Different climate sensitivity for radial growth, but uniform for tree-ring stable isotopes along an aridity gradient in Polylepis tarapacana, the world's highest elevation tree species.

Tree growth is generally considered to be temperature limited at upper elevation treelines, yet climate factors controlling tree growth at semiarid treelines are poorly understood. We explored the influence of climate on stem growth and stable isotopes for Polylepis tarapacana Philipi, the world's highest elevation tree species, which is found only in the South American Altiplano. We developed tree-ring width index (RWI), oxygen (δ18O) and carbon (δ13C) chronologies for the last 60 years at four P. tarapacana stands located above 4400 m in elevation, along a 500 km latitude aridity gradient. Total annual precipitation decreased from 300 to 200 mm from the northern to the southern sites. We used RWI as a proxy of wood formation (carbon sink) and isotopic tree-ring signatures as proxies of leaf-level gas exchange processes (carbon source). We found distinct climatic conditions regulating carbon sink processes along the gradient. Current growing-season temperature regulated RWI at northern-wetter sites, while prior growing-season precipitation determined RWI at arid southern sites. This suggests that the relative importance of temperature to precipitation in regulating tree growth is driven by site water availability. By contrast, warm and dry growing seasons resulted in enriched tree-ring δ13C and δ18O at all study sites, suggesting that similar climate conditions control carbon-source processes along the gradient. Site-level δ13C and δ18O chronologies were significantly and positively related at all sites, with the strongest relationships among the southern drier stands. This indicates an overall regulation of intercellular carbon dioxide via stomatal conductance for the entire P. tarapacana network, with greater stomatal control when aridity increases. This manuscript also highlights a coupling (decoupling) between physiological processes at leaf level and wood formation as a function of similarities (differences) in their climatic sensitivity. This study contributes to a better understanding and prediction of the response of high-elevation Polylepis woodlands to rapid climate changes and projected drying in the Altiplano.

Six centuries of Upper Indus Basin streamflow variability and its climatic drivers.

Our understanding of the full range of natural variability in streamflow, including how modern flow compares to the past, is poorly understood for the Upper Indus Basin (UIB) because of short instrumental gauge records. To help address this challenge, we use Hierarchical Bayesian Regression (HBR) with partial pooling to develop six centuries long (1394-2008 C.E.) streamflow reconstructions at three UIB gauges (Doyian, Gilgit, and Kachora), concurrently demonstrating that HBR can be used to reconstruct short records with interspersed missing data. At one gauge (Partab Bridge), with a longer instrumental record (47 years), we develop reconstructions using both Bayesian Regression (BR) and the more conventionally used Principal Components Regression (PCR). The reconstructions produced by PCR and BR at Partab Bridge are nearly identical and yield comparable reconstruction skill statistics, highlighting that the resulting tree-ring reconstruction of streamflow is not dependent on the choice of statistical method. Reconstructions at all four reconstructions indicate flow levels in the 1990s were higher than mean flow for the past six centuries. While streamflow appears most sensitive to accumulated winter (January-March) precipitation and summer (MJJAS) temperature, with warm summers contributing to high flow through increased melt of snow and glaciers, shifts in winter precipitation and summer temperatures cannot explain the anomalously high flow during the 1990s. Regardless, the sensitivity of streamflow to summer temperatures suggests that projected warming may increase streamflow in coming decades, though long-term water risk will additionally depend on changes in snowfall and glacial mass balance.