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USGS2007

Surface-Water Conditions in Georgia, Water Year 2005

INTRODUCTION The U.S. Geological Survey (USGS) Georgia Water Science Center-in cooperation with Federal, State, and local agencies-collected surface-water streamflow, water-quality, and ecological data during the 2005 Water Year (October 1, 2004-September 30, 2005). These data were compiled into layers of an interactive ArcReaderTM published map document (pmf). ArcReaderTM is a product of Environmental Systems Research Institute, Inc (ESRI?). Datasets represented on the interactive map are * continuous daily mean streamflow * continuous daily mean water levels * continuous daily total precipitation * continuous daily water quality (water temperature, specific conductance dissolved oxygen, pH, and turbidity) * noncontinuous peak streamflow * miscellaneous streamflow measurements * lake or reservoir elevation * periodic surface-water quality * periodic ecological data * historical continuous daily mean streamflow discontinued prior to the 2005 water year The map interface provides the ability to identify a station in spatial reference to the political boundaries of the State of Georgia and other features-such as major streams, major roads, and other collection stations. Each station is hyperlinked to a station summary showing seasonal and annual stream characteristics for the current year and for the period of record. For continuous discharge stations, the station summary includes a one page graphical summary page containing five graphs, a station map, and a photograph of the station. The graphs provide a quick overview of the current and period-of-record hydrologic conditions of the station by providing a daily mean discharge graph for the water year, monthly statistics graph for the water year and period of record, an annual mean streamflow graph for the period of record, an annual minimum 7-day average streamflow graph for the period of record, and an annual peak streamflow graph for the period of record. Additionally, data can be accessed through the layer's link to the National Water Inventory System Web (NWISWeb) Interface.

Georgia↗

USGS2007

Accumulation of metals in fish from lead-zinc mining areas of southeastern Missouri, USA

The potential effects of proposed lead-zinc mining in an ecologically sensitive area were assessed by studying a nearby mining district that has been exploited for about 30 yr under contemporary environmental regulations and with modern technology. Blood and liver samples representing fish of three species (largescale stoneroller, Campostoma oligolepis, n=91; longear sunfish, Lepomis megalotis, n=105; and northern hog sucker, Hypentelium nigricans, n=20) were collected from 16 sites representing a range of conditions relative to lead-zinc mining and ore beneficiation in southeastern Missouri. Samples were analyzed for lead, zinc, and cadmium, and for a suite of biomarkers (reported in a companion paper). A subset of the hog sucker (n=9) representing three sites were also analyzed for nickel and cobalt. Blood and liver lead concentrations were highly correlated (r=0.84-0.85, P < 0.01) in all three species and were significantly (ANOVA, P < 0.01) greater at sites < 10 km downstream of active lead-zinc mines and mills and in a historical lead-zinc mining area than at reference sites, including a site in the area proposed for new mining. Correlations between blood and liver cadmium concentrations were less evident than for lead but were nevertheless statistically significant (r=0.26-0.69, P < 0.01-0.07). Although blood and liver cadmium concentrations were highest in all three species at sites near mines, within-site variability was greater and mining-related trends were less evident than for lead. Blood and liver zinc concentrations were significantly correlated only in stoneroller (r=0.46, P < 0.01) and mining-related trends were not evident. Concentrations of cobalt and nickel in blood and liver were significantly higher (ANOVA, P < 0.01) at a site near an active mine than at a reference site and a site in the historical lead-zinc mining area. These findings confirm previous studies indicating that lead and other metals are released to streams from active lead-zinc mines and are available for uptake by aquatic organisms. ?? 2006 Elsevier Inc. All rights reserved.

Ecotoxicology and Environmental Safety↗

USGS2015

Floodplain complexity and surface metrics: influences of scale and geomorphology

Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.

