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At least 307 records · Page 17Linked to original sources
USGS2006

The origin of neap-spring tidal cycles

The origin of oceanic tides is a basic concept taught in most introductory college-level sedimentology/geology, oceanography, and astronomy courses. Tides are typically explained in the context of the equilibrium tidal theory model. Yet this model does not take into account real tides in many parts of the world. Not only does the equilibrium tidal model fail to explicate amphidromic circulation, it also does not explain diurnal tides in low latitude positions. It likewise fails to explain the existence of tide-dominated areas where neap-spring cycles are synchronized with the 27.32-day orbital cycle of the Moon (tropical month), rather than with the more familiar 29.52-day cycle of lunar phases (synodic month). Both types of neap-spring cycles can be recognized in the rock record. A complete explanation of the origin of tides should include a discussion of dynamic tidal theory. In the dynamic tidal model, tides resulting from the motions of the Moon in its orbit around the Earth and the Earth in its orbit around the Sun are modeled as products of the combined effects of a series of phantom satellites. The movement of each of these satellites, relative to the Earth's equator, creates its own tidal wave that moves around an amphidromic point. Each of these waves is referred to as a tidal constituent. The geometries of the ocean basins determine which of these constituents are amplified. Thus, the tide-raising potential for any locality on Earth can be conceptualized as the result of a series of tidal constituents specific to that region. A better understanding of tidal cycles opens up remarkable opportunities for research on tidal deposits with implications for, among other things, a more complete understanding of the tidal dynamics responsible for sediment transport and deposition, changes in Earth-Moon distance through time, and the possible influences tidal cycles may exert on organisms. ?? 2006 Elsevier B.V. All rights reserved.

Marine Geology↗
USGS2023

Juvenile life history diversity is associated with lifetime individual heterogeneity in a migratory fish

Differences in the life history pathways (LHPs) of juvenile animals are often associated with differences in demographic rates in later life stages. For migratory animals, different LHPs often result in animals from the same population occupying distinct habitats subjected to different environmental drivers. Understanding how demographic rates differ among animals expressing different LHPs may reveal fitness trade-offs that drive the expression of alternative LHPs and enable better prediction of population dynamics in a changing environment. To understand how demographic outcomes and their relationships with environmental variables differ among animals with different LHPs, we analyzed a long-term (2006–2021) mark–recapture dataset for Chinook salmon ( Oncorhynchus tshawytscha ) from the Wenatchee River, Washington, USA. Distinct LHPs represented in this population include either remaining in the natal stream until emigrating to the ocean as a 1-year-old (natal-reach rearing) or emigrating from the natal stream and rearing in downstream habitats for several months before completing the emigration to the ocean as a 1-year-old (downstream rearing). We found that downstream-rearing fish emigrated to the ocean 19 days earlier on average and returned as adults from the ocean at higher rates. We detected a positive correlation between rate of return from the ocean by downstream-rearing fish and coastal upwelling in their spring of outmigration, whereas for natal-reach-rearing fish we detected a positive correlation with sea surface temperature during their first marine summer. Different responses to environmental variability should lead to asynchrony in adult abundance among juvenile LHPs. A higher proportion of downstream-rearing fish returned at younger ages compared with natal-reach-rearing fish, which contributed to variability in age at reproduction and greater mixing across generations. Our results demonstrate how diversity in juvenile LHPs is associated with heterogeneity in demographic rates during subsequent life stages, which can in turn affect variance in aggregate population abundance and response to environmental change. Our findings underscore the importance of considering life history diversity in demographic analyses and provide insights into the effects of life history diversity on population dynamics and trade-offs that contribute to the maintenance of life history diversity.

Washington↗
USGS2019

Application of the Stream Salmonid Simulator (S3) to Klamath River fall Chinook salmon (Oncorhynchus tshawytscha), California—Parameterization and calibration

Executive Summary In this report, we describe application of the Stream Salmonid Simulator (S3) to Chinook salmon ( Oncorhynchus tshawytscha ) in the Klamath River between Keno Dam in southern Oregon and the ocean in northern California. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. It can track different source populations or species, such as major tributary populations that enter a river like the Klamath River. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit affect survival and growth within each habitat unit and movement of fish among habitat units. The physical template of the Klamath River was formed by classifying the river into 2,635 mesohabitat units composed of runs, riffles, and pools. This template enabled modeling of the unimpounded Klamath River between the Keno Dam (the uppermost of four dams) and Iron Gate Dam (the lowermost dam) to address dam-removal scenarios. However, in this report, our focus was on parameterizing and calibrating the model under existing conditions, which included 1,706 discrete habitat units over the 312-kilometer (km) section of river between Iron Gate Dam and the ocean. For each habitat unit, we developed a time series of daily flow, water temperature, and amount of available habitat (weighted usable habitat area [WUA]) for spawners, fry, and parr. WUA time series were constructed using habitat suitability criteria for Chinook salmon applied to eight two-dimensional (2-D) hydrodynamic models that represented the geomorphic variability in habitat across the Klamath River. Results from the 2-D models were then extrapolated to unmodeled habitat units by scaling WUA curves for changes in habitat unit length and width. These variables were then used to drive population dynamics such as egg development and survival and juvenile movement, growth, and survival.

