1,171 research outputs found

    Modelling the cooling effects of urban canals

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    We investigate the effects of canals on urban air temperatures, performing a national-scale analysis of urban canals in the UK and Ireland. Using canal characteristics and high-temporal resolution weather data, we model variability in water temperatures for 2022 at 15-minute intervals and use these data to analyse the effects on surrounding air temperatures. In addition, we incorporate the effects of shading by buildings, which can play a key role in water energy balance. In turn, this has implications for the effectiveness of canals in offsetting temperature extremes as well as the management and regulation of adjacent urban areas

    Re-examining the effects of verbal instructional type on early stage motor learning

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    The present study investigated the differential effects of analogy and explicit instructions on early stage motor learning and movement in a modified high jump task. Participants were randomly assigned to one of three experimental conditions: analogy, explicit light (reduced informational load), or traditional explicit (large informational load). During the two-day learning phase, participants learned a novel high jump technique based on the ‘scissors’ style using the instructions for their respective conditions. For the single-day testing phase, participants completed both a retention test and task-relevant pressure test, the latter of which featured a rising high-jump-bar pressure manipulation. Although analogy learners demonstrated slightly more efficient technique and reported fewer technical rules on average, the differences between the conditions were not statistically significant. There were, however, significant differences in joint variability with respect to instructional type, as variability was lowest for the analogy condition during both the learning and testing phases, and as a function of block, as joint variability decreased for all conditions during the learning phase. Findings suggest that reducing the informational volume of explicit instructions may mitigate the deleterious effects on performance previously associated with explicit learning in the literature

    A Dynamic Ocean Management Tool to Reduce Bycatch and Support Sustainable Fisheries

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    Seafood is anessential sourceofprotein formore than3billionpeopleworldwide, yet bycatchof threatened species in capture fisheries remains a major impediment to fisheries sustainability. Management measures designed to reduce bycatch often result in significant economic losses and even fisheries closures. Static spatial management approaches can also be rendered ineffective by environmental variability and climate change, as productive habitats shift and introduce new interactions between human activities and protected species. We introduce a new multispecies and dynamic approach that uses daily satellite data to track ocean features and aligns scales of management, species movement, and fisheries. To accomplish this, we create species distribution models for one target species and three bycatch-sensitive species using both satellite telemetry and fisheries observer data. We then integrate species-specific probabilities of occurrence into a single predictive surface, weighing the contribution of each species by management concern. We find that dynamic closures could be 2 to 10 times smaller than existing static closures while still providing adequate protection of endangered nontarget species. Our results highlight the opportunity to implement near real time management strategies that would both support economically viable fisheries and meet mandated conservation objectives in the face of changing ocean conditions. With recent advances in eco-informatics, dynamic management provides a new climate-ready approach to support sustainable fisheries

    Dynamic Ocean Management: Defining and Conceptualizing Real-Time Management of the Ocean

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    Most spatial marine management techniques (e.g., marine protected areas) draw stationary boundaries around often mobile marine features, animals, or resource users. While these approaches can work for relatively stationary marine resources, to be most effective marine management must be as fluid in space and time as the resources and users we aim to manage. Instead, a shift towards dynamic ocean management is suggested, defined as management that rapidly changes in space and time in response to changes in the ocean and its users through the integration of near real-time biological, oceanographic, social and/or economic data. Dynamic management can refine the temporal and spatial scale of managed areas, thereby better balancing ecological and economic objectives. Temperature dependent habitat of a hypothetical mobile marine species was simulated to show the efficiency of dynamic management, finding that 82.0 to 34.2 percent less area needed to be managed using a dynamic approach. Dynamic management further complements existing management by increasing the speed at which decisions are implemented using predefined protocols. With advances in data collection and sharing, particularly in remote sensing, animal tracking, and mobile technology, managers are poised to apply dynamic management across numerous marine sectors. Existing examples demonstrate that dynamic management can successfully allow managers to respond rapidly to changes on-the-water, however to implement dynamic ocean management widely, several gaps must be filled. These include enhancing legal instruments, incorporating ecological and socioeconomic considerations simultaneously, developing ‘out-of-the-box’ platforms to serve dynamic management data to users, and developing applications broadly across additional marine resource sectors

