Training Captive-Bred or Translocated Animals to Avoid Predators

Abstract: Animal reintroductions and translocations are potentially important interventions to save species from extinction, but most are unsuccessful. Mortality due to predation is a principal cause of failure. Animals that have been isolated from predators, either throughout their lifetime or over evolutionary time, may no longer express appropriate antipredator behavior. For this reason, conservation biologists are beginning to include antipredator training in pre-release preparation procedures. We describe the evolutionary and ontogenetic circumstances under which antipredator behavior may degenerate or be lost, and we use principles from learning theory to predict which elements can be enhanced or recovered by training. The empirical literature demonstrates that training can improve antipredator skills, but the effectiveness of such interventions is influenced by a number of constraints. We predict that it will be easier to teach animals to cope with predators if they have experienced ontogenetic isolation than if they have undergone evolutionary isolation. Similarly, animals should learn more easily if they have been evolutionarily isolated from some rather than all predators. Training to a novel predator may be more successful if a species has effective responses to similar predators. In contrast, it may be difficult to teach proper avoidance behavior, or to introduce specialized predator-specific responses, if appropriate motor patterns are not already present. We conclude that pre-release training has the potential to enhance the expression of preexisting antipredator behavior. Potential training techniques involve classical conditioning procedures in which animals learn that model predators are predictors of aversive events. However, wildlife managers should be aware that problems, such as the emergence of inappropriate responses, may arise during such training.     

Pollutants and sperm quality: a systematic review and meta-analysis

Environmental Science and Pollution Research - Male fertility and semen quality have declined over recent decades. Among other causes, exposure to environmental and occupational pollution has been...     

Globalization’s limits to the environmental state? Integrating telecoupling into global environmental governance

Globalization entails increased interdependence and interconnectivities among distal regions and social-ecological systems. This global interregional connectedness – telecoupling – gives rise to specific sustainability challenges, which require new governance solutions. Moving beyond ‘scaling-up’ governance to address global environmental problems, and exploring the implications of telecoupling for state-led environmental governance, ways the state can effectively address telecoupled environmental issues both within and beyond national borders are addressed, drawing on the example of soy trade between Brazil and Germany. This builds on recent contributions to the literature on governance of interregional ecological challenges to elaborate potential policy and governance options, ranging from classical bilateral, multilateral, and international agreements, to information-based, economic, and hybrid governance modes. While telecoupled environmental problems create governance challenges related to scale, knowledge gaps, coordination, and state capacity, the state has an important role to play. To explore this further, interdisciplinary inquiry is required that includes but moves beyond the state.     

Review of Agri-Environment Indexes and Stewardship Payments

Agri-environment programs aim to secure environmental and social stewardship services through payments to farmers. A critical component of many agri-environment programs is an agri-environment index (AEI) used to quantify benefits and target investments. An AEI will typically comprise multiple indicators, which are weighted and combined using a utility function, to measure the benefit of investment options (e.g., projects, farms, regions). This article presents a review of AEIs with 11 case studies from agri-environment programs in the United States, Australia, and the United Kingdom. We identify a generic procedure used to define AEIs and explore the implications of alternative methodological approaches. We conclude that AEIs have become an extremely important policy instrument and make suggestions for their improvement.     

A fuzzy multi-attribute model for risk evaluation in workplaces

Risk assessment constitutes a critical phase of the safety management process. It basically consists of evaluating the risks involved in the execution of working activities, so as to provide the managers with information suitable to address intervention measures. The most important activity in risk assessment is the risk evaluation task but, despite its importance, national and international regulations have never formalized a standard methodology for addressing it, leaving companies complete freedom to adopt the approach they consider appropriate. As a consequence, companies generally settle on the use of simple methodologies which frequently are not able to emphasize all the main aspects affecting risk in the workplace and to produce a precise ranking of hazardous activities. In this paper, a new methodology for risk evaluation is then proposed with the aim to overcome limitations of the classical approaches. In particular, new factors are introduced to take into account effects of human behavior and environment on risk level, other than the classical injury magnitude and occurrence probability of an accident. The proposed methodology also integrates an estimative approach based on the fuzzy logic theory, which permits more coherence in the evaluation process, producing a very suitable final rank of hazardous activities. Finally, an actual case study is reported to show the capabilities of the new risk evaluation model.     

