Strong Temporal Dynamics Research Articles

Bidirectional and dynamic relationships between social isolation and frailty among older adults in China

ObjectiveThis study aimed to investigate the bidirectional and dynamic relationships between Social Isolation (SI) and frailty among older adults in China. MethodsUsing data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), this study utilized a Generalized Cross-Lagged Model (GCLM) to examine the temporal interrelationships between SI and frailty among individuals aged 65 years and older. ResultsThe findings revealed significant bidirectional associations between SI and frailty among older adults in China. The GCLM identified strong temporal dynamics in the relationships between SI and frailty, with both effects increasing and showing a "cumulative disadvantage" effect as older adults aged. ConclusionThis study underscores the significance of tailored interventions aimed at mitigating both SI and frailty among older adults in China, thus addressing the bidirectional impact. The findings emphasize the necessity for early intervention strategies to counteract the cumulative disadvantages associated with SI and frailty in later-life outcomes.

Stable Neural Population Dynamics in the Regression Subspace for Continuous and Categorical Task Parameters in Monkeys.

Neural population dynamics provide a key computational framework for understanding information processing in the sensory, cognitive, and motor functions of the brain. They systematically depict complex neural population activity, dominated by strong temporal dynamics as trajectory geometry in a low-dimensional neural space. However, neural population dynamics are poorly related to the conventional analytical framework of single-neuron activity, the rate-coding regime that analyzes firing rate modulations using task parameters. To link the rate-coding and dynamic models, we developed a variant of state-space analysis in the regression subspace, which describes the temporal structures of neural modulations using continuous and categorical task parameters. In macaque monkeys, using two neural population datasets containing either of two standard task parameters, continuous and categorical, we revealed that neural modulation structures are reliably captured by these task parameters in the regression subspace as trajectory geometry in a lower dimension. Furthermore, we combined the classical optimal-stimulus response analysis (usually used in rate-coding analysis) with the dynamic model and found that the most prominent modulation dynamics in the lower dimension were derived from these optimal responses. Using those analyses, we successfully extracted geometries for both task parameters that formed a straight geometry, suggesting that their functional relevance is characterized as a unidimensional feature in their neural modulation dynamics. Collectively, our approach bridges neural modulation in the rate-coding model and the dynamic system, and provides researchers with a significant advantage in exploring the temporal structure of neural modulations for pre-existing datasets.

Can aeration improve bamboo soil fertility of soil below bamboo and fungal diversity under mulching conditions?

AbstractAeration can alleviate soil hypoxia stress of Phyllostachys praecox bamboo under mulching conditions, but how aeration affects soil properties, soil fungal community structure, and bamboo development is unclear. We studied the responses of soil properties, fungal community structure, bamboo shoots, and rhizome growth to organic mulching (TM), mulching with aeration (TA1 and TA2), and no‐mulching treatments (CK) from a field experiment in March and July, 2019. During the mulching period (March), the aeration improvement treatment (TA2) improved soil O2 content, bamboo shoots yield, and soil nutrient availability significantly when compared with TM. TA2 treatment showed significantly higher relative abundances of the genus Trichoderma and functional group endophyte than TM treatment, which might be conducive to soil nutrient transformation and bamboo growth. The TA2 treatment had higher fungal diversity indices than that of the TA1 treatment, suggesting that optimal aeration conditions enhance soil fungal diversity. The fungal community structure also showed strong temporal dynamics in all treatments. Mantel test results indicated soil O2 is the primary factor driving fungal community structure under mulching conditions, while has no impact on the fungal community in summer; fungal community structure was primarily controlled by soil pH in summer. Structural equation model revealed soil NO3−‐N content was responsible directly for bamboo rhizome growth and shoot yield. Our results indicate short‐term mulching is beneficial to soil nutrients improvement and bamboo yield increase, while rational aeration can further facilitate sustainable plantation development under hypoxic soil conditions.

