LarvaTagger: manual and automatic tagging of Drosophila larval behaviour.

MOTIVATION: As more behavioural assays are carried out in large-scale experiments on Drosophila larvae, the definitions of the archetypal actions of a larva are regularly refined. In addition, video recording and tracking technologies constantly evolve. Consequently, automatic tagging tools for Drosophila larval behaviour must be retrained to learn new representations from new data. However, existing tools cannot transfer knowledge from large amounts of previously accumulated data. We introduce LarvaTagger, a piece of software that combines a pre-trained deep neural network, providing a continuous latent representation of larva actions for stereotypical behaviour identification, with a graphical user interface to manually tag the behaviour and train new automatic taggers with the updated ground truth. RESULTS: We reproduced results from an automatic tagger with high accuracy, and we demonstrated that pre-training on large databases accelerates the training of a new tagger, achieving similar prediction accuracy using less data. AVAILABILITY AND IMPLEMENTATION: All the code is free and open source. Docker images are also available. See gitlab.pasteur.fr/nyx/LarvaTagger.jl.

Post-fire stabilization of thaw-affected permafrost terrain in northern Alaska.

In 2007, the Anaktuvuk River fire burned more than 1000 km2 of arctic tundra in northern Alaska, ~ 50% of which occurred in an area with ice-rich syngenetic permafrost (Yedoma). By 2014, widespread degradation of ice wedges was apparent in the Yedoma region. In a 50 km2 area, thaw subsidence was detected across 15% of the land area in repeat airborne LiDAR data acquired in 2009 and 2014. Updating observations with a 2021 airborne LiDAR dataset show that additional thaw subsidence was detected in < 1% of the study area, indicating stabilization of the thaw-affected permafrost terrain. Ground temperature measurements between 2010 and 2015 indicated that the number of near-surface soil thawing-degree-days at the burn site were 3 × greater than at an unburned control site, but by 2022 the number was reduced to 1.3 × greater. Mean annual ground temperature of the near-surface permafrost increased by 0.33 °C/yr in the burn site up to 7-years post-fire, but then cooled by 0.15 °C/yr in the subsequent eight years, while temperatures at the control site remained relatively stable. Permafrost cores collected from ice-wedge troughs (n = 41) and polygon centers (n = 8) revealed the presence of a thaw unconformity, that in most cases was overlain by a recovered permafrost layer that averaged 14.2 cm and 18.3 cm, respectively. Taken together, our observations highlight that the initial degradation of ice-rich permafrost following the Anaktuvuk River tundra fire has been followed by a period of thaw cessation, permafrost aggradation, and terrain stabilization.

Current and projected flood exposure for Alaska coastal communities.

Globally, coastal communities experience flood hazards that are projected to worsen from climate change and sea level rise. The 100-year floodplain or record flood are commonly used to identify risk areas for planning purposes. Remote communities often lack measured flood elevations and require innovative approaches to estimate flood elevations. This study employs observation-based methods to estimate the record flood elevation in Alaska communities and compares results to elevation models, infrastructure locations, and sea level rise projections. In 46 analyzed communities, 22% of structures are located within the record floodplain. With sea level rise projections, this estimate increases to 30-37% of structures by 2100 if structures remain in the same location. Flood exposure is highest in western Alaska. Sea level rise projections suggest northern Alaska will see similar flood exposure levels by 2100 as currently experienced in western Alaska. This evaluation of record flood height, category, and history can be incorporated into hazard planning documents, providing more context for coastal flood exposure than previously existed for Alaska. This basic flood exposure method is transferable to other areas with similar mapping challenges. Identifying current and projected hazardous zones is essential to avoid unintentional development in floodplains and improve long-term safety.

High-throughput automated methods for classical and operant conditioning of Drosophila larvae.

