We describe a new method for the reconstruction (or forecast) of probabilities that distal geographic locations were inundated by a large pyroclastic density current (PDC) in terms of the flow mass and related uncertainties. Using appropriate model input uncertainty distributions, derived from expert judgements using the equal weights combination rule, we can estimate the mass amount needed to reach a marginal locality at any given confidence level and compare this with ambiguous or inexact peripheral field data. Our analysis relies on different versions of the Huppert and Simpson (1980) integral formulation of axisymmetric gravity-driven particle currents. We focus on models which possess analytical solutions, enabling us to utilize a very fast functional approach for enumerating results and uncertainties. In particular, we adapt the ‘energy conoid’ approach to generate inundation maps along radial directions, based on comparison of the mass-dependent kinetic energy of the flow with the potential energy control by topography in the direction of flow at distal ranges. We focus on two alternative conceptual models: (i) Model 1 assumes the entire amount of solid material originates from a prescribed height above the volcano and flows as a granular current slowed by constant friction; (ii) Model 2 is a multi-phase formulation and includes, in addition to suspended particles, interstitial gas thermally buoyant with respect to surrounding cold air. In the latter case, the flow stops propagating at the surface when the solid fraction becomes less than a critical value, and there is lift-off of the remaining mixture of gas and small particulates. Our model parameters can be further constrained where there is reliable field data or information from analogue eruptions. Finally, we used a Bayes Belief Network related to each inversion model to evaluate probabilistically the uncertainties on the mass required, estimating correlation coefficients between input variables and the calculated mass. For any major magnitude ignimbrite PDC scenario, our method provides a rational basis for assessing the probability of distal flow inundation at critical peripheral locations when there is major uncertainty about the actual or predicted extent of flow runout. Example case histories are illustrated.

Ice motion in land terminating regions of the Greenland Ice Sheet is controlled in part by meltwater input into moulins. Moulins, large near-vertical shafts that deliver supraglacial water to the bed, modulate local and regional basal water pressure and ice flow by influencing subglacial drainage efficiency on daily to seasonal timescales. Our previous modeling work found that the geometry of a moulin near the water line has substantial effect on subglacial water pressure variations. Here, we develop a new physically based moulin model which can help constrain moulin shape across the ice sheet and its influence on hydraulic head oscillation, and inform the englacial void parameter used in glacier hydrology modeling. The Moulin Shape (MouSh) model (in Matlab and Python) provides new insight into the evolution of subsurface moulin size and shape at hourly to multi-year timescales. The modeled moulin is initialized as a vertical cylinder. The moulin walls melt back above and below the water line due to the dissipation of turbulent energy, open or close due to viscous and elastic deformation, and freeze inward in winter when cold air temperatures and an absence of meltwater allow refreezing. We combine MouSh modeling results with geometric data from two moulins in Pâkitsoq, western Greenland, which we mapped to the water line. The moulins have heterogeneous shapes and volumes in the top 100 m. This suggests that the size and shape of the upper portion is controlled by local and regional pre-existing fractures, which provide preferential paths for water flow and melting, creating stochastic karst-like conduit shapes. Modeling results show that moulin geometry below the water line is influenced by the hydraulic head, which controls the depth-dependent elastic and viscous closure rates, and by the roughness of the walls, which enhances melt-out rates that oppose moulin closure. We show that subglacial water pressure across the ice sheet is likely influenced by moulin geometry, underscoring the need for including moulins in subglacial models.