California, Oregon↗
USGS2012

The physical hydrogeology of ore deposits

Hydrothermal ore deposits represent a convergence of fluid flow, thermal energy, and solute flux that is hydrogeologically unusual. From the hydrogeologic perspective, hydrothermal ore deposition represents a complex coupled-flow problem—sufficiently complex that physically rigorous description of the coupled thermal (T), hydraulic (H), mechanical (M), and chemical (C) processes (THMC modeling) continues to challenge our computational ability. Though research into these coupled behaviors has found only a limited subset to be quantitatively tractable, it has yielded valuable insights into the workings of hydrothermal systems in a wide range of geologic environments including sedimentary, metamorphic, and magmatic. Examples of these insights include the quantification of likely driving mechanisms, rates and paths of fluid flow, ore-mineral precipitation mechanisms, longevity of hydrothermal systems, mechanisms by which hydrothermal fluids acquire their temperature and composition, and the controlling influence of permeability and other rock properties on hydrothermal fluid behavior. In this communication we review some of the fundamental theory needed to characterize the physical hydrogeology of hydrothermal systems and discuss how this theory has been applied in studies of Mississippi Valley-type, tabular uranium, porphyry, epithermal, and mid-ocean ridge ore-forming systems. A key limitation in the computational state-of-the-art is the inability to describe fluid flow and transport fully in the many ore systems that show evidence of repeated shear or tensional failure with associated dynamic variations in permeability. However, we discuss global-scale compilations that suggest some numerical constraints on both mean and dynamically enhanced crustal permeability. Principles of physical hydrogeology can be powerful tools for investigating hydrothermal ore formation and are becoming increasingly accessible with ongoing advances in modeling software.

Economic Geology↗
USGS2018

Effect of climate change on disease spread in wildlife

A growing body of evidence indicates that climate change alone, or acting synergistically with current anthropogenic threats, is affecting the health of wild populations of aquatic and terrestrial wildlife. Measurable by-products of climate change include elevated atmospheric concentrations of greenhouse gases, higher average global temperatures; variations in global precipitation patterns, rising and warming oceans, altered hydrographs of rivers, and increased mid-continental drying during summer. These consequences affect the terrestrial environment through shifts in phenology, vegetation cover, and fire regimes. Warmer ocean temperatures, increased acidification, rise in sea levels, and reduction in sea ice cover are also leading to widespread ecological changes in marine systems. Wildlife populations face a variety of climate-related pressures, such as changes in animal distribution or density, limitation of food resources, and alteration to critical habitats. The increased potential for emergence and resurgence of diseases that are responsive to environmental conditions also has implications for wildlife populations. Shifts in temperature or other climatic factors may directly affect the incidence of disease in wildlife by altering host-pathogen interactions, promoting vector populations or allowing new ranges for vectors, or reducing development times for parasites. A number of examples from both field and laboratory studies have demonstrated a clear link between warming environments and disease spread. Many climate-related environmental changes also influence wildlife health indirectly. For example, increasing temperatures, in combination with shifts in rainfall and humidity, may aggravate current trends for water resource limitation and habitat degradation or destruction and lead to increased crowding of animal populations, thereby promoting transmission opportunities of pathogens within populations or across species. Although it may be difficult to disentangle the influences of other anthropogenic changes from the direct effects of warming, some ecosystems provide especially useful models for studying climate-related disease spread in wildlife. For example, the effects of climate change on parasite dynamics may be easily observed in the Arctic, where environmental changes are occurring rapidly, anthropogenic influences are relatively limited, and biodiversity is generally low. Marine ecosystems are also undergoing rapid rates of change and may be vulnerable to a variety of natural and anthropogenic perturbations. Although many factors affect the health of organisms in ocean environments, temperature has been clearly linked to an increase in disease prevalence among sessile organisms such as corals. In this chapter, we discuss observed and predicted changes to wildlife health resulting from climate change. Our review will not include all aspects of wildlife health, but will instead focus on established or suspected links between climate drivers and disease spread and discuss examples from the current literature. Here, we define disease spread to include: 1) change in geographical or altitudinal distribution of pathogens, parasites, and vectors and the diseases they cause; 2) change in prevalence or severity of disease; and 3) emergence of novel diseases. Additionally, because wildlife species serve as reservoirs for zoonotic diseases that affect both animals and humans, we include select examples of the effect of climate change on the capacity of wildlife to harbor and spread these disease agents.

