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At least 613 records · Page 34Linked to original sources

USGS2023

Estimates of predator densities using mobile DIDSON surveys: Implications for survival of Central Valley Chinook Salmon

The Sacramento–San Joaquin Delta (hereafter, “the Delta”) is one of the estuaries with the most invasive species in the world, and nonnative predators may be a major factor in the observed decline of Central Valley Chinook Salmon Oncorhynchus tshawytscha over recent decades. In order for managers to take actions that might reduce predation-related mortality for these ecologically, culturally, and economically valuable fish, it is important to understand the factors influencing the distribution and abundance of piscivores in the Delta. In this study, we used a dual-frequency identification sonar (i.e., DIDSON) to conduct mobile surveys to quantify the abundances of piscivores in the Delta. We then used these data to identify the habitat features that are correlated with the abundance of piscivores. Prior to conducting the surveys, we used DIDSON data from captured fish to develop an algorithm to distinguish piscivores from nonpiscivores with high confidence (98% accuracy). A generalized linear mixed-effects model fit to these survey data indicated that predator abundances were most associated with areas of increased submerged aquatic vegetation patches, and channels that are straighter, with increased bathymetric complexity. When applied to the entire survey area, this model was successfully able to predict known areas of high predator densities. These results indicate that one approach to reduce predator densities in key locations throughout the Delta, and improve juvenile salmonid outmigration survival, is to reduce the extent of invasive submerged aquatic vegetation. Because experimental predator removals have been largely ineffective in the Delta, efforts to manipulate habitat to discourage nonnative predator recruitment and favor native species recruitment may provide a more effective solution to improve salmonid survival rates.

California↗

USGS2024

Assessing factors related to Walleye stocking success in the Midwestern United States

Objective The objective of this study was to evaluate stocking success of Walleye Sander vitreus in lakes and reservoirs across the Midwestern United States to inform stocking practices for state agencies. Demand for Walleye stocking may increase if climate change limits the potential for natural recruitment in lakes. Consequently, the strategic distribution of Walleye stocking may maximize fishing opportunities. Methods We synthesized data from 2226 Walleye fry and fingerling stocking events on 653 lakes in the Midwestern United States and used random forest algorithms and mixed-effects linear models to identify abiotic and biotic factors related to Walleye stocking success. Result Latitude and year explained relatively little variation in stocking success compared to within-lake variation. Relative abundance of Largemouth Bass Micropterus nigricans was an important indicator of Walleye stocking success for fry and fingerlings, with stocking success generally decreasing with increased bass abundance. There was an interaction between lake surface area and growing degree-days, as large lakes (>2500 ha) seemed to be more conducive to Walleye stocking success regardless of growing degree-days. The models that we developed did not accurately predict exact levels of Walleye stocking success but were 92–94% accurate in predicting whether the stocking success of both fry and fingerlings would be at or above the 50th percentile. Conclusion These findings may help to inform the management and stocking allocation of Walleye and suggest that future increases in Largemouth Bass abundance and growing degree-days could limit the effectiveness of stocking in some lakes.

Illinois, Indiana, Iowa, Michigan, Minnesota, Nebr↗

USGS2020

Assessing the potential for spectrally based remote sensing of salmon spawning locations

Remote sensing tools are increasingly used for quantitative mapping of fluvial habitats, yet few techniques exist for continuous sampling of aquatic organisms, such as spawning salmonids. This study assessed the potential for spectrally based remote sensing of salmon spawning locations (i.e., redds) using data acquired from unmanned aircraft systems (UAS) along a large, gravel‐bed river. We developed a novel, semi‐automated approach for detecting salmon redds by applying machine learning classification and object detection techniques to UAS‐based imagery. We found that both true colour (RGB) and hyperspectral imagery could be used to identify salmon redds, though with varying degrees of accuracy. Redds were mapped with accuracies of ~0.75 from RGB imagery using logistic regression and support vector machines (SVM) classification algorithms, but this type of data could not be used to identify redds using Object‐based Image Analysis (OBIA). The hyperspectral imagery was more useful for mapping salmon redds, with accuracies greater than 0.9 for both logistic regression and SVM classifiers; OBIA of the hyperspectral data resulted in redd detection accuracies up to 0.86. The hyperspectral imagery also yielded complementary physical habitat information including water depth and substrate composition, which we quantified on the basis of a spectrally based chlorophyll absorption ratio. Overall, the hyperspectral imagery more effectively identified salmon spawning locations than RGB images and was more conducive to the classification approaches we evaluated. Each type of remotely sensed data had advantages and limitations, which are important for potential users to understand when incorporating UAS‐based data collection into river ecosystem studies.

