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At least 1,045 records · Page 58Linked to original sources
USGS2026

Biological and environmental drivers of early life fawn survival in a declining pronghorn population

Pronghorn Antilocapra americana occupy only a portion of their historical range and in Oklahoma occur at the eastern edge of the species' contemporary distribution. Monitoring has suggested pronghorn populations in Oklahoma have declined in recent years. We captured and collared 125 adult females across two winters, monitored them for signs of parturition during each subsequent spring, and then captured and radio-collared 70 fawns ≤ 4 days old. We assessed cause-specific mortality, estimated proportional survival, and visualized survival of fawns through 60 days of life with Kaplan–Meier curves. Nearly 87% of fawn mortalities were attributed to predation, with > 77% of predations attributed to coyotes Canis latrans . Our results indicated that fawn survival was lowest during the first 15 days of life, with 33% of fawns surviving to 15 days and 12% surviving to 60 days. We used known-fate models to evaluate the influence of biological factors (i.e. sex, mass, birth timing), environmental factors (i.e. ambient temperature, precipitation, vegetation), and temporal variation on the probability of early life (i.e. the first 15 days) survival. For each adult female with a collared fawn, we used female space-use patterns for 30 days before and 15 days after parturition to collect environmental covariates. Early life probability of survival was lower for larger fawns, those born earlier in the parturition period (i.e. earlier in the year relative to the range of parturition days), and those with higher pre-parturition temperatures; daily probability of survival decreased with time-since-parturition within the first 15 days of life. Our results indicate poor fawn survival, highlight a potential limitation of population growth, and can inform population management by identifying factors influencing early life fawn survival.

Oklahoma↗
USGS2026

The Sedimentary Geochemistry and Paleoenvironments Project Phase 2 data release: An open data resource for the study of Earth's environmental history

Geochemical data from sedimentary rocks are the primary source of information regarding Earth's surface evolution through time, including its air and water envelopes and interactions with life and deep Earth processes. The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is a scientific consortium centered around open data and community-driven development of cyberinfrastructure tools and resources for sedimentary geochemistry and Earth history. Here we describe the SGP Phase 2 data release, which focused on incorporating Paleoproterozoic and Mesoproterozoic (2500–1000 million years ago) data and better accommodating carbonate data. This data release was built through the involvement of >200 researchers worldwide in academia, government, and industry, and provides the largest available public data resource for our user community in the academic fields of geochemistry, sedimentology, tectonics, paleontology, Earth history, and paleoclimate, as well as the petroleum and minerals industries. The dataset now encompasses 126,006 samples and 4,132,371 geochemical analyses. In addition to direct entry by SGP Team Members, we have ingested and incorporated datasets from the Geoscience Australia OZCHEM database, the Alberta Geological Survey, and the Deep-Time Marine Sedimentary Element Database (DM-SED) compilation. This paper details sampling in the Phase 2 dataset with respect to age, geography, lithology, and other geological characteristics, documents access via our search website and API, discusses possible issues and/or biases in the dataset that could impact analyses, describes plans for governance and stewardship of data from Indigenous lands, and serves as the citable reference paper for the data release.

Chemical Geology↗
USGS2026

Initial condition uncertainty exerts a large and persistent influence on model simulations of ecosystem carbon dynamics in California

