Uncovering further diversity of Ochoterenatrema Caballero, 1943 (Digenea: Lecithodendriidae) in South American bats.

Ochoterenatrema Caballero, 1943 is a genus of lecithodendriid digeneans that prior to this study included 8 species parasitic in bats in the Western Hemisphere. Species of Ochoterenatrema possess a unique morphological feature in form of the pseudogonotyl on the sinistral side of the ventral sucker. In this study, we describe 2 new species of Ochoterenatrema from bats in Ecuador. The new species are readily differentiated from their congeners by a combination of morphological characters, including the distribution of vitelline follicles, length of oesophagus, sucker ratio and the body shape, among other features. We have generated partial nuclear 28S rDNA and mitochondrial cox1 gene DNA sequences from both new species. The newly obtained sequences were used to differentiate among species and study the phylogenetic interrelationships among Ochoterenatrema spp. The internal topology of the clade was weakly supported, although the cox1 tree was much better resolved than the 28S tree. Comparison of sequences revealed 0-1.2% interspecific divergence in 28S and 3.3-20.5% interspecific divergence in cox1 among Ochoterenatrema spp. The new findings demonstrate that bats in South America likely harbor multiple additional undescribed species of Ochoterenatrema. More extensive sampling from broader geographic and host ranges, especially in North America, should allow for a better understanding of the evolution of host associations and morphological traits of this lineage of lecithodendriid digeneans.

Global rainfall erosivity database (GloREDa) and monthly R-factor data at 1 km spatial resolution.

Here, we present and release the Global Rainfall Erosivity Database (GloREDa), a multi-source platform containing rainfall erosivity values for almost 4000 stations globally. The database was compiled through a global collaboration between a network of researchers, meteorological services and environmental organisations from 65 countries. GloREDa is the first open access database of rainfall erosivity (R-factor) based on hourly and sub-hourly rainfall records at a global scale. This database is now stored and accessible for download in the long-term European Soil Data Centre (ESDAC) repository of the European Commission's Joint Research Centre. This will ensure the further development of the database with insertions of new records, maintenance of the data and provision of a helpdesk. In addition to the annual erosivity data, this release also includes the mean monthly erosivity data for 94% of the GloREDa stations. Based on these mean monthly R-factor values, we predict the global monthly erosivity datasets at 1 km resolution using the ensemble machine learning approach (ML) as implemented in the mlr package for R. The produced monthly raster data (GeoTIFF format) may be useful for soil erosion prediction modelling, sediment distribution analysis, climate change predictions, flood, and natural disaster assessments and can be valuable inputs for Land and Earth Systems modelling.

Unveiling soil temperature reached during a wildfire event using ex-post chemical and hydraulic soil analysis.

Wildfires affect different physical, chemical, and hydraulic soil properties, and the magnitude of their effects varies depending on intrinsic soil properties and wildfire characteristics. As a result of climate change, the frequency and intensity of wildfires have increased, and understanding their impact and predicting the temperature to which soils were exposed in previous events is becoming increasingly critical. Hence, the objectives of this study were to develop a soil-heating laboratory procedure to (a) identify changes in soil properties at different temperatures and (b) to infer the temperature ranges to which heated soils have been exposed. Saturated (Ks) and unsaturated (Ku) hydraulic conductivity, pH, electrical conductivity (EC), wet aggregate stability (WAS), soil water repellency index (RIm), and soil organic matter content (SOM) were measured in six laboratory heated (LH) soils at 300, 500, 700, and 900 °C for 2 h. Bulk density (BD) and soil texture were measured in unheated (UH) and wildfire-unheated (WH) samples. UH samples were used as baselines to quantify changes in soil properties, and WH and LH samples were compared to determine the temperatures to which WH soils were exposed. The results show that in the studied temperature range, WAS exhibited a U-shaped trend, opposite to that of pH and EC. Ks and Ku (negative tension of -3 cm) tend to increase with temperature, reaching a maximum of 1.27·10-4 and 5.62·10-5 (m/s) at 900 °C, respectively. RIm was highly dependent on texture; loam soils had an average minimum and maximum of 1.84 and 2.73, at 900 and 300 °C, respectively, while sandy loam soils had an average minimum and maximum of 1.29 and 2.08 at 300 and 900 °C, respectively. Finally, the parameters that provided laboratory variation and a temperature range consistent with the results observed in naturally heated soils were WAS, RIm, pH, and EC.

