Grantee Research Project Results
From Nutrients to Metabolism: Linking Numeric Nutrient Criteria to Ecosystem Composition and Function Using Ecological Stoichiometry
EPA Grant Number: FP917452Title: From Nutrients to Metabolism: Linking Numeric Nutrient Criteria to Ecosystem Composition and Function Using Ecological Stoichiometry
Investigators: Douglass, Rachel Lianna
Institution: University of Florida
EPA Project Officer: Packard, Benjamin H
Project Period: August 1, 2012 through July 31, 2015
Project Amount: $126,000
RFA: STAR Graduate Fellowships (2012) RFA Text | Recipients Lists
Research Category: Fellowship - Ecology , Academic Fellowships
Objective:
The U.S. Environmental Protection Agency recently proposed numeric nutrient criteria for spring ecosystems; however, prior research indicates nutrient concentrations alone may not adequately predict vegetation shifts for spring ecosystems. As such, this study seeks to answer how variation in the bottom-up forcing of changing resource C:N:P ratios and flow interact with top-down effects of grazing to regulate the competitive ability of vascular and algal species in springs. In addition, the study will evaluate how differing compositions of algal and vascular species affect ecosystem metabolism, a measure of ecosystem function, by deploying a suite of three real-time nutrient sensors across a gradient of species composition.
Approach:
By utilizing an in situ experimental approach during spring runs, the competitive ability of vascular versus algal species under two different resource C:N:P regimes found in spring ecosystems will be examined. By comparing the two resource regimes under both high and low flow as well as in the presence and absence of grazers, the study will evaluate the relative influence of bottom-up forces versus top-down grazing effects. In the field, percent cover and biomass of each species will be measured. Next, the study will use real-time nutrient sensing technology combined with vegetation sampling in springs with varying amounts of algal and vascular taxa to determine how variation in primary producer composition affects ecosystem metabolism and the associated stoichiometry. Using the sensor data, ecosystem metabolism will be calculated as well as the C:N:P of the ecosystem, which will be compared to the stoichiometry of the dominant taxa.Expected Results:
Results of these experiments will inform resource managers of the impacts of raising ecosystem C:N ratios on species composition under various flow regimes as well as the extent to which the N:P interacts with the C:N ratio to affect individual species’ competitive ability, and hence, primary producer species composition. This research also is expected to document the extent to which the bottom-up forces of flow and nutrient ratios are influenced by top-down pressure of grazing. Finally, this project will evaluate the effects of differing species composition on ecosystem metabolism.
Potential to Further Environmental/Human Health Protection
Projected population increases and associated land use change are predicted to only exacerbate existing nutrient inputs to these ecosystems. This research provides crucial information to improve environmental decision making by enabling managers to better predict potential effects of nutrient-driven eutrophication on ecosystem composition and function through the use of nutrient ratios under varying flow regimes and grazing intensities. This information can be utilized to formulate effective long-term plans to sustain and restore these economically and ecologically important spring ecosystems.
Supplemental Keywords:
ecological stoichiometry, competitive ability, species compositionProgress and Final Reports:
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.