Effect of 450 MHz Microwave Modulated with 217 Hz on Human EEG in Rest

Summary This study focuses on discrimination of changes, produced by low-level microwave exposure in intensity and time variability of the human EEG at rest. The power spectral density (PSD) method and nonlinear scaling analysis of the length distribution of low variability periods (LDLVP) were selected for analysis of the EEG signal. During the study, 19 healthy volunteers were exposed to a microwave (450 MHz) of 217 Hz frequency on-off modulation. The field power density at the scalp was 0.16 mW/cm². The experimental protocol consisted of ten cycles of repetitive microwave exposure. Signals from frontal, temporal, parietal and occipital EEG channels on EEG theta, alpha and beta rhythms were analysed. Exposure to microwave causes average increase of EEG activity. LDLVP analysis discriminated significant effect in time variability for 2 subjects (11%). PSD method detected significant changes in intensity for 4 subjects (21%). The effect of low-level microwave exposure is stronger on EEG beta rhythm in temporal and parietal regions of the human brain.     

Use of Microbial Community to Evaluate Performance of a Wetland System in Treating Pb/Zn Mine Drainage

The performance of a wetland system in treating lead (Pb)/zinc (Zn) mine drainage was evaluated by using the polyurethane foam unit (PFU) microbial community (method), which has been adopted by China as a standardized procedure for monitoring water quality. The wetland system consisted of four cells with three dominant plants: Typha latifolia, Phragmites australis and Paspalum distichum. Physicochemical characteristics [pH, EC, content of total suspended solid (TSS) and metals (Pb, Zn, Cd, and Cu)] and PFU microbial community in water samples had been investigated from seven sampling sites. The results indicated that the concentrations of Pb, Zn, Cd, Cu, and TSS in the mine drainage were gradually reduced from the inlet to the outlet of the wetland system and 99%, 98%, 75%, 83%, and 68% of these metals and TSS respectively, had been reduced in concentration after the drainage passed through the wetland system. A total of 105 protozoan species were identified, the number of protozoa species and the diversity index (DI) gradually increased, while the heterotrophic index (HI) gradually decreased from the inlet to the outlet of the wetland system. The results indicated that DI, HI, and total number species of protozoa could be used as biological indicators indicating the improvement of water quality.     

Quantifying and Evaluating Ecosystem Health: A Case Study from Moreton Bay, Australia

As part of the program monitoring the ecosystem health of Moreton Bay, Queensland, Australia, we developed a means for assessing ecosystem health that allows quantitative evaluation and spatial representations of the assessments. The management objectives for achieving ecosystem health were grouped into ecosystem objectives, water quality objectives, and human health objectives. For the first two groups, aspects of the ecosystem (e.g., trophic status) were identified, and an indicator was chosen for each aspect. Reference values for each indicator were derived from management objectives and compared with the mapped survey values. Subregions for which the indicator statistic was equal to or better than the assigned reference value are referred to as “compliant zones.” High-resolution surface maps were created from spatial predictions on a fine hexagonal grid for each of the indicators. Eight reporting subregions were established based on the depth and predicted residence times of the water. Within each reporting subregion, the proportion that was compliant was calculated. These results then were averaged to create an integrated ecosystem health index. The ratings by a team of ecosystem experts and the calculated ecosystem health indices had good correspondence, providing assurance that the approach was internally consistent, and that the management objectives covered the relevant biologic issues for the region. This method of calculating and mapping ecosystem health, relating it directly to management objectives, may have widespread applicability for ecosystem assessment.     