Geomorphology↗

USGS2012

StreamStats in North Carolina: A water-resources Web application

A statewide StreamStats application for North Carolina was developed in cooperation with the North Carolina Department of Transportation following completion of a pilot application for the upper French Broad River basin in western North Carolina (Wagner and others, 2009). StreamStats for North Carolina, available at http://water.usgs.gov/osw/streamstats/north_carolina.html, is a Web-based Geographic Information System (GIS) application developed by the U.S. Geological Survey (USGS) in consultation with Environmental Systems Research Institute, Inc. (Esri) to provide access to an assortment of analytical tools that are useful for water-resources planning and management (Ries and others, 2008). The StreamStats application provides an accurate and consistent process that allows users to easily obtain streamflow statistics, basin characteristics, and descriptive information for USGS data-collection sites and user-selected ungaged sites. In the North Carolina application, users can compute 47 basin characteristics and peak-flow frequency statistics (Weaver and others, 2009; Robbins and Pope, 1996) for a delineated drainage basin. Selected streamflow statistics and basin characteristics for data-collection sites have been compiled from published reports and also are immediately accessible by querying individual sites from the web interface. Examples of basin characteristics that can be computed in StreamStats include drainage area, stream slope, mean annual precipitation, and percentage of forested area (Ries and others, 2008). Examples of streamflow statistics that were previously available only through published documents include peak-flow frequency, flow-duration, and precipitation data. These data are valuable for making decisions related to bridge design, floodplain delineation, water-supply permitting, and sustainable stream quality and ecology. The StreamStats application also allows users to identify stream reaches upstream and downstream from user-selected sites and obtain information for locations along streams where activities occur that may affect streamflow conditions. This functionality can be accessed through a map-based interface with the user’s Web browser, or individual functions can be requested remotely through Web services (Ries and others, 2008).

North Carolina↗

USGS2016

A global review of freshwater crayfish temperature tolerance, preference, and optimal growth

Conservation efforts, environmental planning, and management must account for ongoing ecosystem alteration due to a changing climate, introduced species, and shifting land use. This type of management can be facilitated by an understanding of the thermal ecology of aquatic organisms. However, information on thermal ecology for entire taxonomic groups is rarely compiled or summarized, and reviews of the science can facilitate its advancement. Crayfish are one of the most globally threatened taxa, and ongoing declines and extirpation could have serious consequences on aquatic ecosystem function due to their significant biomass and ecosystem roles. Our goal was to review the literature on thermal ecology for freshwater crayfish worldwide, with emphasis on studies that estimated temperature tolerance, temperature preference, or optimal growth. We also explored relationships between temperature metrics and species distributions. We located 56 studies containing information for at least one of those three metrics, which covered approximately 6 % of extant crayfish species worldwide. Information on one or more metrics existed for all 3 genera of Astacidae, 4 of the 12 genera of Cambaridae, and 3 of the 15 genera of Parastacidae. Investigations employed numerous methodological approaches for estimating these parameters, which restricts comparisons among and within species. The only statistically significant relationship we observed between a temperature metric and species range was a negative linear relationship between absolute latitude and optimal growth temperature. We recommend expansion of studies examining the thermal ecology of freshwater crayfish and identify and discuss methodological approaches that can improve standardization and comparability among studies.

Reviews in Fish Biology and Fisheries↗

USGS2022

Higher temperature sensitivity of flowering than leaf-out alters the time between phenophases across temperate tree species

Aim The aims of this study were to evaluate the changes in the length of the time period between leaf-out and flowering across temperate tree species, and associate these changes with potential physiological and environmental drivers to enhance mechanistic insight into these phenomena. Location Central Europe. Time period 1980–2016. Major taxa studied Six temperate woody species. Methods Statistical analyses were carried out based on long-term ground observations of both spring leaf-out and flowering across temperate tree species during 1980–2016, a period characterized by rapid warming. Results The temperature sensitivity of flowering (−5.4 ± 0.04 days/℃, mean ± SE ) was higher than that of leaf-out (−4.6 ± 0.04 days/℃) across all species, regardless of whether leaf-out occurred before or after flowering. This study postulates a hypothesis attributing the different temperature sensitivities to different thermal sensitivities, thermal requirements, and photoperiodic controls. Main conclusions The larger temperature sensitivity of flowering than leaf-out resulted in an extended time period between flowering and leaf-out in species that bloom before leafing out, but a shorter time period between these phenophases in species with the opposite strategy. We would like to emphasize the importance of changes in time period between different phenophases, and we recommend conducting experimental research to reveal the underlying mechanisms of plant phenology response to climate change, and to explore its potential ecological implications.

Global Ecology and Biogeography↗

USGS2017

What mediates tree mortality during drought in the southern Sierra Nevada?

Severe drought has the potential to cause selective mortality within a forest, thereby inducing shifts in forest species composition. The southern Sierra Nevada foothills and mountains of California have experienced extensive forest dieback due to drought stress and insect outbreak. We used high-fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) from the Carnegie Airborne Observatory (CAO) to estimate the effect of forest dieback on species composition in response to drought stress in Sequoia National Park. Our aims were: (1) to quantify site-specific conditions that mediate tree mortality along an elevation gradient in the southern Sierra Nevada Mountains; (2) to assess where mortality events have a greater probability of occurring; and (3) to estimate which tree species have a greater likelihood of mortality along the elevation gradient. A series of statistical models were generated to classify species composition and identify tree mortality, and the influences of different environmental factors were spatially quantified and analyzed to assess where mortality events have a greater likelihood of occurring. A higher probability of mortality was observed in the lower portion of the elevation gradient, on southwest and west-facing slopes, in areas with shallow soils, on shallower slopes, and at greater distances from water. All of these factors are related to site water balance throughout the landscape. Our results also suggest that mortality is species-specific along the elevation gradient, mainly affecting Pinus ponderosa and Pinus lambertiana at lower elevations. Selective mortality within the forest may drive long-term shifts in community composition along the elevation gradient.

