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USGS2026

Requirements, capabilities, and analysis for Earth observations—From user needs to Earth observation solutions

Introduction At the core of the Nation’s land imaging enterprise, the Requirements, Capabilities, and Analysis for Earth Observations (RCA-EO) project serves as the backbone for understanding user needs and shaping the future of Earth observation (EO) systems, products, and technology development. Understanding user needs and continuously tracking observing system capabilities is essential for EO because it ensures that the U.S. Government investments remain aligned with the real-world decisions, applications, and societal benefits they are intended to support. The RCA-EO project collects data users’ land imaging needs, focusing on what needs to be measured rather than specific technology. Collecting this data has resulted in a comprehensive understanding of civil land imaging user needs across scientific and operational applications. Over the past 10 years, the RCA-EO project has interviewed hundreds of subject matter experts, yielding more than a thousand user needs. The RCA-EO project’s analytical tools, models, and methods help inform the development of land imaging systems and products, determine appropriate data purchases, and prioritize partnerships for access to data from missions outside of the USGS. Our tools and databases support decisions with credible, needs-based information.

Fact Sheet↗
USGS2026

Methods for estimating selected low-flow frequency and mean annual flow statistics at gaged and ungaged locations on streams in Georgia, North Carolina, and South Carolina

The U.S. Geological Survey, in cooperation with the Georgia Department of Natural Resources (Environmental Protection Division), North Carolina Department of Environmental Quality (Division of Water Resources), North Carolina Department of Public Safety (Office of Recovery and Resiliency), and South Carolina Department of Environmental Services, updated low-flow frequency, mean annual flow, and flow-duration statistics at 843 streamgages in and near Georgia, North Carolina, and South Carolina. The low-flow frequency statistics are annual minimum 1-day average flow with a 10-year recurrence interval (1Q10), annual minimum 7-day average flow for 2- and 10-year recurrence intervals (7Q2 and 7Q10, respectively), and annual minimum 30-day average flow with 2- and 3-year recurrence intervals (30Q2 and 30Q3, respectively). Monthly 1Q10 and 7Q10, and W7Q10 flow statistics for the winter period (November–March) also are presented. By using data from 604 of the streamgages on streams with streamflows that are not substantially affected by regulation or diversion and are not tidally influenced, regional regression equations were developed to predict flow statistics with prediction intervals at ungaged locations on streams with those same criteria. The regional regression analysis included data from 132 streamgages from adjacent States Alabama, Florida, Tennessee, and Virginia. The final regional regression equations include variables such as drainage area, streamflow variability, precipitation, percentage of impervious area, and percentage of the basin in various ecoregions. The low-flow statistics for the streamgages analyzed and the regional regression equations will be integrated into the U.S. Geological Survey StreamStats application ( https://www.usgs.gov/streamstats ) for Georgia, North Carolina, and South Carolina. StreamStats generates basin characteristics needed to compute low-flow frequency statistics for ungaged locations. A trend analysis of annual minimum 7-day average flows was done for 78 streamgages with at least 30 years of continuous record. Trends were evaluated for 30-, 50‑, 70-, and 90-year periods, ending in climate year 2021, and independence and short- and long-term persistence assumptions were considered. For all trend analysis assumptions, most streamgages did not exhibit significant trends in annual minimum 7-day average flows. Trends in annual precipitation and air temperature were similarly evaluated for the period 1895–2021 to assess the variability of climate for Georgia, North Carolina, and South Carolina.

Georgia, North Carolina, South Carolina↗
USGS2026

Comparing DESIS hyperspectral and Landsat 10 simulated superspectral data for crop type classification in California's Central Valley

