Effects of litter and fine root composition on their decomposition in a Rhodic Paleustalf under different land uses

Plant litter and fine roots are important in maintaining soil organic carbon (C) levels as well as for nutrient cycling. The decomposition of surface-placed litter and fine roots of wheat ( Triticum aestivum ), lucerne ( Medicago sativa ), buffel grass ( Cenchrus ciliaris ), and mulga ( Acacia aneura ), placed at 10-cm and 30-cm depths, was studied in the field in a Rhodic Paleustalf. After 2 years, = 60% of mulga roots and twigs remained undecomposed. The rate of decomposition varied from 4.2 year -1 for wheat roots to 0.22 year -1 for mulga twigs, which was significantly correlated with the lignin concentration of both tops and roots. Aryl+O-aryl C concentration, as measured by 13 C nuclear magnetic resonance spectroscopy, was also significantly correlated with the decomposition parameters, although with a lower R 2 value than the lignin concentration. Thus, lignin concentration provides a good predictor of litter and fine root decomposition in the field.

A multi-scale assessment of physiological processes in arctic tundra plants under natural and simulated climate change scenarios

Climate warming is predicted to cause an increase in the growing season by as much as 30% for regions of the arctic tundra. This will have a significant effect on the physiological activity of the vascular plant species and the ecosystem as a whole. The need to understand the possible physiological change within this ecosystem is confounded by the fact that research in this extreme environment has been limited to periods when conditions are most favorable, mid June–mid August. This study attempted to develop the most comprehensive understanding to date of the physiological activity of seven tundra plant species in the Alaskan Arctic under natural and lengthened growing season conditions. Four interrelated lines of research, scaling from cellular signals to ecosystem processes, set the foundation for this study. ^ I established an experiment looking at the physiological response of arctic sedges to soil temperature stress with emphasis on the role of the hormone abscisic acid (ABA). A manipulation was also developed where the growing season was lengthened and soils were warmed in an attempt to determine the maximum physiological capacity of these seven vascular species. Additionally, the physiological capacities of four evergreens were tested in the subnivean environment along with the potential role anthocyanins play in their activity. The measurements were scaled up to determine the physiological role of these evergreens in maintaining ecosystem carbon fluxes. ^ These studies determined that soil temperature differentials significantly affect vascular plant physiology. ABA appears to be a physiological modifier that limits stomatal processes when root temperatures are low. Photosynthetic capacity was limited by internal plant physiological mechanisms in the face of a lengthened growing season. Therefore shifts in ecosystem carbon dynamics are driven by changes in species composition and biomass production on a per/unit area basis. These studies also found that changes in soil temperatures will have a greater effect of physiological processes than would the same magnitude of change in air temperature. The subnivean environment exhibits conditions that are favorable for photosynthetic activity in evergreen species. These measurements when scaled to the ecosystem have a significant role in limiting the system's carbon source capacity. ^

Local biomass control on the composition and reactivity of particulate organic matter in aquatic environments

Freshwater ecosystems have been recognized as important components of the global carbon cycle, and the flux of organic matter (OM) from freshwater to marine environments can significantly affect estuarine and coastal productivity. The focus of this study was the assessment of carbon dynamics in two aquatic environments, namely the Florida Everglades and small prairie streams in Kansas, with the aim of characterizing the biogeochemistry of OM. In the Everglades, particulate OM (POM) is mostly found as a layer of flocculent material (floc). While floc is believed to be the main energy source driving trophic dynamics in this oligotrophic wetland, not much is known about its biogeochemistry. The objective of this study was to determine the origin/sources of OM in floc using biomarkers and pigment-based chemotaxonomy to assess specific biomass contributions to this material, on a spatial (freshwater marshes vs. mangrove fringe) and seasonal (wet vs. dry) scales. It was found that floc OM is derived from the local vegetation (mainly algal components and macrophyte litter) and its composition is controlled by seasonal drivers of hydrology and local biomass productivity. Photo-reactivity experiments showed that light exposure on floc resulted in photo-dissolution of POC with the generation of significant amounts of both dissolved OM (DOM) and nutrients (N & P), potentially influencing nutrient dynamics in this ecosystem. The bio-reactivity experiments determined as the amount and rate of CO2 evolution during incubation were found to vary on seasonal and spatial scales and were highly influenced by phosphorus limitation. Not much is known on OM dynamics in small headwater streams. The objective of this study was to determine carbon dynamics in sediments from intermittent prairie streams, characterized by different vegetation cover for their watershed (C4 grasses) vs. riparian zone (C3 plants). In this study sedimentary OM was characterized using a biomarker and compound specific carbon stable isotope approach. It was found that the biomarker composition of these sediments is dominated by higher plant inputs from the riparian zone, although inputs from adjacent prairie grasses were also apparent. Conflicting to some extent with the River Continuum Concept, sediments of the upper reaches contained more degraded OM, while the lower reaches were enriched in fresh material deriving from higher plants and plankton sources as a result of hydrological regimes and particle sorting.