Sierra Nevada↗

USGS2019

Flow modification in the Nation’s streams and rivers

This report summarizes a national assessment of flowing waters conducted by the U.S. Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Project and addresses several pressing questions about the modification of natural flows in streams and rivers. The assessment is based on the integration, modeling, and synthesis of monitoring data collected by the USGS and the U.S. Environmental Protection Agency at more than 7,000 streams and rivers across the conterminous United States from 1980 to 2014. Key findings include the following. First, flow in many of the Nation’s streams and rivers is different from what it would be under natural conditions. In particular, low flows are more frequent, are of shorter duration, and vary less from one year to the next than they would naturally. In addition, high flows have been reduced in magnitude, are of shorter duration, are less frequent, and vary less from one year to the next than they would naturally. Other characteristics of natural flows also have been modified. Second, over the last 60 years (1955–2014), climatic trends have caused a change of 50 percent or more in one or more streamflow attributes at two-thirds of climate-sensitive streamgaging sites. However, these climate-induced changes have been less influential on streamflow modification than have land and water-management practices. Third, in every region assessed, streamflow modification was associated with reduced ecological health, as indicated by two biological communities—invertebrates and fish. Biological communities were increasingly likely to be impaired (defined as having lost a statistically significant number of species) in streams with flows most different from natural conditions. Finally, several case studies are presented that illustrate viable management strategies for balancing the water needs of people and ecosystems.

Circular↗

USGS2022

Using a vegetation index to assess wetland condition in the Prairie Pothole Region of North America

Wetlands deliver a suite of ecosystem services to society. Anthropogenic activities, such as wetland drainage, have resulted in considerable wetland loss and degradation, diminishing the intrinsic value of wetland ecosystems worldwide. Protecting remaining wetlands and restoring degraded wetlands are common management practices to preserve and reclaim wetland benefits to society. Accordingly, methods for monitoring and assessing wetlands are required to evaluate their ecologic condition and outcomes of restoration activities. We used an established methodology for conducting vegetation-based assessments and describe a case study consisting of a wetland condition assessment in the Prairie Pothole Region of the North American Great Plains. We provide an overview of an existing method for selecting wetlands to sample across broad geographic distributions using a spatially balanced statistical design. We also describe site assessment protocols, including vegetation survey methods, and how field data were applied to a vegetation index that categorized wetlands according to ecologic condition. Results of the case study indicated that vegetation communities in nearly 50% of the surveyed wetlands were in very poor or poor condition, while only about 25% were considered good or very good . Approximately 70% of wetlands in native grasslands were categorized as good or very good compared to only 12% of those in reseeded grasslands (formerly cropland). In terms of informing restoration and management activities, results indicated that improved restoration practices could include a greater focus on establishing natural vegetation communities, and both restored and native prairie wetlands would benefit from enhanced management of invasive species.

Prairie Pothole Region↗

USGS2002

Environmental setting and water-quality issues of the Mobile River Basin, Alabama, Georgia, Mississippi, and Tennessee

