Rapid survey protocol that provides dynamic information on reef condition to managers of the Great Barrier Reef

Managing to support coral reef resilience as the climate changes requires strategic and responsive actions that reduce anthropogenic stress. Managers can only target and tailor these actions if they regularly receive information on system condition and impact severity. In large coral reef areas like the Great Barrier Reef Marine Park (GBRMP), acquiring condition and impact data with good spatial and temporal coverage requires using a large network of observers. Here, we describe the result of ~10 years of evolving and refining participatory monitoring programs used in the GBR that have rangers, tourism operators and members of the public as observers. Participants complete Reef Health and Impact Surveys (RHIS) using a protocol that meets coral reef managers’ needs for up-to-date information on the following: benthic community composition, reef condition and impacts including coral diseases, damage, predation and the presence of rubbish. Training programs ensure that the information gathered is sufficiently precise to inform management decisions. Participants regularly report because the demands of the survey methodology have been matched to their time availability. Undertaking the RHIS protocol we describe involves three ~20 min surveys at each site. Participants enter data into an online data management system that can create reports for managers and participants within minutes of data being submitted. Since 2009, 211 participants have completed a total of more than 10,415 surveys at more than 625 different reefs. The two-way exchange of information between managers and participants increases the capacity to manage reefs adaptively, meets education and outreach objectives and can increase stewardship. The general approach used and the survey methodology are both sufficiently adaptable to be used in all reef regions.     

GC estimation of organic hydrocarbons that threaten shallow Quaternary sandy aquifer Northwestern Gulf of Suez,Egypt

Soil and groundwater contamination is one of the important environmental problems at petroleum-related sites, which causes critical environmental and health defects. Severe petroleum hydrocarbon contamination from coastal refinery plant was detected in a shallow Quaternary sandy aquifer is bordered by Gulf in the Northwestern Gulf of Suez, Egypt. The overall objective of this investigation is to estimate the organic hydrocarbons in shallow sandy aquifers, released from continuous major point-source of pollution over a long period of time (91 years ago). This oil refinery contamination resulted mainly in the improper disposal of hydrocarbons and produced water releases caused by equipment failures, vandalism, and accidents that caused direct groundwater pollution or discharge into the gulf. In order to determine the fate of hydrocarbons, detailed field investigations were made to provide intensive deep profile information. Eight composite randomly sediment samples from a test plot were selected for demonstration. The tested plot was 50 m long?×?50 m wide?×?70 cm deep. Sediment samples were collected using an American auger around the point 29° 57′ 33″ N and 32° 30′ 40″ E in 2012 and covered an area of 2,500 m² which represents nearly 1/15 of total plant area (the total area of the plant is approximately 3.250 km²). The detected total petroleum hydrocarbons (TPHs) were 2.44, 2.62, 4.54, 4.78, 2.83, 3.22, 2.56, and 3.13 wt%, respectively. TPH was calculated by differences in weight and subjected to gas chromatography (GC). Hydrocarbons were analyzed on Hewlett–Packard (HP-7890 plus) gas chromatograph equipped with a flame ionization detector (FID). The percentage of paraffine of the investigated TPH samples was 7.33, 7.24, 7.58, 8.25, 10.25, 9.89, 14.77, and 17.53 wt%, respectively.     

Models for waste life cycle assessment: Review of technical assumptions

A number of waste life cycle assessment (LCA) models have been gradually developed since the early 1990s, in a number of countries, usually independently from each other. Large discrepancies in results have been observed among different waste LCA models, although it has also been shown that results from different LCA studies can be consistent. This paper is an attempt to identify, review and analyse methodologies and technical assumptions used in various parts of selected waste LCA models. Several criteria were identified, which could have significant impacts on the results, such as the functional unit, system boundaries, waste composition and energy modelling. The modelling assumptions of waste management processes, ranging from collection, transportation, intermediate facilities, recycling, thermal treatment, biological treatment, and landfilling, are obviously critical when comparing waste LCA models.This review infers that some of the differences in waste LCA models are inherent to the time they were developed. It is expected that models developed later, benefit from past modelling assumptions and knowledge and issues. Models developed in different countries furthermore rely on geographic specificities that have an impact on the results of waste LCA models. The review concludes that more effort should be employed to harmonise and validate non-geographic assumptions to strengthen waste LCA modelling.     