Learning which stimuli (classical conditioning) or which actions (operant conditioning) predict rewards or punishments can improve chances of survival. However, the circuit mechanisms that underlie distinct types of associative learning are still not fully understood. Automated, high-throughput paradigms for studying different types of associative learning, combined with manipulation of specific neurons in freely behaving animals, can help advance this field. The Drosophila melanogaster larva is a tractable model system for studying the circuit basis of behaviour, but many forms of associative learning have not yet been demonstrated in this animal. Here, we developed a high-throughput (i.e. multi-larva) training system that combines real-time behaviour detection of freely moving larvae with targeted opto- and thermogenetic stimulation of tracked animals. Both stimuli are controlled in either open- or closed-loop, and delivered with high temporal and spatial precision. Using this tracker, we show for the first time that Drosophila larvae can perform classical conditioning with no overlap between sensory stimuli (i.e. trace conditioning). We also demonstrate that larvae are capable of operant conditioning by inducing a bend direction preference through optogenetic activation of reward-encoding serotonergic neurons. Our results extend the known associative learning capacities of Drosophila larvae. Our automated training rig will facilitate the study of many different forms of associative learning and the identification of the neural circuits that underpin them.

Expanding beaver pond distribution in Arctic Alaska, 1949 to 2019.

Beavers were not previously recognized as an Arctic species, and their engineering in the tundra is considered negligible. Recent findings suggest that beavers have moved into Arctic tundra regions and are controlling surface water dynamics, which strongly influence permafrost and landscape stability. Here we use 70 years of satellite images and aerial photography to show the scale and magnitude of northwestward beaver expansion in Alaska, indicated by the construction of over 10,000 beaver ponds in the Arctic tundra. The number of beaver ponds doubled in most areas between ~ 2003 and ~ 2017. Earlier stages of beaver engineering are evident in ~ 1980 imagery, and there is no evidence of beaver engineering in ~ 1952 imagery, consistent with observations from Indigenous communities describing the influx of beavers over the period. Rapidly expanding beaver engineering has created a tundra disturbance regime that appears to be thawing permafrost and exacerbating the effects of climate change.

Identifying historical and future potential lake drainage events on the western Arctic coastal plain of Alaska.

Arctic lakes located in permafrost regions are susceptible to catastrophic drainage. In this study, we reconstructed historical lake drainage events on the western Arctic Coastal Plain of Alaska between 1955 and 2017 using USGS topographic maps, historical aerial photography (1955), and Landsat Imagery (ca. 1975, ca. 2000, and annually since 2000). We identified 98 lakes larger than 10 ha that partially (>25% of area) or completely drained during the 62-year period. Decadal-scale lake drainage rates progressively declined from 2.0 lakes/yr (1955-1975), to 1.6 lakes/yr (1975-2000), and to 1.2 lakes/yr (2000-2017) in the ~30,000-km2 study area. Detailed Landsat trend analysis between 2000 and 2017 identified two years, 2004 and 2006, with a cluster (five or more) of lake drainages probably associated with bank overtopping or headward erosion. To identify future potential lake drainages, we combined the historical lake drainage observations with a geospatial dataset describing lake elevation, hydrologic connectivity, and adjacent lake margin topographic gradients developed with a 5-m-resolution digital surface model. We identified ~1900 lakes likely to be prone to drainage in the future. Of the 20 lakes that drained in the most recent study period, 85% were identified in this future lake drainage potential dataset. Our assessment of historical lake drainage magnitude, mechanisms and pathways, and identification of potential future lake drainages provides insights into how arctic lowland landscapes may change and evolve in the coming decades to centuries.

Understanding the Effects of Optimal Combination of Spectral Bands on Deep Learning Model Predictions: A Case Study Based on Permafrost Tundra Landform Mapping Using High Resolution Multispectral Satellite Imagery.

