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At least 721 records · Page 40Linked to original sources
USGS2024

Unexpected effect of geographic origin on post-translocation survival in a long-lived reptile, the gopher tortoise

Mitigation translocations move wildlife from specific areas due to conflict with humans over land use at the site. A critical decision when carrying out mitigation translocation is the acceptable distance across which animals can be moved. This decision trades off logistical expediency of unrestricted translocation with the risk of reducing translocation success due to environmental mismatch between origin and translocation site conditions. In this study, we used a large dataset of 502 individually identifiable carcasses to examine the role of geographic origin and translocation distance in the relative survival of 2822 translocated subadult and adult gopher tortoises ( Gopherus polyphemus ), a species experiencing large-scale mitigation translocation, at a recipient site in the Florida panhandle, USA. We hypothesized that if climate or habitat differences between the origin and translocation site influenced survival, tortoises translocated from within the Florida panhandle would have the highest survival. To the contrary, we found that survival slightly increased with increasing climatic difference between origin and recipient site, driven by higher survival of tortoises coming from central Florida sites compared to those from the panhandle and north Florida. This suggests that environmental mismatch due to long-distance translocation is not a main driver of mortality. These models also indicated an effect of season, with a survival advantage to tortoises translocated in the spring and late fall, relative to summer translocations, and a negative effect of initial density on survival. Finally, we also estimated the upper bound on annual survival in three well-monitored groups to be quite low (92–95%) for several years following release, suggesting caution when considering large translocated populations to be viable without first assessing adult survival. Our unexpected results highlight the importance of investigating species-specific sensitivities to translocation distances and indicate the limitations of assumed linear effects of translocation distance on outcomes.

Florida↗
USGS2023

Crop water productivity from cloud-Based landsat helps assess California’s water savings

Demand for food and water are increasing while the extent of arable land and accessible fresh water are decreasing. This poses global challenges as economies continue to develop and the population grows. With agriculture as the leading consumer of water, better understanding how water is used to produce food may help support the increase of Crop Water Productivity (CWP; kg/m 3 ), the ratio of crop output per unit of water input (or crop per drop). Previous large-scale CWP studies have been useful for broad water use modeling at coarser resolutions. However, obtaining more precise CWP, especially for specific crop types in a particular area and growing season as outlined here are important for informing farm-scale water management decision making. Therefore, this study focused on California’s Central Valley utilizing high-spatial resolution satellite imagery of 30 m (0.09 hectares per pixel) to generate more precise CWP for commonly grown and water-intensive irrigated crops. First, two products were modeled and mapped. 1. Landsat based Actual Evapotranspiration (ET a ; mm/d) to determine Crop Water Use (CWU; m 3 /m 2 ), and 2. Crop Productivity (CP; kg/m 2 ) to estimate crop yield per growing season. Then, CWP was calculated by dividing CP by CWU and mapped. The amount of water that can be saved by increasing CWP of each crop was further calculated. For example, in the 434 million m 2 study area, a 10% increase in CWP across the 9 crops analyzed had a potential water savings of 31.5 million m 3 of water. An increase in CWP is widely considered the best approach for saving maximum quantities of water. This paper proposed, developed, and implemented a workflow of combined methods utilizing cloud computing based remote sensing data. The environmental implications of this work in assessing water savings for food and water security in the 21st century are expected to be significant.

California↗
USGS2013

Assessing factors affecting the thermal properties of a passive thermal refuge using three-dimensional hydrodynamic flow and transport modeling

Everglades restoration activities may cause changes to temperature and salinity stratification at the Port of the Islands (POI) marina, which could affect its suitability as a cold weather refuge for manatees. To better understand how the Picayune Strand Restoration Project (PSRP) may alter this important resource in Collier County in southwestern Florida, the USGS has developed a three-dimensional hydrodynamic model for the marina and canal system at POI. Empirical data suggest that manatees aggregate at the site during winter because of thermal inversions that provide warmer water near the bottom that appears to only occur in the presence of salinity stratification. To study these phenomena, the environmental fluid dynamics code simulator was used to represent temperature and salinity transport within POI. Boundary inputs were generated using a larger two-dimensional model constructed with the flow and transport in a linked overland-aquifer density-dependent system simulator. Model results for a representative winter period match observed trends in salinity and temperature fluctuations and produce temperature inversions similar to observed values. Modified boundary conditions, representing proposed PSRP alterations, were also tested to examine the possible effect on the salinity stratification and temperature inversion within POI. Results show that during some periods, salinity stratification is reduced resulting in a subsequent reduction in temperature inversion compared with the existing conditions simulation. This may have an effect on POI’s suitability as a passive thermal refuge for manatees and other temperature-sensitive species. Additional testing was completed to determine the important physical relationships affecting POI’s suitability as a refuge.

