Natural resource managers often make decisions about systems that are variable across time and space. For instance, observed indices may vary among repeated samples from a single location (e.g., a sampling site), from site-to-site within an area (e.g., a lake), from area-to-area (e.g., lake-to-lake), and among years. Although variability has traditionally been viewed as an impediment to understanding responses to change, it may also be able to serve as an indicator. In this webinar, we will discuss variance partitioning as a method for estimating component sources of variability (e.g., temporal and spatial), and we will present a case-study example using long-term survey data on the relative abundance of a recreationally important fish population. Further, we will use these data and estimation models to explore if variance structure may be responsive to large-scale perturbation (e.g., establishment of an invasive species). Characterizing variance components could be informative to decisions about how to monitor and manage natural resources under uncertain future conditions, such as climate change. We will conclude by considering decision making in the presence of uncertainty more broadly, and we will illustrate how quantitative forecasting models can serve as effective decision-support tools by helping account for both what is known and known to be unknown when attempting to identify management options able to achieve management objectives.
Brian Irwin is the Assistant Unit Leader (Fisheries) at the Georgia Cooperative Fish and Wildlife Research Unit and a faculty member of the Warnell School of Forestry and Natural Resources at the University of Georgia. Prior to joining USGS, he worked at the Quantitative Fisheries Center at Michigan State University developing models to support fisheries management in the Great Lakes. His research interests include ecological change, fish population dynamics, and decision making linked to conservation and management of natural resources.
Tiffany Vidal is a PhD student at the University of Georgia with an interest in understanding how fish populations respond to perturbation, with an emphasis on climate change. Her research is currently focused on fish populations in the Great Lakes Basin, and she hopes to build predictive models that will help inform monitoring and management of fish populations. Prior to enrolling at UGA, she completed a Master’s degree at the University of Massachusetts’ School for Marine Sciences and Technology, studying the reproductive biology of golden tilefish.
--> See video here (presentation starts near 30:00): https://www.fuzemeeting.com/replay_meeting/4cc8aefb/7061362
Trimmed video will be posted to Vimeo soon.