Search

Producción Científica, Standard procedures to obtain high-quality images of wood samples have become a bottleneck in the digitization of dendrochronology. Digitization is currently dominated by flatbed scanners, but the use of these devices is limited by sample length and surface flatness. Although several solutions based on digital photography have been published, they lack effective digitization processes or are too expensive to be widely adopted. Free open-source software and hardware has emerged as an alternative to create research tools that combine reduced costs with high reliability. Here we present CaptuRING, an open-source tool for wood sample digitization combining a do-it-yourself hardware based on Arduino® with a DSLR camera and a free open-source software with an easy-to-use graphical user interface. We compared CaptuRing with image acquisition from a standard flatbed scanner Epson® V750PRO. CaptuRING outperforms scanner image resolution and sharpness, while it removes sample size limitations. Moreover, CaptuRing performs this task in less than half of the time needed by Epson® V750PRO flatbed scanner. CaptuRING emerges as a reliable and low-cost tool to capture high-resolution images of wood samples boosting current digitization processes. The combination of free open software and hardware empowers dendrochronology to advance in wood sample digitization., Junta de Castilla y León, project OUTBREAK (VA171P20) and (IR2020-1-UVA08), Ministerio de Ciencia, Innovación y Universidades, grant number (CGL2017-87309-P) (MGH PRE2018-084106) and project PROWARM (PID2020-118444GA-I00), Universidad Politécnica de Madrid (through Project RP200060107)

Interaction of global change drivers affects forest resilience. Land-use changes (land abandonment) and climate change (a higher frequency and intensity of droughts) are interacting in the Mediterranean Region. Components of resilience in secondary stem growth have been widely studied but, despite the importance of root systems in forest functionality and resilience, non-previous studies have assessed them in coarse roots. In this study, we use Juniperus thurifera tree-ring chronologies in coarse roots and stems to assess biomass allometry and tree resilience to drought events comparing two stages of a forest expansion gradient (mature forests and transition zone) in Alto Tajo Natural Park. We extracted cores of stems and coarse roots in 48 trees distributed in different developmental stages and calculated cross-sectional area increments, root-stem allometric relationship and resilience components for both organs in each individual for two drought events (2005 and 2012). Stem and root growth as well as its allometric exponent were higher in the transition zone than in mature forests. Both organs exhibited a trade-off between resistance and recovery in mature forests but maintenance of higher values in the transition zone. Resilience did not show differences between organs being higher in the transition zone than in mature forests. However, relative resilience in roots in the transition zone was higher than in mature forests, without differences in stems between stages. Finally, the 2012 drought event showed a higher impact on the components of resilience than the 2005 drought event. This study extends the knowledge of root response to drought events and highlights the potential of land-use legacies to reduce the negative impact of climate change by promoting increased root recovery after drought events in trees established in past agricultural lands., This study was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) grant: COMEDIAS (CGL2017-83170-R), FPI fellowship to BAM (PRE2018-083584) and Comunidad de Madrid grant: REMEDINAL TE (Ref. TE-CM.S2018/EMT-4338,2019-2023-Comunidad de Madrid).

Producción Científica, Macaronesian laurel forests are the only remnants of a subtropical palaeoecosystem dominant during the Tertiary in Europe and northern Africa. These biodiverse ecosystems are restricted to cloudy and temperate insular environments in the North Atlantic Ocean. Due to their reduced distribution area, these forests are particularly vulnerable to anthropogenic disturbances and changes in climatic conditions. The assessment of laurel forest trees’ response to climate variation by dendrochronological methods is limited because it was assumed that the lack of marked seasonality would prevent the formation of distinct annual tree rings. The aims of this study were to identify the presence of annual growth rings and to assess the dendrochronological potential of the most representative tree species from laurel forests in Tenerife, Canary Islands. We sampled increment cores from 498 trees of 12 species in two well-preserved forests in Tenerife Island. We evaluated tree-ring boundary distinctness, dating potential, and sensitivity of tree-ring growth to climate and, particularly, to drought occurrence. Eight species showed clear tree-ring boundaries, but synchronic annual tree rings and robust tree-ring chronologies were only obtained for Laurus novocanariensis, Ilex perado subsp. platyphylla, Persea indica and Picconia excelsa, a third of the studied species. Tree-ring width depended on water balance and drought occurrence, showing sharp reductions in growth in the face of decreased water availability, a response that was consistent among species and sites. Inter-annual tree-ring width variation was directly dependent on rainfall input in the humid period, from previous October to current April. The four negative pointer years 1995, 1999, 2008 and 2012 corresponded to severe drought events in the study area. This study gives the first assessment of dendrochronological potential and tree-ring climate sensitivity of tree species from the Tenerife laurel forest, which opens new research avenues for dendroecological studies in Macaronesian laurel forests., Ministerio de Ciencia, Innovación y Universidades (projects PID2019-109906RA-I00, PID2020-118444GA-100 and PID2019-106908RA-I00/AEI/10.13039/501100011033), Ministerio de Ciencia, Innovación y Universidades (predoctoral contract PRE2018-084106), Ministerio de Economía, Industria y Competitividad (project CGL2017-87309-P and postdoctoral grant IJC2019-040571-I), Junta de Castilla y León (projects VA113G19 and IR2020-1-UVA08), Universidad de Valladolid (predoctoral contract 113-2019PREUVA22), Comunidad de Madrid (project S2018/EMT-4338)

