Search Results (116)

European forests are facing ongoing climate change, and certain tree species are being critically impacted. The Norway spruce (Picea abies (L.) Karst.) is one of the most sensitive species to climate fluctuations, a fact manifesting itself through massive dieback resulting in a lack of high-quality timber and timber market destabilization. Therefore, the possibility of wood substitution with non-native spruce species, namely, black spruce (Picea mariana (Mill.) Britt., Sterns, et Poggenburg), Serbian spruce (Picea omorika (Pančić) Purk.), and blue spruce (Picea pungens Engelm.), under the specific conditions of forest reclamations with great potential for future afforestation was tested. Wood density, modulus of rupture, and modulus of elasticity were used to evaluate wood quality in comparison with native Norway spruce. The results confirmed that only the Serbian spruce reached the quality of Norway spruce and even exceeded it in terms of wood density (P. omorika 525 kg·m⁻³ vs. P. abies 517 kg·m⁻³) and exhibited comparable parameters with regard to other properties. The density of the other species was significantly lower for blue spruce (476 kg·m⁻³) and black spruce (468 kg·m⁻³). A similar trend was found for other wood parameters, which confirmed that Norway spruce quality was nearly comparable with that of Serbian spruce. On the other hand, black spruce and blue spruce did not match the quality of Norway spruce. The within-stem variability of the properties tested was low for all the spruce species examined. In conclusion, the Serbian spruce showed great potential for future usage in forest management and is one of the possible methods of Norway spruce replacement in times of unprecedented forest disturbances under the effects of global climate change. Full article

Histosols cover about 8–10% of Lithuania’s territory and most of this area is covered with nutrient-rich organic soils (Terric Histosols). Greenhouse gas (GHG) emissions from drained Histosols contribute more than 25% of emissions from the Land Use, Land Use Change and Forestry (LULUCF) sector. In this study, as the first step of examining the carbon dioxide (CO₂) fluxes in these soils, total soil CO₂ efflux and several environmental parameters (temperature of air and topsoil, soil chemical composition, soil moisture, and water table level) were measured in drained Terric Histosols under three native forest stands and perennial grasslands in the growing seasons of 2020 and 2021. The drained nutrient-rich organic soils differed in terms of concentrations of soil organic carbon and total nitrogen, as well as soil organic carbon and total nitrogen ratio. The highest rate of total soil CO₂ efflux was found in the summer months. Overall, the rate was statistically significant and strongly correlated only with soil and air temperature. A trend emerged that total soil CO₂ efflux was 30% higher in perennial grassland than in forested land. Additional work is still needed to estimate the net CO₂ balance of these soils. Full article

The non-destructive testing of wood fibre properties is crucial for informing forest management decisions and achieving optimal resource utilization. Moisture content (MC) is an important indicator of wood freshness and may reveal the presence of wood degradation. However, efficient methods are still needed to better monitor this property along the forest–wood value chain. The objective of the study was to develop prediction models to evaluate log MC based on the propagation of ground penetrating radar (GPR) signals. A total of 165 trees representing four species (black spruce (Picea mariana (Mill.) B.S.P.), white spruce (Picea glauca (Moench) Voss), red spruce (Picea rubens Sarg.), and balsam fir (Abies balsamea (L.) Mill.)) were harvested in two regions of the province of Quebec. GPR signals were acquired in the green (fresh) state and at three subsequent drying stages. Partial least squares regression (PLSR) and locally weighted PLSR (LWPLSR) were employed to establish relationships between GPR signals (antenna frequency: 1.6 GHz) and log properties. The models were fitted on three calibration sets containing four drying stages and different species mixes. The LWPLSR models performed better than the PLSR models for predicting log MC, with a lower root mean square error (RMSEp range: 10.8%–20.2% vs. 13.0%–20.5%) and a higher R²p (0.63–0.87 vs. 0.62–0.82). Spruce-only models performed considerably better than fir-only models while multi-species models were in-between. Despite the complex anisotropy of wood and the physics of wave propagation, the GPR technology can be successfully used to estimate log moisture content, but the GPR-based MC models should be calibrated for each specific type of wood material. Full article

