Emerging technology for increasing glucosinolates in arugula and mustard greens

Two plant species, arugula (Eruca sativa) and mustard (Brassica juncea) were field-grown under four soil management practices: soil mixed with municipal sewage sludge (SS), soil mixed with horse manure (HM), soil mixed with chicken manure (CM), and no-mulch bare soil (NM) to investigate the impact of soil amendments on the concentration of glucosinolates (GSLs) in their shoots. GSLs, hydrophilic plant secondary metabolites in arugula and mustard were extracted using boiling methanol and separated by adsorption on sephadex ion exchange disposable pipette tips filled with DEAE, a weak base, with a net positive charge that exchange anions such as GSLs. Quantification of GSLs was based on inactivation of arugula and mustard myrosinase and liberation of the glucose moiety from the GSLs molecule by addition of standardized myrosinase (thioglucosidase) and spectrophotometric quantification of the liberated glucose moiety. Overall, GSLs concentrations were significantly greater (1287 µg g^?1 fresh shoots) in plants grown in SS compared to 929, 890, and 981 µg g^?1 fresh shoots in plants grown in CM, HM, and NM soil, respectively. Results also revealed that mustard shoots contained greater concentrations of GSLs (974 µg g^?1 fresh shoots) compared to arugula (651 µg g^?1 fresh shoots).     

Trait space of rare plants in a fire‐dependent ecosystem

The causes of species rarity are of critical concern because of the high extinction risk associated with rarity. Studies examining individual rare species have limited generality, whereas trait‐based approaches offer a means to identify functional causes of rarity that can be applied to communities with disparate species pools. Differences in functional traits between rare and common species may be indicative of the functional causes of species rarity and may therefore be useful in crafting species conservation strategies. However, there is a conspicuous lack of studies comparing the functional traits of rare species and co‐occurring common species. We measured 18 important functional traits for 19 rare and 134 common understory plant species from North Carolina's Sandhills region and compared their trait distributions to determine whether there are significant functional differences that may explain species rarity. Flowering, fire, and tissue‐chemistry traits differed significantly between rare and common, co‐occurring species. Differences in specific traits suggest that fire suppression has driven rarity in this system and that changes to the timing and severity of prescribed fire may improve conservation success. Our method provides a useful tool to prioritize conservation efforts in other systems based on the likelihood that rare species are functionally capable of persisting.     

Review of Italian experience on automotive shredder residue characterization and management

Automotive Shredder Residue (ASR) is a special waste that can be classified as either hazardous or non hazardous depending on the amount of hazardous substances and on the features of leachate gathered from EN12457/2 test. However both the strict regulation concerning landfills and the EU targets related to End-of-Life Vehicles (ELVs) recovery and recycling rate to achieve by 2015 (Directive 2000/53/EC), will limit current landfilling practice and will impose an increased efficiency of ELVs valorization. The present paper considers ELVs context in Italy, taking into account ASRs physical–chemical features and current processing practice, focusing on the enhancement of secondary materials recovery. The application in waste-to-energy plants, cement kilns or metallurgical processes is also analyzed, with a particular attention to the possible connected environmental impacts. Pyrolysis and gasification are considered as emerging technologies although the only use of ASR is debatable; its mixing with other waste streams is gradually being applied in commercial processes. The environmental impacts of the processes are acceptable, but more supporting data are needed and the advantage over (co-)incineration remains to be proven.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Population Structure of Sable in the Baikal Mountain Land: Analysis of Genetic and Phenotypic Traits

Russian Journal of Ecology - The genetic and phenotypic structure (according to the fur color) of 14 sable samples from the Baikal mountain land (BML) has been studied by analyzing 257 animals for...     

Suicide by crashing into a heavy vehicle: Focus on professional drivers using in-depth crash data

Objective: Road traffic suicides typically involve a passenger car driver crashing his or her vehicle into a heavy vehicle, because death is almost certain due to the large mass difference between these vehicles. For the same reason, heavy-vehicle drivers typically suffer minor injuries, if any, and have thus received little attention in the research literature. In this study, we focused on heavy-vehicle drivers who were involved as the second party in road suicides in Finland.

