Heidi K. Hirsh, Thomas A. Oliver, Thomas Dobbelaere, Ana M. Palacio-Castro, Hannah C. Barkley, Alice E. Webb, Emmanuel Hanert, Ian C. Enochs
{"title":"Statistical Prediction of In Situ Coral Reef Carbonate Dynamics Using Endmember Chemistry, Hydrodynamic Models, And Benthic Composition","authors":"Heidi K. Hirsh, Thomas A. Oliver, Thomas Dobbelaere, Ana M. Palacio-Castro, Hannah C. Barkley, Alice E. Webb, Emmanuel Hanert, Ian C. Enochs","doi":"10.1007/s10498-025-09438-x","DOIUrl":null,"url":null,"abstract":"<div><p>In the face of rapidly compounding climate change impacts, including ocean acidification (OA), it is critical to understand present-day stress exposure and to anticipate the biogeochemical conditions experienced by vulnerable ecosystems like coral reefs. To meaningfully predict nearshore carbonate chemistry, we must account for the complexity of the local benthic community, as well as connectivity between habitats and relevant endmember carbonate chemistry. Here, we adopt a system-scale approach to predict site-scale effects of benthic metabolism on the carbonate system of the Florida Reef Tract (FRT). We utilize bimonthly carbonate chemistry data from ten cross-shelf transects spanning 250 km of the FRT to model changes in dissolved inorganic carbon (DIC) and total alkalinity (TA). Benthic habitat maps were used to broadly classify communities known to impact carbonate chemistry. A SLIM 2D hydrodynamic model with mesh resolution reaching 100 m over reefs and along the coastline was used to determine the relevant water mass histories and identify the upstream benthic communities shaping local carbonate chemistry. These historical metabolic footprints, or “flowsheds”, were used to build predictive models of the change in DIC and TA at each station. The best predictive models included the chemical impacts of benthic ecosystem metabolism, as defined by water mass trajectories, weighted endmember chemistry, volume, time, and other environmental parameters (light, temperature, salinity, chlorophyll-a, and nitrate). Considering water mass for 5 days prior to sample collection yielded the highest model skill.</p></div>","PeriodicalId":8102,"journal":{"name":"Aquatic Geochemistry","volume":"31 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10498-025-09438-x.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aquatic Geochemistry","FirstCategoryId":"89","ListUrlMain":"https://link.springer.com/article/10.1007/s10498-025-09438-x","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
In the face of rapidly compounding climate change impacts, including ocean acidification (OA), it is critical to understand present-day stress exposure and to anticipate the biogeochemical conditions experienced by vulnerable ecosystems like coral reefs. To meaningfully predict nearshore carbonate chemistry, we must account for the complexity of the local benthic community, as well as connectivity between habitats and relevant endmember carbonate chemistry. Here, we adopt a system-scale approach to predict site-scale effects of benthic metabolism on the carbonate system of the Florida Reef Tract (FRT). We utilize bimonthly carbonate chemistry data from ten cross-shelf transects spanning 250 km of the FRT to model changes in dissolved inorganic carbon (DIC) and total alkalinity (TA). Benthic habitat maps were used to broadly classify communities known to impact carbonate chemistry. A SLIM 2D hydrodynamic model with mesh resolution reaching 100 m over reefs and along the coastline was used to determine the relevant water mass histories and identify the upstream benthic communities shaping local carbonate chemistry. These historical metabolic footprints, or “flowsheds”, were used to build predictive models of the change in DIC and TA at each station. The best predictive models included the chemical impacts of benthic ecosystem metabolism, as defined by water mass trajectories, weighted endmember chemistry, volume, time, and other environmental parameters (light, temperature, salinity, chlorophyll-a, and nitrate). Considering water mass for 5 days prior to sample collection yielded the highest model skill.
期刊介绍:
We publish original studies relating to the geochemistry of natural waters and their interactions with rocks and minerals under near Earth-surface conditions. Coverage includes theoretical, experimental, and modeling papers dealing with this subject area, as well as papers presenting observations of natural systems that stress major processes. The journal also presents `letter''-type papers for rapid publication and a limited number of review-type papers on topics of particularly broad interest or current major controversy.