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Aquatic ecologists routinely count animals to provide critical information for conservation and management. Increased accessibility to underwater recording equipment such as action cameras and unmanned underwater devices has allowed footage to be captured efficiently and safely, without the logistical difficulties manual data collection often presents. It has, however, led to immense volumes of data being collected that require manual processing, and thus significant time, labour and money. The use of deep learning to automate image processing has substantial benefits but has rarely been adopted within the field of aquatic ecology. To test its efficacy and utility, we compared the accuracy and speed of deep learning techniques against human counterparts for quantifying fish abundance in underwater images and video footage. We collected footage of fish assemblages in seagrass meadows in Queensland, Australia. We produced three models using an object detection framework to detect the target species, an ecologically important fish, luderick (Girella tricuspidata). Our models were trained on three randomised 80:20 ratios of training:validation datasets from a total of 6,080 annotations. The computer accurately determined abundance from videos with high performance using unseen footage from the same estuary as the training data (F1 = 92.4%, mAP50 = 92.5%), and from novel footage collected from a different estuary (F1 = 92.3%, mAP50 = 93.4%). The computer’s performance in determining abundance was 7.1% better than human marine experts, and 13.4% better than citizen scientists in single image test datasets, and 1.5% and 7.8% higher in video datasets, respectively. We show that deep learning can be a more accurate tool than humans at determining abundance, and that results are consistent and transferable across survey locations. Deep learning methods provide a faster, cheaper and more accurate alternative to manual data analysis methods currently used to monitor and assess animal abundance and have much to offer the field of aquatic ecology.

Using electrolysis systems to degrade organics in wastewater encourages utilizing this technique to remove micropollutants (MPs) in different types of water. In this work, a cell consisting of an anode as a boron-doped diamond (BDD) electrode combined with a gas diffusion (GDE) cathode without a separator showed that MPs degradation can be effectively achieved. Investigating different operating parameters, it was stated that applying a low current density (2 mA/cm2) and setting the Reynolds number of the electrolyte flow through the cell at the laminar range raised the treatment time by 3 folds at the same energy demand. This arrangement increased the MPs removal. Some substances like diclofenac were removed up to 84% at a longer treatment time of 180 min coupled with an increase in energy demand. The results at the mentioned parameters indicated an adequate generation rate of radicals needed to remove MPs and the oxidation reactions were promoted. The results show high practicability to the investigated electrolysis system in removing MPs in wastewater under considering the need to further reduction of the energy demand.

As systems continue to grow in scale and complexity and have to operate safely in challenging disruptive environments, system safety and resilience has become a critical requirement. This recognition has drawn attention to the concept of resilience, which has different definitions and several different interpretations that tend to be domain specific. For example, resilience in health care clinics means something quite different than resilience in self-driving cars, or energy grids. This paper reviews the different characterizations of resilience and assesses their value proposition in realizing engineered resilient systems. This paper emphasizes the importance of systems modeling in engineering resilient systems and presents an overarching methodology that employs different modeling approaches for operational tasks as a function of problem context. This paper specifically focuses on systems modeling in partially observable and potentially hostile environments. It discusses the need for system model verification, which is key to safety, and system flexibility and adaptability, which are key to resilience. It introduces a formal, probabilistic modeling construct called the “resilience contract.” This construct employs a state-based representation that formalizes the concept of resilience while enabling system model verification and affording requisite flexibility for adaptation and learning. The key findings of our research are that different system modeling approaches and algorithms are needed based on mission tasks and operational context; adaptive capacity and continual adaptability are the two promising characterizations of resilience that can be cost-effectively realized in real-world systems; and the resilience contract construct is an effective means for probabilistic verification of system model correctness while affording flexibility needed for adaptation and learning. Collectively, these findings contribute to the body of knowledge in both model-based systems engineering (MBSE) and engineered resilient systems.

A system of boron-doped diamond (BDD) anode combined with a gas diffusion electrode (GDE) as a cathode is an attractive kind of electrolysis system to treat wastewater to remove organic pollutants. Depending on the operating parameters and water matrix, the kinetics of the electrochemical reaction must be defined to calculate the reaction rate constant, which enables designing the treatment reactor in a continuous process. In this work, synthetic wastewater simulating the vacuum toilet sewage on trains was treated via a BDD-GDE reactor, where the kinetics was presented as the abatement of chemical oxygen demand (COD) over time. By investigating three different initial COD concentrations (C0,1 ≈ 2 × C0,2 ≈ 4 × C0,3), the kinetics was presented and the observed reaction rate constant kobs. was derived at different current densities (20, 50, 100 mA/cm2). Accordingly, a mathematical model has derived kobs. as a function of the cell potential Ecell. Ranging from 1 × 10−5 to 7.4 × 10−5 s−1, the kobs. is readily calculated when Ecell varies in a range of 2.5–21 V. Furthermore, it was experimentally stated that the highest economic removal of COD was achieved at 20 mA/cm2 demanding the lowest specific charge (~7 Ah/gCOD) and acquiring the highest current efficiency (up to ~48%).

