Geology topics

Seth J. Wenger

Publications and source records attributed to Seth J. Wenger.

34 records · Page 2Linked to original sources

USGS2019

The missing dead: The lost role of animal remains in nutrient cycling in North American Rivers

While leaf litter, wood, and other plant remnants are known to play a central role in lotic ecosystems, animal remains (carcasses, bones, shells) have received less attention. We propose a simple classification scheme for animal remains in rivers based on origin (authochthonous vs. allochthonous) and frequency (pulsed vs continuous). We then present case studies in which we estimate the former biomass of several taxonomic groups that are now diminished in abundance to determine whether their remains could have historically constituted a significant flux of nutrients in rivers of North America. We focus on bones and shells, which decompose slowly and could provide long-term reservoirs of nutrients. We find that carcasses of alligator snapping turtles, once abundant in southeastern rivers, could have provided an amount of phosphorus equivalent to about 1% of total phosphorus (TP) load at median flow, and more at low flows. Mussel shells could have contributed a similar amount (0.8% of TP) but the contribution of beaver carcasses, even at former abundances, was likely small. In contrast, a single documented mass drowning of bison in the Assiniboine River could have contributed half the annual TP load for that river. Such drownings could have been a common occurrence prior to the loss of most wild terrestrial megafauna in North America. We conclude that animal remnants, particularly allochthonous remains from terrestrial animals, formerly played a substantial role in nutrient cycling. Existing models of ecosystem function under reference conditions are incomplete without consideration of these lost animal legacies.

Food Webs↗

USGS2018

Hierarchical multi-population viability analysis

Population viability analysis (PVA) uses concepts from theoretical ecology to provide a powerful tool for quantitative estimates of population dynamics and extinction risks. However, conventional statistical PVA requires long-term data from every population of interest, whereas many species of concern exist in multiple isolated populations that are only monitored occasionally. We present a hierarchical multi-population viability analysis model that increases inference power from sparse data by sharing information among populations to assess extinction risks while accounting for incomplete detection and sampling biases with explicit observation and sampling sub-models. We present a case study in which we customized this model for historical population monitoring data (1985–2015) from federally threatened Lahontan cutthroat trout populations in the Great Basin, USA. Data were counts of fish captured during backpack electrofishing surveys from locations associated with 155 isolated populations. Some surveys (25%) included multi-pass removal sampling, which provided valuable information about capture efficiency. GIS and remote sensing were used to estimate August stream temperatures, peak flows, and riparian vegetation condition in each population each year. Field data were used to derive an annual index of nonnative trout densities. Results indicated that population growth rates were higher in colder streams and that nonnative trout reduced carrying capacities of native trout. Extinction risks increased with more environmental stochasticity and were also related to population extent, water temperatures, and nonnative densities. We developed a graphical user interface to interact with the fitted model results and to simulate future habitat scenarios and management actions to assess their influence on extinction risks in each population. Hierarchical multi-population viability analysis bridges the gap between site-level field observations and population-level processes, making effective use of existing datasets to support management decisions with robust estimates of population dynamics, extinction risks, and uncertainties.

Ecology↗

USGS2018

Stream fish colonization but not persistence varies regionally across a large North American river basin

Many species have distributions that span distinctly different physiographic regions, and effective conservation of such taxa will require a full accounting of all factors that potentially influence populations. Ecologists recognize effects of physiographic differences in topography, geology and climate on local habitat configurations, and thus the relevance of landscape heterogeneity to species distributions and abundances. However, research is lacking that examines how physiography affects the processes underlying metapopulation dynamics. We used data describing occupancy dynamics of stream fishes to evaluate evidence that physiography influences rates at which individual taxa persist in or colonize stream reaches under different flow conditions. Using periodic survey data from a stream fish assemblage in a large river basin that encompasses multiple physiographic regions, we fit multi-species dynamic occupancy models. Our modeling results suggested that stream fish colonization but not persistence was strongly governed by physiography, with estimated colonization rates considerably higher in Coastal Plain streams than in Piedmont and Blue Ridge systems. Like colonization, persistence was positively related to an index of stream flow magnitude, but the relationship between flow and persistence did not depend on physiography. Understanding the relative importance of colonization and persistence, and how one or both processes may change across the landscape, is critical information for the conservation of broadly distributed taxa, and conservation strategies explicitly accounting for spatial variation in these processes are likely to be more successful for such taxa.

