European Journal of Forest Research最新文献

In commercial Pinus taeda stands, the appearance of needle chlorosis has intensified in slow growth areas. This study aimed to verify if Visible Atmospherically Resistant Index (VARI) captures heterogeneity of Pinus taeda development and to determine what specific factors are associated with occurrence of chlorotic symptoms. We evaluated a 14 year-old reforested P. taeda stand that had already undergone two thinnings; the study area encompassed 18.42 ha on soil derived from acidic igneous parent material. A VARI map was used to delineate the area into four classes: Very Low, Low, Medium, and High. In each class, tree growth was evaluated, and samples of tree tissue (needles, trunk cross sections, and fine roots), litter, and soil were collected for evaluation. There were no differences in soil classification and fertility between classes for this acidic low fertility soil. However, compared to the lower VARI classes (Low and Very Low), tree wood volume (without bark) of the High class was 0.20 m³ higher per tree. Higher VARI classes showed greater concentrations of Ca and Mg in needles, bark, and fine roots. The High class also showed higher concentrations of Ca and Mg in litter, but with less litter accumulation. Therefore, VARI efficiently captured tree growth heterogeneity with a direct relationship noted between VARI and tree growth (height, DBH, volume, and trunk mass). In addition, chlorosis symptoms (yellowing) at needle tips and tree crown loss were more likely indicative of Mg deficiency, which probably caused reduced tree development.

The relationship between tree radial growth and climate factors is intricate and affected by various factors related to global climate change. Chinese fir [Cunninghamia lanceolata (Lamb.) Hook.)] is a crucial fast-growing timber species in subtropical China. Its productivity, primarily determined by radial growth, has been influenced by climate change. Our study aimed to explore growth patterns and elucidate the correlation between radial growth and climate factors in Chinese fir plantations across four distinct climatic regions. Through correlation analysis and structural equation model (SEM), we explained the relationship between radial growth trends and climate factors. The results showed that monthly radial growth differed among the four production areas, with an “unimodal curve” in Fujian and Jiangxi, a “bimodal curve” in Hunan, and a “trimodal curve” in Yunnan. Radial growth was positively correlated with temperature and precipitation. The dryness index had a weak correlation with radial growth in Fujian and Jiangxi but a significant positive correlation in Hunan and Yunnan. SEM analyses indicated path coefficients for biological factors influencing radial growth (0.352 in Fujian, 0.616 in Jiangxi, 0.595 in Hunan, and 0.528 in Yunnan) and climate factors ( -0.003 in Fujian, 0.150 in Jiangxi, 0.265 in Hunan, and 0.005 in Yunnan). The factors affecting radial growth were the least in Fujian and the most in Yunnan, indicating greater climate sensitivity in the radial growth of Chinese fir from coastal to inland areas. These results enhance our understanding of climate impacts on forest productivity and offer a scientific basis for sustainably managing subtropical plantations under climate change.

Moso bamboo (Phyllostachys edulis), a non-timber plant resource in China, possesses significant ecological and economic value. However, human activities and climate change have degraded its natural habitat, posing a significant threat to its widespread distribution. To address this, we used species distribution models based on 115 occurrence data and 10 ecological variables to predict the potential suitable areas and spatial change trends of moso bamboo in present and future periods in China. We also analyzed areas with environmental anomalies and the drivers of its geographical variations under climate change. The results showed that the biomod2 ensemble model, consisting of eleven integrated models, exhibited significantly improved accuracy compared to single models. Key environmental factors limiting its distribution were mean diurnal temperature range (bio2), minimum temperature of the coldest month (bio6), precipitation seasonality (bio15), and elevation. Currently, the potential suitable habitat covers 152.74 × 10⁴ km², mainly from south of the Qinling-Huaihe River to north of the Tropic of Cancer. However, under future climate scenarios, these habitats will considerably shrink, especially in highly suitable areas. The moderately suitable habitat will fragment, and the low-suitability boundary will move northward. With the deepening impact of climate change, the entire distribution range will move towards higher latitudes. Hunan, Guizhou, Zhejiang, and western Jiangxi emerge as future climate refuges for moso bamboo, necessitating critical population protection. In summary, our research deepens our insight of how climate change drives the geographic distribution of moso bamboo and offers valuable theoretical support for its cultivation and conservation.