Speech Enhancement With Phase Sensitive Mask Estimation Using a Novel Hybrid Neural Network

A natural choice to model strong temporal dynamics of speech is the recurrent neural network (RNN) since it can exploit the sequential information from consecutive acoustic frames and generalizes the model well to unseen speakers. Besides, the convolutional neural network (CNN) can automatically extract sophisticated speech features that can maximize the performance of a model. In this paper, we propose a hybrid neural network model integrating a new low-complexity fully-convolutional CNN and a long short-term memory (LSTM) network, a variation of RNN, to estimate a phase-sensitive mask for speech enhancement. The model is designed to take full advantages of the temporal dependencies and spectral correlations present in the input speech signal while keeping the model complexity low. Also, an attention technique is embedded to recalibrate the useful CNN-extracted features adaptively. Furthermore, a grouping strategy is employed to reduce the LSTM complexity while keeping the performance almost unchanged. Through extensive comparative experiments, we show that the proposed model significantly outperforms some known neural network-based speech enhancement methods in the presence of highly non-stationary noises, while it exhibits a relatively small number of model parameters compared to some commonly employed DNN-based methods.

Spatial modelling of temporal dynamics in stream fish communities under anthropogenic change

AbstractAimUnderstanding temporal changes in aquatic communities is essential to address the freshwater biodiversity crisis. In particular, it is important to understand the patterns and drivers of spatial variation in local community dynamics, generalizing temporal trends from discrete locations to entire landscapes that are the main focus of management. Here, we present a framework for producing spatially continuous views of community dynamics, focusing on stream fish affected by hydropower development.LocationRiver Sabor, NE Portugal.MethodsWe sampled stream fish at thirty sites between 2012 and 2019. Community trajectory analysis was used to quantify the directionality and velocity of community change, and the geometric resemblance of community trajectories between sites. Geostatistical models for stream networks were used to relate metrics describing community dynamics to environmental variables, while controlling for Euclidean and hydrologic spatial dependencies, and to map spatial variation in community dynamics across the watershed.ResultsTrajectories in multivariate space underlined strong temporal dynamics, with local communities deviating and returning to previous states, but without evidence for directional changes. Accordingly, directionality values were low and not consistently affected by environmental variables. The velocity of community change varied markedly across the watershed and it was strongly affected by stream order and elevation, with faster changes observed in lowland streams draining into hydroelectric reservoirs and with a high proportion of exotic species. Pairwise distances between community trajectories were strongly related to hydrologic and environmental distances between sites.Main conclusionsLocal stream fish communities were in a loose equilibrium across the watershed, but they fluctuated at a faster rate closer to a hydroelectric reservoir. Integrating community trajectory analysis and geostatistical modelling provides a relatively simple framework to understand how, where and why temporal community dynamics vary across dendritic stream networks and to visualize spatial patterns of community change over time in relation to anthropogenic impacts.

Small biodiversity effects on leaf litter production of a seasonal heath vegetation

AbstractAimsWe evaluated the relative importance that biodiversity factors, abiotic conditions, and vegetation structure have on monthly leaf litter production. We tested if biodiversity drives leaf litter production through the increase in species richness or community‐weighted mean traits regardless of the influence of other biodiversity factors that reflect species niche differentiation, such as phylogenetic and functional diversities. We also tested if precipitation imposes greater influence on the production than any asynchronous effects between species that result from temporal niche partitioning.LocationSeasonal heath vegetation that covers white‐sand coastal areas in northeastern Brazil.MethodsWe conducted an observational study across 41 25‐m2permanent plots to sample leaf litter production of the vegetation during 18 months from January 2016 to June 2017 at monthly intervals. We used structural equation modeling in combination with linear mixed models to test the above‐mentioned hypotheses.ResultsOur study encompassed 22 focal species. Species richness was the only biodiversity factor to influence leaf litter production, although its effect was weak, suggesting that the chance of including high‐yielding species by increasing richness enhances the production regardless of the degree of species niche complementarity through functional and phylogenetical dissimilarities. We also observed a major control of precipitation on leaf litter production, as well as a lack of interaction between species richness and its temporal dynamic of production, demonstrating the key role of climate‐mediated controls.ConclusionWe believe that plant diversity loses importance for ecosystem functioning in ecological contexts where the entire community responds similarly to abiotic pressures, particularly if the ecosystem process is marked by strong temporal dynamics. Our study provided empirical support for this line of reasoning since the seasonal heath vegetation responded mostly to rainfall seasonality.

