Feasibility of Applying a Stable Isotopic Tracer for Direct Determination of Dry Particulate Deposition to Soybean Plants

ABSTRACT

A stable rare-earth isotopic tracer was used to measure the deposition of KNO₃ particles on soybean leaves by direct measurement of the tracer on the plant surfaces by thermal-ionization mass spectrometry. Submicrometer particles, made from a solution containing 3 |mg mL^-1 neodymium isotope (¹⁴⁸Nd, 87.9%) and 1,000 mg mL^-1 KNO₃, were dispersed with a two-fluid nozzle and released upwind of a soybean field. Total suspended- and size-fractionated-aerosol particles were collected on an open-face filter and in a micro-orifice impactor, respectively, at a distance of 40 m from the release point. Soybean leaves exposed to the plume were collected at distances ranging from 25 to 100 m. As little as 5.5 pg of the tracer (i.e., excess ¹⁴⁸Nd) was detected in soybean leaves at signal-to-noise ratios ranging from 7,500 to 240,000, in the presence of 200 to 2,700 pg of naturally occurring Nd. The dry-particle deposition velocity, determined from the ratio of the aerial concentration and directly deposited aerosol (geometric mass mean diameter, 0.20 mm) flux, and its corresponding analytical uncertainty were 0.30 cm sec^-1 and 2.5%, respectively.     

Uncertainty-based quantitative assessment of sustainability for higher education institutions

Evaluation of sustainability in various facets of life is gaining increasing importance. Traditionally, different multi-criteria decision-making methods have been used for sustainability assessment. “Sustainability” can be a qualitative concept, and as such several researchers have attempted fuzzy logic for the quantitative assessment of sustainability. This paper outlines a new evaluation model based on fuzzy multi-criteria decision-making. The model is tested for sustainability assessment of higher education institutions (HEIs). It is based on a driving force–pressure–state–exposure–effect–action (DPSEEA) framework and is called uncertainty-based DPSEEA-Sustainability index Model (uD-SiM). The uD-SiM is a causality-based model in which the sustainability index is an outcome of nonlinear impacts of sustainability indicators in different stages of DPSEEA. The percent contribution of driving forces on the sustainability index of HEI is investigated using sensitivity analysis. The study reveals that education in sustainability and global and local research trends are the major driving forces for achieving sustainability in HEI, followed by financial and economic growth rate, social equity, energy requirements rate, and institutional enhancement, in descending order. The results of uD-SiM were found to be more realistic and rational than our earlier proposed approach, D-SiM.     

Designing the Masoala National Park in Madagascar Based on Biological and Socioeconomic Data

Abstract: Conservation biologists have developed powerful tools for reserve selection and design over the past two decades, yet seldom are protected areas actually designed on scientific grounds. Using fundamental biological and socioeconomic principles of conservation science, we designed a new protected area and its multiple-use zone on the Masoala Peninsula in the humid forest zone of Madagascar. The explicit design criteria determined the data gathered for the work, which included (1) spatial distribution and quality of habitat, (2) the areas and species at greatest risk, (3) the relationship between environmental gradients and species distributions, (4) current and predicted human settlement and land and resource use, and (5) the economic potential of natural forest management as an alternative to deforestation. We used a geographic information system to integrate these data layers and applied the design criteria to develop a park proposal that balanced human and wildlife needs. The proposal won the approval of local residents, and a national decree in 1997 designated 2100 km² of rainforest and three satellite marine reserves as the Masoala National Park, with a surrounding multiple-use zone of approximately 1000 km². The new park is Madagascar's largest protected area and protects more lowland (<400 m) humid forest habitat than the entire reserve system combined, a significant step forward in conserving a globally important ecoregion. Consideration of local needs and the national economy was a key element in gaining approval for the Masoala Park. Such an approach toward reserve design could be applied elsewhere to improve chances of establishing and maintaining protected areas over the long term.     

Species Distribution Models of Freshwater Stream Fishes in Maryland and Their Implications for Management

Species distribution models (SDMs) are often used in conservation planning, but their utility can be improved by assessing the relationships between environmental and species response variables. We constructed SDMs for 30 stream fishes of Maryland, USA, using watershed attributes as environmental variables and presence/absence as species responses. SDMs showed substantial agreement between observed and predicted values for 17 species. Most important variables were natural attributes (e.g., ecoregion, watershed area, latitude/longitude); land cover (e.g., %impervious, %row crop) was important for three species. Focused analyses on four representative species (central stoneroller, creek chub, largemouth bass, and white sucker) showed the probability of presence of each species increased non-linearly with watershed area. For these species, SDMs built to predict absent, low, and high densities were similar to presence/absence predictions but provided probable locations of high densities (e.g., probability of high-density creek chub decreased rapidly with watershed area). We applied SDMs to predict suitability of watersheds within the study area for each species. Maps of suitability and the environmental and species response relationships can help develop better management plans.     

Use of fugacity model to analyze temperature-dependent removal of micro-contaminants in sewage treatment plants

Effluents from sewage treatment plants (STPs) are known to contain residual micro-contaminants including endocrine disrupting chemicals (EDCs) despite the utilization of various removal processes. Temperature alters the efficacy of removal processes; however, experimental measurements of EDC removal at various temperatures are limited. Extrapolation of EDC behavior over a wide temperature range is possible using available physicochemical property data followed by the correction of temperature dependency. A level II fugacity-based STP model was employed by inputting parameters obtained from the literature and estimated by the US EPA’s Estimations Programs Interface (EPI) including EPI’s BIOWIN for temperature-dependent biodegradation half-lives. EDC removals in a three-stage activated sludge system were modeled under various temperatures and hydraulic retention times (HRTs) for representative compounds of various properties. Sensitivity analysis indicates that temperature plays a significant role in the model outcomes. Increasing temperature considerably enhances the removal of β-estradiol, ethinyestradiol, bisphenol, phenol, and tetrachloroethylene, but not testosterone with the highest biodegradation rate. The shortcomings of BIOWIN were mitigated by the correction of highly temperature-dependent biodegradation rates using the Arrhenius equation. The model predicts well the effects of operating temperature and HRTs on the removal via volatilization, adsorption, and biodegradation. The model also reveals that an impractically long HRT is needed to achieve a high EDC removal. The STP model along with temperature corrections is able to provide some useful insight into the different patterns of STP performance, and useful operational considerations relevant to EDC removal at winter low temperatures.     

The interrelationships between resource-holding potential,resource-value and reproductive success in territorial males: How much variation can we explain?

A long-standing hypothesis in behavioural ecology posits that males with greater resource-holding potential (RHP) control resource sites deemed more valuable by sexually-receptive females and, thereby, males controlling such sites accrue greater reproductive success (RS). This hypothesis has historically been investigated using three separate but non-mutually exclusive relationships (male RHP vs. resource value, resource value vs. male RS and male RHP vs. RS). The relationships between these three variables are predicted to be strongly positive, however, due to measurement error and biological noise, perfect correlations (r = 1.0) are rare in biology even for well-established relationships. Moreover, the inaccurate identification of either the male trait(s) important to RHP or the resource characteristic sought by females will weaken the observed strength of the relationships. Here, I use meta-analysis to quantitatively describe the general pattern of these relationships in animals. I predict that the relationships between male RHP, resource-value and RS should be significantly positive (male RHP and resource-value should explain a large amount of the variation in male RS). My meta-analysis supports this hypothesis; however, in the best case scenario only ca. 20% of the variation in the response variable was explained. I conclude by identifying areas in which we need to improve our investigations of resource-defence animals and recommending approaches to meet these needs. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.