The National Ecological Observatory Network (NEON) is a long-term ecological observatory focused on collecting and providing open, continental-scale data that characterize and quantify complex and rapidly changing ecological patterns and processes. As part of the broader Observatory design, specific components of the Observatory are available to funded researchers for Principal Investigator-driven studies as part of NEON’s Assignable Asset Program. The available Assignable Assets include the Mobile Deployment Platform (MDP), the Sensor Infrastructure (SI), sampling locations or biological samples as part of the Observational Sampling Infrastructure (OSI), and the remote sensing capabilities of the Airborne Observation Platform (AOP). In addition to the infrastructure assets, NEON has deployable field sampling teams near NEON sites to support specimen collection and observations for specific research needs. Researchers can also gain access to the growing collection of plant and animal specimens and soil and water samples that NEON staff have gathered and stored in the NEON Bioarchive for study and analyses. Mobile Deployment Platform (MDP): NEON offers a suite of these self-contained, mobile arrays of sensors, power systems, and data logging capabilities for capturing atmospheric, soil, and aquatic-based measurements. Sensor Infrastructure (SI): Includes infrastructure (i.e., towers, power, and communications) for physical instrument systems or arrays for collecting environmental data from automated sensor suites. Observational Sampling Infrastructure (OSI): Allows researchers access to NEON sampling locations or to biological samples at NEON sites before samples are archived. Airborne Observation Platform (AOP): Provides a suite of remote sensing instruments mounted into a Twin Otter aircraft for collecting airborne-based data at nearly any site of interest in the U.S.

Rapid and accurate estimation of magnitude is crucial for earthquake and tsunami early warning systems, particularly for coastal populations closest to the rupture zone of a tsunamigenic event, i.e., a “local” tsunami. Traditional seismic approaches introduce time delays that limit their effectiveness near the source, while geodetic approaches typically require a seismic trigger and are limited to empirical scaling relationships. In this study, we extend a physics-based seismogeodetic approach, which combines near-source high-rate 1 Hz Global Navigation Satellite System (GNSS) and 100 Hz acceleration data, originally developed for thrust earthquakes, to strike-slip and normal fault mechanisms. We demonstrate our expanded approach for rapid seismogeodetic magnitude (Mwg) estimation using a set of 16 historical moderate-to-large earthquakes with strike-slip, normal, and thrust mechanisms. We find that considering the propagation of P and S waves in the intermediate and far fields is critical for accurate assessment of strike-slip events. Applying radiation pattern corrections, which are difficult to compute in real time where fault geometry is not readily available, offers only minimal improvements in magnitude estimation. We further broaden the seismogeodetic approach by interpolating coseismic windows from collocated GNSS and accelerometer stations (or stations with only accelerometers and/or broadband seismometers) to stand-alone GNSS stations, thereby increasing the usable network. We present an integrated workflow for rapid magnitude estimation for the different earthquake mechanisms, which leverages tectonic context (Slab2 geometry) to inform model selection, emphasizing the importance of network geometry and station density. Overall, our extended seismogeodetic approach provides rapid warning time (~2-3 minutes after earthquake initiation) for moderate to large events (Mw > 7) with a robust (IQR) Mwg accuracy of ±0.2 magnitude units as the basis for improved earthquake and tsunami warning systems. Our approach is useful in operational environments where shortened latency is of the essence.

The South China Sea (SCS) is one of the largest marginal sea in southeast Asia. The northern continental margin of the SCS has been considered an intermediate between the magma-poor and magma-rich end members. Baiyun sag is located in the deep water area where the northern continental crust had been hyper-thinned to < 12km. The syn-rifting deposition in the Baiyun sag shows distinct features to a classic rift basin at the shallow water area. Based on the high-resolution 3D seismic data interpretation and drilling logging analysis, we interpret a structural sequence corresponding to the hyper-thinning process before the final breakup of the continent. This sequence is bounded by a classic breakup unconformity and a regional transgression surface in the syn-rift strata of the Baiyun Sag; within the sequence, a set of foreset reflectors suggesting a prograding shelf-margin delta. Analog to the Iberia margin of North Atlantic, we use the definitions of Lithospheric Breakup Surface (LBS) and Breakup sequence (BS) and determine the distributions of the LBS and BS in the Baiyun sag. Based on the logging results, we apply subsidence back stripping to recover the palaeogeomorphology background with the development of BS. Finally, based on isostasy, we restore the basin structure using the balanced section technique and analyze the controlling factor of coarse-grained deposition distribution. Our results refine the deposition process related to the hyper-extension and the final breakup of the continental margin.