Uncertainties in terrestrial ecosystem models limit their predictive power. Efforts to reduce projection error have rarely focused on constraining uncertainty in the initial state of the ecosystem, however, despite evidence that matching model initial conditions to real-world observations reduces overall model bias. Here we use an integrated land change and carbon gain-loss model to evaluate the influence of initial condition uncertainty on simulations of California wildland ecosystems during the years 1985–2020. We generated 36 initial conditions scenarios by varying the source data used to initialize state variables and then ran simulations based on each of these scenarios under a constant set of historical conditions. We found that discrepancies in initial forest extent and initial forest age among scenarios generated wide uncertainty ranges in model estimates of terrestrial ecosystem carbon stocks and flux rates at the outset of the simulation period, but differences in initial forest composition had no impact. Over time, forest age became more homogeneous across model scenarios leading to exponential rates of decline in the uncertainty ranges of live biomass and dead wood carbon but little to no impact on uncertainties in litter and soil organic carbon. Uncertainties in individual carbon flux rates were consistent with uncertainties in their source pools. In contrast, model estimates of ecosystem carbon balance demonstrated a shift in system behavior not apparent in trends for individual carbon stocks and fluxes. Specifically, estimates of ecosystem carbon balance converged across scenarios for the first 20 years of the simulation period but then began to diverge at an accelerating rate, possibly due to weakened resilience to the increased frequency and severity of climate-driven disturbances. Our results demonstrate that uncertainty in the initial state of the system can have large and persistent impacts on the predictability of ecosystem carbon dynamics, and that ongoing shifts in external forcing by climate and climate-driven disturbances can exacerbate these impacts.

California↗
USGS2026

Discharge magnitude drives interannual variation in distribution of the invertebrate host Manayunkia occidentalis of the salmon parasite Ceratonova shasta

Objective The objective of this study was to evaluate statistical evidence for relationships between flow event characteristics and annelid host distribution, an important and necessary step toward providing and justifying management actions. Declines in Klamath River salmon have been attributed to infection and disease that are caused by the myxozoan parasite Ceratonova shasta . Flow manipulation has been used to manage risk of C. shasta for juvenile salmonids in this system. One mechanism by which flow-related disturbance can reduce the risk of C. shasta infection for salmon is by reducing populations of the obligate invertebrate host Manayunkia occidentalis . We previously demonstrated that hydraulic conditions during peak discharge events drive the distribution of M. occidentalis and suggested that high-magnitude flow events would be effective for reducing the distribution of the annelid host. However, evidence of the effects of flow events on M. occidentalis was needed to support the use of flow management. Methods To address this knowledge gap, we leveraged a multiyear data set to estimate relationships between the distribution the annelid host and the characteristics of each discharge event. We measured the presence or absence of M. occidentalis at spatially georeferenced sampling locations, stratified across the range of hydraulic and substrate conditions in three reaches annually from 2012 to 2020. Results During the study period, the magnitude of peak discharge ranged from 52.4 to 314.3 m 3 /s. The inclusion of seven additional years’ data in the base model (hierarchical; annual-level covariate + previous “single year” model) resulted in parameter estimates that were similar to those that were derived for the previous (2016) model, supporting that substrate, depth, and velocity during peak discharge predicted annelid distribution. The magnitude model (base model + annual-level covariate for peak discharge) showed evidence of a strong negative association with annelid presence (95% of all Markov chain–Monte Carlo draws were negative). Every 101.9 m 3 /s increase in peak discharge was associated with an estimated 39% decrease in the odds of annelid presence. The estimated effect of magnitude on the probability of annelid presence was illustrated in the contrast between low- and high-magnitude peak discharge scenarios. For both scenarios, the effects of depth, velocity at peak discharge, and substrate, consistent with the previous model (2016), were evident, as was the further reduction in probability of annelid presence at the higher peak discharge. However, under the low-magnitude discharge scenario, M. occidentalis were predicted to be present on smaller less stable substrates and at a wider range of depths and velocities than they were under the high-magnitude discharge scenario. In contrast to the covariate for magnitude, the inclusion of a duration covariate did not show a strong relationship with annelid distribution, which we attributed to the lack of variation in this covariate during the study period. Conclusions This work provides quantitative evidence that high-magnitude peak discharge flow events lead to lower probabilities of annelid host presence. Lower probabilities of annelid hosts are indicative of a reduced distribution of the M. occidentalis host and in turn reduced risk of C. shasta for salmon.

