First description of Candida nivariensis in Brazil: antifungal susceptibility profile and potential virulence attributes

This study evaluated the antifungal susceptibility profile and the production of potential virulence attributes in a clinical strain of Candida nivariensis for the first time in Brazil, as identified by sequencing the internal transcribed spacer (ITS)1-5.8S-ITS2 region and D1/D2 domains of the 28S of the rDNA. For comparative purposes, tests were also performed with reference strains. All strains presented low planktonic minimal inhibitory concentrations (PMICs) to amphotericin B (AMB), caspofungin (CAS), and voriconazole. However, our strain showed elevated planktonic MICs to posaconazole (POS) and itraconazole, in addition to fluconazole resistance. Adherence to inert surfaces was conducted onto glass and polystyrene. The biofilm formation and antifungal susceptibility on biofilmgrowing cells were evaluated by crystal violet staining and a XTT reduction assay. All fungal strains were able to bind both tested surfaces and form biofilm, with a binding preference to polystyrene (p < 0.001). AMB promoted significant reductions (≈50%) in biofilm production by our C. nivariensis strain using both methodologies. This reduction was also observed for CAS and POS, but only in the XTT assay. All strains were excellent protease producers and moderate phytase producers, but lipases were not detected. This study reinforces the pathogenic potential of C. nivariensis and its possible resistance profile to the azolic drugs generally used for candidiasis management.

Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data.

Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems using airborne lidar data. Focusing on an agroforestry system in the Brazilian Amazon, this study first predicted plot-level AGB using fixed-effects regression models that assumed the regression coefficients to be constants. The model prediction errors were then analyzed from the perspectives of tree DBH (diameter at breast height)?height relationships and plot-level wood density, which suggested the need for stratifying agroforestry fields to improve plot-level AGB modeling. We separated teak plantations from other agroforestry types and predicted AGB using mixed-effects models that can incorporate the variation of AGB-height relationship across agroforestry types. We found that, at the plot scale, mixed-effects models led to better model prediction performance (based on leave-one-out cross-validation) than the fixed-effects models, with the coefficient of determination (R2) increasing from 0.38 to 0.64. At the landscape level, the difference between AGB densities from the two types of models was ~10% on average and up to ~30% at the pixel level. This study suggested the importance of stratification based on tree AGB allometry and the utility of mixed-effects models in modeling and mapping AGB of agroforestry systems.

Balancing the environmental benefits of reforestation in agricultural regions

Reforestation is an important tool for reducing or reversing biodiversity loss and mitigating climate change. However, there are many potential compromises between the structural (biodiversity) and functional (carbon sequestration and water yield) effects of reforestation, which can be affected by decisions on spatial design and establishment of plantings. We review the environmental responses to reforestation and show that manipulating the configuration of plantings (location, size, species mix and tree density) increases a range of environmental benefits. More extensive tree plantings (>10. ha) provide more habitat, and greater improvements to carbon and water cycling. Planting a mixture of native trees and shrubs is best for biodiversity, while traditional plantation species, generally non-native species, sequester C faster. Tree density can be manipulated at planting or during early development to accelerate structural maturity and to manage water yields. A diversity of habitats will be created by planting in a variety of landscape positions and by emulating the patchy distribution of forest types, which characterized many regions prior to extensive landscape transformation. Areas with shallow aquifers can be planted to reduce water pollution or avoided to maintain water yields. Reforestation should be used to build forest networks that are surrounded by low-intensity land use and that provide links within regions and between biomes. While there are adequate models for C sequestration and changes in water yields after reforestation, the quantitative understanding of changes in habitat resources and species composition is more limited. Development of spatial and temporal modelling platforms based on empirical models of structural and functional outcomes of reforestation is essential for deciding how to reconfigure agricultural regions. To build such platforms, we must quantify: (a) the influence of previous land uses, establishment methods, species mixes and interactions with adjacent land uses on environmental (particularly biodiversity) outcomes of reforestation and (b) the ways in which responses measured at the level of individual plantings scale up to watersheds and regions. Models based on this information will help widespread reforestation for carbon sequestration to improve native biodiversity, nutrient cycling and water balance at regional scales.

Riparian reforestation: are there changes in soil carbon and soil microbial communities?

