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At least 1,207 records · Page 67Linked to original sources
USGS1996

Empirical Bayes estimation of proportions with application to cowbird parasitism rates

Bayesian models provide a structure for studying collections of parameters such are considered in the investigation of communities, ecosystems, and landscapes. This structure allows for improved estimation of individual parameters by considering them in the context of a group of related parameters. Individual estimates are differntially adjusted toward in overall mean, with the magnitude of their adjustment based on their precision. Consequently, Bayesian estimation allows for a more reliable ranking of parameters and, in particular, a more credible identification of extreme values from a collection of estimates. In Bayesian models, individual parameters are regarded as values sampled from a specified probability distribution, called a prior. The requirements that the prior be known is often regarded as an unattractive feature of Bayesian analysis and may be the reason Bayesian analyses are not frequently applied in ecological studies. Empirical Bayes methods provide an alternative approach that incorporates the structural advantages of Bayesian models while requirng a less stringent specification of prior knowledge. Empirical Bayes methods require only that the prior be in a certain family of distributions, indexed by hyperparameters that can be estimated from the available data. This structur is of interest per se, in addition to its value in allowing for improved estimation of individual parameters; for example, hypothese regarding the existence of distinct subgroups in a collection of paramet ers can be considered under the empirical Bayes framework by allowing the hyperparameters to vary among subgroups. We describe the empirical Bayes approach in application to estimation of proportions, using data obtained in a community—wide study Brown—headed Cowbird paratism rates for illustration. Empirical Bayes estimates identify those species for which there is the greatest evidence of extreme parasitism rates. Subgroup analysis of our data on cowbird parasitism rates indicates that parasitisms rates for neotropical migrants as a group are no greater than those of resident/short—distance migrant in this forest community. Our data and analyses demonstrate that the parasitism rates for certain neotropical migrant species (Wood Thrush and Rose—breasted Grosbeak) are remarkably low while those for others (Ovenbird and Red—eyed Vireo) are remarkably high.

Ecology↗
USGS2026

Decision-centered systems for the future of wildlife conservation

The future of wildlife conservation will be determined by how well we decide, not simply by how much we know. Advances in quantitative ecology, sensor networks, and artificial intelligence have enhanced the field's ability to estimate population states and predict ecological dynamics. Yet, these technological and analytical advancements have not translated into proportional improvements in wildlife conservation decision making. The prevailing science-centered paradigm, which prioritizes research production as the primary route to better management, was appropriate when limited ecological understanding was the primary constraint on decision making. Today, wildlife conservation challenges are more often restricted by inadequate decision-making processes rather than by insufficient information. This paper defines a decision-centered system as an institutional and organizational arrangement in which the generation, integration, and application of scientific knowledge are explicitly structured around the decisions required for wildlife conservation. Decision systems evaluate success not only through scientific rigor, but through the quality of decision-making processes and outcomes they support. Artificial intelligence (AI) is likely to deepen this mismatch by rapidly expanding analytical capacity while leaving the underlying challenges of decision making unresolved. As AI data synthesis, modeling, and estimation become increasingly automated, the comparative advantage of conservation professionals is likely to shift toward tasks requiring human judgment (e.g., eliciting stakeholder values, weighting competing management objectives). The conceptual basis for this shift already exists in structured decision making, adaptive management, and similar frameworks. The remaining barriers to implementation are both institutional and organizational. The rules, norms, and incentive structures governing what counts as good conservation work, including what gets funded, published, and rewarded, will benefit from shifting alongside the agencies, universities, and professional societies that train and employ wildlife professionals. Conditions for this transition include redesigning incentives, training, and governance so that organizations are prepared not only to generate knowledge, but to consistently translate it into effective action.