California↗

USGS2021

The optical river bathymetry toolkit

Spatially distributed information on water depth is essential for many applications in river research and management and, under certain circumstances, can be inferred from remotely sensed data. Although fluvial remote sensing has emerged as a rapidly developing subdiscipline of the riverine sciences, more widespread adoption of these techniques has been hindered by a lack of accessible software. The Optical River Bathymetry Toolkit (ORByT) fills this void by providing a standalone package for mapping water depth from passive optical image data. The ORByT interface enables end users to import images and field‐based depth measurements, create and refine water masks, and perform spectrally based depth retrieval via an Optimal Band Ratio Analysis algorithm. The resulting bathymetric map can be exported as an image file, point cloud, and/or cross section; a thorough accuracy assessment also is incorporated into the workflow. In addition, image‐derived depth estimates can be subtracted from water surface elevations to obtain bed elevations suitable for input to a hydrodynamic model. Potential users of ORByT must bear in mind the inherent limitations of passive optical remote sensing: reliable bathymetry can only be inferred in clear‐flowing, shallow streams; this approach is not appropriate for more turbid, deeper rivers.

River Research and Applications↗

USGS2023

The Toolbox for River Velocimetry using Images from Aircraft (TRiVIA)

Accurate knowledge of the speed at which water moves along a river is essential for understanding ecohydraulic processes and managing natural resources. Measuring flow velocity via remote sensing can be more efficient than conventional field methods, and powerful computational techniques for inferring velocity fields from videos or image time series have been developed. The development of dedicated software tools for particle image velocimetry (PIV) could facilitate greater use of these methods by the river community. This paper introduces a standalone app designed for this exact purpose: the Toolbox for River Velocimetry using Images from Aircraft, or TRiVIA. The program provides a complete workflow for producing spatially distributed velocity vectors from a video or sequence of images, all within an accessible graphical user interface. TRiVIA includes modules for extracting and resampling frames, stabilization and geo-referencing images, defining a region of interest, enhancing images, performing PIV with an efficient ensemble correlation algorithm, visualizing results, assessing accuracy assessment, and exporting PIV output. We illustrate the software's capabilities using an example data set from a large river in Alaska. The initial release of the toolbox is now freely available. Augmenting TRiVIA to incorporate bathymetric information could enable discharge calculation functionality.

River Research and Applications↗

USGS2020

Evaluation of genetic structuring within GIS‐derived Brook Trout management units

Delineation of management units across broad spatial scales can help to visualize population structuring and identify conservation opportunities. Geographical information system (GIS) approaches can be useful for developing broad‐scale management units, especially when paired with field data that can validate the GIS‐based delineations. Genetic data can be useful for evaluating whether management units accurately represent population structuring. The Eastern Brook Trout Joint Venture, a regionwide collaborative group, delineated patch‐based management units for Brook Trout Salvelinus fontinalis by using GIS approaches to inform conservation strategies across the eastern United States. The objectives of this research were to (1) evaluate how well the patches predicted Brook Trout genetic structuring in Connecticut, USA; (2) modify the patches as needed to represent contemporary genetic structuring; and (3) identify catchment‐ and patch‐scale riverscape characteristics that predict genetic diversity. Patches with dams and high levels of upstream impervious surfaces (>3%) had increased intrapatch genetic structuring, which we incorporated into our revised patch delineation algorithm. Patch area and catchment area were the best predictors of genetic diversity, suggesting the importance of maintaining connectivity and incorporating patch‐scale processes into conservation actions. The modified patch layer could be used as the basis for Brook Trout management units to help predict population structuring in the absence of watershed‐scale genetic data, allowing opportunities for Brook Trout conservation to be identified.

