Forest biomass is an essential indicator for monitoring the Earth’s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world’s forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.

The main antioxidants present in plant extracts—quercetin, β-carotene, gallic acid, ascorbic acid, hydroxybenzoic acid, caffeic acid, catechin and scopoletin—are able to synthesize silver nanoparticles when reacting with a Ag NO₃ solution. The UV-visible absorption spectrum recorded with most of the antioxidants shows the characteristic surface plasmon resonance band of silver nanoparticles. Nanoparticles synthesised with ascorbic, hydroxybenzoic, caffeic, and gallic acids and scopoletin are spherical. Nanoparticles synthesised with quercetin are grouped together to form micellar structures. Nanoparticles synthesised by β-carotene, were triangular and polyhedral forms with truncated corners. Pentagonal nanoparticles were synthesized with catechin. We used Fourier-transform infrared spectroscopy to check that the biomolecules coat the synthesised silver nanoparticles. X-ray powder diffractograms showed the presence of silver, AgO, Ag₂O, Ag₃O₄ and Ag₂O₃. Rod-like structures were obtained with quercetin and gallic acid and cookie-like structures in the nanoparticles obtained with scopoletin, as a consequence of their reactivity with cyanide. This analysis explained the role played by the various agents responsible for the bio-reduction triggered by nanoparticle synthesis in their shape, size and activity. This will facilitate targeted synthesis and the application of biotechnological techniques to optimise the green synthesis of nanoparticles.

In Quercus suber, cork oak, a Mediterranean forest tree of economic and social interest, rapid production of isogenic lines and clonal propagation of elite genotypes have been achieved by developing in vitro embryogenesis from microspores and zygotic embryos respectively. Despite its high potential in tree breeding strategies, due to their recalcitrancy, the efficiency of embryogenesis in vitro systems in many woody species is still very low since factors responsible for embryogenesis initiation and embryo development are still largely unknown. The search for molecular and cellular markers during early stages of in vitro embryogenesis constitutes an important goal to distinguish, after induction, responsive from non-responsive cells, and to elucidate the mechanisms involved in embryogenesis initiation for their efficient manipulation. In this work, we have performed a comparative analysis of two embryogenesis pathways derived from microspores and immature zygotic embryos in cork oak in order to characterize early markers of reprogrammed cells in both pathways. Rearrangements of the cell structural organization, changes in epigenetic marks, cell wall polymers modifications and endogenous auxin changes were analyzed at early embryogenesis stages of the two in vitro systems by a multidisciplinary approach. Results showed that early embryo cells exhibited defined changes of cell components which were similar in both embryogenesis in vitro systems, cellular features that were not found in non-embryogenic cells. DNA methylation level and nuclear pattern, proportion of esterified pectins in cell walls, and endogenous auxin levels were different in embryo cells in comparison with microspores and immature zygotic embryo cells from which embryos originated, constituting early embryogenesis markers. These findings suggest that DNA hypomethylation, cell wall remodeling by pectin esterification and auxin increase are involved in early in vitro embryogenesis in woody species, providing new evidences of the developmental pattern similarity between both embryogenesis pathways, from microspores and immature zygotic embryos, in woody species.

The accurate prediction of forest above-ground biomass is nowadays key to implementing climate change mitigation policies, such as reducing emissions from deforestation and forest degradation. In this context, the coefficient of determination ( $R^2$) is widely used as a means of evaluating the proportion of variance in the dependent variable explained by a model. However, the validity of $R^2$ for comparing observed versus predicted values has been challenged in the presence of bias, for instance in remote sensing predictions of forest biomass. We tested suitable alternatives, e.g. the index of agreement ( $d$) and the maximal information coefficient ( $MIC$). Our results show that $d$ renders systematically higher values than $R^2$, and may easily lead to regarding as reliable models which included an unrealistic amount of predictors. Results seemed better for $MIC$, although $MIC$ favoured local clustering of predictions, whether or not they corresponded to the observations. Moreover, $R^2$ was more sensitive to the use of cross-validation than $d$ or $MIC$, and more robust against overfitted models. Therefore, we discourage the use of statistical measures alternative to $R^2$ for evaluating model predictions versus observed values, at least in the context of assessing the reliability of modelled biomass predictions using remote sensing. For those who consider $d$ to be conceptually superior to $R^2$, we suggest using its square $d^2$, in order to be more analogous to $R^2$ and hence facilitate comparison across studies.

Forest stand structure is an important concept for ecology and planning in sustainable forest management. In this article, we consider that the incorporation of complementary multispectral information from optical sensors to Light Detection and Ranging (LiDAR) may be advantageous, especially through data fusion by back-projecting the LiDAR points onto the multispectral image. A multivariate data set of both LiDAR and multispectral metrics was related with a multivariate data set of stand structural variables measured in a Scots pine forest through canonical correlation analysis (CCA). Four statistically significant pairs of canonical variables were found, which explained 83.0% accumulated variance. The first pair of canonical variables related indicators of stand development, i.e. height and volume, with LiDAR height metrics. CCA also found attributes describing stand density to be related to LiDAR and spectral variables determining canopy coverage. Other canonical variables pertained to Lorenz curve-derived attributes, which are measures of within-stand tree size variability and heterogeneity, able to discriminate even-sized from uneven-sized stands. The most relevant result was to find that metrics derived from the multispectral sensor showed significant explanatory potential for the prediction of these structural attributes. Therefore, we concluded that metrics derived from the optical sensor have potential for complementing the information from the LiDAR sensor in describing structural properties of forest stands. We recommend the use of back-projecting for jointly exploiting the synergies of both sensors using similar types of metrics as they are customary in forestry applications of LiDAR.