    Indoline‐6‐Sulfonamide Inhibitors of the Bacterial Enzyme DapE

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    Inhibitors of the bacterial enzyme dapE-encoded N-succinyl-l,l-diaminopimelic acid desuccinylase (DapE; EC 3.5.1.18) hold promise as antibiotics with a new mechanism of action. Herein we describe the discovery of a new series of indoline sulfonamide DapE inhibitors from a high-throughput screen and the synthesis of a series of analogs. Inhibitory potency was measured by a ninhydrin-based DapE assay recently developed by our group. Molecular docking experiments suggest active site binding with the sulfonamide acting as a zinc-binding group (ZBG)

    Fit to Predict? Ecoinformatics for Predicting the Catchability of a Pelagic Fish in Near Real-Time

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    The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing ecoinformatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 years (1990-2014) of NOAA fisheries\u27 observer data from the California drift gillnet fishery, we model relative probability of occurrence (presence-absence) and catchability (total catch) of broadbill swordfish Xiphias gladius in the California Current System (CCS). Using freely-available environmental datasets and open source software, we explore the physical drivers of regional swordfish distribution. Comparing models built upon remotely-sensed datasets with those built upon a data-assimilative configuration of the Regional Ocean Modelling System (ROMS), we explore trade-offs in model construction and address how physical data can affect predictive performance and operational capacity. Swordfish catchability was found to be highest in deeper waters (\u3e1500m) with surface temperatures in the 14-20 degrees C range, isothermal layer depth (ILD) of 20-40m, positive sea surface height anomalies and during the new moon

    A Trait‐Based Framework for Assessing the Vulnerability of Marine Species to Human Impacts

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    Marine species and ecosystems are widely affected by anthropogenic stressors, ranging from pollution and fishing to climate change. Comprehensive assessments of how species and ecosystems are impacted by anthropogenic stressors are critical for guiding conservation and management investments. Previous global risk or vulnerability assessments have focused on marine habitats, or on limited taxa or specific regions. However, information about the susceptibility of marine species across a range of taxa to different stressors everywhere is required to predict how marine biodiversity will respond to human pressures. We present a novel framework that uses life-history traits to assess species’ vulnerability to a stressor, which we compare across more than 44,000 species from 12 taxonomic groups (classes). Using expert elicitation and literature review, we assessed every combination of each of 42 traits and 22 anthropogenic stressors to calculate each species’ or representative species group’s sensitivity and adaptive capacity to stressors, and then used these assessments to derive their overall relative vulnerability. The stressors with the greatest potential impact were related to biomass removal (e.g., fisheries), pollution, and climate change. The taxa with the highest vulnerabilities across the range of stressors were mollusks, corals, and echinoderms, while elasmobranchs had the highest vulnerability to fishing-related stressors. Traits likely to confer vulnerability to climate change stressors were related to the presence of calcium carbonate structures, and whether a species exists across the interface of marine, terrestrial, and atmospheric realms. Traits likely to confer vulnerability to pollution stressors were related to planktonic state, organism size, and respiration. Such a replicable, broadly applicable method is useful for informing ocean conservation and management decisions at a range of scales, and the framework is amenable to further testing and improvement. Our framework for assessing the vulnerability of marine species is the first critical step toward generating cumulative human impact maps based on comprehensive assessments of species, rather than habitats

    For which side the bell tolls: The laterality of approach-avoidance associative networks

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    The two hemispheres of the brain appear to play different roles in emotion and/or motivation. A great deal of previous research has examined the valence hypothesis (left hemisphere = positive; right = negative), but an increasing body of work has supported the motivational hypothesis (left hemisphere = approach; right = avoidance) as an alternative. The present investigation (N = 117) sought to provide novel support for the latter perspective. Left versus right hemispheres were briefly activated by neutral lateralized auditory primes. Subsequently, participants categorized approach versus avoidance words as quickly and accurately as possible. Performance in the task revealed that approach-related thoughts were more accessible following left-hemispheric activation, whereas avoidance-related thoughts were more accessible following right-hemispheric activation. The present results are the first to examine such lateralized differences in accessible motivational thoughts, which may underlie more “downstream” manifestations of approach and avoidance motivation such as judgments, decision making, and behavior
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