326 research outputs found
Rule-based Handling of Hazardous Nitrogen
A rule-based, recursive framework is an ideal approach to support the design of cropping systems (CS). A framework of this type was proposed, arranged into three stages (Silvestri and Bellocchi, 2007): (phase I) prior evaluation (technical, problem-solving, farmer-driven stage), (phase II) posterior evaluation (institutional, environmental monitoring implemented when CS response deviates from expected behaviour), and (phase III) managing the change (participatory, dynamic rearrangement of CS). This sequence is meant to evolve and grow over time through reiterations (Fig. 1), allowing for a continuous adaptation of agricultural productions systems as the business environment and society change. The same procedure was applied in this study to assess the behaviour of an array of CS run in the proximity of Lake Massaciuccoli - an area of Central Italy currently defined as âvulnerable areaâ under EU Directive 676/91 - as part of an action aimed at identifying possible responsibilities of farmers in NO3 contamination of waters (research developed in 2005-2006 under the Italian Ministry of Education, University and Research)
An Indicator to Evaluate the Environmental Impact of Olive Oil Waste Water's Shedding on Cultivated Fields
Several climatic, soil and topographic factors need to be considered when evaluating the impact of human actions on the environment. Such variables may be related in a complex way to environmental impact, thus making its evaluation difficult. Problems of this type emerge when evaluating the risks olive oil waste water pose to the environment when shed on cultivated soils. This paper proposes a fuzzy expert system to calculate a modular indicator, ICARO, which allows an evaluation of the potential environmental impact of the application of olive oil waste water in a field. Five modules were formulated, one ("Waste water") reflecting the nature of the waste water, two ("Groundwater", "Surface water") reflecting the risk for the most sensitive agro-environmental compartments (groundwater, surface water), one ("Crop") reflecting possible consequences on the cropping system adopted, and one ("Soil") reflecting the soil aptitude to receive waste waters.The input variables are therefore waste water amount and properties, site-specific conditions, and characteristics of the application considered. For each input variable, two functions describing membership to the fuzzy subsets Favorable (F) and Unfavorable (U) have been defined. The expert system calculates the value of each module according to both the degree of membership of the input variables to the subsets F and U, and a set of decision rules. The five modules can be considered individually or can be aggregated (again according to level of membership to fuzzy subsets F and U and a set of decision rules) into the synthetic indicator ICARO. Outcomes of a sensitivity analysis are presented. The system is flexible and can be used as a decision aid tool to authorize waste water's shedding or subordinate the distribution on fields to acceptance of some limitations (amount, timing, site, etc)
Sensitivity of a grassland model ensemble to climate change factors: the MACSUR approach.
In grassland modelling, understanding feedbacks between grassland ecosystems and the atmosphere in the context of regional scale climatic changes is essential for the accurate quantification of ecosystem water and carbon (C) fluxes. Different grassland models respond differently to environmental conditions and climatic circumstances. To test the sensitivity of different models to changes in input variables, ensemble modelling approaches are used because they generate an expanded envelope of possible systemic outputs. Here, an ensemble modelling approach was applied to explore water and C fluxes from grasslands in Europe. Seven grassland models were run at nine long-term grassland sites representing a broad gradient of geographic and climatic conditions. It was assessed the sensitivity to climate change factors including precipitation (P), temperature (T) and atmospheric CO2 concentration [CO2]. Baseline weather series (including [CO2]=380 ppm) were modified by changing T and P by -25%, -10%, -5%, +5%, +10%, +25% of the observed standard deviation and [CO2] by +5%, +10%, +15%, +25%, +50%, +100%. The obtained multi-model responses for each driver showed different levels of sensitivity. Soil temperature and gross primary production (GPP) displayed strong sensitivity to air temperature and precipitation. Based on the multi-model median of model responses, altered scenarios of precipitation had an important effect on modelled evapotranspiration from grassland swards. In general, yield biomass and GPP increased with elevated levels of [CO2]. Rising T and [CO2] had a fundamental effect on the C cycling of terrestrial ecosystems. This study demonstrates the use of ensemble modelling to address critical issues of uncertainty associated with individual model predictions, and provides increased understanding of water and C fluxes in grasslands under climate change
Star-formation histories of local luminous infrared galaxies
We present the analysis of the integrated spectral energy distribution (SED)
from the ultraviolet (UV) to the far-infrared and H of a sample of 29
local systems and individual galaxies with infrared (IR) luminosities between
10^11 Lsun and 10^11.8 Lsun. We have combined new narrow-band H+[NII]
and broad-band g, r optical imaging taken with the Nordic Optical Telescope
(NOT), with archival GALEX, 2MASS, Spitzer, and Herschel data. The SEDs
(photometry and integrated H flux) have been fitted with a modified
version of the MAGPHYS code using stellar population synthesis models for the
UV-near-IR range and thermal emission models for the IR emission taking into
account the energy balance between the absorbed and re-emitted radiation. From
the SED fits we derive the star-formation histories (SFH) of these galaxies.