The projected contribution to sea-level rise from the Greenland Ice Sheet currently has a large spread in literature, ranging from about 14 to 255 mm by the year 2100. Part of this spread is due to uncertainty in mass loss from ocean-terminating outlet glaciers in response to terminus retreat. Here, we use a diffusive-kinematic wave formulation of glacier thinning to show that steep bed features can limit thinning from diffusing inland from a glacier’s terminus. This simplified model allows us to rank 141 of Greenland’s outlet glaciers based on their potential to allow thinning to diffuse far inland and, thus, contribute to sea-level rise over the next century. We then target two glaciers: Kakivfaat Sermiat (KAK) in West Greenland and Kangerlussuaq Gletscher (KLG) in East Greenland. Both glaciers have a high potential to contribute to sea-level rise but with contrasting bed geometries; KAK has relatively low ice flux but its geometry can allow thinning to diffuse far inland while KLG has high ice flux but a geometry that will limit thinning to 30 km inland of its terminus. We simulate mass loss from each glacier, in response to prescribed terminus retreat, using a higher-order numerical model, and find very different response times of mass loss from the two glaciers over the next century. KLG reaches a new steady state by 2100, while the slow inland diffusion of thinning causes KAK to continue its response into the next century and beyond. As a result, KAK contributes nearly twice the volume of ice to sea-level rise of KLG by year 2200, suggesting that low-flux glaciers that can allow thinning to spread far into the ice sheet interior may contribute much to sea-level rise as high-flux glaciers that limit thinning to their lowest reaches. By identifying the glaciers around the ice sheet with the highest potential to contribute to sea-level rise, we hope to help focus future higher-order numerical modeling studies working toward narrowing the range in sea-level rise projections.

This study reports the presence of Australasian microtektites in a deep-sea core (U1452) retrieved during International Ocean Discovery Program (IODP) Expedition 354: Bengal Fan. These microtektites are found within a foraminifera-rich calcareous clay layer beneath the Brunhes–Matuyama (B–M) magnetostratigraphic boundary. Most of them are spherical and are less than one millimeter in diameter. Typical splash (dumbbell, teardrop, button etc.) and irregular-shaped forms were recovered. The most abundant microtektites are pale green in color, followed by opaque, pale brown, translucent and transparent varieties. They are characterized by various surficial attributes including pits, mounds, grooves and fractures. Geochemical analyses suggest that the major oxide compositions are very similar to Australasian microtektites, Australasites reported elsewhere and also to the average composition of upper crustal rocks. Transparent bottle green microtektites are relatively richer in MgO content and lower in silica to other microtektites found in U1452. Minor and trace elements show a wide range of distribution and individual samples show variation. Differences in minor and trace elements concentration are possibly due to the contamination from the impact ejecta. Other than microtektites, presence of possibly polymetallic exsolution texture, shocked minerals and unmelted and partly melted ejecta within the microtektite-bearing layer in the northern Indian Ocean provides further evidence that the Australasites and Australasian microtektites might have been formed by the impact of an extraterrestrial projectile at ~0.8 Ma, somewhere in Indochina.

Recent advances in regional climate modelling include finer-scale simulations that can partially resolve deep convective processes. These convection-permitting models can help provide insight on how regional distributions of hazardous convection could evolve in possible future climates. However, the use of these models for representing climatologies of severe wind gusts related to convection has not been explored in detail, including for Australian regional climate. As a result, future projections of this hazard have mostly been estimated using changes in the large-scale environment from global climate models, with significant uncertainties related to this method. Here, we present findings on the ability of a regional, convection-permitting climate model in representing severe wind gusts associated with convection in southeastern Australia. We also examine future changes in the frequency and intensity of severe convective wind events as represented by this convection-permitting model, and compare these with changes in the large-scale environment from the global climate model that forces these simulations.