Florida↗
USGS2016

Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk

The home‐range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home‐range model that can accommodate multiple home‐range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home‐range centers and move among them with some estimable probability. Movement in and around home‐range centers is governed by a two‐dimensional Ornstein‐Uhlenbeck process, while transitions between centers are modeled as a stochastic state‐switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home‐range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters ( Enhydra lutris ) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein‐Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home‐range centers. Females were less likely to move between home‐range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful behavioral insight from complex movement data.

Ecology↗
USGS2023

No evidence for cottonwood forest decline along a flow-augmented western U.S. river

In contrast to many other arid region rivers, streamflow in the South Platte River is heavily augmented by trans-basin water imports and irrigation return flows. Hydrological changes began in the 1880s, resulting in channel narrowing and the development of a continuous Populus-Salix forest by the mid-twentieth century. We assessed the composition, structure and regeneration status of the riparian forest and identified environmental variables affecting annual Populus deltoides tree growth. We sampled forest structure at four sites in 2015, and conducted dendroecological analysis at seven additional sites in 2019. The riparian forest was dominated by P. deltoides , which occurred at all sites, comprising 79% of total tree basal area and 62% of total tree density. Age structure data indicated ongoing though episodic recruitment of P. deltoides , at least over the past ~130 years. We tested 14 linear mixed effects models to describe the effect of climate and streamflow on individual tree growth (modeled as the log of BAI, n = 237 trees). The most parsimonious model selected with AICc explained 28.6% of BAI variability, and included hydrology and climate factors during the growing season (i.e., June–August streamflow, June–July PDSI), some aspects of off-season (i.e., previous November and March) streamflow, along with tree age and study site effects. The riparian forest developed in response to, and has been maintained by, current climate conditions and water management regimes. It may be negatively affected by future climate change and increased urban water demand in the basin.

Colorado↗
USGS2013

A comparison of data-driven groundwater vulnerability assessment methods

Increasing availability of geo-environmental data has promoted the use of statistical methods to assess groundwater vulnerability. Nitrate is a widespread anthropogenic contaminant in groundwater and its occurrence can be used to identify aquifer settings vulnerable to contamination. In this study, multivariate Weights of Evidence (WofE) and Logistic Regression (LR) methods, where the response variable is binary, were used to evaluate the role and importance of a number of explanatory variables associated with nitrate sources and occurrence in groundwater in the Milan District (central part of the Po Plain, Italy). The results of these models have been used to map the spatial variation of groundwater vulnerability to nitrate in the region, and we compare the similarities and differences of their spatial patterns and associated explanatory variables. We modify the standard WofE method used in previous groundwater vulnerability studies to a form analogous to that used in LR; this provides a framework to compare the results of both models and reduces the effect of sampling bias on the results of the standard WofE model. In addition, a nonlinear Generalized Additive Model has been used to extend the LR analysis. Both approaches improved discrimination of the standard WofE and LR models, as measured by the c -statistic. Groundwater vulnerability probability outputs, based on rank-order classification of the respective model results, were similar in spatial patterns and identified similar strong explanatory variables associated with nitrate source (population density as a proxy for sewage systems and septic sources) and nitrate occurrence (groundwater depth).

Milan District↗
USGS2014

Polar bears from space: Assessing satellite imagery as a tool to track Arctic wildlife

Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark- recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.

