Mechanisms of plant species impacts on ecosystem nitrogen cycling

Plant species are hypothesized to impact ecosystem nitrogen cycling in two distinctly different ways. First, differences in nitrogen use efficiency can lead to positive feedbacks on the rate of nitrogen cycling. Alternatively, plant species can also control the inputs and losses of nitrogen from ecosystems. Our current understanding of litter decomposition shows that most nitrogen present within litter is not released during decomposition but incorporated into soil organic matter. This nitrogen retention is caused by an increase in the relative nitrogen content in decomposing litter and a much lower carbon‐to‐nitrogen ratio of soil organic matter. The long time lag between plant litter formation and the actual release of nitrogen from the litter results in a bottleneck, which prevents feedbacks of plant quality differences on nitrogen cycling. Instead, rates of gross nitrogen mineralization, which are often an order of magnitude higher than net mineralization, indicate that nitrogen cycling within ecosystems is dominated by a microbial nitrogen loop. Nitrogen is released from the soil organic matter and incorporated into microbial biomass. Upon their death, the nitrogen is again incorporated into the soil organic matter. However, this microbial nitrogen loop is driven by plant‐supplied carbon and provides a strong negative feedback through nitrogen cycling on plant productivity. Evidence supporting this hypothesis is strong for temperate grassland ecosystems. For other terrestrial ecosystems, such as forests, tropical and boreal regions, the data are much more limited. Thus, current evidence does not support the view that differences in the efficiency of plant nitrogen use lead to positive feedbacks. In contrast, soil microbes are the dominant factor structuring ecosystem nitrogen cycling. Soil microbes derive nitrogen from the decomposition of soil organic matter, but this microbial activity is driven by recent plant carbon inputs. Changes in plant carbon inputs, resulting from plant species shifts, lead to a negative feedback through microbial nitrogen immobilization. In contrast, there is abundant evidence that plant species impact nitrogen inputs and losses, such as: atmospheric deposition, fire‐induced losses, nitrogen leaching, and nitrogen fixation, which is driven by carbon supply from plants to nitrogen fixers. Additionally, plants can influence the activity and composition of soil microbial communities, which has the potential to lead to differences in nitrification, denitrification and trace nitrogen gas losses. Plant species also impact herbivore behaviour and thereby have the potential to lead to animal‐facilitated movement of nitrogen between ecosystems. Thus, current evidence supports the view that plant species can have large impacts on ecosystem nitrogen cycling. However, species impacts are not caused by differences in plant quantity and quality, but by plant species impacts on nitrogen inputs and losses.     

Modeling long-term crop response to fertilizer and soil nitrogen

A simple nitrogen balance model to calculate long-term changes in soil organic nitrogen, nitrogen uptake by the crop and recovery of applied nitrogen, is presented. It functions with time intervals of one year or one growing season. In the model a labile and a stable pool of soil organic nitrogen are distinguished. Transfer coefficients for the various inputs of nitrogen are established that specify the fractions taken up by the crop, lost from the system, and incorporated in soil organic nitrogen. It is shown how input data, model parameters and initial pool sizes can be derived and how the model can be used for calculating long-term changes in total soil organic nitrogen and uptake by the crop. For nitrogen applied annually as fertilizer or organic material the time course of nitrogen uptake and recovery of applied nitrogen is calculated. To test the sensitivity of the model, calculations have been performed for different environmental conditions with higher or lower risks for losses. The model has also been applied to establish fertilizer recommendations for a certain target nitrogen uptake by the crop. Finally, for agricultural systems where periods of cropping alternate with peroids of green fallow the time course of nitrogen uptake by the crop is calculated.     

Soil moisture surpasses elevated CO2 and temperature as a control on soil carbon dynamics in a multi-factor climate change experiment

Some single-factor experiments suggest that elevated CO₂ concentrations can increase soil carbon, but few experiments have examined the effects of interacting environmental factors on soil carbon dynamics. We undertook studies of soil carbon and nitrogen in a multi-factor (CO₂ × temperature × soil moisture) climate change experiment on a constructed old-field ecosystem. After four growing seasons, elevated CO₂ had no measurable effect on carbon and nitrogen concentrations in whole soil, particulate organic matter (POM), and mineral-associated organic matter (MOM). Analysis of stable carbon isotopes, under elevated CO₂, indicated between 14 and 19% new soil carbon under two different watering treatments with as much as 48% new carbon in POM. Despite significant belowground inputs of new organic matter, soil carbon concentrations and stocks in POM declined over four years under soil moisture conditions that corresponded to prevailing precipitation inputs (1,300 mm yr^?1). Changes over time in soil carbon and nitrogen under a drought treatment (approximately 20% lower soil water content) were not statistically significant. Reduced soil moisture lowered soil CO₂ efflux and slowed soil carbon cycling in the POM pool. In this experiment, soil moisture (produced by different watering treatments) was more important than elevated CO₂ and temperature as a control on soil carbon dynamics.     