Accurate land cover classification of tundra is critical to modelling of future climate impacts in the Arctic. Existing classification systems (CAVM, NALCMS, GLC2000) are based on low- to medium-resolution remote sensing imagery which may result in low accuracy where land cover is variable. In this study we focus on southern Baffin Island to create a new classification based on 10-m resolution NDVI from 2018 Sentinel-2 satellite imagery, compare this new classification with existing systems, and characterize dependence of NDVI on spatial resolution based on three ~25-km2 0.5-m resolution WorldView-2 images. We recognized six different land cover types including Polar Semi-Desert (40%), Mesic Tundra (21%), and Wet Sedge Meadow (18%), based on previous studies of Baffin Island. Percent area of these six types within CAVM, NALCM, and GLC2000 cover classes was highly variable. As measured by the relative coefficient of variation, variations in NDVI were greatest at higher spatial resolutions, increasing by 800% with a shift from 0.5-10m2, versus 200% from 10-100 m2. Our results suggest that existing pan-Arctic classifications may not accurately capture land cover patterns on Baffin Island and likely other high-latitude regions, and highlight the need to use these classifications with caution when used to generalize Arctic ecosystem responses to climate change.

Natural and human-made extreme events can alter residential electricity demand in urban areas and stress the electricity grid. Different types of residential electricity consumers, which in some cases account for more than 30% of customers, can present different consumption patterns. Residential electricity demands have been widely analyzed considering single-family consumers; however, multi-family consumers remain comparatively understudied. The deployment of smart electricity meters enables the identification of single- and multi-family residential electricity consumption patterns at high temporal resolution. Using smart electricity meter data for the greater Chicago area, we compare electricity demand profiles reported by smart meters from single- and multi-family consumers in a large and diverse urban environment. The study provides a comprehensive analysis of daily electricity demand profiles of these two types of residential consumers to identify peak electricity consumption times and magnitudes. The analysis also presents correlations of the electricity demand with socioeconomic data at the zip code level. Preliminary results show that median building age, percent of occupancy, and mean commute time are statistically significant predictors of multi-family electricity consumption. Results suggest that single-family consumers have comparable correlation when using the same socioeconomic data with respect to the multi-family users. Uncovering differences between single- and multi-family electricity demands can assist city planners and utility managers to develop tailored demand management strategies.

We compare results of the solar high-energy proton detection with the neutron monitor network in Ground Level Enhancement (GLE) events and the data of pion-decay gamma-ray emission produced by high-energy protons interacting at the Sun. Observational data support the idea of a common origin of the GLE-producing protons and the protons interacting at the Sun to produce sustained gamma-ray emission. Then we discuss capabilities of the CME bow-shock acceleration models to explain the observational data and argue for the flare and CME synergy in production of high-energy protons in the long duration events.

Long period magnetotelluric (MT) data is being collected as a component of the USArray covering the continent of North America at a quasi-regular grid. Data from 250 MT stations were acquired covering the north-western part of the United States of America (USA). Dimensionality analysis was applied using Swift skew, Bahr skew and ellipticity. Results show a 1-D/2-D character for the short periods (< 1 sec) for the shallower structures, while the longer periods (> 1 sec) shows a 3-D character for the deeper structures. Two dimensional Occam inversion was applied for a set of E-W trending profiles to map the regional electrical resistivity distribution to a depth up to crust/mantle transition zone. 2-D resistivity structures were obtained by inverting both the transverse electric (TM) and transverse magnetic (TM) modes. Results show a resistive upper crust with a decreasing resistivity for lower crust. To the west, the subudcting Gorda plate was mapped as a relatively higher resistivity body nearly equal to the Wyoming basin to the east. Thick resistive lithosphere was mapped under Wyoming to the east. The results of this research shows the distribution of the electrical resistivity with adequate details for the shallow depth, while 3D inversion is necessary for the larger depths.

