Forest Ecosystems最新文献

Accurate estimations of biomass and its temporal dynamics are crucial for monitoring the carbon cycle in forest ecosystems and assessing forest carbon sequestration potentials. Recent studies have shown that integrating process-based models (PBMs) with remote sensing data can enhance simulations from stand to regional scales, significantly improving the ability to simulate forest growth and carbon stock dynamics. However, the utilization of PBMs for large-scale simulation of larch carbon storage distribution is still limited. In this study, we applied the parameterized 3-PG (Physiological Principles Predicting Growth) model across the Mengjiagang Forest Farm (MFF) to make broad-scale predictions of the biomass and carbon stocks of Larix olgensis plantation. The model was used to simulate average diameter at breast height (DBH) and total biomass, which were later validated with a wide range of observation data including sample plot data, forest management inventory data, and airborne laser scanning data. The results showed that the 3-PG model had relatively high accuracy for predicting both DBH and total biomass at stand and regional scale, with determination coefficients ranging from 0.78 to 0.88. Based on the estimation of total biomass, we successfully produced a carbon stock map of the Larix olgensis plantation in MFF with a spatial resolution of 20 ​m, which helps with relevant management advice. These findings indicate that the integration of 3-PG model and remote sensing data can well predict the biomass and carbon stock at regional and even larger scales. In addition, this integration facilitates the evaluation of forest carbon sequestration capacity and the development of forest management plans.

Prunus serotina and Robinia pseudoacacia are the most widespread invasive trees in Central Europe. In addition, according to climate models, decreased growth of many economically and ecologically important native trees will likely be observed in the future. We aimed to assess the impact of these two neophytes, which differ in the biomass range and nitrogen-fixing abilities observed in Central European conditions, on the relative aboveground biomass increments of native oaks Quercus robur and Q. petraea and Scots pine Pinus sylvestris. We aimed to increase our understanding of the relationship between facilitation and competition between woody alien species and overstory native trees. We established 72 circular plots (0.05 ​ha) in two different forest habitat types and stands varying in age in western Poland. We chose plots with different abundances of the studied neophytes to determine how effects scaled along the quantitative invasion gradient. Furthermore, we collected growth cores of the studied native species, and we calculated aboveground biomass increments at the tree and stand levels. Then, we used generalized linear mixed-effects models to assess the impact of invasive species abundances on relative aboveground biomass increments of native tree species. We did not find a biologically or statistically significant impact of invasive R. pseudoacacia or P. serotina on the relative aboveground biomass increments of native oaks and pines along the quantitative gradient of invader biomass or on the proportion of total stand biomass accounted for by invaders. The neophytes did not act as native tree growth stimulators but also did not compete with them for resources, which would escalate the negative impact of climate change on pines and oaks. The neophytes should not significantly modify the carbon sequestration capacity of the native species. Our work combines elements of the per capita effect of invasion with research on mixed forest management.

Excessive forest exploitation significantly contributes to land degradation and the creation of human-made deadwood. Stumps are sometimes ignored in studies on the biodiversity of coarse woody debris. We investigated whether the type of stump, i.e. broken stumps (naturally created) and cut stumps (formed during forestry operations) had an impact on the species composition and species diversity as well as due to this fact they can be characterized by plant indicators. The research covered 728 spruce stumps (287 broken and 441 cut stumps) that were inhabited by lichens, liverworts, mosses and vascular plants in mountain forest belt (Karkonosze Mts., Poland). The following types of microhabitats were included in the research: the upper surface and the lateral surface of a stump with both bark and wood. There are statistically significant compositional differences between the two types of stumps, which was demonstrated by ordination analyses and indicator species analysis. According to the generalized linear models, the probability of occurrence increases in cut stumps in case of liverworts and vascular plants and also along the decomposition stages. The generalized linear mixed-effects model showed that there was a higher species richness of liverworts, mosses and vascular plants on the cut stumps and less drier but the reverse situation was in lichens. The generalized additive models for their cover showed similar trends. Almost all of the taxonomic groups were affected by altitude both in terms of species composition and total cover on the stumps. We concluded that cut stumps are an important type of deadwood for biodiversity and provide a convenient habitat, especially for many lichens and bryophytes.