The Mobile River Basin is one of over 50 river basins and aquifer systems being investigated as part of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program. This basin is the sixth largest river basin in the United States, and fourth largest in terms of streamflow, encompassing parts of Alabama, Georgia, Mississippi, and Tennessee. Almost two-thirds of the 44,000-square-mile basin is located in Alabama. Extensive water resources of the Mobile River Basin are influenced by an array of natural and cultural factors. These factors impart unique and variable qualities to the streams, rivers, and aquifers providing abundant habitat to sustain the diverse aquatic life in the basin. Data from Federal, State, and local agencies provide a description of the environmental setting of the Mobile River Basin. Environmental data include natural factors such as physiography, geology, soils, climate, hydrology, ecoregions, and aquatic ecology, and human factors such as reservoirs, land use and population change, water use, and water-quality issues. Characterization of the environmental setting is useful for understanding the physical, chemical, and biological characteristics of surface and ground water in the Mobile River Basin and the possible implications of that environmental setting for water quality. The Mobile River Basin encompasses parts of five physiographic provinces. Fifty-six percent of the basin lies within the East Gulf section of the Coastal Plain Physiographic Province. The remaining northeastern part of the basin lies, from west to east, within the Cumberland Plateau section of the Appalachian Plateaus Physiographic Province, the Valley and Ridge Physiographic Province, the Piedmont Physiographic Province, and the Blue Ridge Physiographic Province. Based on the 1991 land-use data, about 70 percent of the basin is forested, while agriculture, including livestock (poultry, cattle, and swine), row crops (cotton, corn, soybeans, sorghum, and wheat), and pasture land accounts for about 26 percent of the study unit. Agricultural land use is concentrated along the Black Prairie Belt district of the Coastal Plain. Urban areas account for only 3 percent of the total land use; however, the areal extent of the metropolitan statistical areas (MSA) may indicate more urban influences. The MSAs include urban areas outside of the city boundaries and can include adjacent counties. Seven MSAs are delineated in the Mobile River Basin, including Montgomery, Mobile, Tuscaloosa, Birmingham, Gadsden, Anniston, and Atlanta. The total population for the Mobile River Basin was about 3,673,100 in 1990. State water-quality agencies have identified numerous causes and sources of water-body impairment in the Mobile River Basin. In 1996, organic enrichment, dissolved oxygen depletion, elevated nutrient concentrations, and siltation were the most frequently cited causes of impairment, affecting the greatest number of river miles. Bacteria, acidic pH, and elevated metal concentrations also were identified as causes of impairment. The sources for impairment varied among river basins, were largely a function of land use, and were attributed primarily to municipal and industrial sources, mining, and agricultural activities.

Water-Resources Investigations Report↗

USGS2021

Habitat suitability index model improvement recommendations

As part of the model improvement effort for the 2023 Coastal Master Plan, the Habitat Suitability Index (HSI) models used during previous master plans were reevaluated to assess how the model relationships could be improved, and to determine what species should be included in the master plan analyses. This process considered the technical reviews, comments, and suggested improvements provided by model developers, advisory groups, and other experts during previous master plans. Reviews were then conducted to determine the availability of data and information that could be used to make model improvements. As a result of this effort, a recommended list of relevant species to model is provided, and HSI model improvements are recommended that are categorized by whether the suitability index (SI) relationship to be improved is statistical-based or literature-based. The species recommended to be included in the 2023 Coastal Master Plan analyses are: eastern oyster, brown shrimp, white shrimp, blue crab, crayfish, gulf menhaden, spotted seatrout, largemouth bass, American alligator, gadwall, mottled duck, brown pelican, seaside sparrow, and bald eagle. These species were selected because they represent a range of taxonomies, life histories, trophic levels, and habitats, and most are commercially- or recreationally-important in coastal Louisiana. Most of these species were also included in the 2017 Coastal Master Plan analyses, and the models used during that effort should be further improved. Seaside sparrow and bald eagle are new for the master plan, and new models should be developed for the analyses. The 2017 fish, shrimp, and blue crab HSI models included a water quality SI that was based on statistical analyses of species catch and environmental data collected by the Louisiana Department of Wildlife and Fisheries. As suggested during the 2017 Coastal Master Plan, the modeling approach used to develop the water quality SI was revisited and alternate modeling approaches were explored. Using literature and an evaluation of the general steps of model development, three components for HSI model improvement were identified, including 1) selecting alternative modeling approach(es); 2) detecting and resolving statistical issues; and 3) improving model fit and evaluation. Multiple options for each component were explored, which resulted in a proposed multi-step phased approach for model improvement. This proposed approach entails improving the generalized linear models used for the 2017 water quality SIs and then, if desired, comparing them to alternative model approaches (e.g., generalized additive models) to explore model performance and select the best approach to use for the 2023 Coastal Master Plan HSI models. All of the existing master plan HSI models include literature-based SIs, which use information from published studies of species-habitat associations to derive suitability relationships. Similar to previous master plans, these literature-based SIs should be updated and improved for the 2023 Coastal Master Plan using recent literature and new ecological knowledge. Preliminary reviews were conducted and recent information was found that could be used to improve the eastern oyster, crayfish, and potentially brown pelican HSI models; but no appropriate recent literature was located for improvement of the American alligator, gadwall, and mottled duck HSI models. However, it is recommended that the literature reviews and information searches be continued. In addition to the statistical-based water quality SI, the 2017 fish, shrimp, and blue crab HSI models also included a structural habitat SI that was based on literature showing high densities of these species in fragmented marsh. The relationship used for this SI, however, did not account for the effects of other estuarine habitats, such as submerged aquatic vegetation and oyster reefs, which are also important to these species. Therefore, a meta-analysis approach is proposed that would estimate the relative importance of these habitats for each species, and the results of this analysis could be used to calculate a new structural habitat SI for the 2023 Coastal Master Plan.

