Advisor

Barton, Brandon

Committee Member

Catchot, Angus L. Jr.

Committee Member

Counterman, Brian A.

Committee Member

Ervin, Gary N.

Date of Degree

5-1-2020

Original embargo terms

Complete embargo for 1 year||5/17/2021

Document Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy

College

College of Arts and Sciences

Abstract

Predicting the net effect of climate change on communities requires understanding how increasing temperatures alter interactions between predators, herbivores, and plants. Over the last several decades, warming experiments have provided important information about how species and their interactions will respond to increasing temperatures. These studies typically examine climate warming by experimentally increasing temperature at a constant level (24 hours) or asynchronously during the daytime, relative to unwarmed control treatments. However, advances in climate models now project that increases in mean global temperatures have been disproportionately driven by increasing nighttime (minimum) temperatures rather than daytime (maximum) temperatures. The timing of warming could have important ecological implications. For example, while night warming could benefit an organism by increasing temperatures towards a more thermally-optimal environment, day warming could raise temperatures beyond a thermal optimum and induce heat-stress. Consequently, mismatching the timing of warming in experiments relative to actual temperature changes could generate misleading predictions about the effects of climate warming. My dissertation has evaluated climate-warming experiments by characterizing past methods, demonstrating present methods, and providing a foundation for future studies. I conducted a meta-analysis on past terrestrial predator-prey climate warming studies that revealed experimental temperatures rarely match model projections, and the magnitude of this mismatch correlated with increased changes in measured effects. Two experiments, one focused on predator functional traits and the other trophic cascades, showed that different types of warming treatments result in different effects of climate change. The context dependency of warming effects necessitates careful consideration of experimental treatments if studies are to accurately predict the effects of climate warming. Region specific climate data are now readily available. Moving forward, ecologists can use these models to inform their warming treatments and perform experiments with the highest level of realism.

URI

https://hdl.handle.net/11668/16523

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