Model Of Plankton Dynamics Research Articles

High-resolution metagenomic reconstruction of the freshwater spring bloom

BackgroundThe phytoplankton spring bloom in freshwater habitats is a complex, recurring, and dynamic ecological spectacle that unfolds at multiple biological scales. Although enormous taxonomic shifts in microbial assemblages during and after the bloom have been reported, genomic information on the microbial community of the spring bloom remains scarce.ResultsWe performed a high-resolution spatio-temporal sampling of the spring bloom in a freshwater reservoir and describe a multitude of previously unknown taxa using metagenome-assembled genomes of eukaryotes, prokaryotes, and viruses in combination with a broad array of methodologies. The recovered genomes reveal multiple distributional dynamics for several bacterial groups with progressively increasing stratification. Analyses of abundances of metagenome-assembled genomes in concert with CARD-FISH revealed remarkably similar in situ doubling time estimates for dominant genome-streamlined microbial lineages. Discordance between quantitations of cryptophytes arising from sequence data and microscopic identification suggested the presence of hidden, yet extremely abundant aplastidic cryptophytes that were confirmed by CARD-FISH analyses. Aplastidic cryptophytes are prevalent throughout the water column but have never been considered in prior models of plankton dynamics. We also recovered the first metagenomic-assembled genomes of freshwater protists (a diatom and a haptophyte) along with thousands of giant viral genomic contigs, some of which appeared similar to viruses infecting haptophytes but owing to lack of known representatives, most remained without any indication of their hosts. The contrasting distribution of giant viruses that are present in the entire water column to that of parasitic perkinsids residing largely in deeper waters allows us to propose giant viruses as the biological agents of top-down control and bloom collapse, likely in combination with bottom-up factors like a nutrient limitation.ConclusionWe reconstructed thousands of genomes of microbes and viruses from a freshwater spring bloom and show that such large-scale genome recovery allows tracking of planktonic succession in great detail. However, integration of metagenomic information with other methodologies (e.g., microscopy, CARD-FISH) remains critical to reveal diverse phenomena (e.g., distributional patterns, in situ doubling times) and novel participants (e.g., aplastidic cryptophytes) and to further refine existing ecological models (e.g., factors affecting bloom collapse). This work provides a genomic foundation for future approaches towards a fine-scale characterization of the organisms in relation to the rapidly changing environment during the course of the freshwater spring bloom.B2NzroPNjWa1JSkBbq3YLpVideo

Three-dimensional turbulence effects on plankton dynamics behind an obstacle

We study a predator–prey model of plankton dynamics in the two and three-dimensional wakes of turbulent flows behind a cylinder, focusing on the impact of the three-dimensional character of the carrying velocity field on population variance spectra and spatial distributions. By means of direct numerical simulations, we find that the qualitative behavior of the biological dynamics is mostly independent of the space dimensionality, which suggests that only the relation between the typical flow and biological timescales is crucial to observe persistent blooms. Similarly, in both cases, we find that the spectral properties of the planktonic populations are essentially indistinguishable from those of an inert tracer. The main difference arising from the comparison of the two- and three-dimensional configurations concerns the local spatial distribution of plankton density fields. Indeed, the three-dimensional turbulent dynamics tend to destroy the localized coherent structures characterizing the two-dimensional flow, in which the planktonic species are mostly concentrated, thus reducing the phytoplankton biomass in the system.

