Geology topics

Douglas R. Leasure

Publications and source records attributed to Douglas R. Leasure.

6 recordsLinked to original sources

USGS2024

Elemental composition and potential toxicity of the riverine macrophyte Podostemum ceratophyllum Michx. reflects land use in eastern North America

Land use influences surface water quality, often alleviating stoichiometric constraints on primary production and altering biogeochemical cycling. However, land use effects on nutrient content and potential trace metal accumulation in aquatic plants remain unclear, and high concentrations of metals and altered nutrient ratios could impact the health of herbivores and detritivores. We tested for land use effects on nutrient and trace metal accumulation in a widespread riverine macrophyte, Podostemum ceratophyllum , collected from 91 locations from Georgia to Maine, USA in 2014–2016. We quantified carbon (C), nitrogen (N), phosphorus (P), their molar and mass ratios, N and C stable isotopes, and 17 additional elements in dried plants collected from each location to estimate relationships between plant tissue content and watershed land use, which we quantified as agriculture, forest, and development. Decreasing forest cover was correlated with increasing δ 15 N, Mg, Mn, and P in Podostemum tissue. Increasing urban development was correlated with increasing δ 15 N, Mg and P, while increasing agriculture was correlated with a decrease in C: P and the concentrations of multiple metals, along with increases in P, Mg and δ 15 N. Decreases in ratios of N: P and C:P with increasing agriculture and urban development in the watershed indicate more rapid P storage relative to C and N in plant tissue, and increased resource quality of the plant to consumers in these watersheds. We also observed potentially toxic dietary concentrations of some trace metals (B, Cd, Tl, Zn) in plant tissue which could be related to the plant's natural herbivory defense system or to land use. We conclude that land use influences the elemental composition of P. ceratophyllum , and potentially the quality and toxicity of the plant to herbivores and detritivores in eastern North American rivers.

Science of the Total Environment↗

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

The influence of drought on flow‐ecology relationships in Ozark Highland streams

Drought and summer drying can have strong effects on abiotic and biotic components of stream ecosystems. Environmental flow‐ecology relationships may be affected by drought and drying, adding further uncertainty to the already complex interaction of flow with other environmental variables, including geomorphology and water quality. Environment–ecology relationships in stream communities in Ozark Highland streams, USA, were examined over two years with contrasting environmental conditions, a drought year (2012) and a flood year (2013). We analysed fish, crayfish and benthic macroinvertebrate assemblages using two different approaches: (1) a multiple regression analysis incorporating predictor variables related to habitat, water quality, geomorphology and hydrology and (2) a canonical ordination procedure using only hydrologic variables in which forward selection was used to select predictors that were most related to our response variables. Reach‐scale habitat quality and geomorphology were found to be the most important influences on community structure, but hydrology was also important, particularly during the flood year. We also found substantial between‐year variation in environment–ecology relationships. Some ecological responses differed significantly between drought and flood years, while others remained consistent. We found that magnitude was the most important flow component overall, but that there was a shift in relative importance from low flow metrics during the drought year to average flow metrics during the flood year, and the specific metrics of importance varied markedly between assemblages and years. Findings suggest that understanding temporal variation in flow‐ecology relationships may be crucial for resource planning. While some relationships show temporal variation, others are consistent between years. Additionally, different kinds of hydrologic variables can differ greatly in terms of which assemblages they affect and how they affect them. Managers can address this complexity by focusing on relationships that are temporally stable and flow metrics that are consistently important across groups, such as flood frequency and flow variability.

Arkansas, Missouri, Oklahoma↗

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↗

USGS2014

Natural flow regimes of the Ozark-Ouachita Interior Highlands region

Natural flow regimes represent the hydrologic conditions to which native aquatic organisms are best adapted. We completed a regional river classification and quantitative descriptions of each natural flow regime for the Ozark–Ouachita Interior Highlands region of Arkansas, Missouri and Oklahoma. On the basis of daily flow records from 64 reference streams, seven natural flow regimes were identified with mixture model cluster analysis: Groundwater Stable, Groundwater, Groundwater Flashy, Perennial Runoff, Runoff Flashy, Intermittent Runoff and Intermittent Flashy. Sets of flow metrics were selected that best quantified nine ecologically important components of these natural flow regimes. An uncertainty analysis was performed to avoid selecting metrics strongly affected by measurement uncertainty that can result from short periods of record. Measurement uncertainties (bias, precision and accuracy) were assessed for 170 commonly used flow metrics. The ranges of variability expected for select flow metrics under natural conditions were quantified for each flow regime to provide a reference for future assessments of hydrologic alteration. A random forest model was used to predict the natural flow regimes of all stream segments in the study area based on climate and catchment characteristics, and a map was produced. The geographic distribution of flow regimes suggested distinct ecohydrological regions that may be useful for conservation planning. This project provides a hydrologic foundation for future examination of flow–ecology relationships in the region. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Arkansas, Missouri, Oklahoma↗