東華大學圖書館 |

Exploring the Spatial Distribution of Marine Nitrogen Fixation through Statistical Modeling, High-Resolution Observations and Molecular Level Characterization.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Exploring the Spatial Distribution of Marine Nitrogen Fixation through Statistical Modeling, High-Resolution Observations and Molecular Level Characterization./
作者:	Tang, Weiyi.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	193 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
Contained By:	Dissertations Abstracts International80-12B.
標題:	Chemical Oceanography. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13807788
ISBN:	9781392195567

Exploring the Spatial Distribution of Marine Nitrogen Fixation through Statistical Modeling, High-Resolution Observations and Molecular Level Characterization.
Tang, Weiyi.

Exploring the Spatial Distribution of Marine Nitrogen Fixation through Statistical Modeling, High-Resolution Observations and Molecular Level Characterization. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 193 p.

Source: Dissertations Abstracts International, Volume: 80-12, Section: B.

Thesis (Ph.D.)--Duke University, 2019.

This item is not available from ProQuest Dissertations & Theses.

Marine productivity is limited by nitrogen in a large portion of the global ocean. Marine nitrogen fixation, catalyzed by a select group of microorganisms called diazotrophs, converts nitrogen gas (N2) into bioavailable nitrogen that can support the growth of marine phytoplankton. By supplying new nitrogen to marine ecosystems, marine N2 fixation affects marine primary production, the uptake of carbon dioxide and ultimately the global climate. However, the environmental controls on N2 fixation and the physiologies of diverse diazotrophs remain elusive, in great part due to the limited number of observations. As part of this dissertation, I applied a variety of approaches including statistical modeling, high-resolution field measurements, and gene sequencing to characterize the biogeography of marine diazotrophy.The first approach was to model marine N2 fixation and diazotrophs using machine learning methods. To that end, I conducted meta-analyses to update the global datasets of N2 fixation and diazotrophs. The number of observations in these updated datasets are ~80% and over 100% larger than previous datasets, respectively. Simple correlation analyses between N2 fixation rates and different environmental factors failed to identify a single factor explaining marine N2 fixation at a global scale. In contrast, individual diazotrophic phylotypes showed distinct relations to environmental properties. Machine learning methods including random forest (RF) and support vector regression (SVR) simulated the observed N2 fixation and diazotrophs fairly well by accounting for nonlinearities among multiple environmental factors. The estimated global N2 fixation fluxes from the two statistical models were within the range of other studies. However, the machine learning estimates and other simulations in some cases showed substantial disagreement in both the magnitude and distribution of N2 fixation and diazotrophs, especially in high latitudes and the eastern equatorial Pacific, where observations are scarce. The large uncertainties in simulated N2 fixation and diazotrophs emphasized the need for a better understanding of the factors regulating N2 fixation and the physiology of diazotrophs.Achieving this goal can be labor-intensive and difficult with current techniques, which are based on discrete sampling and long incubation time. To overcome some of the drawbacks of traditional methods, our laboratory developed a method for high-frequency underway N2 fixation measurements. This method provides better coverage of the spatial and temporal heterogeneity in N2 fixation. I deployed this method over large swaths of the western North Atlantic Ocean in the summers of 2015, 2016, and 2017, covering over 10,000 km cruise tracks. This extensive survey identified new hotspots of N2 fixation in the coastal waters of the mid-Atlantic Bight. By coupling high-resolution N2 fixation observations with underway estimates of net community production (NCP) derived from O2/Ar measurements, I revealed the heterogeneous contribution of N2 fixation to NCP and to the carbon cycle, with a surprisingly large contribution in coastal waters.In addition to the spatial distribution of N2 fixation, I also characterized types of diazotrophs responsible for N2 fixation and how they responded to varying environmental conditions. By measuring diazotrophic diversity, abundance and activity at high-resolution using newly developed underway sampling and sensing techniques, I captured a shift between diazotrophs from Trichodesmium to UCYN-A from oligotrophic warm (25-29 °C) subtropical Sargasso Sea to the relatively nutrient-enriched cold (13-24 °C) eastern American coastal waters. Meanwhile, N2 fixation rates were significantly enhanced when phosphorus and Fe availabilities, and chlorophyll-a concentration increased across the Gulf Stream into the subpolar and coastal waters. Phosphorus limitation was confirmed with changes in the expression of phosphorus uptake genes in Trichodesmium and UCYN-A. While temperature was the major factor controlling the diazotrophic community, phosphorous was dominantly driving the changes of N2 fixation rates in the western North Atlantic.Overall, this dissertation significantly improves our understanding of the distribution of N2 fixation and diazotrophs and their environmental controls in the western North Atlantic and in the global ocean.

