phytoplankton
There are 0 repository under phytoplankton topic.
AquaticEcoDynamics / libaed2
Code for the AED2 water quality / ecology library
Language:Fortran 13OSU-CEOAS-Schmittner / UVic2.9
This is the base code of the University of Victoria (UVic) Earth System Climate Model version 2.9 with the Model of Ocean Biogeochemistry and Isotopes (MOBI).
Language:Fortran 9seaflow-uw / popcycle
Popcycle is an R package that offers reproducible analytical tools to analyze flow cytometry data collected by SeaFlow
Language:R 9JoanaR / multi-mode-CNN-pytorch
A PyTorch implementation of the Multi-Mode CNN to reconstruct Chlorophyll-a time series in the global ocean from oceanic and atmospheric physical drivers
attention-mechanismsdeep-learninginterpretabilityphytoplanktonpytorchsatellite-datatime-seriesbiogeochemical-regionsglobal-scalephysical-driversseasonal-interannual-timescaleregressionmarine-scienceoceanographyearth-observationremote-sensingclimateocean-colorchlorophyll-aconvolutional-neural-networksLanguage:Jupyter Notebook 6jllort / PISCESv1_1D
As part of my PhD I created a 1D biogeochemical configuration based on PISCES model (version 1 - Bopp et al, 2005) The configuration was created to study the impact of environmental changes (mainly Mixed Layer Depth and Light) over Southern Ocean primary production, from the seasonal to decadal scales.
Language:Fortran 5blackcata / Emergent_Constraints
Calculating future changes in Arctic phytoplankton using the emergent constraint method
Language:Jupyter Notebook 4CassiaCai / MJO_chlorophyll_a_SST
Research Derby project to study the connection between MJO, chlorophyll-a, and SST
Language:Jupyter Notebook 3vaulot / Ribeiro_CARBOM_ISME_2018
Supplementary files for Ribeiro et al. ISME 2018
Language:Shell 3- Language:Jupyter Notebook 2
Modules for the Lagrangian Plankton Model (LPM) integrated on the PALM LES model in the ocean mixed layer
Language:Fortran 2- planktos
cee8 / planktos
Planktos is an image recognition model tailored for classifying various species of phytoplankton. Built using cutting-edge machine learning algorithms, this tool enables researchers and environmentalists to automate and accelerate the identification process, enhancing studies in marine biology and ecology.
Language:Python 2 dkauf42 / PIcurves
Functions and a walkthrough to visualize common photosynthesis-irradiance relationships
Language:MATLAB 2SalishSeaCast / SOG-Bloomcast-Ensemble
Branch of the SoG-bloomcast project that uses an ensemble forecast.
Language:Jupyter Notebook 2PStegmann / Westberry_08_model
An implementation of the depth-resolved phytoplankton primary production model by Westberry et al. 2008.
Language:Fortran 1- fidoplankter
arivers / fidoplankter
An online calculator for iron limitation culture experiments
Language:R 0 Calculate various MHWs(Marine Heat Waves) properties from daily SST datas
Language:Fortran 0Function that calculates the maximum phytoplankton growth rate at specified temperature(s) according to the Eppley growth curve
Language:MATLAB 0Isabell-Hochfeld / Adaptive-Phytoplankton-Community-Model
This work is part of the PhytoArk project.
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poplarShift / ice-edge
Code and data for Randelhoff et al. (2019), "The evolution of light and vertical mixing across a phytoplankton ice-edge bloom"
Language:HTML 0- Language:MATLAB 0
- Language:Jupyter Notebook
- Language:R
lg11235 / mixotroph-adaptive-dynamics
Provides Mathematica code to generate results from "Modeling the Metabolic Evolution of Mixotrophic Phytoplankton in Response to Rising Ocean Surface Temperatures"
Language:Mathematica- spinyAnoxia
robertladwig / spinyAnoxia
Scripts, data and outputs to process the data and recreate the figures from Rohwer, Ladwig et al. (2022)
Language:R Superseded by https://github.com/SalishSeaCast/SOG-Bloomcast-Ensemble. SoG-bloomcast is a an operational oceanography project to provide daily updated forecasts of the first spring phytoplankton bloom in the Strait of Georgia on the British Columbia south coast. In addition to being part of an active research program on the physics and biogeochemistry of the Salish Sea, SoG-bloomcast is intended as a demonstration of how small university research groups can use lightweight software automation to publish near-real-time model results to the web. SoG-bloomcast uses the SOG coupled physics-biogeochemical model for deep estuaries to do its science.
Language:PythonCorrection for flow cytometry histograms when part of the population is in noise
Language:R