The Wildlife Society Bulletin↗
USGS2022

A water quality barometer for Chesapeake Bay: Assessing spatial and temporal patterns using long-term monitoring data

This paper develops a barometer that indexes water quality in the Chesapeake Bay and summarizes quality over spatial regions and temporal periods. The barometer has a basis in risk assessment and hydrology, and is a function of three different metrics of water quality relative to numerical criteria: relative frequency of criterion attainment; magnitude of deviation from a numerical criterion; and duration of criterion attainment. Metrics associated with these features are calculated at the station level, allowing flexibility for simultaneously evaluating multiple stressors, different designated uses, and physical characteristics of the water. The barometer score is then created as a geometric mean of the three metrics. The water quality barometer (WQB) station scores may be spatially aggregated to report habitat scores across a spectrum of spatial resolutions (e.g., management segment, tidal subsystem, or the whole tidal bay). Dissolved oxygen measurements in the Chesapeake Bay collected during summer seasons of 1985 to 2020 are used to evaluate water quality. The WQB score and its bootstrapped confidence interval are reported at the station, segment, tidal subsystem and whole tidal bay levels. Notably, water quality interpreted through application of the WQB with dissolved oxygen concentration data and averaged over the 29-year period of record is good (i.e. protects aquatic living resources) in tributaries such as the James River, Rappahannock River and others; but is not as good in areas such as the Upper Tributaries and the York River. Recent summaries indicate that while the water quality is improving in much of the bay and its tidal tributaries, however, there is an indication of decline in quality in the period 20182020, especially in the upper regions of the Bay. The barometer is designed around using the time series data produced by the Chesapeake Bay Programs annual monitoring strategy; the approach has application to other large water bodies with large scale monitoring programs with extended time series or for integrating information from environmental sensor systems.

Maryland, Virginia↗
USGS2020

The roles of flood magnitude and duration in controlling channel width and complexity on the Green River in Canyonlands, Utah, USA

Predictions of river channel adjustment to changes in streamflow regime based on relations between mean channel characteristics and mean flood magnitude can be useful to evaluate average channel response. However, because these relations assume equilibrium sediment transport, their applicability to cases where streamflow and sediment transport are decoupled may be limited. These general relations also lack the specificity that is required to connect specific characteristics of the streamflow and sediment regime with the dynamics of channel morphological change that create channel complexity, which is often of ecological interest. We integrate historical records of channel change, observations of scour and fill during a snowmelt flood, measurements of sediment transport, and predictions from a two-dimensional streamflow model to describe how annual peak flow magnitude and peak-flow duration interact with the upstream sediment supply to control channel form for a 15-km study reach on the regulated Green River in Canyonlands National Park, Utah. Two major decadal-scale episodes of channel narrowing have occurred within the study area. For each of these episodes, the reduction in average channel width was consistent with the change predicted by hydraulic geometry relations as a function of average flood magnitude. However, channel narrowing occurred during periods of exceptionally low annual floods. The most recent episode of channel narrowing occurred between 1988 and 2009, during low-flow cycles when the 5-yr mean peak flow was less than 60% of the long-term (1959–2016) mean peak flow. These findings, together with findings from previous studies, demonstrate that decreases in peak-flow magnitude caused by streamflow regulation, climate change, or a combination of those factors have driven episodes of channel narrowing on the Green River. Observations of streamflow, sediment-transport, and morphologic change coupled with predictions from a two-dimensional streamflow model indicate that peak flow magnitudes of at least 75% of the long-term mean peak flow are required to transport bed-material sand in suspension in all regions of the multi-thread channel and that the ~2-month duration of the snowmelt flood played an important role in creating conditions necessary to maintain channel conveyance. These results indicate that detailed characterizations of channel response such as these are needed to predict how river channels will respond to changes in streamflow regime that affect annual peak flow magnitude and duration.

Utah↗
USGS2018

Challenges of forecasting flooding on coral reef–lined coasts

Understanding wave-driven coastal flooding is a challenging scientific problem; the need for forecasts is becoming more urgent because of sea level rise, climate change, and ever-growing coastal populations. The tools developed for sandy shorelines are generally not applicable to coral reef–lined coasts with their complex bathymetry, hydrodynamically rough reef platforms, steep and poorly sorted beaches, and low coastal elevations. Advances in understanding and predicting flooding on coral reef–lined coasts thus require concerted efforts from a number of disciplines, including climatology, oceanography, geology, and ecology.

