DOI: 10.5281/zenodo.14183327
title: Environmental Gradients Drive Shifts in Phytoplankton Community Structure

description: The two datasets "EnvironmentalData.csv" and "PSD_TransitionZone.csv" provide information about the environmental conditions and the distribution of phytoplankton populations in the North Pacific Ocean. 

Specifically, the "EnvironmentalData.csv" dataset contains measurements of various environmental parameters, including salinity, temperature, nutrient concentrations, and light availability. These measurements were used to characterize the physical and chemical conditions of the different regions sampled during the study, including the North Pacific Subtropical Gyre (NPSG) and the surrounding regions.  The dataset include:



cruise: The identifier for the research cruise.

lat: Latitude.

lon: Longitude.

date: Date and time of the observation.

salinity: Salinity of the water (PSU).

temp: Water temperature (ºC).

par: Photosynthetically Active Radiation (µmol photons m-2 s-1).

SiO4: Silicate concentration (µM).

NO3_NO2: Nitrate and nitrite concentration (µM).

PO4: Phosphate concentration (µM).

MLD: Mixed layer depth (m).

light: Daily averaged PAR (µmol photons m-2 s-1).


The "PSD_TransitionZone.csv" dataset contains information about the abundance, size, and biomass of different phytoplankton populations, including Prochlorococcus, Synechococcus, picoeukaryotes, and nanoeukaryotes. These data were collected using SeaFlow - a custom-built flow cytometer,  and were used to investigate how the distribution and composition of phytoplankton communities change in relation to environmental gradients. The dataset include:



cruise: The identifier for the research cruise.

date: Date and time of the observation.

pop: Population type.

lat: Latitude.

lon: Longitude.

n_per_uL: Number of cells per microliter (10^6 cells µL-1).

c_per_uL: Carbon per microliter (pgC µL-1).

qc: Carbon quotas (pgC/cell).

diam: Diameter (µm).


The R script "analysis.R" perfoms the analysis of the environmental and phytoplankton data in the North Pacific Ocean. The script performs the following steps:



Data Preprocessing: Cleans and prepares the data for analysis, including handling missing values and converting date/time formats.

Diel Trend Extraction: Extracts diel (day-night) trends from the phytoplankton data using a custom function that decomposes time series data into seasonal, trend, and residual components.

Data Merging: Merges the environmental and phytoplankton data into a single dataset for analysis.

Growth Rate Calculation: Calculates the cellular growth rate of different phytoplankton populations based on changes in their carbon quotas during daylight hours.

North Pacific Subtropical Gyre (NPSG) Boundary Definition: Defines the boundaries of the NPSG based on changes in salinity along the cruise tracks.

Binning and Summarization: Bins the data over distance from the NPSG boundaries and calculates mean and standard deviation for various parameters within each bin.

Figure Generation: Generates several figures, including:



A map showing the cruise tracks and the location of the NPSG.

Plots showing the change in environmental parameters (salinity, temperature, nutrients) across the NPSG boundaries.

Plots showing the change in phytoplankton biomass, abundance, and growth rate across the NPSG boundaries.

A correlation plot showing the relationship between phytoplankton growth, biomass, and environmental parameters.