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The Pliocene epoch (5.3–2.6 Ma) represents the most recent geological interval in which global temperatures were several degrees warmer than today and is therefore considered our best analog for a future anthropogenic greenhouse world. However, our understanding of Pliocene climates is limited by poor age control on existing terrestrial climate archives, especially in the Southern Hemisphere, and by persistent disagreement between paleo-data and models concerning the magnitude of regional warming and/or wetting that occurred in response to increased greenhouse forcing. To address these problems, here we document the evolution of Southern Hemisphere hydroclimate from the latest Miocene to the middle Pliocene using radiometrically-dated fossil pollen records preserved in speleothems from semiarid southern Australia. These data reveal an abrupt onset of warm and wet climates early within the Pliocene, driving complete biome turnover. Pliocene warmth thus clearly represents a discrete interval which reversed a long-term trend of late Neogene cooling and aridification, rather than being simply the most recent period of greater-than-modern warmth within a continuously cooling trajectory. These findings demonstrate the importance of high-resolution chronologies to accompany paleoclimate data and also highlight the question of what initiated the sustained interval of Pliocene warmth.

The stable isotopic composition of precipitation (δ2HP, δ18OP; “water isotopes”) is a powerful tool for tracking water through the atmosphere, as well as fingerprinting land-surface water masses and identifying water cycle biases in isotope-enabled climate models. Water isotopes also underpin our understanding of multi-decadal to multi-centennial water cycle variability via their retrieval from palaeoclimate archives. Water isotopes thereby increase our understanding of past and present – and hence future – water cycle variability. Understanding the drivers of spatial and temporal water isotope variability is a critical first step in applying these tracers for a better understanding of the water cycle. However, water isotope observations are sparse in both space and time. Here we develop and apply a machine learning (random forest) approach to predict spatially continuous monthly δ2HP and δ18OP across the Australian continent at 0.25° resolution from 1962–2023. We train the random forest models on monthly δ2HP (n=5199) and δ18OP (n=5217) observations from 60 sites across Australia. We also predict the deuterium excess of precipitation (dxsP, defined as δ2HP-8×δ18OP). Out-of-sample δ2HP and δ18OP prediction skill is high both geographically and temporally. Skill is slightly lower for the secondary parameter dxsP, likely reflecting the larger reliance of spatio-temporal dxsP variability on moisture source conditions. The random forest models accurately capture both the seasonal cycle of precipitation isotopic variability and long-term annual-mean precipitation isotopic variability across the continent, and outperform estimates from an isotope-enabled atmosphere general circulation model over an equivalent time period. We show that spatio-temporal variability in precipitation amount, precipitation intensity, and surface temperature are particularly important for monthly δ2HP and δ18OP variations across the continent, with local surface pressure also important for dxsP. Drivers of site-level δ2HP, δ18OP, and dxsP are more varied. Overall, the new random forest modelled dataset reveals clear spatial and temporal variability in δ2HP, δ18OP, and dxsP across the Australian continent over the past decades – providing a robust foundation for hydrology, ecology, and palaeoclimate research, as well as an accessible framework for predicting water isotope values in other locations.

Background Circadian (daily) timekeeping is essential to the survival of many organisms. An integral part of all circadian timekeeping systems is negative feedback between an activator and repressor. However, the role of this feedback varies widely between lower and higher organisms. Results Here, we study repression mechanisms in the cyanobacterial and eukaryotic clocks through mathematical modeling and systems analysis. We find a common mathematical model that describes the mechanism by which organisms generate rhythms; however, transcription’s role in this has diverged. In cyanobacteria, protein sequestration and phosphorylation generate and regulate rhythms while transcription regulation keeps proteins in proper stoichiometric balance. Based on recent experimental work, we propose a repressor phospholock mechanism that models the negative feedback through transcription in clocks of higher organisms. Interestingly, this model, when coupled with activator phosphorylation, allows for oscillations over a wide range of protein stoichiometries, thereby reconciling the negative feedback mechanism in Neurospora with that in mammals and cyanobacteria. Conclusions Taken together, these results paint a picture of how circadian timekeeping may have evolved.

Radiometric dating of glacial terminations over the past 640,000 years suggests pacing by Earth’s climatic precession, with each glacial-interglacial period spanning four or five cycles of ~20,000 years. However, the lack of firm age estimates for older Pleistocene terminations confounds attempts to test the persistence of precession forcing. We combine an Italian speleothem record anchored by a uranium-lead chronology with North Atlantic ocean data to show that the first two deglaciations of the so-called 100,000-year world are separated by two obliquity cycles, with each termination starting at the same high phase of obliquity, but at opposing phases of precession. An assessment of 11 radiometrically dated terminations spanning the past million years suggests that obliquity exerted a persistent influence on not only their initiation but also their duration.

