Multi-causal and integrated assessment of sustainability: the case of agriculturization in the Argentine Pampas

Assessing the sustainability of complex development processes requires multi-causal and integrated analyses. We develop a system-based methodology, rooted in interdisciplinary discussion and consensus building between 15 experts, to construct a multi-causal diagram which examines the sustainability of the Argentine Pampas′ process of agriculturization. The resulting diagram includes 25 factors and provides a big-picture of the multiple dimensions and interrelations affecting sustainability. According to this examination, the increasing concentration of production and the incorporation of technological innovations, triggered by economic and institutional factors, are the cause of environmental distresses and social changes, whose consequences for sustainability are still highly disputed. Nevertheless, the symptoms of both environmental and social unsustainability are more evident in the case of the extra-Pampean regions than in the Pampas. This suggests that the Pampean agriculture model should not be transferred to these regions without substantial modifications. The experts did not reach consensus on whether the agriculturization process is overall sustainable or unsustainable. Lack of consensus revolved mainly around opposing perspectives regarding the significance of the threats to environmental sustainability. The magnitude of socio-distributive unbalance and loss of rural jobs were also contentious. Yet, the paper shows how the exercise of building a joint causal diagram was undoubtedly helpful for linking piece-meal disciplinary facts, brought in from all fronts, into a comprehensive and coherent picture. Readers should send their comments on this paper to: BhaskarNath@aol.com within 3 months of publication of this issue.     

Metabolic and bacterial diversity in soils historically contaminated by heavy metals and hydrocarbons

The aim of this study was to characterize soils contaminated by different levels of heavy metals and hydrocarbons (Madonna Dell'Acqua, Pisa, Italy). The soils were chemically and biochemically analysed by measuring the standard chemical properties and some enzyme activities related to microbial activity (dehydrogenase activity) and the soil carbon cycle (total and extracellular beta-glucosidase activities). The metabolic capacities of soil microorganisms to degrade hydrocarbons through catechol 2,3-dioxygenase were also described. The microbial diversity of contaminated and uncontaminated soils was estimated by denaturing gradient gel electrophoresis (DGGE) of amplified 16S rDNA sequences. The PCR/single-strand conformation polymorphism (PCR/SSCP) method was used to estimate the genetic diversity of PAH-degrading genes in both contaminated and uncontaminated soils. A greater bacterial diversity and lower catechol 2,3-dioxygenase activity was detected in unpolluted soils. The complexity of the microbial community (Shannon and Simpson indices) as well as the dehydrogenase soil activity negatively correlated with contamination levels. The greatest PAH-degrading gene diversity and the most intense catechol 2,3-dioxygenase activity were found in the soils with the highest levels of hydrocarbons. Heavy metals and hydrocarbon pollution has caused a genetic and metabolic alteration in microbial communities, corresponding to a reduction in microbial activity. A multi-technique approach combining traditional biochemical methods with molecular-based techniques, along with some methodological improvements, may represent an important tool to expand our knowledge of the role of microbial diversity in contaminated soil.     

Estrogenicity profile and estrogenic compounds determined in river sediments by chemical analysis, ELISA and yeast assays

An effects-directed strategy was applied to bed sediments of a polluted tributary in order to isolate and identify the major estrogenic chemicals it discharges into the River Po, the principal Italian watercourse. Sediment extract was concentrated by solid phase extraction and then fractioned into 10 fractions by reversed phase high performance liquid chromatography (RP-HPLC). Estrogenic activity of whole extract and fractions were determined using a recombinant yeast assay containing the human estrogen receptor (YES). The 10 fractions and whole extract were analysed for target compounds, e.g. estrone (E1), 17beta-estradiol (E2), estriol (E3), 4-nonylphenol (NP), 4-tert-octylphenol (t-OP), bisphenol A (BPA), using both liquid chromatography-tandem mass spectrometry (LC-MS/MS) and non-competitive enzyme-linked immunosorbent assays (ELISA). The YES assay determined high estrogenic activity in whole sediment (15.6 ng/g EE2 equivalents), and positive results for fractions nr 1, 2, 6, 7 and 8. E1, E3 and NP were the main estrogenic chemicals, however, other unidentified compounds contributed to sediment estrogenicity, particularly for polar fractions nr 1 and 2. A GC-MS screening performed in scan mode identified other potential contributors such as phthalates (DBP, BBP), and OP isomers. A next sampling campaign extended to other tributaries and receiving stretches of the River Po confirmed E1, E3 and NP as major estrogenic chemicals potentially threatening other sites of the main river. In general, target compound ELISAs have been shown to be suitable tools for a rapid screening of wide areas or large numbers of environmental samples for estrogenic risk. The potential for interferences suggests however to use cautiously the concentration values obtained from some of the immunoassays.     

A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)

The aim was to develop a reliable and practical quantitative structure-activity relationship (QSAR) model validated by strict conditions for predicting bioconcentration factors (BCF). We built up several QSAR models starting from a large data set of 473 heterogeneous chemicals, based on multiple linear regression (MLR), radial basis function neural network (RBFNN) and support vector machine (SVM) methods. To improve the results, we also applied a hybrid model, which gave better prediction than single models. All models were statistically analysed using strict criteria, including an external test set. The outliers were also examined to understand better in which cases large errors were to be expected and to improve the predictive models. The models offer more robust tools for regulatory purposes, on the basis of the statistical results and the quality check on the input data.     