Producción Científica, Tree pollarding was a dominant management strategy of European forests for centuries creating open agroforestry landscapes with important cultural and environmental values. This traditional practice has been widely abandoned in last decades with a subsequent impact in terms of biodiversity and cultural loss. Central Spain hosts the largest and best-preserved area of pollarded narrow-leaved ash (Fraxinus angustifolia Vahl.) woodlands in Europe. The main aim of this research is to obtain rigorous historical records of pollarding frequency to get adequate information for traditional ash management. We used dendrochronological techniques to evaluate temporal changes of pollarding frequency and rotation length. We analysed the stand level synchrony and the effect of land property on pollarding activity from 322 trees growing in eight pollard stands in Central Spain. Pollarding events were unequivocally identified at tree level by a characteristic change in growth pattern. We identified 2426 tree-level pruning events with the first event dated in 1777. Historical pruning recurrence ranged between 5 and 10 years with higher pollarding frequency on private lands. Pruning events within each site were synchronous, suggesting the existence of a rotational schema within each stand. Pruning frequency decreased drastically in the 1970s matching with the depopulation of rural areas and the general abandonment of traditional practices. Pollarding practices have recovered in recent decades although with lower intensity and lacking the synchronic historical patterns. Providing technical and economic support to make this traditional activity profitably would have strong environmental revenue due the multiple ecosystem services provided by pollarded ashes., iuFOR Institute Unit of Excellence" of the University of Valladolid, funded by the Junta de Castilla y León and co-financed by the European Union (ERDF "Europe drives our growth") project (CLU-2019-01), Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación - MCIN/AEI/10.13039/501100011033 project PROWARM (PID2020-118444GA-100),(IJC2019-040571-I),(grant PRE2018-084106), Junta de Castilla y León, projects, (VA171P20) and (IR2020-1-UVA08), Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCLE

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.

Producción Científica, The ability of trees to endure for millennia, surpassing human lifetimes, and survive the most destructive human and natural hazards is astonishing. But what is the ecological role of tree longevity? Are old trees more than impressive nature wonders? Can ancient trees become effective genetic reservoirs able to recover bygone ecosystems? Oceanic islands are ideal ecosystems to address these questions, as they have experienced recent and intense human-induced environmental changes. In the Canary Islands in the northeastern Atlantic Ocean, human colonization since the fifth century BCE (Rodríguez-Varela et al., 2017) added logging, fire, and grazing pressure to a territory already experiencing regular volcanic activity. Tenerife Island is the most populated island of the Canary Islands archipelago and harbors the largest subalpine ecosystems in the entire Macaronesian Biogeographic Region. Woodlands in the Tenerife subalpine environment were once formed by the Canary Island juniper (Juniperus cedrus Webb. & Berthel.; hereafter juniper; Machado & Galván, 2012, García-Cervigón et al., 2019), but historical human pressure restricted its distribution to inaccessible spots, away from human activity, such as cliffs. [parte del texto], Comunidad de Madrid, Grant/Award Number: REMEDINAL TE-CM (S2018/EMT-4338), Junta de Castilla y León-Consejería de Educación, Grant/Award Numbers: (VA113G19), (VA171P20) y (IR2020-1-UVA08), Ministerio de Ciencia e Innovación, Grant/Award Numbers: LAUREL (PID2019-109906RA-I00), (PRE2018-084106) and PROWARM (PID2020-118444GA-100), Ministerio de Economía, Industria y Competitividad. Grant/Award Number: (IJC2019-040571-I), Secretaría de Estado de Investigación, Desarrollo e Innovación, Grant/Award Number: spRING (CGL2017-87309-P)

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.