Reforestation of pastures in riparian zones has the potential to decrease nutrient runoff into waterways, provide both terrestrial and aquatic habitat, and help mitigate climate change by sequestering carbon (C). Soil microbes can play an important role in the soil C cycle, but are rarely investigated in studies on C sequestration. We surveyed a chronosequence (0-23years) of mixed-species plantings in riparian zones to investigate belowground (chemical and biological) responses to reforestation. For each planting, an adjacent pasture was surveyed to account for differences in soil type and land-use history among plantings. Two remnant woodlands were included in the survey as indicators of future potential of plantings. Both remnant woodlands had significantly higher soil organic C (SOC) content compared with their adjacent pastures. However, there was no clear trend in SOC content among plantings with time since reforestation. The substantial variability in SOC sequestration among plantings was possibly driven by differences in soil moisture among plantings and the inherent variability of SOC content among reference pastures adjacent to plantings. Soil microbial phospholipid fatty acids (PLFA, an indicator of microbial biomass) and activities of decomposition enzymes (β-glucosidase and polyphenol oxidase) did not show a clear trend with increasing planting age. Despite this, there were positive correlations between total SOC concentration and microbial indicators (total PLFA, fungal PLFA, bacterial PLFA and activities of decomposition enzymes) across all sites. The soil microbial community compositions (explored using PLFA markers) of older plantings were similar to those of remnant woodlands. There was a positive correlation between the soil carbon:nitrogen (C:N) and fungal:bacterial (F:B) ratios. These data indicate that in order to maximise SOC sequestration, we need to take into account not only C inputs, but the microbial processes that regulate SOC cycling as well.

Soil carbon saturation: Linking concept and measurable carbon pools

The soil C saturation concept suggests a limit to whole soil organic carbon (SOC) accumulation determined by inherent physicochemical characteristics of four soil C pools: unprotected, physically protected, chemically protected, and biochemically protected. Previous attempts to quantify soil C sequestration capacity have focused primarily on silt and clay protection and largely ignored the effects of soil structural protection and biochemical protection. We assessed two contrasting models of SOC accumulation, one with no saturation limit (i.e., linear first-order model) and one with an explicit soil C saturation limit (i.e., C saturation model). We isolated soil fractions corresponding to the C pools (i.e., free particulate organic matter POM], microaggregate-associated C, silt- and clay-associated C, and non-hydrolyzable C) from eight long-term agroecosystern experiments across the United States and Canada. Due to the composite nature of the physically protected C pool, we firactioned it into mineral- vs. POM-associated C. Within each site, the number of fractions fitting the C saturation model was directly related to maximum SOC content, suggesting that a broad range in SOC content is necessary to evaluate fraction C saturation. The two sites with the greatest SOC range showed C saturation behavior in the chemically, biochemically, and some mineral-associated fractions of the physically protected pool. The unprotected pool and the aggregate-protected POM showed linear, nonsaturating behavior. Evidence of C saturation of chemically and biochemically protected SOC pools was observed at sites far from their theoretical C saturation level, while saturation of aggregate-protected fractions occurred in soils closer to their C saturation level.

Land use effects on soil carbon fractions in the southeastern United States. II. changes in soil carbon fractions along a forest to pasture chronosequence

Since land use change can have significant impacts on regional biogeochemistry, we investigated how conversion of forest and cultivation to pasture impact soil C and N cycling. In addition to examining total soil C, we isolated soil physiochemical C fractions in order to understand the mechanisms by which soil C is sequestered or lost. Total soil C did not change significantly over time following conversion from forest, though coarse (250-2,000 mum) particulate organic matter C increased by a factor of 6 immediately after conversion. Aggregate mean weight diameter was reduced by about 50% after conversion, but values were like those under forest after 8 years under pasture. Samples collected from a long-term pasture that was converted from annual cultivation more than 50 years ago revealed that some soil physical properties negatively impacted by cultivation were very slow to recover. Finally, our results indicate that soil macroaggregates turn over more rapidly under pasture than under forest and are less efficient at stabilizing soil C, whereas microaggregates from pasture soils stabilize a larger concentration of C than forest microaggregates. Since conversion from forest to pasture has a minimal impact on total soil C content in the Piedmont region of Virginia, United States, a simple C stock accounting system could use the same base soil C stock value for either type of land use. However, since the effects of forest to pasture conversion are a function of grassland management following conversion, assessments of C sequestration rates require activity data on the extent of various grassland management practices.

Spatial variability of soil organic carbon in grasslands: implications for detecting change at different scales

Extensive data used to quantify broad soil C changes (without information about causation), coupled with intensive data used for attribution of changes to specific management practices, could form the basis of an efficient national grassland soil C monitoring network. Based on variability of extensive (USDA/NRCS pedon database) and intensive field-level soil C data, we evaluated the efficacy of future sample collection to detect changes in soil C in grasslands. Potential soil C changes at a range of spatial scales related to changes in grassland management can be verified (alpha=0.1) after 5 years with collection of 34, 224, 501 samples at the county, state, or national scales, respectively. Farm-level analysis indicates that equivalent numbers of cores and distinct groups of cores (microplots) results in lowest soil C coefficients of variation for a variety of ecosystems. Our results suggest that grassland soil C changes can be precisely quantified using current technology at scales ranging from farms to the entire nation. (C) 2001 Elsevier Science Ltd. All rights reserved.

