Metal concentrations in used engine oils: Relevance to site assessments of soils

Used engine oils contain metals, which upon entering soils may pose risks to human health or the environment. In this study, previously published concentrations of 23 metals in 213 used engine oil samples from the early 1970s to the mid-1990s are statistically evaluated. Neat (100%) used engine oils were found to contain relatively high concentrations of lead, calcium, and zinc, attributable to piston blow-by of leaded gasoline, calcium salt detergent additives, and zinc-bearing anti-corrosion/anti-oxidation additives, respectively. Wear metal concentrations were lower. The lead concentration in used engine oils in the U.S. declined between the 1970s and early 1990s, potentially providing a basis to constrain the “age” of used engine oil(s) in soils. The concentrations of 23 metals in used engine oils were compared to soil risk benchmarks in 15 representative jurisdictions in the U.S., Canada, Australia, and Europe. The maximum concentrations in neat (100%) used engine oil of eight metals – Be, Co, Fe, Mn, Ni, Se, Ag, and Ti – were lower than their collective minimum benchmarks in soils for the jurisdictions surveyed, indicating their concentrations in soils could not be reasonably expected to exceed any soil benchmarks. Nine metals (As, Ba, Cd, Cr, Cu, Pb, Sn, V and Zn), but particularly arsenic, cadmium, lead, tin, and zinc, were identified as potential contaminants of concern (PCOC) for soils from locations impacted with used engine oils, owing to their higher median concentrations (i.e., 2.5, 1.4, 1038, 5.0, and 922 mg/kg in oil, respectively) relative to most soil benchmarks. Site-specific benchmarks and metal concentrations at reasonable oil in soil concentrations require consideration when developing the suite of PCOC metal analytes for conducting site assessments of soils impacted by used engine oil.     

Effect of Hunting on the Reproduction of the Sable Population

Russian Journal of Ecology - Analysis of hunting samples of the Kamchatka sable population for 2001–2013 has revealed changes in the reproductive parameters of females over the period from...     

Circumpolar status of Arctic ptarmigan: Population dynamics and trends

Rock ptarmigan (Lagopus muta) and willow ptarmigan (L. lagopus) are Arctic birds with a circumpolar distribution but there is limited knowledge about their status and trends across their circumpolar distribution. Here, we compiled information from 90 ptarmigan study sites from 7 Arctic countries, where almost half of the sites are still monitored. Rock ptarmigan showed an overall negative trend on Iceland and Greenland, while Svalbard and Newfoundland had positive trends, and no significant trends in Alaska. For willow ptarmigan, there was a negative trend in mid-Sweden and eastern Russia, while northern Fennoscandia, North America and Newfoundland had no significant trends. Both species displayed some periods with population cycles (short 3–6 years and long 9–12 years), but cyclicity changed through time for both species. We propose that simple, cost-efficient systematic surveys that capture the main feature of ptarmigan population dynamics can form the basis for citizen science efforts in order to fill knowledge gaps for the many regions that lack systematic ptarmigan monitoring programs.

     

Mobility of free surface in different liquids and its influence on water striders locomotion

Dynamics of the surface layer in different liquids is examined by means of infrared thermography of the surface and simultaneous velocity fields measurements using surface and infrared Particle Image Velocimetry. This technique allows measurements and comparison of two velocity fields—at the surface and at small depth about 50–200 μm. In distilled water the velocity fields at the surface and at small depth exhibit significant dissimilarity. The flow field below the surface is essentially 3D, whereas the surface flow is characterized by vanishing 2D divergence of velocity, indicating predominantly planar motion. In contrast, in ethanol–butanol mixture two velocity fields are well correlated, both corresponding to 3D flow with continuous surface renewal. Thermal patterns, observed at the surface, and the flow field structure in different liquids are associated with different boundary conditions for velocity at the surface. Water surface is seldom renewed, which inhibits heat and mass exchange between the liquid and atmosphere. However, absence of vertical advection also enables organisms to live within the surface layer, to stand and walk on the free surface. This is illustrated by the difficulties a water strider faces on the surface of ultrapure water, which exhibits Marangoni convection.     

Evaluating knowledge integration and co-production in a 2-year collaborative learning process with smallholder dairy farmer groups

Although knowledge integration and co-production are integral to transdisciplinary approaches to foster sustainable change in social–ecological systems, this type of research is usually not evaluated based on assessments of the learning process. While participants are meant to be central in such approaches, too often, their perspectives are not central to the evaluation. Moreover, there is limited empirical information about how new knowledge is transformed into action. We respond to these knowledge gaps by analyzing (A) farmers’ perspectives on the collaborative learning process and (B) how farmers’ new knowledge can serve as the basis for changed actions. Theoretically, we are guided by second-order cybernetics and have integrated the Control Loop Model with Learning Loops to extend Kirkpatrick (Evaluating training programs: the four levels, 2nd edn. Berrett-Koehler Publisher, San Francisco, 1998) four-level evaluation scheme. We apply this to evaluate a 2-year collaborative learning process with two smallholder dairy farmer groups in Nakuru County, Kenya that aimed to co-develop local sustainable pathways to reduce milk losses. Results showed that farmers learned by (1) implementing corrective actions based on known cause–effect relations (single-loop learning); (2) discovering new cause–effect relations and testing their effect (double-loop learning); and (3) further questioning and changing their aims (triple-loop learning). Highlighting the importance of knowledge integration and co-production, this collaboration between farmers, researchers, and field assistants improved the farmers’ ability to respond, adapt, and intentionally transform their farming system in relation with complex sustainability challenges. Results demonstrate that the potential of our evaluation scheme to better reflect learning and empowerment experienced by actors involved in transdisciplinary research for sustainability.     

The environmental Kuznets curve and CO2 emissions in the USA

Environmental Science and Pollution Research - In this paper, we analyze the existence of the environmental Kuznets curve as reported by Kuznets (Am Econ Rev 5:1–28, 1955) by using the...     

Movements of spotted seals (<Emphasis Type="Italic">Phoca largha</Emphasis>) in the Sea of Okhotsk according to satellite tagging data

For the first time, satellite tagging of spotted seals (Phoca largha) has been performed in three regions of the Sea of Okhotsk: Chkalov Island in Sakhalin Bay, Ptichy Island, and the Bolshaya River mouth on the western coast of Kamchatka. As a result, regions inhabited by the seals in different periods of their life cycle and differences in the pattern of water area use by animals from different regions have been revealed. The seals from the western Kamchatka coast have covered greater distances during the observation period, compared to the animals from Sakhalin Bay. In the reproductive period, the seals from the western coast spread over the entire northern part of the Sea of Okhotsk, whereas the animals from the Sakhalin Bay move only to the Tatar Strait, the Sea of Japan. None of tagged seals has been located in the “reproductive center” at the eastern coast of Sakhalin. The seals tagged in different regions of the Sea of Okhotsk have never been located in the same place during the entire annual cycle, suggesting that the sea is inhabited by two reproductively isolated groups of ringed seals.     

Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches

Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R² (LL R²) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.