Eos, Earth and Space Science News↗
USGS2003

Genetic variation among interconnected populations of Catostomus occidentalis: Implications for distinguishing impacts of contaminants from biogeographical structuring

Exposure to contaminants can affect survivorship, recruitment, reproductive success, mutation rates and migration, and may play a significant role in the partitioning of genetic variation among exposed and nonexposed populations. However, the application of molecular population genetic data to evaluate such influences has been uncommon and often flawed. We tested whether patterns of genetic variation among native fish populations (Sacramento sucker, Catostomus occidentalis) in the Central Valley of California were consistent with long-term pesticide exposure history, or primarily with expectations based on biogeography. Field sampling was designed to rigorously test for both geographical and contamination influences. Fine-scale structure of these interconnected populations was detected with both amplified fragment length polymorphisms (AFLP) and microsatellite markers, and patterns of variation elucidated by the two marker systems were highly concordant. Analyses indicated that biogeographical hypotheses described the data set better than hypotheses relating to common historical pesticide exposure. Downstream populations had higher genetic diversity than upstream populations, regardless of exposure history, and genetic distances showed that populations from the same river system tended to cluster together. Relatedness among populations reflected primarily directions of gene flow, rather than convergence among contaminant-exposed populations. Watershed geography accounted for significant partitioning of genetic variation among populations, whereas contaminant exposure history did not. Genetic patterns indicating contaminant-induced selection, increased mutation rates or recent bottlenecks were weak or absent. We stress the importance of testing contaminant-induced genetic change hypotheses within a biogeographical context. Strategic application of molecular markers for analysis of fine-scale structure, and for evaluating contaminant impacts on gene pools, is discussed.

Molecular Ecology↗
USGS2009

Use of dendrochronology and dendrochemistry in environmental forensics: Does it meet the Daubert criteria?

Dendrochronological methods have been in use for more than 100 years, providing us a record of climate, human activities (archaeology), floods, fire, mudslides and other geological and biological events. More recently, dendrochemisty has been used to assess the time frames of the onset and existence of environmental contamination. This article assesses the scientific status of dendrochronology and dendrochemistry with respect to the admissibility of expert testimony and Daubert legal criteria. The purpose of this article is to identify the crucial scientific aspects of dendrochronology and dendrochemistry that address the Daubert criteria and Rule 702 as amended in 2000. To clarify terminology, dendrochronology is the precise and reliable assignment of the year of formation of tree rings. Dendroecology is the use of dendrochronology to understand ecological and environmental processes (Schweingruber, 1996). Dendrochemistry is a subdiscipline of dendrochronology that analyzes and interprets the wood chemistry of precisely dated tree rings. Forensic dendrochemistry applies dendrochemistry to resolve environmental disputes and generally deal with questions regarding the timing and/or the source of environmental incidents. One significant application of forensic dendrochemistry to expert testimony is to address issues of anthropogenic contamination. Forensic dendroecology is a similar term to forensic dendrochemistry, but forensic dendrochemistry will be used in this discussion as the latter term emphasizes the use of chemical detection methods. Because dendrochemistry is based on the foundation of dendrochronology, both the former specialty and the latter broader discipline will be discussed. ?? Taylor & Francis Group, LLC.

Environmental Forensics↗
USGS2010

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Level 3 Ecoregions

This data set represents the estimated area of level 3 ecological landscape regions (ecoregions), as defined by Omernik (1987), compiled for every catchment of NHDPlus for the conterminous United States. The source data set is Level III Ecoregions of the Continental United States (U.S. Environmental Protection Agency, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Data Series↗
USGS2020

Using remote sensing products to predict recovery of vegetation across space and time following energy development