Connecticut↗

USGS2013

A generalized Grubbs-Beck test statistic for detecting multiple potentially influential low outliers in flood series

he Grubbs-Beck test is recommended by the federal guidelines for detection of low outliers in flood flow frequency computation in the United States. This paper presents a generalization of the Grubbs-Beck test for normal data (similar to the Rosner (1983) test; see also Spencer and McCuen (1996)) that can provide a consistent standard for identifying multiple potentially influential low flows. In cases where low outliers have been identified, they can be represented as “less-than” values, and a frequency distribution can be developed using censored-data statistical techniques, such as the Expected Moments Algorithm. This approach can improve the fit of the right-hand tail of a frequency distribution and provide protection from lack-of-fit due to unimportant but potentially influential low flows (PILFs) in a flood series, thus making the flood frequency analysis procedure more robust.

Water Resources Research↗

USGS1994

Galileo Photometry of Asteroid 951 Gaspra

Galileo images of Gaspra make it possible for the first time to determine a main-belt asteroid's photometric properties accurately by providing surface-resolved coverage over a wide range of incidence and emission angles and by extending the phase angle coverage to phases not observable from Earth. We combine Earth-based telescopic photometry over phase angles 2° ≤ α ≤ 25° with Galileo whole-disk and disk-resolved data at 33° ≤ α ≤ 51° to derive average global photometric properties in terms of Hapke's photometric model. The microscopic texture and particle phase-function behavior of Gaspra's surface are remarkably like those of other airless rocky bodies such as the Moon. The macroscopic surface roughness parameter, θ̄ = 29°, is slightly larger than that reported for typical lunar materials. The particle single scattering albedo, ώ 0 = 0.36 ± 0.07, is significantly larger than for lunar materials, and the opposition surge amplitude, B 0 = 1.63 ± 0.07, is correspondingly smaller. We determine a visual geometric albedo p v = 0.22 ± 0.06 for Gaspra, in close agreement with p v = 0.22 ± 0.03 estimated from Earth-based observations. Gaspra's phase integral is 0.47, and the bolometric Bond albedo is estimated to be 0.12 ± 0.03. An albedo map derived by correcting Galileo images with our average global photometric function reveals subdued albedo contrasts of ±10% or less over Gaspra's northern hemisphere. Several independent classification algorithms confirm the subtle spectral heterogeneity reported earlier (S. Mottola, M. DiMartino, M. Gonano-Beurer, H. Hoffman, and G. Neukum, 1993, Asteroids, Comets, Meteors, pp. 421-424; M. J. S. Belton et al ., 1992, Science 257, 1647-1652). Whole-disk colors (0.41 ≤ λ ≤ 0.99 μm) vary systematically with longitude by about ±5%, but color differences as large as 30% occur locally. Colors vary continuously between end-member materials whose areal distribution correlates with regional topography. Infrared: violet (0.99:0.41-μm) color ratios on Gaspra are strongly correlated with local elevation, being largest at lower elevations and smaller at higher elevations. No correlation was detected between elevation and the green:violet (0.56:0.41-μm) color ratio. Bright materials with a strong 1-μm absorption occur primarily in association with craters along ridges, while darker materials with 30% weaker 1-μm signatures occur downslope. The variations of color and albedo cannot be easily explained by grain-size effects alone or by differences in photometric geometry. The trends observed are consistent with those revealed by laboratory studies of the effects of comminution, glass formation, and segregation of metal from silicate components in chondritic meteorites and also in some silicate mixtures. The relative importance of these various processes on Gaspra remains to be determined.