Measuring and monitoring soil organic carbon stocks in agricultural lands for climate mitigation

Policies that encourage greenhouse-gas emitters to mitigate emissions through terrestrial carbon (C) offsets – C sequestration in soils or biomass – will promote practices that reduce erosion and build soil fertility, while fostering adaptation to climate change, agricultural development, and rehabilitation of degraded soils. However none of these benefits will be possible until changes in C stocks can be documented accurately and cost-effectively. This is particularly challenging when dealing with changes in soil organic C (SOC) stocks. Precise methods for measuring C in soil samples are well established, but spatial variability in the factors that determine SOC stocks makes it difficult to document change. Widespread interest in the benefits of SOC sequestration has brought this issue to the fore in the development of US and international climate policy. Here, we review the challenges to documenting changes in SOC stocks, how policy decisions influence offset documentation requirements, and the benefits and drawbacks of different sampling strategies and extrapolation methods.

Evaluation of the relationship between Chlamydia pecorum sequence types and disease using a species-specific multi-locus sequence typing scheme (MLST)

Chlamydia pecorum is globally associated with several ovine diseases including keratoconjunctivitis and polyarthritis. The exact relationship between the variety of C. pecorum strains reported and the diseases described in sheep remains unclear, challenging efforts to accurately diagnose and manage infected flocks. In the present study, we applied C. pecorum multi-locus sequence typing (MLST) to C. pecorum positive samples collected from sympatric flocks of Australian sheep presenting with conjunctivitis, conjunctivitis with polyarthritis, or polyarthritis only and with no clinical disease (NCD) in order to elucidate the exact relationships between the infecting strains and the range of diseases. Using Bayesian phylogenetic and cluster analyses on 62 C. pecorum positive ocular, vaginal and rectal swab samples from sheep presenting with a range of diseases and in a comparison to C. pecorum sequence types (STs) from other hosts, one ST (ST 23) was recognised as a globally distributed strain associated with ovine and bovine diseases such as polyarthritis and encephalomyelitis. A second ST (ST 69) presently only described in Australian animals, was detected in association with ovine as well as koala chlamydial infections. The majority of vaginal and rectal C. pecorum STs from animals with NCD and/or anatomical sites with no clinical signs of disease in diseased animals, clustered together in a separate group, by both analyses. Furthermore, 8/13 detected STs were novel. This study provides a platform for strain selection for further research into the pathogenic potential of C. pecorum in animals and highlights targets for potential strain-specific diagnostic test development.

Characterization of tree-to-tree variation in morphological, nutritional and medicinal properties of Canarium indicum nuts

As part of a feasibility study of the commercialization potential of C. indicum nuts as Agroforestry Tree Products in Papua New Guinea, preliminary characterization studies have examined the tree-to-tree variation in morphological traits (nut and kernel mass and kernel:nut ratio), as well as nutritional (carbohydrate, fat, protein, sodium, vitamin E) and medicinal traits (anti-oxidant activity, anti-inflammatory activity and phenolic content) of kernels from 18 to 72 trees in a small number of different villages of Papua New Guinea (East New Britain Province). There was continuous variation in these traits indicating opportunities for multiple trait cultivar development targeted at food and pharmaceutical markets. Certain traits, for example anti-inflammatory activity, in which tree-to-tree variation was highly significant, present greater opportunities than others, such as saturated:unsaturated fatty acid ratio. This intraspecific variation was greater within populations than between populations. The data presented has allowed the development of a strategy to domesticate C. indicum for cultivation in homegardens and cocoa-coconut agroforests, using a participatory approach aimed at the production of agroforestry tree products (AFTPs) to empower small-holders and enhance their livelihoods and income.

Test and develop sustainable and profitable grazing strategies to manage for rainfall variability

The Wambiana grazing trial started in 1997 to test and develop sustainable and profitable grazing strategies to manage for rainfall variability. It is important that this trial continue as the results are still relatively short-term relative to rainfall cycles and significant treatment changes are still occurring. This new proposal will maintain baseline treatments but will modify others based on trial learning’s to date. It builds on treatment differences and evidence collected over the last 12 years to deliver evidence-based guidelines and principles for sustainable and productive management. The trial also links to other projects modelling water quality, climate change, methane emissions and soil C sequestration on grazing lands.

Soil carbon stock in the tropical rangelands of Australia: Effects of soil type and grazing pressure, and determination of sampling requirement.

