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At least 1,297 records · Page 72Linked to original sources
USGS1997

Precious metals associated with Late Cretaceous-early Tertiary igneous rocks of southwestern Alaska

Placer gold and precious metal-bearing lode deposits of southwestern Alaska lie within a region 550 by 350 km, herein referred to as the Kuskokwim mineral belt. This mineral belt has yielded 100,240 kg (3.22 Moz) of gold, 12, 813 kg (412,000 oz) of silver, 1,377,412 kg (39,960 flasks) of mercury, and modest amounts of antimony and tungsten derived primarily from the late Cretaceous-early Tertiary igneous complexes of four major types: (1) alkali-calcic, comagmatic volcanic-plutonic complexes and isolated plutons, (2) calc-alkaline, meta-aluminous reduced plutons, (3) peraluminous alaskite or granite-porphyry sills and dike swarms, and (4) andesite-rhyolite subaerial volcanic rocks. About 80 percent of the 77 to 52 Ma intrusive and volcanic rocks intrude or overlie the middle to Upper Cretaceous Kuskokwim Group sedimentary and volcanic rocks, as well as the Paleozoic-Mesozoic rocks of the Nixon Fork, Innoko, Goodnews, and Ruby preaccretionary terranes. The major precious metal-bearing deposit types related to Late Cretaceous-early Tertiary igneous complexes of the Kuskokwim mineral belt are subdivided as follows: (1) plutonic-hosted copper-gold polymetallic stockwork, skarn, and vein deposits, (2) peraluminous granite-porphory-hosted gold polymetallic deposits, (3) plutonic-related, boron-enriched silver-tin polymetallic breccia pipes and replacement deposits, (4) gold and silver mineralization in epithermal systems, and (5) gold polymetallic heavy mineral placer deposits. Ten deposits genetically related to Late Cretaceous-early Tertiary intrusions contain minimum, inferred reserves amounting to 162,572 kg (5.23 Moz) of gold, 201,015 kg (6.46 Moz) silver, 12,160 metric tons (t) of tin, and 28,088 t of copper. The lodes occur in veins, stockworks, breccia pipes, and replacement deposits that formed in epithermal to mesothermal temperature-pressure conditions. Fluid inclusion, isotopic age, mineral assemblage, alteration assemblage, and structural data indicate that many of the mineral deposits associated with Late Cretaceous-early tertiary volcanic and plutonic rocks represent geologically and spatially related, vertically zoned hydrothermal systems now exposed at several erosional levels. Polymetallic gold deposits of the Kuskokwim mineral belt are probably related to 77 to 52 Ma plutonism and volcanism associated with a period of rapid, north-directed subduction of the Kula plate. The geologic interpretation suggests that igneous complexes of the Kuskokwim mineral belt formed in an intracontinental back-arc setting during a period of extensional, wrench fault tectonics. The Kuskokwim mineral belt has many geologic and metallogenic features similar to other precious metal-bearing systems associated with arc-related igneous rocks such as the Late Cretaceous-early Tertiary Rocky Mountain alkalic province, the Jurassic Mount Milligan district of central British Columbia, the Andean orogen of South America, and the Okhotsk-Chukotka belt of northeast Asia.

Alaska↗
USGS2020

A transect through Vermont's most famous volcano - Mount Ascutney

The Cretaceous Ascutney Mountain igneous complex affords a classic exposure of the White Mountain Igneous Suite. Often called Vermont’s most famous volcano, Mount Ascutney (elev. 3,144 feet, 958 m) stands as a prominent monadnock in the Connecticut River Valley. The mountain often serves as an inspirational landmark, as it does when viewed from locations throughout the valley including the Saint-Gaudens National Historic Site (Walsh, 2017). The Ascutney Mountain igneous complex (Ratcliffe and others, 2011) consists of several mafic to felsic nested plutons including gabbro-diorite exposed at Little Ascutney to the west, and the Ascutney Mountain stock composed of syenite, granite, and related volcanic rocks underlying the main summit to the east (Fig. 1) (Schneiderman, 1989, 1991). Foland and Faul (1977) and Foland and others (1985) dated the gabbro-diorite complex at 125.5 to 122.2 Ma by K-Ar on biotite and by whole rock Rb/Sr, and dated the syenite-granite complex at 123.2 to 121.4 Ma by K-Ar on biotite. During the field trip we will visit the host rocks south of the mountain and the main rocks types of the Ascutney Mountain stock exposed near the summit and along the Mount Ascutney toll road. Mount Ascutney is the classic location where Daly (1903) discussed the evidence for piecemeal stoping as a pluton emplacement mechanism. This theory was later modified to favor cauldron subsidence, or ring-fracture stoping, as an alternative mode of emplacement (Chapman and Chapman, 1940). Our new mapping (Walsh and others, in press), which supersedes an earlier provisional study (Walsh and others, 1996a, b), supports the cauldron subsidence model, and shows that the main Ascutney Mountain stock is a funnel shaped composite pluton in agreement with geophysical data (Daniels, 1990). This field guide will primarily highlight the results of the new geologic mapping. This field guide is modified from a field trip presented in 2017 (Walsh, 2017). Additional stops have been added to examine the host rocks in the region south of the Ascutney Mountain stock. Two hikes are planned as part of this trip. Other NEIGC field trip guides to Mount Ascutney include Stoiber (1954) and Schneiderman (1988).