Producción Científica, Wood microdensitometry provides an integrated measurement of inter and intra-annual changes in wood anatomy and lignification. Although it can be acquired through a wide array of techniques, X-ray-based techniques are still the standard. Conversion of a grayscale X-ray image to density and annual ring boundaries delimitation is performed through image analysis software. Proprietary software has dominated these applications, albeit Free Open Source Software (FOSS) has been developed recently. We present ρ-MtreeRing, a user-friendly FOSS that streamlines the entire microdensitometry analysis process through a graphical user interface based on Shiny R Software without any programming knowledge. We compared the results of this program with the most widely used commercial software (WinDendro), showing the validity of the results. ρ-MtreeRing can be personalized and developed by the microdensitometry research community., Junta de Castilla y León (VA171P20), Ministerio de Ciencia e Innovación y Ministerio de Universidades grant number CGL2017-87309-P (MGH PRE2018-084106) and project PROWARM (PID2020-118444GA-I00), Universidad Politécnica de Madrid (through Project RP200060107), Centro de Recursos Hídricos para la Agricultura y la Minería (ANID/FONDAP/15130015)

Plants in Mediterranean mountains are particularly vulnerable to climatic change. In these environments, low temperature is combined with water shortage during summer, and as a result, the positive effect of global warming theoretically expanding the growing season length may be counterbalanced by rising drought stress. These circumstances may be exacerbated in the rear edge of species distribution, where warmer conditions occur. Here, we examined the climate-growth relationships of Juniperus sabina, a major prostrate shrub above the treeline in Mediterranean mountains, to investigate climate sensitivity and long-term signals stability in four rear-edge populations from southern Spain. We demonstrate that, over recent decades, local climatic conditions have modulated the response of J. sabina secondary growth to the ongoing climate change. We observed a negative effect of winter-spring moisture on secondary growth that suggests a limitation for earlier growth activity at higher elevation, potentially hindering the ability of J. sabina to compensate forthcoming increases in summer drought. At the driest site, we also detected a positive effect of October precipitation, suggesting a second growth pulse by early autumn. Our results provide an example of how local climatic conditions may limit plastic responses of secondary growth to climatic variability. The implications of growth limitation in J. sabina exceed the species-scale level, since these prostrate shrubs play a critical role as nurse plants and local biodiversity foci in Mediterranean mountains.

Tetraclinis articulata is a xerothermic Mediterranean conifer native from NW Africa that grows under semiarid conditions in the Atlas Mountains. This species is particularly well adapted to water scarcity and forms xeric woodlands subjected to recurring drought, aridification and overexploitation. Wood of T. articulata has been considered of limited dendrochronological value due to abundant anatomical anomalies in their growth rings. We studied tree-ring growth and tree-ring features to check its dendrochronological potential and evaluate their climatic signals and drought legacy effects at two semiarid sites with contrasting elevation in Morocco. Tree-ring boundaries were properly identified on wood cores from 60 to 68% of the sampled trees. Intra-annual wood density fluctuations (IADF), microrings, missing rings and rings with undefined limits were most abundant at the low-elevation coastal site than at the mountain site. Microring and missing ring abundance was inversely related to tree-ring growth, independent of cambial age, and mostly dependent on drought occurrence. IADF frequency was independent of tree-ring growth but inversely related to cambial age. A complex response of IADF formation to cool March to June conditions was found at the low-elevation coastal site, while IADF formation in the mountain site was related to May water availability. Undefined ring limits were observed only at the low-elevation site, showing positive relationships with elevated maximum temperatures in previous winter. Previous winter rainfall favored radial growth, but a significant legacy effect of water availability was evident up to three years prior to growth. Tree-ring growth was mostly related to water availability 33 and 26 months prior to growth at low-elevation and mountain sites, respectively. The obtained results reveal a very plastic cambial activity and a strong ability of T. articulata to withstand drought even for long periods.

Oceanic islands ecosystems are among the most endangered in the world, as the effects of ongoing climate change may potentially combine with other pre-existing drivers of plant population decline. In the Canary Islands, nitrogen-fixing Teide broom (Spartocytisus supranubius) is a keystone species in the Teide National Park high mountain ecosystem. However, recruitment failure due to introduced herbivores and dieback episodes are decimating its populations. We explored the role of climate as a potential driver of Teide broom mortality. We analyzed annual rings of Teide broom to reconstruct the impact of climate on secondary growth, intrinsic water use efficiency (iWUE) and mortality, and to explore the potential for growth rates and levels of resilience to act as indicators of mortality risk. We found that higher precipitation from October to February improved Teide broom secondary growth, whereas iWUE increased with high July–August temperatures. Extreme drought events in 2001 and 2012 strongly reduced secondary growth and resulted in subsequent plant death. Individuals that subsequently died had lower growth rates, poorer capacity for growth recovery after drought events and marginally higher iWUE than those which survived. More frequent recurrence of extreme drought events in the future would increase the frequency of dieback episodes, and the combination of a decline in mature individuals and lower recruitment rates due to exotic herbivore pressure would mean an uncertain future for the Teide broom. Our results indicate how global change may impact keystone species in protected areas and highlight the need for urgent implementation of proactive conservation policies.