Drought has severe impacts on the structure and functionality of terrestrial and riverine ecosystems. The mechanism and duration of drought recovery are critical subjects that can have crucial ramifications for ecology, crop yield, carbon uptake, and ecosystem services, and it has not been thoroughly investigated. This study assesses drought recovery of terrestrial and riverine ecosystems for agricultural and hydrological droughts, respectively. Soil moisture simulations from Phase 2 of the North American Land Data Assimilation System (NLDAS-2) are employed to characterize agricultural drought, and streamflow data from the United States Geological Survey (USGS) are utilized for assessing hydrological droughts. Drought recovery for riverine ecosystems is studied considering both quantity and quality of streamflow. Water temperature, dissolved oxygen, and turbidity are the water quality variables considered in this study. Riverine drought recovery is assessed using a multi-stage framework that is applied to 400 streamflow stations across the CONUS for the study period of 1950-2016. On the other hand, terrestrial drought recovery is investigated utilizing ecosystem Gross Primary Productivity (GPP), a metric of photosynthetic activity, for the regions impacted by agricultural drought. GPP data is acquired from the Moderate resolution Imaging Spectroradiometer (MODIS) sensor onboard Terra satellite at 1km spatial resolution and 8-day temporal resolution across the CONUS during 2000 to 2015. The drought affected regions are assumed to be recovered when the post-drought GPP reverts to its regional average value. Results show that in general, riverine drought recovery takes about two months when considering water quality variables, whereas terrestrial drought recovery duration varies between 1 to 4 months depending on drought severity. Additionally, results indicate that drought recovery duration is positively correlated with drought severity.

A modified version of the commercially available RheOptiCAD® was developed to examine the conformational changes and break-up of flocs in clay suspensions in microscopic detail, under shearing action. In contrast to the RheOptiCAD®, our device aims to enable the structural observation of suspensions even when coagulation or settling of particles onto the bottom plate of the shear cell occurs. This challenge was met by using an upright modular microscope instead of an inverted one, equipped with a CMOS camera to record the structural evolution of samples as a function of shear. The verification of the design was done by analysing a model system of un-flocculated and flocculated kaolin suspensions. Additional experiments with natural clay (mud) suspensions were performed.

Flooding, moisture, and climate combined with traffic conditions are responsible for the failure of pavement and traffic disruption. Flooding may deteriorate the structural integrity of the road foundation resulting in huge rehabilitation and maintenance costs. Estimating flooding extent and flow characteristics is, therefore, key to assessing the impact of inundation on road links and networks in low-lying areas that are frequently exposed to flooding water. Such an assessment is helpful for decision-makers in pavement design, rescue operations, and infrastructure planning. Flooding from heavy precipitation is the primary weather-related hazard to transportation infrastructure in the state of Louisiana. Quantification of flood inundation area and depth is essential to quantify the exposure of infrastructure such as pavement and traffic flow to flooding in the changing climate. Two-dimensional hydraulic models that use the governing equation of flow to simulate flow characteristics are widely used to simulate flood extent and depth. However, simulating hydraulic models at acceptably satisfactory resolution and for large spatial extension may require substantial effort. More recent methods have used satellite remote sensing to characterize the extent of the flood, but satellite data still have limitations in producing reliable flood depth information. Modeling framework based on hydraulics and machine learning provides efficient large-scale flood simulation applications. This study tested the GIS tool, the Flood Depth Estimator (FwDET), to estimate complex inundation patterns in an urban setting. When driven by the LiDAR Digital Elevation Modeling and flood extent map, the tool can provide a rapid assessment of the spatial distribution of depth in the flood-prone region and state highway of Amite and Comite Rivers, Louisiana.