Spruce-dominated forests are commonly exposed to disturbances associated with mass occurrences of bark beetles. The dieback of trees triggers many physical and chemical processes in the ecosystem resulting in rapid changes in the vegetation of the lower forest layers. We aimed to determine the response of non-tree understory vegetation to the mass dieback of Norway spruce (Picea abies) in the first years after the disturbance caused by the European spruce bark beetle (Ips typographus) outbreak. Our study area was the Białowieża Biosphere Reserve covering the Polish part of the emblematic Białowieża Forest, in total 597 ​km². The main data source comprised 3,900 phytosociological relevés (combined spring and summer campaigns) collected from 1,300 systematically distributed forest sites in 2016–2018 – the peak years of the bark beetle outbreak. We found that the understory responded immediately to mass spruce dieback, with the most pronounced changes observed in the year of the disturbance and the subsequent year. Shade-tolerant forest species declined in the initial years following the mass spruce dieback, while hemicryptophytes, therophytes, light-demanding species associated with non-forest semi-natural communities, as well as water-demanding forest species, expanded. Oxalis acetosella, the most common understory species in the Białowieża Forest, showed a distinct fluctuation pattern, with strong short-term expansion right after spruce dieback, followed by a gradual decline over the next 3–4 years to a cover level 5 percentage points lower than before the disturbance. Thus, our study revealed that mass spruce dieback selectively affects individual herb species, and their responses can be directional and non-directional (fluctuation). Furthermore, we demonstrated that the mass dieback of spruce temporarily increases plant species diversity (α-diversity).

Background

Understanding the role of species identity in interactions among individuals is crucial for assessing the productivity and stability of mixed forests over time. However, there is limited knowledge concerning the variation in competitive effect and response of different species along climatic gradients. In this study, we investigated the importance of climate, tree size, and competition on the growth of three tree species: spruce (Picea abies), fir (Abies alba), and beech (Fagus sylvatica), and examined their competitive response and effect along a climatic gradient.

Methods

We selected 39 plots distributed across the European mountains with records of the position and growth of 5,759 individuals. For each target species, models relating tree growth to tree size, climate and competition were proposed. Competition was modelled using a neighbourhood competition index that considered the effects of inter- and intraspecific competition on target trees. Competitive responses and effects were related to climate. Likelihood methods and information theory were used to select the best model.

Results

Our findings revealed that competition had a greater impact on target species growth than tree size or climate. Climate did influence the competitive effects of neighbouring species, but it did not affect the target species' response to competition. The strength of competitive effects varied along the gradient, contingent on the identity of the interacting species. When the target species exhibited an intermediate competitive effect relative to neighbouring species, both higher inter- than intraspecific competitive effects and competition reduction occurred along the gradient. Notably, species competitive effects were most pronounced when the target species’ growth was at its peak and weakest when growing conditions were far from their maximum.

Conclusions

Climate modulates the effects of competition from neighbouring trees on the target tree and not the susceptibility of the target tree to competition. The modelling approach should be useful in future research to expand our knowledge of how competition modulates forest communities across environmental gradients.

Mapping individual tree quality parameters from high-density LiDAR point clouds is an important step towards improved forest inventories. We present a novel machine learning-based workflow that uses individual tree point clouds from drone laser scanning to predict wood quality indicators in standing trees. Unlike object reconstruction methods, our approach is based on simple metrics computed on vertical slices that summarize information on point distances, angles, and geometric attributes of the space between and around the points. Our models use these slice metrics as predictors and achieve high accuracy for predicting the diameter of the largest branch per log (DLBs) and stem diameter at different heights (DS) from survey-grade drone laser scans. We show that our models are also robust and accurate when tested on suboptimal versions of the data generated by reductions in the number of points or emulations of suboptimal single-tree segmentation scenarios. Our approach provides a simple, clear, and scalable solution that can be adapted to different situations both for research and more operational mapping.

Increased nitrogen (N) input can potentially lead to secondary phosphorus (P) limitation; however, it remains unclear whether differences in the plant's ability to cope with this P deficiency are related to their growth responses. Using a long-term experiment of N addition in a boreal forest, we explored the potential role of plant nutrient resorption efficiency and its stoichiometry in mediating plant growth responses to increased N input. We recorded the cover and measured the concentration and resorption efficiency of leaf N and P as well as the photosynthesis of a grass Deyeuxia angustifolia and a shrub Vaccinium vitis-idaea. The cover of the grass D. angustifolia increased with increasing N addition, while that of the shrub V. vitis-idaea decreased with N addition rate and almost disappeared from the high-level N addition over time. P resorption efficiency (PRE) increased in D. angustifolia but decreased in V. vitis-idaea with increasing leaf N:P which was increased by N addition for both species. In addition, photosynthesis increased linearly with N resorption efficiency (NRE) and PRE but was better explained by NRE:PRE, changing nonlinearly with the ratio in a hump-shaped trend. Furthermore, the variance (CV) of NRE:PRE for V. vitis-idaea (123%) was considerably higher than that for D. angustifolia (29%), indicating a more stable nutrient resorption stoichiometry of the grass. Taken together, these results highlight that efficient P acquisition and use strategy through nutrient resorption processes could be a pivotal underlying mechanism driving plant growth and community composition shifts under N enrichment.

Forests worldwide are experiencing increasingly intense biotic disturbances; however, assessing impacts of these disturbances is challenging due to the diverse range of organisms involved and the complex interactions among them. This particularly applies to invasive species, which can greatly alter ecological processes in their invaded territories. Here we focus on the pine wood nematode (PWN, Bursaphelenchus xylophilus), an invasive pathogen that has caused extensive mortality of pines in East Asia and more recently has invaded southern Europe. It is expected to expand its range into continental Europe with heavy impacts possible.