Methods: We analyzed 138 road suicides (2011–2016) involving a passenger car crashing into a heavy vehicle. We used in-depth road crash investigation data from the Finnish Crash Data Institute.

Results: The results showed that all but 2 crashes were head-on collisions. Almost 30% of truck drivers were injured, but only a few suffered serious injuries. More than a quarter reported sick leave following their crash. Injury insurance compensation to heavy-vehicle drivers was just above €9,000 on average. Material damage to heavy vehicles was significant, with average insurance compensation paid being €70,500. Three out of 4 truck drivers reported that drivers committing suicide acted abruptly and left them little opportunity for preventive action.

Conclusions: Suicides by crashing into heavy vehicles can have an impact on drivers’ well-being; however, it is difficult to see how heavy-vehicle drivers could avoid a suicide attempt involving their vehicle.     

Seaweeds as bioindicators of heavy metals off a hot spot area on the Egyptian Mediterranean Coast during 2008–2010

Concentrations of Cu, Zn, Cd, Pb, Ni, Co, Fe, Mn, and Hg were measured successively in water, sediments, and six macroalgal species belonging to three algal classes during 3 years (2008–2010) from Abu Qir Bay, Alexandria, Egypt: Chlorophyceae (Enteromorpha compressa, Ulva fasciata), Phaeophyceae (Padina boryana), and Rhodophyceae (Jania rubens, Hypnea musciformis, Pterocladia capillacea). The study aimed to assess the bioaccumulation potential of the seaweeds, as well as to evaluate the extent of heavy metal contamination in the selected study site. Metals were analyzed using atomic absorption spectrophotometry coupled with MH-10 hydride system. The obtained data showed that the highest mean concentrations of Cu, Zn, Fe, and Mn were recorded in E. compressa; Cd, Ni, and Hg exhibited their highest mean concentrations in P. boryana, while Pb and Co were found in J. rubens. Abundance of the heavy metals in the algal species was as follow: Fe?>?Mn?>?Zn?>?Pb?>?Ni?>?Co?>?Cu?>?Cd?>?Hg. E. compressa showed the maximum metal pollution index (MPI) which was 11.55. Bioconcentration factor (BCF) for the metals in algae was relatively high with a maximum value for Mn. The Tomlinson pollution load index (PLI) values for the recorded algal species were low, which ranged between 1.00 in P. boryana and 2.72 in E. compressa. Enrichment factors for sediments were low fluctuating between 0.43 for Hg to 2.33 for Mn. Accordingly, the green alga E. compressa, brown alga P. boryana, and red alga J. rubens can be nominated as bioindicators. Based on MPI and PLI indices, Abu Qir Bay in the present study is considered as low-contaminated area.     

Predictive Model of Avian Electrocution Risk on Overhead Power Lines

Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red‐tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution‐risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high‐risk poles for retrofitting. Modelo Predictivo del Riesgo de Electrocución de Aves en Líneas Eléctricas Elevadas     

Dissipation kinetics,safety evaluation,and assessment of pre-harvest interval (PHI) and processing factor for kresoxim methyl residues in grape

A field dissipation study was conducted to evaluate the pre-harvest interval (PHI) and processing factor (PF) for kresoxim methyl (Ergon 44.3 SC) residues in grapes and during raisin making process at recommended dose (RD) and double the recommended dose (DRD). Kresoxim methyl residues dissipated following 1st-order kinetics with a half-life of 10 and 18 days at RD and DRD, respectively. The PHIs with respect to the European Union maximum residue limit (EU-MRL) of 1 mg kg^?1 for grapes were 13 and 30 days at RD and DRD, respectively. The degradation data during grape to raisin making process were best fitted to nonlinear 1st?+?1st-order kinetics with a half-life ranging between 4 and 8 days for both shade drying and with raisin dryer at different doses. The PFs were 1.19 and 1.24 with shade drying and 1.09 and 1.10 with raisin dryer, respectively, which indicates concentration of the residues during raisin making process. The dietary exposure of kresoxim methyl on each sampling day was less than the respective maximum permissible intake both at RD and DRD. The residues of kresoxim methyl in market samples of grapes and raisins were well below the EU-MRL and were also devoid of any risk of acute toxicity related to dietary exposure.