A document by Fabian Quichimbo. Click on the document to view its contents.

Cryogenic vacuum distillation (CVD) is a widely used technique for extracting plant water from stems for isotopic analysis, but concerns about potential isotopic biases have emerged. Here, we leverage the Cavitron centrifugation technique to extract xylem water and compare its isotopic signature to that of CVD-extracted stem water as well as source water. Conducted under field conditions in tropical northern Australia, our study spans seven tree species naturally experiencing a range of water stress levels. Our findings reveal a significant deuterium bias in CVD-extracted bulk stem water when compared to xylem water (median bias \($-14.9\textperthousand$\)), whereas xylem water closely aligned with source water (median offset \($-1.9\textperthousand$\)). We find substantial variations in deuterium bias among the seven tree species (bias ranging from -19.3 to \($-9.1\textperthousand$\)), but intriguingly, CVD-induced biases were unrelated to environmental factors such as relative stem water content and pre-dawn leaf water potential. These results imply that inter-specific differences may be driven by anatomical traits rather than tree hydraulic functioning. Additionally, our data highlight the potential to use a site-specific deuterium offset, based on the isotopic signature of local source water, for correcting CVD-induced biases.

The state and dynamics of river chemistry are influenced by both anthropogenic and natural catchment characteristics. However, understanding key controls on catchment mean concentrations and export patterns comprehensively across a wide range of climate zones is still lacking, as most of this research is focused on temperate regions. In this study, we investigate the catchment controls on mean concentrations and export patterns (concentration–discharge relationship, C–Q slope) of river chemistry, using a long-term data set of up to 507 sites spanning five climate zones (i.e., arid, Mediterranean, temperate, subtropical, tropical) across the Australian continent. We use Bayesian model averaging (BMA) and hierarchical modelling (BHM) approaches to predict the mean concentrations and export patterns and compare the relative importance of 26 catchment characteristics (e.g., topography, climate, land use, land cover, soil properties and hydrology). Our results demonstrate that mean concentrations result from the interaction of catchment intrinsic and anthropogenic factors (i.e., land use, topography and soil), while export patterns are more influenced by catchment intrinsic characteristics only (i.e., topography). We also found that incorporating the effects of climate zones in a BHM framework improved the predictability of both mean concentrations and C–Q slopes, suggesting the importance of climatic controls on hydrological and biogeochemical processes. Our study provides insights into the contrasting effects of catchment controls across different climate zones. Investigating those controls can inform sustainable water quality management strategies that consider the potential changes in river chemistry state and export behaviour.

We need to understand spatial variability in the mean concentrations and dynamics of riverine water quality for effective water quality management. Using river chemistry data for up to 578 locations across the Australian continent, we assessed the impact of climate zones on (i) interannual mean concentration and (ii) river chemistry dynamics as represented by constituent export regimes (ratio of the coefficients of variation of concentration and discharge) and export patterns (slope of the concentration-discharge relationship). We found that interannual mean concentrations vary significantly by climate zones. However, export regimes and patterns are generally consistent across climate zones. This suggests that intrinsic properties of individual constituents rather than catchment properties determine export regimes and patterns. The spatially consistent river chemistry dynamics highlights the potential to predict riverine water quality across the Australian continent, which will support national riverine water quality management.