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In 2010-2018 Northern Patagonia featured the longest severe drought of the last millennium. This extreme dry spell triggered widespread growth decline and forest dieback. Nonetheless, the roles played by the two major mechanisms driving dieback, hydraulic failure and carbon starvation, are still not clear and understudied in this seasonally dry region. Here, for the 1800-2017 period, we apply a retrospective analysis of radial growth, wood anatomical traits (lumen area, cell-wall thickness) and δ13 C and δ18 O stable isotopes to assess dieback causes of the iconic conifer Araucaria araucana. We selected three stands where declining (defoliated) and non-declining (not defoliated) trees coexisted along a precipitation gradient from the warm-dry Coastal Range to the cool-wet Andes. At all sites declining trees showed lower radial growth and lower theoretical hydraulic conductivity, suggesting a long-lasting process of hydraulic deterioration in their water transport system compared to non-declining, coexisting trees. Wood anatomical traits evidenced that this divergence between declining and non-declining trees started at least seven decades before canopy dieback. In the drier stands, declining trees showed higher water-use efficiency throughout the whole period, which we attributed to early stomatal closure, suggesting a greater carbon starvation risk consistent with thinner cell walls. In the wettest stand, we found the opposite pattern. Here, a reduction in water-use efficiency coupled with thicker cell walls suggested increased carbon assimilation rates and exposure to drought-induced hydraulic failure. The δ18 O values indicated different strategies of gas-exchange between sites which are likely a consequence of microsite conditions and water sources. Multi-proxy, retrospective quantifications of xylem anatomical traits and tree-ring isotopes provide a robust tool to identify and forecast which stands or trees will show dieback or, on the contrary, which will likely withstand and be more resilient to future hotter droughts.

The recent developments in artificial intelligence have the potential to facilitate new research methods in ecology. Especially Deep Convolutional Neural Networks (DCNNs) have been shown to outperform other approaches in automatic image analyses. Here we apply a DCNN to facilitate quantitative wood anatomical (QWA) analyses, where the main challenges reside in the detection of a high number of cells, in the intrinsic variability of wood anatomical features, and in the sample quality. To properly classify and interpret features within the images, DCNNs need to undergo a training stage. We performed the training with images from transversal wood anatomical sections, together with manually created optimal outputs of the target cell areas. The target species included an example for the most common wood anatomical structures: four conifer species; a diffuse-porous species, black alder (Alnus glutinosa L.); a diffuse to semi-diffuse-porous species, European beech (Fagus sylvatica L.); and a ring-porous species, sessile oak (Quercus petraea Liebl.). The DCNN was created in Python with Pytorch, and relies on a Mask-RCNN architecture. The developed algorithm detects and segments cells, and provides information on the measurement accuracy. To evaluate the performance of this tool we compared our Mask-RCNN outputs with U-Net, a model architecture employed in a similar study, and with ROXAS, a program based on traditional image analysis techniques. First, we evaluated how many target cells were correctly recognized. Next, we assessed the cell measurement accuracy by evaluating the number of pixels that were correctly assigned to each target cell. Overall, the “learning process” defining artificial intelligence plays a key role in overcoming the issues that are usually manually solved in QWA analyses. Mask-RCNN is the model that better detects which are the features characterizing a target cell when these issues occur. In general, U-Net did not attain the other algorithms’ performance, while ROXAS performed best for conifers, and Mask-RCNN showed the highest accuracy in detecting target cells and segmenting lumen areas of angiosperms. Our research demonstrates that future software tools for QWA analyses would greatly benefit from using DCNNs, saving time during the analysis phase, and providing a flexible approach that allows model retraining.

Purpose: To investigate in an in vitro model if secondary endobag filling can reduce gutter size during chimney endovascular aneurysm sealing (chEVAS). Materials and Methods: Nellix EVAS systems were deployed in 2 silicone juxtarenal aneurysm models with suprarenal aortic diameters of 19 and 24 mm. Four configurations were tested: EVAS with 6-mm balloon-expandable (BE) or self-expanding (SE) chimney grafts (CGs) in the renal branches of both models. Balloons were inflated simultaneously in the CGs and main endografts during primary and secondary endobag filling and polymer curing. Computed tomography (CT) was performed immediately after the primary and secondary fills. Cross-sectional lumen areas were measured on the CT images to calculate gutter volumes and percent change. CG compression was calculated as the reduction in lumen surface area measured perpendicular to the central lumen line. The largest gutter volume and highest compression were presented per CG configuration per model. Results: Secondary endobag filling reduced the largest gutter volumes from 99.4 to 73.1 mm3 (13.2% change) and 84.2 to 72.0 mm3 (27.6% change) in the BECG configurations and from 67.2 to 44.0 mm3 (34.5% change) and 92.7 to 82.3 mm3 (11.2% change) in the SECG configurations in the 19- and 24-mm models, respectively. Secondary endobag filling increased CG compression in 6 of 8 configurations. BECG compression changed by −0.2% and 5.4% and by −1.0% and 0.4% in the 19- and 24-mm models, respectively. SECG compression changed by 10.2% and 16.0% and by 7.2% and 7.3% in the 19- and 24-mm models, respectively. Conclusion: Secondary endobag filling reduced paragraft gutters; however, this technique did not obliterate them. Increased CG compression and prolonged renal ischemia time should be considered if secondary endobag filling is used.