Book chapter↗
USGS2011

Hydrodynamics of a bathymetrically complex fringing coral reef embayment: Wave climate, in situ observations, and wave prediction

This paper examines the relationship between offshore wave climate and nearshore waves and currents at Hanalei Bay, Hawaii, an exposed bay fringed with coral reefs. Analysis of both offshore in situ data and numerical hindcasts identify the predominance of two wave conditions: a mode associated with local trade winds and an episodic pattern associated with distant source long-period swells. Analysis of 10 months of in situ data within the bay show that current velocities are up to an order of magnitude greater during long-period swell episodes than during trade wind conditions; overall circulation patterns are also fundamentally different. The current velocities are highly correlated with incident wave heights during the swell episodes, while they are not during the modal trade wind conditions. A phase-averaged wave model was implemented with the dual purpose of evaluating application to bathymetrically complex fringing reefs and to examine the propagation of waves into the nearshore in an effort to better explain the large difference in observed circulation during the two offshore wave conditions. The prediction quality of this model was poorer for the episodic condition than for the lower-energy mode, however, it illustrated how longer-period swells are preferentially refracted into the bay and make available far more nearshore wave energy to drive currents compared to waves during modal conditions. The highly episodic circulation, the nature of which is dependent on complex refraction patterns of episodic, long-period swell has implications for flushing and sediment dynamics for incised fringing reef-lined bays that characterize many high islands at low latitudes around the world.

Hawai'i↗
USGS2019

Submarine permafrost map in the arctic modelled using 1D transient heat flux (SuPerMAP)

Offshore permafrost plays a role in the global climate system, but observations of permafrost thickness, state, and composition are limited to specific regions. The current global permafrost map shows potential offshore permafrost distribution based on bathymetry and global sea level rise. As a first‐order estimate, we employ a heat transfer model to calculate the subsurface temperature field. Our model uses dynamic upper boundary conditions that synthesize Earth System Model air temperature, ice mass distribution and thickness, and global sea level reconstruction and applies globally distributed geothermal heat flux as a lower boundary condition. Sea level reconstruction accounts for differences between marine and terrestrial sedimentation history. Sediment composition and pore water salinity are integrated in the model. Model runs for 450 ka for cross‐shelf transects were used to initialize the model for circumarctic modeling for the past 50 ka. Preindustrial submarine permafrost (i.e., cryotic sediment), modeled at 12.5‐km spatial resolution, lies beneath almost 2.5 ×10 6 km 2 of the Arctic shelf. Our simple modeling approach results in estimates of distribution of cryotic sediment that are similar to the current global map and recent seismically delineated permafrost distributions for the Beaufort and Kara seas, suggesting that sea level is a first‐order determinant for submarine permafrost distribution. Ice content and sediment thermal conductivity are also important for determining rates of permafrost thickness change. The model provides a consistent circumarctic approach to map submarine permafrost and to estimate the dynamics of permafrost in the past.

Journal of Geophysical Research C: Oceans↗
USGS2018

Acoustic telemetry observation systems: challenges encountered and overcome in the Laurentian Great Lakes

The Great Lakes Acoustic Telemetry Observation System (GLATOS), organized in 2012, aims to advance and improve conservation and management of Great Lakes fishes by providing information on behavior, habitat use, and population dynamics. GLATOS faced challenges during establishment, including a funding agency-imposed urgency to initiate projects, a lack of telemetry expertise, and managing a flood of data. GLATOS now connects 190+ investigators, provides project consultation, maintains a web-based data portal, contributes data to Ocean Tracking Network’s global database, loans equipment, and promotes science transfer to managers. The GLATOS database currently has 50+ projects, 39 species tagged, 8000+ fish released, and 150+ million tag detections. Lessons learned include (1) seek advice from others experienced in telemetry; (2) organize networks prior to when shared data is urgently needed; (3) establish a data management system so that all receivers can contribute to every project; (4) hold annual meetings to foster relationships; (5) involve fish managers to ensure relevancy; and (6) staff require full-time commitment to lead and coordinate projects and to analyze data and publish results.

Laurentian Great Lakes↗
USGS2012

Projected climate and vegetation changes and potential biotic effects for Fort Benning, Georgia; Fort Hood, Texas; and Fort Irwin, California

The responses of species and ecosystems to future climate changes will present challenges for conservation and natural resource managers attempting to maintain both species populations and essential habitat. This report describes projected future changes in climate and vegetation for three study areas surrounding the military installations of Fort Benning, Georgia, Fort Hood, Texas, and Fort Irwin, California. Projected climate changes are described for the time period 2070–2099 (30-year mean) as compared to 1961–1990 (30-year mean) for each study area using data simulated by the coupled atmosphere-ocean general circulation models CCSM3, CGCM3.1(T47), and UKMO-HadCM3, run under the B1, A1B, and A2 future greenhouse gas emissions scenarios. These climate data are used to simulate potential changes in important components of the vegetation for each study area using LPJ, a dynamic global vegetation model, and LPJ-GUESS, a dynamic vegetation model optimized for regional studies. The simulated vegetation results are compared with observed vegetation data for the study areas. Potential effects of the simulated future climate and vegetation changes for species and habitats of management concern are discussed in each study area, with a particular focus on federally listed threatened and endangered species.

