Ecotoxicity in Aliivibrio fischeri of Ibuprofen,Omeprazole and their Mixtures

The acute ecotoxic effects of ibuprofen and omeprazole and their mixture have been measured using Aliivibrio fischeri as a biomodel. The toxic effects were also tested after 5 days, and an effect-driven approach was used to analyse the results. The toxic effects of the mixtures were compared with the predictions obtained using concentration addition and independent action mathematical methods.

According to the Passino and Smith classification, the results indicate that ibuprofen can be considered slightly toxic (10<EC₅₀ <100?mg?L^-1), while omeprazole can be denoted as moderately toxic (1<EC₅₀ <10?mg?L^-1) to Aliivibrio fischeri. An overestimation of the actual ecotoxic effect of the mixture was found when the concentration addition and independent action methods were applied. Finally, the effect-driven approach indicated that the transformation products of the studied drugs should be prioritized for risk assessment purposes.     

Arsenic biomonitoring using a hyperaccumulator fern (Pteris vittata)

Samples of Pteris vittata L. (brake fern or ladder brake) collected in Genova and in areas outside urban centres, have been analysed for arsenic content in order to assess if hyper accumulating plants are suitable for monitoring purposes. Hyper accumulation ability of the Ligurian fern populations was evaluated by analysing specimens grown with hydroponic media added with As(v). Arsenic concentrations in the range 2-310 microg g(-1) dry weight have been measured in samples collected in different sites along the Ligurian coast. Arsenic concentrations in fern fronds correlate with the estimated arsenic emission in the area, verifying the applicability of P. vittata as an arsenic biomonitor.     

When “It depends” amounts to more than simple contingent relationships: Three canonical forms of inversions

Organizational behavior theories can be subject to potential inversions in the nature of the effects expected or described (i.e. an effect inverts from positive to negative or vice versa). Yet, inversions are rarely considered or assessed. We explore three possible canonical inversions: the maximum or minimum point in a quadratic regression model, the point of intersection in disordinal interactions, and the change of slope in a moderated regression model. We describe both the motivation for, and the theoretical and empirical importance of, considering such inversions in theory‐building and testing. We consider common situations in which inversions are misinterpreted empirically and present methods to conduct explorations for potential inversions. Two different cases of errors concerning inversions can occur. In the first case entailing omission, an inversion is occurring but is not observed in the sample. In the second case, researchers wrongly assume an inversion is occurring in their model, yet the prospective inversion would actually occur out of the range of possible values on the focal variable(s), and is thus not significant. We illustrate different types of inversions using simulated examples. Ultimately, we seek to encourage and equip management researchers to identify important theoretical boundary conditions imposed by inversions. Copyright © 2016 John Wiley & Sons, Ltd.     

Leveraging social media and deep learning to detect rare megafauna in video surveys

Deep learning has become a key tool for the automated monitoring of animal populations with video surveys. However, obtaining large numbers of images to train such models is a major challenge for rare and elusive species because field video surveys provide few sightings. We designed a method that takes advantage of videos accumulated on social media for training deep-learning models to detect rare megafauna species in the field. We trained convolutional neural networks (CNNs) with social media images and tested them on images collected from field surveys. We applied our method to aerial video surveys of dugongs (Dugong dugon) in New Caledonia (southwestern Pacific). CNNs trained with 1303 social media images yielded 25% false positives and 38% false negatives when tested on independent field video surveys. Incorporating a small number of images from New Caledonia (equivalent to 12% of social media images) in the training data set resulted in a nearly 50% decrease in false negatives. Our results highlight how and the extent to which images collected on social media can offer a solid basis for training deep-learning models for rare megafauna detection and that the incorporation of a few images from the study site further boosts detection accuracy. Our method provides a new generation of deep-learning models that can be used to rapidly and accurately process field video surveys for the monitoring of rare megafauna.     

Applying assessments of adaptive capacity to inform natural-resource management in a changing climate

Adaptive capacity (AC)—the ability of a species to cope with or accommodate climate change—is a critical determinant of species vulnerability. Using information on species’ AC in conservation planning is key to ensuring successful outcomes. We identified connections between a list of species’ attributes (e.g., traits, population metrics, and behaviors) that were recently proposed for assessing species’ AC and management actions that may enhance AC for species at risk of extinction. Management actions were identified based on evidence from the literature, a review of actions used in other climate adaptation guidance, and our collective experience in diverse fields of global-change ecology and climate adaptation. Selected management actions support the general AC pathways of persist in place or shift in space, in response to contemporary climate change. Some actions, such as genetic manipulations, can be used to directly alter the ability of species to cope with climate change, whereas other actions can indirectly enhance AC by addressing ecological or anthropogenic constraints on the expression of a species’ innate abilities to adapt. Ours is the first synthesis of potential management actions directly linked to AC. Focusing on AC attributes helps improve understanding of how and why aspects of climate are affecting organisms, as well as the mechanisms by which management interventions affect a species’ AC and climate change vulnerability. Adaptive-capacity-informed climate adaptation is needed to build connections among the causes of vulnerability, AC, and proposed management actions that can facilitate AC and reduce vulnerability in support of evolving conservation paradigms.     