Using localized studies to understand how ecosystems recover can create uncertainty in recovery predictions across landscapes. Large archives of remote sensing data offer opportunities for quantifying the spatial and temporal factors influencing recovery at broad scales and predicting recovery. For example, energy production is a widespread and expanding land use among many semi-arid ecosystems of the Western United States dominated by sagebrush ( Artemisia spp.), a keystone species providing a variety of ecological services. With remotely-sensed (Landsat) estimates of vegetation cover collected every 2–5 years from southwestern Wyoming, USA, over nearly three decades (1985–2015), we modeled changes in sagebrush cover on 375 former oil and gas well pads in response to weather and site-level conditions. We then used modeled relationships to predict recovery time across the landscape as an indicator of resilience for vegetation after well pad disturbances, where faster recovery indicates a greater capacity to recover when similarly disturbed. We found the rate of change in sagebrush cover generally increased with moisture and temperature, particularly at higher elevations. Rate of change in sagebrush cover also increased and decreased with greater percent sand and larger well pads, respectively. We predicted 21% of the landscape would recover to pre-disturbance conditions within 60 years, whereas other areas may require >100 years for recovery. These predictions and maps could inform future restoration efforts as they reflect resilience. This approach also is applicable to other disturbance types (e.g., fires and vegetation removal treatments) across landscapes, which can further improve conservation efforts by characterizing past conditions and monitoring trends in subsequent years.

Wyoming↗
USGS2026

Statewide agent-based model for management of chronic wasting disease in white-tailed deer: PAOvCWD

Chronic wasting disease (CWD) is an always-fatal disease infecting wild cervids globally. Ecologically and economically important, CWD presents a challenge for managing white-tailed deer ( Odocoileus virginianus ). We built an agent-based model to simulate CWD transmission and assess potential management actions that could slow disease spread: PAOvCWD . We developed PAOvCWD using contact rates and other behavioral and ecological metrics estimated from deer monitored in Pennsylvania, USA. We programmed potential management responses (e.g., culling, altered hunter harvest) for all 22 Pennsylvania wildlife management units and validated the efficacy of PAOvCWD using a deer population in south-central Pennsylvania infected with CWD for > 10 years. To support applications of our model, we developed a user-friendly R pipeline that allows implementation with relatively minor modifications. Our pipeline includes four steps: • Steps 1 and 2 generate regional percent forest cover rasters and curate population-level demographics. • Step 3 initializes landscapes and agents using our PAOvPOP model. • Step 4 assesses CWD transmission and management responses using our PAOvCWD model.

Pennsylvania↗
USGS2012

Estimating spatial and temporal components of variation in count data using negative binomial mixed models

P artitioning total variability into its component temporal and spatial sources is a powerful way to better understand time series and elucidate trends. The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes Sander vitreus across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site × year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.

Iowa, Maine, Michigan, Ohio, Wisconsin↗
USGS2026

An automatable method for developing preliminary stream crossing designs using lidar and hydraulic modeling in Massachusetts

Upgrading aging and undersized stream crossings (places where culverts and bridges intersect a stream) with replacements designed for aquatic organism passage can improve infrastructure resiliency, geomorphic stability, and maintenance costs. The goal of this work is to develop preliminary culvert designs that convey hydraulic design floods and meet the Massachusetts Stream Crossings Standards for select existing stream crossing sites across Massachusetts. We derive stream and infrastructure data from lidar and other geospatial datasets as input for one-dimensional hydraulic models. Culvert dimensions are iteratively increased until the structures can convey the hydraulic design flood flows with adequate freeboard. The approach was evaluated by comparing lidar-derived designs to designs produced with surveyed data at 30 stream crossings across Massachusetts. The automatable methodology was then applied to 343 stream crossing sites in the Housatonic River watershed in southwestern Massachusetts. For each stream crossing site, preliminary designs were developed to meet the Massachusetts Stream Crossing Standards and convey the 10-, 4-, 2-, and 1-percent annual exceedance probability flood flows. The U.S. Geological Survey StreamStats web application hosts the 3-sided box, 3-sided arch, and pipe culvert preliminary designs. Provided supporting information includes site information, habitat quality assessments, and modeled water surface elevations. The publicly available preliminary designs can be used by municipalities, engineers, and others to evaluate design options, prioritize replacements, and analyze ecological benefits. These designs also may help municipalities pursue grant opportunities and estimate replacement costs prior to investing in field assessments and engineering design.