Achievement of the ITER NBI ion source parameters for hydrogen at the test facility ELISE and present Status for deuterium

The ELISE test facility, being in operation since 2013, with its half-size ITER ion source accompanies the ITER NBI development program. Besides consolidation of the ion source design, solving technical problems that arise during operation, gaining early experience in ion source operation and maintenance, ELISE has the task to demonstrate the required ion source parameters required by ITER. ELISE made remarkable progress since then, starting from short pulses (10 s) to the ITER target of 1000 s for Hˉ and 3600 s for Dˉ (with the constraint to extract the beam repetitively for 10 s every ≈150 s). For hydrogen, above 90 % of the required level for the extracted current density has been achieved being limited by the available high voltage power supply and the RF power. For deuterium the performance is limited by the much larger amount of co-extracted electrons; here 65% of the extracted current density is demonstrated for the duration of almost one hour. One of the challenges is the strong temporal dynamics of the co-extracted electrons and several measures were taken as the introduction of potential rods, modifications of the magnetic filter field configuration and improved caesium conditioning. Testing the magnetic field configuration planned for the test facility MITICA (prototype of the ITER beamline) showed very good performance but indicated also that the field strength should be kept variable to control ions and electrons for the two isotopes individually. Regarding the beam homogeneity the global uniformity of better than 90 % is usually achieved. Measurements of the beam divergence by beam emission spectroscopy revealed higher divergences for the horizontal lines-of-sight than for the vertical ones due to the non-compensated zig-zag deflection of the beamlets by the magnets in the extraction grid.

Identifying temporal properties of building components and indoor environment for building performance assessment

Buildings are dynamic thermal systems that require energy to maintain a comfortable indoor environment. Knowing these dynamics allows for identifying relevant building characteristics for assessing building energy performance. However, conventional building simulation programs take daily or monthly mean values for performance assessment. These often aggregate the errors and uncertainties between the theoretical and the actual building performance while missing the temporal dynamics on a minute or hourly basis. The objective of this study is to uncover the temporal aspects of building properties using data obtained by a wireless sensor network (WSN).Our analysis focuses on the following seven variables that are relevant for assessing building performance and retrofit measures: indoor air temperature, window opening instances, CO2 concentration, supply temperature from the heating system, outdoor air temperature, heat flux through the wall and the window. Using a single-family residence as a case study, we identify the temporal dynamics of these variables using polar plots on a high-resolution, 5-minute interval dataset. Following this, we define a set of conditional rules to study ‘expected’ and ‘unexpected’ impact of the six variables on the indoor air temperature. We observe strong temporal dynamics for certain building components, resulting in a large time lag. The conditional rule analysis also allows identifying energy saving potentials and factors contributing to the performance gap. For example, we observe high indoor air temperatures and at times when no occupants are present. Finally, we discuss the benefits of this approach with respect to building retrofit and energy performance gap analysis.

Environmental factors and river network position allow prediction of benthic community assemblies: A model of nematode metacommunities

The field of metacommunity studies is growing rapidly, including recent applications to river networks. Most of these studies have targeted a single river network but whether their findings are relevant to other river systems is unknown. This study investigated the influence of environmental, spatial and temporal parameters on the community structure of nematodes in the river networks of the Elbe and Rhine. We asked whether the variance in community structure was better explained by spatial variables representing the watercourse than by overland distances. After determining the patterns in the Elbe river network, we tested whether they also explained the Rhine data. The Elbe data were evaluated using a boosted regression tree analysis. The predictive ability of the model was then assessed using the Rhine data. In addition to strong temporal dynamics, environmental factors were more important than spatial factors in structuring riverine nematode communities. Community structure was more strongly influenced by watercourse than by Euclidean distances. Application of the model’s predictions to the Rhine data correlated significantly with field observations. Our model shows that the consequences of changes in environmental factors or habitat connectivity for aquatic communities across different river networks are quantifiable.

Decarbonising Rotterdam?

Low carbon transitions of urban energy systems have been on urban research and policy agendas for several years now. While the spatialities of infrastructure transitions have been widely discussed, their temporalities have attracted much less attention. This is surprising, since the transition of urban infrastructures in the course of system integration and decarbonisation reveal strong temporal dynamics: new temporalities or temporal requirements not only emerge as a result of technological change (e.g. by integrating fluctuating renewables or storage technologies) but also of changing social practices (e.g. in urban load management or energy use). We argue that aligning urban and infrastructure temporalities involves negotiations between the various energy providers, regulators and users involved and is a highly political process. As we know little about such temporal dynamics so far, this study uses an explorative methodology to elaborate on a conceptual framework of urban and infrastructural temporalities. This framework has been developed in an iterative way by going back and forth between conceptual contributions and empirical findings drawn from expert interviews regarding low carbon transitions in Rotterdam. Our case study of Rotterdam indicates that unsolved challenges in aligning urban and infrastructural temporalities can be seen as a major restriction to realise low carbon energy solutions.