To advance crop type mapping in support of global food and water security, this study compared three spectral configurations: (A) the full 60-band DLR Earth Sensing Imaging Spectrometer (DESIS) hyperspectral narrowband (HNB) dataset, (B) a 14-band subset of DESIS-derived HNBs aligned with the planned Landsat 10 (formerly Landsat Next) spectral configuration (400–1000 nm), and (C) DESIS-based simulations of Landsat 10 superspectral broadbands. The analysis was conducted in California’s Central Valley, hereafter referred to as “the Central Valley”, during the peak growing month of August. DESIS imagery from August 2021, 2022, and 2023 was used sequentially for model development, testing, and independent validation. Over these three years, DESIS provided extensive hyperspectral coverage of much of the 4 million hectares in the Central Valley’s. Analyses were performed on Google Earth Engine using two pixel-based supervised classifiers, Random Forest (RF) and Support Vector Machine (SVM), to differentiate three major crop classes: row crops, grapes and tree crops, and winter wheat/fallow/other. The highest overall accuracy (86%) was achieved using SVM in combination with either the full DESIS hyperspectral dataset or the 14 DESIS narrowbands corresponding to Landsat 10. This finding aligns with earlier studies showing a small number of strategically positioned narrowbands can be optimal for crop type classification. Use of the narrowband datasets resulted in substantially higher accuracy (overall accuracy of 86%) compared to the simulated Landsat 10 broadbands (overall accuracy of 75%), supporting previous studies highlighting the utility of narrowbands. Despite the high accuracy using August imagery, the study indicates more granular crop type classification will require multi-temporal observations spanning the full phenological cycle (June–October), especially for a large number of crop classes. Acquiring task-based hyperspectral imagery over such large areas throughout the growing season remains operationally challenging. In contrast, Landsat 10 superspectral imagery could provide routine coverage across seasons and years that is practical and scalable for future large area crop type mapping and agricultural monitoring.

California↗
USGS2026

Correcting a systematic bias in an ocean drilling project site 882 alkenone sea surface temperature record

Reconstructions of sea surface temperature (SST) in the geologic record are fundamental to our understanding of Earth's climate history and the evaluation of Earth's climate sensitivity to greenhouse gas forcing. SSTs are reconstructed with a variety of methods, including alkenone biomarker lipids produced by certain coccolithophore algae. One such alkenone SST reconstruction from the subpolar northwest Pacific Ocean Drilling Program (ODP) Site 882 (50.21° N, 167.35° E, 3244 m water depth) has played a large role in shaping the paleoclimate science community's view of global climate warmth during the Late Pliocene (3.6–2.6 million years ago) and the subsequent cooling that characterized the intensification of Northern Hemisphere Glaciation (Haug, 1995; Haug et al., 2005; Martínez-Garcia et al., 2010). First, we have found that the values reported in the PANGAEA archive for this ODP Site 882 alkenone dataset were inaccurately reported as U K' 37 values when they are instead U K 37 ( https://doi.org/10.1594/PANGAEA.315092 , Haug and Sarnthein, 2005). This error in the archived data table resulted in the incorporation of inaccurate absolute SST estimates by several studies that applied U K' 37 calibrations to this ODP Site 882 dataset (e.g., Brennan et al., 2022; Clark et al., 2024, 2025; Tierney et al., 2019, 2025b). Second, using other published data from ODP Site 882 (Studer et al., 2012) and nearby Site 883 (51.11° N, 167.46° E, 2384 m water depth; Herbert et al., 2016; Novak et al., 2024), we show that the original Haug (1995) alkenone SST record at ODP Site 882 systematically reports an amplified range of absolute SST values compared to the more recently generated data. This observation is consistent with the known concentration-dependent biases of the gas chromatography chemical ionization mass spectrometry (GC-CI-MS) analytical method used by the original ODP Site 882 study (Chaler et al., 2000, 2003; Haug, 1995; Hefter, 2008; Rosell-Mele et al., 1995). These concentration-dependent analytical biases complicate applying a uniform correction to the entire Haug (1995) dataset. However, we are able to leverage the published datasets to propose a correction and quantification of uncertainty for a subset of the Haug (1995) dataset measured at similar on-column analyte abundance. For these samples, we find an average analytical uncertainty equivalent to ±2.05 °C , which is greater than and in addition to the typical ±1.4 °C 1 σ prediction uncertainty of the U K' 37 sea surface temperature proxy. We then discuss the implications of the corrected dataset for our understanding of late Neogene and Quaternary climate in the Kuroshio Extension region.