EarthArXiv↗
USGS2024

Establishing quantitative benchmarks for soil erosion and ecological monitoring, assessment, and management

Soil erosion can have a multitude of negative impacts on agroecosystems and society and there remains an urgent need for tools to support its management. Quantitative benchmarks based on holistic understanding of erosion processes, ecosystem function, and land use objectives can be used with monitoring data and models to inform assessments and make objective and actionable decisions about erosion management. However, managers currently lack a framework for establishing benchmarks. Here, we present a framework and evaluation of different approaches to establishing quantitative benchmarks for soil erosion and ecological monitoring and assessment that can inform land management decisions. We use monitoring data collected across Chihuahuan Desert ecosystems in the United States and an aeolian sediment transport model to illustrate how benchmarks can be established. Approaches include establishing benchmarks from relationships between soil erosion indicators, reference states and land potential, including state-and-transition models, and desired conditions from existing monitoring data. We discuss the benefits and caveats of the different approaches and show how combining different benchmarking approaches can help users ensure that benchmarks appropriately reflect thresholds for soil erosion and achievable management outcomes. We finish by identifying future research needs to support establishment and application of erosion benchmarks across agroecosystems and recognize the opportunity to extend the benchmarking approaches to management of other agroecosystem processes and services.

Ecological Indicators↗
USGS2015

The Everglades Depth Estimation Network (EDEN) surface-water model, version 2

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that generate daily water-level and water-depth data, and applications that compute derived hydrologic data across the freshwater part of the greater Everglades landscape. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for EDEN in order for EDEN to provide quality-assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The EDEN surface-water model, version 2 (V2), interpolates water-level data from a network of 240 gages to generate gridded daily water-level surfaces for the freshwater domain of the Everglades. When these spatiotemporal continuous surfaces are combined with EDEN’s digital elevation model of ground surface, derived hydrologic data provide scientists and water managers working in the Everglades with data necessary to analyze ecological and biotic responses to hydrologic changes in the Everglades. Derived datasets include water depth, recession rates, days since last dry, water-surface slopes, and hydroperiod. The V2 model includes enhancements from the previous model (version 1; V1) to accommodate changes in the water-level gage network, adjustments to water-level data, improved understanding of the flow dynamics (particularly near canals), and installation of an elevation benchmark network. Enhancements to the V2 model included Expansion of the EDEN domain: The model domain was expanded to include a part of southern Big Cypress National Preserve and northwestern Everglades National Park upstream of the marsh mangrove wetlands, thus completing the coastal connection along the southwestern boundary of the model; and Development of subdomain models: To account for insufficient water-control structure gage data at some subbasin boundaries, subdomain models were developed for five subdomains, and the resulting water-level surfaces were merged to generate the final water-level surface. Model performance statistics show a general improvement in the V2 model as compared to the V1 model. Overall, the root mean squared error (RMSE) was reduced by 2.42 centimeters (cm) to 4.68 cm. In Water Conservation Area 3A North and Water Conservation Area 3B, the RMSE was reduced by 10.88 and 9.15 cm, respectively. In addition to evaluating model performance statistics, 2-cm water-level maps were generated and evaluated for irregular contours that would indicate a potential problem either with data input or water-level estimates. Three applications of the EDEN-modeled water surfaces and other EDEN datasets are presented in the report to show how scientists and resource managers are using EDEN datasets to analyze biological and ecological responses to hydrologic changes in the Everglades. The biological responses of two important Everglades species, alligators and wading birds, to changes in hydrology are described. The effects of hydrology on fire dynamics in the Everglades are also discussed.