PLoS ONE↗
USGS2011

Spatial distribution and risk factors of highly pathogenic avian influenza (HPAI) H5N1 in China

Highly pathogenic avian influenza (HPAI) H5N1 was first encountered in 1996 in Guangdong province (China) and started spreading throughout Asia and the western Palearctic in 2004–2006. Compared to several other countries where the HPAI H5N1 distribution has been studied in some detail, little is known about the environmental correlates of the HPAI H5N1 distribution in China. HPAI H5N1 clinical disease outbreaks, and HPAI virus (HPAIV) H5N1 isolated from active risk-based surveillance sampling of domestic poultry (referred to as HPAIV H5N1 surveillance positives in this manuscript) were modeled separately using seven risk variables: chicken, domestic waterfowl population density, proportion of land covered by rice or surface water, cropping intensity, elevation, and human population density. We used bootstrapped logistic regression and boosted regression trees (BRT) with cross-validation to identify the weight of each variable, to assess the predictive power of the models, and to map the distribution of HPAI H5N1 risk. HPAI H5N1 clinical disease outbreak occurrence in domestic poultry was mainly associated with chicken density, human population density, and elevation. In contrast, HPAIV H5N1 infection identified by risk-based surveillance was associated with domestic waterfowl density, human population density, and the proportion of land covered by surface water. Both models had a high explanatory power (mean AUC ranging from 0.864 to 0.967). The map of HPAIV H5N1 risk distribution based on active surveillance data emphasized areas south of the Yangtze River, while the distribution of reported outbreak risk extended further North, where the density of poultry and humans is higher. We quantified the statistical association between HPAI H5N1 outbreak, HPAIV distribution and post-vaccination levels of seropositivity (percentage of effective post-vaccination seroconversion in vaccinated birds) and found that provinces with either outbreaks or HPAIV H5N1 surveillance positives in 2007–2009 appeared to have had lower antibody response to vaccination. The distribution of HPAI H5N1 risk in China appears more limited geographically than previously assessed, offering prospects for better targeted surveillance and control interventions.

PLoS Pathogens↗
USGS2011

Migration delays caused by anthropogenic barriers: modeling dams, temperature, and success on migrating salmon smolts

Disruption to migration is a growing problem for conservation and restoration of animal populations. Anthropogenic barriers along migration paths can delay or prolong migrations, which may result in a mismatch with migration-timing adaptations. To understand the interaction of dams (as barriers along a migration path), seasonally changing environmental conditions, timing of Atlantic salmon ( Salmo salar ) downstream migration, and ultimate migration success, we used 10 years of river temperature and discharge data as a template upon which we simulated downstream movement of salmon. Atlantic salmon is a cool-water species whose downstream migrating smolts must complete migration before river temperatures become too warm. We found that dams had a local effect on survival as well as a survival effect that was spatially and temporally removed from the encounter with the dam. While smolts are delayed by dams, temperatures downstream can reach lethal or near-lethal temperatures; as a result, the match between completion of migration and the window of appropriate migration conditions can be disrupted. The strength of this spatially and temporally removed effect is at least comparable to the local effects of dams in determining smolt migration success in the presence of dams. We also considered smolts from different tributaries, varying in distance from the river mouth, to assess the potential importance of locally adapted migration timing on the effect of barriers. Migration-initiation temperature affected modeled smolt survival differentially across tributaries, with the success of smolts from upstream tributaries being much more variable across years than that of smolts with a shorter distance to travel. As a whole, these results point to the importance of broadening our spatial and temporal view when managing migrating populations. We must consider not only how many individuals never make it across migration barriers, but also the spatially and temporally removed consequences of delays at the barriers for those individuals that successfully navigate them.

Ecological Applications↗
USGS2013

Empirical estimates to reduce modeling uncertainties of soil organic carbon in permafrost regions: a review of recent progress and remaining challenges

The vast amount of organic carbon (OC) stored in soils of the northern circumpolar permafrost region is a potentially vulnerable component of the global carbon cycle. However, estimates of the quantity, decomposability, and combustibility of OC contained in permafrost-region soils remain highly uncertain, thereby limiting our ability to predict the release of greenhouse gases due to permafrost thawing. Substantial differences exist between empirical and modeling estimates of the quantity and distribution of permafrost-region soil OC, which contribute to large uncertainties in predictions of carbon–climate feedbacks under future warming. Here, we identify research challenges that constrain current assessments of the distribution and potential decomposability of soil OC stocks in the northern permafrost region and suggest priorities for future empirical and modeling studies to address these challenges.