DEVELOPMENT OF EMPIRICAL,GEOGRAPHICALLY SPECIFIC WATER QUALITY CRITERIA: A CONDITIONAL PROBABILITY ANALYSIS APPROACH1

The need for scientifically defensible water quality standards for nonpoint source pollution control continues to be a pressing environmental issue. The probability of impact at differing levels of nonpoint source pollution was determined using the biological response of instream organisms empirically obtained from a statistical survey. A conditional probability analysis was used to calculate a biological threshold of impact as a function of the likelihood of exceeding a given value of pollution metric for a specified geographic area. Uncertainty and natural variability were inherently incorporated into the analysis through the use of data from a probabilistic survey. Data from wadable streams in the mid‐Atlantic area of the U.S. were used to demonstrate the approach. Benthic macroinvertebrate community index values (EPT taxa richness) were used to identify impacted stream communities. Percent fines in substrate (silt/clay fraction, > 0.06 mm) were used as a surrogate indicator for sedimentation. Thresholds of impact due to sedimentation were identified by three different techniques, and were in the range of 12 to 15 percent fines. These values were consistent with existing literature from laboratory and field studies on the impact of sediments on aquatic life in freshwater streams. All results were different from values determined from current regulatory guidance. Finally, it was illustrated how these thresholds could be used to develop criterion for protection of aquatic life in streams.     

Empirical Trials of Plant Field Guides

We designed 3 image‐based field guides to tropical forest plant species in Ghana, Grenada, and Cameroon and tested them with 1095 local residents and 20 botanists in the United Kingdom. We compared users’ identification accuracy with different image formats, including drawings, specimen photos, living plant photos, and paintings. We compared users’ accuracy with the guides to their accuracy with only their prior knowledge of the flora. We asked respondents to score each format for usability, beauty, and how much they would pay for it. Prior knowledge of plant names was generally low (<22%). With a few exceptions, identification accuracy did not differ significantly among image formats. In Cameroon, users identifying sterile Cola species achieved 46–56% accuracy across formats; identification was most accurate with living plant photos. Botanists in the United Kingdom accurately identified 82–93% of the same Cameroonian species; identification was most accurate with specimens. In Grenada, users accurately identified 74–82% of plants; drawings yielded significantly less accurate identifications than paintings and photos of living plants. In Ghana, users accurately identified 85% of plants. Digital color photos of living plants ranked high for beauty, usability, and what users would pay. Black and white drawings ranked low. Our results show the potential and limitations of the use of field guides and nonspecialists to identify plants, for example, in conservation applications. We recommend authors of plant field guides use the cheapest or easiest illustration format because image type had limited bearing on accuracy; match the type of illustration to the most likely use of the guide for slight improvements in accuracy; avoid black and white formats unless the audience is experienced at interpreting illustrations or keeping costs low is imperative; discourage false‐positive identifications, which were common; and encourage users to ask an expert or use a herbarium for groups that are difficult to identify. Pruebas Empíricas de Guías de Campo de Plantas Hawthorne, Cable & Marshall     

Sustainability and comanagement of subsistence hunting in an indigenous reserve in Guyana

Although hunting is a key component of subsistence strategies of many Amazonians, it is also one of the greatest threats to wildlife. Because indigenous reserves comprise over 20% of Amazonia, effective conservation often requires that conservation professionals work closely with indigenous groups to manage resource use. We used hunter‐generated harvesting data in spatially explicit biodemographic models to assess the sustainability of subsistence hunting of indigenous Waiwai in Guyana. We collected data through a hunter self‐monitoring program, systematic follows of hunters, and semistructured interviews. We used these data to predict future densities of 2 indicator species, spider monkeys (Ateles paniscus) and bearded sakis (Chiropotes sagulatus), under different scenarios of human population expansion and changing hunting technology. We used encounter rates from transect surveys and hunter catch‐per‐unit effort (CPUE) to validate model predictions. Paca (Cuniculus paca) (198 /year), Currosaw (Crax alector) (168), and spider monkey (117) were the most frequently harvested species. Predicted densities of spider monkeys were statistically indistinguishable from empirically derived transect data (Kolmogorov–Smirnov D = 0.67, p = 0.759) and CPUE (D = 0.32, p = 1.000), demonstrating the robustness of model predictions. Ateles paniscus and C. sagulatus were predicted to be extirpated from <13% of the Waiwai reserve in 20 years, even under the most intensive hunting scenarios. Our results suggest Waiwai hunting is currently sustainable, primarily due to their low population density and use of bow and arrow. Continual monitoring is necessary, however, particularly if human population increases are accompanied by a switch to shotgun‐only hunting. We suggest that hunter self‐monitoring and biodemographic modeling can be used effectively in a comanagement approach in which indigenous parabiologists continuously provide hunting data that is then used to update model parameters and validate model predictions.     