On-going, high-profile public debate about climate change has focussed attention on how to monitor the soil organic carbon stock (C(s)) of rangelands (savannas). Unfortunately, optimal sampling of the rangelands for baseline C(s) - the critical first step towards efficient monitoring - has received relatively little attention to date. Moreover, in the rangelands of tropical Australia relatively little is known about how C(s) is influenced by the practice of cattle grazing. To address these issues we used linear mixed models to: (i) unravel how grazing pressure (over a 12-year period) and soil type have affected C(s) and the stable carbon isotope ratio of soil organic carbon (delta(13)C) (a measure of the relative contributions of C(3) and C(4) vegetation to C(s)); (ii) examine the spatial covariation of C(s) and delta(13)C; and, (iii) explore the amount of soil sampling required to adequately determine baseline C(s). Modelling was done in the context of the material coordinate system for the soil profile, therefore the depths reported, while conventional, are only nominal. Linear mixed models revealed that soil type and grazing pressure interacted to influence C(s) to a depth of 0.3 m in the profile. At a depth of 0.5 m there was no effect of grazing on C(s), but the soil type effect on C(s) was significant. Soil type influenced delta(13)C to a soil depth of 0.5 m but there was no effect of grazing at any depth examined. The linear mixed model also revealed the strong negative correlation of C(s) with delta(13)C, particularly to a depth of 0.1 m in the soil profile. This suggested that increased C(s) at the study site was associated with increased input of C from C(3) trees and shrubs relative to the C(4) perennial grasses; as the latter form the bulk of the cattle diet, we contend that C sequestration may be negatively correlated with forage production. Our baseline C(s) sampling recommendation for cattle-grazing properties of the tropical rangelands of Australia is to: (i) divide the property into units of apparently uniform soil type and grazing management; (ii) use stratified simple random sampling to spread at least 25 soil sampling locations about each unit, with at least two samples collected per stratum. This will be adequate to accurately estimate baseline mean C(s) to within 20% of the true mean, to a nominal depth of 0.3 m in the profile.

Fen ecosystem carbon gas dynamics in changing hydrological conditions

Northern peatlands are thought to store one third of all soil carbon (C). Besides the C sink function, peatlands are one of the largest natural sources of methane (CH4) to the atmosphere. Climate change may affect the C gas dynamics as well as the labile C pool. Because the peatland C sequestration and CH4 emissions are governed by high water levels, changes in hydrology are seen as the driving factor in peatland ecosystem change. This study aimed to quantify the carbon dioxide (CO2) and CH4 dynamics of a fen ecosystem at different spatial scales: plant community components scale, plant community scale and ecosystem scale, under hydrologically normal and water level drawdown conditions. C gas exchange was measured in two fens in southern Finland applying static chamber and eddy covariance techniques. During hydrologically normal conditions, the ecosystem was a CO2 sink and CH4 source to the atmosphere. Sphagnum mosses and sedges were the most important contributors to the community photosynthesis. The presence of sedges had a major positive impact on CH4 emissions while dwarf shrubs had a slightly attenuating impact. C fluxes varied considerably between the plant communities. Therefore, their proportions determined the ecosystem scale fluxes. An experimental water level drawdown markedly reduced the photosynthesis and respiration of sedges and Sphagnum mosses and benefited shrubs. Consequently, changes were smaller at the ecosystem scale than at the plant group scale. The decrease in photosynthesis and the increase in respiration, mostly peat respiration, made the fen a smaller CO2 sink. CH4 fluxes were significantly lowered, close to zero. The impact of natural droughts was similar to, although more modest than, the impact of the experimental water level drawdown. The results are applicable to the short term impacts of the water level drawdown and to climatic conditions in which droughts become more frequent.

Invariant norm quantifying nonlinear content of Hamiltonian systems

Given a Hamiltonian system, one can represent it using a symplectic map. This symplectic map is specified by a set of homogeneous polynomials which are uniquely determined by the Hamiltonian. In this paper, we construct an invariant norm in the space of homogeneous polynomials of a given degree. This norm is a function of parameters characterizing the original Hamiltonian system. Such a norm has several potential applications. (C) 2010 Elsevier Inc. All rights reserved.

Mesoporous Carbon and Poly(3,4-ethylenedioxythiophene) Composite as Catalyst Support for Polymer Electrolyte Fuel Cells

In situ polymerization of 3,4-ethylenedioxythiophene with sol-gel-derived mesoporous carbon (MC) leading to a new composite and its subsequent impregnation with Pt nanoparticles for application in polymer electrolyte fuel cells (PEFCs) is reported. The composite exhibits good dispersion and utilization of platinum nanoparticles akin to other commonly used microporous carbon materials, such as carbon black. Pt-supported MC-poly(3,4-ethylenedioxythiophene) (PEDOT) composite also exhibits promising electrocatalytic activity toward oxygen reduction reaction, which is central to PEFCs. The PEFC with Pt-loaded MC-PEDOT support exhibits 75% of enhancement in its power density in relation to the PEFC with Pt-loaded pristine MC support while operating under identical conditions. It is conjectured that Pt-supported MC-PEDOT composite ameliorates PEFC performance/durability on repetitive potential cycling. (C) 2010 The Electrochemical Society. DOI: 10.1149/1.3486172] All rights reserved.