Georgia;Texas;California↗
USGS2015

Coastal landforms and processes at the Cape Cod National Seashore, Massachusetts—A primer

Anyone who spends more than a few days on Cape Cod (the Cape) quickly becomes a coastal geologist, quickly learning the rhythms of daily tides and the seasonal cycles of beaches growing and being swept away by storms; swimmers and surfers track how the breakers appear, and dog-walkers notice the hard-packed sand blanketed overnight by an airy layer that leaves deep labored tracks. Careful observers whose paths wander to the ocean’s edge will observe many of the landforms and coastal processes described in this book and if we have done our job well, the stories told here will seem familiar. Watchful experience brings insights; indeed, this is how scientists and perhaps how artists work, describing patterns that explain and predict. When is the next high tide? What will the winter bring? Where do we build, fish, swim? How do wind and waves offshore in the North Atlantic help arrange the plants and dunes and hollows on the beach? And most of all, as human animals drawn to live and play on the edge of the ocean, how do we get the benefits of this complex natural system of geology and biology? How do we affect coastal processes; how is the coast changing now and how is the coast likely to change in years ahead with climate warming and climate change? This book is about the highly dynamic coastal landforms of Cape Cod—the beaches, bluffs, spits, dunes, barrier beaches, estuaries, and salt marshes. What they are, why they are where they are, how they behave with respect to the greater Cape Cod coastal system—how the landforms respond to day-to-day and long-term geologic processes, such as waves and currents, change in sediment transport, relative sea-level rise, and meteorological processes such as hurricanes, nor’easters, and cold front passages. It is also about how the landforms got to be where they are and the way they are and where they are headed in the near future with the predicted effects of global climate warming and change. Our objective is to provide a single source of understandable and readable scientific information for those who live, play, and work on outer Cape Cod and at the Cape Cod National Seashore, as well as to provide an introduction to Cape Cod’s coastal landforms for anyone with an interest in Earth science and nature who wants a better understanding of coastal systems and processes. Basic to an understanding of coastal landforms is the fact that they work together—they interact—as elements of many systems, and therefore our ultimate concern is not the individual landform itself but rather the geologic systems that make up Cape Cod and the Cape Cod National Seashore. Much of this discussion can be applied as well to Nantucket, Martha’s Vineyard, and other coastal regions. The coast of outer Cape Cod, about 15,000 years old and about 30 miles (mi; 50 kilometers [km]) long, is but a tiny piece of the global Earth system that operates within a much larger realm of space and time. Cape Cod’s coastal landforms are temporary holding patterns within a continual interplay of land, sea, atmosphere, climate, ice, and life, including a variety of human activities that both affect and are affected by these processes. These interactions produce the landforms, and the landforms alter the interactions. The resulting landforms provide habitats for a wide variety of coastal plants and animals. The habitats along with their inhabitants and the interacting environmental factors controlling them constitute the Cape’s complex and varied ecosystems. But for now, we are here to enjoy it. We welcome you to delight and wonder at the perpetually changing handshake between the ocean and shore at New England’s Great Beach.

Massachusetts↗
USGS2007

Tectonics of the West Antarctic rift system: new light on the history and dynamics of distributed intracontinental extension

The West Antarctic rift system (WARS) is the product of multiple stages of intracontinental deformation from Jurassic to Present. The Cretaceous rifting phase accomplished >100 percent extension across the Ross Sea and central West Antarctica, and is widely perceived as a product of pure shear extension orthogonal to the Transantarctic Mountains that led to breakup and opening of the Southern Ocean between West Antarctica and New Zealand. New structural, petrological, and geochronological data from Marie Byrd Land reveal aspects of the kinematics, thermal history, and chronology of the Cretaceous intracontinental extension phase that cannot be readily explained by a single progressive event. Elevated temperatures in "Lachlan-type" crust caused extensive crustal melting and mid-crustal flow within a dextral transcurrent strain environment, leading to rapid extension and locally to exhumation and rapid cooling of a migmatite dome and detachment footwall structures. Peak metamorphism and onset of crustal flow that brought about WARS extension between 105 Ma and 90 Ma is kinematically, temporally, and spatially linked to the active convergent margin system of East Gondwana. West Antarctica-New Zealand breakup is distinguished as a separate event at 83-70 Ma, from the standpoint of kinematics and thermal evolution

Open-File Report↗
USGS2011

Biological review of 82 species of coral petitioned to be included in the Endangered Species Act

