Relations of soil properties to topography and vegetation in a subtropical rain forest in southern Taiwan

Soil chemical properties for a subtropical rain forest in the Nanjenshan Reserve, southern Taiwan, were examined to determine soil-landscape and soil-vegetation relationships. Soil sampling sites were separated into four groups based on landscape features and exposure to the prevailing northeasterly monsoon winds. Corresponding vegetation types were delimited along the first DCA axis. The forest showed a drastic change both in structure and floristic composition along the wind-stress gradient. Redundancy analysis (RDA) showed that both topographic variables and vegetation types were needed to explain the variation in soil data. Soil properties that differed significantly among landforms were pH, available N, CEC, exchangeable Al, K, Ca and Mg. Levels of pH, exchangeable Ca and Mg increased in a downslope direction, and exchangeable Al tended to be higher in the upper slope soils. These trends pointed to the importance of slope processes in redistribution of soil minerals. The main differences in soil properties attributed to the influence of the occupying vegetation were apparently aspect dependent. The contents of available N, exchangeable K, and CEC in the 0–40 cm depth of soils under windward low-stature (mostly sclerophyllous) forest were consistently lower compared to those under the leeward forest. For a given catena, however, soil variability associated with vegetation differences seemed to be confounded by the slope processes.     

Estimating base cation weathering rates in Canadian forest soils using a simple texture-based model

Mineral weathering is the primary source of long-term buffering capacity in soils and is important for forest nutrient sustainability. Regional assessments of weathering rates in Canada and the U.S. have employed an empirical clay-based Soil Texture Approximation (STA) owing to limited data availability, although the STA is rarely calibrated before application to a study area. Soil weathering rates estimated with the STA at 75 sites in Canadian forests (6–367 eq ha^?1 year^?1) were on average seven times lower than estimates obtained using the PROFILE model and when mineralogy was not available, the Analysis to Mineralogy model and parameter estimation (143–2,119 eq ha^?1 year^?1). Comparison with a catchment mass balance at a subset of sites in Ontario (n = 19) demonstrated the reliability of PROFILE weathering estimates. A revised (generalized) STA model for total base cation weathering was developed at the 75 study sites to incorporate soil silt content (%) and loss-on-ignition (LOI, %) (BC _w = (1.73 + 0.03 · silt ? 0.06 · LOI) · 1,000 · depth). The model performance (R _adj ²  = 73%) and relative bias (?1%) suggested that the revised STA may have broad application to forest soils in Canada but may not necessarily be suited to all soil texture classes.     

Prediction of take-all disease risk in field soils using a rapid and quantitative DNA soil assay

A rapid, routine DNA-based assay to quantify Gaeumannomyces graminis var. tritici (Ggt), the causal agent of take-all disease of cereals, has been developed and used for the prediction of take-all in a wide range of field soils. Based on the correlation of the DNA-based assay and a soil bioassay, the risk of disease development can be estimated. Ggt DNA levels of <30 pg, 30–50 pg and >50 pg in 0.1 g soil organic matter correspond to low, moderate and high levels of the disease, respectively. Limitations in the prediction of take-all, including sampling requirements to obtain representative soil samples from fields and increasing the sensitivity and the accuracy of the DNA assay, are described. The main advantage in using the DNA-based assay, in estimating the amount of Ggt inoculum in soil, is that the levels of Ggt in soil samples can be assessed rapidly and accurately. Farmers can now have soil samples assessed before sowing. The DNA result can be used to predict the potential yield loss and determine the most appropriate management options using decision support software that is currently available. This DNA technology is currently being used commercially to detect and predict take-all. This revised version was published online in June 2006 with corrections to the Cover Date.     

Root controls on soil microbial community structure in forest soils

We assessed microbial community composition as a function of altered above- and belowground inputs to soil in forest ecosystems of Oregon, Pennsylvania, and Hungary as part of a larger Detritus Input and Removal Treatment (DIRT) experiment. DIRT plots, which include root trenching, aboveground litter exclusion, and doubling of litter inputs, have been established in forested ecosystems in the US and Europe that vary with respect to dominant tree species, soil C content, N deposition rate, and soil type. This study used phospholipid fatty-acid (PLFA) analysis to examine changes in the soil microbial community size and composition in the mineral soil (0–10 cm) as a result of the DIRT treatments. At all sites, the PLFA profiles from the plots without roots were significantly different from all other treatments. PLFA analysis showed that the rootless plots generally contained larger quantities of actinomycete biomarkers and lower amounts of fungal biomarkers. At one of the sites in an old-growth coniferous forest, seasonal changes in PLFA profiles were also examined. Seasonal differences in soil microbial community composition were greater than treatment differences. Throughout the year, treatments without roots continued to have a different microbial community composition than the treatments with roots, although the specific PLFA biomarkers responsible for these differences varied by season. These data provide direct evidence that root C inputs exert a large control on microbial community composition in the three forested ecosystems studied.     