California↗
USGS2026

Albuquerque Seismological Laboratory strategic vision

This circular presents a strategic outlook for the U.S. Geological Survey (USGS) Albuquerque Seismological Laboratory (ASL) for the next 10 years (2026–36). The ASL is a USGS field office in the Geological Hazards Science Center that operates portions of the Advanced National Seismic System and the Global Seismographic Network and focuses on fundamental research for instrumentation testing and data quality. The strategic outlook is categorized into two types of tasks: “Foundational Tasks” and “Aspirational Tasks.” Foundational Tasks are those that maintain the laboratory’s basic operations and services, including regional and global seismic monitoring, improving data quality, and providing instrument testing and support. A suite of Aspirational Tasks is also articulated; these can be considered priority targets of ASL that could improve ASL’s seismic monitoring capabilities and mission. Such tasks include improvements to remote stations, testing capabilities of nonseismic geophysical instruments, detection threshold monitoring, rapid aftershock deployments, and expanding seismic monitoring networks. This report was written with input from the USGS Geological Hazards Science Center, the USGS Earthquake Hazards Program (EHP), and colleagues with an interest in the work done by the ASL. Although the details of these tasks may change, this document can provide guidance on the overarching tasks at the ASL from 2026 to 2036 and an overview of the various components of the ASL and how they fit into the EHP and the Global Seismographic Network Program.

Circular↗
USGS2026

Proceedings of the Floodplain Vegetation Monitoring Workshop for the Long Term Resource Monitoring Element of the Upper Mississippi River Restoration Program, January 7–8, 2025, Moline, Illinois

Preface In anticipation for increased funding made possible by the Water Resources Development Act of 2020, the Upper Mississippi River Restoration (UMRR) Program identified a need to conduct river-wide assessments of floodplain vegetation. In January 2025, we assembled a group of subject matter experts to perform the following tasks: Review Upper Mississippi River Restoration’s current floodplain vegetation research portfolio, Identify important features and goals for long-term floodplain vegetation monitoring, Evaluate the suitability of existing datasets for system-wide vegetation assessments, and Discuss emerging opportunities to learn about floodplain vegetation dynamics from local-scale restoration and management projects. This document is a summarization of what occurred at the meeting and provides suggested next steps toward developing the capacity to conduct routine long-term monitoring and assessment of floodplain vegetation as part of the Upper Mississippi River Restoration Program.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2026

Opportunities and challenges in using Solid Phase Adsorption Toxin Tracking (SPATT) samplers for monitoring cyanotoxins in freshwater and estuarine environments

Cyanobacterial toxins (cyanotoxins) represent a substantial threat to drinking water supplies and safe recreational uses of freshwater resources in watersheds worldwide. Monitoring cyanotoxins can be difficult because toxin events are variable in both space and time, are not always persistent, can be moved easily by wind and currents, and may be degraded biotically or abiotically. Thus, monitoring programs that collect discrete samples on a monthly or even bimonthly interval can miss key events and underestimate cyanotoxin risk or if they capture a high-concentration event, can give a false impression that cyanotoxins are a widespread health hazard. The use of Solid Phase Adsorption Toxin Tracking (SPATT) samplers helps address this issue by providing a time-weighted average estimate of dissolved cyanotoxin occurrence and relative concentrations. SPATT samplers have been used as a complement to traditional monitoring programs and can help elucidate cyanotoxin dynamics. SPATT samplers have been used by six U.S. Geological Survey (USGS) Water Science Centers (New York, California, Oregon, Upper Midwest, New Jersey, and Lower Mississippi-Gulf) to monitor various cyanotoxins in waterbodies such as streams, rivers, lakes, waterfalls, estuaries, and drinking-water intakes. Despite their use across the USGS, there is little guidance available to ensure consistent approaches and data quality across the Bureau. This report summarizes best practices for SPATT deployment and analysis, synthesizes data and describes lessons learned from USGS studies, identifies priority knowledge gaps, and offers considerations for future targeted experiments to help improve data collection and interpretation.

Scientific Investigations Report↗
USGS2026

Science strategy for Cotoni-Coast Dairies, an onshore unit of the California Coastal National Monument

This science strategy describes the scientific mission of the unit, science previously conducted on or near the unit, and the partners who have given considerable effort to produce this science. Further, it identifies priority science needs, outlines the unit’s plan to meet those science needs in coordination with partners, shares scientific protocols for conducting new research, and identifies systems of communication to help ensure science information generated from this research is shared throughout BLM, with partners, and with the public. These components of the science strategy are intended to help achieve the fundamental goals of the effort: to support and expand partnerships while identifying priority science information needs of unit staff and partners and clearly outlining pathways for conducting, communicating, and applying that science.

