River basin salinization as a form of aridity.

Soil-salinization affects, to a different extent, more than one-third of terrestrial river basins (estimate based on the Food and Agriculture Organization Harmonized World Soil Database, 2012). Among these, many are endorheic and ephemeral systems already encompassing different degrees of aridity, land degradation, and vulnerability to climate change. The primary effect of salinization is to limit plant water uptake and evapotranspiration, thereby reducing available soil moisture and impairing soil fertility. In this, salinization resembles aridity and-similarly to aridity-may impose significant controls on hydrological partitioning and the strength of land-vegetation-atmosphere interactions at the catchment scale. However, the long-term impacts of salinization on the terrestrial water balance are still largely unquantified. Here, we introduce a modified Budyko's framework explicitly accounting for catchment-scale salinization and species-specific plant salt tolerance. The proposed framework is used to interpret the water-budget data of 237 Australian catchments-29% of which are already severely salt-affected-from the Australian Water Availability Project (AWAP). Our results provide theoretical and experimental evidence that salinization does influence the hydrological partitioning of salt-affected watersheds, imposing significant constraints on water availability and enhancing aridity. The same approach can be applied to estimate salinization level and vegetation salt tolerance at the basin scale, which would be difficult to assess through classical observational techniques. We also demonstrate that plant salt tolerance has a preeminent role in regulating the feedback of vegetation on the soil water budget of salt-affected basins.

Xylem-phloem hydraulic coupling explains multiple osmoregulatory responses to salt stress.

Salinity is known to affect plant productivity by limiting leaf-level carbon exchange, root water uptake, and carbohydrates transport in the phloem. However, the mechanisms through which plants respond to salt exposure by adjusting leaf gas exchange and xylem-phloem flow are still mostly unexplored. A physically based model coupling xylem, leaf, and phloem flows is here developed to explain different osmoregulation patterns across species. Hydraulic coupling is controlled by leaf water potential, ψl , and determined under four different maximization hypotheses: water uptake (1), carbon assimilation (2), sucrose transport (3), or (4) profit function - i.e. carbon gain minus hydraulic risk. All four hypotheses assume that finite transpiration occurs, providing a further constraint on ψl . With increasing salinity, the model captures different transpiration patterns observed in halophytes (nonmonotonic) and glycophytes (monotonically decreasing) by reproducing the species-specific strength of xylem-leaf-phloem coupling. Salt tolerance thus emerges as plant's capability of differentiating between salt- and drought-induced hydraulic risk, and to regulate internal flows and osmolytes accordingly. Results are shown to be consistent across optimization schemes (1-3) for both halophytes and glycophytes. In halophytes, however, profit-maximization (4) predicts systematically higher ψl than (1-3), pointing to the need of an updated definition of hydraulic cost for halophytes under saline conditions.

Rapid quantitative chemical mapping of surfaces with sub-2 nm resolution.

We present a theory that exploits four observables in bimodal atomic force microscopy to produce maps of the Hamaker constant H. The quantitative H maps may be employed by the broader community to directly interpret the high resolution of standard bimodal AFM images as chemical maps while simultaneously quantifying chemistry in the non-contact regime. We further provide a simple methodology to optimize a range of operational parameters for which H is in the closest agreement with the Lifshitz theory in order to (1) simplify data acquisition and (2) generalize the methodology to any set of cantilever-sample systems.