Deep learning (DL) convolutional neural networks (CNNs) have been rapidly adapted in very high spatial resolution (VHSR) satellite image analysis. DLCNN-based computer visions (CV) applications primarily aim for everyday object detection from standard red, green, blue (RGB) imagery, while earth science remote sensing applications focus on geo object detection and classification from multispectral (MS) imagery. MS imagery includes RGB and narrow spectral channels from near- and/or middle-infrared regions of reflectance spectra. The central objective of this exploratory study is to understand to what degree MS band statistics govern DLCNN model predictions. We scaffold our analysis on a case study that uses Arctic tundra permafrost landform features called ice-wedge polygons (IWPs) as candidate geo objects. We choose Mask RCNN as the DLCNN architecture to detect IWPs from eight-band Worldview-02 VHSR satellite imagery. A systematic experiment was designed to understand the impact on choosing the optimal three-band combination in model prediction. We tasked five cohorts of three-band combinations coupled with statistical measures to gauge the spectral variability of input MS bands. The candidate scenes produced high model detection accuracies for the F1 score, ranging between 0.89 to 0.95, for two different band combinations (coastal blue, blue, green (1,2,3) and green, yellow, red (3,4,5)). The mapping workflow discerned the IWPs by exhibiting low random and systematic error in the order of 0.17-0.19 and 0.20-0.21, respectively, for band combinations (1,2,3). Results suggest that the prediction accuracy of the Mask-RCNN model is significantly influenced by the input MS bands. Overall, our findings accentuate the importance of considering the image statistics of input MS bands and careful selection of optimal bands for DLCNN predictions when DLCNN architectures are restricted to three spectral channels.

Organic Carbon and Nitrogen Stocks Along a Thermokarst Lake Sequence in Arctic Alaska.

Thermokarst lake landscapes are permafrost regions, which are prone to rapid (on seasonal to decadal time scales) changes, affecting carbon and nitrogen cycles. However, there is a high degree of uncertainty related to the balance between carbon and nitrogen cycling and storage. We collected 12 permafrost soil cores from six drained thermokarst lake basins (DTLBs) along a chronosequence north of Teshekpuk Lake in northern Alaska and analyzed them for carbon and nitrogen contents. For comparison, we included three lacustrine cores from an adjacent thermokarst lake and one soil core from a non thermokarst affected remnant upland. This allowed to calculate the carbon and nitrogen stocks of the three primary landscape units (DTLB, lake, and upland), to reconstruct the landscape history, and to analyze the effect of thermokarst lake formation and drainage on carbon and nitrogen stocks. We show that carbon and nitrogen contents and the carbon-nitrogen ratio are considerably lower in sediments of extant lakes than in the DTLB or upland cores indicating degradation of carbon during thermokarst lake formation. However, we found similar amounts of total carbon and nitrogen stocks due to the higher density of lacustrine sediments caused by the lack of ground ice compared to DTLB sediments. In addition, the radiocarbon-based landscape chronology for the past 7,000 years reveals five successive lake stages of partially, spatially overlapping DTLBs in the study region, reflecting the dynamic nature of ice-rich permafrost deposits. With this study, we highlight the importance to include these dynamic landscapes in future permafrost carbon feedback models.

Spatiotemporal remote sensing of ecosystem change and causation across Alaska.

Contemporary climate change in Alaska has resulted in amplified rates of press and pulse disturbances that drive ecosystem change with significant consequences for socio-environmental systems. Despite the vulnerability of Arctic and boreal landscapes to change, little has been done to characterize landscape change and associated drivers across northern high-latitude ecosystems. Here we characterize the historical sensitivity of Alaska's ecosystems to environmental change and anthropogenic disturbances using expert knowledge, remote sensing data, and spatiotemporal analyses and modeling. Time-series analysis of moderate-and high-resolution imagery was used to characterize land- and water-surface dynamics across Alaska. Some 430,000 interpretations of ecological and geomorphological change were made using historical air photos and satellite imagery, and corroborate land-surface greening, browning, and wetness/moisture trend parameters derived from peak-growing season Landsat imagery acquired from 1984 to 2015. The time series of change metrics, together with climatic data and maps of landscape characteristics, were incorporated into a modeling framework for mapping and understanding of drivers of change throughout Alaska. According to our analysis, approximately 13% (~174,000 ± 8700 km2 ) of Alaska has experienced directional change in the last 32 years (±95% confidence intervals). At the ecoregions level, substantial increases in remotely sensed vegetation productivity were most pronounced in western and northern foothills of Alaska, which is explained by vegetation growth associated with increasing air temperatures. Significant browning trends were largely the result of recent wildfires in interior Alaska, but browning trends are also driven by increases in evaporative demand and surface-water gains that have predominately occurred over warming permafrost landscapes. Increased rates of photosynthetic activity are associated with stabilization and recovery processes following wildfire, timber harvesting, insect damage, thermokarst, glacial retreat, and lake infilling and drainage events. Our results fill a critical gap in the understanding of historical and potential future trajectories of change in northern high-latitude regions.

