Temperature and masting control Norway spruce growth, but with high individual tree variability

Tree growth and reproduction are subject to trade-offs in resource allocation. At the same time, they are both influenced by climate. In this study, we combined long records of reproductive effort at the individual- (29 years), population- (41 years) and regional (up to 53 years) scale, and tree ring chronologies, to investigate the effects of climate and reproductive allocation on radial growth in an Alpine Norway spruce forest. Seed and cone production was highly variable between years (mean individual CV = 1.39, population CV = 1.19), but showed high reproductive synchrony between individuals (mean inter-tree correlation = 0.72). No long-term trend in reproductive effort was detected over four decades of observations. At the stand scale, cone production was dominated by a small number of individuals (\u201csuper-producers\u201d), who remained dominant over three decades. Individual tree growth responded positively to summer temperature, but the response to cone production varied between individual trees. Consequently, we found some evidence that mast years were associated with a divergence in growth between high and low cone producing individuals, and a decline in within-population growth synchrony. At the population level we found limited evidence of a relationship between growth and reproduction. Radial growth was lower than average in some mast years, but not in others. This was partly explained by summer temperature during the year of growth, with growth reductions restricted to mast years that coincided with colder than average summers. Regional mast records and tree ring chronologies provided some support to indicate that our results were consistent in other spruce stands, although the effect of mast years on growth appeared to vary between sites. Tree ring variation at the individual and population level, and between-tree growth synchrony are influenced by masting, and consequently dendrochronologists should consider both the occurrence of masting and the individual differences in reproductive effort when interpreting tree ring datasets. Our results also indicate that tree ring chronologies contain information to facilitate reconstruction of mast events, which will help address outstanding questions regarding the future response of masting to climate change

Identificación de maderas colombianas utilizando el Xylotron: Prueba de concepto de una colaboración internacional

Field deployable computer vision wood identification systems can play a key role in combating illegal logging in the real world. This work used 764 xylarium specimens from 84 taxa to develop an image data set to train a classifier to identify 14 commercial Colombian timbers. We imaged specimens from various xylaria outside Colombia, trained and evaluated an initial identification model, then collected additional images from a Colombian xylarium (BOFw), and incorporated those images to refine and produce a final model. The specimen classification accuracy of this final model was ~ 97%, demonstrating that including local specimens can augment the accuracy and reliability of the XyloTron system. Our study demonstrates the first deployable computer vision model for wood identification in Colombia, developed on a timescale of months rather than years by leveraging international cooperation. We conclude that field testing and advanced forensic and machine learning training are the next logical steps.Sistemas de identificación automatizada de maderas pueden fortalecer la lucha contra el tráfico ilegal de maderas. Este trabajo utilizó 764 especímenes de xilotecas, correspondientes a 84 taxones, para desarrollar un modelo de identificación para 14 especies comerciales de Colombia. Se comenzó colectando imágenes de especímenes provenientes de xilotecas fuera de Colombia, que se utilizaron para entrenar y evaluar un modelo inicial. Se colectaron imágenes adicionales provenientes de una xiloteca Colombiana (BOFw), que se utilizaron para refinar y producir el modelo final. La capacidad de reconocimiento de este modelo fue del ~97%, demostrando que incluir muestras locales aumenta la precisión y confiabilidad del sistema [XyloTron]. Este estudio presenta el primer modelo de vision computarizada para identificación de maderas en Colombia, desarrollado en una escala de tiempo corta y bajo cooperación internacional. Concluimos que pruebas en campo y capacitación forense y en aprendizaje automatizado, son los siguientes pasos lógicos a seguir