Alabama, Florida, Georgia↗

USGS2017

The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user-community and predict broad climate warming of rivers and streams

Thermal regimes are fundamental determinants of aquatic ecosystems, which makes description and prediction of temperatures critical during a period of rapid global change. The advent of inexpensive temperature sensors dramatically increased monitoring in recent decades, and although most monitoring is done by individuals for agency‐specific purposes, collectively these efforts constitute a massive distributed sensing array that generates an untapped wealth of data. Using the framework provided by the National Hydrography Dataset, we organized temperature records from dozens of agencies in the western U.S. to create the NorWeST database that hosts >220,000,000 temperature recordings from >22,700 stream and river sites. Spatial‐stream‐network models were fit to a subset of those data that described mean August water temperatures (AugTw) during 63,641 monitoring site‐years to develop accurate temperature models ( r 2 = 0.91; RMSPE = 1.10°C; MAPE = 0.72°C), assess covariate effects, and make predictions at 1 km intervals to create summer climate scenarios. AugTw averaged 14.2°C (SD = 4.0°C) during the baseline period of 1993–2011 in 343,000 km of western perennial streams but trend reconstructions also indicated warming had occurred at the rate of 0.17°C/decade (SD = 0.067°C/decade) during the 40 year period of 1976–2015. Future scenarios suggest continued warming, although variation will occur within and among river networks due to differences in local climate forcing and stream responsiveness. NorWeST scenarios and data are available online in user‐friendly digital formats and are widely used to coordinate monitoring efforts among agencies, for new research, and for conservation planning.

Arizona, California, Colorado, Idaho, Montana, Nev↗

USGS2017

States and rates: Complementary approaches to developing flow‐ecology relationships

In recognition of the influence of flow on riverine habitats and organisms, stream ecologists have devoted considerable effort to the development of quantitative predictive relationships describing ecological responses to flow variability, i.e. flow‐ecology relationships. Methods used to generate flow‐ecology relationships can be thought of as a continuum bookended by pure states approaches on one end and by rates approaches on the other. In pure states approaches, the ecological response is a snapshot of a condition or property (i.e. a state) derived from a single measurement in time. In contrast, ecological responses in rates approaches reflect temporal change (i.e. a rate) and are thus reliant on repeated measurements made over time. Here, we elaborate on the fundamental characteristics of different approaches (pure states, rates and an intermediate approach we call repeated states) for generating flow‐ecology relationships, examine how commonly the different approaches are used in the flow‐ecology literature, conduct an independent analysis to illustrate the different outcomes achieved by applying repeated‐states and rates approaches using a dataset for stream fish diversity in relation to flow magnitude, and identify some of the different ways ecologists are applying rates approaches in flow ecology. Our literature review revealed that repeated‐states approaches (53% of reviewed studies) were used far more commonly than either pure states (19%) or rates (12%) approaches to generate flow‐ecology relationships. The remaining hybrid studies (17%) used both state and rate responses, and thus also relied on repeated measurements over time. Despite frequent collection of data suitable for rates approaches, flow‐ecology relationships have generally been developed using states approaches that relate changes in ecological states to different long‐term average flow conditions, rather than to specific flow sequences over much shorter time intervals. Such flow‐ecology relationships cannot generate temporally specific predictions of ecological responses to changing flow conditions (i.e. the expected change in state following a specific flow sequence), nor can they describe demographic processes underlying observed changes. While there are different scenarios in which a pure or repeated‐states approach would be useful, more frequent use of rates approaches would increase our ability to test flow‐ecology hypotheses and our mechanistic understanding of flow‐ecology relationships.

Freshwater Biology↗

USGS2017

Long-term monitoring data provide evidence of declining species richness in a river valued for biodiversity conservation

Free-flowing river segments provide refuges for many imperiled aquatic biota that have been extirpated elsewhere in their native ranges. These biodiversity refuges are also foci of conservation concerns because species persisting within isolated habitat fragments may be particularly vulnerable to local environmental change. We have analyzed long-term (14- and 20-y) survey data to assess evidence of fish species declines in two southeastern U.S. rivers where managers and stakeholders have identified potentially detrimental impacts of current and future land uses. The Conasauga River (Georgia and Tennessee) and the Etowah River (Georgia) form free-flowing headwaters of the extensively dammed Coosa River system. These rivers are valued in part because they harbor multiple species of conservation concern, including three federally endangered and two federally threatened fishes. We used data sets comprising annual surveys for fish species at multiple, fixed sites located at river shoals to analyze occupancy dynamics and temporal changes in species richness. Our analyses incorporated repeated site-specific surveys in some years to estimate and account for incomplete species detection, and test for species-specific (rarity, mainstem-restriction) and year-specific (elevated frequencies of low- or high-flow days) covariates on occupancy dynamics. In the Conasauga River, analysis of 26 species at 13 sites showed evidence of temporal declines in colonization rates for nearly all taxa, accompanied by declining species richness. Four taxa (including one federally endangered species) had reduced occupancy across the Conasauga study sites, with three of these taxa apparently absent for at least the last 5 y of the study. In contrast, a similar fauna of 28 taxa at 10 sites in the Etowah River showed no trends in species persistence, colonization, or occupancy. None of the tested covariates showed strong effects on persistence or colonization rates in either river. Previous studies and observations identified contaminants, nutrient loading, or changes in benthic habitat as possible causes for fish species declines in the Conasauga River. Our analysis provides baseline information that could be used to assess effectiveness of future management actions in the Conasauga or Etowah rivers, and illustrates the use of dynamic occupancy models to evaluate evidence of faunal decline from time-series data.