Wind energy has emerged as one of the most economically viable renewable energy options in the transition towards a fossil-free society. In Finland, wind farms, consisting of several wind turbines, are commonly located in forested areas, prompting concerns about their potential audio-visual impacts. Despite this, research into how forests might mitigate the adverse effects of wind farms are limited. Forests can effectively serve as noise barrier, with their noise attenuation capacity varying based on the forest’s characteristics. Specifically, the attenuation level depends on the sound’s travel distance through the forest, as well as the size and density of trees. Our study findings indicate that forests can provide up to 10 dB of additional noise attenuation. This was achieved by integrating a forest structure-based model into forest planning calculations, aimed at mitigating noise pollution from wind turbines. Incorporating this noise model as a management objective significantly reduced noise levels in the pilot study area, outperforming traditional business-as-usual management strategies. Furthermore, adapting a combination of uneven-aged and even-aged forest management approaches resulted in more forested landscape, which was more effective in mitigating higher noise levels. Our results contribute important insights that, along with further research, can guide future forest planning and management towards enhanced sustainability.

Scots pine is of greatest importance in northern Germany regarding its cultivation area and expected capability to perform in climate change. However, pine predominantly occurs in monocultures. Therefore, future pine forestry depends on an adaptation to climate change while improving ecological and economic forest functions. Yet future development of pine remains uncertain due to leeway in silvicultural guidelines and future climate. This study questions: (i) what is the range of future pine shares under climate change and different silvicultural management in northern Germany, (ii) how will the current stands develop and (iii) what is the range of uncertainty arising from climate models and silvicultural options? To answer these issues we (i) selected forest development types site- and climate-sensitively to either minimize or to maximize pine shares, (ii) simulated four, now practiced forest management scenarios for 50 years based on the German National Forest Inventory and (iii) analyzed the differences, to be interpreted as uncertainty. Novel to our approach is the site- and climate-sensitive selection of forest development types on large scales which emphasizes the contrasts of the different management guidelines. The results show that growing stock and cultivation area will decrease even if pine is promoted in forestry. The predicted restoration rate ranges from 50 to 72% depending on scenario and previous thinning regime. In conclusion, under the given management concepts and considering today’s high proportion of old pine, restoration is alarmingly slow. Amid the rapidly changing climate, we recommend to further adjust the management guidelines to accelerate forest restoration.

This study explores the nuanced influence of microclimatic conditions on beech stand acclimatization throughout the vegetational season. Three closely situated localities on a north-oriented slope within the National Park Fruška Gora (Serbia) were selected, each exhibiting minimal elevation differences but distinct microhabitat characteristics shaped by orographic and hydrological properties. The hypothesis posits that subtle habitat differentiations imprint distinctive physiological acclimatization patterns in beech stands. Using statistical tools like Multiple Factor Analyses (MFA), Standardized Major Axis (SMA), and Random Forest Analyses (RFA), the study identifies significant relationships among monitored parameters. The vegetational season, extracted from 15 years of NDVI data, reveals prolonged activity with earlier greening and delayed defoliation. MFA analyses highlight the high dependence of beech acclimatization on spatio-temporal properties, showcasing distinctive transitions between months within subpopulations. Reduced July precipitation significantly impacts photosynthetic intensity, transpiration, stomatal conductance, and water use efficiency. Higher localities, closer to the mountain ridge, exhibit heightened vulnerability to water deficit, evident in intense disturbance of photochemical efficiency. In contrast, the lower locality demonstrates tolerance to reduced rainfall, benefitting from additional soil water supply. The severity of drought stress, along with the intricate interplay of microhabitat environmental factors and plant physiological responses, appears to define the acclimatization strategy of beech plants and influence their recovery potential. These findings underscore the spatial microhabitat impact, particularly orographic properties, on beech acclimation to water deficit, with distinct temporal responses at each locality. Implications extend to modified forest management strategies within the National Park, especially in the context of climate change.