A comparison of sediment quality guidelines for toxicity assessment in the Sunderban wetlands (Bay of Bengal, India)

The aim of this paper was to obtain the first screening ecotoxicological risk evaluation in the Sunderban wetlands, the largest prograding delta in the estuarine phase of the River Ganges. The characterization of exposure was conducted by means of an extensive survey of several persistent organic pollutants (PAHs, PCBs, DDTs, PBDEs, HCHs, HCB) measured in seven core sediments from the Sunderban wetlands, obtaining a dataset with more than 2200 analyses. The pollutant effects were assessed by the use of three different sediment quality guidelines (SQGs) previously developed in the literature to evaluate toxicity induced in sediment-dwelling organisms. The three different approaches chosen for risk assessment of the Sunderban were the consensus SQGs obtained by TEC (threshold effect concentration), PEC (probable effect concentration) and EEC (extreme effect concentration), the threshold/probable effect level (TEL/PEL) approach and, finally, the ERL-ERM guidelines, including the m-ERM-Q (mean ERM quotient). The evaluation of the toxicity induced by a mixture of the target pollutants indicated the importance of gamma-HCH contamination in the Sunderban sediments despite the very low concentrations measured in core sediments. A different sensitivity for toxicity assessment due to quality guidelines was obtained, as the consensus SQGs based on TEC were less conservative and protective than the TEL and ERL approaches, while the use of m-ERM-Q seems to be the most powerful tool to predict the toxicity related to a contaminant mixture.     

A stochastic Lagrangian micromixing model for the dispersion of reactive scalars in turbulent flows: role of concentration fluctuations and improvements to the conserved scalar theory under non-homogeneous conditions

Several reaction schemes, based on the conserved scalar theory, are implemented within a stochastic Lagrangian micromixing model to simulate the dispersion of reactive scalars in turbulent flows. In particular, the formulation of the reaction-dominated limit (RDL) reaction scheme is here extended to improve the model performance under non-homogeneous conditions (NHRDL scheme). The validation of the stochastic model is obtained by comparison with the available measurements of reactive pollutant concentrations in a grid-generated turbulent flow. This test case describes the dispersion of two atmospheric reactant species (NO and O₃) and their reaction product (NO₂) in an unbounded turbulent flow. Model inter-comparisons are also assessed, by considering the results of state-of-the-art models for pollutant dispersion. The present validation shows that RDL reaction scheme provides a systematic overestimation (relative error of ca. 85% around the centreline) in computing the local reactant consumption/production rate, whereas the NHRDL scheme drastically reduces this gap (relative error lower than 5% around the centreline). In terms of NO₂ production (or reactant consumption), neglecting concentration fluctuations determines overestimations of the product mean of around 100% and a NO₂ local production of one order of magnitude higher than the reference simulation. In terms of standard deviations, the concentration fluctuations of both the passive and reactive scalars are generally of the same order of magnitude or up to 1 or 2 orders of magnitudes higher than the corresponding ensemble mean values, except for the background reactant close to the plume edges. The study highlights the importance of modelling pollutant reactions depending on the instantaneous instead of the mean concentrations of the reactants, thus quantifying the role of the turbulent fluctuations of concentration, in terms of scalar statistics (mean, standard deviation, intensity of fluctuations, skewness and kurtosis of concentration, segregation coefficient, simulated reaction rate). This stochastic particle method represents an efficient numerical technique to solve the convection–diffusion equation for reactive scalars and involves several application fields: micro-scale air quality (urban and street-canyon scales), accidental releases, impact of odours, water quality and fluid flow industrial processes (e.g. combustion).     

Effect of ferrate on green algae removal

Green algae Cladophora aegagropila, present in cooling water of thermal power plants, causes many problems and complications, especially during summer. However, algae and its metabolites are rarely eliminated by common removal methods. In this work, the elimination efficiency of electrochemically prepared potassium ferrate(VI) on algae from cooling water was investigated. The influence of experimental parameters, such as Fe(VI) dosage, application time, pH of the system, temperature and hydrodynamics of the solution on removal efficiency, was optimized. This study demonstrates that algae C. aegagropila can be effectively removed from cooling water by ferrate. Application of ferrate(VI) at the optimized dosage and under the suitable conditions (temperature, pH) leads to 100% removal of green algae Cladophora from the system. Environmentally friendly reduction products (Fe(III)) and coagulation properties favour the application of ferrate for the treatment of water contaminated with studied microorganisms compared to other methods such as chlorination and use of permanganate, where harmful products are produced.