California↗
USGS2026

Channel morphology and large wood control postfire debris-flow erosion and deposition

Runoff-generated debris flows are a known response to wildfire, and accurately predicting the volume of these debris flows is important for estimating the magnitude of downstream hazards. Prior data collection efforts have focused on debris-flow volume measurements at catchment outlets, but few studies have considered how erosion and deposition modulate the volume of sediment arriving at catchment outlets. This study takes advantage of a high-resolution dataset to document the factors that control the total debris-flow volume reaching the catchment outlet during a fatal postfire debris flow. Using pre- and post-event airborne lidar, satellite imagery and field mapping, we found that a postfire debris flow in the Black Hollow catchment in northern Colorado eroded 136,000 ± 30,000 m 3 and redeposited 27,000 ± 7,500 m 3 in the main channel. Most of the in-channel deposition (52% by volume) occurred where a confined channel reach transitioned to an unconfined channel reach downstream, allowing the flow to widen and deposit material. Wood jams played multiple roles in the debris-flow dynamics, both nucleating deposition (25% of the deposit volume was stored behind wood jams) and exacerbating erosion (50% of the total erosion occurred downstream from a wood dam break). The remaining deposition occurred due to spatial changes in channel slope as well as deposition observed at newly formed channel bars. Using these data in this study, we identified topographic and vegetation metrics that can be used (pre-event) to anticipate where deposition may occur in channels prior to a debris flow.

Colorado↗
USGS2026

The Climate Hazards Center Infrared Precipitation with Stations, version 3

The Climate Hazards Center Infrared Precipitation with Stations (CHIRPS) data stream combines: (1) a high-resolution climatology, (2) thermal infrared (TIR) geostationary satellite observations, and (3) station observations. In the past, CHIRPS version 2 (CHIRPS2) has proven to be valuable for drought monitoring, hydrologic modeling, scientific studies and agricultural decision making. Version 3 (CHIRPS3) improves each of these components. The new version, CHIRPS3 extends to 60°S/N, adopts an improved variance-preserving TIR-to-precipitation estimation method, uses many more stations and station sources than the original CHIRPS2 product, and implements gauge-undercatch correction. In this paper, we evaluate the performance of satellite-only CHIRP3, CHIRP2, IMERG, PERSIANN- CCS, and GPI using high quality interpolated data in twelve regions with dense station coverage. CHIRP3 represents both the observed mean and variance more accurately than CHIRP2. A usage section in Morocco shows that CHIRPS3 better captures the observed rainfall variability when compared to CHIRPS2. This section also demonstrates how station data should be gauge-undercatch-corrected when validating CHIRPS3.

Scientific Data↗
USGS2026

Quality and quantity of terrestrial landscape connectivity in the US Great Lakes Coastal Zone

Context The Great Lakes Coastal Zone (GLCZ), the world’s longest continuous freshwater coastline, consists of interspersed natural and developed landcover and is inhabited by millions of people. Anthropogenic change fragments the GLCZ, decreasing landscape connectivity. Objectives We evaluated functional landscape connectivity of the U.S. GLCZ, assessing regional connectivity, protected areas’ effects on connectivity, and identified pinchpoints where connectivity is most vulnerable. Methods We modeled landscape connectivity to describe corridors and redundant pathways for two scenarios: (1) continuous terrestrial habitat patches and (2) protected areas. We compared these two scenarios by total corridor area and quality at two spatial scales (coastal zone and ecoregion). We used random forest analyses to examine how ecological factors influenced the connectivity rank and pinchpoint values. A principal components analysis identified how land cover influenced connectivity among ecoregions. Results The GLCZ was 69% connected. Although 91% of the GLCZ’s high-quality habitat was within corridors, less than 50% of the corridor area was high-quality (low resistance to movement). While the northernmost region retained high-quality connectivity, connectivity loss and degradation increased with development further south. Corridors between protected areas provided less connectivity, of worse quality, in areas of development and agriculture. Lower connectivity was associated with higher impervious surface cover. Conclusions Protected area placement affected both the quantity and quality of connectivity. Improving and maintaining functional connectivity could be accomplished by strategically restoring and protecting habitats most vulnerable to connectivity loss, predominantly in urban and agricultural regions. Our connectivity improvement index is a useful tool to identify areas where connectivity may be improved.