Given the unknown dynamics of PWN in continental Europe, we reviewed laboratory and field experiments conducted in Asia and southern Europe to parameterize the main components of PWN biology and host-pathogen interactions in the Biotic Disturbance Engine (BITE), a model designed to implement a variety of forest biotic agents, from fungi to large herbivores. To simulate dynamically changing host availability and conditions, BITE was coupled with the forest landscape model iLand. The potential impacts of introducing PWN were assessed in a Central European forest landscape (40,928 ​ha), likely within PWN’s reach in future decades.

A parameter sensitivity analysis indicated a substantial influence of factors related to dispersal, colonization, and vegetation impact, whereas parameters related to population growth manifested a minor effect. Selection of different assumptions about biological processes resulted in differential timing and size of the main mortality wave, eliminating 40%–95% of pine trees within 100 years post-introduction, with a maximum annual carbon loss between 1.3% and 4.2%. PWN-induced tree mortality reduced the Gross Primary Productivity, increased heterotrophic respiration, and generated a distinct legacy sink effect in the recovery period. This assessment has corroborated the ecological plausibility of the simulated dynamics and highlighted the need for new strategies to navigate the substantial uncertainty in the agent’s biology and population dynamics.

Tree allometry plays a crucial role in tree survival, stability, and timber quantity and quality of mixed-species plantations. However, the responses of tree allometry to resource utilisation within the framework of interspecific competition and complementarity remain poorly understood. Taking into consideration strong- and weak-space competition (SC and WC), as well as N₂-fixing and non-N₂-fixing tree species (FN and nFN), a mixed-species planting trial was conducted for Betula alnoides, a pioneer tree species, which was separately mixed with Acacia melanoxylon (SC ​+ ​FN), Erythrophleum fordii (WC ​+ ​FN), Eucalyptus cloeziana (SC ​+ ​nFN) and Pinus kesiya var. langbianensis (WC ​+ ​nFN) in southern China. Six years after planting, tree growth, total nitrogen (N) and carbon (C) contents, and the natural abundances of ¹⁵N and ¹³C in the leaves were measured for each species, and the mycorrhizal colonisation rates of B. alnoides were investigated under each treatment. Allometric variations and their relationships with space competition and nutrient-related factors were analyzed. The results showed a consistent effect of space competition on the height-diameter relationship of B. alnoides in mixtures with FN or nFN. The tree height growth of B. alnoides was significantly promoted under high space competition, and growth in diameter at breast height (DBH), tree height and crown size were all expedited in mixtures with FN. The symbiotic relationship between ectomycorrhizal fungi and B. alnoides was significantly influenced by both space competition and N₂ fixation by the accompanying tree species, whereas such significant effects were absent for arbuscular mycorrhizal fungi. Furthermore, high space competition significantly decreased the water use efficiency (WUE) of B. alnoides, and its N use efficiency (NUE) was much lower in the FN mixtures. Structural equation modeling further demonstrated that the stem allometry of B. alnoides was affected by its NUE and WUE via changes in its height growth, and crown allometry was influenced by the mycorrhizal symbiotic relationship. Our findings provide new insights into the mechanisms driving tree allometric responses to above- and below-ground resource competition and complementarity in mixed-species plantations, which are instructive for the establishment of mixed-species plantations.

Climate change and forest management are recognized as pivotal factors influencing forest ecosystem services and thus multifunctionality. However, the magnitude and the relative importance of climate change and forest management effects on the multifunctionality remain unclear, especially for natural mixed forests. In this study, our objective is to address this gap by utilizing simulations of climate-sensitive transition matrix growth models based on national forest inventory plot data. We evaluated the effects of seven management scenarios (combinations of various cutting methods and intensities) on the future provision of ecosystem services and multifunctionality in mixed conifer-broad-leaved forests in northeastern China, under four climate scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5, and constant climate). Provisioning, regulating, cultural, and supporting services were described by timber production, carbon storage, carbon sequestration, tree species diversity, deadwood volume, and the number of large living trees. Our findings indicated that timber production was significantly influenced by management scenarios, while tree species diversity, deadwood volume, and large living trees were impacted by both climate and management separately. Carbon storage and sequestration were notably influenced by both management and the interaction of climate and management. These findings emphasized the profound impact of forest management on ecosystem services, outweighing that of climate scenarios alone. We found no single management scenario maximized all six ecosystem service indicators. The upper story thinning by 5% intensity with 5-year interval (UST5) management strategy emerged with the highest multifunctionality, surpassing the lowest values by more than 20% across all climate scenarios. In conclusion, our results underlined the potential of climate-sensitive transition matrix growth models as a decision support tool and provided recommendations for long-term strategies for multifunctional forest management under future climate change context. Ecosystem services and multifunctionality of forests could be enhanced by implementing appropriate management measures amidst a changing climate.