Vermont↗
USGS2019

Introduction: Defining and interpreting ecological disturbances

Within the field of ecology, disturbance can be defined as a physical force, agent, or process, either abiotic or biotic, causing a perturbation or stress, to an ecological component or system, relative to a specified reference state and/or system. Disturbance drive ecosystems, and our understanding of how disturbances interact with biological diversity and scales of space, time, and ecological complexity, have matured over a century of advancement in ecology since early ideas of perturbations and community organization were first formalized. Throughout this book, we approach a set of unifying framing questions for disturbance ecology, including: How can disturbances be categorized in meaningful ways? How do we address scale in disturbance ecology? How does geographic context influence ecological consequences of disturbance, in the near and longer terms? In this introductory chapter, we provide an overview of disturbance ecology and the related topics of diversity and scale that are fundamental to understanding the dynamics of perturbed ecosystems. Subsequently, we outline recent advances in disturbance ecology, which have facilitated greater understanding about dynamic systems and context dependencies. These, in turn, have provided richer insights into the complex manner in which ecosystems change under stress. We survey analytical and methodological advances that are expanding the data flows available to inform disturbance ecology as well as the statistical tools available to investigate disturbance dynamics and ecosystem structure and function. Finally, we lay out four core themes threaded through the remainder of the book: (1) fundamental mechanisms related to ecological theory drive complex system behaviors, including the existence of thresholds; (2) dynamics of ecological disturbance are context-dependent and can be unpredictable; (3) antecedent conditions and the legacies of past disturbances influence contemporary ecosystem dynamics; and (4) natural and anthropogenic disturbances interact in complex ways. Summaries are provided for each of the book’s remaining chapters, highlighting how that material relates to these four core themes. In sum, in this introductory chapter we seek to set a foundation for concepts to ground the remainder of the book. By highlighting constraints in past research and identifying research frontiers, we hope to provide a path forward for advancements in disturbance ecology.