Illinois, Indiana, Michigan, Minnesota, New York, ↗
USGS2026

The WOAH global wildlife health collaborating centre network (WOAH-WildNet): A coordinated and transformative approach to global wildlife health challenges

Wildlife health is integral to functioning, complex ecosystems [ 1 ], directly and indirectly influencing the health of people, animals, plants, and the environment [ 2 – 4 ]. Healthy wildlife populations are essential for ecosystem services and are at the heart of the One Health approach [ 3 , 4 ], which aims to sustainably balance and optimize the health of people, animals, and ecosystems through multisectoral and transdisciplinary collaboration [ 5 ]. Despite its importance, wildlife health initiatives often operate in silos, limiting capacity to address transboundary threats such as emerging diseases, pollution, and environmental changes. Anthropogenic changes, including habitat loss, degradation, fragmentation, and unsustainable harvesting, exacerbate wildlife health challenges [6–9]. These pressures disrupt species biology and alter host-pathogen dynamics [10–12], underscoring the importance of coordinated collective action in addressing harmful effects on the health of wild animals. While local conservation efforts are vital, long-term success in safeguarding biodiversity requires a unified, global network. For instance, without harmonized surveillance and response systems, individual institutions cannot effectively track pathogens across borders or share diagnostic capabilities. The World Organisation for Animal Health (WOAH) Collaborating Centre Network for Wildlife Health—WOAH-WildNet—was established to bridge these gaps. By fostering global collaboration, sharing resources, and enabling data exchange, WOAH-WildNet provides a transformative, systems-based approach to wildlife health, managing risks, and enhancing ecosystem resilience. Central to this mission is breaking down silos to promote intersectoral coordinated responses to complex wildlife health challenges.

PLOS Sustainability and Transformation↗
USGS2026

Occurrence of cyanobacteria and associated cyanotoxins in the Raritan Basin Water Supply Complex, New Jersey, August 2020 to August 2021

Harmful algal blooms, particularly cyanobacteria harmful algal blooms (cyanoHABs), have emerged as a substantial global concern because of their detrimental effects on water quality and aquatic ecosystem health. CyanoHABs can produce cyanotoxins, which pose serious health risks to humans and wildlife, such as liver failure and respiratory distress. This is particularly concerning for water bodies that serve as drinking-water sources. Recent trends indicate an increase in the frequency and intensity of cyanoHABs globally. This study focuses on the Raritan Basin Water Supply Complex in New Jersey, where extensive monitoring was conducted from August 2020 to August 2021 to assess the presence of cyanobacteria and associated cyanotoxins. The research utilized a combination of discrete water-quality sampling, continuous monitoring, and solid phase adsorption toxin tracking (SPATT) to capture the dynamics of cyanotoxin occurrence and potential transport. Findings revealed a widespread presence of cyanobacteria and potential for cyanotoxin production, although actual cyanotoxin concentrations remained below drinking water and recreational thresholds. The study, conducted by the U.S. Geological Survey (USGS) in collaboration with the New Jersey Water Supply Authority (NJWSA) and the New Jersey Department of Environmental Protection (NJDEP), highlighted the limitations of traditional sampling methods and emphasized that continuous monitoring can support better understanding of how cyanoHAB conditions change over time and in different places. Genetic testing included quantitative polymerase chain reaction (qPCR) analyses, which demonstrated higher sensitivity, or increased findings of cyanobacteria compared to microscopy, indicating the potential for use in early warning systems. This research underscores that integrating various detection methods and hydrological data can enhance understanding of cyanotoxin dynamics in river systems.