Report↗

USGS2019

Impacts to wildlife of wind energy siting and operation in the United States

Electricity from wind energy is a major contributor to the strategy to reduce greenhouse gas emissions from fossil fuel use and thus reduce the negative impacts of climate change. Wind energy, like all power sources, can have adverse impacts on wildlife. After nearly 25 years of focused research, these impacts are much better understood, although uncertainty remains. In this report, we summarize positive impacts of replacing fossil fuels with wind energy, while describing what we have learned and what remains uncertain about negative ecological impacts of the construction and operation of land-based and offshore wind energy on wildlife and wildlife habitat in the U.S. Finally, we propose research on ways to minimize these impacts. TO SUMMARIZE: 1 Environmental and other benefits of wind energy include near-zero greenhouse gas emissions, reductions of other common air pollutants, and little or no water use associated with producing electricity from wind energy. Various scenarios for meeting U.S. carbon emission reduction goals indicate that a four- to five-fold expansion of land-based wind energy from the current 97 gigawatts (GW) by the year 2050 is needed to minimize temperature increases and reduce the risk of climate change to people and wildlife. 2 Collision fatalities of birds and bats are the most visible and measurable impacts of wind energy production. Current estimates suggest most bird species, especially songbirds, are at low risk of population-level impacts. Raptors as a group appear more vulnerable to collisions. Population-level impacts on migratory tree bats are a concern, and better information on population sizes is needed to evaluate potential impacts to these species. Although recorded fatalities of cave-dwelling bat species are typically low at most wind energy facilities, additional mortality from collisions is a concern given major declines in these species due to white-nose syndrome (WNS). Assessments of regional and cumulative fatality impacts for birds and bats have been hampered by the lack of data from areas with a high proportion of the nation’s installed wind energy capacity. Efforts to expand data accessibility from all regions are underway, and this greater access to data along with improvements in statistical estimators should lead to improved impact assessments. 3 Habitat impacts of wind energy development are difficult to assess. An individual wind energy facility may encompass thousands of acres, but only a small percentage of the landscape within the project area is directly transformed. If a project is sited in previously undisturbed habitat, there is concern for indirect impacts, such as displacement of sensitive species. Studies to date indicate displacement of some species, but the long-term population impacts are unknown. 4 Offshore wind energy development in the U.S. is just beginning. Studies at offshore wind facilities in Europe indicate some bird and marine mammal species are displaced from project areas, but substantial uncertainty exists regarding the individual or population-level impacts of this displacement. Bird and bat collisions with offshore turbines are thought to be less common than at terrestrial facilities, but currently the tools to measure fatalities at offshore wind energy facilities are not available. The wind energy industry, state and federal agencies, conservation groups, academia, and scientific organizations have collaborated for nearly 25 years to conduct the research needed to improve our understanding of risk to wildlife and to avoid and minimize that risk. Efforts to reduce the uncertainty about wildlife risk must keep up withthe pace and scale of the need to reduce carbon emissions. This will require focusing our research priorities and increasing the rate at which we incorporate research results into the development and validation of best practices for siting and operating wind energy facilities.

Issues in Ecology↗

USGS2022

A statistical framework for modelling migration corridors

1. Management of animal populations requires spatially explicit knowledge of movement corridors, such as those used during seasonal migrations. GPS tracking data allows for mapping of corridors from directly observed movements, providing important insights, but tracking data is absent for many populations. 2. We developed a novel statistical corridor modeling approach that predicts movement corridors from cost-distance movement models fit directly to migration tracking data. Unlike existing predictive approaches, this does not require the ad-hoc transformation of habitat suitability surfaces into resistance surfaces. We tested the ability of the approach to recover parameters used to generate simulated movements. We then used GPS data from three migrating mule deer (Odocoileus hemionus) herds in Idaho and Wyoming to model corridors as a function of elevation, slope, aspect, percent shrub, date of peak green-up, snow-off date, and human footprint. We assessed the predictive ability of the fitted models using validation tracks from the same herd as well as from the other herds. 3. The approach reproduced parameters used to generate the simulated movements, predicted the corridors used by migratory populations, and described the direction, magnitude, and confidence levels of the effects of environmental variables on corridors. The effects environmental variables had on corridors differed depending on the herd. Within-herd validation indicated that fitted corridor models are more accurate at predicting migration corridors than null models, and cross-herd validation indicated that fitted models for some herds accurately predicted the observed migrations of other herds. 4. In addition to the practical benefit of mapping corridors for management, our statistical corridor modeling framework sets the stage for evaluating fundamental questions about the fitness tradeoffs, navigation, learning, fidelity, and movement constraints that influence migratory and other corridor-generating behavior. Models of predictive corridors can inform management and planning for the conservation of migrations across taxa, including the potential restoration of corridors. Our corridor modeling approach is also readily applied to non-migratory animal movements.