ISBN: 9781392195567Subjects--Topical Terms:

1674678
Chemical Oceanography.
Subjects--Index Terms:

Diazotroph

Exploring the Spatial Distribution of Marine Nitrogen Fixation through Statistical Modeling, High-Resolution Observations and Molecular Level Characterization.
LDR:05868nmm a2200421 4500 001 2268793
005 20200824100356.5
008 220629s2019 ||||||||||||||||| ||eng d
020 $a 9781392195567
035 $a (MiAaPQ)AAI13807788
035 $a (MiAaPQ)duke:15010
035 $a AAI13807788
040 $a MiAaPQ $c MiAaPQ
100 1 $a Tang, Weiyi. $3 3546094
245 1 0 $a Exploring the Spatial Distribution of Marine Nitrogen Fixation through Statistical Modeling, High-Resolution Observations and Molecular Level Characterization.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 193 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Cassar, Nicolas.
502 $a Thesis (Ph.D.)--Duke University, 2019.
506 $a This item is not available from ProQuest Dissertations & Theses.
506 $a This item must not be sold to any third party vendors.
520 $a Marine productivity is limited by nitrogen in a large portion of the global ocean. Marine nitrogen fixation, catalyzed by a select group of microorganisms called diazotrophs, converts nitrogen gas (N2) into bioavailable nitrogen that can support the growth of marine phytoplankton. By supplying new nitrogen to marine ecosystems, marine N2 fixation affects marine primary production, the uptake of carbon dioxide and ultimately the global climate. However, the environmental controls on N2 fixation and the physiologies of diverse diazotrophs remain elusive, in great part due to the limited number of observations. As part of this dissertation, I applied a variety of approaches including statistical modeling, high-resolution field measurements, and gene sequencing to characterize the biogeography of marine diazotrophy.The first approach was to model marine N2 fixation and diazotrophs using machine learning methods. To that end, I conducted meta-analyses to update the global datasets of N2 fixation and diazotrophs. The number of observations in these updated datasets are ~80% and over 100% larger than previous datasets, respectively. Simple correlation analyses between N2 fixation rates and different environmental factors failed to identify a single factor explaining marine N2 fixation at a global scale. In contrast, individual diazotrophic phylotypes showed distinct relations to environmental properties. Machine learning methods including random forest (RF) and support vector regression (SVR) simulated the observed N2 fixation and diazotrophs fairly well by accounting for nonlinearities among multiple environmental factors. The estimated global N2 fixation fluxes from the two statistical models were within the range of other studies. However, the machine learning estimates and other simulations in some cases showed substantial disagreement in both the magnitude and distribution of N2 fixation and diazotrophs, especially in high latitudes and the eastern equatorial Pacific, where observations are scarce. The large uncertainties in simulated N2 fixation and diazotrophs emphasized the need for a better understanding of the factors regulating N2 fixation and the physiology of diazotrophs.Achieving this goal can be labor-intensive and difficult with current techniques, which are based on discrete sampling and long incubation time. To overcome some of the drawbacks of traditional methods, our laboratory developed a method for high-frequency underway N2 fixation measurements. This method provides better coverage of the spatial and temporal heterogeneity in N2 fixation. I deployed this method over large swaths of the western North Atlantic Ocean in the summers of 2015, 2016, and 2017, covering over 10,000 km cruise tracks. This extensive survey identified new hotspots of N2 fixation in the coastal waters of the mid-Atlantic Bight. By coupling high-resolution N2 fixation observations with underway estimates of net community production (NCP) derived from O2/Ar measurements, I revealed the heterogeneous contribution of N2 fixation to NCP and to the carbon cycle, with a surprisingly large contribution in coastal waters.In addition to the spatial distribution of N2 fixation, I also characterized types of diazotrophs responsible for N2 fixation and how they responded to varying environmental conditions. By measuring diazotrophic diversity, abundance and activity at high-resolution using newly developed underway sampling and sensing techniques, I captured a shift between diazotrophs from Trichodesmium to UCYN-A from oligotrophic warm (25-29 °C) subtropical Sargasso Sea to the relatively nutrient-enriched cold (13-24 °C) eastern American coastal waters. Meanwhile, N2 fixation rates were significantly enhanced when phosphorus and Fe availabilities, and chlorophyll-a concentration increased across the Gulf Stream into the subpolar and coastal waters. Phosphorus limitation was confirmed with changes in the expression of phosphorus uptake genes in Trichodesmium and UCYN-A. While temperature was the major factor controlling the diazotrophic community, phosphorous was dominantly driving the changes of N2 fixation rates in the western North Atlantic.Overall, this dissertation significantly improves our understanding of the distribution of N2 fixation and diazotrophs and their environmental controls in the western North Atlantic and in the global ocean.
590 $a School code: 0066.
650 4 $a Chemical Oceanography. $3 1674678
650 4 $a Biological oceanography. $3 2122748
650 4 $a Biogeochemistry. $3 545717
653 $a Diazotroph
653 $a Gene sequencing
653 $a High resolution observation
653 $a High resolution sampling
653 $a Machine learning
653 $a Marine nitrogen fixation
690 $a 0403
690 $a 0416
690 $a 0425
710 2 $a Duke University. $b Earth and Ocean Sciences. $3 3194646
773 0 $t Dissertations Abstracts International $g 80-12B.
790 $a 0066
791 $a Ph.D.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13807788