A simple model for estimating changes in rainfall erosivity caused by variations in rainfall patterns.

A major challenge when coupling soil loss models with precipitation forecasts from Global Circulation Models (GCMs) is that their time resolutions do not generally agree. Precipitation forecasts from GCM must be scaled down; however, the distribution of the rainfall intensity, which can affect soil loss as much as precipitation amounts, is usually not considered in this process. Therefore, the objective of this study was to develop a statistical equation for computing event-based rainfall erosivity under changing precipitation patterns using the least amount of information possible. For this purpose, an empirical equation for predicting event-based rainfall erosivity was developed using the product of the total precipitation P and the maximum 0.5-h rainfall intensity, I0.5. This equation was calibrated using measured precipitation data from 28 sites in Central Chile and then tested with simulated data with different rainfall patterns from the CLIGEN (CLImate GENerator) weather generator. More than 53,000 rainfall events were analyzed, where the equation consistently provided R2 values of 0.99 for every dataset used, revealing its robustness when used in potential climate change scenarios in the study site. However, because computing I0.5 requires estimating precipitation at a high time resolution, the relationship was recalibrated and tested using 1 through 24-h maximum rainfall intensities. Using these intensities, the equation provided erosivity estimates with R2 ranging from 0.78 to 0.99, where better results were obtained as the resolution of the data increased. This study provides the methodology for building and testing the proposed equation and discusses its advantages and limitations.

A comprehensive evaluation of pedotransfer functions for predicting soil water content in environmental modeling and ecosystem management.

Many pedotransfer functions (PTFs) have been developed for predicting the soil water content at different matric potentials. The use of these functions has been encouraged because of the time and work typically required for measuring it, while the PTFs require commonly measured soil properties such as sand, silt, clay, organic matter content, or bulk density for predicting water retention. In addition, several environmental and ecosystem management simulation models such as DRAINMOD, HYDRUS, EPIC, SPAW, and WEPP use PTFs for computing soil hydraulic properties. Because of the increasing use of the PTFs and their effect in many soil water simulation and transport models, this study revised and tested 13 different PTFs for predicting soil water content at -33 and -1500 kPa, values usually known as field capacity and wilting point. Three of these PTFs were derived from tropical soils while the rest were developed with soil samples collected across the United States. These PTFs were evaluated in Chilean soils as an independent dataset and their improvement after calibration was assessed with this new data. The results demonstrate that the PTFs performance depends on the soils used for their development as the estimates showed a significant improvement after calibration. When predicting water content, Rawls et al. (2004) was the best function before calibration (RMSE = 0.08 for -33 and -1500 kPa), while Gupta and Larson (1979) was the best after calibration (RMSE of 0.06 and 0.05, and r2 values of 0.69 and 0.66 at -33 and -1500 kPa, respectively). Nonlinear PTFs performed better than linear PTFs when predicting water content at field capacity. Finally, bulk density proved to be the key variable and can be used as footprint for soils changes through time. Organic matter content was also a significant input but improved the estimates for some specific matric potentials and PTFs.

A New Method for Sensing Soil Water Content in Green Roofs Using Plant Microbial Fuel Cells.

Green roofs have many benefits, but in countries with semiarid climates the amount of water needed for irrigation is a limiting factor for their maintenance. The use of drought-tolerant plants such as Sedum species, reduces the water requirements in the dry season, but, even so, in semiarid environments these can reach up to 60 L m-2 per day. Continuous substrate/soil water content monitoring would facilitate the efficient use of this critical resource. In this context, the use of plant microbial fuel cells (PMFCs) emerges as a suitable and more sustainable alternative for monitoring water content in green roofs in semiarid climates. In this study, bench and pilot-scale experiments using seven Sedum species showed a positive relationship between current generation and water content in the substrate. PMFC reactors with higher water content (around 27% vs. 17.5% v/v) showed larger power density (114.6 and 82.3 µW m-2 vs. 32.5 µW m-2). Moreover, a correlation coefficient of 0.95 (±0.01) between current density and water content was observed. The results of this research represent the first effort of using PMFCs as low-cost water content biosensors for green roofs.

Isolation and detection of circulating tumour cells from metastatic melanoma patients using a slanted spiral microfluidic device.

