Footprint of recycled water subsidies downwind of Lake Michigan

Continental evaporation is a significant and dynamic flux within the atmospheric water budget, but few methods provide robust observational constraints on the large-scale hydroclimatological and hydroecological impacts of this ‘recycled-water' flux. We demonstrate a geospatial analysis that provides such information, using stable isotope data to map the distribution of recycled water in shallow aquifers downwind from Lake Michigan. The δ2H and δ18O values of groundwater in the study region decrease from south to north, as expected based on meridional gradients in climate and precipitation isotope ratios. In contrast, deuterium excess (d = δ2H − 8 × δ18O) values exhibit a significant zonal gradient and finer-scale spatially patterned variation. Local d maxima occur in the northwest and southwest corners of the Lower Peninsula of Michigan, where ‘lake-effect' precipitation events are abundant. We apply a published model that describes the effect of recycling from lakes on atmospheric vapor d values to estimate that up to 32% of recharge into individual aquifers may be derived from recycled Lake Michigan water. Applying the model to geostatistical surfaces representing mean d values, we estimate that between 10% and 18% of the vapor evaporated from Lake Michigan is re-precipitated within downwind areas of the Lake Michigan drainage basin. Our approach provides previously unavailable observational constraints on regional land-atmosphere water fluxes in the Great Lakes Basin and elucidates patterns in recycled-water fluxes that may influence the biogeography of the region. As new instruments and networks facilitate enhanced spatial monitoring of environmental water isotopes, similar analyses can be widely applied to calibrate and validate water cycle models and improve projections of regional hydroecological change involving the coupled lake-atmosphere-land system. Read More: http://www.esajournals.org/doi/abs/10.1890/ES12-00062.1

Soil property and management effects on grassland microbial communities across a latitudinal gradient in Germany

There is much interest in the identification of the main drivers controlling changes in the microbial community that may be related to sustainable land use. We examined the influence of soil properties and land-use intensity (N fertilization, mowing, grazing) on total phospholipid fatty acid (PLFA) biomass, microbial community composition (PLFA profiles) and activities of enzymes involved in the C, N, and P cycle. These relationships were examined in the topsoil of grasslands from three German regions (Schorfheide-Chorin (SCH), Hainich-Dun (HAI), Schwabische Alb (ALB)) with different parent material. Differences in soil properties explained 60% of variation in PLFA data and 81% of variation in enzyme activities across regions and land-use intensities. Degraded peat soils in the lowland areas of the SCH with high organic carbon (OC) concentrations and sand content contained lower PLFA biomass, lower concentrations of bacterial, fungal, and arbuscular mycorrhizal PLFAs, but greater enzyme activities, and specific enzyme activities (per unit microbial biomass) than mineral soils in the upland areas of the HAI and ALB, which are finer textured, drier, and have smaller OC concentrations. After extraction of variation that originated from large-scale differences among regions and differences in land-use intensities between plots, soil properties still explained a significant amount of variation in PLFA data (34%) and enzyme activities (60%). Total PLFA biomass and all enzyme activities were mainly related to OC concentration, while relative abundance of fungi and fungal to bacterial ratio were mainly related to soil moisture. Land-use intensity (LUI) significantly decreased the soil C:N ratio. There was no direct effect of LUI on total PLFA biomass, microbial community composition, N and P cycling enzyme activities independent of study region and soil properties. In contrast, the activities and specific activities of enzymes involved in the C cycle increased significantly with LUI independent of study region and soil properties, which can have impact on soil organic matter decomposition and nutrient cycling. Our findings demonstrate that microbial biomass and community composition as well as enzyme activities are more controlled by soil properties than by grassland management at the regional scale. (C) 2013 Elsevier B.V: All rights reserved.

Clinical outcomes of patients with low-flow, low-gradient, severe aortic stenosis and either preserved or reduced ejection fraction undergoing transcatheter aortic valve implantation