Explaining the mechanism of the coexistence of sympatric species is an important goal of ecology. Five species of woodpeckers coexist in the broadleaved Korean pine forest of Liangshui National Nature Reserve, including the Black Woodpecker (Dryocopus martius), Great Spotted Woodpecker (Dendrocopos major), Lesser Spotted Woodpecker (Dendrocopos minor), Three-toed Woodpecker (Picoides tridactylus), and White-backed Woodpecker (Dendrocopos leucotos). Woodpeckers are considered to be keystone species because of their role as ecosystem engineers, creating breeding and shelter sites for many vertebrate and invertebrate taxa. As woodpeckers are predominant in primary forests, they are sensitive to changes in forest ecosystems. To understand their coexistence mechanisms and propose conservation strategies, it is necessary to investigate their foraging niche differentiation. This study aimed to identify the foraging behavior parameters and foraging tree parameters of five woodpecker species in Liangshui Reserve from October to December. The foraging niches of five woodpecker species were observed, including the type of foraging techniques, foraging height, foraging site, foraging duration, tree species being foraged upon, diameter of the foraging tree at breast height, foraging tree height, and decay status of trees. Our results identified that there were significant differences in the overall foraging ecology of the five species of woodpecker at Liangshui Reserve. The Great Spotted Woodpecker and Lesser Spotted Woodpecker had more diverse foraging patterns and preferred to forage on live trees. The Black Woodpecker and Three-toed Woodpecker excavated and pecked at the trunks of decaying spruce and fir trees. The White-backed Woodpecker preferred to forage in broadleaved trees. The choice of foraging sites was complicated. The size of the foraging trees and decay status of trees were important bases for woodpeckers when choosing trees to forage from. Different woodpeckers achieve stable coexistence through the separation of their foraging niches. This information regarding foraging behavior and foraging tree characteristics provides a basis to study the coexistence patterns of woodpeckers. Our research into woodpecker foraging should be used to inform forest management practices, protect forest ecosystem diversities, and maintain woodpecker community diversity. Full article

The boreal forest of northwestern North America covers an extensive area, contains vast amounts of carbon in its vegetation and soil, and is characterized by extensive wildfires. Catastrophic crown fires in these forests are fueled predominantly by only two evergreen needle-leaf tree species, black spruce (Picea mariana (Mill.) B.S.P.) and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.). Identifying where these flammable species grow through time in the landscape is critical for understanding wildfire risk, damages, and human exposure. Because medium resolution landcover data that include species detail are lacking, we developed a compound modeling approach that enabled us to refine the available evergreen forest category into highly flammable species and less flammable species. We then expanded our refined landcover at decadal time steps from 1984 to 2014. With the aid of an existing burn model, FlamMap, and simple succession rules, we were able to predict future landcover at decadal steps until 2054. Our resulting land covers provide important information to communities in our study area on current and future wildfire risk and vegetation changes and could be developed in a similar fashion for other areas. Full article

Forest productivity is a key driver of forest growth and yield and a critical information need for forest management and planning. Traditionally, this information has come from field plots, but these are expensive to measure and have limited coverage. Remote sensing, on the other hand, can provide forest inventory attributes on landscape scales and with a relatively low cost. A common predictor of forest productivity is site index (SI), traditionally estimated from age and height. In plantations, age can often be treated as a known quantity, but in natural-origin forests (of which Canada has vast swaths), age is often unknown and must be estimated, requiring expensive field work and resulting in a high level of error which, in turn, introduces error into SI estimates. The objective of this study is to generate estimates of SI from two successive LiDAR captures. The 99th percentiles (p99) of LiDAR returns from two successive captures 13 years apart were used along with species-specific SI curves to estimate SI. The results were compared to field-based estimates of SI for two major boreal species, jack pine and black spruce in managed and unmanaged conditions. Overall, the difference between the LiDAR-based SI and the field estimate was 2% with a relative mean squared error of 18%. For the few situations in which the height change was small or negative (less than 0.5%/year), SI was estimated from the average p99 and an assumed age of 100. The advantage of this method is that it does not require field sampling or estimates of age. Using two successive LiDAR captures, wall to wall estimates of SI can be generated at the grid cell level (e.g., 20 × 20 m), a level of detail generally not found in inventories. Overall, our results demonstrate the excellent potential for estimating SI from LiDAR alone, without age, to provide detailed productivity information for forest management and inventory that has been lacking in most large-scale inventories until now. Full article

The ability to accurately assess the impact of organic soil drainage on greenhouse gas emissions (GHG) is still limited. Methane (CH₄) emissions are characterized by significant variations, and GHG emissions from nutrient-rich organic soil in the region have not been extensively studied. The aim of this study was to assess CH₄ and nitrous oxide (N₂O) emissions from nutrient-rich organic soil in hemiboreal forests to provide insights into their role in regional GHG balance. Over the course of one year, CH₄ and N₂O emissions, as well as their affecting factors, were monitored in 31 forest compartments in Latvia in both drained and undrained nutrient-rich organic soils. The sites were selected to include forests of different ages, dominated by silver birch (Betula pendula Roth), Norway spruce (Picea abies (L.) Karsten), and black alder (Alnus glutinosai (L.) Gärtner), as well as clearcuts. Soil GHG emissions were estimated by collecting gas samples using the closed manual chamber method and analyzing these samples with a gas chromatograph. In addition, soil temperature and groundwater level (GW) measurements were conducted during gas sample collection. The mean annual CH₄ emissions from drained and undrained soil were −4.6 ± 1.3 and 134.1 ± 134.7 kg CH₄ ha⁻¹ year⁻¹, respectively. N₂O emissions from undrained soil (4.1 ± 1.4 kg N₂O ha⁻¹ year⁻¹) were significantly higher compared to those from drained soil (1.7 ± 0.6 kg N₂O ha⁻¹ year⁻¹). In most of the study sites, undrained soil acted as a CH₄ sink, with the soil estimated as a mean source of CH₄, which was determined by one site where an emission hotspot was evident. The undrained soil acted as a CH₄ sink due to the characteristics of GW level fluctuations, during which the vegetation season GW level was below 20 cm. Full article

The soil microbiome plays major roles in the below-ground processes and productivity of forest ecosystems. Atmospheric nitrogen (N) deposition is predicted to increase globally and might create disturbances in soil microbial communities, essentially by modifying soil chemistry. However, the impacts of higher N deposition on the soil microbiome in N-limited northern forests are still unclear. For 16 years, we simulated N deposition by adding ammonium nitrate at rates of 3 and 10 times the ambient N deposition directly into soils located in three bioclimatic domains of the eastern Canadian forest (i.e., sugar maple–yellow birch, balsam fir–white birch, and black spruce–feather moss). We identified changes in the microbial communities by isolating the DNA of the L, F, and H soil horizons, as well as by sequencing amplicons of the bacterial 16S rRNA gene and the fungal ITS region. We found that long-term increased N deposition had no effect on soil microbial diversity, but had moderate impacts on the composition of the bacterial and fungal communities. The most noticeable change was the increase in ectomycorrhizal fungi ASV abundance, potentially due to increased tree root growth on fertilized plots. Our work suggests that, in N-limited northern forests, extra N is rapidly mobilized by vegetation, thus minimizing impacts on the soil microbiome. Full article

Today, the emphasis is on environmentally friendly materials. Alkali lignin and spruce sawdust are suitable natural alternatives for removing dyes from wastewater. The main reason for using alkaline lignin as a sorbent is the recovery of waste black liquor from the paper industry. This work deals with removing dyes from wastewater using spruce sawdust and lignin at two different temperatures. The decolorization yields were calculated as the final values. Increasing the temperature during adsorption leads to higher decolorization yields, which may be due to the fact that some substances react only at elevated temperatures. The results of this research are useful for the treatment of industrial wastewater in paper mills, and the waste black liquor (alkaline lignin) can be used as a biosorbent. Full article

This study compared the canopy height model (CHM) performance obtained from large-format airborne and very high-resolution satellite stereo imagery (VHRSI), with airborne laser scanning (ALS) data, for growing stock (stand volume) estimation in mature, dense Latvian hemiboreal forests. The study used growing stock data obtained by ALS-based individual tree detection as training/reference data for the image-based and ALS CHM height metrics-based growing stock estimators. The study only compared the growing stock species-specific area-based regression models which are based solely on tree/canopy height as a predictor variable applied to regular rectangular 0.25 and 1 ha plots and irregular forest stands. This study showed that ALS and image-based (IB) height metrics demonstrated comparable effectiveness in growing stock prediction in dense closed-canopy forests. The relative RMSEs did not exceed 20% of the reference mean values for all models. The best relative RMSEs achieved were 13.6% (IB) and 15.7% (ALS) for pine 0.25 ha plots; 10.3% (IB) and 12.1% (ALS) for pine 1 ha plots; 16.4% (IB) and 12.2% (ALS) for spruce 0.25 ha plots; 17.9% (IB) and 14.2% (ALS) for birch 0.25 ha plots; 15.9% (IB) and 18.9% (ALS) for black alder 0.25 ha plots. This research suggests that airborne imagery and, accordingly, image-based CHMs collected regularly can be an efficient solution for forest growing stock calculations/updates, in addition to a traditional visual forest inventory routine. However, VHRSI can be the fastest and cheapest solution for monitoring forest growing stock changes in vast and dense forestland under optimal data collection parameters. Full article

Tree-counting methods based on computer vision technologies are low-cost and efficient in contrast to the traditional tree counting methods, which are time-consuming, laborious, and humanly infeasible. This study presents a method for detecting and counting tree seedlings in images using a deep learning algorithm with a high economic value and broad application prospects in detecting the type and quantity of tree seedlings. The dataset was built with three types of tree seedlings: dragon spruce, black chokeberries, and Scots pine. The data were augmented via several data augmentation methods to improve the accuracy of the detection model and prevent overfitting. Then a YOLOv5 object detection network was built and trained with three types of tree seedlings to obtain the training weights. The results of the experiments showed that our proposed method could effectively identify and count the tree seedlings in an image. Specifically, the MAP of the dragon spruce, black chokeberries, and Scots pine tree seedlings were 89.8%, 89.1%, and 95.6%, respectively. The accuracy of the detection model reached 95.10% on average (98.58% for dragon spruce, 91.62% for black chokeberries, and 95.11% for Scots pine). The proposed method can provide technical support for the statistical tasks of counting trees. Full article

The timings of the onset and ending of xylogenesis define the time window when environmental conditions are suitable for xylem formation. The relationship between the occurrence of xylem phenological events and the related climatic factors is critical to revealing how xylem formation responds to the changing climate. Given that temperature is the most important factor influencing growth in the boreal forest, we monitored air temperature and xylem phenology at five permanent plots of black spruce (Picea mariana (Mill.) BSP) along a latitudinal gradient of the boreal forest of Quebec, Canada. Microcores were collected weekly or biweekly from five to ten trees per site during the growing seasons from 2002 to 2019. We compared the relationships between air temperature and timings of the onset and termination of xylogenesis, testing the hypothesis that spring temperatures trigger the initiation of cambial activity. The onset of xylogenesis occurred from late May (DOY 149) to mid-June (DOY 163), and it terminated between late August (DOY 240) and late September (DOY 270). The spring phases of xylem phenology showed similar inter-annual variation among sites, while the variation in autumnal phases was less correlated among sites. The onset of xylogenesis was negatively correlated with the mean May temperature, and the correlations were consistent among sites, with r ranging from −0.61 to −0.77. The warmer May temperatures would advance cambial resumption, allowing the initial hypothesis that spring temperatures are a driving factor of xylogenesis to be accepted. With an increase of 1 °C in the mean May temperature, cambial resumption could be advanced by 2.7 days. Yet, no relationship between the termination of xylem phenology and monthly temperature was established, suggesting that other factors, possibly endogenous, could have affected the xylem phenology in autumn. Under warming conditions, we expect an advancement in the onset of xylogenesis, which may lengthen the growing season and potentially enhance cell production in black spruce. Full article