Strong temporal dynamics of QTL action on plant growth progression revealed through high-throughput phenotyping in canola.

SummaryA major challenge of plant biology is to unravel the genetic basis of complex traits. We took advantage of recent technical advances in high‐throughput phenotyping in conjunction with genome‐wide association studies to elucidate genotype–phenotype relationships at high temporal resolution. A diverse Brassica napus population from a commercial breeding programme was analysed by automated non‐invasive phenotyping. Time‐resolved data for early growth‐related traits, including estimated biovolume, projected leaf area, early plant height and colour uniformity, were established and complemented by fresh and dry weight biomass. Genome‐wide SNP array data provided the framework for genome‐wide association analyses. Using time point data and relative growth rates, multiple robust main effect marker–trait associations for biomass and related traits were detected. Candidate genes involved in meristem development, cell wall modification and transcriptional regulation were detected. Our results demonstrate that early plant growth is a highly complex trait governed by several medium and many small effect loci, most of which act only during short phases. These observations highlight the importance of taking the temporal patterns of QTL/allele actions into account and emphasize the need for detailed time‐resolved analyses to effectively unravel the complex and stage‐specific contributions of genes affecting growth processes that operate at different developmental phases.

Transcriptome and Proteome Profiling of Neural Induced Pluripotent Stem Cells from Individuals with Down Syndrome Disclose Dynamic Dysregulations of Key Pathways and Cellular Functions

Down syndrome (DS) or trisomy 21 (T21) is a leading genetic cause of intellectual disability. To gain insights into dynamics of molecular perturbations during neurogenesis in DS, we established a model using induced pluripotent stem cells (iPSC) with transcriptome profiles comparable to that of normal fetal brain development. When applied on iPSCs with T21, transcriptome and proteome signatures at two stages of differentiation revealed strong temporal dynamics of dysregulated genes, proteins and pathways belonging to 11 major functional clusters. DNA replication, synaptic maturation and neuroactive clusters were disturbed at the early differentiation time point accompanied by a skewed transition from the neural progenitor cell stage and reduced cellular growth. With differentiation, growth factor and extracellular matrix, oxidative phosphorylation and glycolysis emerged as major perturbed clusters. Furthermore, we identified a marked dysregulation of a set of genes encoded by chromosome 21 including an early upregulation of the hub gene APP, supporting its role for disturbed neurogenesis, and the transcription factors OLIG1, OLIG2 and RUNX1, consistent with deficient myelination and neuronal differentiation. Taken together, our findings highlight novel sequential and differentiation-dependent dynamics of disturbed functions, pathways and elements in T21 neurogenesis, providing further insights into developmental abnormalities of the DS brain.

Inter-annual dynamics and persistence of small mammal communities in a selectively logged tropical forest in Borneo

Understanding temporal change and long-term persistence of species and communities is vital if we are to accurately assess the relative values of human-modified habitats for biodiversity. Despite a large literature and emerging consensus demonstrating a high conservation value of selectively logged tropical rainforests, few studies have taken a long-term perspective. We resampled small mammals (≤ 1 kg) in a heavily logged landscape in Sabah, Borneo between 2011 and 2016 to investigate temporal patterns of species-level changes in population density. We found that small mammal population density in heavily logged forest was highly variable among years, consistent with patterns previously observed in unlogged forest, and uncovered evidence suggesting that one species is potentially declining towards local extinction. Across nine species, population densities varied almost sevenfold during our 6-year study period, highlighting the extremely dynamic nature of small mammal communities in this ecosystem. Strictly terrestrial murid species tended to exhibit strong temporal dynamics, whereas semi-arboreal foraging species such as treeshrews had more stable dynamics. We found no relationships between population density and fruit/seed mass, and therefore no evidence that our patterns represent responses to inter-annual mast fruiting of the dominant canopy dipterocarp trees. This may be due to the removal of most of the canopy during logging, and hence the dipterocarp seed resource, although it possibly also reflects spatiotemporal limitations of our data. Our results underline the importance of understanding long-term variability in animal communities before developing conservation and management recommendations for human-altered ecosystems.

Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex

Working memory (WM) is a cognitive function for temporary maintenance and manipulation of information, which requires conversion of stimulus-driven signals into internal representations that are maintained across seconds-long mnemonic delays. Within primate prefrontal cortex (PFC), a critical node of the brain's WM network, neurons show stimulus-selective persistent activity during WM, but many of them exhibit strong temporal dynamics and heterogeneity, raising the questions of whether, and how, neuronal populations in PFC maintain stable mnemonic representations of stimuli during WM. Here we show that despite complex and heterogeneous temporal dynamics in single-neuron activity, PFC activity is endowed with a population-level coding of the mnemonic stimulus that is stable and robust throughout WM maintenance. We applied population-level analyses to hundreds of recorded single neurons from lateral PFC of monkeys performing two seminal tasks that demand parametric WM: oculomotor delayed response and vibrotactile delayed discrimination. We found that the high-dimensional state space of PFC population activity contains a low-dimensional subspace in which stimulus representations are stable across time during the cue and delay epochs, enabling robust and generalizable decoding compared with time-optimized subspaces. To explore potential mechanisms, we applied these same population-level analyses to theoretical neural circuit models of WM activity. Three previously proposed models failed to capture the key population-level features observed empirically. We propose network connectivity properties, implemented in a linear network model, which can underlie these features. This work uncovers stable population-level WM representations in PFC, despite strong temporal neural dynamics, thereby providing insights into neural circuit mechanisms supporting WM.

Soil Nitrogen Five Years after Bark Beetle Infestation in Lodgepole Pine Forests

The unprecedented scale of recent mountain pine beetle (Dendroctonus ponderosae, MPB) infestation in lodgepole pine (Pinus contorta ex Loudon var. latifolia Engelm. ex S. Watson) forests of western North America may significantly impact the role of forest soils as important sinks for global C and N. The aim of this study was to explain soil and litter N responses in stands experiencing total mortality during the first 5 yr of MPB outbreak. Four-year monitoring (2009–2012) of needlefall deposition, soil water-filled pore space (WFPS), NH₄, NO₃, potentially mineralizable N (PMN), dissolved organic N (DON), N₂O, and CH₄ was established in Medicine Bow National Forest in stands of different infestation histories (infested in 2007, 2008, and uninfested). Results suggest that total stand mortality demonstrated strong temporal dynamics. First-year soil responses included increases in PMN and were followed by WFPS and NH₄ increases in the second year, NO₃ increase in the third year, and DON increase in in the fourth year of the infestation. Litter NH₄ increased within 1 yr, but litter PMN, NO₃, and DON increased 3 yr after the infestation, suggesting enhanced litter decomposability. Soil N₂O and CH₄ fluxes also started to increase 4 yr after the infestation. These changes were indicative of ongoing disequilibrium for the period of at least 5 yr after MPB infestation. The magnitude of N mineralization and N₂O and CH₄ fluxes may continue to increase beyond the initial 5 yr of monitoring because litter-derived labile N will probably contribute to the second pulse of N mineralization.

Revisiting caching in content delivery networks

Content Delivery Networks (CDNs) differ from other caching systems in terms of both workload characteristics and performance metrics. However, there has been little prior work on large-scale measurement and characterization of content requests and caching performance in CDNs. For workload characteristics, CDNs deal with extremely large content volume, high content diversity, and strong temporal dynamics. For performance metrics, other than hit ratio, CDNs also need to minimize the disk operations and the volume of traffic from origin servers. In this paper, we conduct a large-scale measurement study to characterize the content request patterns using real-world data from a commercial CDN provider.

