Project Type:

Project

Project Sponsors:

  • National Science Foundation - NSF

Project Award:

  • $1,599,022

Project Timeline:

2021-08-15 – 2026-07-31



Lead Principal Investigator:



CAREER: Predicting ecosystem metabolism of rocky intertidal communities in warming and acidifying oceans.


Project Type:

Project

Project Sponsors:

  • National Science Foundation - NSF

Project Award:

  • $1,599,022

Project Timeline:

2021-08-15 – 2026-07-31


Lead Principal Investigator:



The recent devastating impacts of global warming and ocean acidification on rocky intertidal ecosystems are expected to increase as the oceans continue to warm and acidify. Further, loss of critical foundation species as a result of extreme heating events and ocean acidification lead to feedback loops that further alter ecosystem functioning. While there have been several studies on the physiology of individual organisms as well as species interactions in response to OA and warming in rocky systems, far less research has been conducted on ecosystem-scale metabolic responses. Here, I take a critical step in understanding how altered environmental conditions affect ecosystem functioning in rocky intertidal systems through laboratory and field experiments, and modeling using long-term data sets. Specifically, my overarching question is: How does shifting environmental variability and loss of foundation species interact to affect ecosystem functioning in rocky intertidal communities? I propose to test a series of hypothesized mechanisms through which different warming regimes, lowered pH, and community disturbance lead to altered community metabolism and ultimately affect ecosystem function. I propose the following research aims: 1) Identify community thermal performance curves of multiple ecosystem functions at high and low pH. 2) Characterize drivers of ecosystem functioning in situ using natural changes in environmental variability before and after a disturbance. 3) Use 16 years of publicly available community composition and environmental time-series data to hindcast ecosystem metabolic rates and predict how ecosystem metabolism may change in the future. These research aims will be further supported by educational opportunities for undergraduate and graduate students, with a focus on supporting underrepresented minorities, and by collaborating with an artist-in-residence to communicate science to the broader public.






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