Monitoring organic contaminants in eggs of glaucous and glaucous-winged gulls (Larus hyperboreus and Larus glaucescens) from Alaska

Gull eggs have been used to monitor contaminants in many parts of the world. The Seabird Tissue Archival and Monitoring Project (STAMP) is a long-term program designed to track trends in pollutants in northern marine environments using seabird eggs. Glaucous and glaucous-winged gull (Larus hyperboreus and Larus glaucescens) eggs collected in 2005 from seven Alaskan colonies were analyzed for organic contaminants. Concentrations ranged from below detection limits to 322 ng g⁻¹ wet mass in one egg for 4,4′-DDE and differed among the samples collected in the Gulf of Alaska and Bering and Chukchi Seas. Chick growth and survival rates may be affected by the contaminant levels found in the eggs, but the eggs should be safe for human consumption if they are eaten in small quantities. STAMP plans to continue collecting and banking gull eggs for future real-time and retrospective analyses.     

Emission profile of 18 carbonyl compounds,CO, CO2, and NOx emitted by a diesel engine fuelled with diesel and ternary blends containing diesel,ethanol and biodiesel or vegetable oils

The impact of vehicular emissions on air depends, among other factors, on the composition of fuel and the technology used to build the engines. The reduction of vehicular emissions requires changes in the fuel composition, and improving the technologies used in the manufacturing of engines and for the after-treatment of gases. In general, improvements to diesel engines have targeted not only emission reductions, but also reductions in fuel consumption. However, changes in the fuel composition have been shown to be a more rapid and effective alternative to reduce pollution. Some factors should been taken into consideration when searching for an alternative fuel to be used in diesel engines, such as emissions, fuel stability, availability and its distribution, as well as its effects on the engine durability. In this work, 45 fuel blends were prepared and their stability was evaluated. The following mixtures (v/v/v) were stable for the 90-day period and were used in the emission study: diesel/ethanol – 90/10%, diesel/ethanol/soybean biodiesel – 80/15/5%, diesel/ethanol/castor biodiesel – 80/15/5%, diesel/ethanol/residual biodiesel – 80/15/5%, diesel/ethanol/soybean oil – 90/7/3%, and diesel/ethanol/castor oil – 90/7/3%. The diesel/ethanol fuel showed higher reduction of NO_x emission at a lower load (2 kW) when compared with pure diesel. The other fuels showed a decrease of NO_x emissions in the ranges of 6.9–75% and 4–85% at 1800 rpm and 2000 rpm, respectively. The combustion efficiencies of the diesel can be enhanced by the addition of the oxygenate fuels, like ethanol and biodiesel/vegetable oil, resulting in a more complete combustion in terms of NO_x emission. In the case of CO₂ the decreases were in the ranges of 5–24% and 4–6% at 1800 rpm and 2000 rpm, respectively. Meanwhile, no differences were observed in CO emission. The carbonyl compounds (CC) studied were formaldehyde, acetaldehyde, propionaldehyde, acrolein, acetone, crotonaldehyde, butyraldehyde, butanone, benzaldehyde, isovaleraldehyde, valeraldehyde, o-toluenaldehyde, m-toluenaldehyde, p-toluenaldehyde, hexaldehyde, octaldehyde, 2,5-dimethylbenzaldehyde, and decaldehyde. Among them, formaldehyde, acetaldehyde, acetone, and propionaldehyde showed the highest emission concentrations. When ternary blend contains vegetable oil, there is a strong tendency to increase the emissions of the high weight CC and decrease the emissions of the low weight CC. The highest concentration of acrolein was observed when the fuel contains diesel, ethanol and biodiesel. With the exception of NO_x, the use of ternary blended fuels resulted on the increase in the emission rates of the studied compounds.     

Back-extrapolation of estimates of exposure from current land-use regression models