China and many developing countries face dual challenges in achieving carbon neutrality and controlling multi-media Hg pollution. Previous studies have employed computable general equilibrium models to assess China’s atmospheric Hg emissions under various CO2 mitigation and end-of-pipe Hg control scenarios. However, these models rely on highly aggregated sectoral classifications, failing to differentiate between specific technologies with varying Hg emission factors. Moreover, these studies overlook Hg emissions to other environmental media, particularly industrial waste, which can later re-emit Hg into the atmosphere during waste recycling processes. Given that comprehensive utilization of industrial waste is widely recognized as an effective CO2 reduction strategy, identifying pathways that synergistically mitigate both CO2 and multi-media Hg emissions is crucial. To address these gaps, we selected and enhanced the technology-rich integrated assessment model GCAM-China. First, we disaggregated non-ferrous metal smelting sectors (including zinc and lead smelting) from other industry, as these are major sources of both CO2 and multi-media Hg emissions. Next, we incorporated cement production technologies that co-process industrial waste, given the cement sector’s role as a primary sink for such waste. Finally, we integrated multi-media Hg emission factors and industrial waste generation rates into key GCAM-China sectors, enabling the model to simultaneously estimate CO2 emissions, multi-media Hg emissions, and industrial waste generation. Using this improved framework, we developed scenarios aligned with China’s carbon neutrality goals, end-of-pipe Hg controls, and industrial waste utilization. Preliminary results indicate that achieving carbon neutrality will be the primary driver of multi-media Hg mitigation, reducing atmospheric Hg emissions by 52.9%, aquatic Hg releases by 87.1%, and Hg entering industrial waste by 79.8%. However, while end-of-pipe controls and waste utilization can reduce Hg emissions in one environmental medium, they may inadvertently shift pollution across media. These findings highlight the need for whole-process control strategies to effectively address both climate change and multi-media Hg pollution.

Seismograms recorded at an array of 10 closely spaced seismometers in the western United States are stacked about the ScP phase and display a complex set of phase arrivals in addition to ScP. One dimensional forward modeling with ultra-low velocity zone structures are unable to match the observed waveform. Forward modeling with core-rigidity zone structures, where S-waves can propagate in a thin layer below the core-mantle boundary, provide reasonable waveform fits to the largest amplitude phases. The basic core-rigidity zone model has thickness of 1.1 km, shear wave velocity of 1.8 km/s, and density decrease of 10%, although tradeoffs in model parameters are observed. Waveform fits are insensitive to small changes in P-wave velocity in the core-rigidity zone. To match trailing smaller amplitude phases, S-wave multiples are modeled in the core-rigidity zone. Cross correlation of ScP waveforms from 392 EarthScope seismometer sites surrounding the small array site shows discrete patches of similarity to the above model. These results point to a spatially large but patchy core-rigidity zone beneath Mexico and adds to the small set of previous core-rigidity zone observations globally.

Enhanced precipitation of magnetospheric energetic particles during substorms increases ionospheric electron density and conductance. Such enhancements, which have timescales of a few hours, are not reproduced by the current ionospheric models. Using EISCAT (Tromso) measurements we reconstruct the substorm related response of electron densities and conductances in the ionosphere with respect to the intensity of substorm injections. We also investigate how the intensity of the response is influenced by the variations of the plasma sheet high energy (tens keV) fluxes and solar wind state. To characterise the intensity of substorm injection at a 5min time step we use the midlatitude positive bay (MPB) index which basically responds to the substorm current wedge variations. We build response functions (LPF filters) between T0-1h and T0+4hrs (T0 is a substorm onset time) in different MLT sectors to estimate the magnitude and delays of the ionospheric density response at different altitudes. The systematic and largest relative substorm related changes are mostly observed in the lowest part of E and in D regions. It starts and reaches maximum magnitude near midnight, from which it mainly propagates toward east, where it decays when passing into the noon-evening sector. Such MLT structure corresponds to the drift motion of the injected high energy electron cloud in the magnetosphere. Besides the injection intensity, we look at how the magnitude of the response depends on the energetic (tens keV) fluxes level in the plasma sheet before the substorm onset. We use a previously developed empirical model of the plasma sheet fluxes with solar wind parameters as inputs to count the plasma sheet fluxes with energy 10, 31 and 93 keV in the reference point of transition region (6 Re, 270o SM Long). We found that during enhanced high energy fluxes in the plasma sheet before the substorm (fast solar wind, high solar wind reconnection electric field) the background ionisation in the ionosphere, as well as the peak ionisation value during the substorm, are higher. This implies that together with substorm intensity the prehistory of the plasma sheet/solar wind state forms the magnitude development of substorm related ionospheric response. Research was supported by Russian Ministry of Science and Higher Education grant № 075-15-2021-583

