About

Andrew Barton received his Ph.D in Climate Physics and Chemistry from Massachusetts Institute of Technology in 2011, and was an NSF International Research Postdoctoral Fellow hosted jointly between Duke University and the University of Liverpool in the United Kingdom. Dr. Barton joined the faculty of Biological Sciences and the Scripps Institution of Oceanography in 2016. His research focuses on marine phytoplankton, microscopic photosynthetic organisms living in the ocean surface that form the base of the marine food chain and impact larger marine organisms. His work seeks to map the distribution of phytoplankton species in the ocean and understand the biological and ecological processes underlying these patterns. He investigates how changes in Earth's climate, including natural variability and long-term human-driven changes, can alter phytoplankton community composition and distribution. To study these complex natural processes, he develops advanced computer models that simulate the marine environment and plankton interactions, integrating these models with real-world observational data to derive new insights into marine plankton life. His research aims to build understanding of this critical component of life on Earth.

Research topics

• Biology
• Ecology
• Environmental science
• Oceanography
• Geology
• Atmospheric sciences

Selected publications

• Reversible Regime Change: Climate-driven phytoplankton community shifts in the Cariaco Basin, Venezuela

  2025-09-01

  articleOpen access

  Phytoplankton communities are integral to oceanic biogeochemical cycles and are sensitive indicators of climate-driven environmental variability. Long-term time series capture this variability, allowing us to unravel the effects of environmental change on local communities. This study investigates changes in the phytoplankton community of the Cariaco Basin, off the coast of Venezuela, from 1995 to 2017, using monthly water column observations integrated with climate indices and meteorological data. To investigate impacts of larger-scale climate variability, we considered the Atlantic Multidecadal Oscillation (AMO) index and the Multivariate El Niño Southern Oscillation index (MEI v.2), both linked to variations in local weather and upwelling in the Cariaco Basin. Cluster analysis identified two distinct community states separated by a shift from high to low upwelling conditions in 2004. In 2014, community and environmental conditions returned a state similar to that before the shift in 2004. In contrast, diversity declined between 1998 and 2009 independently of changes in the upwelling regime. To quantify effects of climate and bottom-up drivers on phytoplankton community changes, we employed gradient forest analysis and found the AMO index was the strongest predictor, closely followed by in situ variables related to upwelling (sea surface temperature and nitrate concentration) and the MEI v.2. Our study emphasizes the impact of long-term climatic oscillations, such as the AMO, on the phytoplankton community of a tropical coastal ecosystem through modulation of the upwelling system and suggests a possible cyclic (if not resilient) behavior of this tropical marine ecosystem under global change.

  PublisherOA PDFDOI

• Real‐Time Empirical Risk Assessment From Recurrent Coastal Sewage Plumes

  GeoHealth · 2025-12-01

  articleOpen accessSenior author

  Abstract Untreated wastewater enters the ocean at an outfall in Mexico and spreads to the San Diego‐Tijuana (USA‐Mexico) border region, posing significant risks to human health. Here, we developed a risk assessment tool for coastal communities, leveraging hindcast oceanographic simulations (2017–2019), to link changes in temperature and salinity at the coastline to high wastewater concentrations. We first calculated the modeled timescales (i.e., duration and return time) of wastewater exposure for popular beaches in the region. Most high wastewater exposure events occurred about once a month and lasted less than a week at the southern locations (e.g., Imperial Beach), and occurred less frequently and for shorter periods of time further north (e.g., Coronado). Using the same hindcast simulations, we then identified relationships between anomalous environmental conditions and wastewater concentration along the coastline. High wastewater concentrations were typically associated with lower salinity and temperature, reflecting the low salinity of wastewater and the colder temperatures of water originating south of the USA‐Mexico border. Statistical models with only parameters of salinity and temperature anomalies captured a large proportion of the variation in wastewater‐associated risk of illness ( R 2 = 0.63–0.78). We tested the risk assessment approach with several months of recent observations (January–December 2024) to show how this tool may be practically applied. This study provides an efficient method for developing risk models that utilize commonly measured environmental data, with applications to other pollution‐impacted coastal locations.

