Kelly O Maloney, Ph.D.

Many at-risk species lack standardized surveys across their range or quantitative data capable of detecting demographic trends. As a result, extinction risk assessments often rely on ordinal categories of risk based on explicit criteria or expert elicitation. This study demonstrates a Bayesian approach to assessing extinction risk based on this...

Random forests have become an established tool for classication and regres- sion, in particular in high-dimensional settings and in the presence of non-additive predictor-response relationships. For bounded outcome variables restricted to the unit interval, however, classical modeling approaches based on mean squared error loss may severely suer...

Land‐use and climate change are significantly affecting stream ecosystems, yet understanding of their long‐term impacts is hindered by the few studies that have simultaneously investigated their interaction and high variability among future projections. We modeled possible effects of a suite of 2030, 2060, and 2090 land‐use and climate scenarios...

A primary goal for Chesapeake Bay watershed restoration is to improve stream health and function in 10% of stream miles by 2025. Predictive spatial modeling of stream conditions, when accurate, is one method to fill gaps in monitoring coverage and estimate baseline conditions for restoration goals. Predictive modeling can also monitor progress as...

We conducted a large-scale assessment of unconventional oil and gas (UOG) development effects on brook trout (Salvelinus fontinalis) distribution. We compiled 2231 brook trout collection records from the Upper Susquehanna River Watershed, USA. We used boosted regression tree (BRT) analysis to predict occurrence probability at the 1:24,000 stream-...