Microbial immobilization drives nitrogen cycling differences among plant species

In many terrestrial ecosystems nitrogen (N) limits productivity and plant community composition is influenced by N availability. However, vegetation is not only controlled by N; plant species may influence ecosystem N dynamics through positive or negative effects on N cycling. We examined four potential mechanisms of plant species effects on nitrogen (N) cycling. We found no species differences in gross ammonification suggesting there are no changes in the ecosystem N cycling rate between the soil organic matter pool (SOM) and the plant/microbial pool. We also found weak differences among plant species in gross nitrification, thus plant species only marginally change the relative sizes of the NH₄⁺ and NO₃^? pools. Next, more than 90% of mineralized N was microbially immobilized, and microbial N immobilization was positively correlated with root biomass. Finally, while species differed in extractable soil NO3^? concentration, these differences were not related to root biomass suggesting that microbial immobilization drives net N mineralization and soil NO₃^? levels. Our results indicate that plant species do not cause feedbacks on the N cycling rate among the three major ecosystem N pools over nine years. However, plant carbon (C) inputs to the soil control microbial N immobilization and thereby change N partitioning between the plant and microbial N pools. Furthermore our results suggest that the SOM pool can act as a strong bottleneck for N cycling in these systems.     

Dynamics of C,N, P and S in grassland soils: a model

We have developed a model to simulate the dynamics of C, N, P, and S in cultivated and uncultivated grassland soils. The model uses a monthly time step and can simulate the dynamics of soil organic matter over long time periods (100 to 10,000 years). It was used to simulate the impact of cultivation (100 years) on soil organic matter dynamics, nutrient mineralization, and plant production and to simulate soil formation during a 10,000 year run. The model was validated by comparing the simulated impact of cultivation on soil organic matter C, N, P, and S dynamics with observed data from sites in the northern Great Plains. The model correctly predicted that N and P are the primary limiting nutrients for plant production and simulated the response of the system to inorganic N, P, and S fertilizer. Simulation results indicate that controlling the C:P and C:S ratios of soil organic matter fractions as functions of the labile P and S levels respectively, allows the model to correctly simulate the observed changes in C:P and C:S ratios in the soil and to simulate the impact of varying the labile P and S levels on soil P and S net mineralization rates.     

Increased soil carbon storage through plant diversity strengthens with time and extends into the subsoil

Soils are important for ecosystem functioning and service provisioning. Soil communities and their functions, in turn, are strongly promoted by plant diversity, and such positive effects strengthen with time. However, plant diversity effects on soil organic matter have mostly been investigated in the topsoil, and there are only very few long-term studies. Thus, it remains unclear if plant diversity effects strengthen with time and to which depth these effects extend. Here, we repeatedly sampled soil to 1 m depth in a long-term grassland biodiversity experiment. We investigated how plant diversity impacted soil organic carbon and nitrogen concentrations and stocks and their stable isotopes ¹³C and ¹⁵N, as well as how these effects changed after 5, 10, and 14 years. We found that higher plant diversity increased carbon and nitrogen storage in the topsoil since the establishment of the experiment. Stable isotopes revealed that these increases were associated with new plant-derived inputs, resulting in less processed and less decomposed soil organic matter. In subsoils, mainly the presence of specific plant functional groups drove organic matter dynamics. For example, the presence of deep-rooting tall herbs decreased carbon concentrations, most probably through stimulating soil organic matter decomposition. Moreover, plant diversity effects on soil organic matter became stronger in topsoil over time and reached subsoil layers, while the effects of specific plant functional groups in subsoil progressively diminished over time. Our results indicate that after changing the soil system the pathways of organic matter transfer to the subsoil need time to establish. In our grassland system, organic matter storage in subsoils was driven by the redistribution of already stored soil organic matter from the topsoil to deeper soil layers, for example, via bioturbation or dissolved organic matter. Therefore, managing plant diversity may, thus, have significant implications for subsoil carbon storage and other critical ecosystem services.     