Georgia↗

USGS2017

Viability analysis for multiple populations

Many species of conservation interest exist solely or largely in isolated populations. Ideally, prioritization of management actions among such populations would be guided by quantitative estimates of extinction risk, but conventional methods of demographic population viability analysis (PVA) model each population separately and require temporally extensive datasets that are rarely available in practice. We introduce a general class of statistical PVA that can be applied to many populations at once, which we term multiple population viability analysis or MPVA. The approach combines models of abundance at multiple spatial locations with temporal models of population dynamics, effectively borrowing information from more data-rich populations to inform inferences for data-poor populations. Covariates are used to explain population variability in space and time. Using Bayesian analysis, we illustrate the method with a dataset of Lahontan cutthroat trout ( Oncorhynchus clarkii henshawi ) observations that previously had been analyzed with conventional PVA. We find that MPVA predictions are similar in bias and higher in precision than predictions from simple PVA models that treat each population individually; moreover, the use of covariates in MPVA allows for predictions in minimally-sampled and unsampled populations. The basic MPVA model can be extended in multiple ways, such as by linking to a sampling and observation model to provide a full accounting of uncertainty. We conclude that the approach has great potential to expand the use of PVA for species that exist in multiple, isolated populations.

Biological Conservation↗

USGS2017

Spatial and temporal variability in the effects of wildfire and drought on thermal habitat for a desert trout

We studied how drought and an associated stressor, wildfire, influenced stream flow permanence and thermal regimes in a Great Basin stream network. We quantified these responses by collecting information with a spatially extensive network of data loggers. To understand the effects of wildfire specifically, we used data from 4 additional sites that were installed prior to a 2012 fire that burned nearly the entire watershed. Within the sampled network 73 reaches were classified as perennial, yet only 51 contained surface water during logger installation in 2014. Among the sites with pre-fire temperature data, we observed 2–4 °C increases in maximum daily stream temperature relative to an unburned control in the month following the fire; effects (elevated up to 6.6 °C) appeared to persist for at least one year. When observed August mean temperatures in 2015 (the peak of regionally severe drought) were compared to those predicted by a regional stream temperature model, we observed deviations of −2.1°-3.5°. The model under-predicted and over-predicted August mean by > 1 °C in 54% and 10% of sites, respectively, and deviance from predicted was negatively associated with elevation. Combined drought and post-fire conditions appeared to greatly restrict thermally-suitable habitat for Lahontan cutthroat trout ( Oncorhynchus clarkii henshawi ).

Oregon↗

USGS2016

Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity

The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are much weaker than anticipated and may be too subtle for detection given the widespread use of sparse water temperature datasets or imprecise surrogates like elevation and air temperature. Through application of large water-temperature databases evaluated for sensitivity to historical air-temperature variability and computationally interpolated to provide high-resolution thermal habitat information for a 222,000-km network, we estimate a less dire thermal plight for cold-water species within mountains of the northwestern United States. Stream warming rates and climate velocities were both relatively low for 1968–2011 (average warming rate = 0.101 °C/decade; median velocity = 1.07 km/decade) when air temperatures warmed at 0.21 °C/decade. Many cold-water vertebrate species occurred in a subset of the network characterized by low climate velocities, and three native species of conservation concern occurred in extremely cold, slow velocity environments (0.33–0.48 km/decade). Examination of aggressive warming scenarios indicated that although network climate velocities could increase, they remain low in headwaters because of strong local temperature gradients associated with topographic controls. Better information about changing hydrology and disturbance regimes is needed to complement these results, but rather than being climatic cul-de-sacs, many mountain streams appear poised to be redoubts for cold-water biodiversity this century.