Flash droughts have recently gained significant attention due to their severe economic and ecological impacts. Despite extensive and growing research on flash drought processes, predictability, and trends, there is still no standard quantitative definition that encompasses all flash drought characteristics and pathways. This has motivated efforts to define, inventory, monitor, and forecast flash drought events. In our recent studies of flash droughts over the United States, we have introduced the Soil Moisture Volatility Index definition (SMVI) to inventory the onset dates and severity of flash across the Contiguous United States (CONUS) for the period 1979-2018. Post to an extended evaluation and comparison to other flash drought definitions and independent vegetation and crop datasets for seminal flash drought events, the SMVI has proved effectiveness in capturing flash drought onset in both humid and semi-arid regions. Using our SMVI inventory of flash droughts, we examine and classify flash droughts events based on multiple land surface and atmospheric conditions that may represent predictable drivers using a K-means-based clustering methodology. We found that there are three distinct classes of flash drought that can be diagnosed in our inventory. The first defined class of events are the “dry and demanding” droughts, showing high anomalies of evaporative demand and low soil moisture levels; The second are “evaporative” events, which develop under conditions of high demand and when elevated evapotranspiration accelerates soil drying, and a third class that we refer to as “stealth” events, which may be challenging to predict based on precursor atmospheric conditions due to the lack of a clear atmospheric signal with the observed modest anomalies. The contrasting meteorological and surface process signatures of the three classes do, however, indicate that events identified as “flash drought” using a reasonable definition, including events that have been widely reported as seminal flash droughts, represent a diversity of onset and intensification processes. Our results suggest that recognizing this diversity is critical to advance our understanding and ability to predict these events.

The Southwest Watershed Research Center (SWRC) of the United States Department of Agriculture-Agricultural Research Service has been conducting arid and semiarid (dryland) watershed research since 1953. This included establishment and continuous operation of the Walnut Gulch Experimental Watershed (WGEW) in southeast Arizona. The 149 km2 ephemeral watershed is one of the most densely instrumented dryland research catchments in the world with a drainage area greater than 10 km2. This instrumentation captures many aspects of the hydrological cycle including how precipitation is partitioned into soil moisture, runoff and evapotranspiration and its subsequent effects on sediment transport, vegetation productivity, carbon sequestration, and groundwater recharge. The long-term, high-resolution record of observations on the WGEW enables understanding of the mean and variability of the hydrological processes, not well characterized with shorter term records, that fail to capture the large variability common to dryland regions. This presentation will highlight trends in temperature, precipitation, and runoff over the WGEW observation period. Additional research findings made by the SWRC and collaborators on erosion; plant productivity and carbon sequestration; the facilitation of soil water redistribution by plant roots; and groundwater recharge will also be presented.

The rise of high-throughput phenotyping (HTP) has led to a dramatic increase in the ability to rapidly – and accurately – phenotype various organisms including plants. However, methods for efficiently managing, processing, analyzing, and sharing HTP data have not caught up to this new-found ability to collect big data which in turn introduces a whole host of new challenges. To address these, we have architected and implemented a multi-faceted infrastructure of webservices to further unify and automate the entire data collection process. We have integrated CyVerse and Slack into our IoHTP, two commonly used tools within plant science labs. CyVerse is a cloud-based data storage & management solution and Slack allows for bilateral instant-message communication with the HTP machines to keep researchers in touch with their autonomous experiments. Next, we are also developing our own website for administering jobs remotely to any number of (possibly geographically distributed) HTP machines. This innovative open-source approach has the potential to further advance high-throughput phenotyping worldwide by allowing interdisciplinary experts, namely in the plant and computer sciences, to collaborate more effectively and efficiently.

Iron is the fourth most common element found in the earth crust. Although it may not be as important for soil fertility as, e.g., phosphorus, nitrogen and organic matter, its absence would be detrimental to plant growth. At the same time, iron oxides are highly correlated with phosphorus availability. Iron is thus an indicator for soil fertility and the usability of an area for cultivation of crop. A relatively high spectral resolution is needed for mapping iron oxide contents with spectral reflectance data, and remote sensing is the only suitable tool for surveying large areas at a high temporal and spatial interval. Sentinel-2 MSI (MultiSpectral Instrument) is the Landsat-like spatial resolution (10–60 m) super-spectral instrument of the European Space Agency (ESA), aimed at additional data continuity for global land surface monitoring with Landsat and Satellite Pour l’Observation de la Terre (SPOT) missions. Several studies with simulated and real data have been conducted in the last several years to show the potential of Sentinel-2 MSI, including its use for geological remote sensing, mineral mapping in particular. Sentinel-2 has several bands that cover the 0.9 μm iron absorption feature, while space-borne sensors traditionally used for geologic remote sensing, like ASTER and Landsat, had only one band in this feature. In this paper, we show a comparison of Sentinel-2 and AVIRIS to demonstrate the usability of the VNIR bands for mapping the near-infrared iron absorption feature. Next, we present spectral indices for mapping iron minerals that are important in soil fertility and mineral exploration.