Predator-prey plankton dynamics in turbulent flow past an obstacle

Plankton constitutes the productive base of aquatic ecosystems and plays an essential role in the global carbon cycle. The impact of hydrodynamic conditions on the biological activity of plankton species can manifest in a variety of different ways and the understanding of the basic effects due to multiscale complex flows still appears incomplete. Here, we consider a predator-prey model of plankton dynamics in the presence of a turbulent flow past an idealized island, to investigate the conditions under which an algal bloom is observed, and the resulting patchiness of plankton distributions. By means of direct numerical simulations, we explore the role of the turbulent intensity and of the island shape. In particular, we focus on population variance spectra, and on their relation with the statistical features of the turbulent flow, as well as on the correlation between the spatial distribution of the planktonic species and velocity field persistent structures. We find that both the average biomass and local plankton dynamics critically depend on the relation between advective and biological time scales, confirming and extending previous results obtained in simpler flow settings. We further provide evidence that, in the present system, due to local flow action plankton accumulates in localized filamentary regions. Small turbulent scales are found to impact the statistics of plankton density fields at very fine scales, but the main global features of the population dynamics only weakly depend on the Reynolds number and are also found to be remarkably independent of the geometrical details of the obstacle.

Predictability of plankton communities in an unpredictable world

Summary1. Plankton ecology contributes significantly to ecological theory building, because plankton organisms are relatively easy to manipulate and have short generation times and a relatively small set of traits making them an ideal experimental model system for addressing both general ecological questions as well more system‐specific questions.2. Since the environment is changing at an unprecedented rate, there is an ongoing demand for predictions from plankton ecology on the consequences of global change.3. In 2010, a colloquium was held on three subjects: chaos versus predictability in plankton dynamics, global patterns versus regional differences in plankton dynamics and climate‐induced changes in plankton dynamics.4. Papers in this Special Issue propose a new model of plankton dynamics under climate change in different climate zones; offer increased attention to the role of winters in resetting population dynamics; discuss the effects of climate change on ecological stoichiometry and efficiency of trophic transfer; describe the relative and interacting effects of changes in temperature and hydrology on plankton; and analyse the effects of climate change on host–parasite dynamics.5. Important research gaps include increased monitoring of understudied climatic zones, adaptation of plankton organisms to altered environmental conditions, interactions of climate change with legacy nutrients, interactions with other anthropogenic pressures and interactions with the infochemical network.

Markov chain model of phytoplankton dynamics

Markov chain model of phytoplankton dynamicsA discrete-time stochastic spatial model of plankton dynamics is given. We focus on aggregative behaviour of plankton cells. Our aim is to show the convergence of a microscopic, stochastic model to a macroscopic one, given by an evolution equation. Some numerical simulations are also presented.

Influence of spatial heterogeneity on the type of zooplankton functional response: A study based on field observations

Mathematical models of plankton dynamics are sensitive to the choice of type of zooplankton functional response, i.e., to how the rate of intake of food varies with the food density. Conventionally, the conclusion on the actual type of functional response for a given zooplankton species is made based upon laboratory analysis on experimental feeding. In this paper, we show that such an approach can be too simplistic and misleading. Based on real ocean data obtained from three expeditions of R/V Jan Mayen in the Barents Sea in 2003–2005, we demonstrate that vertical heterogeneity in algal distribution as well as active vertical movement of herbivorous zooplankton can modify the type of trophic response completely. In particular, we found that the rate of average intake of algae by Calanus glacialis exhibits a Holling type III response, instead of Holling type I or II found previously in laboratory experiments. We argue that this conceptual discrepancy is due to the ability of the zooplankton to feed in layers with high algal density and to avoid depths with lower algal density. Since theoretical studies would predict enhancing in system stability in the case of Holling type III, our results may be of importance for understanding the main factors controlling plankton dynamics.