Long‐term changes in forest carbon under temperature and nitrogen amendments in a temperate northern hardwood forest

Currently, forests in the northeastern United States are net sinks of atmospheric carbon. Under future climate change scenarios, the combined effects of climate change and nitrogen deposition on soil decomposition, aboveground processes, and the forest carbon balance remain unclear. We applied carbon stock, flux, and isotope data from field studies at the Harvard forest, Massachusetts, to the ForCent model, which integrates above‐ and belowground processes. The model was able to represent decadal‐scale measurements in soil C stocks, mean residence times, fluxes, and responses to a warming and N addition experiment. The calibrated model then simulated the longer term impacts of warming and N deposition on the distribution of forest carbon stocks. For simulation to 2030, soil warming resulted in a loss of soil organic matter (SOM), decreased allocation to belowground biomass, and gain of aboveground carbon, primarily in large wood, with an overall small gain in total system carbon. Simulated nitrogen addition resulted in a small increase in belowground carbon pools, but a large increase in aboveground large wood pools, resulting in a substantial increase in total system carbon. Combined warming and nitrogen addition simulations showed a net gain in total system carbon, predominately in the aboveground carbon pools, but offset somewhat by losses in SOM. Hence, the impact of continuation of anthropogenic N deposition on the hardwood forests of the northeastern United States may exceed the impact of warming in terms of total ecosystem carbon stocks. However, it should be cautioned that these simulations do not include some climate‐related processes, different responses from changing tree species composition. Despite uncertainties, this effort is among the first to use decadal‐scale observations of soil carbon dynamics and results of multifactor manipulations to calibrate a model that can project integrated aboveground and belowground responses to nitrogen and climate changes for subsequent decades.     

戴云山黄山松林土壤碳组分的海拔变化特征及影响因素

海拔梯度可能通过多种环境因子影响土壤有机质,土壤有机碳库是土壤有机质的重要组成部分,其微小变化将会产生极其重要的影响。因此海拔差异可能导致海拔间土壤碳库差异。土壤有机碳是反映土壤肥力的重要指标,可能受土壤理化性质和微生物等多种因素的影响。黄山松是高山地绿化和用材的优良树种,近年来戴云山自然保护区内高海拔地区的黄山松群落呈现衰退趋势。研究戴云山黄山松林土壤有机碳组分沿海拔梯度的变化情况,不仅可以为该区域碳库估算提供科学依据,而且有助于揭示影响黄山松生长变化的机理。因此,选取戴云山不同海拔[1300 m (L)、1450 m (M)和1600 m (H)]梯度的黄山松林,对其土壤基本理化性质、有机碳组分及微生物特征进行测定和分析。研究发现,海拔梯度下土壤养分含量呈先升高后降低的变化趋势,土壤碳组分含量与其变化一致,且微生物生物量碳和微生物生物量氮均在M海拔处最高,海拔梯度对碳水解酶没有显著影响。冗余分析表明,总氮是影响土壤有机碳变化的最主要因素,其次是碳氮比。因此在海拔跨度不大的情况下,土壤有机碳动态可能主要受氮素而非温度的影响。高海拔地区土壤惰性碳占比高,未来可能会持续加剧该地区黄山松的生长困境,使该区域碳库受到影响。     

Species richness and soil properties in Pinus ponderosa forests: A structural equation modeling analysis

Question: How are the effects of mineral soil properties on understory plant species richness propagated through a network of processes involving the forest overstory, soil organic matter, soil nitrogen, and understory plant abundance? Location: North‐central Arizona, USA. Methods: We sampled 75 0.05‐ha plots across a broad soil gradient in a Pinus ponderosa (ponderosa pine) forest ecosystem. We evaluated multivariate models of plant species richness using structural equation modeling. Results: Richness was highest at intermediate levels of understory plant cover, suggesting that both colonization success and competitive exclusion can limit richness in this system. We did not detect a reciprocal positive effect of richness on plant cover. Richness was strongly related to soil nitrogen in the model, with evidence for both a direct negative effect and an indirect non‐linear relationship mediated through understory plant cover. Soil organic matter appeared to have a positive influence on understory richness that was independent of soil nitrogen. Richness was lowest where the forest overstory was densest, which can be explained through indirect effects on soil organic matter, soil nitrogen and understory cover. Finally, model results suggest a variety of direct and indirect processes whereby mineral soil properties can influence richness. Conclusions: Understory plant species richness and plant cover in P. ponderosa forests appear to be significantly influenced by soil organic matter and nitrogen, which are, in turn, related to overstory density and composition and mineral soil properties. Thus, soil properties can impose direct and indirect constraints on local species diversity in ponderosa pine forests.     