For nearly half of them the star-formation rate appears to be approximately
constant during the last few Gyrs. In the other half, the current
star-formation rate seems to be enhanced by a factor of 3-20 with respect to
that occured ~1 Gyr ago. Objects with constant SFH tend to be more massive than
starbursts and they are compatible with the expected properties of a
main-sequence (M-S) galaxy. Likewise, the derived SFHs show that all our
objects were M-S galaxies ~1 Gyr ago with stellar masses between 10^10.1 and
10^11.5 Msun. We also derived from our fits the average extinction (A_v=0.6-3
mag) and the polycyclic aromatic hydrocarbons (PAH) luminosity to L(IR) ratio
(0.03-0.16). We combined the A_v with the total IR and H luminosities
into a diagram which can be used to identify objects with rapidly changing
(increasing or decreasing) SFR during the last 100 Myr.Comment: 16 pages + online material, accepted for publication in A&
Modelling transpiration of greenhouse gerbera (Gerbera jamesonii H. Bolus) grown in substrate with saline water in a Mediterranean climate
Gerbera plants were grown in semi-closed rockwool culture under greenhouse conditions in different seasons in a Mediterranean climate. The plants were irrigated using either fresh (FW; 1.0 mol mâ3NaCl)or moderately saline (SW; 9.0 mol mâ3NaCl) water. In autumn, NaCl concentration did not influence significantly plant growth, flower production and transpiration (E), which instead were reduced in springin the plants irrigated with SW. In both seasons, water salinity did not affect leaf stomatal resistance (rl),which was determined by the inversion of the PenmanâMonteith (PM) equation or measured with a diffusion porometer. The PM formula and two regression equations were calibrated and validated for estimating the hourly rate of daytime transpiration (Ed); a regression model was also fit to nocturnal transpiration (En). Regression models predicted Edas a function of vapour pressure deficit (VPD) and/or the radiation intercepted by the canopy. Leaf area index (LAI), which is required by all the equations, was modelled as function of crop thermal time (i.e. growing degree days). The PM model predicted Ed using a constant value of rl. Model calibration and validation were performed using independent data sets. The irrigation with FW or SW did not require a different calibration of transpiration models. Both PM formula and regression equations provided accurate estimates of Ed; fitted equations explained between 80% and96% of the variance in measured Ed. A linear regression of En against (LAI·VPD) accounted for 92% of measured En
Cardiopulmonary exercise testing in a combined screening approach to individuate pulmonary arterial hypertension in systemic sclerosis
Objectives The DETECT algorithm has been developed to identify SSc patients at risk for pulmonary arterial hypertension (PAH) yielding high sensitivity but low specificity, and positive predictive value. We tested whether cardiopulmonary exercise testing (CPET) could improve the performance of the DETECT screening strategy. Methods Consecutive SSc patients over a 30-month period were screened with the DETECT algorithm and positive subjects were referred for CPET before the execution of right-heart catheterization. The predictive performance of CPET on top of DETECT was evaluated and internally validated via bootstrap replicates. Results Out of 314 patients, 96 satisfied the DETECT application criteria and 54 were positive. PAH was ascertained in 17 (31.5%) and pre-capillary pulmonary hypertension in 23 (42.6%) patients. Within CPET variables, the slope of the minute ventilation to carbon dioxide production relationship (VE/VCO2 slope) had the best performance to predict PAH at right-heart catheterization [median (interquartile range) of specificity 0.778 (0.714\u20130.846), positive predictive value 0.636 (0.556\u20130.750)]; exploratory analysis on pre-capillary yielded a specificity of 0.714 (0.636\u20130.8) and positive predictive value of 0.714 (0.636\u20130.8). Conclusion In association with the DETECT algorithm, CPET may be considered as a useful tool in the workup of SSc-related pulmonary hypertension. The sequential determination of the VE/VCO2 slope in DETECT-positive subjects may reduce the number of unnecessary invasive procedures without any loss in the capability to capture PAH. This strategy had also a remarkable performance in highlighting the presence of pre-capillary pulmonary hypertension