Priority areas for the conservation of subtropical indigenous forest in southern Africa: a case study from KwaZulu-Natal

Southern Africa's subtropical forest biome, though small and highly fragmented, supports much of the region's biodiversity. With limited resources available for conservation and the exploitative use of forest escalating, identifying a network of priority forest reserves is important. We examine the distribution of forest birds, butterflies and mammals in KwaZulu-Natal, South Africa. Using an iterative algorithm we explore the efficiency of existing protected areas, species richness and rarity hotspots, prime forest sites (selected by forest area) and complementary networks as alternative approaches to priority reserve selection, as well as the potential use of indicator taxa. Existing protected areas represent 98% of species but are relatively inefficient in terms of area. Alternative selection criteria represent a high proportion of species (86–92%) and provide efficient bases for developing fully representative reserve networks. All species are represented within a network of 22 complementary quarter degree cells. This network includes several larger forests and existing protected areas and is recommended for priority conservation. Complementary networks identified separately for birds, butterflies and mammals overlap little, but each represents a high proportion of the remaining taxa, supporting their potential as representative 'indicator' taxa. The evolutionary history of the three main forest types in KwaZulu-Natal explains observed spatial patterns of alternative reserve networks. Priority areas are concentrated in scarp and coastal forest belts, regions of comparatively recent evolutionary activity with high species richness. Afromontane forest is older and less diverse, but its inclusion in any reserve network is necessary for the full representation of forest diversity.     

Predicting forest site productivity in temperate lowland from forest floor, soil and litterfall characteristics using boosted regression trees

Aims

The aim of this study is on the one hand to identify the most determining variables predicting the site productivity of pedunculate oak, common beech and Scots pine in temperate lowland forests of Flanders; and on the other hand to test whether the accuracy of site productivity models based exclusively on soil or forest floor predictor variables is similar to the accuracy achieved by full ecosystem models, combining all soil, vegetation, humus and litterfall composition related variables.

Methods

Boosted Regression Trees (BRT) were used to model in a climatically homogeneous region the relationship between environmental variables and site productivity. A distinction was made between soil (soil physical and chemical), forest floor (vegetation and humus) and ecosystem (soil, forest floor and litterfall composition jointly) predictors.

Results

Our results have illustrated the strength of BRT to model the non-linear behaviour of ecological processes. The ecosystem models, based on all collected variables, explained most of the variability and were more accurate than those limited to either soil or forest floor variables. Nevertheless, both the soil and forest floor models can serve as good predictive models for many forest management practices.

Conclusions

Soil granulometric fractions and litterfall nitrogen concentrations were the most effective predictors of forest site productivity in Flanders. Although many studies revealed a fertilising effect of increased nitrogen deposition, nitrogen saturation seemed to reduce species’ productivity in this region.     

Nitrogen addition reduces soil respiration in a mature tropical forest in southern China