Modeling Light Use Efficiency in a Subtropical Mangrove Forest Equipped with CO2 Eddy Covariance °C

Despite the importance of mangrove ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these forests remain poorly understood. This limited understanding is partly a result of the challenges associated with in situ flux studies. Tower-based CO2 eddy covariance (EC) systems are installed in only a few mangrove forests worldwide, and the longest EC record from the Florida Everglades contains less than 9 years of observations. A primary goal of the present study was to develop a methodology to estimate canopy-scale photosynthetic light use efficiency in this forest. These tower-based observations represent a basis for associating CO2 fluxes with canopy light use properties, and thus provide the means for utilizing satellite-based reflectance data for larger scale investigations. We present a model for mangrove canopy light use efficiency utilizing the enhanced green vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that is capable of predicting changes in mangrove forest CO2 fluxes caused by a hurricane disturbance and changes in regional environmental conditions, including temperature and salinity. Model parameters are solved for in a Bayesian framework. The model structure requires estimates of ecosystem respiration (RE), and we present the first ever tower-based estimates of mangrove forest RE derived from nighttime CO2 fluxes. Our investigation is also the first to show the effects of salinity on mangrove forest CO2 uptake, which declines 5% per each 10 parts per thousand (ppt) increase in salinity. Light use efficiency in this forest declines with increasing daily photosynthetic active radiation, which is an important departure from the assumption of constant light use efficiency typically applied in satellite-driven models. The model developed here provides a framework for estimating CO2 uptake by these forests from reflectance data and information about environmental conditions.

Ecological Homogenization of Urban USA

A visually apparent but scientifically untested outcome of land-use change is homogenization across urban areas, where neighborhoods in different parts of the country have similar patterns of roads, residential lots, commercial areas, and aquatic features. We hypothesize that this homogenization extends to ecological structure and also to ecosystem functions such as carbon dynamics and microclimate, with continental-scale implications. Further, we suggest that understanding urban homogenization will provide the basis for understanding the impacts of urban land-use change from local to continental scales. Here, we show how multi-scale, multi-disciplinary datasets from six metropolitan areas that cover the major climatic regions of the US (Phoenix, AZ; Miami, FL; Baltimore, MD; Boston, MA; Minneapolis–St Paul, MN; and Los Angeles, CA) can be used to determine how household and neighborhood characteristics correlate with land-management practices, land-cover composition, and landscape structure and ecosystem functions at local, regional, and continental scales.

Lianas and soil nutrients predict fine-scale distribution of above-ground biomass in a tropical moist forest

Acknowledgements. This study was supported by the FP7-PEOPLE-2013-IEF Marie-Curie Action – SPATFOREST. Tree data from BCI were provided by the Center for Tropical Forest Science of the Smithsonian Tropical Research Institute and the primary granting agencies that have supported the BCI plot tree census. Data for the liana censuses were supported by the US National Science Foundation grants: DEB-0613666, DEB-0845071, and DEB-1019436 (to SAS). Soil data was funded by the National Science Foundation grants DEB021104, DEB021115, DEB0212284 and DEB0212818 supporting soils mapping in the BCI plot. We thank Helene Muller-Landau for providing some data on tree height for some BCI trees. We also thank all the people that contributed to obtain the data.

