Mountain glaciation greatly enhances oxidative weathering rates of organic carbon in rocks and associated carbon dioxide release.

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Formation and crystallisation of the Lunar Magma Ocean (LMO) was one of the most incisive events during the early evolution of the Moon. Lunar Magma Ocean solidification concluded with the coeval formation of K-, REE-and P-rich components (KREEP) and an ilmenite-bearing cumulate (IBC) layer. Gravitational overturn of the lunar mantle generated eruptions of basaltic rocks with variable Ti contents, of which their δ 49 Ti variations may now reflect variable mixtures of ambient lunar mantle and the IBC. To better understand the processes generating the spectrum of lunar low-Ti and high-Ti basalts and the role of Ti-rich phases such as ilmenite, we determined the mass dependent Ti isotope composition of four KREEP-rich samples, 12 low-Ti, and eight high-Ti mare basalts by using a 47 Ti-49 Ti double spike. Our data reveal significant variations in δ 49 Ti for KREEPrich samples (+0.117 to +0.296 ‰) and intra-group variations in the mare basalts (-0.030 to +0.055 ‰ for low-Ti and +0.009 to +0.115 ‰ for high-Ti basalts). We modelled the δ 49 Ti of KREEP using previously published HFSE data as well as the δ 49 Ti evolution during fractional crystallisation of the LMO. Both approaches yield δ 49 Ti KREEP similar to measured values and are in excellent agreement with previous studies. The involvement of ilmenite in the petrogenesis of the lunar mare basalts is further evaluated by combining our results with element ratios of HFSE, U and Th, revealing that partial melting in an overturned lunar mantle and fractional crystallisation of ilmenite must be the main processes accounting for mass dependent Ti isotope variations in lunar basalts. Based on our results we can also exclude formation of high-Ti basalts by simple assimilation of ilmenite by ascending melts from the depleted lunar mantle. Rather, our data are in accord with melting of these basalts from a hybrid mantle source formed in the aftermath of gravitational lunar mantle overturn, which is in good agreement with previous Fe isotope data.

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Understanding the effect of horseshoe-surface combinations on hoof kinematics at gallop is relevant for optimising performance and minimising injury in racehorse-jockey dyads. This intervention study assessed hoof breakover duration in Thoroughbred ex-racehorses from the British Racing School galloping on turf and artificial tracks in four shoeing conditions: barefoot, aluminium-rubber composite (GluShu), aluminium and steel. Shoe-surface combinations were tested in a randomized order and horse-rider pairings (n=14) remained constant. High-speed video cameras (Sony DSC-RX100M5) filmed the hoof-ground interactions at 1000 frames per second. The time taken for a hoof marker wand fixed to the lateral hoof wall to rotate through an angle of 90 degrees during 384 breakover events was quantified using Tracker software. Data were collected for leading and non-leading front and hind limbs, at gallop speeds ranging from 23–56 km h-1. Linear mixed-models assessed whether speed, surface, shoeing condition or any interaction between these parameters (fixed factors) significantly affected breakover duration. Day and horse-rider pair were included as random factors and speed was included as a covariate. The significance threshold was set at p<0.05. For all limbs, breakover times decreased as gallop speed increased (p<0.0005), although a greater relative reduction in breakover duration for hindlimbs was apparent beyond approximately 45 km h-1. Breakover duration was longer on turf compared to the artificial surface (p≤0.04). In the non-leading hindlimb only, breakover duration was affected by shoeing condition (p=0.025) and an interaction between shoeing condition and speed (p=0.023). Future work seeks to relate these results to hoof accelerometer data.

Understanding the effect of horseshoe–surface combinations on hoof kinematics at gallop is relevant for optimising performance and minimising injury in racehorse–jockey dyads. This intervention study assessed hoof breakover duration in Thoroughbred ex-racehorses from the British Racing School galloping on turf and artificial tracks in four shoeing conditions: aluminium, barefoot, aluminium–rubber composite (GluShu) and steel. Shoe–surface combinations were tested in a randomized order and horse–jockey pairings (n = 14) remained constant. High-speed video cameras (Sony DSC-RX100M5) filmed the hoof-ground interactions at 1000 frames per second. The time taken for a hoof marker wand fixed to the lateral hoof wall to rotate through an angle of 90 degrees during 384 breakover events was quantified using Tracker software. Data were collected for leading and non-leading forelimbs and hindlimbs, at gallop speeds ranging from 23–56 km h−1. Linear mixed-models assessed whether speed, surface, shoeing condition and any interaction between these parameters (fixed factors) significantly affected breakover duration. Day and horse–jockey pair were included as random factors and speed was included as a covariate. The significance threshold was set at p < 0.05. For all limbs, breakover times decreased as gallop speed increased (p < 0.0005), although a greater relative reduction in breakover duration for hindlimbs was apparent beyond approximately 45 km h−1. Breakover duration was longer on turf compared to the artificial surface (p ≤ 0.04). In the non-leading hindlimb only, breakover duration was affected by shoeing condition (p = 0.025) and an interaction between shoeing condition and speed (p = 0.023). This work demonstrates that speed, ground surface and shoeing condition are important factors influencing the galloping gait of the Thoroughbred racehorse.