Redesigning harvest strategies for sustainable fishery management in the face of extreme environmental variability

Short-lived, fast-growing species that contribute greatly to global capture fisheries are sensitive to fluctuations in the environment. Uncertainties in exact stock–environment relationships have meant that environmental variability and extremes have been difficult to integrate directly into fisheries management. We applied a management strategy evaluation approach for one of Australia's large prawn stocks to test the robustness of harvest control rules to environmental variability. The model ensemble included coupled environmental-population models and an alternative catchability scenario fitted to historical catch per unit effort data. We compared the efficacy of alternative management actions to conserve marine resources under a variable environment while accounting for fisher livelihoods. Model fits to catch per unit effort were reasonably good and similar across operating models (OMs). For models that were coupled to the environment, environmental parameters for El Niño years were estimated with good associated precision, and OM3 had a lower AIC score (77.61)  than the base model (OM1, 80.39), whereas OM2 (AIC 82.41) had a similar AIC score, suggesting the OMs were all plausible model alternatives. Our model testing resulted in a plausible subset of management options, and stakeholders selected a permanent closure of the first fishing season based on overall performance of this option; ability to reduce the risk of fishery closure and stock collapse; robustness to uncertainties; and ease of implementation. Our simulation approach enabled the selection of an optimal yet pragmatic solution for addressing economic and conservation objectives under a variable environment with extreme events.     

Practitioner insights as a means of setting a context for conservation

A key obstacle to conservation success is the tendency of conservation professionals to tackle each challenge individually rather than collectively and in context. We sought to prioritize barriers to conservation previously described in the conservation literature. We undertook an online survey of 154 practitioners from over 70 countries to ascertain the most important barriers to conservation they faced. We used statistical analyses to identify the key impediments to conservation success and to examine whether these were affected by organizational attributes. Twenty-one barriers were identified. The importance ascribed to those was influenced by continent of operation and organization size, but not by organization age or autonomy (from larger parent organizations). We found the most important barriers to consider when undertaking conservation action were wider issues (e.g., population growth, consumerism, favoring development, and industrial-scale activity), operating environment (e.g., lack of political will, ineffective law enforcement, weak governments, corruption, safety and security), community attributes (e.g., dynamics, conflicts, and education levels), and the way conservation is undertaken (overconfidence, lack of funding, and externally set agendas). However, we advise against applying a one-size-fits-all approach. We propose that conservationists account for the complex socioecological systems they operate in if they are to achieve success.     

Comparing the effect of elevated pCO2 and temperature on the fertilization and early development of two species of oysters

This study compared the synergistic effects of elevated pCO₂ and temperature on the early life history stages of two ecologically and economically important oysters: the Sydney rock oyster, Saccostrea glomerata and the Pacific oyster, Crassostrea gigas. Gametes, embryos, larvae and spat were exposed to four pCO₂ (375, 600, 750, 1,000 μatm) and four temperature (18, 22, 26, 30°C) levels. At elevated pCO₂ and suboptimal temperatures, there was a reduction in the fertilization success of gametes, a reduction in the development of embryos and size of larvae and spat and an increase in abnormal morphology of larvae. These effects varied between species and fertilization treatments with S. glomerata having greater sensitivity than C. gigas. In the absence of adaptation, C. gigas may become the more dominant species along the south-eastern coast of Australia, recruiting into estuaries currently dominated by the native S. glomerata.     

Life cycle assessment of biogas upgrading technologies

This article evaluates the life cycle assessment (LCA) of three biogas upgrading technologies. An in-depth study and evaluation was conducted on high pressure water scrubbing (HPWS), as well as alkaline with regeneration (AwR) and bottom ash upgrading (BABIU), which additionally offer carbon storage. AwR and BABIU are two novel technologies that utilize waste from municipal solid waste incinerators - namely bottom ash (BA) and air pollution control residues (APC) - and are able to store CO(2) from biogas through accelerated carbonation processes. These are compared to high pressure water scrubbing (HPWS) which is a widely used technology in Europe. The AwR uses an alkaline solution to remove the CO(2) and then the solution - rich in carbonate and bicarbonate ions - is regenerated through carbonation of APC. The BABIU process directly exposes the gas to the BA to remove and immediately store the CO(2), again by carbonation. It was determined that the AwR process had an 84% higher impact in all LCA categories largely due to the energy intensive production of the alkaline reactants. The BABIU process had the lowest impact in most categories even when compared to five other CO(2) capture technologies on the market. AwR and BABIU have a particularly low impact in the global warming potential category as a result of the immediate storage of the CO(2). For AwR, it was determined that using NaOH instead of KOH improves its environmental performance by 34%. For the BABIU process the use of renewable energies would improve its impact since accounts for 55% of the impact.