Tundra be dammed: Beaver colonization of the Arctic.

Increasing air temperatures are changing the arctic tundra biome. Permafrost is thawing, snow duration is decreasing, shrub vegetation is proliferating, and boreal wildlife is encroaching. Here we present evidence of the recent range expansion of North American beaver (Castor canadensis) into the Arctic, and consider how this ecosystem engineer might reshape the landscape, biodiversity, and ecosystem processes. We developed a remote sensing approach that maps formation and disappearance of ponds associated with beaver activity. Since 1999, 56 new beaver pond complexes were identified, indicating that beavers are colonizing a predominantly tundra region (18,293 km2 ) of northwest Alaska. It is unclear how improved tundra stream habitat, population rebound following overtrapping for furs, or other factors are contributing to beaver range expansion. We discuss rates and likely routes of tundra beaver colonization, as well as effects on permafrost, stream ice regimes, and freshwater and riparian habitat. Beaver ponds and associated hydrologic changes are thawing permafrost. Pond formation increases winter water temperatures in the pond and downstream, likely creating new and more varied aquatic habitat, but specific biological implications are unknown. Beavers create dynamic wetlands and are agents of disturbance that may enhance ecosystem responses to warming in the Arctic.

Sedimentary and geochemical characteristics of two small permafrost-dominated Arctic river deltas in northern Alaska.

Arctic river deltas are highly dynamic environments in the northern circumpolar permafrost region that are affected by fluvial, coastal, and permafrost-thaw processes. They are characterized by thick sediment deposits containing large but poorly constrained amounts of frozen organic carbon and nitrogen. This study presents new data on soil organic carbon and nitrogen storage as well as accumulation rates from the Ikpikpuk and Fish Creek river deltas, two small, permafrost-dominated Arctic river deltas on the Arctic Coastal Plain of northern Alaska. A soil organic carbon storage of 42.4 ± 1.6 and 37.9 ± 3.5 kg C m- 2 and soil nitrogen storage of 2.1 ± 0.1 and 2.0 ± 0.2 kg N m- 2 was found for the first 2 m of soil for the Ikpikpuk and Fish Creek river delta, respectively. While the upper meter of soil contains 3.57 Tg C, substantial amounts of carbon (3.09 Tg C or 46%) are also stored within the second meter of soil (100-200 cm) in the two deltas. An increasing and inhomogeneous distribution of C with depth is indicative of the dominance of deltaic depositional rather than soil forming processes for soil organic carbon storage. Largely, mid- to late Holocene radiocarbon dates in our cores suggest different carbon accumulation rates for the two deltas for the last 2000 years. Rates up to 28 g C m- 2 year- 1 for the Ikpikpuk river delta are about twice as high as for the Fish Creek river delta. With this study, we highlight the importance of including these highly dynamic permafrost environments in future permafrost carbon estimations.

A lake-centric geospatial database to guide research and inform management decisions in an Arctic watershed in northern Alaska experiencing climate and land-use changes.