Book chapter↗
USGS2017

Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon

In 1992, Snake River basin fall Chinook salmon (Oncorhynchus tshawytscha) were listed for protection under the U.S. Endangered Species Act (NMFS 1992) and the population remained below 1000 individuals until 2000. Since then, returns from natural production has rebounded to over 20,000 spawners owing to a host of factors including reduced harvest (Peters et al. 2001), stable minimum spawning flows (Groves and Chandler 1999), summer flow augmentation (Connor et al. 2003), predator control (Beamesderfer et al. 1996), hatchery supplementation (Rosenberger et al. 2017), improved juvenile passage structures (Adams et al. 2014), summer spill operations (Perry et al. 2006; Adams et al. 2008), and periods of favorable ocean conditions and food availability (Logerwell et al. 2003; Peterson et al. 2014). Given this change in abundance coincident with numerous management actions and fluctuation in environmental drivers, quantifying which factors contributed to the observed rebound in natural production can provide critical insights into future management actions for this at-risk population. Multistage life cycle models provide a powerful analytical framework for understating how each life stage of a population contributes to population growth rate (Moussalli and Hilborn 1986; Greene and Beechie 2004). Multistage models may also be used as an analytical framework to explicitly estimate demographic parameters of a population model. This approach has an advantage over single-stage stock-recruitment models by allowing population growth rates to be partitioned among life stages rather than aggregated over an entire life cycle. Such partitioning allows for estimating 1) stage-specific density dependence, and 2) stage-specific effects of environmental factors or management actions. For example, Zabel et al. (2006) estimated parameters of a multistage model used in the context of a population viability analysis for spring/summer Chinook salmon in the Snake River, but such an approach has yet to be applied to fall Chinook salmon in the Snake River basin. Typically, data informing estimates of abundance at particular “check points” in the life cycle determines the complexity of the multistage model that can be fit to the data. For fall Chinook salmon, we are developing a two-stage model that encompasses: 1) upstream passage of spawners at Lower Granite Dam (LGR) to the subsequent downstream passage of their progeny at the dam, and 2) downstream passage of juveniles at LGR to their subsequent return from the ocean and passage at the Dam 2‒6 years later. This approach partitions the life cycle of fall Chinook salmon both spatially and temporally, which allows us to fit and compare alternative models with covariates specific to each stage. Our previous report to the ISAB (Zabel et al. 2013) detailed methods for estimating abundance of naturally produced adults and juveniles passing Lower Granite Dam, which provides the requisite data for fitting a two-stage model. The intent of this report is to describe the structure of the two-stage life cycle model, present preliminary results from fitting the model to data, and outline future directions and developments. As is clear from the diversity of models presented in this report, “life cycle models” range from very simple theoretically based population models (e.g., the Beverton-Holt stock- recruitment model) to very complex spatially explicit simulation models linked to hydrosystem hydrodynamic models (e.g., the COMPASS model for a single transition in a life cycle model, Zabel et al. 2008). We chose to develop a model of intermediate complexity that casts the two- stage life cycle model in a state-space framework (Newman et al. 2014). We chose to use a state-space framework implemented in a Bayesian framework because: • It provides both a statistical estimation framework for retrospective statistical analysis and a stochastic simulation framework for prospective analysis to evaluate alternative management actions. • Abundance estimates are uncertain. A state-space framework accounts for observation uncertainty in the abundance estimates and other data (e.g., age structure) while simultaneously estimating process uncertainty. • It allows for missing data. By drawing missing data from an appropriate probability model, uncertainty owing to missing data can be propagated without having to omit data or assume fixed values for missing data. Thus, a two-stage state-space life cycle model for fall Chinook salmon strikes an appropriate balance between model complexity, tractability, and applicability given the goals of performing both retrospective and prospective analysis to guide future management of this population.

Idaho, Oregon, Washington, Wyoming↗
USGS2013

Aftershocks of the 2010 M w 7.2 El Mayor-Cucapah earthquake revealcomplex faulting in the Yuha Desert, California

We detect and precisely locate over 9500 aftershocks that occurred in the Yuha Desert region during a 2 month period following the 4 April 2010 M w 7.2 El Mayor-Cucapah (EMC) earthquake. Events are relocated using a series of absolute and relative relocation procedures that include Hypoinverse, Velest, and hypoDD. Location errors are reduced to ~40 m horizontally and ~120 m vertically.Aftershock locations reveal a complex pattern of faulting with en echelon fault segments trending toward the northwest, approximately parallel to the North American-Pacific plate boundary and en echelon, conjugate features trending to the northeast. The relocated seismicity is highly correlated with published surface mapping of faults that experienced triggered surface slip in response to the EMC main shock. Aftershocks occurred between 2 km and 11 km depths, consistent with previous studies of seismogenic thickness in the region. Three-dimensional analysis reveals individual and intersecting fault planes that are limited in their along-strike length. These fault planes remain distinct structures at depth, indicative of conjugate faulting, and do not appear to coalesce onto a throughgoing fault segment. We observe a complex spatiotemporal migration of aftershocks, with seismicity that jumps between individual fault segments that are active for only a few days to weeks. Aftershock rates are roughly consistent with the expected earthquake production rates of Dieterich (1994). The conjugate pattern of faulting and nonuniform aftershock migration patterns suggest that strain in the Yuha Desert is being accommodated in a complex manner.

California↗
USGS2016

Evaluating geothermal and hydrogeologic controls on regional groundwater temperature distribution