The increasing popularity of online commerce provides a new opportunity to investigate and quantify the dynamics of pet trade. Understanding these dynamics, including relationships between species characteristics and a species’ relative abundance in trade, can assist in informing trade regulation for conservation and biosecurity. We identified the leading correlates behind the abundance in the Australian pet trade of parrot (Psittaciformes) and passerine (Passeriformes) species. We examined 14,000 online sales of parrots and passerines collected from a popular online Australian marketplace in 2019 (representing 235 species) using an automated data collection method. We identified the characteristics that correlated with online species abundance; including (i) breeding and handling requirements; (ii) trade and availability; and (iii) appearance and behaviour. We found 55% of parrot species and 64% of passerine species traded online were non-native to Australia; of these, 81% and 85% respectively have an extreme risk of establishing invasive populations. Species abundance of both orders was correlated with cheaper prices, which is also associated with a higher invasion risk. Trade in parrots was correlated with attractive birdsongs, being easier to care for, and a preference for native Australian species. Passerine abundance was correlated with attractive plumage colour and, to a lesser extent, the availability of colour mutations and smaller geographic range sizes. These results, combined with an understanding of consumer behaviour and international trends, may help predict which species will become abundant in domestic trade in the future, and identify current and future invasion risks to assist in environmental biosecurity efforts.

Understanding and modelling the passage of groundwater is important for a wide range of environmental and earth science disciplines. The science of groundwater modelling is mature, and advanced modelling algorithms are routinely implemented, for example via the widely used MODFLOW software. However, for the non-specialist scientist or student, the fundamentals of such software can be difficult to comprehend, whilst the algorithms are arguably too complex to be easily applied for many applications which require integration of a groundwater model with climate, surface-water, soil or ecological data. In this context, a spreadsheet-based groundwater model (A2016), capable of solving transient groundwater behaviour in multiple spatial dimensions, was developed. Inter-comparison tests investigating nine transient groundwater scenarios were performed between MODFLOW, A2016 and the Time-dependent Groundwater Modeling using Spreadsheet Simulation (TGMSS) model. Results demonstrated that A2016 is directly comparable to MODFLOW, with identical hydraulic heads in all model experiments. TGMSS was not able to accurately simulate hydraulic heads for any of the model experiments. A groundwater–lake interaction scenario was identified for which MODFLOW will produce unrealistic results, due to the way conductance beneath lakes is determined. Applying a specified saturated thickness approximation for the region beneath the lake resulted in improved lake–groundwater interactions. A2016 is potentially useful for educational purposes and as a tool for groundwater experiments by non-specialists, as it is modular in nature and incorporates MODFLOW terminology and techniques.

Understanding the modern day relationship between climate and the oxygen isotopic composition of precipitation (δ 18 O P ) is crucial for obtaining rigorous palaeoclimate reconstructions from a variety of archives. To date, the majority of empirical studies into the meteorological controls over δ 18 O P rely upon daily, event scale, or monthly time series from individual locations, resulting in uncertainties concerning the representativeness of statistical models and the mechanisms behind those relationships. Here, we take an alternative approach by analysing daily patterns in δ 18 O P from multiple stations across the British Isles ( n  = 10–70 stations). We use these data to examine the spatial and seasonal heterogeneity of regression statistics between δ 18 O P and common predictors (temperature, precipitation amount and the North Atlantic Oscillation index; NAO). Temperature and NAO are poor predictors of daily δ 18 O P in the British Isles, exhibiting weak and/or inconsistent effects both spatially and between seasons. By contrast δ 18 O P and rainfall amount consistently correlate at most locations, and for all months analysed, with spatial and temporal variability in the regression coefficients. The maps also allow comparison with daily synoptic weather types, and suggest characteristic δ 18 O P patterns, particularly associated with Cylonic Lamb Weather Types. Mapping daily δ 18 O P across the British Isles therefore provides a more coherent picture of the patterns in δ 18 O P , which will ultimately lead to a better understanding of the climatic controls. These observations are another step forward towards developing a more detailed, mechanistic framework for interpreting stable isotopes in rainfall as a palaeoclimate and hydrological tracer.

Circadian clocks control the timing of many physiological events in the 24-h day. When individuals undergo an abrupt external shift (e.g., change in work schedule or travel across multiple time zones), circadian clocks become misaligned with the new time and may take several days to adjust. Chronic circadian misalignment, e.g., as a result of shift work, has been shown to lead to several physical and mental health problems. Despite the serious health implications of circadian misalignment, relatively little is known about how genetic variation affects an individual’s ability to entrain to abrupt external changes. Accordingly, we used the one-hour advance from the onset of daylight saving time (DST) as a natural experiment to comprehensively study how individual heterogeneity affects the shift of sleep/wake cycles in response to an abrupt external time change. We found that individuals genetically predisposed to a morning tendency adjusted to the advance in a few days, while genetically predisposed evening-inclined individuals had not shifted. Observing differential effects by genetic disposition after a one-hour advance underscores the importance of heterogeneity in adaptation to external schedule shifts. These genetic differences may affect how individuals adjust to jet lag or shift work as well.