Apatite (U-Th)/He (AHe) thermochronology depends on accurate knowledge of how diffusion occurs. This involves measurement of core diffusion kinetics as well as understanding the behavior of migrating He atoms. Drawing from previous studies as well as data obtained via continuous ramped heating (CRH), we assess several processes that need to be integrated into a single model for He diffusion in apatite. CRH analyses conducted at different heating rates show a kinetic response for both the “normal” lower-temperature and the higher-temperature release peaks, with peaks shifting to lower temperatures at lower heating rates. Where we do see a rollover in Arrhenius trends it also shows a kinetic response, being deferred to higher temperatures at higher heating rates, though many samples with unimodal release peaks do not show a significant rollover; fluorapatites seem to show more prominent rollover. For samples showing multiple release peaks, we find that their Arrhenius data often transition from one lower-temperature trend to another at higher temperatures that has about the same slope and thus activation energy. This looks very much like MDD behavior in K-feldspar, and MDD domain analysis fits the observed data very well, even if mechanisms involving discrete domain sizes are implausible. This interesting and unexplained result must speak to the nature of what is happening during analysis of samples having trapped He. To explore our data, we coded a simple diffusion model in which single He atoms are free to jump within a grid, but can also arrive at grid nodes designated as reversible sinks, escape from which depends on an exponentially temperature- dependent probability. The model includes radiogenic He production over geological thermal histories followed by laboratory CRH outgassing. When conditioned using D values observed for AHe, the model accurately predicts parameters such as closure temperature and fractional loss. When traps are introduced, the model simulates the essential nature of the dual-peak CRH results we see. Three important results emerge from this model. (1) Few sinks need be present. (2) Trapping occurs twice during diffusion, first in nature and then again during laboratory outgassing, meaning that the ratio of the gas amounts beneath each CRH peak overestimates the geological trapping. (2) Trapping in nature is very dependent on the sample’s thermal history: it is smallest for ancient rapid cooling and largest for samples that reside in the PRZ (allowing more radiogenic production to find traps before diffusion ceases). This model raises the possibility that complex CRH data record extended thermal-history information. If CRH and 4He/3He analysis were combined the 3He lab outgassing would record the sample’s trapping dynamics, and the 4He outgassing would reflect that plus a segment of the sample’s thermal history, which could be extracted using the 3He observations.

Potential habitat models have become an increasingly used method for characterizing fish larval habitat. Describing the potential habitat of fish larvae can yield insight into distribution patterns over temporal and spatial scales that cannot be easily characterized w discrete ichthyoplankton surveys, as well as setting a reference against which to assess the impact of anthropogenic and natural disturbances. Potential habitats are defined based on larval distribution and the environmental conditions that are suitable for development and survival. In the central Gulf of México (GoM), mesoscale circulation is dominated by the Loop Current (LC), LC-derived anticyclonic eddies that are transported westward and cyclonic eddies; these features influence productivity and water column characteristics and hence larval habitat. A semi-permanent cyclonic eddy in the Bay of Campeche (southern GoM) and other processes such as regional upwelling and offshore transport can also influence larval potential habitat. Between 2011-2017 nine oceanographic cruises covering the Mexican EEZ were conducted and fish larvae were collected using a bongo net sampler. Five taxa with different life history strategies, abundance and distribution patterns, spawning seasonality, and of varying economic importance were selected for the characterization of their potential habitat (Auxis spp., Benthosema suborbitale, Bregmaceros atlanticus, Caranx crysos and Cubiceps pauciradiatus). Their potential habitat will be characterized using generalized additive models correlating larval distribution with environmental parameters derived from in situ CTD and satellite-based measurements. The results of this study will yield insight into the potential larval habitat of representative fish species throughout the central and southern Gulf of Mexico.