Icarus↗

USGS2016

Complexity Theory

A complex system consists of many interacting parts, generates new collective behavior through self organization, and adaptively evolves through time. Many theories have been developed to study complex systems, including chaos, fractals, cellular automata, self organization, stochastic processes, turbulence, and genetic algorithms.

Book chapter↗

USGS2015

Bioenergetics modeling of percid fishes

A bioenergetics model for a percid fish represents a quantitative description of the fish’s energy budget. Bioenergetics modeling can be used to identify the important factors determining growth of percids in lakes, rivers, or seas. For example, bioenergetics modeling applied to yellow perch ( Perca flavescens ) in the western and central basins of Lake Erie revealed that the slower growth in the western basin was attributable to limitations in suitably sized prey in western Lake Erie, rather than differences in water temperature between the two basins. Bioenergetics modeling can also be applied to a percid population to estimate the amount of food being annually consumed by the percid population. For example, bioenergetics modeling applied to the walleye ( Sander vitreus ) population in Lake Erie has provided fishery managers valuable insights into changes in the population’s predatory demand over time. In addition, bioenergetics modeling has been used to quantify the effect of the difference in growth between the sexes on contaminant accumulation in walleye. Field and laboratory evaluations of percid bioenergetics model performance have documented a systematic bias, such that the models overestimate consumption at low feeding rates but underestimate consumption at high feeding rates. However, more recent studies have shown that this systematic bias was due, at least in part, to an error in the energy budget balancing algorithm used in the computer software. Future research work is needed to more thoroughly assess the field and laboratory performance of percid bioenergetics models and to quantify differences in activity and standard metabolic rate between the sexes of mature percids.

Book chapter↗

USGS1987

Computer graphics for quality control in the INAA of geological samples

A data reduction system for the routine instrumental activation analysis of samples is described, with particular emphasis on interactive graphics capabilities for evaluating analytical quality. Graphics procedures have been developed to interactively control the analysis of selected photopeaks during spectral analysis, and to evaluate detector performance during a given counting cycle. Graphics algorithms are also used to compare the data on reference samples with accepted values, to prepare quality control charts to evaluate long term precision and to search for systematic variations in data on reference samples as a function of time. ?? 1987 Akade??miai Kiado??.

Journal of Radioanalytical and Nuclear Chemistry A↗

USGS1995

Optimization techniques for integrating spatial data

Two optimization techniques ta predict a spatial variable from any number of related spatial variables are presented. The applicability of the two different methods for petroleum-resource assessment is tested in a mature oil province of the Midcontinent (USA). The information on petroleum productivity, usually not directly accessible, is related indirectly to geological, geophysical, petrographical, and other observable data. This paper presents two approaches based on construction of a multivariate spatial model from the available data to determine a relationship for prediction. In the first approach, the variables are combined into a spatial model by an algebraic map-comparison/integration technique. Optimal weights for the map comparison function are determined by the Nelder-Mead downhill simplex algorithm in multidimensions. Geologic knowledge is necessary to provide a first guess of weights to start the automatization, because the solution is not unique. In the second approach, active set optimization for linear prediction of the target under positivity constraints is applied. Here, the procedure seems to select one variable from each data type (structure, isopachous, and petrophysical) eliminating data redundancy. Automating the determination of optimum combinations of different variables by applying optimization techniques is a valuable extension of the algebraic map-comparison/integration approach to analyzing spatial data. Because of the capability of handling multivariate data sets and partial retention of geographical information, the approaches can be useful in mineral-resource exploration. ?? 1995 International Association for Mathematical Geology.