Proceedings of the National Academy of Sciences of↗

USGS2016

Urbanization and stream ecology: Diverse mechanisms of change

The field of urban stream ecology has evolved rapidly in the last 3 decades, and it now includes natural scientists from numerous disciplines working with social scientists, landscape planners and designers, and land and water managers to address complex, socioecological problems that have manifested in urban landscapes. Over the last decade, stream ecologists have met 3 times at the Symposium on Urbanization and Stream Ecology (SUSE) to discuss current research, identify knowledge gaps, and promote future research collaborations. The papers in this special series on urbanization and stream ecology include both primary research studies and conceptual synthesis papers spurred from discussions at SUSE in May 2014. The themes of the meeting are reflected in the papers in this series emphasizing global differences in mechanisms and responses of stream ecosystems to urbanization and management solutions in diverse urban streams. Our hope is that this series will encourage continued interdisciplinary and collaborative research to increase the global understanding of urban stream ecology toward stream protection and restoration in urban landscapes.

Freshwater Science↗

USGS2014

Applications of spatial statistical network models to stream data

Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., nonindependence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.

WIREs Water↗

USGS2013

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site-specific frequency distributions of occurrence probabilities across a species’ range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1–42.5 thousand km; this was predicted to decline to 0.5–7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.

Idaho;Montana↗

USGS2013

Modelling dendritic ecological networks in space: anintegrated network perspective

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).

Ecology Letters↗

USGS2011

Use of recent and historical records to estimate status and trends of a rare and imperiled stream fish, Percina jenkinsi (Percidae)

Rarely encountered animals may be present but undetected, potentially leading to incorrect assumptions about the persistence of a local population or the conservation priority of a particular area. The federally endangered and narrowly endemic Conasauga logperch ( Percina jenkinsi ) is a good example of a rarely encountered fish species of conservation concern, for which basic population statistics are lacking. We evaluated the occurrence frequency for this species using surveys conducted with a repeat-observation sampling approach during the summer of 2008. We also analyzed museum records since the late 1980s to evaluate the trends in detected status through time. The results of these analyses provided support for a declining trend in this species over a portion of its historical range, despite low estimated detection probability. We used the results to identify the expected information return for a given level of monitoring where the sampling approach incorporates incomplete detection. The method applied here may be of value where historic occurrence records are available, provided that the assumption of constant capture efficiency is reasonable.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2011

Role of climate and invasive species in structuring trout distributions in the interior Columbia River Basin, USA

Recent and projected climate warming trends have prompted interest in impacts on coldwater fishes. We examined the role of climate (temperature and flow regime) relative to geomorphology and land use in determining the observed distributions of three trout species in the interior Columbia River Basin, USA. We considered two native species, cutthroat trout ( Oncorhynchus clarkii ) and bull trout ( Salvelinus confluentus ), as well as nonnative brook trout ( Salvelinus fontinalis ). We also examined the response of the native species to the presence of brook trout. Analyses were conducted using multilevel logistic regression applied to a geographically broad database of 4165 fish surveys. The results indicated that bull trout distributions were strongly related to climatic factors, and more weakly related to the presence of brook trout and geomorphic variables. Cutthroat trout distributions were weakly related to climate but strongly related to the presence of brook trout. Brook trout distributions were related to both climate and geomorphic variables, including proximity to unconfined valley bottoms. We conclude that brook trout and bull trout are likely to be adversely affected by climate warming, whereas cutthroat trout may be less sensitive. The results illustrate the importance of considering species interactions and flow regime alongside temperature in understanding climate effects on fish.

Columbia River Basin↗

USGS2010

Conservation planning for imperiled aquatic species in an urbanizing environment

As the global area devoted to urban uses grows, an increasing number of freshwater species will face imperilment due to urbanization effects. Management of these impacts on both private and public lands is necessary to ensure species persistence. Such management entails several hallenges: (1) development of a management policy appropriate to the stressors; (2) linking stressor levels to species population attributes; (3) forecasting the effects of alternative management policy decisions on the species, and (4) using adaptive management to adjust the policy in the future. We illustrate how these challenges were addressed under the Etowah Habitat Conservation Plan (Etowah HCP), a management plan for three federally protected fish species in Georgia, USA. The plan involved the creation of a management policy to address the impacts of the greatest stressor, stormwater runoff, as well as other stressors. Models were constructed to link population indices of the three species with a key indicator of stormwater runoff, effective impervious area (EIA). Then, models were applied to projected levels of EIA under full watershed buildout to fine-tune the parameters of the management policy. Forecasting indicated that the most sensitive species, the Etowah darter, was likely to decline by 84% in the absence of the Etowah HCP, but only 23% if the Etowah HCP were implemented. Although there was substantial uncertainty in model predictions, an adaptive management plan was established to incorporate new data and to adjust management policies as necessary.

Landscape and Urban Planning↗