Mercury’s surface is dominated by tectonic landforms formed by compression. Other than within basins, extensional landforms are not well known and have been presumed to be much rarer, with only a handful reported [1]. To date, two types of extensional grabens associated with lobate scarps have been described in literature: pristine back-scarp grabens associated with small lobate scarps (10s of kms in length and 10s of metres in relief) [2] and crestal grabens found on Calypso Rupes (381km in length and ~1km in relief) [3], [4]. This study identifies that such extensional grabens found on lobate scarps are much more widespread than previously recognised. These form when thrusting produces a hanging wall anticline, and local tensional stresses along the anticlinal axis cause antithetic faults to form in the folded strata, parallel or sub-parallel along the hinge zone, producing a down-dropped fault block. These small-scale features (often less than 1km in width, 10s of kms in length and likely 10s to 100s of metres in depth) are not expected survive 100s of millions of years because of regolith formation and impact gardening masking their signature [1], [2]. Our discovery and documentation of more extensional grabens may indicate that significant movement on many of Mercury’s large lobate scarps persisted until geologically recent times. [1] P. K. Byrne, C. Klimczak, and A. M. C. Sengör, “The Tectonic Character of Mercury,” in Mercury : The View After MESSENGER, 1st Editio., S. C. Solomon, L. R. Nittler, and B. J. Anderson, Eds. Cambridge: Cambridge University Press, 2018, pp. 249–286. [2] T. R. Watters, K. Daud, M. E. Banks, M. M. Selvans, C. R. Chapman, and C. M. Ernst, “Recent tectonic activity on Mercury revealed by small thrust fault scarps,” Nat. Geosci., vol. 9, no. 10, pp. 743–747, 2016. [3] C. Klimczak, P. K. Byrne, A. M. C. Şengör, and S. C. Solomon, “Principles of structural geology on rocky planets,” Can. J. Earth Sci., vol. 56, no. 12, pp. 1437–1457, Dec. 2019. [4] M. E. Banks et al., “Duration of activity on lobate-scarp thrust faults on Mercury,” J. Geophys. Res. E Planets, vol. 120, no. 11, pp. 1751–1762, 2015.

Stone Aerospace is developing the SUNFISH® autonomous underwater vehicle (AUV) which addresses many of the challenges of remote, autonomous exploration in unstructured environments such as the Ocean Worlds of the outer Solar System. The descendant of larger AUVs developed at Stone Aerospace (e.g. the NASA-funded DEPTHX, ENDURANCE, and ARTEMIS vehicles), SUNFISH is miniaturized, person-portable, six-degree-of-freedom (6-DOF) hovering vehicle with built-in precision navigation and control, multibeam mapping, imaging, and CTD capabilities. It was designed to be a highly-capable platform for operating in a wide variety of complex 3D spaces, ranging from man-made (e.g. piers) to natural (e.g. reefs, caves, and under ice). Building on these base functionalities, we have developed high-level capabilities for performing simultaneous localization and mapping (SLAM), exploration, path planning, and precision return home and docking. We describe these capabilities, and present a demonstration in the unstructured labyrinthine 3D environment of Peacock Springs in Florida, USA. SUNFISH and its technologies have direct application in several astrobiology-relevant goals, including furthering exploration and life search strategies for Ocean Worlds, as well as enabling Earth-analog fieldwork in structurally complex, remote aqueous environments such as caves, under ice shelves, or in sub-glacial lakes.

Recent observation reveals a stunning fact that the coastal tides are experiencing a rapid change in the last century in several places in the world. To achieve a wide and refined understanding of the phenomenon, high-accuracy tide level data is needed more than ever. In-situ measurements – the traditional and main data source to support tidal harmonic analysis – are often sparse and limited to fixed positions, insufficient to provide information about the spatiotemporal variability of tidal processes beyond the tidal gauges. Satellite altimetry may fundamentally change the situation. This technology measures water level with increased spatial coverage and resolutions. However, satellite altimetry has not been used in tidal analysis due to two major limitations in the harmonic analysis: a) a minimum length of sampled observed data is required to recognize a sufficient number of tidal constituents according to the Rayleigh criterion and b) data sampling/acquisition frequency must be at least two times the major tidal frequencies to avoid the aliasing issue dictated by Nyquist theorem. To address these issues, a novel compressed-sensing approach is proposed to break the limitations. In this method, the prior information of the regional tides (e.g., a reference tidal station near the location of interest) is collected to support a stepwise optimization process to obtain the amplitudes and phase terms of the tide signal for data series with different lengths and time intervals. Instead of least-square-fit approach, stochastic gradient decent is employed using Pytorch. A preliminary study shows that the proposed method can generate the tidal amplitudes and phases with a sampling interval of 16 days and a total data length of 30 days with an acceptable error. The results of this study can be useful to determine an optimum frequency and length for tidal data acquisition for the upcoming SWOT (Surface Water Ocean Topography) satellite, which is supposed to be launched in November 2022 to measure sea and terrestrial water level around the globe for three years and with average revisit time of 11 days.