The problem of estimating recent genetic connectivity in a changing world

Accurate understanding of population connectivity is important to conservation because dispersal can play an important role in population dynamics, microevolution, and assessments of extirpation risk and population rescue. Genetic methods are increasingly used to infer population connectivity because advances in technology have made them more advantageous (e.g., cost effective) relative to ecological methods. Given the reductions in wildlife population connectivity since the Industrial Revolution and more recent drastic reductions from habitat loss, it is important to know the accuracy of and biases in genetic connectivity estimators when connectivity has declined recently. Using simulated data, we investigated the accuracy and bias of 2 common estimators of migration (movement of individuals among populations) rate. We focused on the timing of the connectivity change and the magnitude of that change on the estimates of migration by using a coalescent‐based method (Migrate‐n) and a disequilibrium‐based method (BayesAss). Contrary to expectations, when historically high connectivity had declined recently: (i) both methods over‐estimated recent migration rates; (ii) the coalescent‐based method (Migrate‐n) provided better estimates of recent migration rate than the disequilibrium‐based method (BayesAss); (iii) the coalescent‐based method did not accurately reflect long‐term genetic connectivity. Overall, our results highlight the problems with comparing coalescent and disequilibrium estimates to make inferences about the effects of recent landscape change on genetic connectivity among populations. We found that contrasting these 2 estimates to make inferences about genetic‐connectivity changes over time could lead to inaccurate conclusions.     

Material and energy recovery from Automotive Shredded Residues (ASR) via sequential gasification and combustion

Shredding is the common end-of-life treatment in Europe for dismantled car wrecks. It produces the so-called Automotive Shredded Residue (ASR), usually disposed of in landfill. This paper summarizes the outcome of a study carried out by Politecnico di Milano and LEAP with the support of Actelios SpA on the prospects of a technology based on sequential gasification and combustion of this specific waste stream. Its application to the treatment of ASR allows the recovery of large fractions of metals as non-oxidized, easily marketable secondary raw materials, the vitrification of most of the ash content and the production of power via a steam cycle. Results show that despite the unfavourable characteristics of ASR, the proposed technology can reach appealing energy performances. Three of four environmental impact indicators and the cumulative energy demand index are favourable, the main positive contributes being electricity production and metal recovery (mainly aluminium and copper). The only unfavourable indicator is the global warming index because, since most of the carbon in ASR comes from fossil sources, the carbon dioxide emissions at the stack of the thermal treatment plant are mainly non-renewable and, at the same time, the avoided biogas production from the alternative disposal route of landfilling is minor.     

Modelling with uncertainty: Introducing a probabilistic framework to predict animal population dynamics

Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback–Leibler distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios.We illustrate the framework’s power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results.     

Humic acid in ice: Photo-enhanced conversion of nitrogen dioxide into nitrous acid

Laboratory studies on the heterogeneous conversion of nitrogen dioxide into nitrous acid on irradiated ice films containing humic acid are described. It was found that the presence of light in the visible range of the solar spectrum significantly enhances the rate of nitrous acid release from a humic acid doped ice film. This process might contribute to observed HONO production in snow, where the NO₂ is thought to originate from nitrate photolysis. Analysis of the experimental data based on the Langmuir Hinshelwood model framework allowed quantification of the observed dependencies of the nitrous acid production rate on nitrogen dioxide concentration. The observed dependencies on the humic acid concentration as well as on the irradiation intensity were used to estimate light-driven HONO fluxes for environmental snow covers.     

Effects of environmentally relevant concentrations of metallic compounds on the flatfish Scophthalmus maximus: biomarkers of neurotoxicity,oxidative stress and metabolism

Flatfish species, such as the turbot (Scophthalmus maximus), are common targets for toxic effects, since they are exposed through the food chain (ingestion of contaminated preys) and are in direct contact with the waterborne contaminant and sediments. Furthermore, these fish species live in close proximity to interstitial water that frequently dissolves high amounts of contaminants, including metals. Despite this significant set of characteristics, the present knowledge concerning flatfish contamination and toxicity by metals is still scarce. To attain the objective of assessing the effects of metals on a flatfish species, S. maximus specimens were chronically exposed to lead, copper and zinc, at ecologically relevant concentrations, and biochemical (oxidative stress: catalase and glutathione S-transferases activities, and lipid peroxidation; neurotoxicity: cholinesterase activity) parameters were assessed on selected tissues (gills and liver). Copper had no significant effects on all tested parameters; lead was causative of significant increases in liver GSTs activities and also in lipoperoxidation of gill tissue; exposure to zinc caused a significant increase in catalase activity of gill tissue. None of the tested metals elicited noteworthy effects in terms of neurotoxicity. The obtained results showed that only the metal lead is of some environmental importance, since it was able to cause deleterious modifications of oxidative nature at relevant concentrations.