Environmental Research Letters↗
USGS2020

Do empirical observations support commonly-held climate change range shift hypotheses? A systematic review protocol

Background Among the most widely anticipated climate-related impacts to biodiversity are geographic range shifts, whereby species shift their spatial distribution in response to changing climate conditions. In particular, a series of commonly articulated hypotheses have emerged: species are expected to shift their distributions to higher latitudes, greater elevations, and deeper depths in response to climate change, reflecting an underlying hypothesis that species will move to cooler locations to track spatial changes in the temperature of their current range. Yet, many species are not demonstrating range shifts consistent with these hypotheses. Resolving this discrepancy and providing effective explanations for the observed variability in species’ range shifts is urgently needed to help support a range of natural resource management decisions. Here, we propose a protocol to review the body of evidence for commonly-held climate change range shift hypotheses at the species level focusing on observed latitudinal, longitudinal, elevational, and depth shifts in response to temperature and precipitation changes. We aim to answer the question: what is the impact of anthropogenic climate change (specifically changes in temperature and precipitation) on species ranges? Methods In this review protocol, we propose to conduct a systematic search of literature from internet databases and search engines in English. Articles will be screened in a two-stage process (title/abstract and full text) to evaluate whether they meet a list of eligibility criteria (e.g., presents species-level data, compares >1 time period). Initial data coding and extraction will be completed by four reviewers and checked by a secondary reviewer from among our co-authors. We will perform a formal meta-analysis to document estimated effect size using the subset of available range-shift data expressed in distance per time (e.g., km/decade). We will also use multinomial logistic regression models to assess the probability that species are shifting in a direction that supports our hypotheses (i.e. towards higher latitudes, greater elevations, and deeper depths). We will account for study methodology as a potential source of variation.

Environmental Evidence↗
USGS2019

Negative frequency-dependent foraging behaviour in a generalist herbivore (Alces alces) and its stabilizing influence on food-web dynamics

1. Resource selection is widely appreciated to be context‐dependent and shaped by both biological and abiotic factors. However, few studies have empirically assessed the extent to which selective foraging behaviour is dynamic and varies in response to environmental conditions for free‐ranging animal populations. 2. Here, we assessed the extent that forage selection fluctuated in response to different environmental conditions for a free‐ranging herbivore, moose (Alces alces), in Isle Royale National Park, over a 10‐year period. More precisely, we assessed how moose selection for coniferous versus deciduous forage in winter varied between geographic regions and in relation to (a) the relative frequency of forage types in the environment (e.g. frequency‐dependent foraging behaviour), (b) moose abundance, (c) predation rate (by grey wolves) and (d) snow depth. These factors are potentially important for their influence on the energetics of foraging. We also built a series of food‐chain models to assess the influence of dynamic foraging strategies on the stability of food webs. 3. Our analysis indicates that moose exhibited negative frequency dependence, by selectively exploiting rare resources. Frequency‐dependent foraging was further mediated by density‐dependent processes, which are likely to be predation, moose abundance or some combination of both. In particular, frequency dependence was weaker in years when predation risk was high (i.e. when the ratio of moose to wolves was relatively low). Selection for conifers was also slightly weaker during deep snow years. 4. The food‐chain analysis indicates that the type of frequency‐dependent foraging strategy exhibited by herbivores had important consequences for the stability of ecological communities. In particular, the dynamic foraging strategy that we observed in the empirical analysis (i.e. negative frequency dependence being mediated by density‐dependent processes) was associated with more stable food web dynamics compared to fixed foraging strategies. 5. The results of this study indicated that forage selection is a complex ecological process, varying in response to both biological (predation and moose density) and abiotic factors (snow depth) and over relatively small spatial scales (between regions). This study also provides a useful framework for assessing the influence of other aspects of foraging behaviour on the stability of food web dynamics.

Michigan↗
USGS2024

The 3D Elevation Program—Supporting New Hampshire’s economy

Introduction The topography of New Hampshire ranges from the Coastal Lowlands to the Eastern New England Upland to the White Mountains region. High-quality statewide elevation data are useful in managing this very diverse landscape. For example, the short coastline, including the Great Bay estuary and the Hampton-Seabrook marshes, is of disproportionately high value to New Hampshire’s tourist economy. The vulnerability of the coast to the effects of sea-level rise underscores the need for accurate, high-quality nearshore topographic elevation data and offshore bathymetric data to effectively manage the coast’s valuable resources, which include important fisheries, habitat, and infrastructure. Another important use for accurate elevation data in New Hampshire is in the evaluation of flood hazards and their potential environmental and infrastructure effects. This evaluation includes mapping of inundation and sediment transport, and assessing the associated costs of flooding. Addressing this challenge requires detailed knowledge of both surface topography and inland bathymetry. Other important activities having a substantial economic element and needing accurate elevation data include geologic resource assessment and hazard mitigation, urban and regional planning, infrastructure and construction management, and cultural resources preservation and management. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional model of the Earth’s surface and aboveground features.