Mathematical Geology↗

USGS2005

The inverse problem of refraction travel times, part II: Quantifying refraction nonuniqueness using a three-layer model

This paper is the second of a set of two papers in which we study the inverse refraction problem. The first paper, "Types of Geophysical Nonuniqueness through Minimization," studies and classifies the types of nonuniqueness that exist when solving inverse problems depending on the participation of a priori information required to obtain reliable solutions of inverse geophysical problems. In view of the classification developed, in this paper we study the type of nonuniqueness associated with the inverse refraction problem. An approach for obtaining a realistic solution to the inverse refraction problem is offered in a third paper that is in preparation. The nonuniqueness of the inverse refraction problem is examined by using a simple three-layer model. Like many other inverse geophysical problems, the inverse refraction problem does not have a unique solution. Conventionally, nonuniqueness is considered to be a result of insufficient data and/or error in the data, for any fixed number of model parameters. This study illustrates that even for overdetermined and error free data, nonlinear inverse refraction problems exhibit exact-data nonuniqueness, which further complicates the problem of nonuniqueness. By evaluating the nonuniqueness of the inverse refraction problem, this paper targets the improvement of refraction inversion algorithms, and as a result, the achievement of more realistic solutions. The nonuniqueness of the inverse refraction problem is examined initially by using a simple three-layer model. The observations and conclusions of the three-layer model nonuniqueness study are used to evaluate the nonuniqueness of more complicated n-layer models and multi-parameter cell models such as in refraction tomography. For any fixed number of model parameters, the inverse refraction problem exhibits continuous ranges of exact-data nonuniqueness. Such an unfavorable type of nonuniqueness can be uniquely solved only by providing abundant a priori information. Insufficient a priori information during the inversion is the reason why refraction methods often may not produce desired results or even fail. This work also demonstrates that the application of the smoothing constraints, typical when solving ill-posed inverse problems, has a dual and contradictory role when applied to the ill-posed inverse problem of refraction travel times. This observation indicates that smoothing constraints may play such a two-fold role when applied to other inverse problems. Other factors that contribute to inverse-refraction-problem nonuniqueness are also considered, including indeterminacy, statistical data-error distribution, numerical error and instability, finite data, and model parameters. ?? Birkha??user Verlag, Basel, 2005.

Pure and Applied Geophysics↗

USGS2010

Combined effects of tectonic and landslide-generated Tsunami Runup at Seward, Alaska during the Mw 9.2 1964 earthquake

We apply a recently developed and validated numerical model of tsunami propagation and runup to study the inundation of Resurrection Bay and the town of Seward by the 1964 Alaska tsunami. Seward was hit by both tectonic and landslide-generated tsunami waves during the M W "> M W MW 9.2 1964 megathrust earthquake. The earthquake triggered a series of submarine mass failures around the fjord, which resulted in landsliding of part of the coastline into the water, along with the loss of the port facilities. These submarine mass failures generated local waves in the bay within 5 min of the beginning of strong ground motion. Recent studies estimate the total volume of underwater slide material that moved in Resurrection Bay to be about 211 million m 3 (Haeussler et al. in Submarine mass movements and their consequences, pp 269–278, 2007 ). The first tectonic tsunami wave arrived in Resurrection Bay about 30 min after the main shock and was about the same height as the local landslide-generated waves. Our previous numerical study, which focused only on the local landslide-generated waves in Resurrection Bay, demonstrated that they were produced by a number of different slope failures, and estimated relative contributions of different submarine slide complexes into tsunami amplitudes (Suleimani et al. in Pure Appl Geophys 166:131–152, 2009 ). This work extends the previous study by calculating tsunami inundation in Resurrection Bay caused by the combined impact of landslide-generated waves and the tectonic tsunami, and comparing the composite inundation area with observations. To simulate landslide tsunami runup in Seward, we use a viscous slide model of Jiang and LeBlond (J Phys Oceanogr 24(3):559–572, 1994 ) coupled with nonlinear shallow water equations. The input data set includes a high resolution multibeam bathymetry and LIDAR topography grid of Resurrection Bay, and an initial thickness of slide material based on pre- and post-earthquake bathymetry difference maps. For simulation of tectonic tsunami runup, we derive the 1964 coseismic deformations from detailed slip distribution in the rupture area, and use them as an initial condition for propagation of the tectonic tsunami. The numerical model employs nonlinear shallow water equations formulated for depth-averaged water fluxes, and calculates a temporal position of the shoreline using a free-surface moving boundary algorithm. We find that the calculated tsunami runup in Seward caused first by local submarine landslide-generated waves, and later by a tectonic tsunami, is in good agreement with observations of the inundation zone. The analysis of inundation caused by two different tsunami sources improves our understanding of their relative contributions, and supports tsunami risk mitigation in south-central Alaska. The record of the 1964 earthquake, tsunami, and submarine landslides, combined with the high-resolution topography and bathymetry of Resurrection Bay make it an ideal location for studying tectonic tsunamis in coastal regions susceptible to underwater landslides.