Estimating abundance without recaptures of marked pallid sturgeon in the Mississippi River

Abundance estimates are essential for assessing the viability of populations and the risks posed by alternative management actions. An effort to estimate abundance via a repeated mark‐recapture experiment may fail to recapture marked individuals. We devised a method for obtaining lower bounds on abundance in the absence of recaptures for both panmictic and spatially structured populations. The method assumes few enough recaptures were expected to be missed by random chance. The upper Bayesian credible limit on expected recaptures allows probabilistic statements about the minimum number of individuals present in the population. We applied this method to data from a 12‐year survey of pallid sturgeon (Scaphirhynchus albus) in the lower and middle Mississippi River (U.S.A.). None of the 241 individuals marked was recaptured in the survey. After accounting for survival and movement, our model‐averaged estimate of the total abundance of pallid sturgeon ≥3 years old in the study area had a 1%, 5%, or 25% chance of being <4,600, 7,000, or 15,000, respectively. When we assumed fish were distributed in proportion to survey catch per unit effort, the farthest downstream reach in the survey hosted at least 4.5–15 fish per river kilometer (rkm), whereas the remainder of the reaches in the lower and middle Mississippi River hosted at least 2.6–8.5 fish/rkm for all model variations examined. The lower Mississippi River had an average density of pallid sturgeon ≥3 years old of at least 3.0–9.8 fish/rkm. The choice of Bayesian prior was the largest source of uncertainty we considered but did not alter the order of magnitude of lower bounds. Nil‐recapture estimates of abundance are highly uncertain and require careful communication but can deliver insights from experiments that might otherwise be considered a failure.     

Network analysis of a stakeholder community combatting illegal wildlife trade

The illegal wildlife trade has emerged as a growing and urgent environmental issue. Stakeholders involved in the efforts to curb wildlife trafficking include nongovernmental organizations (NGOs), academia, and state government and enforcement bodies. The extent to which these stakeholders work and communicate among each other is fundamental to effectively combatting illicit trade. Using the United Kingdom as a case study, we used a social network analysis and semistructured interviews of stakeholders to assess communication relationships in the counter wildlife trafficking community. The NGOs consistently occupied 4 of the 5 most central positions in the generated networks, whereas academic institutions routinely occupied 4 of the 5 most peripheral positions. However, NGOs were the least diverse in their communication practices compared with the other stakeholder groups. Stakeholders identified personal relationships as the most important aspect of functioning communication. Participant insights also showed that stakeholder-specific variables (e.g., ethical and confidentiality concerns), competition, and fundraising can have a confounding effect on intercommunication. Evaluating communication networks and intrastakeholder communication trends is essential to creating cohesive, productive, and efficient responses to the challenges of combatting illegal wildlife trade. Article impact statement: Communication among those combatting illegal wildlife trade is confounded by stakeholder variables (ethics, confidentiality), competition, and fundraising.     

Quantifying the rebound effects of residential solar panel adoption

Customers who adopt solar panels can reduce their energy bills and lower the effective average electricity prices they pay. When the price falls, a solar consumer might consume more electricity than before – a solar rebound effect. We provide the first empirical evidence of residential solar rebound effects in the U.S. We use household level hourly and daily electricity meter data as well as hourly solar panel electricity generation data from 277 solar homes and about 4000 non-solar homes from 2013 to 2017 in Phoenix Arizona. Using matching methods and a fixed effects panel regression approach, we find that when solar electricity generation increases by 1 kWh, solar homes increase their total electricity consumption by 0.18 kWh. This indicates that solar rebound effects are estimated at 18%. Building upon our theoretical framework, the increase in consumer surplus from solar panel adoption is estimated at $972/yr.     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.