A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms
Abstract Increasing occurrence of harmful algal blooms across the land–water interface poses significant risks to coastal ecosystem structure and human health. Defining significant drivers and their interactive impacts on blooms allows for more effective analysis and identification of specific condi...
Guardado en:
| Autores principales: | , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/dd7df49158cb41a3b4bb951dcbcc95f2 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:dd7df49158cb41a3b4bb951dcbcc95f2 |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:dd7df49158cb41a3b4bb951dcbcc95f22021-12-02T19:16:14ZA novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms10.1038/s41598-021-98110-92045-2322https://doaj.org/article/dd7df49158cb41a3b4bb951dcbcc95f22021-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98110-9https://doaj.org/toc/2045-2322Abstract Increasing occurrence of harmful algal blooms across the land–water interface poses significant risks to coastal ecosystem structure and human health. Defining significant drivers and their interactive impacts on blooms allows for more effective analysis and identification of specific conditions supporting phytoplankton growth. A novel iterative Random Forests (iRF) machine-learning model was developed and applied to two example cases along the California coast to identify key stable interactions: (1) phytoplankton abundance in response to various drivers due to coastal conditions and land-sea nutrient fluxes, (2) microbial community structure during algal blooms. In Example 1, watershed derived nutrients were identified as the least significant interacting variable associated with Monterey Bay phytoplankton abundance. In Example 2, through iRF analysis of field-based 16S OTU bacterial community and algae datasets, we independently found stable interactions of prokaryote abundance patterns associated with phytoplankton abundance that have been previously identified in laboratory-based studies. Our study represents the first iRF application to marine algal blooms that helps to identify ocean, microbial, and terrestrial conditions that are considered dominant causal factors on bloom dynamics.Yiwei ChengVed N. BhootKarl KumbierMarilou P. Sison-MangusJames B. BrownRaphael KudelaMichelle E. NewcomerNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Yiwei Cheng Ved N. Bhoot Karl Kumbier Marilou P. Sison-Mangus James B. Brown Raphael Kudela Michelle E. Newcomer A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms |
| description |
Abstract Increasing occurrence of harmful algal blooms across the land–water interface poses significant risks to coastal ecosystem structure and human health. Defining significant drivers and their interactive impacts on blooms allows for more effective analysis and identification of specific conditions supporting phytoplankton growth. A novel iterative Random Forests (iRF) machine-learning model was developed and applied to two example cases along the California coast to identify key stable interactions: (1) phytoplankton abundance in response to various drivers due to coastal conditions and land-sea nutrient fluxes, (2) microbial community structure during algal blooms. In Example 1, watershed derived nutrients were identified as the least significant interacting variable associated with Monterey Bay phytoplankton abundance. In Example 2, through iRF analysis of field-based 16S OTU bacterial community and algae datasets, we independently found stable interactions of prokaryote abundance patterns associated with phytoplankton abundance that have been previously identified in laboratory-based studies. Our study represents the first iRF application to marine algal blooms that helps to identify ocean, microbial, and terrestrial conditions that are considered dominant causal factors on bloom dynamics. |
| format |
article |
| author |
Yiwei Cheng Ved N. Bhoot Karl Kumbier Marilou P. Sison-Mangus James B. Brown Raphael Kudela Michelle E. Newcomer |
| author_facet |
Yiwei Cheng Ved N. Bhoot Karl Kumbier Marilou P. Sison-Mangus James B. Brown Raphael Kudela Michelle E. Newcomer |
| author_sort |
Yiwei Cheng |
| title |
A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms |
| title_short |
A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms |
| title_full |
A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms |
| title_fullStr |
A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms |
| title_full_unstemmed |
A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms |
| title_sort |
novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/dd7df49158cb41a3b4bb951dcbcc95f2 |
| work_keys_str_mv |
AT yiweicheng anovelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT vednbhoot anovelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT karlkumbier anovelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT mariloupsisonmangus anovelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT jamesbbrown anovelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT raphaelkudela anovelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT michelleenewcomer anovelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT yiweicheng novelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT vednbhoot novelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT karlkumbier novelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT mariloupsisonmangus novelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT jamesbbrown novelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT raphaelkudela novelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms AT michelleenewcomer novelrandomforestapproachtorevealinginteractionsandcontrolsonchlorophyllconcentrationandbacterialcommunitiesduringcoastalphytoplanktonblooms |
| _version_ |
1718377001415344128 |