Climate of the Past↗
USGS2026

A Lake Charr pangenome reveals highly conserved Ohnologs as drivers of phenotypic diversity

Whole-genome duplication (WGD) is hypothesized to spur evolutionary diversification by producing genome-wide duplicate gene sets (Ohnologs) that are initially functionally redundant but can diverge markedly as the effects of relaxed selection accumulate over time. However, the underlying mechanisms remain unclear, in part because genomic studies often reconstruct Ohnolog evolution over millions of years, during which subsequent mutations can obscure deep-time signals. Investigating the relationship between Ohnolog evolution and diversification on a contemporary timescale offers clearer insights. We explore this relationship in Lake Charr ( Salvelinus namaycush ), where ∼10% of genes are retained highly conserved polyploid duplicates following the Salmonid-Specific Fourth Round WGD. Using 31 chromosome-level assemblies of Lake Charr from morphologically and ecologically diverse populations, joined into a pangenome graph, we characterized 189,555 structural variants (SVs) that were significantly less likely to affect genes retained as sequence-conserved Ohnolog pairs, nuancing the hypothesis that gene redundancy, relaxed selection, and functional diversification are intertwined. However, we found that SVs affecting such conserved Ohnologs may be potent drivers of adaptive evolution. Notably, we identified a putative 938-Kb interchromosomal translocation containing 25 genes with highly conserved Ohnologs in a paralogous (but untranslocated) genomic block. This putative translocation appears to have facilitated Ohnolog divergence in ankrd11 and hp , genes putatively linked to craniofacial and lipid metabolic diversity in sympatric Lake Superior morphs. This research reveals that conserved Ohnologs previously presumed to be redundant remain a reservoir for adaptive change.

BioRxiv↗
USGS2026

Quantifying avian resilience to habitat change to support conservation decision-making

Habitat loss and degradation are two of the main drivers of contemporary avian population declines. Wildlife managers are increasingly advocating for tools that provide decision support to set priorities for restoration or conservation efficiently. We demonstrate how to derive two species-specific management and resilience metrics: the greatest management impact point (GMIP) and the ecological resilience threshold (RT). The GMIP indicates the amount of environmental change in a landscape where habitat improvements are expected to have the greatest impact on species’ occurrence. The RT represents the amount of environmental change in a landscape that a species can tolerate before the steepest change in occupancy is expected to begin. We estimate species-specific metrics using the amount of uncharacteristic exotic vegetation as an index of environmental change, and demonstrate how multispecies patterns may suggest potential management strategies. We estimated occupancy models using 5 years of multispecies avian detection data from the Integrated Monitoring in Bird Conservation Regions program in the State of Utah, USA (hereafter, Utah). Based on the estimated relationship between species’ occupancy and amounts of uncharacteristic exotic vegetation, we derive RT and GMIP scores for 61 species breeding in Utah. We found wide interspecific variation in resilience to amounts of exotic vegetation, with species generally clustering at extreme values. Our results demonstrate that birds in Utah appear more resilient to amounts of uncharacteristic exotic vegetation at coarser spatial resolution, showing greater variance and lower average RTs at finer spatial resolution. Species that are not fully resilient to the range of uncharacteristic exotic vegetation observed in this study are expected to respond most strongly, on average, to management actions in landscapes with high levels of exotic vegetation; however, early detection and rapid response is likely the most effective strategy. Quantified across many species, these metrics can be used to identify and prioritize landscapes where current environmental conditions could be maintained to avoid the greatest species’ declines, or which maximize expected biodiversity returns on investment in environmental restoration. Managers can consider either focal species’ resilience for tailored conservation planning or summarize species resilience to create efficient management plans that maximize outcomes for multiple species.