list 83 coral species as threatened or endangered under the U.S. Endangered Species Act. The petition was based on a predicted decline in available habitat for the species, citing anthropogenic climate change and ocean acidification as the lead factors among the various stressors responsible for the potential decline. The NMFS identified 82 of the corals as candidate species, finding that the petition provided substantive information for a potential listing of these species. The NMFS established a Biological Review Team (BRT) to prepare this Status Review Report that examines the status of these 82 candidate coral species and evaluates extinction risk for each of them. This document makes no recommendations for listing, as that is a separate evaluation to be conducted by the NMFS. The BRT considered two major factors in conducting this review. The first factor was the interaction of natural phenomena and anthropogenic stressors that could potentially contribute to coral extinction. After extensive review of available scientific information, the BRT considers ocean warming, disease, and ocean acidification to be the most influential threats in posing extinction risks to the 82 candidate coral species between now and the year 2100. Threats of local origin but having widespread impact, such as sedimentation, nutrient enrichment, and fishing, were considered of medium importance in determining extinction risks. It is acknowledged that many other threats (e.g., physical damage from storms or ship groundings, invasive species or predator outbreaks, collection and trade) also negatively affect corals, often acutely and dramatically, but generally at relatively small local scales. These local threats were considered to be of limited scope and not deemed to contribute appreciably to the risk of species extinction, except in those special cases where species have restricted geographic or habitat ranges or species have already undergone precipitous population declines such that these local threats further contribute to depensatory processes that can magnify extinction risks (e.g., feedback-loops whereby individual survival decreases with smaller population size). The BRT acknowledges that local and global threats operate on different time scales and, though there is high confidence in the general progression of some key global threats, such as ocean warming and ocean acidification, there is much less certainty in the timing and spatial patterns of these threats. There is also substantial uncertainty in the abilities of the 82 candidate coral species to tolerate or adapt to each of the threats examined, as well as uncertainty in the dynamics of multiple simultaneous stresses. The BRT specifically identified increasing human population levels and the intensity of their collective human consumption as the root drivers of almost all global and local threats to coral species. In evaluating future threat impacts, the BRT attempted to project current trends, without assumptions of future policy changes or technological advances that could potentially alter the projections used in this analysis.

NOAA Technical Memorandum↗
USGS2024

Snake River Fall Chinook Salmon research and monitoring

In Chapter 1, we report on development and application of an integrated population model (IPM) for the natural-origin fall Chinook salmon population upstream of Lower Granite Dam. This year’s efforts represent the third update to the model. Initial efforts focused on generating juvenile and adult abundance estimates, with estimates of uncertainty, for informing the life-cycle model and estimating the effects of covariates on key demographic parameters. The goals of this year’s report are to 1) describe the modifications and advances made since the previous report, 2) to annually update and report the abundance estimates and other quantities used in the model, 3) to provide annual estimates of population parameters estimated by the IPM, and 4) to outline the next year’s tasks for advancing and/or applying the model. Since our last report on the life-cycle model, we have made a number of changes including: 1) incorporating jack abundance and age-structure data into the observation model, 2) changing smolt-to-adult survival (SAR) for subyearling and yearling to partial SARs that represent the joint probability surviving and entering the ocean at a given juvenile age, 3) combining age categories for rarely observed ages, 4) using scale data from unmarked fish to estimate age structure, and 5) generating composite life-cycle demographic parameters (cumulative capacity and productivity) from stage-specific parameters. We also generated juvenile abundance estimates, extended the model to include three additional brood years (1992– 2021), and ran the model to forecast returns to Lower Granite in 2022. For posterior medians of life stage-specific parameters, we estimated a mean productivity of 438 natural-origin juvenile recruits per female spawner, a capacity of 1.36 million juveniles, and a mean smolt-to-adult survival (SAR) of 1.2%. We detected strong density-dependent regulation, with juvenile recruits per spawner declining to about 50 juvenile recruits per female spawner at high spawner abundance. Across the entire life cycle, these stage-specific parameters resulted in a median cumulative intrinsic productivity of 1.93 adult female recruits per female spawner and a median equilibrium abundance of 2,851 female spawners (7,842 total spawners). Annual juvenile productivity varied from about 250–1,000 juveniles per spawner but displayed no temporal trends or patterns. For the three most recent brood years added to the model, recruits per spawner were higher than average but well within the range of uncertainty observed over the entire time series. In contrast to juvenile recruitment variability, SAR varied considerably among years and exhibited two periods of high survival (1996–2001 and 2007–2012) when SAR ranged from 2% to 6% and cumulative productivity ranged from 2 to 8 recruits per spawner. Partial SARs revealed that yearling outmigrants contributed substantially to the high SARs in the first high-survival period, but the second period was dominated by subyearlings. Yearlings contributed >30% to SAR in most years prior to 2007, and <30% since 2007. Our two-stage IPM provides a wealth of information about population dynamics affecting two key life-stage transitions (spawner to juvenile, and juvenile to spawner) centered on passage at Lower Granite Dam. By summarizing these stage-specific demographic parameters across the entire life cycle, this information will be useful for informing the recovery status of this threatened population. Whereas previous versions introduced hydrosystem and ocean covariates into the model, this phase of model development focused on solidifying the underlying model structure by introducing the concept of partial SARs and developing composite productivity and capacity as a function of underlying stage-specific parameters. Given this advancement, our next steps are to re-incorporate covariates into the model, specifically to understand how different factors affect partial SARs of subyearling and yearlings. Longer term model developments include:1) incorporating hatchery fish to explicitly estimate their survival as an alternative method for estimating natural-origin age composition, 2) expanding the model’s structure to include the three major spawning aggregates, 3) more explicitly modeling hydrosystem effects including transportation, and 4) using the model to assess retrospective and prospective management actions. In 2022, the U.S. Geological Survey (USGS) focused adult salmon survey efforts in the Snake River on deepwater redd searches and fish collection for parentage-based tagging (PBT) analyses. We use used a boat-mounted underwater video camera to count 99 deepwater redds at 16 of the 29 sites surveyed. Redd depths averaged 4.4 m. In conjunction with the Idaho Power Company, we collected genetic samples from 318 live fall Chinook salmon (Oncorhynchus tshawytscha) and 19 carcasses at 40 unique geographic locations that spanned 91 river kilometers. Eighty fish were collected at three sites (High Range [rkm 332.3], Dug Bar [rkm 315.4], and Three Creek [rkm 384.0]), which accounted for 23% of all collected fish in 2022. Most (333 fish) post-spawned salmon were collected from early to mid-November just after the peak of spawning. A summary of 2021 PBT results produced by the Idaho Power Company can be found in Appendix A.2. Beach seining and PIT tagging of subyearling fall Chinook salmon was conducted in Snake and Salmon rivers to obtain information on population metrics and growth as well as to provide data for ongoing life-cycle modeling. In the Snake River, we collected 7,496 subyearlings, tagged 4,139, and recaptured 502 (12.1%). Using 8-mm tags in 45–49-mm fish allowed us to represent an additional 25% of the juvenile population through PIT tagging beyond just using standard 9- and 12-mm tags. In the Salmon River, we captured 206 natural subyearlings with the majority (52%) of fish being captured at two sites: rkm 20 and 26. We tagged 145 subyearlings and recaptured 9 fish. Many of the subyearlings we tagged in the Snake River were detected passing Lower Granite Dam, but only 4 fish tagged in the Salmon River were detected. In total we detected 484 (11.3%) tagged fish at Lower Granite Dam, and detection rates varied by tag size and passage route. More subyearlings were detected passing via the removable spill weir (RSW) earlier in the season while more fish were detected passing through the juvenile fish bypass system (JBS) earlier in the season while more fish were detected passing via the removable spill weir (RSW) later in the season. In general, fish tagged with 12-mm PIT tags had higher detection rates than fish tagged with smaller tags. Survival to Lower Granite Dam was low and ranged from 0.22 to 0.36. Season-wide, growth of subyearlings was higher in the lower reach than in the upper reach of the Snake River.

