News

A new paper led by Ben Goldstein provides guidance to practitioners on when to use data integration for a species distribution modeling application. We provide a variety of practical considerations for researchers, students, and practitioners to consider the pros and cons of data integration.

Check out our new paper on multivariate spatial models for small area estimation of species-specific forest parameters. We apply our modeling framework to estimate species-level biomass for the 20 most common tree species across the Southern US, which resulted in large precision improvements relative to classical approaches.

Check out our new paper on multivariate spatial models for small area estimation of species-specific forest parameters. We apply our modeling framework to estimate species-level biomass for the 20 most common tree species across the Southern US, which resulted in large precision improvements relative to classical approaches.

The SEFS Lab is thrilled to welcome the first two PhD students in the lab: Alexa Busby and Darius Ledbetter. Alexa will be exploring relationships between forest management and understudied wildlife in the southeastern US.

The Statistical Ecology and Forest Science Lab is excited that Dr. Michelle Pretorius has joined the lab as a Postdoctoral Research Scholar. Michelle will be working with FIA data and applications to inform wildlife and biodiversity conservation.

We recently wrote a short discussion paper on an exciting new development in spatial occupancy models by Wilson Wright and Mevin Hooten. Find our discussion and the paper by Wright and Hooten here.

A paper led by Chris Dean at University College London was recently published in Ecology Letters. Using spOccupancy, we applied occupancy models to better understand sampling biases in the dinosaur fossil record.

A new paper led by Casey Youngflesh at Clemson University was recently published in Ecology Letters on the role of environmental variation in shaping life history of birds across the globe.

A new paper led by Ken Kellner at Michigan State University was recently published in Ecology. We assessed the analytic reproducibility of nearly 500 papers from 2018-2022, finding that only 7% of papers had R code that ran without any errors.

A fun new paper led by Gabriela Quinlan at Penn State University was just published in Science of the Total Environment. Using a dataset from Maryland and joint species distribution models implemented in spAbundance, we provide the largest scale, most phylogenetically resolved assessment of non-native honey bee density effects on wild bee abundance to date.