Circulating Tumour Cells (CTCs) are promising cancer biomarkers. Several methods have been developed to isolate CTCs from blood samples. However, the isolation of melanoma CTCs is very challenging as a result of their extraordinary heterogeneity, which has hindered their biological and clinical study. Thus, methods that isolate CTCs based on their physical properties, rather than surface marker expression, such as microfluidic devices, are greatly needed in melanoma. Here, we assessed the ability of the slanted spiral microfluidic device to isolate melanoma CTCs via label-free enrichment. We demonstrated that this device yields recovery rates of spiked melanoma cells of over 80% and 55%, after one or two rounds of enrichment, respectively. Concurrently, a two to three log reduction of white blood cells was achieved with one or two rounds of enrichment, respectively. We characterised the isolated CTCs using multimarker flow cytometry, immunocytochemistry and gene expression. The results demonstrated that CTCs from metastatic melanoma patients were highly heterogeneous and commonly expressed stem-like markers such as PAX3 and ABCB5. The implementation of the slanted microfluidic device for melanoma CTC isolation enables further understanding of the biology of melanoma metastasis for biomarker development and to inform future treatment approaches.

Global rainfall erosivity assessment based on high-temporal resolution rainfall records.

The exposure of the Earth's surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha-1 h-1 yr-1, with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.

Predicting the particle size distribution of eroded sediment using artificial neural networks.

Water erosion causes soil degradation and nonpoint pollution. Pollutants are primarily transported on the surfaces of fine soil and sediment particles. Several soil loss models and empirical equations have been developed for the size distribution estimation of the sediment leaving the field, including the physically-based models and empirical equations. Usually, physically-based models require a large amount of data, sometimes exceeding the amount of available data in the modeled area. Conversely, empirical equations do not always predict the sediment composition associated with individual events and may require data that are not always available. Therefore, the objective of this study was to develop a model to predict the particle size distribution (PSD) of eroded soil. A total of 41 erosion events from 21 soils were used. These data were compiled from previous studies. Correlation and multiple regression analyses were used to identify the main variables controlling sediment PSD. These variables were the particle size distribution in the soil matrix, the antecedent soil moisture condition, soil erodibility, and hillslope geometry. With these variables, an artificial neural network was calibrated using data from 29 events (r2=0.98, 0.97, and 0.86; for sand, silt, and clay in the sediment, respectively) and then validated and tested on 12 events (r2=0.74, 0.85, and 0.75; for sand, silt, and clay in the sediment, respectively). The artificial neural network was compared with three empirical models. The network presented better performance in predicting sediment PSD and differentiating rain-runoff events in the same soil. In addition to the quality of the particle distribution estimates, this model requires a small number of easily obtained variables, providing a convenient routine for predicting PSD in eroded sediment in other pollutant transport models.

Boron stress response and accumulation potential of the extremely tolerant species Puccinellia frigida.

Phytoremediation is a promising technology to tackle boron toxicity, which restricts agricultural activities in many arid and semi-arid areas. Puccinellia frigida is a perennial grass that was reported to hyperaccumulate boron in extremely boron-contaminated sites. To further investigate its potential for phytoremediation, we determined its response to boron stress under controlled conditions (hydroponic culture). Also, as a first step towards understanding the mechanisms underlying its extreme tolerance, we evaluated the presence and expression of genes related with boron tolerance. We found that P. frigida grew normally even at highly toxic boron concentrations in the medium (500mg/L), and within its tissues (>5000mg/kg DW). We postulate that the strategies conferring this extreme tolerance involve both restricting boron accumulation and an internal tolerance mechanism; this is consistent with the identification of putative genes involved in both mechanisms, including the expression of a possible boron efflux transporter. We also found that P. frigida hyperaccumulated boron over a wide range of boron concentrations. We propose that P. frigida could be used for boron phytoremediation strategies in places with different soil characteristics and boron concentrations. Further studies should pave the way for the development of clean and low-cost solutions to boron toxicity problems.

Active and legacy mining in an arid urban environment: challenges and perspectives for Copiapó, Northern Chile.