Utah↗
USGS2026

Site-specific amplifications in Northwestern Turkiye: A generic approach

In this study, we derive generic site amplification functions applicable to Northwestern Türkiye and follow guidance on site classifications established by the United States National Earthquake Hazards Reduction Program (NEHRP). We employ the one-dimensional (1-D) equivalent linear ground response analysis method and focus on recordings from a select suite of free-field strong motion (SM) stations. These particular SM stations are associated with a comprehensive geotechnical site conditions dataset comprising 76 shear-wave velocity profiles. Despite their varying resolutions and depths, this diversity allows for a more representative analysis across different site conditions, enhancing the robustness of our findings. For analyses, we utilize a robust set of global ground motion records, selected from both within and outside of Türkiye, to serve as strong and weak input bedrock motions. Site amplification is determined by propagating these bedrock records through 76 site-specific Afet ve Acil Durum Yönetimi Başkanlığı (AFAD) station profiles and calculating the spectral acceleration ratio between the ground surface and the input motion. Our analyses reveal substantial disparities between the amplification functions derived from 1-D site response analyses using strong and weak input motions. These disparities are central to our analysis and inform the subsequent comparison with site amplification functions reported in the literature. We compare the generic site amplification functions derived in this study with those reported in the literature for regions with similar geological and seismic conditions to Northwestern Türkiye. For example, site amplification functions for NEHRP Site Classes C and D have been documented for Greece and the United States utilizing frequency-dependent methods such as the quarter-wavelength approximation. Our findings reveal that the generic site amplification functions derived in this study exhibit differences in peak amplitudes and predominant frequencies compared to those in the literature, reflecting regional variations in geotechnical and seismic properties. This study represents an initial effort to formulate generic site amplification functions for Türkiye, with a particular emphasis on the Northwestern region. A thorough literature review indicated no prior studies have proposed such functions specifically for this area.

Northwestern Turkiye↗
USGS2026

Interplanetary electric fields for extreme magnetic storms

Using a list of sudden-commencement storms, the ring-current index, and 1-h near-Earth solar-wind measurements from solar cycles 20–25, we develop extreme-value statistical models relating storm intensity 𝐷 =max⁡{−𝐷⁢𝑠⁢𝑡} to the storm main-phase maximum duskward interplanetary electric field 𝐸 . The conditional relationship 𝐷|𝐸 is demonstrably sublinear—linear models are confidently rejected—indicating saturation of magnetospheric response under extreme solar-wind forcing. An event like that of July 2012 ( 𝐸 =69.6 mV/m), if Earth-directed, would be associated with a median storm intensity of 𝐷 =49⁢5 648 378 nT. Storms comparable to March 1989 ( 𝐷 =594 nT) correspond to electric fields of 𝐸 =5⁢4 76 39 mV/m, while Carrington-class storms ( 𝐷 =964 nT) correspond to 𝐸 =9⁢5 133 68 mV/m—substantially lower than several previous estimates. These results indicate that solar-wind conditions capable of driving extremely intense magnetic storms are less exceptional, and potentially more frequent, than previously thought.

Geophysical Research Letters↗
USGS2026

Stream temperature variability in headwater beaver dam complexes in relation to hydrologic and environmental factors

Beaver modify hydrological regimes and have the ability to both increase water storage and alter stream temperatures. For these reasons, beaver translocation and the construction of human engineered beaver-dam analogs (BDAs) have become popular tools for climate-change adaptation. However, there is a lack of understanding about how beaver engineering affects stream temperature. The results from previous studies vary considerably and the drivers of the discrepancies remain unclear. We investigated the longitudinal and vertical variation of stream temperature in and around 24 sites consisting of one or more beaver ponds across 17 headwater streams around the Methow and Okanogan river valleys of Washington State (USA). We then explored possible hydrologic and environmental drivers of observed thermal patterns. Despite considerable variation, we found that beaver ponds were often associated with an increase in downstream temperatures. The magnitude of this effect increased with total pond hydraulic height, which was directly related to the number and size of ponds per site. We also found that pond bottoms were cooler than upstream inflow sites for a period of time in the afternoon. Thus, although beaver dam complexes in the Methow River watershed do not consistently cool streams—and in fact often increase downstream temperatures—the bottoms of beaver ponds can create relatively cool water areas during the hottest part of the day. Furthermore, if managers choose to use beaver translocation or BDAs, locations with topography that would result in deeper ponds with more canopy cover may limit negative temperature effects on coldwater aquatic biota.