AIMS Our aim was to evaluate the invasive haemodynamic indices of high-risk symptomatic patients presenting with 'paradoxical' low-flow, low-gradient, severe aortic stenosis (AS) (PLF-LG) and low-flow, low-gradient severe AS (LEF-LG) and to compare clinical outcomes following transcatheter aortic valve implantation (TAVI) among these challenging AS subgroups. METHODS AND RESULTS Of 534 symptomatic patients undergoing TAVI, 385 had a full pre-procedural right and left heart catheterization. A total of 208 patients had high-gradient severe AS [HGAS; mean gradient (MG) ≥40 mmHg], 85 had PLF-LG [MG ≤ 40 mmHg, indexed aortic valve area [iAVA] ≤0.6 cm(2) m(-2), stroke volume index ≤35 mL/m(2), ejection fraction (EF) ≥50%], and 61 had LEF-LG (MG ≤ 40 mmHg, iAVA ≤0.6 cm(2) m(-2), EF ≤40%). Compared with HGAS, PLF-LG and LEF-LG had higher systemic vascular resistances (HGAS: 1912 ± 654 vs. PLF-LG 2006 ± 586 vs. LEF-LG 2216 ± 765 dyne s m(-5), P = 0.007) but lower valvulo-arterial impedances (HGAS: 7.8 ± 2.7 vs. PLF-LG 6.9 ± 1.9 vs. LEF-LG 7.7 ± 2.5 mmHg mL(-1) m(-2), P = 0.027). At 30 days, no differences in cardiac death (6.5 vs. 4.9 vs. 6.6%, P = 0.90) or death (8.4 vs. 6.1 vs. 6.6%, P = 0.88) were observed among HGAS, PLF-LG, and LEF-LG groups, respectively. At 1 year, New York Heart Association functional improvement occurred in most surviving patients (HGAS: 69.2% vs. PLF-LG 71.7% vs. LEF-LG 89.3%, P = 0.09) and no significant differences in overall mortality were observed (17.6 vs. 20.5 vs. 24.5%, P = 0.67). Compared with HGAS, LEF-LG had a higher 1 year cardiac mortality (adjusted hazard ratio 2.45, 95% confidence interval 1.04-5.75, P = 0.04). CONCLUSION TAVI in PLF-LG or LEF-LG patients is associated with overall mortality rates comparable with HGAS patients and all groups profit symptomatically to a similar extent.

Secondary Forests and Local Livelihoods along a Gradient of Accessibility: A Case Study in Northern Laos

Rural livelihoods in developing countries can be enhanced by improving access to natural resources, services, and markets. In remote rural areas of the humid or semihumid tropics, forests represent an important resource for livelihoods. In countries like Laos, where most primary forest has been converted to secondary forest, and where an intricate and interlinked mosaic of forest and farmland prevails, people depend on secondary forests as a prime source of goods and services. The linkages between local livelihoods and secondary forest resources are subject to changes caused by improving accessibility. This article studies how accessibility affects the condition of forests and local livelihoods by comparing three villages along a gradient of accessibility in Phonxay district, Luang Prabang province, northern Laos. The results of this research show that accessibility strengthens the influence of the government and of markets, and that local livelihoods improve with increasing accessibility, while forest condition deteriorates.

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.

Topoclimatological case-study of Alpine pastures near the Albula Pass in the eastern Swiss Alps

Alpine grasslands are an important source of fodder for the cattle of Alpine farmers. Only during the short summer season can these pastures be used for grazing. With the anticipated climate change, it is likely that plant production – and thus the fodder basis for the cattle – will be influenced. Investigating the dependence of biomass production on topoclimatic factors will allow us to better understand how anticipated climate change may influence this traditional Alpine farming system. Because small-scale topoclimatological variations of the main meteorological variables: temperature, humidity, precipitation, shortwave incoming radiation and wind speed are not easily derived from available long-term climate stations in mountainous terrain, it was our goal to investigate the topoclimatic variations over the pastures belonging to the Alp Weissenstein research station north of the Albula Pass in the eastern Swiss Alps. We present a basic assessment of current topoclimatic conditions as a site characterization for ongoing ecological climate change studies. To be able to link short-term studies with long-term climate records, we related agrometeorological measurements with those of surrounding long-term sites run by MeteoSwiss, both on valley bottoms (Davos, Samedan), and on mountain tops (Weissfluhjoch, Piz Corvatsch). We found that the Davos climate station north of the study area is most closely correlated with the local climate of Alp Weissenstein, although a much closer site (Samedan) exists on the other side of the Albula Pass. Mountain top stations, however, did not provide a convincing approximation for the climate at Alp Weissenstein. Direct comparisons of near-surface measurements from a set of 11 small weather stations distributed over the domain where cattle and sheep are grazed indicate that nocturnal minimum air temperature and minimum vapor pressure deficit are mostly governed by the altitudinal gradient, whereas daily maxima – including also wind speed – are more strongly depending on vegetation cover and less on the altitude.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Identification of the Causative Bacteria in Musculoskeletal Infections Using 16s rDNA - Denaturing Gradient Gel Electrophoresis Analysis