Response of soil respiration (CO₂ emission) to simulated nitrogen (N) deposition in a mature tropical forest in southern China was studied from October 2005 to September 2006. The objective was to test the hypothesis that N addition would reduce soil respiration in N saturated tropical forests. Static chamber and gas chromatography techniques were used to quantify the soil respiration, following four‐levels of N treatments (Control, no N addition; Low‐N, 5 g N m^?2 yr^?1; Medium‐N, 10 g N m^?2 yr^?1; and High‐N, 15 g N m^?2 yr^?1 experimental inputs), which had been applied for 26 months before and continued throughout the respiration measurement period. Results showed that soil respiration exhibited a strong seasonal pattern, with the highest rates found in the warm and wet growing season (April–September) and the lowest rates in the dry dormant season (December–February). Soil respiration rates showed a significant positive exponential relationship with soil temperature, whereas soil moisture only affect soil respiration at dry conditions in the dormant season. Annual accumulative soil respiration was 601±30 g CO₂‐C m^?2 yr^?1 in the Controls. Annual mean soil respiration rate in the Control, Low‐N and Medium‐N treatments (69±3, 72±3 and 63±1 mg CO₂‐C m^?2 h^?1, respectively) did not differ significantly, whereas it was 14% lower in the High‐N treatment (58±3 mg CO₂‐C m^?2 h^?1) compared with the Control treatment, also the temperature sensitivity of respiration, Q₁₀ was reduced from 2.6 in the Control with 2.2 in the High‐N treatment. The decrease in soil respiration occurred in the warm and wet growing season and were correlated with a decrease in soil microbial activities and in fine root biomass in the N‐treated plots. Our results suggest that response of soil respiration to atmospheric N deposition in tropical forests is a decline, but it may vary depending on the rate of N deposition.     

Investigation of nitrification in forest soils with soil percolation columns

Soil percolation columns in which a pF of 2 could be maintained were developed to study nitrification in soils and litter of an acid and a calcareous forest soil location. High nitrification rates were observed in the calcareous soil. In the acid soil nitrification was much slower. A column filled with leaf litter gave a low nitrification rate at the start of the experiment, but a high rate was found after 60 days of percolation with an ammonium-containing medium of pH 4. In this leaf litter high numbers of autotrophic bacteria were just present at the beginning of the experiment, whereas at the end only low numbers were detected. Results indicate that autotrophic bacteria from acid soils are sensitive to a pH increase.     

Influences of soil acidity on Streptomyces populations inhabiting forest soils.

The Streptomyces populations inhabiting five acidic forest soils were examined. It was found that lowering the pH of a medium selective for streptomycetes (starch-casein agar) to the pH of the particular soil horizon being plated influenced both the total numbers and types of streptomycetes that were isolated from the soils examined in this study. On the acidified medium both the numbers of streptomycetes and the percentage of total bacteria on the plates represented by streptomycetes increased (as compared with the same medium with a pH of 7.2). These differences were greatest on the isolations from the most acid soils. The largest concentrations of streptomycetes were found in the surface horizon (0 to 15 cm) and the litter layer immediately over the surface mineral horizon. Acidity tolerance tests demonstrated that random samplings of isolates contained acidophilic, neutrophilic, and acidoduric strains, with the largest numbers of acidophiles being found on the acidified media from the most acid soils. There were no differences between overall utilization of selected carbohydrates among the isolates taken from either the neutral or acidic media, although a larger proportion of the acid media isolates produced acid from the carbohydrates. Evidence is presented which indicates that different types of streptomycetes were isolated on the acid media, and possible reasons for the presence of these acid-tolerant populations are discussed.     

Microbial diversity of topographical gradient profiles in Fushan forest soils of Taiwan

To evaluate the microbial diversity of Fushan forest soils, the variation of soil properties, microbial populations, and soil DNA with soil depth in three sites of different altitude were analyzed. Microbial population, moisture content, total organic carbon (C_org), and total nitrogen (N_tot) decreased with increasing soil depth. The valley site had the lowest microbial populations among the three tested sites due to the low organic matter content. Bacterial population was the highest among the microbial populations. The ratios of cellulolytic microbes to the total bacteria in organic layers were high, implying their roles in the carbon cycle. The microbial biomass carbon (C_mic) and nitrogen (N_mic) contents ranged from 130.5 to 564.1 μg g⁻¹ and from 16.7 to 95.4 μg g⁻¹, respectively. The valley had the lowest C_mic and N_mic. The organic layer had the highest C_mic and N_mic and decreased with soil depth. Analysis using denaturing gradient gel electrophoresis (DGGE) of polymerase chain reaction (PCR) amplicons of 16S rDNA showed that the bacterial diversity of the three sites were very similar to each other in the major bands, and the variation was in the minor bands. However, the patterns in PCR-DGGE profile through gradient horizons were different, indicating the prevalence of specific microbes at different horizons. These results suggest that the microbial diversity in the deeper horizons is not simply the diluted analogs of the surface soils and that some microbes dominate only in the deeper horizons. Topography influenced the quantity and diversity of microbial populations.     