Washington↗
USGS2026

Conservation enhances resilience of the United States Duck Factory as environmental shifts may diminish landscape-scale waterfowl breeding capacity

Wetlands in the U.S. Prairie Pothole Region (USPPR) provide habitat for an estimated 5 million breeding ducks and remain a focal point for North American waterfowl conservation. After decades of investment, almost 20% of the USPPR is protected by some form of wetland or grassland conservation. We synthesized four decades of modeling studies aimed at understanding how environmental change may impact duck populations. We built upon past modeling efforts by applying an integrated scenario-based approach to inform wetland-waterfowl conservation planning. By century’s end, all scenarios projected declines (27%–53%) in breeding duck abundance in the USPPR. Despite these declines, areas in the USPPR with higher rates of protection and wetland density will likely continue to support the most breeding ducks, indicating resilient conservation planning. Our findings underscore the benefits of interdisciplinary efforts that can inform complex conservation decision-making in the face of environmental uncertainty.

Iowa, Minnesota, Montana, North Dakota, South Dako↗
USGS2026

Pliocene (Piacenzian) planktic foraminiferal biogeography: Insights into how planktic biogeography is linked to climate and socioeconomic impacts on marine ecosystems

The Piacenzian Age (3.60–2.58 Ma) of the Pliocene Epoch was characterized by globally warmer climates, higher sea levels, and atmospheric CO 2 similar to present. Utilizing a robust dataset of 2,101 samples and over 637,000 foraminifer specimens from 77 deep-sea core sites worldwide, we document planktic foraminifer biogeography and biodiversity during the mid-Piacenzian Warm Period (mPWP). Cluster analysis and multidimensional scaling reveal five major bioregions: tropical, warm subtropical, transitional, polar, and a distinct North Atlantic polar bioregion. Each bioregion was dominated by characteristic species with well-established temperature preferences. Analyses demonstrate higher species richness and evenness in low and mid-latitudes, with increased diversity associated with periods of climatic warming and poleward expansion of warm water assemblages. The long-term stability of biogeographic patterns underscores ecological conservatism but also highlights potential vulnerability to rapid anthropogenic climate change. Our findings emphasize the critical role of planktic foraminifers in reconstructing past ocean conditions and offer valuable insights into links between planktic biogeography, climate, and socioeconomic impacts on marine ecosystems. This work advances our understanding of marine ecosystem responses to climate extremes and provides a foundation for future regional and temporal analyses of planktic foraminifer biogeography under global change scenarios.

Frontiers in Earth Science↗
USGS2026

The geologic history of the Chehalis Forearc Basin, Washington State, USA

The Chehalis basin is located between the Cascade arc and the Coast Range in southwest Washington State. It consists of sedimentary and volcanic rocks deposited throughout the Cenozoic and is underlain by the Siletzia terrane, a thick, large igneous province accreted in the Eocene. Here, we constrain evolution of the Chehalis basin depocenter using isochore maps derived from isostatic gravity anomalies, borehole data, and stratigraphy for several time periods: the Eocene (47.6–36.8 Ma), the Oligocene (36.8–20 Ma), and the Neogene (20–0 Ma). Our results suggest that local subsidence is driven by deformation on faults that bound and intersect the basin. We see northward depocenter migration, interpreted as a shift in deformation from the northwest striking Cedar Creek fault to the west striking Doty fault. We interpret these data in terms of the long-term north-south shortening and clockwise rotation of the Cascadia forearc. During the Eocene, the Cedar Creek fault was preferentially aligned with north-south shortening, but became less active when clockwise rotation brought the Doty fault into east-west alignment with the stress field. Sediment accumulation rates decreased from 196 m/Myr in the Paleogene (∼40–20 Ma) to 27 m/Myr in the Neogene (∼20–0 Ma) as Miocene uplift of the Coast Range limited accommodation space and shifted the depositional environment from marine to fluvial. Our results are consistent with the geologic evolution of the Portland and Tualatin basins to the south and reveal a depositional and structural history uniquely shaped by clockwise rotation of the Cascadia forearc.

