Understanding how the biosphere will persist through the current biodiversity crisis is the single greatest challenge facing ecology. Rapid environmental changes impact nearly every ecosystem and ecological process, and thus it is essential to be able to model how those changes affect populations and communities to improve our understanding of the fundamental ecological processes and to support conservation.
Most of my research falls into the general theme of understanding population and community responses to external drivers and identifying the best way to model those processes to make predictions. I am especially interested in time series analysis, ecological modeling, model transferability, and bringing together disparate data sources to gain a general understanding of a topic. For example, I am currently working projects addressing the following topics:
Synthesizing what is already known about a topic and building on previous work is a key stage in the scientific process, however, an ever-expanding body of literature makes it challenging to systematically identify and analyze existing evidence. I am developing new methods of evidence synthesis to help cope with the explosion of scientific literature while still applying systematic principles to promote transparency and reduce bias when conducting literature reviews and meta-analyses.
Within this arena, I am largely focused on: 1) applying principles of study design to all types of synthesis, including conceptual model development and syntheses with undefined question components, 2) reducing time and effort for syntheses on broad topics through automation, decision rules for screening effort, and stopping criteria, and 3) increasing transparency and inclusivity in the synthesis process through community-driven evidence synthesis. Specifically, I am working on: