd, W. M. Insect feculæ. J. N. Y. Entomol. Soc. 58, 154–168 (1950).
    Google Scholar 
    35.Lancucka-Srodoniowa, M. Tertiary coprolites imitating fruits of the Araliaceae. Acta Soc. Bot. Pol. 33, 469–473 (1964).Article 

    Google Scholar 
    36.Scott, A. C. Trace fossils of plant–arthropod interactions. Short Courses Paleontol. 5, 197–223 (1992).Article 

    Google Scholar 
    37.Weiss, H. B. & Boyd, W. M. Insect feculæ, II. J. N. Y. Entomol. Soc. 60, 25–30 (1952).
    Google Scholar 
    38.Parker, F. D., Tepedino, V. J. & Bohart, G. E. Notes on the biology of a common sunflower bee, Melissodes (Eumelissodes) agilis Cresson. J. N. Y. Entomol. Soc. 89, 43–52 (1981).
    Google Scholar 
    39.Sarzetti, L. C., Labandeira, C. C. & Genise, J. F. Reply to: Melittosphex (Hymenoptera: Melittosphecidae), a primitive bee and not a wasp. Palaeontology 52, 484 (2008).
    Google Scholar 
    40.Ohl, M. & Engel, M. S. Die Fossilgeschichte der Bienen und ihrer nächsten Verwandten (Hymenoptera: Apoidea). Denisia 20, 687–700 (2007).
    Google Scholar 
    41.Pant, D. D. & Singh, R. Preliminary observations on insect–plant relationships in Allahabad plants of Cycas. Palms Cycads 32, 10–14 (1990).
    Google Scholar 
    42.Labandeira, C. C. The paleobiology of pollination and its precursors. Paleontol. Soc. Pap. 6, 233–270 (2000).Article 

    Google Scholar 
    43.Procheş, Ş. & Johnson, S. D. Beetle pollination of the fruit-scented cones of the South African cycad Stangeria eriopus. Am. J. Bot. 96, 1722–1730 (2009).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    44.Tarno, H. et al. Types of frass produced by the ambrosia beetle Platypus quercivorus during gallery construction, and host suitability of five tree species for the beetle. J. For. Res. 16, 68–75 (2011).Article 

    Google Scholar 
    45.Friis, E. M., Pedersen, K. R. & Crane, P. R. Fossil floral structures of a basal angiosperm with monocolpate, reticulate-acolumellate pollen from the Early Cretaceous of Portugal. Grana 39, 226–239 (2000).Article 

    Google Scholar 
    46.Nambudiri, E. M. V. & Binda, P. L. Dicotyledonous fruits associated with coprolites from the upper Cretaceous (Maastrichtian) Whitemud Formation, southern Saskatchewan, Canada. Rev. Palaeobot. Palynol. 59, 57–66 (1989).Article 

    Google Scholar 
    47.Lupia, R., Herendeen, P. S. & Keller, J. A. A new fossil flower and associated coprolites: evidence for angiosperm–insect interactions in the Santonian (Late Cretaceous) of Georgia, U.S.A. Int. J. Plant Sci. 163, 675–686 (2002).Article 

    Google Scholar 
    48.Zhang, L. et al. The water lily genome and the early evolution of flowering plants. Nature 577, 79–84 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    49.Coiro, M., Doyle, J. A. & Hilton, J. How deep is the conflict between molecular and fossil evidence on the age of angiosperms? New Phytol. 223, 83–99 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    50.Liu, Z.-J., Huang, D., Cai, C. & Wang, X. The core eudicot boom registered in Myanmar amber. Sci. Rep. 8, 16765 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    51.Friis, E. M. & Pedersen, K. R. in Palynology: Principles and Applications (ed. Jansonius, J.) 409–426 (American Association of Stratigraphic Palynologists Foundation, 1996).52.Schönenberger, J. & Friis, E. M. Fossil flowers of ericalean affinity from the Late Cretaceous of southern Sweden. Am. J. Bot. 88, 467–480 (2001).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    53.The Angiosperm Phylogeny Group et al. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. Soc. 181, 1–20 (2016).54.Peris, D. et al. False blister beetles and the expansion of gymnosperm–insect pollination modes before angiosperm dominance. Curr. Biol. 27, 897–904 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    55.Cai, C. et al. Beetle pollination of cycads in the Mesozoic. Curr. Biol. 28, 2806–2812 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar  More

  • in

    Global climate and nutrient controls of photosynthetic capacity

    1.De Kauwe, M. G. et al. Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe. Biogeosciences 12, 7503–7518 (2015).Article 

    Google Scholar 
    2.Smith, N. G. & Keenan, T. F. Mechanisms underlying leaf photosynthetic acclimation to warming and elevated CO2 as inferred from least‐cost optimality theory. Global Change Biol. 26, 5202–5216 (2020).Article 

    Google Scholar 
    3.Farquhar, G. D., von Caemmerer, S. & Berry, J. A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149, 78–90 (1980).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    4.Wullschleger, S. D. Biochemical limitations to carbon assimilation in C3 plants—a retrospective analysis of the A/Ci curves from 109 Species. J. Exp. Bot. 44, 907–920 (1993).CAS 
    Article 

    Google Scholar 
    5.Lloyd, J., Bloomfield, K., Domingues, T. F. & Farquhar, G. D. Photosynthetically relevant foliar traits correlating better on a mass vs an area basis: of ecophysiological relevance or just a case of mathematical imperatives and statistical quicksand? New Phytol. 199, 311–321 (2013).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    6.De Kauwe, M. G. et al. A test of the ‘one-point method’ for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis. New Phytol. 210, 1130–1144 (2015).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    7.Ferreira Domingues, T. et al. Biome-specific effects of nitrogen and phosphorus on the photosynthetic characteristics of trees at a forest-savanna boundary in Cameroon. Oecologia 178, 659–672 (2015).PubMed Central 
    Article 

    Google Scholar 
    8.Domingues, T. F. et al. Co-limitation of photosynthetic capacity by nitrogen and phosphorus in West Africa woodlands. Plant, Cell Environ. 33, 959–980 (2010).CAS 
    Article 

    Google Scholar 
    9.Walker, A. P. et al. The relationship of leaf photosynthetic traits -VcmaxandJmax- to leaf nitrogen, leaf phosphorus, and specific leaf area: a meta-analysis and modeling study. Ecol. Evol. 4, 3218–3235 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    10.Wang, H. et al. Towards a universal model for carbon dioxide uptake by plants. Nat. Plants 3, 734–741 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    11.Smith, N. G. et al. Global photosynthetic capacity is optimized to the environment. Ecol. Lett. 22, 506–517 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    12.Prentice, I. C., Dong, N., Gleason, S. M., Maire, V. & Wright, I. J. Balancing the costs of carbon gain and water transport: testing a new theoretical framework for plant functional ecology. Ecol. Lett. 17, 82–91 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Givnish, T. J. On the Economy of Plant Form and Function: Proceedings of the Sixth Maria Moors Cabot Symposium, Vol. 6 (Cambridge University Press, 1986).14.Maire, V. et al. Global effects of soil and climate on leaf photosynthetic traits and rates. Glob. Ecol. Biogeogr. 24, 706–717 (2015).Article 

    Google Scholar 
    15.Franklin, O. et al. Organizing principles for vegetation dynamics. Nat. Plants 6, 444–453 (2020).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    16.Ali, A. A. et al. A global scale mechanistic model of photosynthetic capacity (LUNA V1.0). Geosci. Model Dev. 9, 587–606 (2016).Article 

    Google Scholar 
    17.Dewar, R. et al. New insights into the covariation of stomatal, mesophyll and hydraulic conductances from optimization models incorporating nonstomatal limitations to photosynthesis. New Phytol. 217, 571–585 (2017).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    18.Caldararu, S., Thum, T., Yu, L. & Zaehle, S. Whole-plant optimality predicts changes in leaf nitrogen under variable CO 2 and nutrient availability. New Phytol. 225, 2331–2346 (2019).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    19.Wright, I. J. et al. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    20.Wang, H. et al. The China Plant Trait Database: toward a comprehensive regional compilation of functional traits for land plants. Ecology 99, 500–500 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    21.Wang, H. et al. Photosynthetic responses to altitude: an explanation based on optimality principles. New Phytol. 213, 976–982 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.Lavergne, A. et al. Historical changes in the stomatal limitation of photosynthesis: empirical support for an optimality principle. New Phytol. 225, 2484–2497 (2019).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    23.Maire, V. et al. The coordination of leaf photosynthesis links C and N fluxes in C3 plant species. PLoS ONE 7, e38345 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    24.Fürstenau Togashi, H. et al. Thermal acclimation of leaf photosynthetic traits in an evergreen woodland, consistent with the coordination hypothesis. Biogeosciences 15, 3461–3474 (2018).Article 
    CAS 

    Google Scholar 
    25.Kumarathunge, D. P. et al. Acclimation and adaptation components of the temperature dependence of plant photosynthesis at the global scale. New Phytol. 222, 768–784 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.Wright, I. J., Reich, P. B. & Westoby, M. Strategy shifts in leaf physiology, structure and nutrient content between species of high- and low-rainfall and high- and low-nutrient habitats. Funct. Ecol. 15, 423–434 (2001).Article 

    Google Scholar 
    27.Rogers, A. The use and misuse of V c,max in earth system models. Photosynth. Res. 119, 15–29 (2013).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    28.Dong, N. et al. Leaf nitrogen from first principles: field evidence for adaptive variation with climate. Biogeosciences 14, 481–495 (2017).CAS 
    Article 

    Google Scholar 
    29.Reich, P. B. & Schoettle, A. W. Role of phosphorus and nitrogen in photosynthetic and whole plant carbon gain and nutrient use efficiency in eastern white pine. Oecologia 77, 25–33 (1988).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    30.Raaimakers, D., Boot, R. G. A., Dijkstra, P. & Pot, S. Photosynthetic rates in relation to leaf phosphorus content in pioneer versus climax tropical rainforest trees. Oecologia 102, 120–125 (1995).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    31.Goll, D. S. et al. Nutrient limitation reduces land carbon uptake in simulations with a model of combined carbon, nitrogen and phosphorus cycling. Biogeosciences 9, 3547–3569 (2012).CAS 
    Article 

    Google Scholar 
    32.Reich, P. B., Oleksyn, J. & Wright, I. J. Leaf phosphorus influences the photosynthesis–nitrogen relation: a cross-biome analysis of 314 species. Oecologia 160, 207–212 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    33.Evans, J. R. Photosynthesis and nitrogen relationships in leaves of C3 plants. Oecologia 78, 9–19 (1989).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.Reich, P. B., Walters, M. B., Ellsworth, D. S. & Uhl, C. Photosynthesis-nitrogen relations in Amazonian tree species. Oecologia 97, 62–72 (1994).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    35.Kattge, J., Knorr, W., Raddatz, T. & Wirth, C. Quantifying photosynthetic capacity and its relationship to leaf nitrogen content for global-scale terrestrial biosphere models. Global Change Biol. 15, 976–991 (2009).Article 

    Google Scholar 
    36.Evans, J. R. & Clarke, V. C. The nitrogen cost of photosynthesis. J. Exp. Bot. 70, 7–15 (2018).Article 
    CAS 

    Google Scholar 
    37.Marschner, H. in Mineral Nutrition of Higher Plants, 405–435 (Elsevier, 1995).38.Niinemets, Ü., Wright, I. J. & Evans, J. R. Leaf mesophyll diffusion conductance in 35 Australian sclerophylls covering a broad range of foliage structural and physiological variation. J. Exp. Bot. 60, 2433–2449 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    39.Malhi, Y. et al. The variation of productivity and its allocation along a tropical elevation gradient: a whole carbon budget perspective. New Phytol. 214, 1019–1032 (2016).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    40.Wang, H. et al. Acclimation of leaf respiration consistent with optimal photosynthetic capacity. Global Change Biol. 26, 2573–2583 (2020).Article 

    Google Scholar 
    41.Peng, Y., Bloomfield, K. J. & Prentice, I. C. A theory of plant function helps to explain leaf-trait and productivity responses to elevation. New Phytol. 226, 1274–1284, (2020).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    42.Gvozdevaite, A. et al. Leaf-level photosynthetic capacity dynamics in relation to soil and foliar nutrients along forest–savanna boundaries in Ghana and Brazil. Tree Physiol. 38, 1912–1925 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Terrer, C. et al. Nitrogen and phosphorus constrain the CO 2 fertilization of global plant biomass. Nat. Clim. Change 9, 684–689 (2019).CAS 
    Article 

    Google Scholar 
    44.Meir, P. et al. in Advances in Photosynthesis and Respiration, 89–105 (Springer International Publishing, 2017).45.Luo, X. & Keenan, T. F. Global evidence for the acclimation of ecosystem photosynthesis to light. Nat. Ecol. Evol. 4, 1351–1357 (2020).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    46.Stocker, B. D. et al. P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production. Geosci. Model Dev. 13, 1545–1581 (2020).Article 

    Google Scholar 
    47.Lavergne, A., Sandoval, D., Hare, V. J., Graven, H. & Prentice, I. C. Impacts of soil water stress on the acclimated stomatal limitation of photosynthesis: insights from stable carbon isotope data. Global Change Biol. 26, 7158–7172 (2020).48.Zhou, S., Duursma, R. A., Medlyn, B. E., Kelly, J. W. G. & Prentice, I. C. How should we model plant responses to drought? An analysis of stomatal and non-stomatal responses to water stress. Agric. For. Meteorol. 182-183, 204–214 (2013).Article 

    Google Scholar 
    49.Zhou, S. et al. Short-term water stress impacts on stomatal, mesophyll and biochemical limitations to photosynthesis differ consistently among tree species from contrasting climates. Tree Physiol. 34, 1035–1046 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    50.Katul, G., Manzoni, S., Palmroth, S. & Oren, R. A stomatal optimization theory to describe the effects of atmospheric CO2 on leaf photosynthesis and transpiration. Ann. Bot. 105, 431–442 (2009).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    51.Manzoni, S. et al. Optimizing stomatal conductance for maximum carbon gain under water stress: a meta-analysis across plant functional types and climates. Funct. Ecol. 25, 456–467 (2011).Article 

    Google Scholar 
    52.Medlyn, B. E. et al. Reconciling the optimal and empirical approaches to modelling stomatal conductance. Global Change Biol. 17, 2134–2144 (2011).Article 

    Google Scholar 
    53.Crous, K. Y. et al. Photosynthesis of temperate Eucalyptus globulus trees outside their native range has limited adjustment to elevated CO2 and climate warming. Global Change Biol. 19, 3790–3807 (2013).Article 

    Google Scholar 
    54.Zhou, S.-X., Medlyn, B. E. & Prentice, I. C. Long-term water stress leads to acclimation of drought sensitivity of photosynthetic capacity in xeric but not riparian Eucalyptus species. Ann. Bot. 117, 133–144 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    55.Smith, N. G. & Dukes, J. S. Short-term acclimation to warmer temperatures accelerates leaf carbon exchange processes across plant types. Global Change Biol. 23, 4840–4853 (2017).Article 

    Google Scholar 
    56.Katul, G., Leuning, R. & Oren, R. Relationship between plant hydraulic and biochemical properties derived from a steady‐state coupled water and carbon transport model. Plant, Cell Environ. 26, 339–350 (2003).CAS 
    Article 

    Google Scholar 
    57.Stocker, B. D. et al. Quantifying soil moisture impacts on light use efficiency across biomes. New Phytol. 218, 1430–1449 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    58.Kattge, J. & Knorr, W. Temperature acclimation in a biochemical model of photosynthesis: a reanalysis of data from 36 species. Plant, Cell Environ. 30, 1176–1190 (2007).CAS 
    Article 

    Google Scholar 
    59.van der Plas, F. et al. Plant traits alone are poor predictors of ecosystem properties and long-term ecosystem functioning. Nat. Ecol. Evol. 4, 1602–1611 (2020).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    60.Quesada, M. et al. Succession and management of tropical dry forests in the Americas: review and new perspectives. For. Ecol. Manag. 258, 1014–1024 (2009).Article 

    Google Scholar 
    61.Phillips, O. L. et al. Drought–mortality relationships for tropical forests. New Phytol. 187, 631–646 (2010).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    62.Laliberté, E., Lambers, H., Burgess, T. I. & Wright, S. J. Phosphorus limitation, soil-borne pathogens and the coexistence of plant species in hyperdiverse forests and shrublands. New Phytol. 206, 507–521 (2014).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    63.Conroy, J. P., Smillie, R. M., Küppers, M., Bevege, D. I. & Barlow, E. W. Chlorophyll a fluorescence and photosynthetic and growth responses of pinus radiata to phosphorus deficiency, drought stress, and high CO2. Plant Physiol. 81, 423–429 (1986).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    64.Loustau, D., Brahim, M. B., Gaudillere, J. P. & Dreyer, E. Photosynthetic responses to phosphorus nutrition in two-year-old maritime pine seedlings. Tree Physiol. 19, 707–715 (1999).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    65.Warren, C. R. & Adams, M. A. Phosphorus affects growth and partitioning of nitrogen to Rubisco in Pinus pinaster. Tree Physiol. 22, 11–19 (2002).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    66.Bloomfield, K. J., Farquhar, G. D. & Lloyd, J. Photosynthesis–nitrogen relationships in tropical forest tree species as affected by soil phosphorus availability: a controlled environment study. Funct. Plant Biol. 41, 820–832 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    67.Crous, K. Y., Ósvaldsson, A. & Ellsworth, D. S. Is phosphorus limiting in a mature Eucalyptus woodland? Phosphorus fertilisation stimulates stem growth. Plant Soil 391, 293–305 (2015).CAS 
    Article 

    Google Scholar 
    68.Sivak, M. N. & Walker, D. A. Photosynthesis in vivo can be limited by phosphate supplY. New Phytol. 102, 499–512 (1986).CAS 
    Article 

    Google Scholar 
    69.Kiirats, O., Cruz, J. A., Edwards, G. E. & Kramer, D. M. Feedback limitation of photosynthesis at high CO2 acts by modulating the activity of the chloroplast ATP synthase. Funct. Plant Biol. 36, 893–901 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    70.Ellsworth, D. S., Crous, K. Y., Lambers, H. & Cooke, J. Phosphorus recycling in photorespiration maintains high photosynthetic capacity in woody species. Plant, Cell Environ. 38, 1142–1156 (2015).CAS 
    Article 

    Google Scholar 
    71.Zhang, S. & Dang, Q. L. Effects of carbon dioxide concentration and nutrition on photosynthetic functions of white birch seedlings. Tree Physiol. 26, 1457–1467 (2006).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    72.Lambers, H. et al. Proteaceae from severely phosphorus-impoverished soils extensively replace phospholipids with galactolipids and sulfolipids during leaf development to achieve a high photosynthetic phosphorus-use-efficiency. New Phytol. 196, 1098–1108 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    73.Meir, P., Levy, P. E., Grace, J. & Jarvis, P. G. Photosynthetic parameters from two contrasting woody vegetation types in West Africa. Plant Ecol. 192, 277–287 (2007).Article 

    Google Scholar 
    74.Kull, O. Acclimation of photosynthesis in canopies: models and limitations. Oecologia 133, 267–279 (2002).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    75.Field, C. & Mooney, H. in On the Economy of Plant Form and Function: Proceedings of the Sixth Maria Moors Cabot Symposium, Evolutionary Constraints on Primary Productivity, Adaptive Patterns of Energy Capture in Plants, Harvard Forest, August 1983 (Cambridge University Press, 1986).76.Niinemets, Ü. Research review. Components of leaf dry mass per area – thickness and density – alter leaf photosynthetic capacity in reverse directions in woody plants. New Phytol. 144, 35–47 (1999).Article 

    Google Scholar 
    77.Lloyd, J. et al. Optimisation of photosynthetic carbon gain and within-canopy gradients of associated foliar traits for Amazon forest trees. Biogeosciences 7, 1833–1859 (2010).CAS 
    Article 

    Google Scholar 
    78.Anten, N. P. R. Optimal photosynthetic characteristics of individual plants in vegetation stands and implications for species coexistence. Ann. Bot. 95, 495–506 (2004).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    79.Alton, P. B. & North, P. Interpreting shallow, vertical nitrogen profiles in tree crowns: a three-dimensional, radiative-transfer simulation accounting for diffuse sunlight. Agric. For. Meteorol. 145, 110–124 (2007).Article 

    Google Scholar 
    80.Rogers, A. et al. A roadmap for improving the representation of photosynthesis in Earth system models. New Phytol. 213, 22–42 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    81.Tosens, T. & Laanisto, L. Mesophyll conductance and accurate photosynthetic carbon gain calculations. J. Exp. Bot. 69, 5315–5318 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    82.Niinemets, Ü., Díaz-Espejo, A., Flexas, J., Galmés, J. & Warren, C. R. Importance of mesophyll diffusion conductance in estimation of plant photosynthesis in the field. J. Exp. Bot. 60, 2271–2282 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    83.Farquhar, G. D., O’Leary, M. H. & Berry, J. A. On the relationship between carbon isotope discrimination and the intercellular carbon dioxide concentration in leaves. Funct. Plant Biol. 9, 121–137 (1982).CAS 
    Article 

    Google Scholar 
    84.Bernacchi, C. J., Singsaas, E. L., Pimentel, C., Portis, A. R. Jr & Long, S. P. Improved temperature response functions for models of Rubisco-limited photosynthesis. Plant, Cell Environ. 24, 253–259 (2001).CAS 
    Article 

    Google Scholar 
    85.Bernacchi, C. J., Pimentel, C. & Long, S. P. In vivo temperature response functions of parameters required to model RuBP-limited photosynthesis. Plant, Cell Environ. 26, 1419–1430 (2003).CAS 
    Article 

    Google Scholar 
    86.Scafaro, A. P. et al. Strong thermal acclimation of photosynthesis in tropical and temperate wet-forest tree species: the importance of altered Rubisco content. Global Change Biol. 23, 2783–2800 (2017).Article 

    Google Scholar 
    87.Warton, D. I., Wright, I. J., Falster, D. S. & Westoby, M. Bivariate line-fitting methods for allometry. Biol. Rev. 81, 259–291 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    88.Team, R. C. R.: a Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).89.Atkin, O. K. et al. Global variability in leaf respiration in relation to climate, plant functional types and leaf traits. New Phytol. 206, 614–636 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    90.Bahar, N. H. A. et al. Leaf-level photosynthetic capacity in lowland Amazonian and high-elevation Andean tropical moist forests of Peru. New Phytol. 214, 1002–1018 (2016).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    91.Bloomfield, K. J. et al. The validity of optimal leaf traits modelled on environmental conditions. New Phytol. 221, 1409–1423 (2018).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    92.Cernusak, L. A., Hutley, L. B., Beringer, J., Holtum, J. A. M. & Turner, B. L. Photosynthetic physiology of eucalypts along a sub-continental rainfall gradient in northern Australia. Agric. For. Meteorol. 151, 1462–1470 (2011).Article 

    Google Scholar 
    93.Xu, H. Y., et al. Predictability of leaf traits with climate and elevation: a case study in Gongga Mountain, China. Tree Physiol. https://doi.org/10.1093/treephys/tpab003 (2021).94.Walker, A. P., et al. A Global Data Set of Leaf Photosynthetic Rates, Leaf N and P, and Specific Leaf Area (Oak Ridge National Laboratory Distributed Active Archive Center, 2014). https://doi.org/10.3334/ORNLDAAC/1224.95.Kattge, J. et al. TRY–a global database of plant traits. Global Change Biol. 17, 2905–2935 (2011).Article 

    Google Scholar 
    96.Collatz, G. J., Ribas-Carbo, M. & Berry, J. A. Coupled photosynthesis-stomatal conductance model for leaves of C4 plants. Funct. Plant Biol. 19, 519 (1992).Article 

    Google Scholar 
    97.Rogers, A., Serbin, S. P., Ely, K. S., Sloan, V. L. & Wullschleger, S. D. Terrestrial biosphere models underestimate photosynthetic capacity and CO2 assimilation in the Arctic. New Phytol. 216, 1090–1103 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    98.Burnett, A. C., Davidson, K. J., Serbin, S. P. & Rogers, A. The “one‐point method” for estimating maximum carboxylation capacity of photosynthesis: a cautionary tale. Plant, Cell Environ. 42, 2472–2481 (2019).CAS 
    Article 

    Google Scholar 
    99.Harris, I., Jones, P. D., Osborn, T. J. & Lister, D. H. Updated high-resolution grids of monthly climatic observations–the CRU TS3.10 Dataset. Int. J. Climatol. 34, 623–642 (2013).Article 

    Google Scholar 
    100.Jones, H. G. Plants and Microclimate (Cambridge University Press, 2009).101.Weedon, G. P. et al. The WFDEI meteorological forcing data set: WATCH forcing data methodology applied to ERA-interim reanalysis data. Water Resour. Res. 50, 7505–7514 (2014).Article 

    Google Scholar 
    102.Davis, T. W. et al. Simple process-led algorithms for simulating habitats (SPLASH v.1.0): robust indices of radiation, evapotranspiration and plant-available moisture. Geosci. Model Dev. 10, 689–708 (2017).Article 

    Google Scholar 
    103.Berberan-Santos, M. N., Bodunov, E. N. & Pogliani, L. On the barometric formula. Am. J. Phys. 65, 404–412 (1997).Article 

    Google Scholar 
    104.Peng, Y., et al. Dataset of Global Climate and Nutrient Controls of Photosynthetic Capacity (Zenodo, 2021). https://doi.org/10.5281/zenodo.4568148. More

  • in

    A theoretical analysis of tumour containment

    1.Norton, L. & Simon, R. Tumor size, sensitivity to therapy, and design of treatment schedules. Cancer Treat. Rep. 61, 1307–1317 (1977).CAS 
    PubMed 

    Google Scholar 
    2.Goldie, J. H. & Coldman, A. J. A mathematic model for relating the drug sensitivity of tumors to their spontaneous mutation rate. Cancer Treat. Rep. 63, 1727–1733 (1979).CAS 
    PubMed 

    Google Scholar 
    3.Gatenby, R. A. A change of strategy in the war on cancer. Nature 459, 508–509 (2009).CAS 
    Article 

    Google Scholar 
    4.Zhang, J., Cunningham, J. J., Brown, J. S. & Gatenby, R. A. Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer. Nat. Commun. 8, 1816 (2017).Article 

    Google Scholar 
    5.Martin, R. B., Fisher, M. E., Minchin, R. F. & Teo, K. L. Optimal control of tumor size used to maximize survival time when cells are resistant to chemotherapy. Math. Biosci. 110, 201–219 (1992).CAS 
    Article 

    Google Scholar 
    6.Gatenby, R. A., Silva, A. S., Gillies, R. J. & Frieden, B. R. Adaptive therapy. Cancer Res. 69, 4894–4903 (2009).CAS 
    Article 

    Google Scholar 
    7.Gatenby, R. & Brown, J. The evolution and ecology of resistance in cancer therapy. Cold Spring Harb. Perspect. Med. 10, a040972 (2020).CAS 
    Article 

    Google Scholar 
    8.Bourguet, D. et al. Heterogeneity of selection and the evolution of resistance. Trends Ecol. Evol. 28, 110–118 (2013).Article 

    Google Scholar 
    9.Tabashnik, B. E., Brévault, T. & Carrière, Y. Insect resistance to Bt crops: lessons from the first billion acres. Nat. Biotechnol. 31, 510–521 (2013).CAS 
    Article 

    Google Scholar 
    10.Cunningham, J. J. A call for integrated metastatic management. Nat. Ecol. Evol. 3, 996–998 (2019).Article 

    Google Scholar 
    11.Bacevic, K. Spatial competition constrains resistance to targeted cancer therapy. Nat. Commun. 8, 1995 (2017).Article 

    Google Scholar 
    12.Silva, A. S. et al. Evolutionary approaches to prolong progression-free survival in breast cancer. Cancer Res. 72, 6362–6370 (2012).CAS 
    Article 

    Google Scholar 
    13.Enriquez-Navas, P. M. et al. Exploiting evolutionary principles to prolong tumor control in preclinical models of breast cancer. Sci. Transl. Med. 8, 327ra24 (2016).Article 

    Google Scholar 
    14.Monro, H. C. & Gaffney, E. A. Modelling chemotherapy resistance in palliation and failed cure. J. Theor. Biol. 257, 292–302 (2009).CAS 
    Article 

    Google Scholar 
    15.Carrère, C. Optimization of an in vitro chemotherapy to avoid resistant tumours. J. Theor. Biol. 413, 24–33 (2017).Article 

    Google Scholar 
    16.Gallaher, J. A., Enriquez-Navas, P. M., Luddy, K. A., Gatenby, R. A. & Anderson, A. R. A. Spatial heterogeneity and evolutionary dynamics modulate time to recurrence in continuous and adaptive cancer therapies. Cancer Res. 78, 2127–2139 (2018).CAS 
    Article 

    Google Scholar 
    17.Hansen, E., Woods, R. J. & Read, A. F. How to use a chemotherapeutic agent when resistance to it threatens the patient. PLoS Biol. 15, e2001110 (2017).Article 

    Google Scholar 
    18.Cunningham, J. J., Brown, J. S., Gatenby, R. A. & Staňková, K. Optimal control to develop therapeutic strategies for metastatic castrate resistant prostate cancer. J. Theor. Biol. 459, 67–78 (2018).CAS 
    Article 

    Google Scholar 
    19.West, J., Ma, Y. & Newton, P. K. Capitalizing on competition: an evolutionary model of competitive release in metastatic castration resistant prostate cancer treatment. J. Theor. Biol. 455, 249–260 (2018).Article 

    Google Scholar 
    20.Pouchol, C., Clairambault, J., Lorz, A. & Trélat, E. Asymptotic analysis and optimal control of an integro-differential system modelling healthy and cancer cells exposed to chemotherapy. J. Math. Pures Appl. 116, 268–308 (2018).Article 

    Google Scholar 
    21.Carrère, C. & Zidani, H. Stability and reachability analysis for a controlled heterogeneous population of cells. Optim. Control Appl. Methods 41, 1678–1704 (2020).Article 

    Google Scholar 
    22.Greene, J. M., Sanchez-Tapia, C. & Sontag, E. D. Mathematical details on a cancer resistance model. Front. Bioeng. Biotechnol. 8, 501 (2020).Article 

    Google Scholar 
    23.Martin, R. B., Fisher, M. E., Minchin, R. F. & Teo, K. L. Low-intensity combination chemotherapy maximizes host survival time for tumors containing drug-resistant cells. Math. Biosci. 110, 221–252 (1992).CAS 
    Article 

    Google Scholar 
    24.Gerlee, P. The model muddle: in search of tumor growth laws. Cancer Res. 73, 2407–2411 (2013).CAS 
    Article 

    Google Scholar 
    25.Noble, R., Burri, D., Kather, J. N. & Beerenwinkel, N. Spatial structure governs the mode of tumour evolution. Preprint at bioRxiv https://doi.org/10.1101/586735 (2019).26.Hansen, E. & Read, A. F. Cancer therapy: attempt cure or manage drug resistance? Evol. Appl. 13, 1660–1672 (2020).Article 

    Google Scholar 
    27.Enriquez-Navas, P. M., Wojtkowiak, J. W. & Gatenby, R. A. Application of evolutionary principles to cancer therapy. Cancer Res. 75, 4675–4680 (2015).CAS 
    Article 

    Google Scholar 
    28.Gatenby, R. A. & Brown, J. S. Integrating evolutionary dynamics into cancer therapy. Nat. Rev. Clin. Oncol. 17, 675–686 (2020).Article 

    Google Scholar 
    29.Strobl, M. A. R. et al. Turnover modulates the need for a cost of resistance in adaptive therapy. Cancer Res. https://doi.org/10.1158/0008-5472.CAN-20-0806 (2020).Article 
    PubMed 

    Google Scholar 
    30.Bozic, I. et al. Evolutionary dynamics of cancer in response to targeted combination therapy. eLife 2, e00747 (2013).Article 

    Google Scholar 
    31.Pérez-García, V. M. et al. Universal scaling laws rule explosive growth in human cancers. Nat. Phys. 16, 1232–1237 (2020).Article 

    Google Scholar 
    32.Greene, J. M., Gevertz, J. L. & Sontag, E. S. Mathematical approach to differentiate spontaneous and induced evolution to drug resistance during cancer treatment. JCO Clin. Cancer Inform. 3, CCI.18.00087 (2019).PubMed Central 

    Google Scholar 
    33.Kuosmanen, T. et al. Drug-induced resistance evolution necessitates less aggressive treatment. Preprint at bioRxiv https://doi.org/10.1101/2020.10.07.330134 (2020).34.Fusco, D., Gralka, M., Kayser, J., Anderson, A. & Hallatschek, O. Excess of mutational jackpot events in expanding populations revealed by spatial Luria–Delbrück experiments. Nat. Commun. 7, 12760 (2016).CAS 
    Article 

    Google Scholar 
    35.Mistry, H. B. Evolutionary based adaptive dosing algorithms: beware the cost of cumulative risk. Preprint at bioRxiv https://doi.org/10.1101/2020.06.23.167056 (2020).36.Benzekry, S. et al. Classical mathematical models for description and prediction of experimental tumor growth. PLoS Comput. Biol. 10, e1003800 (2014).Article 

    Google Scholar 
    37.Vaghi, C. et al. Population modeling of tumor growth curves and the reduced Gompertz model improve prediction of the age of experimental tumors. PLoS Comput. Biol. 16, e1007178 (2020).CAS 
    Article 

    Google Scholar 
    38.Hansen, E., Karslake, J., Woods, R. J., Read, A. F. & Wood, K. B. Antibiotics can be used to contain drug-resistant bacteria by maintaining sufficiently large sensitive populations. PLoS Biol. 18, e3000713 (2020).CAS 
    Article 

    Google Scholar 
    39.Soetaert, K. E. R., Petzoldt, T. & Setzer, R. W. Solving differential equations in R : package deSolve. J. Stat. Softw. 33, 9 (2010). More

  • in

    Corrosion and transformation of solution combustion synthesized Co, Ni and CoNi nanoparticles in synthetic freshwater with and without natural organic matter

    1.Inshakova, E. & Inshakova, A. Nanomaterials and nanotechnology: prospects for technological re-equipment in the power engineering industry. IOP Conference Series: Materials Science and Engineering 709, 033020. https://doi.org/10.1088/1757-899x/709/3/033020 (2020).CAS 
    Article 

    Google Scholar 
    2.Grassian, V. H. When size reallymatters: size-dependent properties and surface chemistry of metal and metal oxide nanoparticles in gas and liquid phase environments. J. Phys. Chem. C 112, 18303–18313. https://doi.org/10.1021/jp806073t (2008).CAS 
    Article 

    Google Scholar 
    3.Jayathilaka, W. et al. Significance of nanomaterials in wearables: a review on wearable actuators and sensors. Adv. Mater. 31, e1805921. https://doi.org/10.1002/adma.201805921 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    4.Pokhrel, S. & Mädler, L. Flame made particles for sensors, catalysis and energy storage applications. Energy Fuels https://doi.org/10.1021/acs.energyfuels.0c02220 (2020).Article 
    PubMed 

    Google Scholar 
    5.Anthony, L. S., Perumal, V., Mohamed, N. M., Saheed, M. S. M. & Gopinath, S. C. B. in Nanomaterials for Healthcare, Energy and Environment Advanced Structured Materials Ch. Chapter 3, 51–69 (2019).
    Google Scholar 
    6.Sharma, N., Ojha, H., Bharadwaj, A., Pathak, D. P. & Sharma, R. K. Preparation and catalytic applications of nanomaterials: a review. RSC Adv. 5, 53381–53403. https://doi.org/10.1039/c5ra06778b (2015).CAS 
    Article 
    ADS 

    Google Scholar 
    7.Xin, Y. et al. High-entropy alloys as a platform for catalysis: progress, challenges, and opportunities. ACS Catal. 10, 11280–11306. https://doi.org/10.1021/acscatal.0c03617 (2020).CAS 
    Article 

    Google Scholar 
    8.Wu, W. Inorganic nanomaterials for printed electronics: a review. Nanoscale 9, 7342–7372. https://doi.org/10.1039/c7nr01604b (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    9.Abdalla, A. M. et al. Nanomaterials for solid oxide fuel cells: a review. Renew. Sustain. Energy Rev. 82, 353–368. https://doi.org/10.1016/j.rser.2017.09.046 (2018).CAS 
    Article 

    Google Scholar 
    10.Choudhary, N. et al. Asymmetric supercapacitor electrodes and devices. Adv. Mater. https://doi.org/10.1002/adma.201605336 (2017).Article 
    PubMed 

    Google Scholar 
    11.Yu, Z., Tetard, L., Zhai, L. & Thomas, J. Supercapacitor electrode materials: nanostructures from 0 to 3 dimensions. Energy Environ. Sci. 8, 702–730. https://doi.org/10.1039/c4ee03229b (2015).CAS 
    Article 

    Google Scholar 
    12.Das, S., Sen, B. & Debnath, N. Recent trends in nanomaterials applications in environmental monitoring and remediation. Environ. Sci. Pollut. Res. Int. 22, 18333–18344. https://doi.org/10.1007/s11356-015-5491-6 (2015).Article 
    PubMed 

    Google Scholar 
    13.Santhosh, C. et al. Role of nanomaterials in water treatment applications: a review. Chem. Eng. J. 306, 1116–1137. https://doi.org/10.1016/j.cej.2016.08.053 (2016).CAS 
    Article 

    Google Scholar 
    14.Riley, M. K. & Vermerris, W. Recent advances in nanomaterials for gene delivery-a review. Nanomater. (Basel) https://doi.org/10.3390/nano7050094 (2017).Article 

    Google Scholar 
    15.Dasari Shareena, T. P., McShan, D., Dasmahapatra, A. K. & Tchounwou, P. B. A review on graphene-based nanomaterials in biomedical applications and risks in environment and health. Nanomicro Lett. https://doi.org/10.1007/s40820-018-0206-4 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    16.Jeyaraj, M., Gurunathan, S., Qasim, M., Kang, M. H. & Kim, J. H. A comprehensive review on the synthesis, characterization, and biomedical application of platinum nanoparticles. Nanomater. (Basel) https://doi.org/10.3390/nano9121719 (2019).Article 

    Google Scholar 
    17.Abazari, S., Shamsipur, A., Bakhsheshi-Rad, H. R., Ramakrishna, S. & Berto, F. Graphene family nanomaterial reinforced magnesium-based matrix composites for biomedical application: a comprehensive review. Metals https://doi.org/10.3390/met10081002 (2020).Article 

    Google Scholar 
    18.Siddique, S. & Chow, J. C. L. Application of nanomaterials in biomedical imaging and cancer therapy. Nanomater. (Basel) https://doi.org/10.3390/nano10091700 (2020).Article 

    Google Scholar 
    19.Mayakrishnan, G., Elayappan, V., Kim, I. S. & Chung, I. M. Sea-island-like morphology of cuni bimetallic nanoparticles uniformly anchored on single layer graphene oxide as a highly efficient and noble-metal-free catalyst for cyanation of aryl halides. Sci. Rep. 10, 677. https://doi.org/10.1038/s41598-020-57483-z (2020).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    20.Sheikh-Mohseni, M. A., Hassanzadeh, V. & Habibi, B. Reduced graphene oxide supported bimetallic Ni–Co nanoparticles composite as an electrocatalyst for oxidation of methanol. Solid State Sci. https://doi.org/10.1016/j.solidstatesciences.2019.106022 (2019).Article 

    Google Scholar 
    21.Khort, A., Romanovski, V., Leybo, D. & Moskovskikh, D. CO oxidation and organic dyes degradation over graphene–Cu and graphene–CuNi catalysts obtained by solution combustion synthesis. Sci. Rep. https://doi.org/10.1038/s41598-020-72872-0 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    22.Wang, D. et al. Nickel-cobalt layered double hydroxide nanosheets with reduced graphene oxide grown on carbon cloth for symmetric supercapacitor. Appl. Surf. Sci. 483, 593–600. https://doi.org/10.1016/j.apsusc.2019.03.345 (2019).CAS 
    Article 
    ADS 

    Google Scholar 
    23.Khort, A. et al. Graphene@metal nanocomposites by solution combustion synthesis. Inorg. Chem. https://doi.org/10.1021/acs.inorgchem.0c00673 (2020).Article 
    PubMed 

    Google Scholar 
    24.Xu, L. et al. The crucial role of environmental coronas in determining the biological effects of engineered nanomaterials. Small https://doi.org/10.1002/smll.202003691 (2020).Article 
    PubMed 

    Google Scholar 
    25.Wang, X., Odnevall Wallinder, I. & Hedberg, Y. Bioaccessibility of nickel and cobalt released from occupationally relevant alloy and metal powders at simulated human exposure scenarios. Ann. Work Expo. Health https://doi.org/10.1093/annweh/wxaa042 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    26.Atapour, M., Wang, X., Färnlund, K., Odnevall Wallinder, I. & Hedberg, Y. Corrosion and metal release investigations of selective laser melted 316L stainless steel in a synthetic physiological fluid containing proteins and in diluted hydrochloric acid. Electrochim. Acta 354, 136748. https://doi.org/10.1016/j.electacta.2020.136748 (2020).CAS 
    Article 

    Google Scholar 
    27.Mei, N., Hedberg, J., Odnevall Wallinder, I. & Blomberg, E. Influence of biocorona formation on the transformation and dissolution of cobalt nanoparticles under physiological conditions. ACS Omega 4, 21778–21791. https://doi.org/10.1021/acsomega.9b02641 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    28.Ekvall, M. T., Hedberg, J., Odnevall Wallinder, I., Hansson, L. A. & Cedervall, T. Long-term effects of tungsten carbide (WC) nanoparticles in pelagic and benthic aquatic ecosystems. Nanotoxicology 12, 79–89. https://doi.org/10.1080/17435390.2017.1421274 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    29.Hedberg, J., Ekvall, M. T., Hansson, L.-A., Cedervall, T. & Odnevall Wallinder, I. Tungsten carbide nanoparticles in simulated surface water with natural organic matter: dissolution, agglomeration, sedimentation and interaction with Daphnia magna. Environ. Sci. Nano 4, 886–894. https://doi.org/10.1039/c6en00645k (2017).CAS 
    Article 

    Google Scholar 
    30.Hedberg, J., Blomberg, E. & Odnevall Wallinder, I. In the search for nanospecific effects of dissolution of metallic nanoparticles at freshwater-like conditions: a critical review. Environ. Sci. Technol. 53, 4030–4044. https://doi.org/10.1021/acs.est.8b05012 (2019).CAS 
    Article 
    PubMed 
    ADS 

    Google Scholar 
    31.Cappellini, F. et al. Mechanistic insight into reactivity and (geno)toxicity of well-characterized nanoparticles of cobalt metal and oxides. Nanotoxicology 12, 602–620. https://doi.org/10.1080/17435390.2018.1470694 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    32.Varma, A., Mukasyan, A. S., Rogachev, A. S. & Manukyan, K. V. Solution combustion synthesis of nanoscale materials. Chem Rev 116, 14493–14586. https://doi.org/10.1021/acs.chemrev.6b00279 (2016).CAS 
    Article 
    PubMed 

    Google Scholar 
    33.Khort, A., Podbolotov, K., Serrano-García, R. & Gunko, Y. One-step solution combustion synthesis of pure Ni nanopowders with enhanced coercivity: the fuel effect. J. Solid State Chem. https://doi.org/10.1016/j.jssc.2017.05.043 (2017).Article 

    Google Scholar 
    34.Podbolotov, K. B. et al. Solution combustion synthesis of copper nanopowders: the fuel effect. Combust. Sci. Technol. 189, 1878–1890. https://doi.org/10.1080/00102202.2017.1334646 (2017).CAS 
    Article 

    Google Scholar 
    35.Khort, A., Podbolotov, K., Serrano-Garcia, R. & Gun’ko, Y. One-step solution combustion synthesis of cobalt nanopowder in air atmosphere: the fuel effect. Inorg. Chem. 57, 1464–1473. https://doi.org/10.1021/acs.inorgchem.7b02848 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    36.Yermekova, Z., Roslyakov, S. I., Kovalev, D. Y., Danghyan, V. & Mukasyan, A. S. One-step synthesis of pure γ-FeNi alloy by reactive sol–gel combustion route: mechanism and properties. J. Sol-Gel Sci. Technol. https://doi.org/10.1007/s10971-020-05252-9 (2020).Article 

    Google Scholar 
    37.Khort, A. A. & Podbolotov, K. B. Preparation of BaTiO3 nanopowders by the solution combustion method. Ceram. Int. 42, 15343–15348. https://doi.org/10.1016/j.ceramint.2016.06.178 (2016).CAS 
    Article 

    Google Scholar 
    38.Xiang, H.-Z., Xie, H.-X., Mao, A., Jia, Y.-G. & Si, T.-Z. Facile preparation of single phase high-entropy oxide nanocrystalline powders by solution combustion synthesis. Int. J. Mater. Res. https://doi.org/10.3139/146.111874 (2020).Article 

    Google Scholar 
    39.Mukasyan, A. S., Rogachev, A. S. & Aruna, S. T. Combustion synthesis in nanostructured reactive systems. Adv. Powder Technol. 26, 954–976. https://doi.org/10.1016/j.apt.2015.03.013 (2015).CAS 
    Article 

    Google Scholar 
    40.Pradhan, S. et al. Influence of humic acid and dihydroxy benzoic acid on the agglomeration, adsorption, sedimentation and dissolution of copper, manganese, aluminum and silica nanoparticles—a tentative exposure scenario. PLoS ONE 13, e0192553. https://doi.org/10.1371/journal.pone.0192553 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    41.Pradhan, S., Hedberg, J., Blomberg, E., Wold, S. & Odnevall Wallinder, I. Effect of sonication on particle dispersion, administered dose and metal release of non-functionalized, non-inert metal nanoparticles. J. Nanopart. Res. 18, 285. https://doi.org/10.1007/s11051-016-3597-5 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    42.Malloy, A. & Carr, B. NanoParticle tracking analysis—the haloTM system. Part. Part. Syst. Charact. 23, 197–204. https://doi.org/10.1002/ppsc.200601031 (2006).Article 