Strong, Long-Term Temporal Dynamics of an Ecological Network

Nature is organized into complex, dynamical networks of species and their interactions, which may influence diversity and stability. However, network research is, generally, short-term and depict ecological networks as static structures only, devoid of any dynamics. This hampers our understanding of how nature responds to larger disturbances such as changes in climate. In order to remedy this we studied the long-term (12-yrs) dynamics of a flower-visitation network, consisting of flower-visiting butterflies and their nectar plants. Global network properties, i.e. numbers of species and links, as well as connectance, were temporally stable, whereas most species and links showed a strong temporal dynamics. However, species of butterflies and plants varied bimodally in their temporal persistance: Sporadic species, being present only 1–2(-5) years, and stable species, being present (9-)11–12 years, dominated the networks. Temporal persistence and linkage level of species, i.e. number of links to other species, made up two groups of species: Specialists with a highly variable temporal persistence, and temporally stable species with a highly variable linkage level. Turnover of links of specialists was driven by species turnover, whereas turnover of links among generalists took place through rewiring, i.e. by reshuffling existing interactions. However, in spite of this strong internal dynamics of species and links the network appeared overall stable. If this global stability-local instability phenomenon is general, it is a most astonishing feature of ecological networks.

Linné’s floral clock is slow without pollinators – flower closure and plant‐pollinator interaction webs

Temporal patterns of flower opening and closure within a day are known as Linné's floral clock. Time of flower closure has been explained mainly by light in the traditional botanical literature. We show with a set of experiments that Asteraceae flower heads can close within three hours after pollination, whereas un-pollinated flower heads stay open until the late afternoon. This suggests that closing time strongly depends on pollinators. Using plant-pollinator interaction webs we further demonstrate that the daily pattern of flower opening and the rapid response to pollination can impose strong temporal dynamics on interspecific interactions within a single day. We observed pollinator species turnover and changes in facilitation vs. competition among plants. Our results show for the first time that pollination induces rapid flower closure on the community level. This causes imprecision in Linné's floral clock with far-reaching consequences for plant-pollinator interactions.

Organic amendments with reduced chemical fertilizer promote soil microbial development and nutrient availability in a subtropical paddy field: The influence of quantity, type and application time of organic amendments

Understanding the effects of alternative farming on soil quality parameters, such as microbial communities, size, activity and soil nutrient content, is of central importance to concepts of sustainability. Combining organic amendments with chemical fertilizer is a promising approach to develop more sustainable fertilization strategies. We investigated the impacts of quantity, type and application time of organic amendments on temporal dynamics of paddy soil microbial biomass, activity, carbon fractions and nutrient status under a long-term field experiment in a rice–rice cropping system. We established treatments with seven fertilization practices characterized by different quantities and application times of green manure (GM), farmyard manure (FYM) and rice straw (RS) in combination with low amount of chemical fertilizers. We further established one treatment with only recommended amount of chemical fertilizer and an unfertilized control. At all sampling times, organic amendments with low amount of chemical fertilizer enhanced microbial biomass, activity and nutrient availability more than recommended amount of chemical fertilization only and an unfertilized control, with higher quantities of FYM resulting in stronger effects than all other organic amendments. The strongest increase of microbial biomass, activity, carbon and nutrient availability was generally found in the treatment with the most diverse resources and highest amount of organic amendments. Principle component analysis indicated that most soil variables measured were correlated to total soil organic C. Regression analysis indicated that the integrated paddy soil properties were closely related to yearly C input and rice yield. Strong temporal dynamics were demonstrated for all soil variables, indicating that we need multiple time sampling strategies to explore the overall influences of fertilization practices on paddy soil. Our results indicate that the development of effective fertilization practices, especially by manipulating the quantity and type of organic amendments, may improve long-term sustainability of paddy soil ecosystems.

Langfristige Entwicklung von zwei Waldgesellschaften im Białowieża-Urwald

The results of a long-term study on the natural forest dynamics of two forest communities on one sample plot within the Białowieża National Park in Poland are presented. The two investigated forest communities consist of the Pino-Quercetum and the Tilio-Carpinetum type with the major tree species Pinus sylvestris, Picea abies, Betula sp., Quercus robur, Tilia cordata and Carpinus betulus. The results reveal strong temporal dynamics of both forest communities since 1936 in terms of tree species composition and of general stand structure. The four major tree species Scots pine, birch, English oak and Norway spruce, which were dominant until 1936, have gradually been replaced by lime and hornbeam. At the same time, the analysis of structural parameters indicates a strong trend towards a homogenization of the vertical stand structure. Possible causes for these dynamics may be changes in sylviculture, climate change and atmospheric deposition. Based on the altered tree species composition it can be concluded that a simple ≪copying≫ (mimicking) of the processes taking place in natural forests may not guarantee the conservation of the multifunctional character of the respective forests.