Acidification and release of nutrients from organic matter — a model analysis

A simple, phenomenological model is proposed to describe the behaviour of nett mineralization of nitrogen from the soil organic matter.Experimental evidence shows that nett mineralization of nitrogen is increased following artificial acidification of soil forests. The model seems to describe appropriately this phenomenon and some testable predictions are derived from it. These predictions seem to give a clue to the intriguing difficulty of establishing effects of acid rain in coniferous forest ecosystems.A discussion is also given on how the model can be extended to nutrient elements other than nitrogen.     

蚂蚁筑巢对西双版纳热带森林土壤有机氮矿化的影响

蚂蚁作为生态系统工程师能够调节土壤微生物及理化环境,进而对热带森林土壤有机氮矿化速率及其时间动态产生显著影响。以西双版纳白背桐热带森林群落为研究对象,采用室内需氧培养法测定土壤有机氮矿化速率,比较蚁巢和非蚁巢土壤有机氮矿化速率的时间动态,揭示蚂蚁筑巢活动引起土壤无机氮库、微生物生物量碳及化学性质改变对有机氮矿化速率时间动态的影响。结果表明：（1）蚂蚁筑巢显著影响土壤有机氮矿化速率（P<0.01）,相较于非蚁巢,蚁巢土壤有机氮矿化速率提高了261%;（2）土壤有机氮矿化速率随月份推移呈明显的单峰型变化趋势,即6月最大（蚁巢1.22 mg kg^-1 d^-1、非蚁巢0.41 mg kg^-1 d^-1）,12月最小（蚁巢0.82 mg kg^-1 d^-1、非蚁巢0.18 mg kg^-1 d^-1）;（3）两因素方差分析表明,不同月份及不同处理对土壤有机氮矿化速率、NH₄-N及NO₃-N产生显著影响（P<0.05）,但对NO₃-N的交互作用不显著;（4）蚂蚁筑巢显著提高了无机氮库（NH₄-N与NO₃-N）、微生物生物量碳、有机质、水解氮、全氮及易氧化有机碳等土壤养分含量,而降低了土壤pH值;（5）回归分析表明,铵态氮和硝态氮对土壤有机氮矿化速率产生显著影响,分别解释87.89%、61.84%的有机氮矿化速率变化;（6）主成份分析表明NH₄-N、微生物生物量碳及有机质是影响有机氮矿化速率时间动态的主要因素,而全氮、NO₃-N、易氧化有机碳、水解氮及pH对土壤有机氮矿化速率的影响次之,且pH与土壤有机氮矿化速率呈显著负相关。总之,蚂蚁筑巢活动主要通过影响土壤NH₄-N、微生物生物量碳及有机质的状况,进而调控西双版纳热带森林土壤有机氮矿化速率的时间动态。研究结果将有助于进一步提高对土壤氮矿化生物调控机制的认识。     

Simultaneous Estimation of Actual Litter Enzymatic Catalysis and Respiration Rates with a Simple Model of C Dynamics in Sphagnum-Dominated Peatlands

C dynamics in soils plays an important role in the interactions between climate and terrestrial ecosystems. Given the importance of the soil C pool in future climate scenarios, accurate models that can then be integrated into global models are required. On the one hand, models of soil C dynamics can be very simplistic in that only solid organic matter (OM) is taken into account with constant rates. Such models can miss important features of soil C dynamics such as enzymatic activity and CO₂ production. On the other hand, some models are too complicated to be experimentally calibrated, tested, and widely used. We propose a model of soil C dynamics that (i) integrates all C fluxes from the solid to the gaseous form, and (ii) can be easily implemented experimentally. Because peatlands are important C stores that are experiencing vegetation changes, the model was tested on experimental results obtained with peatland litter: Sphagnum cuspidatum (autochtonous vegetation), Molinia caerulea, and Betula spp. (both invasive species). Our model was able to accurately describe the early stages of C dynamics in litter especially when only one pool of OM was used and when catalysis and respiration rates were allowed to decrease with time. Our model is efficient in assessing the entire actual catalysis rate. This is a notable achievement as usually, enzyme activity is measured on specific enzymes in conditions often far from actual ones. Our model appeared to be sufficiently robust and worthy of development, keeping in mind that it should remain experimentally testable.     