    Google Scholar 
    43.Patil, K. C., Hegde, M. S., Rattan, T. & Aruna, S. T. Chemistry of Nanocrystalline Oxide Materials. Combustion Synthesis, Properties and Applications (World Scientific Publishing Co. Pte. Ltd., 2008).44.Sdobnyakov, N. et al. Solution combustion synthesis and Monte Carlo simulation of the formation of CuNi integrated nanoparticles. Comput. Mater. Sci. 184, 109936. https://doi.org/10.1016/j.commatsci.2020.109936 (2020).CAS 
    Article 

    Google Scholar 
    45.Niu, B. et al. Sol-gel autocombustion synthesis of nanocrystalline high-entropy alloys. Sci. Rep. 7, 3421. https://doi.org/10.1038/s41598-017-03644-6 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    46.Cheng, M. et al. Core@shell CoO@Co 3 O 4 nanocrystals assembling mesoporous microspheres for high performance asymmetric supercapacitors. Chem. Eng. J. 327, 100–108. https://doi.org/10.1016/j.cej.2017.06.042 (2017).CAS 
    Article 

    Google Scholar 
    47.Biesinger, M. C. et al. Resolving surface chemical states in XPS analysis of first row transition metals, oxides and hydroxides: Cr, Mn, Fe, Co and Ni. Appl. Surf. Sci. 257, 2717–2730. https://doi.org/10.1016/j.apsusc.2010.10.051 (2011).CAS 
    Article 
    ADS 

    Google Scholar 
    48.Dubey, P., Kaurav, N., Devan, R. S., Okram, G. S. & Kuo, Y. K. The effect of stoichiometry on the structural, thermal and electronic properties of thermally decomposed nickel oxide. RSC Adv. 8, 5882–5890. https://doi.org/10.1039/c8ra00157j (2018).CAS 
    Article 
    ADS 

    Google Scholar 
    49.Preda, I. et al. Surface contributions to the XPS spectra of nanostructured NiO deposited on HOPG. Surf. Sci. 606, 1426–1430. https://doi.org/10.1016/j.susc.2012.05.005 (2012).CAS 
    Article 
    ADS 

    Google Scholar 
    50.Lynch, I., Dawson, K. A., Lead, J. R. & Valsami-Jones, E. In Nanoscience and the Environment Vol. 7 (eds Jamie R. Lead & Eugenia Valsami-Jones) Ch. 4, 127–156 (Elsiver, 2014).51.Lefevre, G. In situ Fourier-transform infrared spectroscopy studies of inorganic ions adsorption on metal oxides and hydroxides. Adv. Colloid Interface Sci. 107, 109–123. https://doi.org/10.1016/j.cis.2003.11.002 (2004).CAS 
    Article 
    PubMed 

    Google Scholar 
    52.Hay, M. B. & Myneni, S. C. B. Structural environments of carboxyl groups in natural organic molecules from terrestrial systems. Part 1: Infrared spectroscopy. Geochim. Cosmochim. Acta 71, 3518–3532. https://doi.org/10.1016/j.gca.2007.03.038 (2007).CAS 
    Article 
    ADS 

    Google Scholar 
    53.Mudunkotuwa, I. A. & Grassian, V. H. Biological and environmental media control oxide nanoparticle surface composition: the roles of biological components (proteins and amino acids), inorganic oxyanions and humic acid. Environ. Sci. Nano 2, 429–439. https://doi.org/10.1039/c4en00215f (2015).CAS 
    Article 

    Google Scholar 
    54.Li, H. et al. The gas-phase formation of tin dioxide nanoparticles in single droplet combustion and flame spray pyrolysis. Combust. Flame 215, 389–400. https://doi.org/10.1016/j.combustflame.2020.02.004 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    55.Xu, C. et al. One-step solution combustion synthesis of CuO/Cu2O/C anode for long cycle life Li-ion batteries. Carbon 142, 51–59. https://doi.org/10.1016/j.carbon.2018.10.016 (2019).CAS 
    Article 

    Google Scholar 
    56.Trusov, G. V. et al. Spray solution combustion synthesis of metallic hollow microspheres. J. Phys. Chem. C 120, 7165–7171. https://doi.org/10.1021/acs.jpcc.6b00788 (2016).CAS 
    Article 

    Google Scholar 
    57.Hedberg, Y. S. & Odnevall Wallinder, I. Metal release from stainless steel in biological environments: a review. Biointerphases 11, 018901. https://doi.org/10.1116/1.4934628 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    58.Dale, A. L., Lowry, G. V. & Casman, E. A. Accurate and fast numerical algorithms for tracking particle size distributions during nanoparticle aggregation and dissolution. Environ. Sci. Nano 4, 89–104. https://doi.org/10.1039/c6en00330c (2017).CAS 
    Article 

    Google Scholar 
    59.He, D., Bligh, M. W. & Waite, T. D. Effects of aggregate structure on the dissolution kinetics of citrate-stabilized silver nanoparticles. Environ. Sci. Technol. 47, 9148–9156. https://doi.org/10.1021/es400391a (2013).CAS 
    Article 
    PubMed 
    ADS 

    Google Scholar 
    60.Korshin, G. V., Perry, S. A. L. & Ferguson, J. F. Influence of NOM on copper corrosion. J. Am. Water Works Assoc. 88, 36–47. https://doi.org/10.1002/j.1551-8833.1996.tb06583.x (1996).CAS 
    Article 

    Google Scholar 
    61.Sarker, P. et al. High-entropy high-hardness metal carbides discovered by entropy descriptors. Nat. Commun. 9, 4980. https://doi.org/10.1038/s41467-018-07160-7 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    62.Pei, Z., Yin, J., Hawk, J. A., Alman, D. E. & Gao, M. C. Machine-learning informed prediction of high-entropy solid solution formation: beyond the Hume-Rothery rules. npj Comput. Mater. https://doi.org/10.1038/s41524-020-0308-7 (2020).Article 

    Google Scholar 
    63.Balasubramanian, K., Khare, S. V. & Gall, D. Valence electron concentration as an indicator for mechanical properties in rocksalt structure nitrides, carbides and carbonitrides. Acta Mater. 152, 175–185. https://doi.org/10.1016/j.actamat.2018.04.033 (2018).CAS 
    Article 
    ADS 

    Google Scholar 
    64.Moskovskikh, D. et al. Extremely hard and tough high entropy nitride ceramics. Sci. Rep. 10, 19874. https://doi.org/10.1038/s41598-020-76945-y (2020).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    65.Sangiovanni, D. G., Hultman, L. & Chirita, V. Supertoughening in B1 transition metal nitride alloys by increased valence electron concentration. Acta Mater. 59, 2121–2134. https://doi.org/10.1016/j.actamat.2010.12.013 (2011).CAS 
    Article 
    ADS 

    Google Scholar  More