Alaska↗

USGS2016

Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence

The seismic spectrum can be constructed by assuming a Brune spectral model and estimating the parameters of seismic moment ( M 0 ), corner frequency ( f c ), and high-frequency site attenuation ( κ ). Using seismic data collected during the 2010–2011 Canterbury, New Zealand, earthquake sequence, we apply the non-linear least-squares Gauss–Newton method, a deterministic downhill optimization technique, to simultaneously determine the M 0 , f c , and κ for each event-station pair. We fit the Brune spectral acceleration model to Fourier-transformed S-wave records following application of path and site corrections to the data. For each event, we solve for a single M 0 and f c , while any remaining residual kappa, κ r "> κ r κr , is allowed to differ per station record to reflect varying high-frequency falloff due to path and site attenuation. We use a parametric forward modeling method, calculating initial M 0 and f c values from the local GNS New Zealand catalog M w, GNS magnitudes and measuring an initial κ r "> κ r κr using an automated high-frequency linear regression method. Final solutions for M 0 , f c , and κ r "> κ r κr are iteratively computed through minimization of the residual function, and the Brune model stress drop is then calculated from the final, best-fit f c . We perform the spectral fitting routine on nested array seismic data that include the permanent GeoNet accelerometer network as well as a dense network of nearly 200 Quake Catcher Network (QCN) MEMs accelerometers, analyzing over 180 aftershocks M w,GNS ≥ 3.5 that occurred from 9 September 2010 to 31 July 2011. QCN stations were hosted by public volunteers and served to fill spatial gaps between existing GeoNet stations. Moment magnitudes determined using the spectral fitting procedure ( M w,SF ) range from 3.5 to 5.7 and agree well with M w,GNS , with a median difference of 0.09 and 0.17 for GeoNet and QCN records, respectively, and 0.11 when data from both networks are combined. The majority of events are calculated to have stress drops between 1.7 and 13 MPa (20th and 80th percentile, correspondingly) for the combined networks. The overall median stress drop for the combined networks is 3.2 MPa, which is similar to median stress drops previously reported for the Canterbury sequence. We do not observe a correlation between stress drop and depth for this region, nor a relationship between stress drop and magnitude over the catalog considered. Lateral spatial patterns in stress drop, such as a cluster of aftershocks near the eastern extent of the Greendale fault with higher stress drops and lower stress drops for aftershocks of the 2011 M w,GNS 6.2 Christchurch mainshock, are found to be in agreement with previous reports. As stress drop is arguably a method-dependent calculation and subject to high spatial variability, our results using the parametric Gauss–Newton algorithm strengthen conclusions that the Canterbury sequence has stress drops that are more similar to those found in intraplate regions, with overall higher stress drops that are typically observed in tectonically active areas.

