Tootfinder

Qualitative Dynamics of a Discrete Phytoplankton-Zooplankton System with Holling Type II Grazing and Type III Toxin Release
Sobirjon Shoyimardonov
https://arxiv.org/abs/2507.18094

Qualitative Dynamics of a Discrete Phytoplankton-Zooplankton System with Holling Type II Grazing and Type III Toxin Release
We study the dynamics of a discrete phytoplankton-zooplankton model with Holling type~II grazing and Holling type~III toxin release. The existence and stability of positive fixed points are analyzed, and conditions for the occurrence of Neimark--Sacker bifurcation are established. We show how feedback control can suppress complex dynamics near bifurcation. Global stability of the boundary equilibrium is also discussed. Numerical simulations confirm the theoretical findings, illustrating the ric…

Qualitative Dynamics of a Discrete Phytoplankton-Zooplankton System with Holling Type II Grazing and Type III Toxin Release
Sobirjon Shoyimardonov
https://arxiv.org/abs/2507.18094

My @… colleague Alex Hayward recently published an alarming paper on how @… satellite data can detect changes in #Antarctic ecosystems.
They just published this nice piece on it.
QT from BlueSky
"Antarctica's tiniest climate witnesses are changing 🦠
Climate is reshaping Antarctic phytoplankton, impacting carbon storage and the marine food chain. 25 years of ESA Climate Change Initiative satellite data paired with 14,000 in-situ samples reveal how."
https://climate.esa.int/en/news-events/shift-in-Antarctic-plankton/

Weekend #Plankton Factoid 🦠🦐
Did you know that plankton can get sunburn? UV radiation can affect microbes, #phytoplankton and #zooplankton by causing cellular molecular or genetic damage. Whil…

Detecting the most probable transition phenomenon of a nutrient-phytoplankton-zooplankton system
Hui Wang, Ying Wang, Xi Chen
https://arxiv.org/abs/2507.12915 https://

Detecting the most probable transition phenomenon of a nutrient-phytoplankton-zooplankton system
The population biology model holds a significant position within ecosystems. Introducing stochastic perturbations into the model can more accurately depict real biological processes. In this paper, we primarily investigate the most probable transition phenomenon in a three-dimensional nutrient-phytoplankton-zooplankton (NPZ) plankton model. With appropriate parameter values, the system coexists with a stable equilibrium point and a stable limit cycle. Under noise perturbations, transitions occu…

Combining machine learning with data assimilation to improve the quality of phytoplankton forecasting in a shelf sea environment
Deep S Banerjee, Jozef Skakala, David Ford
https://arxiv.org/abs/2508.02400

Combining machine learning with data assimilation to improve the quality of phytoplankton forecasting in a shelf sea environment
We demonstrate that combining machine learning with data assimilation leads to a major improvement in phytoplankton short-range (1-5 day) forecasts for the North-West European Shelf (NWES) seas. We show that excess nitrate concentrations are a major reason behind known biases in phytoplankton forecasts during late Spring and Summer, which can grow fast with lead time. Assimilating observations of nitrate would potentially help address this, but NWES nitrate data are typically not available in s…

Mixtures of Neural Network Experts with Application to Phytoplankton Flow Cytometry Data
Ethan Pawl, Fran\c{c}ois Ribalet, Paul A. Parker, Sangwon Hyun
https://arxiv.org/abs/2507.01375

Mixtures of Neural Network Experts with Application to Phytoplankton Flow Cytometry Data
Flow cytometry is a valuable technique that measures the optical properties of particles at a single-cell resolution. When deployed in the ocean, flow cytometry allows oceanographers to study different types of photosynthetic microbes called phytoplankton. It is of great interest to study how phytoplankton properties change in response to environmental conditions. In our work, we develop a nonlinear mixture of experts model for simultaneous clustering and regression utilizing random-weight neur…

Consider: we came fairly close to extincting the various species crucial to this cycle *AND STILL COULD.*
The problem today isn’t the ongoing symbolic & subsistence whaling, it is that we have ravaged the ocean ecosystem in ways we don’t understand, such as noise pollution.
We really don’t understand enough about the subsystems of the oceans to be fucking with them in the ways we have been during the past century.

Bioluminescence in turbulence: intermittent straining lights up dinoflagellates
Praphul Kumar, Jason R. Picardo
https://arxiv.org/abs/2509.13273 https://ar…

Bioluminescence in turbulence: intermittent straining lights up dinoflagellates
Dinoflagellates are marine phytoplankton that emit flashes of light in response to flow-induced deformation; they are responsible for illuminating breaking-waves, wakes of ships, and other intensely turbulent spots of the upper ocean. Here, we ask how bioluminescence is affected by the fluctuating nature of turbulence -- a question motivated by the dependence of emitted flashes on both the extent and rate of deformation. Introducing a light-emitting dumbbell as a minimal model, we study the Lag…

Discrete Dynamics of a Phytoplankton-Zooplankton Model with Toxin-Mediated Interactions
Sobirjon Shoyimardonov
https://arxiv.org/abs/2508.07942 https://arx…

Discrete Dynamics of a Phytoplankton-Zooplankton Model with Toxin-Mediated Interactions
We investigate the dynamics of a discrete phytoplankton-zooplankton model incorporating Holling type~III predation and Holling type~II toxin release. The existence and stability of positive fixed points are analyzed, and it is shown that when two such points, $E_1$ and $E_2$, exist, $E_2$ is always a saddle. A Neimark-Sacker bifurcation at $E_1$ is verified using the normal form method, indicating the emergence of closed invariant curves. This bifurcation implies that phytoplankton and zooplank…

Replaced article(s) found for q-bio.OT. https://arxiv.org/list/q-bio.OT/new
[1/1]:
- Parameterization of Photoinhibition For Phytoplankton
Mohammad M. Amirian, Zoe V. Finkel, Emmanuel Devred, Andrew J. Irwin