Musculoskeletal infections are infections of the bone and surrounding tissues. They are currently diagnosed based on culture analysis, which is the gold standard for pathogen identification. However, these clinical laboratory methods are frequently inadequate for the identification of the causative agents, because a large percentage (25-50%) of confirmed musculoskeletal infections are false negatives in which no pathogen is identified in culture. My data supports these results. The goal of this project was to use PCR amplification of a portion of the 16S rRNA gene to test an alternative approach for the identification of these pathogens and to assess the diversity of the bacteria involved. The advantages of this alternative method are that it should increase sample sensitivity and the speed of detection. In addition, bacteria that are non-culturable or in low abundance can be detected using this molecular technique. However, a complication of this approach is that the majority of musculoskeletal infections are polymicrobial, which prohibits direct identification from the infected tissue by DNA sequencing of the initial 16S rDNA amplification products. One way to solve this problem is to use denaturing gradient gel electrophoresis (DGGE) to separate the PCR products before DNA sequencing. Denaturing gradient gel electrophoresis (DGGE) separates DNA molecules based on their melting point, which is determined by their DNA sequence. This analytical technique allows a mixture of PCR products of the same length that electrophoreses through agarose gels as one band, to be separated into different bands and then used for DNA sequence analysis. In this way, the DGGE allows for the identification of individual bacterial species in polymicrobial-infected tissue, which is critical for improving clinical outcomes. By combining the 16S rDNA amplification and the DGGE techniques together, an alternative approach for identification has been used. The 16S rRNA gene PCR-DGGE method includes several critical steps: DNA extraction from tissue biopsies, amplification of the bacterial DNA, PCR product separation by DGGE, amplification of the gel-extracted DNA, and DNA sequencing and analysis. Each step of the method was optimized to increase its sensitivity and for rapid detection of the bacteria present in human tissue samples. The limit of detection for the DNA extraction from tissue was at least 20 Staphylococcus aureus cells and the limit of detection for PCR was at least 0.05 pg of template DNA. The conditions for DGGE electrophoreses were optimized by using a double gradient of acrylamide (6 – 10%) and denaturant (30-70%), which increased the separation between distinct PCR products. The use of GelRed (Biotium) improved the DNA visualization in the DGGE gel. To recover the DNA from the DGGE gels the gel slices were excised, shredded in a bead beater, and the DNA was allowed to diffuse into sterile water overnight. The use of primers containing specific linkers allowed the entire amplified PCR product to be sequenced and then analyzed. The optimized 16S rRNA gene PCR-DGGE method was used to analyze 50 tissue biopsy samples chosen randomly from our collection. The results were compared to those of the Memorial Hermann Hospital Clinical Microbiology Laboratory for the same samples. The molecular method was congruent for 10 of the 17 (59%) culture negative tissue samples. In 7 of the 17 (41%) culture negative the molecular method identified a bacterium. The molecular method was congruent with the culture identification for 7 of the 33 (21%) positive cultured tissue samples. However, in 8 of the 33 (24%) the molecular method identified more organisms. In 13 of the 15 (87%) polymicrobial cultured tissue samples the molecular method identified at least one organism that was also identified by culture techniques. Overall, the DGGE analysis of 16S rDNA is an effective method to identify bacteria not identified by culture analysis.

Tree growth response along an elevational gradient: climate or genetics?

Environment and genetics combine to influence tree growth and should therefore be jointly considered when evaluating forest responses in a warming climate. Here, we combine dendroclimatology and population genetic approaches with the aim of attributing climatic influences on growth of European larch (Larix decidua) and Norway spruce (Picea abies). Increment cores and genomic DNA samples were collected from populations along a ~900-m elevational transect where the air temperature gradient encompasses a ~4 °C temperature difference. We found that low genetic differentiation among populations indicates gene flow is high, suggesting that migration rate is high enough to counteract the selective pressures of local environmental variation. We observed lower growth rates towards higher elevations and a transition from negative to positive correlations with growing season temperature upward along the elevational transect. With increasing elevation there was also a clear increase in the explained variance of growth due to summer temperatures. Comparisons between climate sensitivity patterns observed along this elevational transect with those from Larix and Picea sites distributed across the Alps reveal good agreement, and suggest that tree-ring width (TRW) variations are more climate-driven than genetics-driven at regional and larger scales. We conclude that elevational transects are an extremely valuable platform for understanding climatic-driven changes over time and can be especially powerful when working within an assessed genetic framework.

Recent trends in Inner Asian forest dynamics to temperature and precipitation indicate high sensitivity to climate change

Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO2. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area ‘browning’ during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prior-year lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO2 causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO2 fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO2 fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.