Christchurch↗

USGS2017

Shear-wave velocity model from Rayleigh wave group velocities centered on the Sacramento/San Joaquin Delta

Rayleigh wave group velocities obtained from ambient noise tomography are inverted for an upper crustal model of the Central Valley, California, centered on the Sacramento/San Joaquin Delta. Two methods were tried; the first uses SURF96, a least-squares routine. It provides a good fit to the data, but convergence is dependent on the starting model. The second uses a genetic algorithm, whose starting model is random. This method was tried at several nodes in the model and compared to the output from SURF96. The genetic code is run five times and the variance of the output of all five models can be used to obtain an estimate of error. SURF96 produces a more regular solution mostly because it is typically run with a smoothing constraint. Models from the genetic code are generally consistent with the SURF96 code sometimes producing lower velocities at depth. The full model, calculated using SURF96, employed a 2-pass strategy, which used a variable damping scheme in the first pass. The resulting model shows low velocities near the surface in the Central Valley with a broad asymmetrical sedimentary basin located close to the western edge of the Central Valley near 122°W longitude. At shallow depths the Rio Vista Basin is found nestled between the Pittsburgh/Kirby Hills and Midland faults, but a significant basin also seems to exist to the west of the Kirby Hills fault. There are other possible correlations between fast and slow velocities in the Central Valley and geologic features such as the Stockton Arch, oil or gas producing regions and the fault-controlled western boundary of the Central Valley.

California↗

USGS2016

Integrating subsistence practice and species distribution modeling: assessing invasive elodea’s potential impact on Native Alaskan subsistence of Chinook salmon and whitefish

Alaska has one of the most rapidly changing climates on earth and is experiencing an accelerated rate of human disturbance, including resource extraction and transportation infrastructure development. Combined, these factors increase the state’s vulnerability to biological invasion, which can have acute negative impacts on ecological integrity and subsistence practices. Of growing concern is the spread of Alaska’s first documented freshwater aquatic invasive plant Elodea spp. (elodea). In this study, we modeled the suitable habitat of elodea using global and state-specific species occurrence records and environmental variables, in concert with an ensemble of model algorithms. Furthermore, we sought to incorporate local subsistence concerns by using Native Alaskan knowledge and available statewide subsistence harvest data to assess the potential threat posed by elodea to Chinook salmon ( Oncorhynchus tshawytscha ) and whitefish ( Coregonus nelsonii ) subsistence. State models were applied to future climate (2040–2059) using five general circulation models best suited for Alaska. Model evaluations indicated that our results had moderate to strong predictability, with area under the receiver-operating characteristic curve values above 0.80 and classification accuracies ranging from 66 to 89 %. State models provided a more robust assessment of elodea habitat suitability. These ensembles revealed different levels of management concern statewide, based on the interaction of fish subsistence patterns, known spawning and rearing sites, and elodea habitat suitability, thus highlighting regions with additional need for targeted monitoring. Our results suggest that this approach can hold great utility for invasion risk assessments and better facilitate the inclusion of local stakeholder concerns in conservation planning and management.

Alaska↗

USGS2024

Modeling the potential spread of the non-native regal demoiselle, Neopomacentrus cyanomos, in the western Atlantic

Predicting the potential distribution of a non-native species can assist management efforts to mitigate impacts on recipient ecosystems. However, such predictions are lacking for marine species, such as the non-native regal demoiselle, Neopomacentrus cyanomos , that is currently expanding its distribution in the western Atlantic. We used correlative species distribution models with three common algorithms to predict suitable habitat for N. cyanomos in the region. We compared models developed using native, non-native, and global occurrences to differentiate drivers across separate ranges using a suite of 12 environmental characteristics. While final models included an ensemble of variables, the majority ranked the combined effect of temperature variables as a key predictor correlated with the distribution of N. cyanomos. Habitat suitability increased as water temperatures increased beyond 16 °C and where annual thermal ranges were greater than 10 °C at the shallowest depth with substrate within a study cell (~ 9.2 km 2 resolution). Habitat suitability also increased where maximum surface temperatures were greater than 27 °C. In the non-native range, the proportion of reef available in each cell was another important variable increasing the suitable habitat for N. cyanomos . Our models predicted high habitat suitability for N. cyanomos throughout the Greater Caribbean, in higher latitudes along North and South American Atlantic coasts, in the eastern Pacific Ocean, and highlights key areas where managers can monitor and target potential removal efforts. The distribution of this non-native species is likely to continue expanding throughout the region with little known about potential implications on native communities.

Coral Reefs↗