Washington↗
USGS2026

Conflicts and collisions with an endangered carnivore: Landscape drivers and spatial risk pattern

Human–wildlife conflicts and anthropogenic mortality are expected to increase with the continuous encroachment on natural habitats within and around protected areas, yet the processes governing these risks remain poorly understood. We investigated the spatiotemporal dynamics and drivers of two distinct processes involving the endangered Florida panther ( Puma concolor coryi ; hereafter, panther): (1) direct human–panther interactions and livestock depredation (hereafter, conflicts), and (2) vehicle collisions (hereafter, collisions). Using long-term data collected between 2006 and 2022 within the panther's breeding range in Southwest Florida, USA, we applied dynamic occupancy models to estimate probabilities of occurrence, colonization, and extinction of conflicts and collisions while accounting for imperfect detection. A total of 277 conflicts and 239 collisions were recorded during the study period. Occurrence probabilities for both conflicts and collisions increased during the early years of the study and subsequently stabilized. Landscape configuration consistently showed strong associations with both processes. Conflicts were more likely in areas with fragmented but closely spaced habitat patches, whereas collisions were more likely along road segments characterized by connected landscapes with low resistance to panther movement. In contrast, areas that showed greater distances between habitat patches and increased proportions of protected area were associated with lower probabilities of conflict or collision persistence over time. A predictive map was created to highlight areas with high probability of conflict and road segments with high probability of collision in Southwest Florida, USA. Identifying areas with elevated risk can inform targeted mitigation strategies, including habitat management, wildlife crossings, and outreach efforts, and further support long-term coexistence between humans and large carnivore populations.

Florida↗
USGS2026

Ecogeomorphologic response of a tidally restricted salt marsh to tidal restoration and sea-level rise

Diked marshes with decades of restricted tidal flow exhibit fundamentally altered hydrologic and ecologic dynamics that result in limited vertical accretion, land subsidence, and underdeveloped tidal channels. These changes complicate marsh restoration efforts and constrain the marsh's ability to build elevation in response to future sea levels. In this study, we developed an integrated hydrodynamic and marsh accretion model to conduct the first assessment of the restoration potential of a diked marsh in response to reintroduction of tidal flow and sea-level rise (SLR). We applied our model to evaluate changes in biomass production in the Herring River estuary, Cape Cod, MA, USA—which has experienced significant ecological shifts due to more than a century of tidal restriction—in response to a range of SLR scenarios, tidal flow conditions, management interventions, and biomass production rates through 2100. We found that with restoration of tidal flow, the simulated marsh extent expanded in areas with efficient drainage, increasing biomass production by up to 4.4 times. However, when SLR was imposed, parts of the marsh gradually transitioned to open water, leading to a decline in marsh coverage from 19% to as low as 12%. Management interventions aimed at enhancing marsh elevation and improving the drainage capacity of tidal channels slowed marsh loss, supporting marsh area through 2100. Our findings provide insight into the key drivers of marsh resilience and loss, and our approach can be applied across tidally restricted and restored systems to develop targeted, adaptive restoration strategies that achieve desired ecological outcomes.

Massachusetts↗
USGS2026

Restoration is a partial but not complete solution for long-term declines in oyster populations—A case history from the northeastern Gulf of America

Objective We sought to evaluate whether oyster reef restoration is associated with sustained increases in intertidal eastern oyster Crassostrea virginica density in Suwannee Sound, Florida, and to examine how commercial fishing activity and freshwater discharge may modify those patterns. Methods We monitored intertidal oyster reefs for 14 years, including 9 years prior to large-scale restoration (completed in 2018) and 5 years of standardized postrestoration monitoring beginning in 2019 at Lone Cabbage Reef, an offshore intertidal reef complex that was rebuilt to target elevation using dolomite limestone. A Bayesian negative-binomial generalized linear mixed model framework estimated oyster densities while accounting for spatial differences among inshore, nearshore, and offshore reefs; variation in transect length; and temporal variability. We assessed restoration effectiveness via repeated-measures monitoring of fixed restored sites and landscape-scale comparisons of restored versus unrestored reefs. We evaluated covariates of management interest—commercial fishing activity and river discharge—using model comparison and posterior predictions of oyster density at observed covariate values. Results Restoration produced large per-area gains in live-oyster density on offshore reefs. At four fixed restored offshore stations, mean densities rose from near 0 to 91 oysters/m 2 (95% credible interval [CrI] = 43–185) within 6 months and reached 244 oysters/m 2 (95% CrI = 134–433) by year 5 at fixed restoration stations. At the broader landscape scale, restored offshore reefs averaged about 83 oysters/m 2 (95% CrI = 26–157) across sites and postrestoration periods, whereas model-based estimates for restored offshore reefs reached 218 oysters/m 2 (95% CrI = 128–366) in the final sampling period. Conclusions Restoring reef substrate rebuilt the physical capacity for oysters to persist and grow at Lone Cabbage Reef, yielding sustained density gains that degraded sites did not achieve on their own. Harvest status and river discharge showed weak, inconsistent associations once restoration was included, consistent with the interpretation that oyster cultch provides structural capacity, while environmental and fishing conditions modulate around it. Rebuilding and conserving oyster cultch constitute the essential first step to repair and sustain degraded oyster reefs; fishing regulations or favorable environmental conditions alone are unlikely to replace the need for reef structure.