Snow depth, soil freezing and nitrogen cycling in a northern hardwood forest landscape

Increases in soil freezing associated with decreases in snow cover have been identified as a significant disturbance to nitrogen (N) cycling in northern hardwood forests. We created a range of soil freezing intensity through snow manipulation experiments along an elevation gradient at the Hubbard Brook Experimental Forest (HBEF) in the White Mountains, NH USA in order to improve understanding of the factors regulating freeze effects on nitrate (NO₃ ^?) leaching, nitrous oxide (N₂O) flux, potential and in situ net N mineralization and nitrification, microbial biomass carbon (C) and N content and respiration, and denitrification. While the snow manipulation treatment produced deep and persistent soil freezing at all sites, effects on hydrologic and gaseous losses of N were less than expected and less than values observed in previous studies at the HBEF. There was no relationship between frost depth, frost heaving and NO₃ ^? leaching, and a weak relationship between frost depth and winter N₂O flux. There was a significant positive relationship between dissolved organic carbon (DOC) and NO₃ ^? concentrations in treatment plots but not in reference plots, suggesting that the snow manipulation treatment mobilized available C, which may have stimulated retention of N and prevented treatment effects on N losses. While the results support the hypothesis that climate change resulting in less snow and more soil freezing will increase N losses from northern hardwood forests, they also suggest that ecosystem response to soil freezing disturbance is affected by multiple factors that must be reconciled in future research.     

Snow depth manipulation and its influence on soil frost and water dynamics in a northern hardwood forest

Climate change will likelyresult in warmer winter temperatures leading toless snowfall in temperate forests. Thesechanges may lead to increases in soil freezingbecause of lack of an insulating snow cover andchanges in soil water dynamics during theimportant snowmelt period. In this study, wemanipulated snow depth by removing snow for twowinters, simulating the late development of thesnowpack as may occur with global warming, toexplore the relationships between snow depth,soil freezing, soil moisture, and infiltration.We established four sites, each with two pairedplots, at the Hubbard Brook Experimental Forest(HBEF) in New Hampshire, U.S.A. and instrumentedall eight plots with soil and snow thermistors,frost tubes, soil moisture probes, and soillysimeters. For two winters, we removed snowfrom the designated treatment plots untilFebruary. Snow in the reference plots wasundisturbed. The treatment winters (1997/1998 and1998/1999) were relatively mild, withtemperatures above the seasonal norm and snowdepths below average. Results show the treatedplots accumulated significantly less snow andhad more extensive soil frost than referenceplots. Snow depth was a strong regulator ofsoil temperature and frost depth at all sites.Soil moisture measured by time domainreflectometry probes and leaching volumescollected in lysimeters were lower in thetreatment plots in March and April compared tothe rest of the year. The ratio of leachatevolumes collected in the treatment plots tothat in the reference plots decreased as thesnow ablation seasons progressed. Our data showthat even mild winters with low snowfall,simulated by snow removal, will result inincreased soil freezing in the forests at theHBEF. Our results suggest that a climate shifttoward less snowfall or a shorter duration ofsnow on the ground will produce increases insoil freezing in northern hardwood forests.Increases in soil freezing will haveimplications for changes in soil biogeochemicalprocesses.     

Nitrogen aboveground turnover and soil stocks to 8 m depth in primary and selectively logged forest in southern Amazonia

Extensive areas of Amazonia undergo selective logging, modifying forest structure and nutrient cycles. Anthropogenic‐accelerated rates of nitrogen (N) turnover could increase N loss and affect regeneration, carbon sequestration and timber production. We quantified leaf area reduction, canopy opening and downed biomass and resultant N flux from reduced impact logging (RIL) activities. We compared canopy reduction, surface soil moisture and nitrate to 8 m depth between logged gaps and intact primary forest to determine if logging activities increase subsoil nitrate. To test long‐term logging effects, we evaluated surface N stocks along a 12‐year postlogging chronosequence. At the harvest rate of 2.6 trees ha^?1, total N additions in logging gaps, including leaves and wood from felled crowns (24.8 kg N ha^?1) and other killed trees (41.9 kg N ha^?1), accounted for over 80% of the total N addition to aboveground necromass from all logging activities (81.9 kg N ha^?1). Despite this N turnover by logging, belowground nitrate storage to 8 m depth did not differ between logging gaps and primary forest at the low harvest rate and disturbance intensity of this study. Soil water depletion also did not differ between gaps and primary forest over 1 year, indicating the impact on belowground inorganic N was low. Compared with primary forest, nitrate concentrations to 8 m depth in logging gaps were only significantly higher at 60–100 cm, suggesting some N redistribution beyond the bulk of the fine roots in logging gaps. Extrapolated to the Amazon Basin scale, we provide a conservative estimate that logging damage and bole export under RIL would turn over 0.14 ± 0.07 to 0.23 ± 0.12 Tg N yr^?1 based on 1999–2002 selective logging rates. Greater damage during conventional selective logging would cause higher N turnover throughout the Amazon Basin than our results based on RIL.     

