A time-compressed simulated geomagnetic storm influences the nest-exiting flight angles of the stingless bee Tetragonisca angustula

Insects have been used as models for understanding animal orientation. It is well accepted that social insects such as honeybees and ants use different natural cues in their orientation mechanism. A magnetic sensitivity was suggested for the stingless bee Schwarziana quadripunctata, based on the observation of a surprising effect of a geomagnetic storm on the nest-exiting flight angles. Stimulated by this result, in this paper, the effects of a time-compressed simulated geomagnetic storm (TC-SGS) on the nest-exiting flight angles of another stingless bee, Tetragonisca angustula, are presented. Under an applied SGS, either on the horizontal or vertical component of the geomagnetic field, both nest-exiting flight angles, dip and azimuth, are statistically different from those under geomagnetic conditions. The angular dependence of ferromagnetic resonance (FMR) spectra of whole stingless bees shows the presence of organized magnetic nanoparticles in their bodies, which indicates this material as a possible magnetic detector.     

Use of native mosses as biomonitors of heavy metals and nitrogen deposition in the surroundings of two steel works

A biomonitoring survey using the moss species Hypnum cupressiforme Hedw. was conducted in the surroundings of two steel plants located in the North of Spain. Levels of V, Cr, Ni, Cu, Zn, As, Cd, Hg, Pb and N were determined. Very high concentrations in the areas of study were detected when compared to nearby unaffected regions. Similar trends were observed for all the elements in the differently orientated transects, showing an appreciable influence of the NW prevailing winds of the region in the dispersion of pollutants, as well as a clear decreasing gradient in the concentrations of metals in mosses within a distance of 1500 meters from the facilities. A differentiation between the elements emitted by the chimney as result of the industrial activity (V, Cr, Ni, Cu and As) and those with a high presence in steel slag deposits (Zn, Cd, Hg and Pb) was observed. The range of contamination was also established by means of the Contamination Factor, indicating a category 4 out of 6 categories, which shows the high levels reported in the areas of study. A different dynamic was registered for nitrogen regarding the rest of the heavy metals analysed except for Hg, probably due to the elevated volatility and mobility of both elements, as well as their high persistence in the atmosphere.     

Variability in environmental impacts of Brazilian soybean according to crop production and transport scenarios

Soybean production and its supply chain are highly dependent on inputs such as land, fertilizer, fuel, machines, pesticides and electricity. The expansion of this crop in Brazil in recent decades has generated concerns about its environmental impacts. To assess these impacts, two representative chains supplying soybeans to Europe were identified: Center West (CW) and Southern (SO) Brazil. Each supply chain was analyzed using Life Cycle Assessment methodology. We considered different levels of use of chemical and organic fertilizers, pesticides and machinery, different distances for transportation of inputs and different yield levels. Because transportation contributed strongly to environmental impacts, a detailed study was performed to identify the routes used to transport soybeans to seaports. Additionally, we considered different levels of land occupation and land transformation to represent the impact of deforestation in the CW region. Environmental impacts were calculated for 1000 kg of soybean up to and including the delivery to Europe at the seaport in Rotterdam, at 13% humidity. Overall results showed that the impacts are greater for CW than for SO for all impact categories studied, including acidification (7.7 and 5.3 kg SO₂ eq., respectively), climate change (959 and 510 kg CO₂ eq.), cumulative energy demand (12,634 and 6,999 MJ) and terrestrial ecotoxicity (4.9 and 3.1 kg 1,4-DCB eq.), except eutrophication and land occupation. The same trend was observed for the crop-production stage. Efforts to reduce chemical fertilizers and diesel consumption can reduce CO₂ emissions. Although deforestation for crop production has decreased in recent years, the contribution of deforestation to climate change and cumulative energy demand remains significant. In the CW scenario deforestation contributed 29% to climate change and 20% to cumulative energy demand. Results also showed that although there are different transportation options in Brazil, the current predominance of road transport causes severe environmental impacts. In CW, road transport contributed 19% to climate change and 24% to cumulative energy demand, while in SO it contributed 12% and 15% to these impacts, respectively. Improvements in the logistics of transportation, giving priority to rail and river transports over road transport, can contribute significantly to reducing greenhouse gas emissions and decreasing energy use. Future studies involving Brazilian soybeans should take into account the region of origin as different levels of environmental impact are predicted.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Transport and retention of Cryptosporidium parvum oocysts in sandy soils

