Research Grants/Fellowships/SBIR

Towards a Mechanistic Understanding of the Response of Rocky Shoreline Communities to Multiple Climate Change Scenarios

EPA Grant Number: FP917429
Title: Towards a Mechanistic Understanding of the Response of Rocky Shoreline Communities to Multiple Climate Change Scenarios
Investigators: Barner, Allison K
Institution: Oregon State University
EPA Project Officer: Just, Theodore J.
Project Period: September 1, 2012 through August 31, 2015
Project Amount: $126,000
RFA: STAR Graduate Fellowships (2012) RFA Text |  Recipients Lists
Research Category: Academic Fellowships , Fellowship - Ecology



Because predictions about future species distributions that are made under current climate conditions may not hold up as climate rapidly changes, accurate predictions of future ecosystem change require a mechanistic, experimental understanding of the species interactions (competition, facilitation) that structure communities. Current bioclimate prediction models do not account for species interactions, and to explore the consequences of ignoring interactions, this research will utilize a framework incorporating observational surveys, experimental manipulation and exploratory community-level modeling to investigate and predict intertidal community dynamics under climate change. The study asks: (1) What are the patterns of natural macroalgal community structure and function under different environmental gradients related to climate change along the California Current System? (2) What are the structural and functional responses of constructed communities to experimental climate change? (3) What are the predicted future trajectories for marine macroalgal communities under climate change?


This study will use existing variability in environmental conditions along the Oregon and California coasts as climate change proxies to test the effects of storm intensification and sea level rise on intertidal macroalgal communities through modifications to species interactions. The study will use large-scale, spatially explicit surveys of the macroalgal communities and environmental conditions to model current and future species distributions and ecosystem function (productivity). Transplant experiments across gradients relevant to climate change (storm intensification = wave exposure, sea level rise = tidal height) will be conducted to evaluate how climate change might affect macroalgal species interactions, and community structure and function. Finally, this study will test the predictive power of a series of bioclimate models that do and do not include species interactions using results from the observational and experimental work.

Expected Results:

Although the need to incorporate species interactions into bioclimate models is recognized widely, there have been no experimental comparisons between predictions made by climate envelope models and species interaction models. This project will quantify these differences to understand the benefits and limitations to each modeling approach and identify sources of uncertainty in bioclimate models. It is expected that there will be large differences in the predicted future community structure and function among models, and that the model incorporating interactions under climate change will have the greatest ability to explain environment- structure-function associations. However, these predictions may not be relevant at large spatial scales, where oceanography and regional climate forcing is more important. This study will provide the unique ability to predict and compare changes to macroalgal coastal community structure and ecosystem function under different climate scenarios and models.

Potential to Further Environmental/Human Health Protection

Through in situ manipulations and modeling, the study will explore how individual species loss affects the functioning of this ecosystem, with crucial implications for ecosystem management. Resource managers and policy makers face a quandary, as traditional management tactics may not be valid when species distributions and interactions are altered. Thus, understanding the performance of models of species distributions under multiple climate change factors is critical to informing adaptive management and directing conservation effort. The results of this proposed research will have cross-system implications in management, as the theory and models developed here will be applicable in systems beyond the rocky intertidal, intended to engage in a more general discourse on community theory and its application to climate change.