Simulating Grass-Legume Dynamics: a Phenomenological Submodel

A simple recipe for modelling the dynamics of the legume componentof a grass-legume pasture simulator is proposed, avoiding someof the difficulties associated with representing the pasturesubmodel as autonomous but interacting grass and legume components.A target legume content of the sward is assumed to depend onthe carbon[ratio]nitrogen ratio in the plant substrate carbonand nitrogen pools (these represent the labile and easily mobilizableC and N pools in the plant). The rate at which the actual legumecontent approaches the target content is proportional to thegross specific growth rate of the pasture. The canopy extinctioncoefficient and the dinitrogen fixation rate for the pastureare adjusted according to the changing legume content. The methodhas been incorporated into a generic single-species grasslandsimulator, the Hurley Pasture Model. Seasonal changes in legumefraction and associated variables are simulated. Next, the responseof the legume fraction to step changes in nitrogen fertilizerapplication, carbon dioxide concentration, rainfall and temperatureare predicted for a grazed pasture. Yield from frequent harvestingis also examined for four treatments: ambient and elevated carbondioxide x low and high nitrogen fertilizer application. Qualitatively,the simulations agree well with experimental findings. Thisindicates that some important aspects of grass-legume competitioncould operate primarily through the pasture carbon[ratio]nitrogensubstrate ratio. This ratio may determine those characteristicsof morphology, growth and function that largely define the differentialsuccess of the two components of grass-legume swards; however,causation would not be proved (as far as this is scientificallypossible) without a detailed mechanistic model. The approachmay be useful for the investigation of management and climate-changeproblems in grassland. Copyright 2001 Annals of Botany Company Grass, legume, model, grassland, ecosystem, simulator     

Dynamic model of the response of a vegetative grass crop to light, temperature and nitrogen

Abstract A previously described growth model of the vegetative grass crop is extended to include a simple representation of the root system, uptake of nitrogen from a soil nitrogen pool, and response to fertilizer application. The model simulates the processes of light interception, photosynthesis, partitioning of new growth, leaf area expansion, growth and maintenance respiration, ageing of plant tissues, senescence, recycling of substrates from senescing tissues, nitrogen uptake by the plant, leaching, mineralization, and fertilizer application. A principal component of the model, nitrogen uptake, is assumed to depend positively on plant carbon substrate concentration and soil nitrogen concentration, and to be inhibited by plant nitrogen substrate concentration. The dynamic responses to different levels of soil nitrogen, of shoot and root growth, nitrogen uptake and root activity, carbon and nitrogen plant substrate concentrations, and the fraction of substrate carbon used by the shoots, are examined; realistic behaviour is observed. The model predicts nitrogen fertilizer responses of yield and plant nitrogen content, which are compared directly with experimental data; good agreement is obtained.     

Fire effects on ecosystem nitrogen cycling in a Californian bishop pine forest

Fire can cause severe nitrogen (N) losses from grassland, chaparral, and temperate and boreal forest ecosystems. Paradoxically, soil ammonium levels are markedly increased by fire, resulting in high rates of primary production in re-establishing plant communities. In a manipulative experiment, we examined the influence of wild-fire ash residues on soil, microbial and plant N pools in a recently burned Californian bishop pine (Pinus muricata D. Don) forest. Ash stimulated post-fire primary production and ecosystem N retention through direct N inputs from ash to soils, as well as indirect ash effects on soil N availability to plants. These results suggest that redistribution of surface ash after fire by wind or water may cause substantial heterogeneity in soil N availability to plants, and could be an important mechanism contributing to vegetation patchiness in fire-prone ecosystems. In addition, we investigated the impact of fire on ecosystem N cycling by comparing ¹⁵N natural abundance values from recently burned and nearby unburned P. muricata forest communities. At the burned site, ¹⁵N natural abundance in recolonising species was similar to that in bulk soil organic matter. By contrast, there was a marked ¹⁵N depletion in the same species relative to the total soil N pool at the unburned site. These results suggest that plant uptake of nitrate (which tends to be strongly depleted in ¹⁵N because of fractionation during nitrification) is low in recently burned forest communities but could be an important component of eco- system N cycling in mature conifer stands. Received: 29 June 1999 / Accepted: 24 October 1999     

Growth and mineral nutrition of the native trees Pollalesta discolor and the N-fixing Inga densiflora in relation to the soil properties of a degraded volcanic soil of the Ecuadorian Amazon