A series of miscible-displacement experiments was conducted to examine the retention and transport behavior of oocysts in natural porous media. Three soils and a model sand were used that differed in physical and geochemical properties. Transport behavior was examined under various treatment conditions to help evaluate retention mechanisms. Significant retention of oocysts was observed for all media despite the fact that conditions were unfavorable for physicochemical interactions with respect to DLVO theory. The magnitude of retention was not influenced significantly by alterations in solution chemistry (reduction in ionic strength) or soil surface properties (removal of soil organic matter and metal oxides). On the basis of the observed results, it appears that retention by secondary energy minima or geochemical microdomains was minimal for these systems. The porous media used for the experiments exhibited large magnitudes of surface roughness, and it is suggested that this surface roughness contributed significantly to oocyst retention.     

Synergistic vulnerabilities: climate variability and fire management policy increase farming challenges in southeastern Mexico

Agricultural fire for land preparation is central in the livelihoods of subsistence farmers practicing shifting cultivation. Achieving a good agricultural burn, one in which the biomass is thoroughly consumed within the chosen area, depends on specific weather conditions. Fire use decisions are also shaped by institutions that define the timing and rules for fire use but also constrain the alternatives and shape adaptive capacities. Global and regional climate changes interact with the institutional framing of fire management affecting local fire use and burn outcomes. These effects are documented and analyzed to suggest adaptations to existing governance systems. We examined subsistence farmers’ socio-ecological vulnerability in the Calakmul municipality, located in southeastern Mexico. Using interviews with farmers and government agents, as well as participatory mapping and observation of agricultural burns, we studied fire management knowledge, practices and burn outcomes. Our results describe a continuum of burn outcomes covering good agricultural burns, uncontrolled burns leading to wildfires and “malquemados” literally poorly burned areas. Malquemados represent unsuccessful combustion associated with excess moisture that results in scorched vegetation. We discuss how unexpected early rains trigger effects that cascade through space and the ecological, economic and cultural domains. We argue that fire management has been historically approached from a conservation standpoint yet agricultural fire use and wildfire prevention should also be addressed from a rural development perspective. This shift in fire management would lead to the proper inclusion of the entire array of burn outcomes in studies and policies addressing farmers’ vulnerability amplified by synergistic effects between climate variability and institutional change.     

Effect of ibuprofen exposure on blood,gill, liver,and brain on common carp (Cyprinus carpio) using oxidative stress biomarkers

Although trace concentrations of ibuprofen (IBP) have been detected in diverse water bodies, there is currently insufficient information on the potentially deleterious effects of this xenobiotic. The present study aimed to determine whether IBP induces oxidative stress in brain, liver, gill, and blood of the common carp Cyprinus carpio. To this end, the median lethal concentration at 96 h (96-h LC₅₀) was determined and the lowest observed adverse effect level was established. Carp were exposed to the latter concentration (17.6 mg L^?1) for 12, 24, 48, 72, and 96 h, and the following biomarkers were evaluated: lipid peroxidation (LPX) and activity of the antioxidant enzymes superoxide dismutase, catalase, and glutathione peroxidase. Results indicated that LPX and antioxidant enzymes’ activity increased significantly (p?<?0.05) with respect to the control group in liver, gill, and blood, while no significant differences occurred in brain. In conclusion, IBP induced oxidative stress on C. carpio, the liver being the organ most affected by this damage.     

Does vehicle colour influence crash risk?

An often asked question regarding vehicle safety is whether vehicle colour has an influence on crash risk and if so, what is the differential in risk between the various colours of vehicles available. The major objective of this study was to assess the relationship between vehicle colour and crash risk through the analysis of real crash outcomes described in Police reported crash data. The study employed induced exposure methods utilising single vehicle crashes as the comparison crash type. It estimated the crash risk associated with each vehicle colour relative to a reference colour which was chosen to be white. Results of the analysis identified a clear statistically significant relationship between vehicle colour and crash risk. Compared to white vehicles, a number of colours were associated with higher crash risk. These colours were black, blue, grey, green, red and silver. The association between vehicle colour and crash risk was strongest during daylight hours where relative crash risks were higher for the colours listed compared to white by up to around 10%. No colour had a statistically significantly lower crash risk than white although crash risks for a number of other colours were not statistically significantly different from white.