Removal of Cr(VI) from water by in natura and magnetic nanomodified hydroponic lettuce roots

Environmental Science and Pollution Research - Biosorption is a viable and environmentally friendly process to remove pollutants and species of commercial interest. Biological materials are...     

Assumptions in ecosystem service assessments: Increasing transparency for conservation

Conservation efforts are increasingly supported by ecosystem service assessments. These assessments depend on complex multi-disciplinary methods, and rely on a number of assumptions which reduce complexity. If assumptions are ambiguous or inadequate, misconceptions and misinterpretations may arise when interpreting results of assessments. An interdisciplinary understanding of assumptions in ecosystem service science is needed to provide consistent conservation recommendations. Here, we synthesise and elaborate on 12 prevalent types of assumptions in ecosystem service assessments. These comprise conceptual and ethical foundations of the ecosystem service concept, assumptions on data collection, indication, mapping, and modelling, on socio-economic valuation and value aggregation, as well as about using assessment results for decision-making. We recommend future assessments to increase transparency about assumptions, and to test and validate them and their potential consequences on assessment reliability. This will support the taking up of assessment results in conservation science, policy and practice.Electronic supplementary materialThe online version of this article (10.1007/s13280-020-01379-9) contains supplementary material, which is available to authorized users.     

Understanding complex drivers of wildlife crime to design effective conservation interventions

In conservation understanding the drivers of behavior and developing robust interventions to promote behavioral change is challenging and requires a multifaceted approach. This is particularly true for efforts to address illegal wildlife use, where pervasive—and sometimes simplistic—narratives often obscure complex realities. We used an indirect questioning approach, the unmatched count technique, to investigate the drivers and prevalence of wildlife crime in communities surrounding 2 national parks in Uganda and combined scenario interviews and a choice experiment to predict the performance of potential interventions designed to tackle these crimes. Although poverty is often assumed to be a key driver of wildlife crime, we found that better-off households and those subject to human–wildlife conflict and those that do not receive any benefits from the parks’ tourism revenue sharing were more likely to be involved in certain types of wildlife crime, especially illegal hunting. The interventions predicted to have the greatest impact on reducing local participation in wildlife crime were those that directly addressed the drivers including, mitigating damage caused by wildlife and generating financial benefits for park-adjacent households. Our triangulated approach provided insights into complex and hard-to-access behaviors and highlighted the importance of going beyond single-driver narratives.     

Information content of female copulation calls in wild long-tailed macaques (<Emphasis Type="Italic">Macaca fascicularis</Emphasis>)

Primates are unusual in that many females display sexual signals, such as sex skin swellings/colorations and copulation calls, without any sex role reversal. The adaptive function of these signals remains largely unclear, although it has been suggested that they provide males with information on female reproductive status. For sex skin swellings, there is increasing evidence that they represent a graded signal indicating the probability of ovulation. Data on the functional significance of copulation calls are much scarcer. To clarify the information content of such calls, we recorded copulation calls in wild long-tailed macaques (Macaca fascicularis) and analysed the structure of these calls during the ovarian cycle. Specifically, we correlated selected call parameters with the female oestrogen to progestogen ratio (obtained from faecal samples), which are known to be elevated during the female's fertile phase. In addition, we ran a general linear mixed model for these call parameters, testing factors (cycle phase, occurrence/absence of ejaculation, male dominance status, occurrence/absence of mate guarding) which potentially influence female copulation calls in primates. Our results show that copulation calls of female long-tailed macaques signal mating outcome and rank of the mating partner, but not female reproductive status. They also show for the first time on primates that copulation calls can convey information on whether a female is mate guarded or not. We suspect that the function of these calls is manipulation of male mating and mate-guarding behaviour and that in this way the degree of sperm competition and ultimately male reproductive success is influenced.     

Body Mass Index (BMI) as a first-line screening criterion for detection of excessive daytime sleepiness among professional drivers