Microbial community composition shapes enzyme patterns in topsoil and subsoil horizons along a latitudinal transect in Western Siberia

Soil horizons below 30 cm depth contain about 60% of the organic carbon stored in soils. Although insight into the physical and chemical stabilization of soil organic matter (SUM) and into microbial community composition in these horizons is being gained, information on microbial functions of subsoil microbial communities and on associated microbially-mediated processes remains sparse. To identify possible controls on enzyme patterns, we correlated enzyme patterns with biotic and abiotic soil parameters, as well as with microbial community composition, estimated using phospholipid fatty acid profiles. Enzyme patterns (i.e. distance-matrixes calculated from these enzyme activities) were calculated from the activities of six extracellular enzymes (cellobiohydrolase, leucine-amino-peptidase, N-acetylglucosaminidase, chitotriosidase, phosphatase and phenoloxidase), which had been measured in soil samples from organic topsoil horizons, mineral topsoil horizons, and mineral subsoil horizons from seven ecosystems along a 1500 km latitudinal transect in Western Siberia. We found that hydrolytic enzyme activities decreased rapidly with depth, whereas oxidative enzyme activities in mineral horizons were as high as, or higher than in organic topsoil horizons. Enzyme patterns varied more strongly between ecosystems in mineral subsoil horizons than in organic topsoils. The enzyme patterns in topsoil horizons were correlated with SUM content (i.e., C and N content) and microbial community composition. In contrast, the enzyme patterns in mineral subsoil horizons were related to water content, soil pH and microbial community composition. The lack of correlation between enzyme patterns and SUM quantity in the mineral subsoils suggests that SOM chemistry, spatial separation or physical stabilization of SUM rather than SUM content might determine substrate availability for enzymatic breakdown. The correlation of microbial community composition and enzyme patterns in all horizons, suggests that microbial community composition shapes enzyme patterns and might act as a modifier for the usual dependency of decomposition rates on SUM content or C/N ratios. (C) 2015 The Authors. Published by Elsevier Ltd.

Dynamics deflection analysis of nanoelectromechanical switches based on carbon nanotubes

This paper aims to develop an effective numerical simulation technique for the dynamic deflection analysis of nanotubes-based nanoswitches. The nanoswitch is simplified to a continuum structure, and some key material parameters are extracted from typical molecular dynamics (MD). An advanced local meshless formulation is applied to obtain the discretized dynamic equations for the numerical solution. The developed numerical technique is firstly validated by the static deflection analyses of nanoswitches, and then, the fundamental dynamic properties of nanoswitches are analyzed. A parametric comparison with the results in the literature and from experiments shows that the developed modelling approach is accurate, efficient and effective.

Soil carbon saturation : implications for measurable carbon pool dynamics in long-term incubations

The efficiency of agricultural management practices to store SOC depends on C input level and how far a soil is from its saturation level (i.e. saturation deficit). The C Saturation hypothesis suggests an ultimate soil C stabilization capacity defined by four SOM pools capable of C saturation: (1) non-protected, (2) physically protected, (3) chemically protected and (4) biochemically protected. We tested if C saturation deficit and the amount of added C influenced SOC storage in measurable soil fractions corresponding to the conceptual chemical, physical, biochemical, and non-protected C pools. We added two levels of C-13- labeled residue to soil samples from seven agricultural sites that were either closer to (i.e., A-horizon) or further from (i.e., C-horizon) their C saturation level and incubated them for 2.5 years. Residue-derived C stabilization was, in most sites, directly related to C saturation deficit but mechanisms of C stabilization differed between the chemically and biochemically protected pools. The physically protected C pool showed a varied effect of C saturation deficit on C-13 stabilization, due to opposite behavior of the POM and mineral fractions. We found distinct behavior between unaggregated and aggregated mineral-associated fractions emphasizing the mechanistic difference between the chemically and physically protected C-pools. To accurately predict SOC dynamics and stabilization, C Saturation of soil C pools, particularly the chemically and biochemically protected pools, should be considered. (C) 2008 Elsevier Ltd. All rights reserved.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

Simulation of gas-phase nanoparticle dynamics in the plasma-enhanced chemical vapor deposition of carbon nanostructures

The results of 1D simulation of nanoparticle dynamics in the areas adjacent to nanostructured carbon-based films exposed to chemically active complex plasma of CH4 + H2 + Ar gas mixtures are presented. The nanoparticle-loaded near-substrate (including sheath and presheath) areas of a low-frequency (0.5 MHz) inductively coupled plasma facility for the PECVD growth of the ordered carbon-based nanotip structures are considered. The conditions allowing one to predict the size of particles that can pass through the plasma sheath and softly land onto the surface are formulated. The possibility of soft nano-cluster deposition without any additional acceleration common for some existing nano-cluster deposition schemes is demonstrated. The effect of the substrate heating power and the average atomic mass of neutral species is studied numerically and verified experimentally.