A one-dimensional (1-D) analytic solution is developed for heat transport through an aquifer system where the vertical temperature profile in the aquifer is nearly uniform. The general anisotropic form of the viscous heat generation term is developed for use in groundwater flow simulations. The 1-D solution is extended to more complex geometries by solving the equation for piece-wise linear or uniform properties and boundary conditions. A moderately complex example, the Eastern Snake River Plain (ESRP), is analyzed to demonstrate the use of the analytic solution for identifying important physical processes. For example, it is shown that viscous heating is variably important and that heat conduction to the land surface is a primary control on the distribution of aquifer and spring temperatures. Use of published values for all aquifer and thermal properties results in a reasonable match between simulated and measured groundwater temperatures over most of the 300 km length of the ESRP, except for geothermal heat flow into the base of the aquifer within 20 km of the Yellowstone hotspot. Previous basal heat flow measurements (∼110 mW/m 2 ) made beneath the ESRP aquifer were collected at distances of >50 km from the Yellowstone Plateau, but a higher basal heat flow of 150 mW/m 2 is required to match groundwater temperatures near the Plateau. The ESRP example demonstrates how the new tool can be used during preliminary analysis of a groundwater system, allowing efficient identification of the important physical processes that must be represented during more-complex 2-D and 3-D simulations of combined groundwater and heat flow.

Idaho↗
USGS2018

Combining InSAR and GPS to determine transient movement and thickness of a seasonally active low-gradient translational landslide

The combined application of continuous Global Positioning System data (high temporal resolution) with spaceborne interferometric synthetic aperture radar data (high spatial resolution) can reveal much more about the complexity of large landslide movement than is possible with geodetic measurements tied to only a few specific measurement sites. This approach is applied to an ~4 km 2 reactivated translational landslide in the Columbia River Gorge (Washington State), which moves mainly during the winter rainy season. Results reveal the complex three-dimensional shape of the landslide mass, how onset of sliding relates to cumulative rainfall, how surface velocity during sliding varies with location on the topographically complex landslide surface, and how the ground surface subsides slightly in weeks prior to downslope sliding.

Geophysical Research Letters↗
USGS2016

Surficial geological tools in fluvial geomorphology: Chapter 2

Increasingly, environmental scientists are being asked to develop an understanding of how rivers and streams have been altered by environmental stresses, whether rivers are subject to physical or chemical hazards, how they can be restored, and how they will respond to future environmental change. These questions present substantive challenges to the discipline of fluvial geomorphology, especially since decades of geomorphologic research have demonstrated the general complexity of fluvial systems. It follows from the concept of complex response that synoptic and short-term historical views of rivers will often give misleading understanding of future behavior. Nevertheless, broadly trained geomorphologists can address questions involving complex natural systems by drawing from a tool box that commonly includes the principles and methods of geology, hydrology, hydraulics, engineering, and ecology.

Book chapter↗
USGS2019

Spatially explicit network analysis reveals multi-species annual cycle movement patterns of sea ducks

Conservation of long-distance migratory species poses unique challenges. Migratory connectivity—that is, the extent to which groupings of individuals at breeding sites are maintained in wintering areas—is frequently used to evaluate population structure and assess use of key habitat areas. However, for species with complex or variable annual-cycle movements, this traditional bimodal framework of migratory connectivity may be overly simplistic. Like many other waterfowl, sea ducks often travel to specific pre- and post-breeding sites outside their nesting and wintering areas to prepare for migration and, in some cases, molt their flight feathers. These additional molt migrations may play a key role in population structure, but are not included in traditional models of migratory connectivity. Network analysis, which applies graph theory to assess landscape connectivity, offers a powerful tool for quantitatively assessing the contributions of different sites used throughout the annual cycle to complex spatial networks. We collected satellite telemetry data on annual cycle movements of over 500 individual sea ducks of five species from throughout eastern North America and the Great Lakes. From these data, we constructed a multi-species network model of migratory patterns and site use over the course of the breeding, molting, wintering, and migration periods. Our results highlight inter- and intra-specific differences in the patterns and complexity of annual-cycle movement patterns, including the central importance of staging and molting sites in James Bay and the St. Lawrence River to multi-species habitat connectivity. We also discuss potential applications of network migration models to conservation prioritization, identification of population units, and integrating different data streams.

Ecological Applications↗
USGS2023

A big data–model integration approach for predicting epizootics and population recovery in a keystone species

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus ) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally >0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host–pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data–model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.

Arizona, Colorado, Kansas, Montana, Nebraska, New ↗
USGS2018

A method to detect discontinuities in census data

The distribution of pattern across scales has predictive power in the analysis of complex systems. Discontinuity approaches remain a fruitful avenue of research in the quest for quantitative measures of resilience because discontinuity analysis provides an objective means of identifying scales in complex systems and facilitates delineation of hierarchical patterns in processes, structure, and resources. However, current discontinuity methods have been considered too subjective, too complicated and opaque, or have become computationally obsolete; given the ubiquity of discontinuities in ecological and other complex systems, a simple and transparent method for detection is needed. In this study, we present a method to detect discontinuities in census data based on resampling of a neutral model and provide the R code used to run the analyses. This method has the potential for advancing basic and applied ecological research.