Xylem is a vascular tissue that conducts sap (water and dissolved minerals) from the roots to the rest of the plant while providing physical support and resources. Sap is conducted within dead hollow cells (called vessels in flowering plants) arranged to form long pipes. Once formed, vessels do not change their structure and last from years to millennia. Vessels’ configuration (size, abundance, and spatial pattern) constitutes a record of the plant–environment relationship, and therefore, a tool for monitoring responses at the plant and ecosystem level. This information can be extracted through quantitative anatomy; however, the effort to identify and measure hundreds of thousands of conductive cells is an inconvenience to the progress needed to have solid assessments of the anatomical–environment relationship. In this paper, we propose an automatic methodology based on convolutional neural networks to segment xylem vessels. It includes a post-processing stage based on the use of redundant information to improve the performance of the outcome and make it useful in different sample configurations. Three different neural networks were tested obtaining similar results (pixel accuracy about 90%), which indicates that the methodology can be effectively used for segmentation of xylem vessels into images with non-homogeneous variations of illumination. The development of accurate automatic tools using CNNs would reduce the entry barriers associated with quantitative xylem anatomy expanding the use of this technique by the scientific community.

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.

Aim of study: The main objective is to determine the best machine-learning algorithm to classify the stand types of Monteverde forests combining LiDAR, orthophotography, and Sentinel-2 data, thus providing an easy and cheap method to classify Monteverde stand types.Area of study: 1500 ha forest in Monteverde, North Tenerife, Canary Islands.Material and methods: RF, SVML, SVMR and ANN algorithms are used to classify the three Monteverde stand types. Before training the model, feature selection of LiDAR, orthophotography, and Sentinel-2 data through VSURF was carried out. Comparison of its accuracy was performed.Main results: Five LiDAR variables were found to be the most efficient for classifying each object, while only one Sentinel-2 index and one Sentinel-2 band was valuable. Additionally, standard deviation and mean of the Red orthophotography colour band, and ratio between Red and Green bands were also found to be suitable. SVML is confirmed as the most accurate algorithm (0.904, 0.041 SD) while ANN showed the lowest value of 0.891 (0.073 SD). SVMR and RF obtain 0.902 (0.060 SD) and 0.904 (0.056 SD) respectively. SVML was found to be the best method given its low standard deviation.Research highlights: The similar high accuracy values among models confirm the importance of taking into account diverse machine-learning methods for stand types classification purposes and different explanatory variables. Although differences between errors may not seem relevant at a first glance, due to the limited size of the study area with only three plus two categories, such differences could be highly important when working at large scales with more stand types.ADDITIONAL KEY WORDSRF algorithm, SVML algorithm, SVMR algorithm, ANN algorithm, LiDAR, orthophotography, Sentinel-2ABBREVIATIONS USEDANN, artificial neural networks algorithm; Band04, Sentinel-2 band 04 image data; BR, brezal; DTHM, digital tree height model; DTHM-2016, digital tree height model based on 2016 LiDAR data; DTM, digital terrain model; DTM-2016, digital terrain model based on 2016 LiDAR data; FBA, fayal-brezal-acebiñal; FCC, canopy cover; HEIGHT-2009, maximum height based on 2009 LiDAR data; HGR, height growth based on 2009 and 2016 LiDAR data; LA, laurisilva; NDVI705, Sentinel-2 index image data; NMF, non-Monteverde forest; NMG, non-Monteverde ground; P95-2016, height percentile 95 based on 2016 LiDAR data; RATIO R/G, ratio between Red and Green bands orthophotograph data; RED, Red band orthophotograph data; Red-SD, standard deviation of the Red band orthophotograph data; RF, random forest algorithm; SVM, support vector machine algorithm; SVML, linear support vector machine algorithm; SVMR, radial support vector machine algorithm; VSURF, variable selection using random forest.

Xylem is a vascular tissue that conveys water and dissolved minerals from the roots to the rest of the plant and also provides physical support. The most important cells present in xylem are called vessels. These cells are arranged to form long pipes that carry water through the tree. The identification, counting and subsequent characterization of xylem vessels is essential for monitoring tree health and its relationship with climatic conditions. Although automatic and semi-automatic image processing tools are available to analyze the structure of xylem at the cellular level, they usually require the supervision of an expert to obtain optimal segmentation, making it a highly time-consuming process. To overcome this limitation, a Convolutional Neural Network model was used to process digital images of 23 branch sections in order to segment the xylem vessels. The obtained results were compared with other two classical methods, Otsu's thresholding method, and an active contour method known as Chan-Vese segmentation algorithm. The obtained results show the potential of convolutional neural networks to overcome aspects such as non-homogeneous illumination of images, where conventional methods tend to obtain unsatisfactory results.