New Jersey↗
USGS2026

Phytoplankton responses to experimental nitrogen and phosphorus loading in the eutrophic and colored Caloosahatchee River, Florida

The Caloosahatchee River, located in southwest Florida, is a eutrophic and colored river that flows from Lake Okeechobee westward into its estuary and the Gulf of America. Cyanobacterial harmful algal blooms (HABs) are a documented problem along this freshwater-to-marine waterway where nutrient enrichment has been identified as a key factor in bloom occurrence but has not been experimentally tested in the river. This study is the first to test the effects of inorganic nutrient loading on phytoplankton assemblages in the Caloosahatchee River and the effects of different nutrient sources on phytoplankton dynamics at different times of the year. Three independent, in situ experiments were conducted to test the effects of daily, incrementally increased ammonium, nitrate, and phosphate loading on phytoplankton at different times of the year (summer, fall, winter). Over the 72-hour enclosure period, phytoplankton abundance metrics (cell concentration, chlorophyll- a , and phycocyanin), dissolved oxygen, and pH increased, and fluorescent dissolved organic matter and turbidity decreased in all treatments and controls. Increased phytoplankton abundance metrics relative to controls were observed after 72 hours of exposure to elevated ammonium and nitrate in summer and only ammonium in winter, suggesting periodic nitrogen limitation; however, no treatment effects on phytoplankton assemblage structure in terms of resemblance and diversity metrics were found. Increases in total cell concentrations were driven by elevated growth rates of already dominant taxa but not sufficiently to form a visible bloom. Cyanobacteria consistently dominated the phytoplankton, particularly Aphanocapsa and Merismopedia , whereas the common HAB-forming Microcystis maintained consistently low abundance. This study provides new information on the ecology of phytoplankton assemblages in the Caloosahatchee River and could be used by water resources managers to evaluate strategies for controlling cyanobacterial HABs in the river.

Florida↗
USGS2026

Incorporating data sets with multiple sources of uncertainty in integrated species distribution models

Data integration methods aim to improve species distribution estimates by incorporating multiple sources of uncertainty across datasets. Two major sources of uncertainty are: (1) variation in sampling effort across space and within datasets, and (2) variation in reliability associated with data collection protocols or timing among datasets. Our goal was to evaluate how different approaches to address these uncertainties influence predictive performance of integrated models. We modeled distributions of four bird species using three datasets that differed in sampling design. We examined three strategies to reduce uncertainty: (1) filtering data, (2) incorporating functions that account for uncertainty in observation models, and (3) varying how datasets are integrated into a single estimate. We first examine methods to account for variable effort in observations, focusing on both spatial differences in sampling intensity and effort given to a single observation record. We then examine approaches to account for data sets with differing reliability. Sampling effort was best addressed through conservative filtering, including spatial thinning and excluding observations with highly variable effort. Next, we considered how to account for potential false positive detections—due to either misidentification or changes in distributions. We found that treating less reliable data as a covariate, an approach previously suggested for data integration that can greatly speed up model fitting, performed well. Other effective approaches included directly modeling false positive rates and complete exclusion of less reliable data sets. Our results provide insights into best practices in integrated modeling for handling uncertainty in integrated models. We demonstrate the flexible options available when using integrated models to address uncertainty.

Pennsylvania↗
USGS2026

Suitability of ground-motion models for seismic hazard assessment in Puerto Rico and the U.S. Virgin Islands