Urban expansion in areas of active and legacy mining imposes a sustainability challenge, especially in arid environments where cities compete for resources with agriculture and industry. The city of Copiapó, with 150,000 inhabitants in the Atacama Desert, reflects this challenge. More than 30 abandoned tailings from legacy mining are scattered throughout its urban and peri-urban area, which include an active copper smelter. Despite the public concern generated by the mining-related pollution, no geochemical information is currently available for Copiapó, particularly for metal concentration in environmental solid phases. A geochemical screening of soils (n = 42), street dusts (n = 71) and tailings (n = 68) was conducted in November 2014 and April 2015. Organic matter, pH and elemental composition measurements were taken. Notably, copper in soils (60-2120 mg/kg) and street dusts (110-10,200 mg/kg) consistently exceeded international guidelines for residential and industrial use, while a lower proportion of samples exceeded international guidelines for arsenic, zinc and lead. Metal enrichment occurred in residential, industrial and agricultural areas near tailings and the copper smelter. This first screening of metal contamination sets the basis for future risk assessments toward defining knowledge-based policies and urban planning. Challenges include developing: (1) adequate intervention guideline values; (2) appropriate geochemical background levels for key metals; (3) urban planning that considers contaminated areas; (4) cost-effective control strategies for abandoned tailings in water-scarce areas; and (5) scenarios and technologies for tailings reprocessing. Assessing urban geochemical risks is a critical endeavor for areas where extreme events triggered by climate change are likely, as the mud flooding that impacted Copiapó in late March 2015.

Sediment composition for the assessment of water erosion and nonpoint source pollution in natural and fire-affected landscapes.

Water erosion is a leading cause of soil degradation and a major nonpoint source pollution problem. Many efforts have been undertaken to estimate the amount and size distribution of the sediment leaving the field. Multi-size class water erosion models subdivide eroded soil into different sizes and estimate the aggregate's composition based on empirical equations derived from agricultural soils. The objective of this study was to evaluate these equations on soil samples collected from natural landscapes (uncultivated) and fire-affected soils. Chemical, physical, and soil fractions and aggregate composition analyses were performed on samples collected in the Chilean Patagonia and later compared with the equations' estimates. The results showed that the empirical equations were not suitable for predicting the sediment fractions. Fine particles, including primary clay, primary silt, and small aggregates (<53 µm) were over-estimated, and large aggregates (>53 µm) and primary sand were under-estimated. The uncultivated and fire-affected soils showed a reduced fraction of fine particles in the sediment, as clay and silt were mostly in the form of large aggregates. Thus, a new set of equations was developed for these soils, where small aggregates were defined as particles with sizes between 53 µm and 250 µm and large aggregates as particles>250 µm. With r(2) values between 0.47 and 0.98, the new equations provided better estimates for primary sand and large aggregates. The aggregate's composition was also well predicted, especially the silt and clay fractions in the large aggregates from uncultivated soils (r(2)=0.63 and 0.83, respectively) and the fractions of silt in the small aggregates (r(2)=0.84) and clay in the large aggregates (r(2)=0.78) from fire-affected soils. Overall, these new equations proved to be better predictors for the sediment and aggregate's composition in uncultivated and fire-affected soils, and they reduce the error when estimating soil loss in natural landscapes.

Differential arsenic binding in the sediments of two sites in Chile's lower Loa River basin.

Fluvial sediments from two lower Loa River basin sites in northern Chile were compared in order to probe the effects of vegetation and organic matter (OM) on As accumulation in fluvial environments. The two sites were the Sloman dam, which lacks macrophytes and has a low OM content (2.4%) in sediments, and the Quillagua Oasis, which is 23 km downstream from the Sloman site and has a higher OM (6.2%) in sediments and abundant aquatic plant life. The Quillagua site had preferential As enrichment with a co-occurrence pattern that differed from that of the Sloman site, which had a lower As concentration (1528 vs. 262 mg/kg d.w., respectively). At the Quillagua site, As concentration was strongly correlated with Mn and OM (r = 0.91 and 0.85, respectively); while at the Sloman site, As concentration in sediments was significantly correlated with Ca and Sr (r = 0.63 and 0.54, respectively). Sequential extraction analyses showed that the Sloman site had higher percentage of easily exchangeable As within the surface sediment (12%, 45 mg/kg d.w.) compared with the Quillagua site (3%, 40 mg/kg d.w.). These contrasting results suggest that both vegetation and OM control the immobilization and accumulation of As in the arid Loa River basin.

Natural attenuation process via microbial oxidation of arsenic in a high Andean watershed.