Idaho, Oregon, Washington↗
USGS2023

Calibration of the Trinity River Stream Salmonid Simulator (S3) with extension to the Klamath River, California, 2006–17

The Trinity River is managed in two sections: (1) the upper 64-kilometer (km) “restoration reach” downstream from Lewiston Dam and (2) the 120-km lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously constructed and calibrated for the restoration reach. In this report, we extended and parameterized S3 for the 120-km section of the lower Trinity River to the confluence with the Klamath River and then to the Pacific Ocean in northern California. S3 is a deterministic life-stage structured-population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive (1) survival and growth within each habitat unit and (2) movement of fish among habitat units. The physical template of the Trinity River was formed by classifying the river into 910 meso-habitat units that were designated into runs, riffles, or pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival. We estimated key movement and survival parameters by calibrating the model to 12 years (2007–18) of weekly juvenile abundance estimates from two rotary screw traps: (1) the Pear Tree trap near the downstream end of the restoration reach and (2) the Willow Creek trap site is about 40.2 km upriver from the Trinity River’s confluence with the Klamath River. The calibration consisted of replicating historical conditions as closely as possible (for example: flow, temperature, spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location. We also evaluated four alternative model structures that included either no density-dependence, density-independent movement and survival, density-dependent survival, or density-dependent movement. Akaike information criterion model selection was used to evaluate the strength of evidence for alternative model structures to simulate the observed abundance estimates. Model selection supported the conclusion that the fully density-dependent model and density-dependent survival model was better supported by the data than the no density-dependence or density-dependent movement model. Because density-dependent movement was favored in past evaluations, we focus on the results from the fully density-dependent model. Parameter estimates from this model indicated that fry were less likely than parr to move downstream and that fry moved slower. Fry had a lower daily survival probability than parr. In contrast, hatchery fish had the highest probability of movement and the lowest daily survival probability. Fitting the model to both traps individually enabled us to independently compare the fit and performance of S3 at simulating fish abundance, timing, and growth of juvenile salmon in the upper restoration reach and lower Trinity River. We obtained a better fit to the data at the Willow Creek trap site than we obtained at the Pear Tree trap site, regardless of whether we fit the model to the abundances at the Pear Tree trap or Willow Creek trap. This better fit was surprising given that the S3 input data for the upper restoration reach required fewer assumptions than fitting to the Willow Creek trap site that is farther down river. Fitting S3 to weekly abundances at the Willow Creek trap site required making assumptions about (1) extrapolating capacity-flow relationships to unmeasured habitat units; (2) spatially allocating spawners within the lower Trinity River; and (3) approximating the abundance, timing, and size of juveniles entering from tributaries. The model provided better fit to the data at the Willow Creek trap site. In the weekly abundance estimates, in relation to the S3 simulated abundances, several migration years’ (2011, 2015–17) weekly abundance estimates appeared truncated and were near or at peak annual abundances in January, suggesting that a large fraction of juveniles was migrating as early as December at the Pear Tree trap site. Some early life dynamics may not be currently incorporated into S3. For example, the estimation of abundance at the Pear Tree trap may be biased because of size selectivity. Knowing about selectivity at the Pear Tree trap could greatly improve S3’s ability to predict weekly and peak abundances each year.

