BatTool: projecting bat populations facing multiple stressors using a demographic model.

Bats provide ecologically and agriculturally important ecosystem services but are currently experiencing population declines caused by multiple environmental stressors, including mortality from white-nose syndrome and wind energy development. Analyses of the current and future health and viability of these species may support conservation management decision making. Demographic modeling provides a quantitative tool for decision makers and conservation managers to make more informed decisions, but widespread adoption of these tools can be limited because of the complexity of the mathematical, statistical, and computational components involved in implementing these models. In this work, we provide an exposition of the BatTool R package, detailing the primary components of the matrix projection model, a publicly accessible graphical user interface ( https://rconnect.usgs.gov/battool ) facilitating user-defined scenario analyses, and its intended uses and limitations (Wiens et al., US Geol Surv Data Release 2022; Wiens et al., US Geol Surv Softw Release 2022). We present a case study involving wind energy permitting, weighing the effects of potential mortality caused by a hypothetical wind energy facility on the projected abundance of four imperiled bat species in the Midwestern United States.

Gaussian process forecasts Pseudogymnoascus destructans will cover coterminous United States by 2030.

White-nose syndrome has been decimating populations of several bat species since its first occurrence in the Northeastern United States in the winter 2006-2007. The spread of the disease has been monitored across the continent through the collaboration of many organizations. Inferring the rate of spread of the disease and predicting its arrival at new locations is critical when assessing the current and predicting the future status and trends of bat species. We developed a model of disease spread that simultaneously achieves high-predictive performance, computational efficiency, and interpretability. We modeled white-nose syndrome spread using Gaussian process variations to infer the spread rate of the disease front, identify areas of anomalous time of arrival, and provide future forecasts of the expected time of arrival throughout North America. Cross-validation of model predictive performance identified a stationary Gaussian process without an additional residual error process as the best-supported model. Results indicated that white-nose syndrome is likely to spread throughout the entire continental United States by 2030. These annually updatable model predictions will be useful in determining the horizon over which disease management actions must take place as well as in status and trend assessments of disease-affected bats.

Successful Problem Solving in Genetics Varies Based on Question Content.

Problem solving is a critical skill in many disciplines but is often a challenge for students to learn. To examine the processes both students and experts undertake to solve constructed-response problems in genetics, we collected the written step-by-step procedures individuals used to solve problems in four different content areas. We developed a set of codes to describe each cognitive and metacognitive process and then used these codes to describe more than 1800 student and 149 expert answers. We found that students used some processes differently depending on the content of the question, but reasoning was consistently predictive of successful problem solving across all content areas. We also confirmed previous findings that the metacognitive processes of planning and checking were more common in expert answers than student answers. We provide suggestions for instructors on how to highlight key procedures based on each specific genetics content area that can help students learn the skill of problem solving.

Interrater Reliability for a Two-Interval, Observer-Based Procedure for Measuring Hearing in Young Children.

Purpose To overcome methodology limitations for studying auditory development in young children, we have recently developed an observer-based procedure that uses a conditioned, play-based, motor response (see Bonino & Leibold, 2017). The purpose of this article was to examine interrater reliability for the method. Method Video recordings of test sessions of 2- to 4-year-old children (n = 17) were examined. Detection of a 1000-Hz warble tone was measured with the Play Observer-Based, Two-Interval (PlayO2I) method in each of two conditions: for a fixed intensity level (30 dB SPL) or for a variable intensity level signal (0-30 dB SPL). All test sessions were scored independently by three observers (one real-time, two offline). Observer consensus was evaluated with Fleiss' kappa statistic. To determine if summary data were similar across the observers of each test session, the proportion of correct trials (fixed-level condition) or threshold (variable-level condition) were computed. Results The strength of observer consensus was classified as "almost perfect" and "substantial" for the fixed-level and variable-level conditions, respectively. Follow-up analysis of the variable-level data indicated that differences in observer consensus were seen based on the signal level, the type of response behavior provided by the child, and the confidence level of the real-time observer. Resulting summary data were similar across the three observers of each test session: no significant differences for estimates of the proportion of correct trials or threshold. Conclusions Results from this study confirm strong interrater reliability for the method. The PlayO2I method is a powerful tool for measuring detection and discrimination abilities in young children. Supplemental Material https://doi.org/10.23641/asha.12978197.