Modelling nitrous oxide emission from water-logged soils of a spruce forest ecosystem using the biogeochemical model Wetland-DNDC

During the last decades, decision makers and policy have increasingly demanded for regional and national inventories of greenhouse gas emission, such as nitrous oxide (N₂O), to develop appropriate strategies and mitigation options. A potential way to derive large-scale estimates of N₂O emission is the use of process-based models, such as PnET-N-DNDC or Wetland-DNDC. While PnET-N-DNDC has been effectively applied for various upland forest ecosystems, the Wetland-DNDC model has not yet been validated with regard to N₂O emission. We calibrated and validated the Wetland-DNDC model on the basis of a 4-year field data set of two water-logged soils (Humic Gleysol and Histic Gleysol) of a spruce forest ecosystem. Model calibration by means of the Levenberg–Marquardt algorithm considerably improved the model performance for the period of calibration (2001–2002). The error variance was reduced by up to a factor of two and the modelling efficiency was increased from −1.24 to −0.15 (Humic Gleysol) and from −0.42 to 0.1 (Histic Gleysol). However, the model performance for the period of validation (2003–2004) and particularly for the extreme dry period in summer 2003 was not fully satisfying, notably with regard to the temporal pattern of the N₂O emission.     

An agent-based model of sleeping sickness: simulation trials of a forest focus in southern Cameroon

An agent-based model (AMB) used to simulate the spread of Human African Trypanosomiasis is presented together with the results of simulations of a focus of the disease. This model is a completely spatialized approach taking into account a series of often overlooked parameters such as human behaviour (activity-related movements), the density and mobility of the disease vectors--tsetse flies (Glossina spp.)--and the influence of other tsetse feeding hosts (livestock and wild animal populations). The agents that represent humans and tsetse flies move in a spatially structured environment managed by specialized location agents. Existing compartmental mathematical models governed by differential equations fail to incorporate the spatial dimension of the disease transmission. Furthermore, on a small scale, transmission is unrealistically represented by entities less than one. This ABM was tested with data from one village of the Bipindi sleeping sickness focus (southern Cameroon) and with obtained realistic simulations of stable transmission involving an animal reservoir. In varying different spatial configurations, we observe that the stability of spread is linked to the spatial complexity (number of heterogeneous locations). The prevalence is very sensitive to the human densities and to the number of tsetse flies initially infected in a given location. A relatively low and durable prevalence is obtained with shortening the phase I. In addition, we discuss some upgrading possibilities, in particular the linkage to a Geographical Information System (GIS). The agent-based approach offers new ways to understanding the spread of the disease and a tool to evaluate risk and test control strategies.     

Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case study

Background

State-of-the-art protein-ligand docking methods are generally limited by the traditionally low accuracy of their scoring functions, which are used to predict binding affinity and thus vital for discriminating between active and inactive compounds. Despite intensive research over the years, classical scoring functions have reached a plateau in their predictive performance. These assume a predetermined additive functional form for some sophisticated numerical features, and use standard multivariate linear regression (MLR) on experimental data to derive the coefficients.

Results

In this study we show that such a simple functional form is detrimental for the prediction performance of a scoring function, and replacing linear regression by machine learning techniques like random forest (RF) can improve prediction performance. We investigate the conditions of applying RF under various contexts and find that given sufficient training samples RF manages to comprehensively capture the non-linearity between structural features and measured binding affinities. Incorporating more structural features and training with more samples can both boost RF performance. In addition, we analyze the importance of structural features to binding affinity prediction using the RF variable importance tool. Lastly, we use Cyscore, a top performing empirical scoring function, as a baseline for comparison study.

