The water absorbability of beech (Fagus sylvatica l.) and fir (Abies alba mill.) organic matter in the forest floor

The organic horizons of forest soils are characterised by double capillarity: between particles and inside them. It has been hypothesized that the time required to fill the internal capillarity of organic particles depends on their botanical origin and the degree of their decomposition. The aim of the present study is to determine the time of water absorption by organic matter that is part of the Ol and Ofh horizons of selected beech (Fagus sylvatica L.) and fir (Abies alba Mill.) stands. The present research on water absorbability lasted for 14 days and consisted in measuring the absorption time in organic particles from the moment of immersion of an air-dry sample in water until the particles soaked in water exceeded the density of 1.0 g·cm^-3.  It was found that in fir organic matter the time of water absorption decreases with the advancement of decomposition. In beech stands, progressing decomposition processes result in a longer water absorption time. The dynamics of water absorption of organic matter indicates that no single rainfall is able to entirely fill the internal capillarity of organic particles, whereby the organic horizons of forest soils can maintain the ability to retain water even in long-term rainfall.

Transcriptome profiling in Camellia japonica var. decumbens for the discovery of genes involved in chilling tolerance under cold stress

Camellia japonica var. decumbens is a naturally occurring highly cold resistant variety of Camellia japonica which is suitable for snowy and cold regions. However, the underlying cold-adaptive mechanisms associated with gene regulation have been poorly investigated. We analyzed the transcriptomic changes caused by cold stress in a cold-tolerant accession. Samples were collected at the end of each temperature treatment (T1, T3, T5, T7 and T9 represent the temperatures 25°C, 0°C, -4°C, -8°C and -12°C, respectively). Sample T1 at 25°C was used as control. Based on transcriptome analysis, 2828, 2384, 3099 and 3075 differentially expressed genes (DEGs) were up-regulated, and 3184, 2592, 2373 and 2615 DEGs were down-regulated by analyzing T3/T1, T5/T1, T7/T1 and T9/T1, respectively. A gene ontology (GO) analysis revealed an enrichment of GO terms such as response to stimulus, metabolic process, catalytic activity or binding. Out of the larger number of DEGs, 67 functional and regulatory DEGs stood out, since they were functionally characterized in other models. These genes are cold-responsive transcription factors (26) or involved in cold sensor or signal transduction (17) and in the stabilization of the plasma membrane and osmosensing response (24). These results suggest rapid and multiple molecular mechanisms of perception, transduction and responses to cold stress in cold acclimation of Camellia japonica var. decumbens. They could also serve as a valuable resource for relevant research on cold-tolerance and help to explore cold-related genes to foster the understanding of low-temperature tolerance and plant-environment interactions.

Forest inventory sensitivity to UAS-based image processing algorithms

Frequent and accurate estimation of forest structure parameters, such as number of trees per hectare or total height, are mandatory for sustainable forest management. Unmanned aircraft system (UAS) equipped with inexpensive sensors can be used to monitor and measure forest structure. The detailed information provided by the UAS allows tree level forest inventory. However, tree identification depends on a variety of parameters defining the image processing and tree segmentation algorithms. The objective of our study was to identify parameter combinations that accurately delineated trees and their heights. We evaluated the impact of different tree segmentation and point cloud generation algorithms on forest inventory from imagery collected with a UAS over a mature Douglas-fir plantation forest. We processed the images with two commonly used commercial software packages, Agisoft PhotoScan and Pix4Dmapper, both implementing image processing algorithms called Structure from Motion. For each software we generated photogrammetric point clouds by varying the parameters defining the implementation. We segmented individual trees and heights using three tree algorithms: Variable Window Filter, Graph-Theoretical, and Watershed Segmentation. We assessed the impact of image processing algorithms on forest inventory by comparing the estimated trees with trees manually identified from the point clouds. We found that the type of tree segmentation and image processing algorithms have a significant effect in accurately identifying trees. For tree height estimation, we found strong evidence that image processing algorithms had significant effects, whereas tree segmentation algorithms did not significantly affect tree height estimation.These findings may be of interest to others that are using high-resolution spatial imagery to estimate forest inventory parameters.

Assessing the forest-wood chain at local level: A Multi-Criteria Decision Analysis (MCDA) based on the circular bioeconomy principles