Florida↗
USGS2018

Evaluation of biodiversity data portals based on requirement analysis

In recent years, concern about the misuse of natural resources has been increasing. It is essential to know in detail the biodiversity of an ecosystem to understand and analyze the impact of human activities on nature, as well as to promote the economic growth of a country. To achieve these goals, public and private institutions are aggregating and sharing biological data around the world by means of biodiversity data portals. The main purpose of those portals is to provide a set of tools that help users and institutions catalog, analyze, and publish raw data about different species in a manner that is open and freely available to any interested party. Normally the process of choosing the best software solution is not straightforward. This paper proposes a methodology to evaluate a collection of data portals to establish a clear and consistent selection process that analyzes a collection of requirements and research purposes. The proposed approach is based on three strategies: the use of software engineering techniques to identify the desired group of features to be available in the data portal; the application of the Kano Satisfaction Model to score each requirement according to a preset weight of importance; and the use of tree-maps to visualize the requirements based on their implementation priority, to establish a portal deployment road-map. The proposed methodology is broadly applicable to portal analyses for many communities of practice.

Ecological Informatics↗
USGS2026

A tool to monitor hydrologic conditions on tree islands in the Everglades

Tree islands are patchy upland forested habitats in Florida's Everglades that face degradation and disappearance due to altered hydrologic patterns. The U.S. Geological Survey coordinated with the Miccosukee Tribe of Indians of Florida and the Seminole Tribe of Florida to co-develop a decision-support tool based on tree-island hydrologic conditions. Everglades managers can use this tool to help with restoration planning and water operations decisions that affect tree-island conditions. After a series of organized workshops and meetings, a list of hydrologic metrics was selected as indicators of tree-island health, including hydroperiod, number of days since last dry, and maximum water depth at the head of the island. As a result, a web application tool, called ETree, has been developed and is publicly available online. This web application provides data on daily metrics for the current Everglades water year and annual summaries for past years, beginning in 2000.

Florida↗
USGS2023

Parentage-based tagging using mothers balances accuracy and cost for discriminating between natural and stocked recruitment for inland fisheries

Hatchery programmes are frequently used to supplement inland fisheries, yet achieving successful management outcomes often requires information on stocked versus naturally reproduced fish abundance. Parentage-based tagging – genetically assigning offspring to their parents – has potential to be an effective approach for distinguishing stocked and naturally reproduced fish. However, several challenges may limit its application to inland fisheries, including genetic relatedness among populations that can affect identification accuracy and high costs of genotyping large broodstocks. Here, we demonstrate the efficacy of parentage-based tagging based on broodmothers in the Lake Ontario Chinook Salmon fishery, which uses thousands of broodparents and has potential for substantial relatedness between stocked and naturally reproduced fish. Restricting parent sampling to broodmothers reduced costs by two-thirds, was logistically pragmatic, and achieved >95% accuracy in distinguishing stocked from naturally reproduced salmon. Combined, these results highlight the potential wide applicability of parentage-based tagging for assessing stocking programmes in inland waters.

New York, Ontario↗
USGS2005

Assessing ecological integrity of Ozark rivers to determine suitability for protective status

Preservation of extraordinary natural resources, protection of water quality, and restoration of impaired waters require a strategy to identify and protect least-disturbed streams and rivers. We applied two objective, quantitative methods to determine stream ecological integrity of headwater reaches of 10 Ozark rivers, 5 with Wild and Scenic River federal protective status. Thirty-four variables representing macroinvertebrate and fish assemblage characteristics, in-stream habitat, riparian vegetation, water quality, and watershed attributes were quantified for each river and analyzed using two multivariate approaches. The first approach, cluster and discriminant analyses, identified two groups of river with only one variable (% forested watershed) reliably distinguishing groups. Our second approach employed ordinal scaling to compare variables for each river to conceptually ideal conditions that were developed as a composite of optimal attributes among the 10 rivers. The composite distance of each river from ideal was then calculated using a unidimensional ranking technique. Two rivers without Wild and Scenic River designation ranked highest relative to ideal (highest ecological integrity), and two others, also without designation, ranked most distant from ideal (lowest ecological integrity). Fish density, number of intolerant fish species, and invertebrate density were influential biotic variables for scaling. Contributing physical variables included riparian forest cover, water nitrate concentration, water turbidity, percentage of forested watershed, percentage of private land ownership, and road density. These methods provide a framework for refinement and application in other regions to facilitate the process of establishing least-disturbed reference conditions and identifying rivers for protection and restoration. ?? 2005 Springer Science+Business Media, Inc.

Environmental Management↗