  PublisherOA PDFDOI

• Temporal dynamics and distributions of sardine and anchovy in the southern California Current Ecosystem

  Canadian Journal of Fisheries and Aquatic Sciences · 2025-01-01

  articleOpen access

  Anchovies and sardines are some of the most economically and ecologically important and well-studied fishes on Earth, but there is still uncertainty regarding how distributions and abundances change through time and space. We bring together larval abundance data for northern anchovy ( Engraulis mordax) and Pacific sardine ( Sardinops sagax) collected by United States and Mexican scientists over 50 years (1963–2015) to test the Basin and Asynchrony hypotheses. The Basin hypothesis states that a species’ geographic range and spawning area ( R) increase with overall abundance ( A) according to a power law, R = aA b , where the exponent ( b) is less than ∼0.5 when the rate of increasing area occupied saturates as population size increases. The Asynchrony hypothesis postulates that anchovy and sardine abundances are negatively correlated through time. We found that the Basin hypothesis was supported for both species but the Asynchrony hypothesis was not during this 53-year period. Due to collaboration between US and Mexican scientists, we were able to better understand how two important fishes utilize their environment.

  PublisherOA PDFDOI

• Traits determine dispersal and colonization abilities of microbes

  Applied and Environmental Microbiology · 2025-02-20 · 7 citations

  articleOpen access

  Many microbes disperse through the air, yet the phenotypic traits that enhance or constrain aerial dispersal or allow successful colonization of new habitats are poorly understood. We used a metabarcoding bacterial and eukaryotic data set to explore the trait structures of the aquatic, terrestrial, and airborne microbial communities near the Salton Sea, California, as well as those colonizing a series of experimental aquatic mesocosms. We assigned taxonomic identities to amplicon sequence variants (ASVs) and matched them to functional trait values through published papers and databases that infer phenotypic and/or metabolic traits information from taxonomy. We asked what traits distinguish successful microbial dispersers and/or colonizers from terrestrial and aquatic source communities. Our study found broad differences in taxonomic and trait composition between dispersers and colonizers compared to the source soil and water communities. Dispersers were characterized by larger cell diameters, colony formation, and fermentation abilities, while colonizers tended to be phototrophs that form mucilage and have siliceous coverings. Shorter population doubling times, spore-, and/or cyst-forming organisms were more abundant among the dispersers and colonizers than the sources. These results show that the capacity for aerial dispersal and colonization varies among microbial functional groups and taxa and is related to traits that affect other functions like resource acquisition, predator avoidance, and reproduction. The ability to disperse and colonize new habitats may therefore distinguish microbial guilds based on tradeoffs among alternate ecological strategies.IMPORTANCEMicrobes have long been thought to disperse rapidly across biogeographic barriers; however, whether dispersal or colonization vary among taxa or groups or is related to cellular traits remains unknown. We use a novel approach to understand how microorganisms disperse and establish themselves in different environments by looking at their traits (physiology, morphology, life history, and behavior characteristics). By collecting samples from habitats including water, soil, and the air and colonizing experimental tanks, we found dispersal and invasion vary among microorganisms. Some taxa and functional groups are found more often in the air or colonizing aquatic environments, while others that are commonly found in the soil or water rarely disperse or invade new habitat. Interestingly, the traits that help microorganisms survive and thrive also play a role in their ability to disperse and colonize. These findings have significant implications for understanding microorganisms' success and adaptation to new environments.

  PublisherDOI

• Extreme wildfire conditions shift coastal phytoplankton community structure in California

