A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife.     

Territorial counter-singing in male sac-winged bats (<Emphasis Type="Italic">Saccopteryx bilineata</Emphasis>): low-frequency songs trigger a stronger response

In many animal species, individuals compete for resources but avoid escalated conflicts by threat displays, i.e. a mutual signalling behaviour that enables the opponents to predict the outcome of the conflict without the necessity of actual fighting. For example, territory holders may use acoustic signals to communicate not only their own identity and the borders of their territory but also their competitive quality, fighting ability and motivation. Here, we show that male sac-winged bats, Saccopteryx bilineata, adjust their vocal territorial displays according to the fundamental frequency of territorial songs of their opponents. In playback experiments with territorial males, low-frequency stimuli elicited a higher territorial song rate and length than high-frequency stimuli. Male S. bilineata that sing more often and with lower fundamental frequencies have been shown to sire more offspring than their competitors. Fundamental frequency of territorial songs, hence, may reveal male quality and, consequently, the resulting threat posed to competing males. We argue that this is reflected in the increased response of competitors to low-frequency territorial songs shown here. Such competitive signalling behaviour has been shown in a few mammal species like red deer and baboons but, thus far, not in bats. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Comparison of 24 h averaged VOC monitoring results for residential indoor and outdoor air using Carbopack X-filled diffusive samplers and active sampling--a pilot study

Analytical results obtained by thermal desorption GC/MS for 24 h diffusive sampling of 11 volatile organic compounds (VOCs) are compared with results of time-averaged active sampling at a known constant flow rate. Air samples were collected with co-located duplicate diffusive sampling tubes and one passivated canister. A total of eight multiple-component sampling events took place at fixed positions inside and outside three private homes. Subsequently, a known amount of sample air was transferred from the canister to an adsorbent tube for analysis by thermal desorption GC/MS. Results for the 11 most prevalent compounds--Freon 11, 1,3-butadiene, benzene, toluene, tetrachloroethene, ethylbenzene, m,p-xylene, o-xylene, 4-ethyltoluene, 1,3,5-trimethylbenzene, and p-dichlorobenzene--show that the ratio of average study values (diffusive sampling to active sampling) is 0.92 with 0.70 and 1.14 extreme ratios. Absolute percent difference for duplicate samples using diffusive sampling was <10% for the four most prevalent compounds. Agreement between the two sampling approaches indicates that the prediction of approximately constant diffusive sampling rates based on previous laboratory studies is valid under the field conditions.     

Comprehensive analysis of the carbon impacts of vehicle intelligent speed control

In recent years sophisticated technologies have been developed to control vehicle speed based on the type of road the vehicle is driven on using Global Positioning Systems and in-car technology that can alter the speed of the vehicle. While reducing the speed of road vehicles is primarily of interest from a safety perspective, vehicle speed is also an important determinant of vehicle emissions and thus these technologies can be expected to have impacts on a range of exhaust emissions. This work analyses the results from a very large, comprehensive field trial that used 20 instrumented vehicles with and without speed control driven almost 500,000 km measuring vehicle speed at 10 Hz. We develop individual vehicle modal emissions models for CO₂ for 30 Euro III and Euro IV cars at a 1-Hz time resolution. Generalized Additive Models were used to describe how emissions from individual vehicles vary depending on their driving conditions, taking account of variable interactions and time-lag effects. We quantify the impact that vehicle speed control has on-vehicle emissions of CO₂ by road type, fuel type and driver behaviour. Savings in CO₂ of ≈6% were found on average for motorway-type roads when mandatory speed control was used compared with base case conditions. For most other types of road, speed control has very little effect on emissions of CO₂ and in some cases can result in increased emissions for low-speed limit urban roads. We also find that there is on average a 20% difference in CO₂ emission between the lowest and highest emitting driver, which highlights the importance of driver behaviour in general as a means of reducing emissions of CO₂.     

Inside-sediment partitioning of PAH, PCB and organochlorine compounds and inferences on sampling and normalization methods

Comparability of sediment analyses for semivolatile organic substances is still low. Neither screening of the sediments nor organic-carbon based normalization is sufficient to obtain comparable results. We are showing the interdependency of grain-size effects with inside-sediment organic-matter distribution for PAH, PCB and organochlorine compounds. Surface sediment samples collected by Van-Veen grab were sieved and analyzed for 16 PAH, 6 PCB and 18 organochlorine pesticides (OCP) as well as organic-matter content. Since bulk concentrations are influenced by grain-size effects themselves, we used a novel normalization method based on the sum of concentrations in the separate grain-size fractions of the sediments. By calculating relative normalized concentrations, it was possible to clearly show underlying mechanisms throughout a heterogeneous set of samples. Furthermore, we were able to show that, for comparability, screening at <125 μm is best suited and can be further improved by additional organic-carbon normalization.     

Estimation of road traffic emission factors from a long term tracer study

Road traffic emissions, one of the largest source categories in megacity inventories, are highly uncertain. It is essential to develop methodologies to reduce these uncertainties to manage air quality more effectively. In this paper, we propose a methodology to estimate road traffic emission factors (EFs) from a tracer experiment and from roadside pollutants measurements. We emitted continuously during about 300 non-consecutive hours a passive tracer from a finite line source placed on one site of an urban street. At the same time, we measured continuously the resulting tracer concentrations at the other side of the street with a portable on-line gas chromatograph. We used n-propane contained in commercial liquid petroleum gas (LPG) as a passive tracer. Propane offers several advantages to traditional tracers (SF6, N2O, CFCs): low price, easily available, non-reactive, negligible global warming potential, and easy to detect with commercial on-line gas chromatographs.The tracer experiment was carried out from January to March 2007 in a busy street of Ho Chi Minh City (Vietnam). Traffic volume, weather information and pollutant concentrations were also measured at the measurement site. We used the results of the tracer experiment to calculate the dilution factors and afterwards we used these dilution factors, the traffic counts and the pollutant concentrations to estimate the EFs. The proposed method assumes that the finite emission line represents the emission produced by traffic in the full area of the street and therefore there is an error associated to this assumption. We use the Computational Fluids Dynamics (CFD) model MISKAM to calculate this error and to correct the HCMC EFs. EFs for 15 volatile organic compounds (VOCs) and NO are reported here. A comparison with available studies reveals that most of the EFs estimated here are within the range of EFs reported in other studies.     

