Geology topics

Daniel C. Dauwalter

Publications and source records attributed to Daniel C. Dauwalter.

8 recordsLinked to original sources

USGS2020

A call for global action to conserve native trout in the 21st century and beyond

Trout and char (hereafter, trout ) represent some of the more culturally, economically and ecologically important taxa of freshwater fishes worldwide (Kershner, Williams, Gresswell, & Lobón‐Cerviá, 2019a ). Native to all continents in the Northern Hemisphere (as well as western Mediterranean Africa), trout belong to seven genera ( Oncorhynchus , Salvelinus, Salmo , Hucho, Parahucho, Brachymystax and Salvethymus ), which are distributed across more than 60 countries (Muhlfeld et al., 2019 ). Despite their broad importance as indicators of biodiversity in cold‐water ecosystems (Haak & Williams, 2013 ), as well as cultural icons for food and recreation, nearly half of the world's recognised trout species (IUCN, 2018 ) are imperilled or at risk of global extinction (Muhlfeld et al., 2018 , 2019 ). The root causes of their vulnerability include broad‐scale alteration of landscapes and watersheds, dams, overharvest, pollution, interactions with hatchery‐bred conspecifics and non‐native species. However, emerging threats such as climate change and related problems such as the spread of diseases and parasites pose significant challenges and uncertainties to native trout and their habitats (Kovach et al., 2016 ; Muhlfeld et al., 2018 ). Ultimately, conservation of native trout depends on understanding their diversity, a willingness to address threats at their root causes and implementing progressive conservation solutions that promote persistence of these iconic species in the face of growing human pressures.

Ecology of Freshwater Fish↗

USGS2020

Global status of trout and char: Conservation challenges in the twenty-first century

Freshwater ecosystems are among the most threatened ecosystems in the world (Richter et al. 1997; Strayer and Dudgeon 2010), and freshwater fishes may now be the most threatened group of vertebrates (Ricciardi and Rasmussen 1999; Vorosmarty et al. 2010; Darwall and Freyhof 2016). Of the 7,300 freshwater fish species globally assessed by the International Union for Conservation of Nature (IUCN, www.iucnredlist.org) in 2013, nearly one of every three species was threatened with extinction (Darwall and Freyhof 2016). Growing pressures from a multitude of direct and indirect human stressors (e.g., habitat loss and degradation, pollution, invasive species, overexploitation, diversion or alteration of biological flows, climate change, and others) threaten the persistence of many freshwater fish species and entire aquatic communities around the globe (Limburg et al. 2011). This pattern is particularly true for salmonid fishes (family Salmonidae, subfamily Salmoninae, belonging to the genera Oncorhynchus, Salvelinus, Salmo, Hucho, Parahucho, Brachymystax, and Salvethymus). Salmonids are globally-distributed, coldwater taxa with life-cycles restricted entirely to freshwater ecosystems (typically referred to as trout and char), but also Atlantic and Pacific salmon with more complex anadromous life-histories.

Book chapter↗

USGS2019

Application of multiple-population viability analysis to evaluate species recovery alternatives

Population viability analysis (PVA) is a powerful conservation tool, but one that remains unapproachable for many species. This is particularly true for species with multiple, broadly-distributed populations for which collecting suitable data can be challenging. A recently-developed method of multiple population viability analysis (MPVA), however, addresses many limitations of traditional PVA. We build on previous development of MPVA for Lahontan cutthroat trout (LCT), a species listed under the US Endangered Species Act which is distributed broadly across habitat fragments in the Great Basin, USA. We simulated potential management scenarios and assessed their effects on population sizes and extinction risks in 211 streams where LCT exist or may be reintroduced.

Conservation Biology↗

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

Trout in hot water: A call for global action

Trout are one of the most culturally, economically, and ecologically important taxonomic groups of freshwater fishes worldwide (1). Native to all continents in the Northern Hemisphere, trout are a taxonomically diverse group of fishes belonging to 7 genera (Oncorhynchus, Salvelinus, Salmo, Hucho, Parahucho, Brachymystax, and Salvethymus) distributed across 52 countries. These coldwater specialists provide recreation and food to millions of people, and play important roles in ecosystem functioning and health (2). They are also extremely sensitive to human disturbances because they require cold, clean, complex, and connected habitats for survival and persistence (3) – all attributes that humans have substantially altered and degraded (4, 5). Despite their broad importance as societal icons and as indicators of biodiversity, many of the world’s trout species and lineages are endangered and some require immediate conservation efforts to reverse their precarious decline.

Science↗

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↗

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↗

USGS2011

Watershed morphology of highland and mountain ecoregions in eastern Oklahoma

The fluvial system represents a nested hierarchy that reflects the relationship among different spatial and temporal scales. Within the hierarchy, larger scale variables influence the characteristics of the next lower nested scale. Ecoregions represent one of the largest scales in the fluvial hierarchy and are defined by recurring patterns of geology, climate, land use, soils, and potential natural vegetation. Watersheds, the next largest scale, are often nested into a single ecoregion and therefore have properties that are indicative of a given ecoregion. Differences in watershed morphology (relief, drainage density, circularity ratio, relief ratio, and ruggedness number) were evaluated among three ecoregions in eastern Oklahoma: Ozark Highlands, Boston Mountains, and Ouachita Mountains. These ecoregions were selected because of their high-quality stream resources and diverse aquatic communities and are of special management interest to the Oklahoma Department of Wildlife Conservation. One hundred thirty-four watersheds in first- through fourth-order streams were compared. Using a nonparametric, two-factor analysis of variance (α= 0.05) we concluded that the relief, drainage density, relief ratio, and ruggedness number all changed among ecoregion and stream order, whereas circularity ratio only changed with stream order. Our study shows that ecoregions can be used as a broad-scale framework for watershed management.

Oklahoma↗