Horseshoes influence how horses’ hooves interact with different ground surfaces, during the impact, loading and push-off phases of a stride cycle. Consequently, they impact on the biomechanics of horses’ proximal limb segments and upper body. By implication, different shoe and surface combinations could drive changes in the magnitude and stability of movement patterns in horse-jockey dyads. This study aimed to quantify centre of mass (COM) displacements in horse-jockey dyads galloping on turf and artificial tracks in four shoeing conditions: 1) aluminium; 2) barefoot; 3) GluShu; and 4) steel. Thirteen retired racehorses and two jockeys at the British Racing School were recruited for this intervention study. Tri-axial acceleration data were collected close to the COM for the horse (girth) and jockey (kidney-belt), using iPhones (Apple Inc.) equipped with an iOS app (SensorLog, sample rate = 50 Hz). Shoe-surface combinations were tested in a randomized order and horse-jockey pairings remained constant. Tri-axial acceleration data from gallop runs were filtered using bandpass Butterworth filters with cut-off frequencies of 15 Hz and 1 Hz, then integrated for displacement using Matlab. Peak displacement was assessed in both directions (positive ‘maxima’, negative ‘minima’) along the cranio-caudal (CC, positive = forwards), medio-lateral (ML, positive = right) and dorso-ventral (DV, positive = up) axes for all strides with frequency ≥2 Hz (mean = 2.06 Hz). Linear mixed-models determined whether surfaces, shoes or shoe-surface interactions (fixed factors) significantly affected the displacement patterns observed, with day, run and horse-jockey pairs included as random factors; significance was set at p<0.05. Data indicated that surface-type significantly affected peak COM displacements in all directions for the horse (p<0.0005) and for all directions (p≤0.008) but forwards in the jockey. The largest differences were observed in the DV-axis, with an additional 5.7 mm and 2.5 mm of downwards displacement for the horse and jockey, respectively, on the artificial surface. Shoeing condition significantly affected all displacement parameters except ML-axis minima for the horse (p≤0.007), and all displacement parameters for the jockey (p<0.0005). Absolute differences were again largest vertically, with notable similarities amongst displacements from barefoot and aluminium trials compared to GluShu and steel. Shoe-surface interactions affected all but CC-axis minima for the jockey (p≤0.002), but only the ML-axis minima and maxima and DV-axis maxima for the horse (p≤0.008). The results support the idea that hoof-surface interface interventions can significantly affect horse and jockey upper-body displacements. Greater sink of hooves on impact, combined with increased push-off during the propulsive phase, could explain the higher vertical displacements on the artificial track. Variations in distal limb mass associated with shoe-type may drive compensatory COM displacements to minimize the energetic cost of movement. The artificial surface and steel shoes provoked the least CC-axis movement of the jockey, so may promote greatest stability. However, differences between horse and jockey mean displacements indicated DV-axis and CC-axis offsets with compensatory increases and decreases, suggesting the dyad might operate within displacement limits to maintain stability. Further work is needed to relate COM displacements to hoof kinematics and to determine whether there is an optimum configuration of COM displacement to optimise performance and minimise injury.

Molybdenite-bearing porphyry deposits are the predominant supplier of molybdenum to industrialized society and one of the main hosts of Mo in the upper continental crust. The Mo isotope compositions (δ98/95Mo, normalized to NIST3134 equals 0‰) of molybdenite show considerable variation (–1.62 to +2.27‰), but the factors controlling this variability remain poorly constrained. This information is critical for underpinning genetic models of porphyry deposits, understanding elemental cycling, and utilizing the δ98/95Mo of marine sediments as a paleoredox proxy. Using the well-characterized Qulong porphyry Cu-Mo deposit (Tibet) as an example, here we discuss how rapid cooling, facilitated by mixing hot magmatic fluid with cold meteoric water, can be a controlling factor on efficient mineralization, and then tackle how fluid evolution regulates molybdenum isotope fractionation. Molybdenites, which preferentially partition isotopically light Mo (Rayleigh fractionation), precipitated from a single fluid will develop a heavier δ98/95Mo composition over time, and this also creates heterogeneous δ98/95Mo between molybdenite grains. Whereas a fluid undergoing multiple episodes of intensive boiling will gradually lose its isotopically heavy Mo to the vapor phase, molybdenites crystallizing successively from the residual liquid will then have lighter δ98/95Mo over time. However, when mineralization efficiency becomes too low, a negligible variation in δ98/95Mo of molybdenite is observed. Given that the mineralization efficiency (i.e., the amount of Mo crystallized as molybdenite from the fluid) rarely reaches 100% and molybdenite favors isotopically light Mo, the presence of a residual fluid with isotopically heavy Mo is inevitable. This residual fluid may then become trapped in alteration halos; hence, δ98/95Mo has the potential to aid in locating the mineralization center (e.g., lighter δ98/95Mo toward the orebody). The residual fluid may also feed surface hydrological systems and eventually impact Mo cycling. Our study highlights that understanding the controls of isotope fractionation is critical to bridge the gap between ore formation and elemental cycling, and that other transition metals (e.g., Cu, Fe, and Zn) may follow similar trajectories.