Land use regression has been used in epidemiologic studies to estimate long-term exposure to air pollution within cities. The models are often developed toward the end of the study using recent air pollution data. Given that there may be spatially-dependent temporal trends in urban air pollution and that there is interest for epidemiologists in assessing period-specific exposures, especially early-life exposure, methods are required to extrapolate these models back in time. We present herein three new methods to back-extrapolate land use regression models. During three two-week periods in 2005–2006, we monitored nitrogen dioxide (NO₂) at about 130 locations in Montreal, Quebec, and then developed a land-use regression (LUR) model. Our three extrapolation methods entailed multiplying the predicted concentrations of NO₂ by the ratio of past estimates of concentrations from fixed-site monitors, such that they reflected the change in the spatial structure of NO₂ from measurements at fixed-site monitors. The specific methods depended on the availability of land use and traffic-related data, and we back-extrapolated the LUR model to 10 and 20 years into the past. We then applied these estimates to residential information from subjects enrolled in a case–control study of postmenopausal breast cancer that was conducted in 1996.Observed and predicted concentrations of NO₂ in Montreal decreased and were correlated in time. The estimated concentrations using the three extrapolation methods had similar distributions, except that one method yielded slightly lower values. The spatial distributions varied slightly between methods. In the analysis of the breast cancer study, the odds ratios were insensitive to the method but varied with time: for a 5 ppb increase in NO₂ using the 2006 LUR the odds ratio (OR) was about 1.4 and the ORs in predicted past concentrations of NO₂ varied (OR～1.2 for 1985 and OR～1.3–1.5 for 1996). Thus, the ORs per unit exposure increased with time as the range and variance of the spatial distributions decreased, and this is due partly to the regression coefficient being approximately inversely proportional to the variance of exposure. Changing spatial variability complicates interpretation and this may have important implications for the management of risk. Further studies are needed to estimate the accuracy of the different methods.     

Metabolic signatures associated with environmental pollution by metals in Doñana National Park using P. clarkii as bioindicator

Bioindicators can reflect the effects of pollutants on their metabolism, being widely used to assess environmental stress. In this sense, the crab Procambarus clarkii has been previously proposed to monitor the contamination in Doñana National Park (southwest Spain) using conventional biomarkers. In this work, a metabolomic approach based on direct infusion mass spectrometry, which allows an easy and quick study of a large number of metabolites in a single run, was used for pollution assessment of this area, considering the biological response of this organism to contamination. In addition, metal accumulation in crab tissues was determined. Thus, the integrated analysis of metabolomic and metallomic data enabled the study of metabolic response of the organism against pollution. Several metabolites were discovered as potential biomarkers of pollution, such as decreased levels of carnosine, alanine, niacinamide, acetoacetate, pantothenic acid, ascorbate, glucose-6-phosphate, arginine, glucose, lactate, phospholipids, and tryglicerides, as well as elevated levels of acetyl carnitine, phosphocholine, choline, and uric acid. In this way, metal-induced toxicity could be related to metabolic impairments, principally oxidative stress, metabolic dysfunction, and dyslipidemia.     

An Assessment of Road Impacts on Wildlife Populations in U.S. National Parks

Current United States National Park Service (NPS) management is challenged to balance visitor use with the environmental and social consequences of automobile use. Wildlife populations in national parks are increasingly vulnerable to road impacts. Other than isolated reports on the incidence of road-related mortality, there is little knowledge of how roads might affect wildlife populations throughout the national park system. Researchers at the Western Transportation Institute synthesized information obtained from a system-wide survey of resource managers to assess the magnitude of their concerns on the impacts of roads on park wildlife. The results characterize current conditions and help identify wildlife-transportation conflicts. A total of 196 national park management units (NPS units) were contacted and 106 responded to our questionnaire. Park resource managers responded that over half of the NPS units’ existing transportation systems were at or above capacity, with traffic volumes currently high or very high in one quarter of them and traffic expected to increase in the majority of units. Data is not generally collected systematically on road-related mortality to wildlife, yet nearly half of the respondents believed road-caused mortality significantly affected wildlife populations. Over one-half believed habitat fragmentation was affecting wildlife populations. Despite these expressed concerns, only 36% of the NPS units used some form of mitigation method to reduce road impacts on wildlife. Nearly half of the respondents expect that these impacts would only worsen in the next five years. Our results underscore the importance for a more systematic approach to address wildlife-roadway conflicts for a situation that is expected to increase in the next five to ten years.     

