Satellite data and machine learning reveal the incidence of late frost defoliations on Iberian beech forests.

Climate warming is driving an advance of leaf unfolding date in temperate deciduous forests, promoting longer growing seasons and higher carbon gains. However, an earlier leaf phenology also increases the risk of late frost defoliation (LFD) events. Compiling the spatiotemporal patterns of defoliations caused by spring frost events is critical to unveil whether the balance between the current advance in leaf unfolding dates and the frequency of LFD occurrence is changing and represents a threaten for the future viability and persistence of deciduous forests. We combined satellite imagery with machine learning techniques to reconstruct the spatiotemporal patterns of LFD events for the 2003-2018 period in the Iberian range of European beech (Fagus sylvatica), at the drier distribution edge of the species. We used MODIS Vegetation Index Products to generate a Normalized Difference Vegetation Index (NDVI) time series for each 250 × 250 m pixel in a total area of 1,013 km2 (16,218 pixels). A semi-supervised approach was used to train a machine learning model, in which a binary classifier called Support Vector Machine with Global Alignment Kernel was used to differentiate between late frost and non-late frost pixels. We verified the obtained estimates with photointerpretation and existing beech tree-ring chronologies to iteratively improve the model. Then, we used the model output to identify topographical and climatic factors that determined the spatial incidence of LFD. During the study period, LFD was a low recurrence phenomenon that occurred every 15.2 yr on average and showed high spatiotemporal heterogeneity. Most LFD events were condensed in 5 yr and clustered in western forests (86.5% in one-fifth of the pixels) located at high elevation with lower than average precipitation. Elevation and longitude were the major LFD risk factors, followed by annual precipitation. The synergistic effects of increasing drought intensity and rising temperature combined with more frequent late frost events may determine the future performance and distribution of beech forests. This interaction might be critical at the beech drier range edge, where the concentration of LFD at high elevations could constrain beech altitudinal shifts and/or favor species with higher resistance to late frosts.

Tree ring segmentation using UNEt TRansformer neural network on stained microsections for quantitative wood anatomy.

Forests are critical in the terrestrial carbon cycle, and the knowledge of their response to ongoing climate change will be crucial for determining future carbon fluxes and climate trajectories. In areas with contrasting seasons, trees form discrete annual rings that can be assigned to calendar years, allowing to extract valuable information about how trees respond to the environment. The anatomical structure of wood provides highly-resolved information about the reaction and adaptation of trees to climate. Quantitative wood anatomy helps to retrieve this information by measuring wood at the cellular level using high-resolution images of wood micro-sections. However, whereas large advances have been made in identifying cellular structures, obtaining meaningful cellular information is still hampered by the correct annual tree ring delimitation on the images. This is a time-consuming task that requires experienced operators to manually delimit ring boundaries. Classic methods of automatic segmentation based on pixel values are being replaced by new approaches using neural networks which are capable of distinguishing structures, even when demarcations require a high level of expertise. Although neural networks have been used for tree ring segmentation on macroscopic images of wood, the complexity of cell patterns in stained microsections of broadleaved species requires adaptive models to accurately accomplish this task. We present an automatic tree ring boundary delineation using neural networks on stained cross-sectional microsection images from beech cores. We trained a UNETR, a combined neural network of UNET and the attention mechanisms of Visual Transformers, to automatically segment annual ring boundaries. Its accuracy was evaluated considering discrepancies with manual segmentation and the consequences of disparity for the goals of quantitative wood anatomy analyses. In most cases (91.8%), automatic segmentation matched or improved manual segmentation, and the rate of vessels assignment to annual rings was similar between the two categories, even when manual segmentation was considered better. The application of convolutional neural networks-based models outperforms human operator segmentations when confronting ring boundary delimitation using specific parameters for quantitative wood anatomy analysis. Current advances on segmentation models may reduce the cost of massive and accurate data collection for quantitative wood anatomy.

Haplotypes in the GC, CYP2R1 and CYP24A1 Genes and Biomarkers of Bone Mineral Metabolism in Older Adults.

Candidate gene studies have analyzed the effect of specific vitamin D pathway genes on vitamin D availability; however, it is not clear whether genetic variants also affect overall bone metabolism. This study evaluated the association between genetic polymorphisms in GC, CYP2R1 and CYP24A1 and serum levels of total 25(OH)D, iPTH and other mineral metabolism biomarkers (albumin, total calcium and phosphorus) in a sample of 273 older Spanish adults. We observed a significant difference between CYP2R1 rs10741657 codominant model and total 25(OH)D levels after adjusting them by gender (p = 0.024). In addition, the two SNPs in the GC gene (rs4588 and rs2282679) were identified significantly associated with iPTH and creatinine serum levels. In the case of phosphorus, we observed an association with GC SNPs in dominant model. We found a relationship between haplotype 2 and 25(OH)D levels, haplotype 4 and iPTH serum levels and haplotype 7 and phosphorus levels. In conclusion, genetic variants in CYP2R1 and GC could be predictive of 25(OH)D and iPTH serum levels, respectively, in older Caucasian adults. The current study confirmed the role of iPTH as one of the most sensitive biomarkers of vitamin D activity in vivo.

Warmer springs have increased the frequency and extension of late-frost defoliations in southern European beech forests.

Climate change is increasing the frequency of extreme climate events, causing profound impacts on forest function and composition. Late frost defoliation (LFD) events, the loss of photosynthetic tissues due to low temperatures at the start of the growing season, might become more recurrent under future climate scenarios. Therefore, the detection of changes in late-frost risk in response to global change emerges as a high-priority research topic. Here, we used a tree-ring network from southern European beech (Fagus sylvatica L.) forests comprising Spain, Italy and the Austrian Alps, to assess the incidence of LFD events in the last seven decades. We fitted linear-mixed models of basal area increment using different LFD indicators considering warm spring temperatures and late-spring frosts as fixed factors. We reconstructed major LFD events since 1950, matching extreme values of LFD climatic indicators with sharp tree-ring growth reductions. The last LFD events were validated using remote sensing. Lastly, reconstructed LFD events were climatically and spatially characterized. Warm temperatures before the late-spring frost, defined by high values of growing-degree days, influenced beech growth negatively, particularly in the southernmost populations. The number of LFD events increased towards beech southern distribution edge. Spanish and the southernmost Italian beech forests experienced higher frequency of LFD events since the 1990s. Until then, LFD events were circumscribed to local scales, but since that decade, LFD events became widespread, largely affecting the whole beech southwestern distribution area. Our study, based on in-situ evidence, sheds light on the climatic factors driving LFD occurrence and illustrates how increased occurrence and spatial extension of late-spring frosts might constrain future southern European beech forests' growth and functionality. Observed alterations in the climate-phenology interactions in response to climate change represent a potential threat for temperate deciduous forests persistence in their drier/southern distribution edge.