OBJECTIVES: Obstructive sleep apnea (OSA) is the main predisposing factor of excessive daytime sleepiness (EDS), and, therefore, increases the risk of road crashes. However, it is difficult to rely on medical intake for OSA or fatigue since drivers' symptoms reports are not reliable. On the other hand, direct measurement of EDS among large numbers of drivers carries serious practical drawbacks. Obstructive sleep apnea, in turn, is strongly related to obesity, and elevated body mass index (BMI) is considered one of the major risk factors for OSA. Thus, it could be postulated that BMI may carry predictive value for EDS proneness. METHODS: The present study examined the interrelation between BMI, degree of OSA, as measured with Respiratory Distress Index (RDI), and the degree of EDS, as measured with the mean sleep onset latency in the Multiple Sleep Latency Test (MSLT) among obese (BMI = 32) professional drivers. The drivers went through polysomnography followed by the five sessions of MSLT in the next day. RESULTS: In accordance with prior studies, we have found strong correlation between BMI and the degree of OSA on the one hand, and between the degree of OSA and EDS on the other hand. OSA was detected among 77.7% of the drivers, 47.1% were sleepy, 19% had severe sleepiness [mean sleep latency [MSL < or = 5 min.], 28.1% had moderate sleepiness [MSL < or = 10 min.]. None of the drivers complained about any sleep problem, including snoring, and all reported that they do not experience excessive daytime sleepiness. Thus, there was no correlation between their subjective report and objective findings. CONCLUSIONS: Obese drivers with BMI above 32 are highly prone to be sleepy during the day. Their subjective reports of OSA or fatigue symptoms are not reliable. Therefore it is highly recommended to screen them easily by weight and height measure for further sleep study and decision about their driving abilities.     

Observations from using models to fit the gas production of varying volume test cells and landfills

Landfill operators are looking for more accurate models to predict waste degradation and landfill gas production. The simple microbial growth and decay models, whilst being easy to use, have been shown to be inaccurate. Many of the newer and more complex (component) models are highly parameter hungry and many of the required parameters have not been collected or measured at full-scale landfills. This paper compares the results of using different models (LANDGEM, HBM, and two Monod models developed by the author) to fit the gas production of laboratory scale, field test cell and full-scale landfills and discusses some observations that can be made regarding the scalability of gas generation rates.The comparison of these results show that the fast degradation rate that occurs at laboratory scale is not replicated at field-test cell and full-scale landfills. At small scale, all the models predict a slower rate of gas generation than actually occurs. At field test cell and full-scale a number of models predict a faster gas generation than actually occurs.Areas for future work have been identified, which include investigations into the capture efficiency of gas extraction systems and into the parameter sensitivity and identification of the critical parameters for field-test cell and full-scale landfill predication.     

Need for multiscale planning for conservation of urban bats

For over a century there have been continual efforts to incorporate nature into urban planning. These efforts (i.e., urban reconciliation) aim to manage and create habitats that support biodiversity within cities. Given that species select habitat at different spatial scales, understanding the scale at which urban species respond to their environment is critical to the success of urban reconciliation efforts. We assessed species–habitat relationships for common bat species at 50‐m, 500‐m, and 1 km spatial scales in the Chicago (U.S.A.) metropolitan area and predicted bat activity across the greater Chicago region. Habitat characteristics across all measured scales were important predictors of silver‐haired bat (Lasionycteris noctivagans) and eastern red bat (Lasiurus borealis) activity, and big brown bat (Eptesicus fuscus) activity was significantly lower at urban sites relative to rural sites. Open vegetation had a negative effect on silver‐haired bat activity at the 50‐m scale but a positive effect at the 500‐m scale, indicating potential shifts in the relative importance of some habitat characteristics at different scales. These results demonstrate that localized effects may be constrained by broader spatial patterns. Our findings highlight the importance of considering scale in urban reconciliation efforts and our landscape predictions provide information that can help prioritize urban conservation work.     

Collaborative governance for climate change adaptation in Canada: experimenting with adaptive co-management

The search for strategies to address ‘super wicked problems’ such as climate change is gaining urgency, and a collaborative governance approach, and adaptive co-management in particular, is increasingly recognized as one such strategy. However, the conditions for adaptive co-management to emerge and the resulting network structures and relational patterns remain unclear in the literature. To address these identified needs, this study examines social relationships from a network perspective while initiating a collaborative multiactor initiative aimed to develop into adaptive co-management for climate change adaptation, an action research project undertaken in the Niagara region of Canada. The project spanned 1 year, and a longitudinal analysis of participants’ networks and level of participation in the process was performed. Evidence of support for climate change adaptation from the process included the development of deliberative and adaptive responses to opportunities presented to the group and the development of a strong subgroup of participants where decision-making was centered. However, the complexity of the challenge of addressing climate change, funding constraints, competing initiatives, and the lack of common views among participants may have contributed to the group, highlighting the finding that beneficial network structural features and relational patterns are necessary but not sufficient condition for the development of an adaptive co-management process. The context of climate change adaptation may require a different social network structure and processes than other contexts for adaptive co-management to occur, and there may be limitations to adaptive co-management for dealing with super wicked problems.     

Combining state and transition models with dynamic Bayesian networks

Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks - so-called dynamic Bayesian networks (DBNs) - for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.