Multiyear monitoring of survival following mitigation-driven translocation of a long-lived threatened reptile

Translocation is used by managers to mitigate the negative impacts of development on species. Moving individuals to a new location is challenging, and many translocation attempts have failed. Robust, posttranslocation monitoring is therefore important for evaluating effects of translocation on target species. We evaluated the efficacy of a translocation designed to mitigate the effects of a utility-scale solar energy project on the U.S. federally listed Mojave desert tortoise (Gopherus agassizii). The species is a long-lived reptile threatened by a variety of factors, including habitat loss due to renewable energy development in the Mojave Desert and portions of the Colorado Desert in southern California (southwestern United States). We translocated 58 individual tortoises away from the project's construction site and intensively monitored them over 5 years (2012–2017). We monitored these individuals and tortoises located in the translocation release area (resident tortoises; n = 112) and control tortoises (n = 149) in a nearby location. We used our tortoise encounter data and known-fate survival models to estimate annual and cumulative survival. Translocated tortoises in each of 2 size classes (120–160 mm, >160 mm) did not survive at lower rates than resident and control tortoises over the study period. For models with different sets of biotic and abiotic covariates, annual and cumulative estimates of survival were always >0.87 and >0.56, respectively. Larger tortoises tended to have higher survival, but translocated tortoises were not differentially affected by the covariates used to model variation in survival. Based on these findings, our translocation design and study protocols could inform other translocation projects for desert species. Our case study highlights the benefits of combining rigorous scientific monitoring with well-designed, mitigation-driven management actions to reduce the negative effects of development on species of conservation concern.     

Campesino hunting and conservation in Latin America

Hunting presents a paradox for biodiversity conservation. It is both a problem and a solution to species declines and poverty. Yet, conservation scientists hold different assumptions about the significance and sustainability of hunting based on the cultures and identities of hunters. In Latin America, conservationists largely sort hunters as either indigenous or campesino. Indigenous hunters are often characterized as culturally driven stewards of wildlife sustainability. Campesino hunters, by contrast, are described as peasants—cultureless, uneducated, and uncaring toward wildlife sustainability. Although such ethnically fueled hunting discourse promotes hunting research, campesino hunters remain underrepresented in most comparative hunting reviews. Moreover, there are no targeted syntheses on the current state of knowledge about campesino hunting, nothing to guide conservation research and practice with and for the largest group of hunters in Latin America. We reviewed 334 articles published from 1937 to 2018 in English (55%) and Spanish (45%)—mostly published in 145 peer-reviewed journals—on the meanings, motivations, and sustainability of campesino hunting in Latin America. Although studies spanned 17 countries, 7 ecosystems, and >75 indigenous and nonindigenous demographics in 30 research contexts, they predominantly focused on nonindigenous campesinos for species-specific conservation and protected area management in tropical broadleaf forests of Mexico, Peru, and Colombia. Authors used 12 methods to collect campesino hunting data, primarily interviews, surveys, and questionnaires, and drew from 10 local and traditional knowledge themes about wildlife trends and uses. Eighteen drivers, 14 constraints, and 10 conflicts—mainly subsistence, income, ethics, regulations, and crop or livestock protection—shaped whether campesino hunters pursued 799 species, 70% of which were least concern species. Yet, only 25 studies (8%) empirically assessed sustainability. Our results show the need for increased interdisciplinary and geographic engagement with campesino hunting across Latin America.     

COVID-19: the impact of a global crisis on sustainable development teaching

Environment, Development and Sustainability - The COVID-19 pandemic has caused a global crisis, one which also influences the ways sustainability is being taught at universities. This paper...     

A condition metric for Eucalyptus woodland derived from expert evaluations

The evaluation of ecosystem quality is important for land‐management and land‐use planning. Evaluation is unavoidably subjective, and robust metrics must be based on consensus and the structured use of observations. We devised a transparent and repeatable process for building and testing ecosystem metrics based on expert data. We gathered quantitative evaluation data on the quality of hypothetical grassy woodland sites from experts. We used these data to train a model (an ensemble of 30 bagged regression trees) capable of predicting the perceived quality of similar hypothetical woodlands based on a set of 13 site variables as inputs (e.g., cover of shrubs, richness of native forbs). These variables can be measured at any site and the model implemented in a spreadsheet as a metric of woodland quality. We also investigated the number of experts required to produce an opinion data set sufficient for the construction of a metric. The model produced evaluations similar to those provided by experts, as shown by assessing the model's quality scores of expert‐evaluated test sites not used to train the model. We applied the metric to 13 woodland conservation reserves and asked managers of these sites to independently evaluate their quality. To assess metric performance, we compared the model's evaluation of site quality with the managers’ evaluations through multidimensional scaling. The metric performed relatively well, plotting close to the center of the space defined by the evaluators. Given the method provides data‐driven consensus and repeatability, which no single human evaluator can provide, we suggest it is a valuable tool for evaluating ecosystem quality in real‐world contexts. We believe our approach is applicable to any ecosystem.