Geology topics

Lester L. Yuan

Publications and source records attributed to Lester L. Yuan.

3 recordsLinked to original sources

USGS2024

Using models of local environmental conditions for biological assessment

A common approach for biological assessment is to compare current observations of biota at a site to predictions of the biota that would occur if the site were in reference condition. To estimate these reference expectations, predictive bioassessment models use only data collected at reference sites and estimate relationships between biota and environmental variables that are unaffected by human activities (i.e., immutable variables). However, in some areas where human activities are pervasive, few reference sites are available. Here, we introduce a new approach for bioassessment, in which we first estimate relationships between widely available measurements of both immutable and human-influenced landscape variables and local environmental conditions (conductivity, dissolved total P, total suspended solids, percentage of sand and fines in the substrate, and dissolved organic C), and then we estimate the relationship between these local environmental variables and total macroinvertebrate richness. We then calculate the values of the local environmental variables under reference conditions by adjusting predictors that are strongly influenced by human activities to levels that are consistent with those observed at reference sites. Reference values of local environmental variables are then combined with the model for taxon richness to calculate taxon richness expected under reference conditions. Predictions of total taxon richness in validation data using the new approach are similar in accuracy and precision as predictions calculated using a traditional approach that focuses only on reference site data. The new approach complements existing bioassessment methods by highlighting types of sites in which estimates of reference expectations are uncertain and by improving our understanding of how instream stressors affect expected total taxon richness.

conterminous United States↗

USGS2021

The application of metacommunity theory to the management of riverine ecosystems

River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this article, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists, and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.

WIREs Water↗

USGS2009

Using propensity scores to estimate the effects of insecticides on stream invertebrates from observational data

Analyses of observational data can provide insights into relationships between environmental conditions and biological responses across a broader range of natural conditions than experimental studies, potentially complementing insights gained from experiments. However, observational data must be analyzed carefully to minimize the likelihood that confounding variables bias observed relationships. Propensity scores provide a robust approach for controlling for the effects of measured confounding variables when analyzing observational data. Here, we use propensity scores to estimate changes in mean invertebrate taxon richness in streams that have experienced insecticide concentrations that exceed aquatic life use benchmark concentrations. A simple comparison of richness in sites exposed to elevated insecticides with those that were not exposed suggests that exposed sites had on average 6.8 fewer taxa compared to unexposed sites. The presence of potential confounding variables makes it difficult to assert a causal relationship from this simple comparison. After controlling for confounding factors using propensity scores, the difference in richness between exposed and unexposed sites was reduced to 4.1 taxa, a difference that was still statistically significant. Because the propensity score analysis controlled for the effects of a wide variety of possible confounding variables, we infer that the change in richness observed in the propensity score analysis was likely caused by insecticide exposure.

Environmental Toxicology and Chemistry↗