  Limnology and Oceanography · 2025-11-28

  articleOpen access

  Abstract Extreme wildfires have increased in frequency and intensity globally, particularly in the Western United States. Here we examine how the 2020 Lightning Complex Fires in California influenced coastal phytoplankton communities using monitoring network data products in the Monterey Bay, the ocean region closest to this large fire. We observed no clear response in ocean chlorophyll a , often considered a proxy for total phytoplankton biomass, during and after the fires. However, using phytoplankton community composition observations we detected a shift in phytoplankton size and taxonomic structure that coincided with the timing of the fires. Small centric diatoms initially dominated, followed by a proliferation of chain‐forming diatoms, including Asterionellopsis , Skeletonema , Hemiaulus , Leptocylindrus , Thalassionema , and Thalassiosira . Cross‐correlation analysis and generalized additive models identified wildfire aerosols (PM2.5) as a significant predictor of these diatom blooms, though the precise mechanisms remain uncertain. We speculate that a combination of nutrient deposition, light limitation from smoke shading, interactions with oceanographic conditions, and differential mortality due to grazing or toxicity drove the observed phytoplankton shifts. This study provides rare observational evidence linking extreme wildfires to changes in coastal phytoplankton communities and underscores the need for sustained ocean monitoring, rapid‐response sampling, and mechanistic studies to unravel these complex wildfire–ocean interactions.

  PublisherDOI

• Relationships between phytoplankton pigments and DNA- or RNA-based abundances support ecological applications

  Biogeosciences · 2025-11-14 · 2 citations

  articleOpen accessCorresponding

  Abstract. Observations of phytoplankton abundances and community structure are critical towards understanding marine ecosystems. Common approaches to determine group-specific abundances include measuring phytoplankton pigments with high-performance liquid chromatography and DNA-based metabarcoding. Increasingly, mRNA abundances with metatranscriptomics are also employed. As phytoplankton pigments are used to develop and validate remote sensing algorithms, further comparisons between pigments and other metrics are needed to validate the extent to which these measurements agree for group-specific abundances; however, most previous comparisons have been hindered by metabarcoding and metatranscriptomics solely producing relative abundance data. By employing quantitative approaches that express both 18S rRNA genes (DNA) and total mRNA as concentrations, we show that these measurements are related for several eukaryotic phytoplankton groups. We further propose that integration of these can be used to examine ecological patterns more deeply. For example, productivity-diversity relationships of both the whole community and individual groups show a dinoflagellate-driven negative trend rather than the commonly found unimodal pattern. Pigments are also shown to relate to certain harmful algal bloom-forming taxa as well as the expression of sets of genes. Altogether, these results suggest that potential models of pigment concentrations via hyperspectral remote sensing may enable improved assessments of global phytoplankton community structure. These assessments may further support the detection of harmful algal blooms and the development of Earth system models.

  PublisherOA PDFDOI

• The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python

  Geoscientific model development · 2024-02-13 · 2 citations

  articleOpen accessCorresponding

  Abstract. Plankton community modeling is a critical tool for understanding the processes that shape marine ecosystems and their impacts on global biogeochemical cycles. These models can be of variable ecological, physiological, and physical complexity. Many published models are either not publicly available or implemented in static and inflexible code, thus hampering adoption, collaboration, and reproducibility of results. Here we present Phydra, an open-source library for plankton community modeling, and Xarray-simlab-ODE (XSO), a modular framework for efficient, flexible, and reproducible model development based on ordinary differential equations. Both tools are written in Python. Phydra provides pre-built models and model components that can be modified and assembled to develop plankton community models of various levels of ecological complexity. The components can be created, adapted, and modified using standard variable types provided by the XSO framework. XSO is embedded in the Python scientific ecosystem and is integrated with tools for data analysis and visualization. To demonstrate the range of applicability and how Phydra and XSO can be used to develop and execute models, we present three applications: (1) a highly simplified nutrient–phytoplankton (NP) model in a chemostat setting, (2) a nutrient–phytoplankton–zooplankton–detritus (NPZD) model in a zero-dimensional pelagic ocean setting, and (3) a size-structured plankton community model that resolves 50 phytoplankton and 50 zooplankton size classes with functional traits determined by allometric relationships. The applications presented here are available as interactive Jupyter notebooks and can be used by the scientific community to build, modify, and run plankton community models based on differential equations for a diverse range of scientific pursuits.