Self-organization and dynamics of nanoparticles in chemically active plasmas for low-temperature deposition of silicon and carbon-based nanostructured films

Self-organization and dynamic processes of nano/micron-sized solid particles grown in low-temperature chemically active plasmas as well as the associated physico-chemical processes are reviewed. Three specific reactive plasma chemistries, namely, of silane (SiH4), acetylene (C 2H2), and octafluorocyclobutane (c-C4F 8) RF plasma discharges for plasma enhanced chemical vapor deposition of amorphous hydrogenated silicon, hydrogenated and fluorinated carbon films, are considered. It is shown that the particle growth mechanisms and specific self-organization processes in the complex reactive plasma systems are related to the chemical organization and size of the nanoparticles. Correlation between the nanoparticle origin and self-organization in the ionized gas phase and improved thin film properties is reported. Self-organization and dynamic phenomena in relevant reactive plasma environments are studied for equivalent model systems comprising inert buffer gas and mono-dispersed organic particulate powders. Growth kinetics and dynamic properties of the plasma-assembled nanoparticles can be critical for the process quality in microelectronics as well as a number of other industrial applications including production of fine metal or ceramic powders, nanoparticle-unit thin film deposition, nanostructuring of substrates, nucleating agents in polymer and plastics synthesis, drug delivery systems, inorganic additives for sunscreens and UV-absorbers, and several others. Several unique properties of the chemically active plasma-nanoparticle systems are discussed as well.

Prediction of thermal expansion properties of carbon nanotubes using molecular dynamics simulations

The axial coefficients of thermal expansion (CTE) of various carbon nanotubes (CNTs), i.e., single-wall carbon nanotubes (SWCNTs), and some multi-wall carbon nanotubes (MWCNTs), were predicted using molecular dynamics (MDs) simulations. The effects of two parameters, i.e., temperature and the CNT diameter, on CTE were investigated extensively. For all SWCNTs and MWCNTs, the obtained results clearly revealed that within a wide low temperature range, their axial CTEs are negative. As the diameter of CNTs decreases, this temperature range for negative axial CTEs becomes narrow, and positive axial CTEs appear in high temperature range. It was found that the axial CTEs vary nonlinearly with the temperature, however, they decrease linearly as the CNT diameter increases. Moreover, within a wide temperature range, a set of empirical formulations was proposed for evaluating the axial CTEs of armchair and zigzag SWCNTs using the above two parameters. Finally, it was found that the absolute value of the negative axial CTE of any MWCNT is much smaller than those of its constituent SWCNTs, and the average value of the CTEs of its constituent SWCNTs. The present fundamental study is very important for understanding the thermal behaviors of CNTs in such as nanocomposite temperature sensors, or nanoelectronics devices using CNTs.

Formation of carbon nanoscrolls from graphene nanoribbons : a molecular dynamics study

Carbon nanoscrolls (CNSs) are one of the carbon-based nanomaterials similar to carbon nanotubes (CNTs) but are not widely studied in spite of their great potential applications. Their practical applications are hindered by the challenging fabrication of the CNSs. A physical approach has been proposed recently to fabricate the CNS by rolling up a monolayer graphene nanoribbon (GNR) around a CNT driven by the interaction energy between them. In this study, we perform extensive molecular dynamics (MD) simulations to investigate the various factors that impact the formation of the CNS from GNR. Our simulation results show that the formation of the CNS is sensitive to the length of the CNT and temperature. When the GNR is functionalized with hydrogen, the formation of the CNS is determined by the density and distribution of the hydrogen atoms. Graphyne, the allotrope of graphene, is inferior to graphene in the formation of the CNS due to the weaker bonds and the associated smaller atom density. The mechanism behind the rolling of GNR into CNS lies in the balance between the GNR–CNT van der Waals (vdW) interactions and the strain energy of GNR. The present work reveals new important insights and provides useful guidelines for the fabrication of the CNS.