Magnetic susceptibility measurements as proxy method to monitor soil pollution: development of experimental protocols for field surveys

In the framework of the development of new methods for measuring and monitoring soil pollution, this paper deals with the use of magnetic methodologies to monitor the heavy metals presence in soils. In particular it shows a procedure for collecting magnetic susceptibility measurements in order to interpret them as proxy variable for monitoring heavy metals in soils. Magnetic measurements are carried out using a magnetic susceptibility meter with two different probes for in situ field surveys. The experimental procedure is divided in two parts. In the first part we carry out laboratory tests aimed to evaluate, for both the probes, the effective investigation depth for soil, the measurement reproducibility under different conditions, and the influence of water content. We complete this part comparing in situ measurements obtained by means of two probes with different characteristics. In the second part we carry out tests to evaluate the relationships between heavy metal levels and magnetic susceptibility values of soil samples. We investigate the variability of the magnetic susceptibility measurements contaminating different soil samples with well known concentration of heavy metals. Moreover we study the correlation between magnetic susceptibility values and metal concentrations, determined by means of AAS, in soil samples collected during a field survey. Results suggest that a careful check of the experimental procedure play a crucial role for using magnetic susceptibility measurements for heavy metals in situ monitoring. This is very helpful both for improving the quality of data and for making simpler data interpretation.     

Longevity can buffer plant and animal populations against changing climatic variability

Both means and year-to-year variances of climate variables such as temperature and precipitation are predicted to change. However, the potential impact of changing climatic variability on the fate of populations has been largely unexamined. We analyzed multiyear demographic data for 36 plant and animal species with a broad range of life histories and types of environment to ask how sensitive their long-term stochastic population growth rates are likely to be to changes in the means and standard deviations of vital rates (survival, reproduction, growth) in response to changing climate. We quantified responsiveness using elasticities of the long-term population growth rate predicted by stochastic projection matrix models. Short-lived species (insects and annual plants and algae) are predicted to be more strongly (and negatively) affected by increasing vital rate variability relative to longer-lived species (perennial plants, birds, ungulates). Taxonomic affiliation has little power to explain sensitivity to increasing variability once longevity has been taken into account. Our results highlight the potential vulnerability of short-lived species to an increasingly variable climate, but also suggest that problems associated with short-lived undesirable species (agricultural pests, disease vectors, invasive weedy plants) may be exacerbated in regions where climate variability decreases.     

Modeling sources of nutrients in rivers draining into the Bay of Bengal—a scenario analysis

Regional Environmental Change - We model future trends in river export of nutrients to the Bay of Bengal, and the sources of this pollution. We focus on total nitrogen (TN), total phosphorus (TP),...     

A Numerical Model for the Transport of Chromium and Fine Sediments

A mathematical model which represents the transport processes of heavy metals and fine sediments in a fluvial stream was developed. The model consists of a three-equation system: the first one for total chromium concentration in the water column, C _Tw, the second one for total suspended sediment concentration, S _w, and the third one for chromium concentration in bed sediments, r. The third equation represents the chromium exchange between the water column and bed sediments by two processes: diffusion of soluble chromium and erosion/deposition of chromium sorbed to sediments. The basic assumption of the model is the instantaneous equilibrium. The main parameters are the partition coefficients in the water column and bed sediments, the depth of the active bed sediment layer, and the mass transfer coefficient between the water column and sediment pore water. The numerical model approximates the equations of advection–dispersion for chromium in water and suspended sediments by using a Eulerian third-order scheme. Numerical vs. analytical solutions were considered satisfactory for different initial, boundary, and sedimentological conditions. In order to estimate the impact of a chromium side discharge, the model was implemented for the Salado River in a reach of 65.6-km long (Santa Fe, Argentina). The results showed the effect of chromium discharge on almost the whole reach, then the vulnerability of the water quality in the Salado River when the flow was low was evidenced. When comparing the computed and measured results, the former showed a reasonable representation of the presence of chromium in water and bed sediments.     

Contaminants in water: non-target UHPLC/MS analysis

Contamination of water resources is one of the major problems to be faced for environment preservation and sustainability. The monitoring of target compounds based on mass spectrometry and selected reaction monitoring mode is often insufficient to definitely assess the quality of surface water. Also potentially harmful non-target pollutants simultaneously present must be taken into account. Liquid chromatography coupled with tandem mass spectrometry is suitable to obtain complete information on water composition. Hybrid mass spectrometers such as triple quadrupole/linear ion trap, hybrid quadrupole/time-of-flight and linear ion trap/orbitrap analyzers should be used. Here, we review ultra-high performance liquid chromatography coupled with mass spectrometry methods developed for post-target and non-target screening analysis of water emerging contaminants, such as pesticides and their degradation products, pharmaceuticals and drug side-reaction products, surfactants and illicit drugs. The major points are the following: (1) the possibility of performing retrospective analysis only by high-resolution mass analyzer; (2) the compatibility of mass analyzer with ultra-high performance liquid chromatography; (3) the use of deconvolution software to detect unknowns; and (4) the limited availability of library database.