Ecology and Evolution↗
USGS2016

The statistical power to detect cross-scale interactions at macroscales

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Ecosphere↗
USGS2017

The value of information for woodland management: Updating a state–transition model

Value of information (VOI) analyses reveal the expected benefit of reducing uncertainty to a decision maker. Most ecological VOI analyses have focused on population models rarely addressing more complex community models. We performed a VOI analysis for a complex state–transition model of Box-Ironbark Forest and Woodland management. With three management alternatives (limited harvest/firewood removal (HF), ecological thinning (ET), and no management), managing the system optimally (for 150 yr) with the original information would, on average, increase the amount of forest in a desirable state from 19% to 35% (a 16-percentage point increase). Resolving all uncertainty would, on average, increase the final percentage to 42% (a 19-percentage point increase). However, only resolving the uncertainty for a single parameter was worth almost two-thirds the value of resolving all uncertainty. We found the VOI to depend on the number of management options, increasing as the management flexibility increased. Our analyses show it is more cost-effective to monitor low-density regrowth forest than other states and more cost-effective to experiment with the no-management alternative than the other management alternatives. Importantly, the most cost-effective strategies did not include either the most desired forest states or the least understood management strategy, ET. This implies that managers cannot just rely on intuition to tell them where the most VOI will lie, as critical uncertainties in a complex system are sometimes cryptic.

Victoria↗
USGS2020

Is your ad hoc model selection strategy affecting your multimodel inference?

(Yackulic) 1. Ecologists routinely fit complex models with multiple parameters of interest, where hundreds or more competing models are plausible. To limit the number of fitted models, ecologists often define a model selection strategy composed of a series of stages in which certain features of a model are compared while other features are held constant. Defining these multi-stage strategies requires making a series of decisions, which may potentially impact inferences, but have not been critically evaluated. 2. We begin by identifying key features of strategies, introducing descriptive terms when they did not already exist in the literature. Strategies differ in how they define and order model building stages. Sequential-by-sub-model strategies focus on one sub-model (parameter) at a time with modeling of subsequent sub-models dependent on the selected model structures from the previous stages. Secondary candidate set strategies model sub-models independently and combine the top set of models from each sub-model for selection in a final stage. Build-up approaches define stages across sub-models and increase in complexity at each stage. Strategies also differ in how the top set of models is selected in each stage and whether they use null or more complex model structures for non-target sub-models. 3. We tested the performance of different model selection strategies using four datasets and three model types. For each dataset, we determined the “true” distribution of AIC weights by fitting all plausible models. Then, we calculated the number of models that would have been fitted and the portion of “true” AIC weight we recovered under different model selection strategies. 4. Sequential-by-sub-model strategies often performed poorly. Build-up or secondary candidate sets were more reliable, provided all models within 5 AIC of the top model were carried forward to subsequent stages. The structure of non-target sub-models was less important. 5. Multi-stage approaches cannot compensate for a lack of critical thought in selecting covariates and building models to represent competing a priori hypotheses. However, even when competing hypotheses for different sub-models are limited, thousands or more models may be possible so strategies to explore candidate model space reliably and efficiently will be necessary.

Ecosphere↗
USGS2005

Development of partial rock veneers by root throw in a subalpine setting

Rock veneers stabilize hillslope surfaces, occur especially in areas of immature soil, and form through a variety of process sets that includes root throw. Near Westcliffe, Colorado, USA, data were collected from a 20 ?? 500 m transect on the east slope of the Sangre de Cristo Mountains. Ages of pit/mound complexes with rock fragments exposed at the surface by root throw ranged from recent (freshly toppled tree) to unknown (complete tree decay). Calculations based on dimensions of the pit/mound complexes, estimated time of free topppling, sizes of exposed rock fragments, and percentage rock covers at pit/mound complexes, as well as within the transect area, indicate that recent rates of root throw have resulted in only partial rock veneering since late Pleistocene deglaciation. Weathering of rock fragments prevent development of an extensive rock veneer and causes a balance, achieved within an estimated 700 years, between the rates of rock-fragment exposure by root throw and clast disintegration by chemical reduction. The estimated rate of rock-fragment reduction accounts for part of the fluvial sediment yields observed for forested subalpine areas of western North America. Copyright ?? 2005 John Wiley & Sons, Ltd.

