Singular Spectrum Analysis of Hydroecological Parameter Dynamics of Lake Naroch’ in the Years 1978–2015

Singular Spectrum Analysis (SSA) has been used to decompose continuous series of data on certain characteristics of Lake Naroch’ ecosystem during the vegetative seasons of years 1978–2015 into a long-time trend, a periodic component, and a residue not amenable to decomposition. The contribution of each component to changes in this variable has been assessed. The trends accounted for 78–97% of parameter variability, and the periodic components accounted for 2.5–15%. The fluctuations of phytoplankton and zooplankton biomass dynamics were the most diverse, and the contribution of these components was the greatest (15 and 8%, respectively). The periodic components in the changes of all parameters could be divided into four groups according to period duration (17–22, 7–15, 4–7, and less than 4 years). Multidimensional factor analysis of seven biotic parameters was performed in order to identify fluctuations in the ecosystem. Five major factors accounting for 93.6% of ecosystem changes together were identified, and each factor variable was subjected to SSA analysis. The period durations were similar for the oscillatory components identified. The first factor was interpreted as a trophic status of the water body, the second was taken to be the geographical location that defines the amount of solar radiation energy available, the third was taken to be the availability of biogenic elements (phosphorus in particular), and the fourth was interpreted as specific developmental cycles of live components of the ecosystem.     

Overestimation of self-reported driving exposure: Results from the SHRP2 Naturalistic Driving Study

Objectives: The accuracy of self-reported driving exposure has questioned the validity of using self-reported mileage to inform research questions. Studies examining the accuracy of self-reported driving exposure compared to objective measures find low validity, with drivers overestimating and underestimating driving distance. The aims of the current study were to (1) examine the discrepancy between self-reported annual mileage and driving exposure the following year and (2) investigate whether these differences depended on age and annual mileage.

Methods: Two estimates of drivers’ self-reported annual mileage collected during vehicle installation (obtained via prestudy questionnaires) and approximated annual mileage driven (based upon Global Positioning System data) were acquired from 3,323 participants who participated in the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study.

Results: A Wilcoxon signed rank test showed that there was a significant difference between self-reported and annual driving exposure during participation in SHRP 2, with the majority of self-reported responses overestimating annual mileage the following year, irrespective of whether an ordinal or ratio variable was examined. Over 15% of participants provided self-reported responses with over 100% deviation, which were exclusive to participants underestimating annual mileage. Further, deviations in reporting differed between participants who had low, medium, and high exposure, as well as between participants in different age groups.

Conclusions: These findings indicate that although self-reported annual mileage is heavily relied on for research, such estimates of driving distance may be an overestimate of current or future mileage and can influence the validity of prior research that has utilized estimates of driving exposure.     

Using environmental and geographic data to optimize ex situ collections and preserve evolutionary potential

Maintenance of biodiversity through seed banks and botanical gardens, where the wealth of species’ genetic variation may be preserved ex situ, is a major goal of conservation. However, challenges can persist in optimizing ex situ collections if trade-offs exist among cost, effort, and conserving species evolutionary potential, particularly when genetic data are not available. We evaluated the genetic consequences of population preservation informed by geographic (isolation by distance [IBD]) and environmental (isolation by environment [IBE]) distance for ex situ collections for which population provenance is available. We used 19 genetic and genomic data sets from 15 plant species to assess the proportion of population genetic differentiation explained by geographic and environmental factors and to simulate ex situ collections prioritizing source populations based on pairwise geographic distance, environmental distance, or both. Specifically, we tested the impact prioritizing sampling based on these distances may have on the capture of neutral, functional, or putatively adaptive genetic diversity and differentiation. Individually, IBD and IBE explained limited population genetic differences across all 3 genetic marker classes (IBD, 10–16%; IBE, 1–5.5%). Together, they explained a substantial proportion of population genetic differences for functional (45%) and adaptive (71%) variation. Simulated ex situ collections revealed that inclusion of IBD, IBE, or both increased allelic diversity and genetic differentiation captured among populations, particularly for loci that may be important for adaptation. Thus, prioritizing population collections based on environmental and geographic distance data can optimize genetic variation captured ex situ. For the vast majority of plant species for which there is no genetic information, these data are invaluable to conservation because they can guide preservation of genetic variation needed to maintain evolutionary potential within collections.     

The use of nanovermiculite catalyst in the study of removal of the organic load and degradation of atrazine via ozone process in RPB reactor

Abstract

The main objective of this study is the degradation of a synthetic solution of atrazine by a modified vermiculite catalyzed ozonation, in a rotating packed bed (RPB) reactor. A 0.5?L RPB reactor was used to perform the experiments, using a Central Composite Design (CCD) response surface to construct the quadratic model based on the factors: pH, catalyst concentration and reactor rotation frequency. The response variable was the removal of the organic load measured in terms of Chemical Oxygen Demand (COD). After the complete quadratic model was constructed through the response surface, the COD degradation process had an optimal removal of 41% under the following conditions: pH 8.0, rotation of 1150?rpm and catalyst concentration 0.66?g L^?1.     

Variability of the Ecological and Morphological Characteristics of Field Vole (Microtus agrestis) in the Southern and Middle Urals

Russian Journal of Ecology - The variability of the ecological and morphological characteristics of the field vole was studied on samples collected in its two localities of the Southern Urals and...     

Understanding interactions between urban development policies and GHG emissions: A case study in Stockholm Region

Human-induced urban growth and sprawl have implications for greenhouse gas (GHG) emissions that may not be included in conventional GHG accounting methods. Improved understanding of this issue requires use of interactive, spatial-explicit social–ecological systems modeling. This paper develops a comprehensive approach to modeling GHG emissions from urban developments, considering Stockholm County, Sweden as a case study. GHG projections to 2040 with a social–ecological system model yield overall greater emissions than simple extrapolations in official climate action planning. The most pronounced difference in emissions (39% higher) from energy use single-residence buildings resulting from urban sprawl. And this difference is not accounted for in the simple extrapolations. Scenario results indicate that a zoning policy, restricting urban development in certain areas, can mitigate 72% of the total emission effects of the model-projected urban sprawl. The study outcomes include a decision support interface for communicating results and policy implications with policymakers.