Idaho, Wyoming↗

USGS2007

Year-class formation of upper St. Lawrence River northern pike

Variables associated with year-class formation in upper St. Lawrence River northern pike Esox lucius were examined to explore population trends. A partial least-squares (PLS) regression model (PLS 1) was used to relate a year-class strength index (YCSI; 1974-1997) to explanatory variables associated with spawning and nursery areas (seasonal water level and temperature and their variability, number of ice days, and last day of ice presence). A second model (PLS 2) incorporated four additional ecological variables: potential predators (abundance of double-crested cormorants Phalacrocorax auritus and yellow perch Perca flavescens), female northern pike biomass (as a measure of stock-recruitment effects), and total phosphorus (productivity). Trends in adult northern pike catch revealed a decline (1981-2005), and year-class strength was positively related to catch per unit effort (CPUE; R2 = 0.58). The YCSI exceeded the 23-year mean in only 2 of the last 10 years. Cyclic patterns in the YCSI time series (along with strong year-classes every 4-6 years) were apparent, as was a dampening effect of amplitude beginning around 1990. The PLS 1 model explained over 50% of variation in both explanatory variables and the dependent variable, YCSI first-order moving-average residuals. Variables retained (N = 10; Wold's statistic ??? 0.8) included negative YCSI associations with high summer water levels, high variability in spring and fall water levels, and variability in fall water temperature. The YCSI exhibited positive associations with high spring, summer, and fall water temperature, variability in spring temperature, and high winter and spring water level. The PLS 2 model led to positive YCSI associations with phosphorus and yellow perch CPUE and a negative correlation with double-crested cormorant abundance. Environmental variables (water level and temperature) are hypothesized to regulate northern pike YCSI cycles, and dampening in YCSI magnitude may be related to a combination of factors, including wetland habitat changes, reduced nutrient loading, and increased predation by double-crested cormorants. ?? Copyright by the American Fisheries Society 2007.

North American Journal of Fisheries Management↗

USGS2026

Investigating hydrologic alteration under historical and future scenarios in the Mobile River and Perdido River basins using the cubist algorithm

This study investigates the impacts of human activities and climate variability on hydrologic alterations in the Mobile River and Perdido River Basins of Alabama. The research uses a machine learning approach, specifically cubist models, to quantify and predict changes in flow duration curves (FDCs) under both historical (1980–2009) and future climate scenarios. Future climate projections include the Representative Concentration Pathways (RCP 4.5 and RCP 8.5) and the Shared Socioeconomic Pathways (SSP2 4.5 and SSP5 8.5), evaluated for two future periods: 1980–2069 and 1980–2099. The models incorporate a wide range of covariates, including basin geomorphology, aquifer characteristics, land cover, water storage, environmental factors, solar radiation, census data, and water use data. Under the baseline period (1980–2009), most level 12 hydrologic unit codes (HUC12s) in both basins showed alterations, with substantial differences observed between pre- and post-alteration FDCs. The model performance varied, with a Nash–Sutcliffe Efficiency between 0.91 and 0.95 for testing and between 0.98 and 0.99 for training during the baseline period. Future projections under the RCP 4.5 and RCP 8.5 scenarios generally differed significantly from baseline conditions across all flow regimes ( p < 0.05). In contrast, SSP2 4.5 showed comparatively limited statistical significance, while SSP5 8.5 exhibited significant departures from baseline conditions across all flow regimes, reflecting the greater influence of high-emissions climate forcing on projected hydrologic alterations. Overall, the RCP scenarios projected more widespread statistically significant changes than the corresponding SSP scenarios at the same forcing level, particularly when comparing RCP4.5 with SSP2-4.5, while both RCP8.5 and SSP5-8.5 consistently indicated greater hydrologic alterations than their moderate-emissions counterparts. These findings highlight the importance of considering different flow regimes when assessing the impacts of climate variability on streamflow. This study contributes to the understanding of hydrologic alterations in the Mobile River and Perdido River Basins, providing insights for water resource management and ecological conservation efforts in the region.