Earth Surface Processes and Landforms↗
USGS2021

Relative effectiveness of D-Frame dip nets, quatrefoil light traps, and towed ichthyoplankton nets for larval Muskellunge

Muskellunge Esox masquinongy are large, predatory game fish whose association with shallow, complex habitats is well documented, particularly during early life stages. Despite this association, relatively little guidance exists regarding effective sampling of Muskellunge larvae and previous efforts to sample larval Muskellunge have been met with limited success. Therefore, our objective was to determine the relative effectiveness of three sampling gears for capturing naturally produced Muskellunge larvae. Larvae were sampled during 2019 and 2020 at known Muskellunge spawning locations in Snipe Lake, Wisconsin, with D-frame dip nets (1,000-µm mesh), quatrefoil light traps, and towed ichthyoplankton nets (1,000-µm mesh). Sixty larval Muskellunge were captured across all gears, and catches in D-frame dip nets comprised nearly 87% (52 of 60) of the total catch. Furthermore, D-frame dip nets captured the broadest size range of larval Muskellunge (TL range = 14–33 mm). Greater effectiveness of D-frame dip nets in comparison with other gears is likely related to their ability to be used in and around structurally complex habitats without fouling or clogging. Our results suggest that D-frame dip nets should be considered as a cost- and time-effective tool for targeting larval Muskellunge in complex habitats.

Wisconsin↗
USGS2024

Wood you believe it? Experimental addition of nonnative wood enhances instream habitat for native dryland fishes

Flow alteration and riparian vegetation encroachment are causing habitat simplification with severe consequences for native fishes. To assess the effectiveness of enhancing simplified habitat in a large dryland river, we experimentally added invasive wood at 19 paired treatment and reference (no wood added) subreaches (50–100 m) within the main channel of the San Juan River. Using a before-after-control-impact design, we sampled fishes and macroinvertebrates, and quantified habitat complexity. After wood addition, total native fish densities were 2.2× higher in treatments compared with references, whereas total nonnative fish densities exhibited no response. Macroinvertebrate densities were 6.8× higher, and habitat complexity increased in treatments. Counts of geomorphic features in treatments increased from 1 to a maximum of 11 following wood addition, while the number of features in references remained unchanged. Wood addition has potential to instigate natural riverine processes, ultimately enhancing native fish habitat by increasing macroinvertebrate densities and habitat complexity in dryland rivers. Water overallocation and increasing aridity will continue to challenge efforts to improve habitat conditions with environmental flows alone, and managers might consider integrating non-flow alternatives like addition of abundant, invasive wood to reduce habitat simplification.

New Mexico, Utah↗
USGS2024

Effects of 2D hydrodynamic model resolution on habitat estimates for rearing Coho Salmon in contrasting channel forms

Estimating the impacts of water allocation decisions on fish populations and habitat availability is an important part of environmental flow assessments, especially in locations where water resources are limited. Two-dimensional hydrodynamic models (2DHMs) are commonly coupled with biological models to estimate fish habitat quality, area, and capacity across a range of proposed streamflows. Increasingly, resource managers are relying on landscape-scale model domains with coarse model resolutions to maintain feasible computational loads, but this may affect habitat estimates if the mesh element size of the model exceeds the spatial scale relevant to the organism. We investigated how coarsening the resolution of a 2DHM influences the area and spatial distribution of estimated Coho Salmon ( Oncorhynchus kisutch ) fry habitats. We used an interpolation scheme that upscaled mesh elements from a high-resolution (0.25 m 2 ) 2DHM to quantify and visualize the effects of 2DHM resolution on estimates of Coho Salmon fry habitat for two contrasting channel morphologies and across a broad range of streamflows. Estimates of Coho Salmon fry habitat at increasingly coarser resolutions led to 20%–50% reductions in weighted usable habitat area (WUA) across several streamflow scenarios for a complex channel type, but did not impact estimates in a confined, flume-like channel. Additionally, flow-to-habitat area relationships were not congruent at a given streamflow when resolution coarsened. Along with almost 500% more high-quality habitat area estimated in the complex channel type over the confined, discrepancies in habitat area increased with higher flows in areas defined as optimal for rearing Coho Salmon fry. Considering that complex channel types contain critical habitat for Coho Salmon fry, this study suggests coarse 2DHM resolutions may exclude important wetted edge and off-channel habitats from environmental flow assessments.

California↗