Lakes are dominant and diverse landscape features in the Arctic, but conventional land cover classification schemes typically map them as a single uniform class. Here, we present a detailed lake-centric geospatial database for an Arctic watershed in northern Alaska. We developed a GIS dataset consisting of 4362 lakes that provides information on lake morphometry, hydrologic connectivity, surface area dynamics, surrounding terrestrial ecotypes, and other important conditions describing Arctic lakes. Analyzing the geospatial database relative to fish and bird survey data shows relations to lake depth and hydrologic connectivity, which are being used to guide research and aid in the management of aquatic resources in the National Petroleum Reserve in Alaska. Further development of similar geospatial databases is needed to better understand and plan for the impacts of ongoing climate and land-use changes occurring across lake-rich landscapes in the Arctic.

Smoke signals: The decline of brand identity predicts reduced smoking behaviour following the introduction of plain packaging.

This study tests a social identity based mechanism for the effectiveness of plain tobacco packaging legislation, introduced in Australia in December 2012, to reduce cigarette smoking. 178 Australian smokers rated their sense of identification with fellow smokers of their brand, positive brand stereotypes, quitting behaviours and intentions, and smoking intensity, both before and seven months after the policy change. Mediation analyses showed that smokers, especially those who initially identified strongly with their brand, experienced a significant decrease in their brand identity following the introduction of plain packaging and this was associated with lower smoking behaviours and increased intentions to quit. The findings provide the first quantitative evidence that brand identities may help maintain smoking behaviour, and suggest the role of social-psychological processes in the effectiveness of public health policy.

Recent Arctic tundra fire initiates widespread thermokarst development.

Fire-induced permafrost degradation is well documented in boreal forests, but the role of fires in initiating thermokarst development in Arctic tundra is less well understood. Here we show that Arctic tundra fires may induce widespread thaw subsidence of permafrost terrain in the first seven years following the disturbance. Quantitative analysis of airborne LiDAR data acquired two and seven years post-fire, detected permafrost thaw subsidence across 34% of the burned tundra area studied, compared to less than 1% in similar undisturbed, ice-rich tundra terrain units. The variability in thermokarst development appears to be influenced by the interaction of tundra fire burn severity and near-surface, ground-ice content. Subsidence was greatest in severely burned, ice-rich upland terrain (yedoma), accounting for ~50% of the detected subsidence, despite representing only 30% of the fire disturbed study area. Microtopography increased by 340% in this terrain unit as a result of ice wedge degradation. Increases in the frequency, magnitude, and severity of tundra fires will contribute to future thermokarst development and associated landscape change in Arctic tundra regions.

A global database of lake surface temperatures collected by in situ and satellite methods from 1985-2009.

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985-2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues.

Continuous hemoglobin monitoring during massive blood transfusion in a multivisceral pediatric transplant patient.

A 10 year old, 25 kg girl, who was formerly a conjoined twin at the heart, diaphragm, liver, duodenum, bile ducts, and intestine, was admitted for a repeat liver, small bowel, pancreas, and kidney multivisceral transplant after having intestinal and liver failure. Intraoperatively, the patient had excessive bleeding, coagulopathy, and acidosis. Pulse co-oximetry was used for continuous monitoring of hemoglobin (Hb) during the procedure. Although noninvasive Hb appeared to follow a trend that correlated with arterial Hb concentration, it did not show accurate agreement with measured values from intermittent blood gas analysis. It may not be reliable during cases with abnormal physiology, rapid blood loss, and massive transfusion.

Nepafenac: an ophthalmic nonsteroidal antiinflammatory drug for pain after cataract surgery.