Rivers in northern Chile have arsenic (As) concentrations at levels that are toxic for humans and other organisms. Microorganism-mediated redox reactions have a crucial role in the As cycle; the microbial oxidation of As (As(III) to As(V)) is a critical transformation because it favors the immobilization of As in the solid phase. We studied the role of microbial As oxidation for controlling the mobility of As in the extreme environment found in the Chilean Altiplano (i.e., > 4000 meters above sea level (masl) and < 310 mm annual rainfall), which are conditions that have rarely been studied. Our model system was the upper Azufre River sub-basin, where the natural attenuation of As from hydrothermal discharge (pH 4-6) was observed. As(III) was actively oxidized by a microbial consortium, leading to a significant decrease in the dissolved As concentrations and a corresponding increase in the sediment's As concentration downstream of the hydrothermal source. In-situ oxidation experiments demonstrated that the As oxidation required biological activity, and microbiological molecular analysis confirmed the presence of As(III)-oxidizing groups (aroA-like genes) in the system. In addition, the pH measurements and solid phase analysis strongly suggested that the As removal mechanism involved adsorption or coprecipitation with Fe-oxyhydroxides. Taken together, these results indicate that the microorganism-mediated As oxidation contributed to the attenuation of As concentrations and the stabilization of As in the solid phase, therefore controlling the amount of As transported downstream. This study is the first to demonstrate the microbial oxidation of As in Altiplano basins and its relevance in the immobilization of As.

Aqueous SDS micelle-promoted acid-catalyzed domino ABB' imino Diels-Alder reaction: a mild and efficient synthesis of privileged 2-methyl-tetrahydroquinoline scaffolds.

A new green protocol for the efficient synthesis of pharmacologically relevant 4-amidyl-2-methyl-1,2,3,4-tetrahydroquinolines (THQs) through the domino type ABB' imino Diels-Alder reaction in acidified water in the presence of sodium dodecyl sulphate (SDS) surfactant was developed for the first time. The influence of the SDS micelles and their different concentrations (5.0, 8.2 and 12.0 mM) on reactivity of the imino Diels-Alder reaction was studied. It was found that the best THQ yields (70-99%) are achieved above the critical micellar concentration (12 mM) using pH 1.0-2.5. This procedure resulted in a general and clean environmentally benign protocol to obtain the privileged diastereospecific cis 2,4-disubstituted THQ molecules of highest biological interest.

Testing the Wisconsin Phosphorus Index with year-round, field-scale runoff monitoring.

The Wisconsin Phosphorus Index (WPI) is one of several P indices in the United States that use equations to describe actual P loss processes. Although for nutrient management planning the WPI is reported as a dimensionless whole number, it is calculated as average annual dissolved P (DP) and particulate P (PP) mass delivered per unit area. The WPI calculations use soil P concentration, applied manure and fertilizer P, and estimates of average annual erosion and average annual runoff. We compared WPI estimated P losses to annual P loads measured in surface runoff from 86 field-years on crop fields and pastures. As the erosion and runoff generated by the weather in the monitoring years varied substantially from the average annual estimates used in the WPI, the WPI and measured loads were not well correlated. However, when measured runoff and erosion were used in the WPI field loss calculations, the WPI accurately estimated annual total P loads with a Nash-Sutcliffe Model Efficiency (NSE) of 0.87. The DP loss estimates were not as close to measured values (NSE = 0.40) as the PP loss estimates (NSE = 0.89). Some errors in estimating DP losses may be unavoidable due to uncertainties in estimating on-farm manure P application rates. The WPI is sensitive to field management that affects its erosion and runoff estimates. Provided that the WPI methods for estimating average annual erosion and runoff are accurately reflecting the effects of management, the WPI is an accurate field-level assessment tool for managing runoff P losses.

Instrumentation for measuring runoff, sediment, and chemical losses from agricultural fields.

This work describes a simple, passive sampling system for measuring runoff, sediment, and chemical losses from typical agricultural fields. The sampler consists of a 5 to 7 m wide runoff collector connected to a series of multislot divisors. These divisors split the flow into aliquots, providing a continuous sampling during the runoff event. Divisors were located in a wooden box below ground level. With an adequate pump, this system can operate in fields with a slope gradient as low as 2%, and can stay in the field during winter to record first snowmelt-generated runoff. A radio transmitter reports by telemetry the occurrence and magnitude of any runoff event, and indicates when the system should be sampled and emptied. This article includes a description of the equipment, advantages, and disadvantages based on 2 yr of operation, and examples of data collected.