Gene flow affects the genetic diversity and structure of tree species and can be influenced by stress related to changing climatic conditions. The study of tree species planted in locations outside their natural range, such as arboreta or botanical gardens, allows us to analyse the effect of severe fragmentation on patterns and distances of gene flow. Paternity analysis based on microsatellite marker genotyping was used to analyse how fragmentation affects gene flow among individuals of Quercus rubra L. distributed in a small isolated group of trees (15 trees) planted in the arboretum on the North Campus of the University of Göttingen. For paternity analysis, 365 seedlings from four seed parents were selected and genotyped using 16 microsatellites. The analysis revealed the majority of pollen (84.89%) originated from trees within the site and identified three large full-sib families consisting of 145, 63 and 51 full-sibs. The average pollen dispersal distance for the four seed parents ranged from 17.3 to 103.6 meters. We observed substantial genetic differentiation among effective pollen clouds of the four seed parents (G’’_ST = 0.407) as a result of cross pollination between neighboring trees. No self-fertilization was observed. Gene dispersal via pollen followed the expected distance-dependent pattern, and we observed a significant influx of external pollen (15.11%, ranging from 8.64 to 26.26% for individual seed parents) from a diverse set of donors (30). Long-distance pollen dispersal could explain the presence of significant genetic variation even in isolated natural Q. rubra populations.

The efficiency of forest logging operations can be strongly affected by the layout of the harvesting pattern, which is usually based on silvicultural constraints and technical feasibility. Specifically, individual tree volume and the spatial distribution of trees significantly impact the overall harvesting performance. Spatial optimization of tree selection at the forest stand level may improve timber harvest efficiency by maximizing key performance indicators, such as the economic benefit, under given operational and silvicultural constraints. In this study, we applied two harvesting operation-optimization approaches based on integer programming for uphill cable yarding operations in mountain areas, including tree selection and load maximization. The first approach involves tree selection based on single tree harvest, while the second one performs tree selection based on tree clusters harvest per work cycle. As input elements a productivity model, derived by time-motion study with a Mounty MT50-2 and individual tree parameters extracted from high-resolution airborne laser scanning data, were prepared. Single tree information was further rated by financial value, and subsequently combined with the productivity model, allowing a detailed breakdown of operational costs. The results showed that optimizing the tree selection while respecting the allowable cut timber volume established in the harvesting plan can improve the efficiency of forest operations. The cluster approach was shown to be more efficient in terms of economic benefit compared to the actual selection, with an increase of 24.94%. However, the single tree approach resulted in a decrease of economic benefit compared to the actual selection, with a decrease of 22.85%.

Forests, essential components of ecosystems, are managed for sustainable timber production in forest plantations to meet the growing demand for wood products. The intricate balance between sustainable forest management and logging residue management practices is crucial for ecological integrity and economic viability. Logging residues, byproducts of timber harvesting, significantly influence carbon and nutrient cycling, soil structure, and overall ecosystem health. Recent technological advancements, particularly the use of drones integrated with artificial intelligence, enable the processing of large datasets, providing meaningful insights into logging residues and forest dynamics. This study aims to evaluate the quantification and distribution of logging residues in forest plantations, utilizing machine learning classification models fed with drone-based images. The classification was performed using a Random Forest model fed with spectral and terrain variables, whereas the volume estimations were derived from field measurements and from the drone classification. Overall the classification achieved solid results (Overall Accuracy of 0.89), and the volume estimation resulting in solid comparison with field estimation (ratio 0.72–1.98), but poor correlation (R² of 0.26 and 0.36). We concluded that the proposed methodology is suitable for classifying and assessing residues distribution over recently harvested areas, but further improvement of the volume estimation methodology is necessary to ensure comprehensive and precise assessment of residue distribution over recently harvested areas.

Understanding the growth efficiency of individual trees, or growth per unit of resource utilization, can inform silvicultural management strategies to maximize tree and stand growth. Stand structure—the size and spatial distributions of trees within the stand—strongly influences water, light, and nutrient availability, as well as the resource-use efficiency of each tree. Key silvicultural tools for stand management include manipulating tree density, size distribution, and arrangement by controlling natural regeneration, artificial seeding, planting seedlings, and/or subsequent thinning of established trees. We analyzed two sets of plots from even-aged stands of common coniferous species in central Spain, 106 pure Scots pine (Pinus sylvestris) and 92 pure Mediterranean pine (Pinus pinaster), to examine the dynamics of the dominance hypothesis, the relationship between stand structure and growth, and the relationship between structure and growth efficiency. Our main findings revealed a negative impact of size-class uniformity on stand growth in both Scots pine and Mediterranean pine, while the positive effect of tree size on growth efficiency was supported for Mediterranean pine stands but uncertain for Scots pine. At the operational level, our results highlight how thinning intensity is more important than the thinning method in Mediterranean pinewoods and how thinning can benefit the provision of multiple ecosystem services. We also recommend integrating dominance effects on growth into individual tree modelling.