OBJECTIVE: To examine the efficacy of nepafenac in the treatment of pain and inflammation in patients after cataract surgery using evidence from controlled clinical studies. DATA SOURCES: Citations in Google Scholar, PubMed, and Web of Science from January 1, 2005, to March 25, 2013, were identified using nepafenac and cataract as search terms. STUDY SELECTION AND DATA EXTRACTION: The literature search was limited to human studies published in English. Three trials that compared nepafenac with other nonsteroidal antiinflammatory drugs (NSAIDs) were included. DATA SYNTHESIS: The pharmacokinetics and pharmacodynamics of nepafenac 0.1% suspension (and its active metabolite, amfenac) were compared with bromfenac 0.09% solution and ketorolac 0.4% solution with respect to aqueous humor concentrations and ability to reduce cyclooxygenase 1 and 2 (COX-1 and COX-2) enzymes. The maximum concentration (C(max)) values of ketorolac and amfenac were statistically similar, while the C(max) of bromfenac was significantly lower than that of amfenac. Ketorolac most effectively inhibited COX-1 enzymes; COX-2 enzymes were most effectively reduced by amfenac. When nepafenac 0.1% suspension was compared with placebo and ketorolac 0.5% solution, nepafenac achieved a higher percentage cure rate than placebo at day 14 (p = 0.0241). Significant differences in cure rates between nepafenac and ketorolac were not observed. Nepafenac 0.1%, bromfenac 0.09%, and ketorolac 0.45% were compared to determine which most effectively reduced prostaglandin E2 (PGE2) following surgery. PGE2 concentrations were significantly lowest in the ketorolac group, followed by the bromfenac and nepafenac groups, respectively. Topical nepafenac 0.1% suspension was approved in 2005. A 0.3% suspension was approved in October 2012. The 0.3% product may have some advantages over its predecessor: it is dosed once rather than thrice daily, which may increase patient adherence and improve outcomes. The price and dosing frequency of the 0.3% product are comparable to those of bromfenac 0.09% solution. CONCLUSIONS: The 2 nepafenac products appear to be equally efficacious, with a slightly increased adverse event rate in patients using the 0.3% versus 0.1% formulation. Head-to-head clinical trials that compare the 0.3% product with the 0.1% product or other commercially available NSAIDs are unavailable.

Stereotype threat and hazard perception among provisional license drivers.

Stereotype threat refers to the negative impact a stereotype about one's group can have on one's performance in domains relevant to the stereotype. In the current paper, we explore whether the negative stereotype of provisional license drivers (PLDs) might produce stereotype threat in a driving-related hazard perception task. We manipulate threat by asking participants to self-identify as PLDs in a categorization condition, or by reminding PLD participants explicitly of the stereotype of PLDs in an explicit stereotype condition. Results reveal increments in hazard perception in the categorization condition, and decrements in hazard perception in the explicit stereotype condition. Mediation analysis reveals that hazard perception performance is fully mediated by increased effort in the categorization condition and by decreased effort in the explicit stereotype condition. We discuss these findings in terms of their implications for stereotype threat and its mediators, and for public policy that explicitly discriminates between PLDs and other driver groups.

Arctic lake physical processes and regimes with implications for winter water availability and management in the National Petroleum Reserve Alaska.

Lakes are dominant landforms in the National Petroleum Reserve Alaska (NPRA) as well as important social and ecological resources. Of recent importance is the management of these freshwater ecosystems because lakes deeper than maximum ice thickness provide an important and often sole source of liquid water for aquatic biota, villages, and industry during winter. To better understand seasonal and annual hydrodynamics in the context of lake morphometry, we analyzed lakes in two adjacent areas where winter water use is expected to increase in the near future because of industrial expansion. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus imagery acquired between 1985 and 2007 were analyzed and compared with climate data to understand interannual variability. Measured changes in lake area extent varied by 0.6% and were significantly correlated to total precipitation in the preceding 12 months (p < 0.05). Using this relation, the modeled lake area extent from 1985 to 2007 showed no long-term trends. In addition, high-resolution aerial photography, bathymetric surveys, water-level monitoring, and lake-ice thickness measurements and growth models were used to better understand seasonal hydrodynamics, surface area-to-volume relations, winter water availability, and more permanent changes related to geomorphic change. Together, these results describe how lakes vary seasonally and annually in two critical areas of the NPRA and provide simple models to help better predict variation in lake-water supply. Our findings suggest that both overestimation and underestimation of actual available winter water volume may occur regularly, and this understanding may help better inform management strategies as future resource use expands in the NPRA.