The visual inspection of fresh cut spruce wood (Picea abies, L. Karst.) showed the variability of its colour. Wood visual inspection is a part of wood quality assessment, for example, prior to or after its processing. The detail spruce wood colour analysis was performed using spectrophotometric data. The colour was measured by the bench-top spectrophotometer CM-5 Konica Minolta. The spectrophotometer was calibrated with a built-in white standard and on air. The whole analysis was performed in an xy chromaticity diagram supplemented with coordinate Y and CIE L*a*b* colour spaces. The ratio of the white chromophore amount to the amount of all achromatic chromophores is related to the Y coordinate. The ratio of the chromatic chromophore amount to all chromophores amount is saturation. The constructed model of the spruce wood colour is composed of four chromophores. The white chromophore belongs to holocellulose. The black chromophore belongs to lignin. The saturation is influenced by two chromophores. One of them belongs to extractives, another to lignin. The amounts of chromophores correlated with the spruce wood chemical composition. The chemical composition was measured using the procedures of Seifert, Wise, Sluiter, and ASTM. Moreover, the wood colour is affected by the moisture content. Full article

We have sequenced the chloroplast genome of red spruce (Picea rubens) for the first time using the single-end, short-reads (44 bp) Illumina sequences, assembled and functionally annotated it, and identified simple sequence repeats (SSRs). The contigs were assembled using SOAPdenovo2 following the retrieval of chloroplast genome sequences using the black spruce (Picea mariana) chloroplast genome as the reference. The assembled genome length was 122,115 bp (gaps included). Comparatively, the P. rubens chloroplast genome reported here may be considered a near-complete draft. Global genome alignment and phylogenetic analysis based on the whole chloroplast genome sequences of Picea rubens and 10 other Picea species revealed high sequence synteny and conservation among 11 Picea species and phylogenetic relationships consistent with their known classical interrelationships and published molecular phylogeny. The P. rubens chloroplast genome sequence showed the highest similarity with that of P. mariana and the lowest with that of P. sitchensis. We have annotated 107 genes including 69 protein-coding genes, 28 tRNAs, 4 rRNAs, few pseudogenes, identified 42 SSRs, and successfully designed primers for 26 SSRs. Mononucleotide A/T repeats were the most common followed by dinucleotide AT repeats. A similar pattern of microsatellite repeats occurrence was found in the chloroplast genomes of 11 Picea species. Full article

In boreal forests in Canada, broadleaf stands are characterized by generally well-drained soils and a humus-rich layer. In contrast, spruce-moss stands are often characterized by more poorly drained soils and acidic humus layer. However, presence of these two forest types in various degrees of mixture in stands can be beneficial to spruce seedlings productivity. It was hypothesized that leaf litter and humus from pure spruces-moss stands, pure broadleaf stands, and mixed stand may influence Black spruce (Picea mariana (Mill.) BSP) seedling growth and development differently. A greenhouse experiment was carried out to evaluate the effect of different leaf litter and different humus on spruces seedlings. Our results suggest better development for seedlings grown in humus from mixed stands and pure broadleaf stands compared to humus from pure B. spruce or standard forest nursery substrate. Furthermore, leaf litter from broadleaf trees species, such as species Speckle alder (Alnus rugosa (Du Roi) R.T. Clausen), T. aspen (Populus tremuloides Michx), Willows (Salix spp.) and Paper birch (Betula papyrifera Marsh.), has shown distinct results in the growth and development of B. spruce seedlings in greenhouse. Furthermore, promotion of mixed stand can increase B. spruce productivity by improving the physicochemical composition of the forest floor. Full article