We perform linear mixed-effects analyses with a ground-motion dataset to evaluate how well ground-motion models (GMMs) fit active crustal, subduction interface, and subduction intraslab earthquakes in Puerto Rico and the US Virgin Islands. Most of the GMMs reproduce the spatial variation in peak ground motions with earthquake magnitude and rupture distance but predict ground motions 0.3–1.0 natural log units (35%–270%) greater than observations. Two GMMs developed for Puerto Rico that are based on ground-motion records from mostly magnitude 4–5 earthquakes do not perform as well. We attribute the period-dependent overprediction in observed ground motions to differences between the observed site response and the linear site response in the GMMs. Consequently, we developed region-specific GMMs by adjusting the period-dependent linear site response coefficients and period-dependent constant coefficients to remove most of the bias between predicted ground motions and observations. For the analysis, we compile ground-motion records and process waveforms to build a dataset with 10,127 records at 72 stations from 849 magnitude 4.0–6.4 earthquakes between 1 January 2006 and 31 March 2024. The earthquakes include active crustal, subduction interface, and subduction intraslab events. We evaluate the GMMs using the time-averaged shear wave speed in the top 30 m ( ), which we compile from site surveys and proxy values computed from horizontal to vertical spectral ratios. Site terms exhibit strong consistency across GMMs and crustal and subduction earthquakes, indicating that the linear mixed-effects analysis successfully isolates the effects of local site response. The event terms show little spatial correlation and more substantial variability than in other regions, which we attribute to uncertainties in the earthquake magnitudes. This analysis guides the selection of the GMMs for the 2025 update of the National Seismic Hazard Model for Puerto Rico and the US Virgin Islands.

Puerto Rico, U.S. Virgin Islands↗
USGS2026

Pre-restoration sediment budget of a tidally restricted estuary reveals potential for landward transport

Unnatural tidal restrictions are common features in estuaries, often arising from agricultural practices, road construction, or drainage activities. Restrictions tend to attenuate tides landward of the structure but can induce more complex effects in the seaward direction, including modification of natural geomorphic processes. The Herring River Estuary is the site of the largest salt marsh restoration effort in the northeast United States. We deployed a suite of instruments over one year to identify the role of tidal and atmospheric processes on sediment dynamics. We find 6.2·10 6 kg yr -1 of sediment is exported from the system through its only channel; this seaward-directed flux indicates that the seaward Wellfleet Harbor is not a sediment source for the Herring River Estuary. The sediment floodebb differential is landward above the tidal restriction, producing a divergent, transgressive embayment. The mudflats are the primary source of this sediment, eroding at rates of 0.1 and 5.3 cm yr -1 at the shallow and deep stations, respectively. Sediment is resuspended on the mudflats during wind events and exported from the system when landward-directed winds produced a seaward return flow. Ebb-dominated tides also yield net sediment export during calm periods. Once the tidal restriction is removed, the areas landward of the restriction may become a large sediment sink. It is possible that sediment from the embayment between the mouth and the restriction begins to move landward rather than seaward, but it is unlikely that Wellfleet Harbor would supply additional sediment. Therefore, as the subsided salt marshes landward of the tidal restriction begin to accrete sediment, it would most likely come at the expense of the seaward channel bottoms, mudflats, and salt marsh shorelines described in this study. In partitioning the sediment budget to geomorphic processes, this work presents a significant advance in the understanding of the linkage between a tidally restricted estuary and its seaward embayment. As tidal restriction removal becomes a more common restoration practice, the understanding of pre-removal baseline conditions becomes important for developing conceptual models of post-removal geomorphic evolution.

Massachusetts↗
USGS2026

From model to action: Identifying the gaps in coastal marsh models for decision making

Coastal salt marsh modeling projects are designed to answer questions about where salt marshes may migrate, how they can migrate, and how they will be impacted by changing water levels. While this information is vital for climate-resilient marsh conservation, translating these findings into actionable results remains a challenge. The authors examined the actionability of marsh modeling efforts in the United States by analyzing data collected from semi-structured interviews of marsh model users ( n = 24) across two ongoing projects along the U.S. East Coast and the Gulf of America (Gulf of Mexico). By qualitatively analyzing the interview data, the authors found that the tasks of practitioners who use coastal marsh model outputs fall into three major themes: (1) marsh restoration, (2) planning with uncertainty, and (3) conserving habitat for marsh-reliant species. For each of these themes, the authors identify unmet needs, including high spatial resolution information for local planning, accessible descriptions of uncertainty to increase user confidence, and the incorporation of human dimensions data (e.g., human alterations to the landscape such as impoundments and culverts) for a comprehensive understanding of the coastal salt marsh. Marsh modeling projects should strategize how to fulfil these unmet user needs so that marsh modeling outputs can better support decisions related to marsh conservation and restoration.

Gulf of America, United States East Coast↗