Extending the environmental risk assessment for oseltamivir (Tamiflu®) under pandemic use conditions to the coastal marine compartment

In case of an avian-influenza-derived human flu pandemic, an inordinately high use of medicines over several weeks is predicted, in particular for the recommended influenza antiviral oseltamivir (Tamiflu). While the risk of oseltamivir to sewage works and freshwater bodies has already been assessed, the fact that a large percentage of the human population worldwide lives relatively close to the sea raises concern for its environmental compatibility in coastal marine waters. The potential risk of high oseltamivir use to the marine compartment is assessed in this publication, based on the 2003 European Community Technical Guidance Document (TGD) for risk assessment. Subchronic embryo–larval ecotoxicity tests with three marine invertebrates (Pomatoceros triqueter, Annelida; Mytilus edulis, Mollusca; Paracentrotus lividus, Echinodermata) and chronic growth inhibition tests with two different groups of marine microalgae (Isochrysis galbana, Haptophyta; Skeletonema costatum, Heterokontophyta) were performed with the active substance oseltamivir carboxylic acid to derive a dependable marine predicted no-effect concentration (PNEC). This was compared to a predicted environmental concentration (PEC) for oseltamivir in coastal waters, based on the worst-case freshwater PEC. The PEC/PNEC risk characterisation ratio for the marine compartment is well below 1, which in the terminology of the TGD signifies no immediate concern. Further, while oseltamivir may be persistent (P), it is not bioaccumulative (B) nor highly ecotoxic (T) and therefore not a PBT substance. In conclusion, even a high pandemic use of oseltamivir would not lead to a significant risk for the marine compartment, in confirmation of the risk assessment for sewage works and freshwaters.     

Are anthropogenic factors affecting nesting habitat of sea turtles? The case of Kanzul beach,Riviera Maya-Tulum (Mexico)

Marine coast modification and human pressure affects many species, including sea turtles. In order to study nine anthropogenic impacts that might affect nesting selection of females, incubation and hatching survival of loggerhead (Caretta caretta) and green turtle (Chelonia mydas), building structures were identified along a 5.2 km beach in Kanzul (Mexico). A high number of hotels and houses (88; 818 rooms), with an average density of 16.6 buildings per kilometer were found. These buildings form a barrier which prevents reaching the beach from inland, resulting in habitat fragmentation. Main pressures were detected during nesting selection (14.19% of turtle nesting attempts interrupted), and low impact were found during incubation (0.77%) and hatching (4.7%). There were three impacts defined as high: beach furniture that blocks out the movement of hatchlings or females, direct pressure by tourists, and artificial beachfront lighting that can potentially mislead hatchlings or females. High impacted areas showed lowest values in nesting selection and hatching success. Based on our results, we suggest management strategies to need to be implemented to reduce human pressure and to avoid nesting habitat loss of loggerhead and green turtle in Kanzul, Mexico.     

Multiple-year black carbon measurements and source apportionment using Delta-C in Rochester,New York

Black carbon (BC), an important component of the atmospheric aerosol, has climatic, environmental, and human health significance. In this study, BC was continuously measured using a two-wavelength aethalometer (370 nm and 880 nm) in Rochester, New York, from January 2007 to December 2010. The monitoring site is adjacent to two major urban highways (I-490 and I-590), where 14% to 21% of the total traffic was heavy-duty diesel vehicles. The annual average BC concentrations were 0.76 μg/m³, 0.67 μg/m³, 0.60 μg/m³, and 0.52 μg/m³ in 2007, 2008, 2009, and 2010, respectively. Positive matrix factorization (PMF) modeling was performed using PM_2.5 elements, sulfate, nitrate, ammonia, elemental carbon (EC), and organic carbon (OC) data from the U.S. Environmental Protection Agency (EPA) speciation network and Delta-C (UVBC_370nm – BC_880nm) data. Delta-C has been previously shown to be a tracer of wood combustion factor. It was used as an input variable in source apportionment models for the first time in this study and was found to play an important role in separating traffic (especially diesel) emissions from wood combustion emissions. The result showed the annual average PM_2.5 concentrations apportioned to diesel emissions in 2007, 2008, 2009, and 2010 were 1.34 μg/m³, 1.25 μg/m³, 1.13 μg/m³, and 0.97 μg/m³, respectively. The BC conditional probability function (CPF) plots show a large contribution from the highway diesel traffic to elevated BC concentrations. The measurements and modeling results suggest an impact of the U.S Environmental Protection Agency (EPA) 2007 Heavy-Duty Highway Rule on the decrease of BC and PM_2.5 concentrations during the study period.

Implications: This study suggests that there was an observable impact of the U.S EPA 2007 Heavy-Duty Highway Rule on the ambient black carbon concentrations in Rochester, New York. Aethalometer Delta-C was used as an input variable in source apportionment models and it allowed the separation of traffic (especially diesel) emissions from wood combustion emissions.