The use of gas diffusion electrodes (GDEs) in microbial fuel cells (MFCs) can improve their cell performance, but tends to cause fouling. In order to allow long-term stable operation, the search for antifouling methods is necessary. Therefore, an antibacterial coating with ammonium compounds is investigated. Within the first 30 days of operation, the maximum measured power density of a GDE with antibacterial ionomer was 606 mW m−2. The GDE without an antifouling treatment could only reach a maximum of 284 mW m−2. Furthermore, there was an optimum in the loading amount with ionomer below 2.6 mg cm−2. Further investigations showed that additional aeration of the GDEs by a fan had a negative effect on their performance. Despite the higher performance, the antibacterial coating could not prevent biofilm growth at the surface of the GDE. The thickness of the biofilm was only reduced by 14–16%. However, the weight of the biofilm on the treated GDEs was 62–80% less than on a GDE without an antifouling treatment. Consequently, the coating cannot completely prevent fouling, but possibly leads to a lower density of the biofilm or prevents clogging of the pores inside the electrodes and improves their long-term stability.

Cross-habitat facilitative processes can enhance seascape restoration outcomes but there is uncertainty around the spatial dependencies of these processes across habitats. We synthesised the influence of environmental parameters on six processes underpinning cross-habitat facilitation and identified the linear distances over which they operate between habitats. All six process types occur at distances commonly used in seascape restoration demonstrating how harnessing facilitation can scale-up restoration to meet national and international goals.

Microbial fuel cells are a promising technology for future wastewater treatment, as it allows cleaning and power generation simultaneously. The bottleneck of microbial fuel cells is often its cathodes because they determine the power output. Gas diffusion electrodes might overcome this bottleneck due to their low production costs and high oxygen reduction rates. However, biofilm formation on the gas diffusion electrodes reduces their performance over time. In this work, a new reactor design of the microbial fuel cell using rotating gas diffusion electrodes is presented. The biofilm growth on the electrode during operation was observed and its effect on the performance of the microbial fuel cell was examined. In addition, different antifouling strategies were investigated over a period of 80 days. It was found that already after 7 days of operation a complete biofilm had grown on an untreated gas diffusion electrode. However, this does not seem to affect the performance of the cells in the beginning. Differences in the performance of the reactors with and without an antifouling strategy only become apparent from day 15 onwards. The use of UV radiation and antibacterial membranes leads to the best results with maximum power densities of approx. 200 mW m−2 while the untreated microbial fuel cell only achieves a maximum power density of approx. 20 mW m−2.

This paper is concerned with a priori error estimates for the local incremental minimization scheme, which is an implicit time discretization method for the approximation of rateindependent systems with nonconvex energies. We first show by means of a counterexample that one cannot expect global convergence of the scheme without any further assumptions on the energy. For the class of uniformly convex energies, we derive error estimates of optimal order, provided that the Lipschitz constant of the load is sufficiently small. Afterwards, we extend this result to the case of an energy, which is only locally uniformly convex in a neighborhood of a given solution trajectory. For the latter case, the local incremental minimization scheme turns out to be superior compared to its global counterpart, as a numerical example demonstrates.

Around cities, natural wetlands are rapidly being destroyed and replaced with wetlands constructed to treat stormwater. Although the intended purpose of these wetlands is to manage urban stormwater, they are inhabited by wildlife that might be exposed to contaminants. These effects will be exacerbated if animals are unable to differentiate between stormwater treatment wetlands of varying quality and some function as “ecological traps” (i.e., habitats that animals prefer despite fitness being lower than in other habitats). To examine if urban stormwater wetlands can be ecological traps for frogs, we tested if survival, metamorphosis-related measures, and predator avoidance behaviors of frogs differed within mesocosms that simulated stormwater wetlands with different contaminant levels, and paired this with a natural oviposition experiment to assess breeding-site preferences. We provide the first empirical evidence that these wetlands can function as ecological traps for frogs. Tadpoles had lower survival and were less responsive to predator olfactory cues when raised in more polluted stormwater wetlands, but also reached metamorphosis earlier and at a larger size. A greater size at metamorphosis was likely a result of increased per capita food availability due to higher mortality combined with eutrophication, although other compensatory effects such as selective-mortality removing smaller individuals from low-quality mesocosms may also explain these results. Breeding adults laid comparable numbers of eggs across wetlands with high and low contaminant levels, indicating no avoidance of the former. Since stormwater treatment wetlands are often the only available aquatic habitat in urban landscapes we need to better understand how they perform as habitats to guide management decisions that mitigate their potential ecological costs. This may include improving wetland quality so that fitness is no longer compromised, preventing colonization by animals, altering the cues animals use when selecting habitats, pretreating contaminated water prior to release, providing off-line wetlands nearby, or simply not constructing stormwater treatment wetlands in sensitive areas. Our study confirms the potential for urban stormwater treatment wetlands to function as ecological traps and highlights the need for greater awareness of their prevalence and impact at landscape scales.

Seagrass meadows are threatened by multiple pressures, jeopardizing the many benefits they provide to humanity and biodiversity, including climate regulation and food provision through fisheries production. Conservation of seagrass requires identification of the main pressures contributing to loss and the regions most at risk of ongoing loss. Here, we model trajectories of seagrass change at the global scale and show they are related to multiple anthropogenic pressures but that trajectories vary widely with seagrass life-history strategies. Rapidly declining trajectories of seagrass meadow extent (>25% loss from 2000 to 2010) were most strongly associated with high pressures from destructive demersal fishing and poor water quality. Conversely, seagrass meadow extent was more likely to be increasing when these two pressures were low. Meadows dominated by seagrasses with persistent life-history strategies tended to have slowly changing or stable trajectories, while those with opportunistic species were more variable, with a higher probability of either rapidly declining or rapidly increasing. Global predictions of regions most at risk for decline show high-risk areas in Europe, North America, Japan, and southeast Asia, including places where comprehensive long-term monitoring data are lacking. Our results highlight where seagrass loss may be occurring unnoticed and where urgent conservation interventions are required to reverse loss and sustain their essential services.