Long-term climate reconstructions are frequently based on tree-ring high-resolution proxies extracted from subfossil peatland trees. Peatlands are peculiar ecosystems characterized by high moisture in the upper soil part which creates a harsh living environment for trees. The climate mostly indirectly influences tree growth determining seasonal variations in the water table level. Within this framework, the aim of this study was to investigate climate responses of trees (Pinus sylvestris L.) growing inside and outside a Southern Alpine peat bog, by using tree-ring and wood anatomical traits (e.g. tracheid number and dimension, cell-wall thickness). Our results showed differences in the xylem structure and climate signal recorded by peatland and mineral soil trees. Peatland trees were characterized by narrow rings and tracheids with thinner cell wall. Summer temperature and precipitation were the major drivers of xylem formation in peatland trees. At intra-annual level wood anatomical traits revealed a complex within-ring signal during the growing season. The multi-parameters approach together with the high-resolution gained by using tree-ring sectors allowed us to obtain new detailed information on the xylem development of peatland trees and climate drivers that influenced it.

Lumen vessel sizing is important for optimization of interventional outcomes for treatment of vascular disease. The objective of this study is to develop an injection-less method to determine the lumen diameter, using multiple frequencies that eliminates the need for saline injections. We utilize the same electrical conductance devices developed for the two-injection method. A mathematical electrical model was devised to estimate the lumen area and diameter of the arteries. In vitro experiments were used to validate the method for various lumen diameters with both 5-5-5 (peripheral) and 2-2-2 (coronary) spacing conductance guidewires. The majority of 11 vessel data fall within one standard deviation and all the data fall within two standard deviations. The results indicate that the two-frequency model can reasonably predict the lumen diameter in an in-vitro test set-up. Our findings show that this approach can potentially translate to in vivo which would enable pull-back to reconstruct the lumen area profile of the vessel.

Climate change can induce substantial modifications in xylem structure and water transport capacity of trees exposed to environmental constraints. To elucidate mechanisms of xylem plasticity in response to climate, we retrospectively analysed different cell anatomical parameters over tree-ring series in Norway spruce (Picea abies L. Karst.). We sampled 24 trees along an altitudinal gradient (1200, 1600 and 2100 m above sea level, a.s.l.) and processed 2335 ± 1809 cells per ring. Time series for median cell lumen area (MCA), cell number (CN), tree-ring width (RW) and tree-ring-specific hydraulic conductivity (Kr) were crossed with daily temperature and precipitation records (1926-2011) to identify climate influence on xylem anatomical traits. Higher Kr at the low elevation site was due to higher MCA and CN. These variables were related to different aspects of intra-seasonal climatic variability under different environmental conditions, with MCA being more sensitive to summer precipitation. Winter precipitation (snow) benefited most parameters in all the sites. Descending the gradient, sensitivity of xylem features to summer climate shifted mostly from temperature to precipitation. In the context of climate change, our results indicate that higher summer temperatures at high elevations will benefit cell production and xylem hydraulic efficiency, whereas reduced water availability at lower elevations could negatively affect tracheids enlargement and thus stem capacity to transport water.

International audience; The anatomical differences of mature black spruces and balsam firs were examined at stem and root level in order to characterize their wood properties at cellular level and link these differences to climate.* Anatomical variability of these species was evaluated in relation to climate data gathered from 2001 to 2004 during the cell enlargement (CE) and wall thickening and lignification (WTL) phases. Lumen area, single cell wall thickness and total tracheid radial diameter were analyzed and regrouped into earlywood and latewood.* Results from a principal component analysis (PCA) indicated that both first eigenvectors account for 82% and 90% of total variance for CE and WTL respectively. These component factors revealed that precipitation, humidity and number of days with precipitation significantly influence the lumen area (p = 0.0168) and radial cell diameter (p = 0.0222) in earlywood. Significant differences were registered between species and tree parts (stem and root) for the lumen area, radial cell diameter and cell wall thickness in both earlywood and latewood.* In our study, black spruce exhibited smaller tracheid size in both stem and roots compared to balsam fir. Furthermore, the lower amount of tracheids produced during the growing season and higher proportion of latewood ensure a higher wood density of black spruce. The influence of temperature on earlywood formation is significant, whereas no influence was observed on latewood.; Les différences anatomiques au niveau de la tige et du système racinaire d'épinettes noires et de pins gris matures ont été examinées afin de caractériser la qualité de leur bois au niveau cellulaire et de le relier aux conditions climatiques.* Les propriétés anatomiques de ces espèces ont été évaluées en relation avec des variables climatiques compilées au cours des années 2001 à 2004 durant la phase d'élargissement des cellules (CE) et celle de l'épaississement et de la lignification des parois (WTL). L'aire du lumen, l'épaisseur des parois ainsi que le nombre total de trachéides au niveau du diamètre radial des cellules ont été analysés et regroupés selon le bois final et le bois initial.* Les résultats issus d'une analyse en composantes principales (PCA) ont révélé que les deux premiers facteurs (eigenvector) représentent 82 % et 90 % de la variance totale de CE et de WTL respectivement. Ces composantes ont indiqué que la précipitation, l'humidité et le nombre de jours avec pluie influencent significativement la formation de l'aire du lumen (p = 0.0168) et le diamètre radial des cellules (p = 0.0222) dans le bois initial. Des différences significatives ont aussi été enregistrées entre les espèces et les parties de l'arbre pour l'aire du lumen, le diamètre radial des cellules et l'épaisseur des parois dans le bois initial comme dans le bois final.* Dans notre étude, l'épinette noire a présenté dans les tiges et les racines des trachéides de plus petite dimension contrairement au sapin baumier. De plus, la faible quantité de trachéides produite durant la saison de croissance combinée à une proportion plus grande de bois final confère à l'épinette noire une densité de bois plus élevée. Une influence significative de la température a été enregistrée sur la formation du bois initial.