During the 21st century, human–environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex coupled-systems. Human–environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. We outline specific applications for addressing SES questions, highlight current challenges, and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 years, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the research community to further explore interdisciplinary questions and theories that might leverage NEON AOP data, and present a new Research Coordination Network aimed at supporting these efforts.

Cryospheric data is increasing in size, demanding highly computational analyses. Open science principles, including collaboration, enable efficient, tested, reproducible, and diverse computational resource development. The ICESat-2 science community continues to coalesce around these ideals through contributions to icepyx, a community and open-source Python library for obtaining and working with large (~500 GB/day) data products from the ICESat-2 satellite/ATLAS laser altimeter. Our presentation will focus on the history, motivation, and process of creating this community, developing shared computational tools, and collating a set of example workflows within Jupyter Notebooks focused on ICESat-2 data. We will present new and in-the-works examples and features of the library, including enhanced pre-data-download visualizations, collaborative developments for multi-mission and -sensor data access, and data read-in/merging functionality. We will also highlight the community building events (including hackweeks) that drive this group and showcase some of the research supported and enabled by this software library.

For field workers around the world, wheat trials are often synonymous with wheat heads counting: a tedious but important task to measure this important yield component. Deep Learning has been a promising solution to automate the acquisition of wheat head density from a high-throughput phenotyping system, but it has been shown to be sensitive to changing acquisition conditions, also known as “domain change.” In response, an international collaboration built the “Global Wheat Head Dataset” in 2020 and 2021, a collection of 6515 images acquired during 47 different acquisition sessions in 12 countries. In addition to these datasets, two data competitions were held in 2020 (Kaggle, over 2,200 competitors) and 2021 (AIcrowd, over 400 competitors). The winning solutions are expected to be usable in plant phenotyping pipelines to robustly assess wheat spike density. We tested this hypothesis by evaluating the 2021 winning solution on an independent dataset consisting of images measured both in the field and in the image by a human, taken with the same acquisition protocol. We use triple collocation analysis to demonstrate that the predicted density appears to be more reliable than the human density measured in the field and in the image. Furthermore, we demonstrate that Global Wheat Head Dataset can be used to estimate wheat ear density from a drone.

Turbulence generated by aquatic vegetation plays a vital role in the interfacial transfer process at the air-water interface and sediment-water interface (AWI and SWI), impacting the dissolved oxygen (DO) level, a key indicator of water quality for aquatic ecosystems. We investigated the influence of vegetation, under different submergence ratios and plant densities, on the interfacial gas transfer mechanisms. We conducted laboratory experiments in a unidirectional recirculating flume with simulated rigid vegetation on a sediment bed. Two-dimensional planar Particle Image Velocimetry (2D-PIV) was used to characterize the mean flow field and turbulent quantities. Gas transfer rates at the AWI were determined by monitoring the DO concentration during the re-aeration process in water. SWI interfacial transfer fluxes were estimated by measuring the DO concentration difference between the near-surface and near-bed values. Compared to previous observations on a smooth bed without sediment, the presence of sediment enhances the bottom roughness, which generates stronger bed-shear turbulence. The experimental result shows that turbulence generated from the bed does not affect the surface transfer process directly. However, the near-bed suspended sediment provides a negative buoyancy term that reduces the transfer efficiency according to the predictions by a modified Surface Renewal model for vegetated flows. The measured interfacial transfer fluxes across the SWI show a clear dependence on the within-canopy flow velocity, indicating that bed shear turbulence and within-canopy turbulence are critical indicators of transfer efficiency at SWI in vegetated flows. A new Reynolds number dependence model using near-bed turbulent kinetic energy as an indicator is proposed to provide a universal prediction for the interfacial flux across the SWI in flows with aquatic vegetation. Our study provides critical insight for future studies on water quality management and ecosystem restoration in natural water environments such as lakes, rivers, and wetlands.

