D. C. Laughlin

You shall know a species by the company it keeps: leveraging co-occurrence data to improve ecological prediction

The paper uses species co-occurrence data to create vectors that improve predictions of ecological responses, showing they capture unique information beyond traits and phylogeny.

Estimating the net effect of functional traits on fitness across species and environments

The paper develops a modeling framework to estimate how functional traits affect species fitness across environments and species, finding that traits interact with size and temperature to shape demographic performance and fitness landscapes.

Predictions of biodiversity are improved by integrating trait-based competition with abiotic filtering

The paper introduces a framework integrating trait-based competition with abiotic filtering to improve predictions of species abundances and community structure.

Global Root Traits (GRooT) Database

The paper creates the Global Root Trait (GRooT) Database to integrate root trait data into large-scale analyses by standardizing and curating root trait records from diverse studies.

The fungal collaboration gradient dominates the root economics space in plants

The paper identifies a collaboration gradient in root economics that expands the traditional fast-slow resource acquisition spectrum by incorporating mycorrhizal partnerships.