Conclusions

Machine-learning scoring functions are fundamentally different from classical scoring functions because the former circumvents the fixed functional form relating structural features with binding affinities. RF, but not MLR, can effectively exploit more structural features and more training samples, leading to higher prediction performance. The future availability of more X-ray crystal structures will further widen the performance gap between RF-based and MLR-based scoring functions. This further stresses the importance of substituting RF for MLR in scoring function development.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-291) contains supplementary material, which is available to authorized users.     

Effect of alginite amendment on microbial activity and soil water content in forest soils

The effect of the amendment with alginite, an organic rock originating from the biomass of fossilized unicellular algae, on microbial activity of forest soils was tested using a pot experiment. Five variants of soil-alginite mixtures were tested in three replicates with two forest soils: a loose sandy soil and a sandy loam. Gravimetric moisture closely correlated with the dose of alginite in both soils. Basal respiration and catalase activity increased with the dose of alginite in the sandy soil, but not in the sandy loam, where the highest response was observed at intermediate doses of alginite. The correlations of microbial activity parameters with moisture in the sandy soil were also much closer than in the sandy loam. The amendment with alginite was thus effective in improving some of the selected microbial activity indicators, but the optimum dose of alginite strongly depends on soil texture.     

Effects of forest management on soil N cycling in beech forests stocking on calcareous soils

The effects of forest management (thinning) on gross and net N conversion, the balance of inorganic N production and consumption, inorganic N concentrations and on soil microbial biomass in the Ah layer were studied in situ during eight intensive field measuring campaigns in the years 2002–2004 at three beech (Fagus sylvatica L.) forest sites. At all sites adjacent thinning plots (“T”) and untreated control plots (“C”) were established. Since the sites are characterized either by cool-moist microclimate (NE site and NW site) or by warm-dry microclimate (SW site) and thinning took place in the year 1999 at the NE and SW sites and in the year 2003 at the NW site the experimental design allowed to evaluate (1) short-term effects (years 1–2) of thinning at the NW site and (2) medium-term effects (years 4–6) of thinning under different microclimate at the SW and NE site. Microbial biomass N was consistently higher at the thinning plots of all sites during most of the field campaigns and was overall significantly higher at the SWT and NWT plots as compared to the corresponding untreated control plots. The size of the microbial biomass N pool was found to correlate positively with both gross ammonification and gross nitrification as well as with extractable soil NO₃⁻ concentrations. At the SW site neither gross ammonification, gross nitrification, gross ammonium (NH₄⁺) immobilization and gross nitrate (NO₃⁻) immobilization nor net ammonification, net nitrification and extractable NH₄⁺ and NO₃⁻ contents were significantly different between control and thinning plot. At the NET plot lower gross ammonification and gross NH₄⁺ immobilization in conjunction with constant nitrification rates coincided with higher net nitrification and significantly higher extractable NO₃⁻ concentrations. Thus, the medium-term effects of thinning varied with different microclimate. The most striking thinning effects were found at the newly thinned NW site, where gross ammonification and gross NH₄⁺ immobilization were dramatically higher immediately after thinning. However, they subsequently tended to decrease in favor of gross nitrification, which was significantly higher at the NWT plot as compared to␣the␣NWC plot during all field campaigns after␣thinning except for April 2004. This increase␣in␣gross nitrification at the NWT plot (1.73 mg N kg⁻¹ sdw day⁻¹ versus 0.48 mg N kg⁻¹ sdw day⁻¹ at the NWC plot) coincided with significantly higher extractable NO₃⁻ concentrations (4.59 mg N kg⁻¹ sdw at the NWT plot versus 0.96 mg N kg⁻¹ sdw at the NWC plot). Pronounced differences in relative N retention (the ratio of gross NH₄⁺ immobilization + gross NO₃⁻ immobilization to gross ammonification + gross nitrification) were found across the six research plots investigated and could be positively correlated to the soil C/N ratio (R = 0.94; p = 0.005). In sum, the results obtained in this study show that (1) thinning can lead to a shift in the balance of microbial inorganic N production and consumption causing a clear decrease in the N retention capacity in the monitored forest soils especially in the first two years after thinning, (2)␣the resistance of the investigated forest ecosystems to disturbances of N cycling by thinning may vary with different soil C contents and C/N ratios, e. g. caused by differences in microclimate, (3) thinning effects tend to decline with the growth of understorey vegetation in the years 4–6 after thinning.