  PublisherOA PDFDOI

• Relationships between phytoplankton pigments and DNA- or RNA-based abundances support ecological applications

  2024-11-04 · 3 citations

  preprintOpen accessCorresponding

  Abstract. Observations of phytoplankton abundances and community structure are critical towards understanding marine ecosystems. Common approaches to determine group-specific abundances include measuring phytoplankton pigments via high-performance liquid chromatography and DNA-based metabarcoding. Increasingly, mRNA abundances via metatranscriptomics are also employed. As phytoplankton pigments are used to develop and validate remote sensing algorithms, further comparisons between pigments and other metrics are needed to validate the extent to which these measurements agree for group-specific abundances; however, most previous comparisons have been hindered by metabarcoding and metatranscriptomics solely producing relative abundance data. By employing quantitative approaches that express both 18S rDNA and total mRNA as concentrations, we show that these measurements are related for several eukaryotic phytoplankton groups. We further propose that integration of these can be used to examine ecological patterns more deeply. For example, productivity-diversity relationships of both the whole community and individual groups show a dinoflagellate-driven negative trend rather than the commonly-found unimodal pattern. Pigments are also shown to relate to certain harmful algal bloom-forming taxa as well as the expression of sets of genes. Altogether, these results suggest that potential models of pigment concentrations via hyperspectral remote sensing may enable improved assessments of global phytoplankton community structure, including the detection of harmful algal blooms, and support the development of ecosystem models.

  PublisherOA PDFDOI

• Changes in Arctic Ocean plankton community structure and trophic dynamics on seasonal to interannual timescales

  2024-05-07

  preprintOpen accessSenior authorCorresponding

  Abstract. The Arctic Ocean experiences significant seasonal to interannual environmental changes, including in temperature, light, sea ice, and surface nutrient concentrations, that influence the dynamics of marine plankton populations. Here, we use a hindcast simulation (1948–2009) of size-structured Arctic Ocean plankton communities, ocean circulation, and biogeochemical cycles in order to better understand how seasonal to interannual changes in the environment influence phytoplankton physiology, plankton community structure, trophic dynamics, and fish production in the Arctic Ocean. The growth of model phytoplankton was primarily limited in winter, spring, and fall by light, but in summer, the growth of smaller and larger phytoplankton was mostly limited by temperature and nutrient availability, respectively. The dominant trophic pathway in summer was from phytoplankton to herbivorous zooplankton, such that the average trophic position of model zooplankton was lower in the summer growing season compared with the rest of the year. On interannual timescales, changes in plankton community composition were strongly tied to interannual changes in bottom-up forcing by the environment. In the summer, in years with lower ice and warmer temperatures, the biomass of phytoplankton and zooplankton was higher, the size abundance relationship slopes were more negative (indicative of a phytoplankton community enriched in smaller phytoplankton), zooplankton had higher mean trophic position (indicative of greater carnivory), and potential fisheries production was greater, fueled by increased mesozooplankton biomass and flux of organic matter to the benthos. The summertime shift toward greater carnivory in warmer and low-ice years was due primarily to changes in phenology, with phytoplankton and microzoopankton blooms occurring approximately one month earlier in these conditions, and carnivorous zooplankton increasing in abundance during summer. The model provides a spatially and temporally complete overview of changes in plankton communities in the Arctic Ocean occurring on seasonal to interannual timescales, and provides insights on the mechanisms underlying these changes as well as their broader biogeochemical and ecosystems significance.

  PublisherDOI

• Supplementary material to "Changes in Arctic Ocean plankton community structure and trophic dynamics on seasonal to interannual timescales"

  2024-05-07

  preprintOpen accessSenior author
  PublisherOA PDFDOI

Recent grants

• IRFP: Physical Regulation of Long-Term Ecosystem Variability in the North Atlantic

  NSF · $124k · 2013–2014

Frequent coauthors

• Charles A. Stock

  NOAA Geophysical Fluid Dynamics Laboratory

  32 shared

• Fernando González Taboada

  21 shared

• Jessica Y. Luo

  NOAA Geophysical Fluid Dynamics Laboratory

  21 shared

• Peter J. S. Franks

  University of Massachusetts Dartmouth

  20 shared

• Eric C. Orenstein

  Monterey Bay Aquarium Research Institute

  18 shared

• Ariel Rabines

  Scripps Institution of Oceanography

  17 shared

• Robert Lampe

  University of California, San Diego

  17 shared

• Andrew E. Allen

  Scripps Institution of Oceanography

  17 shared

Education

• PhD

  Massachusetts Institute of Technology

  2011