Florida↗
USGS2026

Across-track tilt concept for sun glint mitigation in future Earth-observing missions

Sun glint is a major limitation for spaceborne optical remote sensing of aquatic environments, particularly in tropical and subtropical regions. By dominating the at-sensor radiance, sun glint complicates atmospheric correction and reduces the quality of aquatic reflectance products derived across Earth observation missions. This study presents a machine learning framework to quantify sun glint probability and evaluates the across-track tilt observational concept as a potential sun glint mitigation approach for satellite remote sensing missions. More than 14,000 cloud-free Landsat 8 and 9 scenes were analyzed to quantify glint occurrence as a function of sun-sensor geometry, latitude, and season. Logistic regression and machine learning models identified solar zenith angle (SZA), wind speed, and viewing zenith angle (VZA) as the primary predictors of sun glint probability, achieving >98% classification accuracy. Sun glint contamination was found to be negligible for SZA > 40° but frequent at SZA <35°, particularly in forward-scattering geometries. Introducing a 3° across-track westward tilt reduces the proportion of glint-contaminated pixels by ~21% in tropical and subtropical regions, while larger tilts of 6°, 9°, and 12° yield reductions of 43%, 59%, and 74%, respectively. These findings underscore the value of incorporating glint mitigation strategies in future Earth observing mission designs. A modest across-track tilt, combined with post-acquisition glint detection and correction, offers a practical pathway to increasing the availability of high-quality aquatic observations for monitoring inland and coastal water quality and ecosystems.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2026

Long-term aridity shapes grassland drought resistance and modulates the roles of plant diversity and functional composition

Understanding the drivers of plant community stability is crucial for predicting ecosystem responses to extreme drought events. In grasslands, drought resistance supports the maintenance of key functions such as above-ground primary productivity, making the identification of resistance drivers essential to guide management under climate change. Proposed factors contributing to grassland stability include multiple diversity facets, functional traits and long-term climate, but most assessments focus on temporal invariability under historical disturbance regimes, leaving mechanisms of extreme drought resistance and their variation across climatic contexts relatively underexplored. Here, we analysed data from 54 grassland sites of the International Drought Experiment to examine the resistance of above-ground net primary productivity to a short-term (i.e. 1 year) extreme drought. We investigated the relative importance and joint influence of functional composition (i.e. community-weighted means of leaf and root traits), plant diversity facets (taxonomic, functional and phylogenetic) and climate (aridity and rainfall variability) on drought resistance. We used structural equation models to disentangle direct, indirect, and moderating pathways linking these drivers to drought resistance. Long-term aridity appeared as one of the most important drivers of grassland resistance to drought, with more arid sites showing lower resistance. Moreover, aridity impacted resistance through indirect effects by shaping functional composition and plant diversity, and by moderating the influence of plant diversity and functional composition. Functional composition related to dehydration avoidance and dehydration tolerance was also positively associated with resistance, while diversity had a weaker relationship with resistance, mostly through functional and phylogenetic facets. Interannual rainfall variability also influenced resistance, with different effects in more arid versus humid and less arid sites. Synthesis . Widely studied stability drivers such as plant diversity and functional composition have only partial explanatory power for short-term drought resistance of above-ground productivity in grasslands at a global scale. The abiotic context, particularly long-term aridity, is crucial for understanding ecosystem responses to rainfall variation and can improve predictive models for advancing the study of ecosystem resistance to drought. Along with management practices that target high species diversity or specific traits, restoration and conservation practices should support vulnerable sites experiencing high aridity

Journal of Ecology↗