New Hampshire↗
USGS2002

Visualization of Flow Alternatives, Lower Missouri River

Background The U.S. Army Corps of Engineers (COE) 'Missouri River Master Water Control Manual' (Master Manual) review has resulted in consideration of many flow alternatives for managing the water in the river (COE, 2001; 1998a). The purpose of this report is to present flow-management alternative model results in a way that can be easily visualized and understood. This report was updated in October 2001 to focus on the specific flow-management alternatives presented by the COE in the 'Master Manual Revised Draft Environmental Impact Statement' (RDEIS; COE, 2001). The original version (February 2000) is available by clicking here. The COE, U.S. Fish and Wildlife Service (FWS), Missouri River states, and Missouri River basin tribes have been participating in discussions concerning water management of the Missouri River mainstem reservoir system (MRMRS), the Missouri River Bank Stabilization and Navigation Project, and the Kansas River reservoir system since 1986. These discussions include general input to the revision of the Master Manual as well as formal consultation under Section 7 of the Endangered Species Act. In 2000, the FWS issued a Biological Opinion that prescribed changes to reservoir management on the Missouri River that were believed to be necessary to preclude jeopardy to three endangered species, the pallid sturgeon, piping plover, and interior least tern (USFWS, 2000). The combined Missouri River system is large and complex, including many reservoirs, control structures, and free-flowing reaches extending over a broad region. The ability to assess future impacts of altered management scenarios necessarily involves complex, computational models that attempt to integrate physical, chemical, biological, and economic effects. Graphical visualization of the model output is intended to improve understanding of the differences among flow-management alternatives.

Colorado, Iowa, Kansas, Missouri, Montana, Nebrask↗
USGS1989

Terrestrial population models for ecological risk assessment: A state-of-the-art review

Few attempts have been made to formulate models for predicting impacts of xenobiotic chemicals on wildlife populations. However, considerable effort has been invested in wildlife optimal exploitation models. Because death from intoxication has a similar effect on population dynamics as death by harvesting, these management models are applicable to ecological risk assessment. An underlying Leslie-matrix bookkeeping formulation is widely applicable to vertebrate wildlife populations. Unfortunately, however, the various submodels that track birth, death, and dispersal rates as functions of the physical, chemical, and biotic environment are by their nature almost inevitably highly species- and locale-specific. Short-term prediction of one-time chemical applications requires only information on mortality before and after contamination. In such cases a simple matrix formulation may be adequate for risk assessment. But generally, risk must be projected over periods of a generation or more. This precludes generic protocols for risk assessment and also the ready and inexpensive predictions of a chemical's influence on a given population. When designing and applying models for ecological risk assessment at the population level, the endpoints (output) of concern must be carefully and rigorously defined. The most easily accessible and appropriate endpoints are (1) pseudoextinction (the frequency or probability of a population falling below a prespecified density), and (2) temporal mean population density. Spatial and temporal extent of predicted changes must be clearly specified a priori to avoid apparent contradictions and confusion.

Environmental Toxicology and Chemistry↗
USGS2018

Quantifying the visual-sensory landscape qualities that contribute to cultural ecosystem services using social media and LiDAR

Landscapes are increasingly recognized for providing valuable cultural ecosystem services with numer- ous non-material benefits by serving as places of rest, relaxation, and inspiration that ultimately improve overall mental health and physical well-being. Maintaining and enhancing these valuable benefits through targeted management and conservation measures requires understanding the spatial and tem- poral determinants of perceived landscape values. Content contributed through mobile technologies and the web are emerging globally, providing a promising data source for localizing and assessing these land- scape benefits. These georeferenced data offer rich in situ qualitative information through photos and comments that capture valued and special locations across large geographic areas. We present a novel method for mapping and modeling landscape values and perceptions that leverages viewshed analysis of georeferenced social media data. Using a high resolution LiDAR (Light Detection and Ranging) derived digital surface model, we are able to evaluate landscape characteristics associated with the visual- sensory qualities of outdoor recreationalists. Our results show the importance of historical monuments and attractions in addition to specific environmental features which are appreciated by the public. Evaluation of photo-image content highlights the opportunity of including temporally and spatially vari- able visual-sensory qualities in cultural ecosystem services (CES) evaluation like the sights, sounds and smells of wildlife and weather phenomena.