Alabama↗

USGS2015

Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery

Fluvial sediment, a vital surface water resource, is hazardous in excess. Suspended sediment, the most prevalent source of impairment of river systems, can adversely affect flood control, navigation, fisheries and aquatic ecosystems, recreation, and water supply (e.g., Rasmussen et al., 2009; Qu, 2014). Monitoring programs typically focus on suspended-sediment concentration (SSC) and discharge (SSQ). These time-series data are used to study changes to basin hydrology, geomorphology, and ecology caused by disturbances. The U.S. Geological Survey (USGS) has traditionally used physical sediment sample-based methods (Edwards and Glysson, 1999; Nolan et al., 2005; Gray et al., 2008) to compute SSC and SSQ from continuous streamflow data using a sediment transport-curve (e.g., Walling, 1977) or hydrologic interpretation (Porterfield, 1972). Accuracy of these data is typically constrained by the resources required to collect and analyze intermittent physical samples. Quantifying SSC using continuous instream turbidity is rapidly becoming common practice among sediment monitoring programs. Estimations of SSC and SSQ are modeled from linear regression analysis of concurrent turbidity and physical samples. Sediment-surrogate technologies such as turbidity promise near real-time information, increased accuracy, and reduced cost compared to traditional physical sample-based methods (Walling, 1977; Uhrich and Bragg, 2003; Gray and Gartner, 2009; Rasmussen et al., 2009; Landers et al., 2012; Landers and Sturm, 2013; Uhrich et al., 2014). Statistical comparisons among SSQ computation methods show that turbidity-SSC regression models can have much less uncertainty than streamflow-based sediment transport-curves or hydrologic interpretation (Walling, 1977; Lewis, 1996; Glysson et al., 2001; Lee et al., 2008). However, computation of SSC and SSQ records from continuous instream turbidity data is not without challenges; some of these include environmental fouling, calibration, and data range among sensors. Of greatest interest to many programs is a hysteresis in the relationship between turbidity and SSC, attributed to temporal variation of particle size distribution (Landers and Sturm, 2013; Uhrich et al., 2014). This phenomenon causes increased uncertainty in regression-estimated values of SSC, due to changes in nephelometric reflectance off the varying grain sizes in suspension (Uhrich et al., 2014). Here, we assess the feasibility and application of close-range remote sensing to quantify SSC and particle size distribution of a disturbed, and highly-turbid, river system. We use a consumer-grade digital camera to acquire imagery of the river surface and a depth-integrating sampler to collect concurrent suspended-sediment samples. We then develop two empirical linear regression models to relate image spectral information to concentrations of fine sediment (clay to silt) and total suspended sediment. Before presenting our regression model development, we briefly summarize each data-acquisition method.

Conference Paper↗

USGS2007

Scale-dependent approaches to modeling spatial epidemiology of chronic wasting disease.

This e-book is the product of a second workshop that was funded and promoted by the United States Geological Survey to enhance cooperation between states for the management of chronic wasting disease (CWD). The first workshop addressed issues surrounding the statistical design and collection of surveillance data for CWD. The second workshop, from which this document arose, followed logically from the first workshop and focused on appropriate methods for analysis, interpretation, and use of CWD surveillance and related epidemiology data. Consequently, the emphasis of this e-book is on modeling approaches to describe and gain insight of the spatial epidemiology of CWD. We designed this e-book for wildlife managers and biologists who are responsible for the surveillance of CWD in their state or agency. We chose spatial methods that are popular or common in the spatial epidemiology literature and evaluated them for their relevance to modeling CWD. Our opinion of the usefulness and relevance of each method was based on the type of field data commonly collected as part of CWD surveillance programs and what we know about CWD biology, ecology, and epidemiology. Specifically, we expected the field data to consist primarily of the infection status of a harvested or culled sample along with its date of collection (not date of infection), location, and demographic status. We evaluated methods in light of the fact that CWD does not appear to spread rapidly through wild populations, relative to more highly contagious viruses, and can be spread directly from animal to animal or indirectly through environmental contamination. We discovered that many of the wellpublished methods were developed for fast-spreading human diseases, such as influenza and measles. While these methods are applicable to fast spreading wildlife diseases, such as foot-and-mouth disease or West Nile virus, many are not likely to work well for CWD. Only limited data exist to evaluate geographic and spatial spread because many locations where we find CWD tend to be locations where samples have just been taken or sample sizes have just become large enough to have a high probability of detecting a low prevalence. Consequently, methods that work well to describe or predict the spread of foot-and-mouth disease throughout England, which occurred within a year, do not work well for describing or predicting CWD spread. We did not exclude methods that we regarded as inappropriate; rather, we included methods that are commonly used for disease epidemiology and then discussed their applicability for modeling the spatial epidemiology of CWD. We hope including inappropriate methods with an explanation of why they are ill-suited for CWD will make it easier to drop them from consideration and explain to others why they were not recommended for spatial modeling of CWD. We organized the three chapters by scale and extent for which each method was developed or best suited. The first chapter covers methods appropriate to multi-jurisdictional or multi-state modeling, which we call “regional” scale. The second chapter covers methods appropriate for within state areas such as wildlife management units or metapopulations, which we call “landscape” scale. The third chapter covers methods appropriate for population or individual-based modeling, which we call “fine” scale. We know this rubric is somewhat artificial because many methods work at multiple scales. We hope, however, that this structure addresses some of the challenges faced by managers that work at local, regional, state, and national scales. Further, the resolution of empirical data often changes with spatial scale, which affects the utility of different modeling approaches. For example, individual-based models work best at modeling spread within populations, while risk analysis is most useful for summarizing data over larger scales such as a region. Because some methods are applicable at several scales, however, we included a graphic at the beginning of each method that indicates the range of scales for which it applies. For example, the graphic to the right indicates that the method is most applicable for regional-scale modeling. There is also a question of resolution as well as scale and extent for each method. CWD surveillance data have been collected over large areas, such as a wildlife management unit or state, but the resolution of the data may be fine scale with GPS locations for many samples. For each method, we described the required resolution of the data and describe the type of data required, as well as what questions the method could answer and how useful the method is, given typical CWD data. For each scale, we presented a focal approach that would be useful for understanding the spatial pattern and epidemiology of CWD, as well as being a useful tool for CWD management. The focal approaches include risk analysis and micromaps for the regional scale, cluster analysis for the landscape scale, and individual based modeling for the fine scale of within population. For each of these methods, we used simulated data and walked through the method step by step to fully illustrate the “how to”, with specifics about what is input and output, as well as what questions the method addresses. We also provided a summary table to, at a glance, describe the scale, questions that can be addressed, and general data required for each method described in this e-book. We hope that this review will be helpful to biologists and managers by increasing the utility of their surveillance data, and ultimately be useful for increasing our understanding of CWD and allowing wildlife biologists and managers to move beyond retroactive fire-fighting to proactive preventative action.