Low-lying coastal and estuarine areas are among the most populated regions globally, have high economic significance, and are increasingly threatened by climate change, sea level rise, nuisance flooding, and extreme storms. Nature-based coastal protections are sustainable and sea-level resilient alternatives compared to traditional solutions such as dikes and seawalls. Submerged aquatic vegetation (SAV) or seagrasses can provide coastal flood and erosion protection by attenuating storm wave and current energy and stabilizing seabed sediments. However, more research is needed to understand the interactions between flow, SAVs, and sediments. These dynamic interactions affect flow at different scales and seagrass productivity. In this study, we present field measurements of current and wave evolution over a seagrass meadow in South Bay, Virginia. The high vertical resolution measurements show how currents change from above-canopy to in-canopy waters. Wave measurements indicate the dissipation and frequency modulation over the canopy. The results are compared with hydrodynamic simulations using a two-way coupled flow-vegetation interaction model that simulates nonlinear current and wave evolution as well as dynamics of highly flexible vegetation.

Climate-induced episodes of extensive tree mortality worldwide are leading to abrupt changes in forest carbon stocks. A severe frost in early February 2011 triggered widespread tree mortality in the lowland tropical dry forest (TDF) of northwestern Mexico. The studied landscape in southern Sonora is composed by a patchy matrix dominated by mature, secondary (originated in abandoned fields), and active agricultural fields. In this forest, we used allometric equations to assessed frost-induced changes in aboveground biomass (AGB) stocks in mature and secondary tropical dry forests. For AGB estimations we used 48 1-ha plots (24 plots per forest type) distributed within four distant subareas in our 83 230 ha study area. On each plot, we recorded all live/dead individuals, and a total of 11 205 woody plants were registered, of which 7 137 (with at least a stem DBH > 2.5 cm) were likely present before the frost, and the remaining smaller ones were considered as new recruits regenerated from seeds (4,068 individuals). From those plants present before the frost, 26 842 and 8 059 were live and dead stems, and 1 222 were dead individuals. All registered live and dead stems accounted for a total of 273.4 Mg of AGB in our study plots (4.8 ha). From this amount, 57.3 Mg was necromass (dead stems). Interestingly, only two out of a total of 74 registered species contributed with ca. 80% of this necromass. These highly sensitive species are the tree legumes Lysioma divaricatum and Acacia cochliacantha. On average, AGB in the studied mature and secondary TDF was 64.3 and 49.6 Mg ha-1, respectively. The corresponding necromass for these forests was 10.9 and 13 Mg ha, respectively. The 2011 frost induced a greater change from live biomass to necromass in secondary than mature forests, 26.2% and 16.9%, respectively, which can be explained by the higher abundance of individuals from sensitive species in secondary forests. Our results suggest that climate-induced shifts in carbon stocks are linked to previous land-use changes in tropical dry forests. Restoration plans of these degraded lands should consider the vulnerability of tropical dry forest species to climate extremes.

The Arctic Ocean's Wandel Sea is the easternmost sector of the Last Ice Area, where thick, old sea ice is expected to endure longer than elsewhere. Nevertheless, in August 2020 the area experienced record-low sea ice concentration. Here we use satellite data and sea ice model experiments to determine what caused this record sea ice minimum. In our simulations there was a multi-year sea-ice thinning trend due to climate change. Natural climate variability expressed as wind-forced ice advection and subsequent melt added to this trend. In spring 2020, the Wandel Sea had a mixture of both thin and---unusual for recent years---thick ice, but this thick ice was not sufficiently widespread to prevent the summer sea ice concentration minimum. With continued thinning, more frequent low summer sea ice events are expected. We suggest that the Last Ice Area, an important refuge for ice-dependent species, is less resilient to warming than previously thought.