North Carolina↗
USGS2011

The USA National Phenology Network; taking the pulse of our planet

People have tracked phenology for centuries and for the most practical reasons: it helped them know when to hunt and fish, when to plant and harvest crops, and when to navigate waterways. Now phenology is being used as a tool to assess climate change and its effects on both natural and modified ecosystems. How is the timing of events in plant and animal life cycles, like flowering or migration, responding to climate change? And how are those responses, in turn, affecting people and ecosystems? The USA National Phenology Network (the Network) is working to answer these questions for science and society by promoting a broad understanding of plant and animal phenology and their relationship to environmental change. The Network is a consortium of organizations and individuals that collect, share, and use phenology data, models, and related information to enable scientists, resource managers, and the public to adapt in response to changing climates and environments. In addition, the Network encourages people of all ages and backgrounds to observe and record phenology as a way to discover and explore the nature and pace of our dynamic world. The National Coordinating Office (NCO) of the Network is a resource center that facilitates and encourages widespread collection, integration, and sharing of phenology data and related information (for example, meteorological and hydrological data). The NCO develops and promotes standardized methods for field data collection and maintains several online user interfaces for data upload and download, as well as data exploration, visualization, and analysis. The NCO also facilitates basic and applied research related to phenology, the development of decision-support tools for resource managers and planners, and the design of educational and outreach materials

Fact Sheet↗
USGS2013

Review of a model to assess stranding of juvenile salmon by ship wakes along the Lower Columbia River, Oregon and Washington

Long period wake waves from deep draft vessels have been shown to strand small fish, particularly juvenile Chinook salmon Oncorhynchus tschawytcha, in the lower Columbia River (LCR). The U.S. Army Corps of Engineers is responsible for maintaining the shipping channel in the LCR and recently conducted dredging operations to deepen the shipping channel from an authorized depth of 40 feet(ft) to an authorized depth of 43 ft (in areas where rapid shoaling was expected, dredging operations were used to increase the channel depth to 48 ft). A model was developed to estimate stranding probabilities for juvenile salmon under the 40- and 43-ft channel scenarios, to determine if channel deepening was going to affect wake stranding (Assessment of potential stranding of juvenile salmon by ship wakes along the Lower Columbia River under scenarios of ship traffic and channel depth: Report prepared for the Portland District U.S. Army Corps of Engineers, Portland, Oregon). The U.S. Army Corps of Engineers funded the U.S. Geological Survey to review this model. A total of 30 review questions were provided to guide the review process, and these questions are addressed in this report. In general, we determined that the analyses by Pearson (2011) were appropriate given the data available. We did identify two areas where additional information could have been provided: (1) a more thorough description of model diagnostics and model selection would have been useful for the reader to better understand the model framework; and (2) model uncertainty should have been explicitly described and reported in the document. Stranding probability estimates between the 40- and 43-ft channel depths were minimally different under most of the scenarios that were examined by Pearson (2011), and a discussion of the effects of uncertainty given these minimal differences would have been useful. Ultimately, however, a stochastic (or simulation) model would provide the best opportunity to illustrate uncertainty within a given set of model predictions, but such an approach would require a substantial amount of additional data collection. Several review questions focused on the accuracy and precision of the model estimates, but we were unable to address these questions because of the limited data that currently exists regarding wake stranding in the LCR. Additional field studies will be required to validate findings from Pearson (2011), if concerns regarding accuracy and precision remain a priority. Although the Pearson (2011) model provided a useful examination of stranding under pre-construction and post-construction conditions, future research will be required to better understand the effects of wake stranding on juvenile salmonids throughout the entire LCR. If additional information on wake stranding is desired in the future, the following topics may be of interest: (1) spatial examination of wake stranding throughout the entire LCR; (2) additional evaluation of juvenile salmonid behavior and population dynamics; (3) assessing and integrating predicted changes in ship development; and (4) assessing and integrating predicted changes in climate on environmental factors known to cause stranding.

Oregon;Washington↗