California↗
USGS2025

Cosmic dust reveals dynamic shifts in central Arctic sea-ice coverage over the past 30,000 years

Arctic sea-ice loss affects biological productivity, sustenance in coastal communities, and geopolitics. Forecasting these impacts requires mechanistic understanding of how Arctic sea ice responds to climate change, but this is limited by scarce long-term records. We present continuous 30,000-year reconstructions of sea-ice coverage from the Arctic Ocean based on measurements of two isotopes, thorium-230 and extraterrestrial helium-3, whose burial ratio changes with sea-ice coverage. We found that the central Arctic was perennially covered by sea ice during the last glaciation. Sea-ice cover retreated during the deglaciation approximately 15,000 years ago, culminating in seasonal sea-ice coverage in the warm early Holocene, before ice coverage increased into the late Holocene. Sea-ice changes closely correlate with biological nutrient consumption, supporting projections of a nutrient-starved central Arctic Ocean with continued sea-ice loss.

Science↗
USGS2007

Glaciers dominate eustatic sea-level rise in the 21st century

Ice loss to the sea currently accounts for virtually all of the sea-level rise that is not attributable to ocean warming, and about 60% of the ice loss is from glaciers and ice caps rather than from the two ice sheets. The contribution of these smaller glaciers has accelerated over the past decade, in part due to marked thinning and retreat of marine-terminating glaciers associated with a dynamic instability that is generally not considered in mass-balance and climate modeling. This acceleration of glacier melt may cause 0.1 to 0.25 meter of additional sea-level rise by 2100.

Science↗
USGS2018

Paleoclimate Records: Providing context and understanding of current Arctic change

At present, the Arctic Ocean is experiencing changes in ocean surface temperature and sea ice extent that are unprecedented in the era of satellite observations, which extend from the 1980s to the present (see sections 5c,d). To provide context for current changes, scientists turn to paleoclimate records to document and study anthropogenic influence and natural decadal and multidecadal climate variability in the Arctic system. Paleoceanographic records extend limited Arctic instrumental measurements back in time and are central to improving our understanding of climate dynamics and the predictive capability of climate models. By comparing paleoceanographic records with modern observations, scientists can place the rates and magnitudes of modern Arctic change in the context of those inferred from the geological record. Over geological time, paleoceanographic reconstructions using, for instance, marine sediment cores indicate that the Arctic has experienced huge sea ice fluctuations. These fluctuations range from nearly completely ice-free to totally ice-covered conditions. The appearance of ice-rafted debris and sea ice-dependent diatoms in Arctic marine sediments indicate that the first Arctic sea ice formed approxi-mately 47 million years ago (St. John 2008; Stickley et al. 2009; Fig. SB5.1), coincident with an interval of declining atmospheric carbon dioxide (CO2) concentration, global climate cooling, and expansion of Earths cryosphere during the middle Eocene. The development of year-round (i.e., perennial) sea ice in the central Arctic Ocean, similar to conditions that exist today, is evident in sediment records as early as 1418 million years ago (Darby 2008). These records suggest that transitions in sea ice cover occur over many millennia and often vary in concert with the waxing and waning of circum-Arctic land ice sheets, ice shelves, and long-term fluctuations in ocean and atmospheric temperature and atmospheric CO2 concentrations (Stein et al. 2012; Jakobsson et al. 2014). Over shorter time scales, shallow sediment records from Arctic Ocean continental shelves allow more detailed, higher-resolution (hundreds of years resolution) reconstructions of sea ice history extending through the Holocene (11 700 years ago to present), the most recent interglacial period. A notable feature of these records is an early Holocene sea ice minimum, corresponding to a thermal maximum (warm) period from 11 000 to 5000 years ago, when the Arctic may have been warmer and had less summertime sea ice than today (Kaufman et al. 2004). However, it is not clear that the Arctic was ice-free at any point during the Holocene (Polyak et al. 2010). High-resolution paleosea ice records from the western Arctic in the Chukchi and East Siberian Seas indicate that sea ice concentrations increased through the Holocene in concert with decreasing summer solar insolation (sunlight). Sea ice extent in this region also varied in response to the volume of Pacific water delivered via the Bering Strait into the Arctic Basin (Stein et al. 2017; Polyak et al. 2016). Records from the Fram Strait (Mller et al. 2012), Laptev Sea (Hrner et al. 2016), and Canadian Arctic Archipelago (Vare et al. 2009) also indicate a similar long-term expansion of sea ice and suggest sea ice extent in these regions is modulated by the varying influx of warm Atlantic water into the Arctic Basin (e.g., Werner et al. 2013). Taken together, available records support a circum-Arctic sea ice expansion during the late Holocene. A notably high-resolution summer sea ice history (<5-year resolution) has been established for the last 1450 years using a network of terrestrial records (tree ring , lake sediment, and ice core records) located around the margins of the Arctic Ocean (Kinnard et al. 2011). Results summarized in Fig. SB5.2 indicate a pronounced decline in summer sea ice extent beginning in the 20th century, with exceptionally low ice extent recorded since the mid-1990s, consistent with the satellite record (see section 5d). While several episodes of reduced and expanded sea ice extent occur in association with climate anomalies such as the Medieval Climate Warm Period (AD 8001300) and the Little Ice Age (AD 14501850), the magnitude and pace of the modern decline in sea ice is outside of the range of natural variability and unprecedented in the 1450-year reconstruction (Kinnard et al. 2011). A radiocarbon-dated driftwood record of the Ellesmere ice shelf in the Canadian High Arctic, the oldest landfast ice in the Northern Hemisphere, also demonstrates a substantial reduction in ice extents over the 20th century (England et al. 2017). A supporting sediment record indicates that inflowing Atlantic water in Fram Strait has warmed by 2C since 1900, driving break up and melt of sea ice (Spielhagen et al. 2011). Complementary mooring and satellite observations show the Atlantification of the eastern Arctic due to enhanced inflow of warm saline water through Fram Strait (Nilsen et al. 2016) and nutrient-rich Pacific water via the Bering has increased by more than 50% (Woodgate et al. 2012), further driving sea ice melt and warming seas. Similar high-resolution proxy records from Arctic regions also indicate that the modern rate of increasing annual surface air temperatures has not been observed over at least the last 2000 years (McKay and Kaufman 2014). Scientists conclude that broad-scale sea ice variations recorded in the paleo record were dominantly driven by changes in basin-scale changes in atmospheric circulation patterns, fluctuations in air temperature, strength of incoming solar radiation, and changes in the inflow of warm water via Pacific and Atlantic inflows (Polyak et al. 2010). There is general consensus that ice-free Arctic summers are likely before the end of the 21st century (e.g., Stroeve et al. 2007; Massonnet et al. 2012), while some climate model projections suggest ice-free Arctic summers as early as 2030 (Wang and Overland 2009). Paleoclimate studies and observational time series attribute the decline in sea ice extent and thickness over the last decade to both enhanced greenhouse warming and natural climate variability. While understanding the interplay of these factors is critical for future projections of Arctic sea ice and ecosystems, most observational time series records cover only a few decades. This highlights the need for additional paleoceanographic reconstructions across multiple spatial and temporal domains to better understand the drivers and implications of present and future Arctic Ocean change.