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USGS1998

Assemblage organization in stream fishes: Effects of environmental variation and interspecific interactions

We assessed the relative importance of environmental variation, interspecific competition for space, and predator abundance on assemblage structure and microhabitat use in a stream fish assemblage inhabiting Coweeta Creek, North Carolina, USA. Our study encompassed a 10–yr time span (1983–1992) and included some of the highest and lowest flows in the last 58 years. We collected 16 seasonal samples which included data on: (1) habitat availability (total and microhabitat) and microhabitat diversity, (2) assemblage structure (i.e., the number and abundances of species comprising a subset of the community), and (3) microhabitat use and overlap. We classified habitat availability data on the basis of year, season, and hydrologic period. Hydrologic period (i.e., pre–drought [PR], drought [D], and post–drought [PO]) represented the temporal location of a sample with respect to a four–year drought that occurred during the study. Hydrologic period explained a greater amount of variance in habitat availability data than either season or year. Total habitat availability was significantly greater during PO than in PR or D, although microhabitat diversity did not differ among either seasons or hydrologic periods. There were significantly fewer high–flow events (i.e., ≥2.1 m 3 /s) during D than in either PR or PO periods. We observed a total of 16 species during our investigation, and the total number of species was significantly higher in D than in PR samples. Correlation analyses between the number of species present (total and abundant species) and environmental data yielded limited results, although the total number of species was inversely correlated with total habitat availability. A cluster analysis grouped assemblage structure samples by hydrologic period rather than season or year, supporting the contention that variation in annual flow had a strong impact on this assemblage. The drought had little effect on the numerical abundance of benthic species in this assemblage; however, a majority of water–column species increased in abundance. The increased abundances of water–column species may have been related to the decrease in high-flow events observed during the drought. Such high–flow events are known to cause mortality in stream fishes. Microhabitat use data showed that species belonged to one of three microhabitat guilds: benthic, lower water column, and mid water column. In general, species within the same guild did not exhibit statistically distinguishable patterns of microhabitat use, and most significant differences occurred between members of different guilds. However, lower water–column guild species frequentlywere not separable from all members of either benthic or mid–water–column species. Variations in the abundance of potential competitors or predators did not produce strong shifts in microhabitat use by assemblage members. Predators were present in the site in only 9 of 16 seasonal samples and never were abundant (maximum number observed per day was 2). In conclusion, our results demonstrate that variability in both mean and peak flows had a much stronger effect on the structure and use of spatial resources within this assemblage then either interspecific competition for space or predation. Consequently, we suspect that the patterns in both assemblage structure and resource use displayed by fishes in Coweeta Creek arose from the interaction between environmental variation and species–specific evolutionary constraints on behavior, morphology, and physiology.

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