Climate-scale modelling of suspended sediment load in an Alpine catchment debris flow (Rio Cordon-northeastern Italy)
Pulsing storms and prolonged rainfall can drive hydrological damaging events in mountain regions with soil erosion and debris flow in river catchments. The paper presents a parsimonious model for estimating climate forcing on sediment loads in an Alpine catchment (Rio Cordon, northeastern Italian Alps). Hydroclimatic forcing was interpreted by the novel CliSMSSL (Climate-Scale Modelling of Suspended Sediment Load) model to estimate annual sediment loads. We used annual data on suspended-solid loads monitored at an experimental station from 1987 to 2001 and on monthly precipitation data. The quality of sediment load data was critically examined, and one outlying year was identified and removed from further analyses. This outlier revealed that our model underestimates exceptionally high sediment loads in years characterized by a severe flood event. For all other years, the CliSMSSL performed well, with a determination coefficient (R2) equal to 0.67 and a mean absolute error (MAE) of 129 Mg yâ1. The calibrated model for the period 1986â2010 was used to reconstruct sediment loads in the river catchment for historical times when detailed precipitation records are not available. For the period 1810â2010, the model results indicate that the past centuries have been characterized by large interannual to interdecadal fluctuations in the conditions affecting sediment loads. This paper argues that climate-induced erosion processes in Alpine areas and their impact on environment should be given more attention in discussions about climate-driven strategies. Future work should focus on delineating the extents of these findings (e.g., at other catchments of the European Alpine belt) as well as investigating the dynamics for the formation of sediment loads
Use of pJANUSâą-02-001 as a calibrator plasmid for Roundup Ready soybean event GTS-40-3-2 detection: an interlaboratory trial assessment
Owing to the labelling requirements of food and feed products containing materials derived from genetically modified organisms, quantitative detection methods have to be developed for this purpose, including the necessary certified reference materials and calibrator standards. To date, for most genetically modified organisms authorized in the European Union, certified reference materials derived from seed powders are being developed. Here, an assessment has been made on the feasibility of using plasmid DNA as an alternative calibrator for the quantitative detection of genetically modified organisms. For this, a dual-target plasmid, designated as pJANUSâą-02-001, comprising part of a junction region of genetically modified soybean event GTS-40-3-2 and the endogenous soybean-specific lectin gene was constructed. The dynamic range, efficiency and limit of detection for the soybean event GTS-40-3-2 real-time quantitative polymerase chain reaction (Q-PCR) system described by Terry et al. (J AOAC Int 85(4):938â944, 2002) were shown to be similar for in house produced homozygous genomic DNA from leaf tissue of soybean event GTS-40-3-2 and for plasmid pJANUSâą-02-001 DNA backgrounds. The performance of this real-time Q-PCR system using both types of DNA templates as calibrator standards in quantitative DNA analysis was further assessed in an interlaboratory trial. Statistical analysis and fuzzy-logic-based interpretation were performed on critical method parameters (as defined by the European Network of GMO Laboratories and the Community Reference Laboratory for GM Food and Feed guidelines) and demonstrated that the plasmid pJANUSâą-02-001 DNA represents a valuable alternative to genomic DNA as a calibrator for the quantification of soybean event GTS-40-3-2 in food and feed products
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