Precipitation over the past four centuries in the Dieshan Mountains as inferred from tree rings: An introduction to an HHT-based method

To improve our understanding of the Asian monsoon system, we developed a hydroclimate reconstruction in a marginal monsoon shoulder region for the period prior to the industrial era. Here, we present the first moisture sensitive tree-ring chronology, spanning 501 years for the Dieshan Mountain area, a boundary region of the Asian summer monsoon in the northeastern Tibetan Plateau. This reconstruction was derived from 101 cores of 68 old-growth Chinese pine (Pinus tabulaeformis) trees. We introduce a Hilbert–Huang Transform (HHT) based standardization method to develop the tree-ring chronology, which has the advantages of excluding non-climatic disturbances in individual tree-ring series. Based on the reliable portion of the chronology, we reconstructed the annual (prior July to current June) precipitation history since 1637 for the Dieshan Mountain area and were able to explain 41.3% of the variance. The extremely dry years in this reconstruction were also found in historical documents and are also associated with El Niño episodes. Dry periods were reconstructed for 1718–1725, 1766–1770 and 1920–1933, whereas 1782–1788 and 1979–1985 were wet periods. The spatial signatures of these events were supported by data from other marginal regions of the Asian summer monsoon. Over the past four centuries, out-of-phase relationships between hydroclimate variations in the Dieshan Mountain area and far western Mongolia were observed during the 1718–1725 and 1766–1770 dry periods and the 1979–1985 wet period.

Influence of the background wind on the local soil moisture-precipitation feedback

The importance of soil moisture anomalies on airmass convection over semiarid regions has been recognized in several studies. The underlying mechanisms remain partly unclear. An open question is why wetter soils can result in either an increase or a decrease of precipitation (positive or negative soil moisture–precipitation feedback, respectively). Here an idealized cloud-resolving modeling framework is used to explore the local soil moisture–precipitation feedback. The approach is able to replicate both positive and negative feedback loops, depending on the environmental parameters. The mechanism relies on horizontal soil moisture variations, which may develop and intensify spontaneously. The positive expression of the feedback is associated with the initiation of convection over dry soil patches, but the convective cells then propagate over wet patches where they strengthen and preferentially precipitate. The negative feedback may occur when the wind profile is too weak to support the propagation of convective features from dry to wet areas. Precipitation is then generally weaker and falls preferentially over dry patches. The results highlight the role of the midtropospheric flow in determining the sign of the feedback. A key element of the positive feedback is the exploitation of both low convective inhibition (CIN) over dry patches (for the initiation of convection) and high CAPE over wet patches (for the generation of precipitation).

Oxygen isotope ratios (18O/16O) of hemicellulose-derived sugar biomarkers in plants, soils and sediments as paleoclimate proxy II: insight from a climate transect study

The oxygen isotopic composition of precipitation (δ18Oprec) is well known to be a valuable (paleo-)climate proxy. Paleosols and sediments and hemicelluloses therein have the potential to serve as archives recording the isotopic composition of paleoprecipitation. In a companion paper (Zech et al., 2014) we investigated δ18Ohemicellulose values of plants grown under different climatic conditions in a climate chamber experiment. Here we present results of compound-specific δ18O analyses of arabinose, fucose and xylose extracted from modern topsoils (n = 56) along a large humid-arid climate transect in Argentina in order to answer the question whether hemicellulose biomarkers in soils reflect δ18Oprec. The results from the field replications indicate that the homogeneity of topsoils with regard to δ18Ohemicellulose is very high for most of the 20 sampling sites. Standard deviations for the field replications are 1.5‰, 2.2‰ and 1.7‰, for arabinose, fucose and xylose, respectively. Furthermore, all three hemicellulose biomarkers reveal systematic and similar trends along the climate gradient. However, the δ18Ohemicellulose values (mean of the three sugars) do not correlate positively with δ18Oprec (r = −0.54, p < 0.014, n = 20). By using a Péclet-modified Craig-Gordon (PMCG) model it can be shown that the δ18Ohemicellulose values correlate highly significantly with modeled δ18Oleaf water values (r = 0.81, p < 0.001, n = 20). This finding suggests that hemicellulose biomarkers in (paleo-)soils do not simply reflect δ18Oprec but rather δ18Oprec altered by evaporative 18O enrichment of leaf water due to evapotranspiration. According to the modeling results, evaporative 18O enrichment of leaf water is relatively low (∼10‰) in the humid northern part of the Argentinian transect and much higher (up to 19‰) in the arid middle and southern part of the transect. Model sensitivity tests corroborate that changes in relative air humidity exert a dominant control on evaporative 18O enrichment of leaf water and thus δ18Ohemicellulose, whereas the effect of temperature changes is of minor importance. While oxygen exchange and degradation effects seem to be negligible, further factors needing consideration when interpreting δ18Ohemicellulose values obtained from (paleo-)soils are evaporative 18O enrichment of soil water, seasonality effects, wind effects and in case of abundant stem/root-derived organic matter input a partial loss of the evaporative 18O enrichment of leaf water. Overall, our results prove that compound-specific δ18O analyses of hemicellulose biomarkers in soils and sediments are a promising tool for paleoclimate research. However, disentangling the two major factors influencing δ18Ohemicellulose, namely δ18Oprec and relative air humidity controlled evaporative 18O enrichment of leaf water, is challenging based on δ18O analyses alone.