Local ecological knowledge (LEK) is the experiential knowledge of local people gained through day-to-day interactions with the environment. LEK can provide detailed, real-time information about target species, ecological resources, and rapid state shifts in ecosystems. LEK is becoming more important as a source of data for conservation research and management. LEK can supplement conventional ecological surveys and data by providing rich context and detail on the state of local ecosystems by the people who work on these ecosystems every day as part of their livelihoods (Burbidge et al., 1988, Turvey et al., 2010b). Many communities in the Coastal Bend region of Texas have citizens whose livelihoods depend entirely on ecosystems as well as economies largely dependent on ecotourism. Ecotourism important to Coastal Bend economies includes recreational fishing, coastal parks, birding, and other forms of wildlife tourism. These same communities were majorly impacted by Hurricane Harvey and are continuing to slowly recover one year after the storm. Ecotourism stakeholders possess detailed knowledge on 1) changes to the ecosystem post Harvey across scales, 2) the needs for prioritized ecosystem restoration and conservation initiatives that may quicken ecotourism recovery post-Harvey, and 2) possible blind spots for conservation and resource management of which decision-makers may be unaware. Given the urgency and heavy financial burden of hurricane recovery, LEK can be pathway to resilience. Resilience in the Coastal Bend post-Harvey would see communities, ecosystems, and economies not only recovering quickly to their pre-storm states, but also harnessing the ability to absorb similar shocks in the future. LEK can act as a pathway to resilience during hurricane recovery as it is inexpensive, first-hand, detailed knowledge of changes to ecosystem functions linked to economic development. These changes may be addressed by decision-makers and resource managers looking to enable post-storm recovery. This presentation discusses how ecotourism-dependent communities in the Texas Coastal Bend use LEK to recover from Hurricane Harvey and build resilience to future extreme events as a model framework for how LEK can be used more widely to enhance resilience, respond to hazards, and facilitate adaptation.

Worldwide, the fisheries sector is growing with improved technologies to meet the ever-growing demand for seafood. However, with climate change and increasing marine pollution, there are also significant concerns about declining biodiversity and its impact on income and livelihoods for small-scale fishers. There is a significant shift from traditional fishing methods to mechanization and aquaculture in India. However, the new alternatives have come with many downsides which often go unnoticed. Mechanized fishing contributes to GHGs emissions, destruction of the seabed, overexploitation, and disrupting the ocean food chain. Likewise, coastal aquaculture emits GHGs during feed production, discharges organic and inorganic wastes, involves LULC changes and destroys ecologically sensitive areas (ESAs), leading to loss of various ecosystem services that increase environmental vulnerability and leads to higher ecological footprint. The impacts of climate change on the fishing sector and coastal areas are well established. However, there is a need to understand the impact of changes in fishing techniques on coastal zones and climate change. In this paper, the changes in the fishing sector are evaluated, followed by the development of a framework to assess the impacts of those changes on coastal zones and climate change. The changes in commercial fishing techniques are assessed by determining the dominant fishing techniques prevailing across India, along with reasons for a shift from traditional methods. A Life-Cycle Cost Assessment (LCCA) of the dominant techniques, aquaculture and mechanized fishing, helped to verify the need for such a shift. Two case study areas are selected for sample data collection for computing LCCA of aquaculture and mechanized fishing - Worli in Mumbai and Bhimavaram in Andhra Pradesh for studying mechanized fishing and aquaculture respectively. LCCA of the dominant techniques against traditional techniques showed that economic viability is one of the major reasons for the shift, which was later confirmed during the interviews with fishermen. These methods though profitable have various impacts on coastal ecosystems and emit GHGs making them unsustainable. The paper develops a framework to categorize the impacts of these changes on coastal zones and climate change and suggests appropriate methods to compute those impacts.