Bulletin American Meteorological Society↗
USGS2018

Assessing the impact of open-ocean and back-barrier shoreline change on Dauphin Island, Alabama, at multiple time scales over the last 75 years

Dauphin Island and Little Dauphin Island, collectively, make up a geomorphically complex barrier island system located along Alabama’s southern coast, separating Mississippi Sound from the Gulf of Mexico and Mobile Bay. The barrier island system provides numerous economical (tourism, fisheries) and natural (habitat for migratory birds, natural protection of inland and coastal areas from storms) benefits to the State of Alabama. The complex geomorphology of Dauphin Island is partly a response to temporal variations in the direction and magnitude of sediment transport along and across the barrier island system. In this report, we present open-ocean and back-barrier shoreline change rates at different time scales to evaluate the island’s dominant behavior (expansion or widening and contraction or narrowing) over the last 75 years. The spatial and temporal variability of barrier island width provides baseline and historical context for potential restoration alternatives being considered as part of the Alabama Barrier Island Restoration Feasibility Study. Open-ocean shorelines have eroded continuously over the last 75 years, with rates ranging from 1.5 to 4 meters per year. Back-barrier shorelines are less uniform than open-ocean shorelines, but are, on average, also eroding over the same period. Periods of back-barrier progradation are observed but generally occur during discrete, large altering events like hurricanes that overwash or breach narrow sections of the barrier island. Because both shorelines are eroding, the width of the island has decreased during the last 75 years. The section to the west of a breach that opened during Hurricanes Ivan and Katrina (known as Katrina Cut) exhibits a steady, rapid decrease in width while the section to the east of the breach has gone through periods of expansion and contraction and has only recently begun slowly narrowing. Although the recent trends indicate declining widths, the back-barrier progradation rates in this area were the highest compared to other time periods, which abated extreme narrowing caused by increased open-ocean shoreline erosion. These data and the interpreted results indicate that both short-term (annual) and long-term (decadal) cross-barrier sediment exchange is a key component of sustaining barrier island width. Therefore, any mechanisms that influence this exchange, whether from natural processes (overwash, breaching, or inlet dynamics) or human activities (development, post-storm recovery, restoration), should be considered when evaluating the long-term sustainability of barrier island systems.

Alabama↗