Land reclamation in the humid tropics, using native tree plantations, requires a better knowledge of plant-soil interactions, and of patterns of growth of several poorly known species. We examined the establishment and mineral nutrition of two early-successional native tree species, Inga densiflora (N-fixing) and Pollalesta discolor, in relation to properties of a degraded Hydrandept volcanic soil in Ecuadorian Amazon. Initial content of organic matter was the most significant soil variable in explaining the growth of pure stands of both species and was strongly related to effective cation exchange capacity (ECEC) and to net total N mineralization. Leaves of Pollalesta discolor had greater concentration of nutrients than Inga densiflora, which led to a litter-layer rich in nutrients. Deficient concentrations of foliar P, detected on plots with low soil organic matter, were linked to poor growth of Inga densiflora, and indicate that this species may be P-limited. The inclusion of Inga densiflora did not stimulate the growth of Pollalesta discolor in mixed stands. This study indicates that soil organic matter management is an important issue on these degraded volcanic soils. We suggest that a reduction of the pool of labile organic matter appears to hamper tree productivity through a nutrient shortage. The high variability of the degraded soil studied proved to be an obstacle to tree growth and establishment. This revised version was published online in July 2006 with corrections to the Cover Date.     

Modelling soil organic matter levels after long-term applications of crop residues,and farmyard and green manures

A computer simulation model for long-term soil organic matter dynamics was developed and evaluated with data from long-term field trials in Belgium, Germany and The Netherlands. The model distinguishes four pools of soil organic components (including a microbial biomass pool) with different chemical properties. Transformation rates are described by (pseudo) first order kinetics. Effects of temperature and soil moisture tension were included. Simulation results were in agreement with experimental data from arable farming practices where common input rates were applied. Model calculations overestimated soil organic matter levels when green manures or exceptionally high input rates were applied. Inadequate experimental estimations of organic matter input rates and insufficient modelling of the soil preservation capacity for organic matter and biomass are likely reasons. After changes in the soil organic matter-input management it may take more than a century to reach new equilibrium levels.     

土壤有机质模型的比较分析

土壤有机质作为土壤C库,其含量和动态变化对全球C循环、土壤肥力、土壤质量和健康起着重要作用。SOM模型利用经验性的假设和已有数据对土壤有机质含量和动态变化进行模拟,尤其是可以对无法取得足够必要数据的试验进行模拟,所以SOM模型成为定量研究土壤有机质积累分解的重要手段,利用SOM模型有助于对土壤有机质分解机理的研究,并且可通过SOM模型对土壤CO2排放量、植物生产量进行预测。同时也可对农业管理措施做出评估,文中对几种SOM模型进行了概述,尤其对有影响的RothC模型和CENTURY模型进行了比较分析。     

抚育间伐对长白落叶松人工林土壤碳、氮及其组分的影响

抚育间伐作为重要的森林经营措施之一,能够改变林分结构和稳定性,进而影响森林生态系统的生物地球化学循环.然而,抚育间伐对森林土壤碳、氮循环的影响程度如何尚不明确,尤其缺少长期试验结果报道.本研究以黑龙江省孟家岗林场经过4种不同强度和频度的抚育间伐处理后的60年生长白落叶松人工林为研究对象(4次低强度的间伐,LT4;3次中等强度的间伐,MT3;2次高强度间伐,HT2;不进行间伐的对照,CK),从酸水解法划分土壤碳、氮库(活性碳、氮库Ⅰ,活性碳、氮库Ⅱ和惰性碳、氮库)的角度研究了抚育间伐对长白落叶松人工林土壤总有机碳、全氮的影响机制.结果表明: 抚育间伐显著增加了土壤有机碳和全氮含量,增幅分别高达48.7%～50.3%和28.9%～42.7%.抚育间伐均增加了3种碳、氮组分的含量,而增加的程度因碳、氮组分和抚育间伐措施的不同而异.与活性碳库Ⅰ和活性碳库Ⅱ的增加程度相比,惰性碳库的增加程度最大,LT4、MT3和HT2处理下惰性碳库分别增加71%、69%和75%.此外,抚育间伐也显著增加了惰性碳占土壤总有机碳的比例.LT4显著提高了土壤微生物生物量碳、氮含量和微生物熵,而MT3和HT2对微生物生物量碳、氮和微生物熵却无显著影响.抚育间伐可能通过产生较多的粗木质残体于土体中,增加土壤木栓质和木质素等顽固组分的输入,进而导致土壤惰性碳含量增加,降低有机质的分解,最终导致土壤有机碳增加.