Adaptive model of plankton dynamics for the North Atlantic

Plankton ecosystems in the North Atlantic display strong regional and interannual variability in productivity and trophic structure, which cannot be captured by simple plankton models. Additional compartments subdividing functional groups can increase predictive power, but the high number of parameters tends to compromise portability and robustness of model predictions. An alternative strategy is to use property state variables, such as cell size, normally considered constant parameters in ecosystem models, to define the structure of functional groups in terms of both behaviour and response to physical forcing. This strategy may allow us to simulate realistically regional and temporal differences among plankton communities while keeping model complexity at a minimum. We fit a model of plankton and DOM dynamics globally and individually to observed climatologies at three diverse locations in the North Atlantic. Introducing additional property state variables is shown to improve the model fit both locally and globally, make the model more portable, and help identify model deficiencies. The zooplankton formulation exerts strong control on model performance. Our results suggest that the current paradigm on zooplankton allometric functional relationships might be at odds with observed plankton dynamics. Our parameter estimation resulted in more realistic estimates of parameters important for primary production than previous data assimilation studies. Property state variables generate complex emergent functional relationships, and might be used like tracers to differentiate between locally produced and advected biomass. The model results suggest that the observed temperature dependence of heterotrophic growth efficiency [Rivkin, R.B., Legendre, L., 2001. Biogenic carbon cycling in the upper ocean: effects of microbial respiration. Science 291 (5512) 2398–2400] could be an emergent relation due to intercorrelations among temperature, nutrient concentration and growth efficiency. A major advantage of using property state variables is that no additional parameters are required, such that differences in model performance can be directly related to model structure rather than parameter tuning.

Towards resolving the paradox of enrichment: The impact of zooplankton vertical migrations on plankton systems stability

Eutrophication, often resulting from human activity, is a serious threat to aquatic communities. Theoretical analysis of this phenomenon, based on conceptual mathematical models, leads to controversial predictions known as Rosenzweig's paradox of enrichment. At the same time, field observations demonstrate that real plankton communities exhibit various mechanisms of self-regulation which can buffer negative effects of enrichment. In this paper, we study potential effects of zooplankton vertical migration on stability of plankton systems functioning. We consider an intrinsically unstable plankton model, which is characterized by an unlimited phytoplankton multiplication and population oscillations of increasing amplitude, and investigate whether vertical migrations of zooplankton can stabilize such a system at low plankton densities. By means of developing two different models accounting for different ecological situations, e.g. deep waters and shallow waters, we show that vertical migrations of zooplankton can result in stabilization of eutrophic plankton systems. Thus, we show that this mechanism, rarely taken into account in models of plankton dynamics, may be important for resolving the paradox of enrichment in plankton communities.

Seasonal versus synoptic variability in planktonic production in a high‐latitude marginal sea: The Gulf of St. Lawrence (Canada)

The Gulf of St. Lawrence (Canada) is a subarctic marginal sea characterized by highly variable hydrodynamic conditions that generate a spatial heterogeneity in the marine production. A better understanding of physical‐biological linkages is needed to improve our ability to evaluate the effects of climate variability and change on the gulf's planktonic production. We develop a three‐dimensional (3‐D) eddy permitting resolution physical‐biological coupled model of plankton dynamics in the Gulf of St. Lawrence. The planktonic ecosystem model accounts for the competition between simplified herbivorous and microbial food webs that characterize bloom and post‐bloom conditions, respectively, as generally observed in temperate and subarctic coastal waters. It is driven by a fully prognostic 3‐D sea ice‐ocean model with realistic tidal, atmospheric, and hydrological forcing. The simulation shows a consistent seasonal primary production cycle, and highlights the importance of local sea ice dynamics for the timing of the vernal bloom and the strong influence of the mesoscale circulation on planktonic production patterns at subregional scales.

Quantifying the effects of dynamical noise on the predictability of a simple ecosystem model

AbstractThe need to understand the effects of anthropogenic perturbations on ocean biology has renewed interest in ecosystem and biogeochemical models in recent years. We develop a nonlinear time series approach to quantify the effects of different types of noise on ecosystem dynamics. Different types of noise can alter the local predictability of the system, induce qualitative regime shifts in model dynamics, and destroy (create) internal nonlinear oscillations and chaos. The ecosystem model we use in our article is a model of plankton dynamics and nitrogen cycling. It is a compartmental model (NPZD) consisting of compartments for nitrogen (N), phytoplankton (P), zooplankton (Z), and detritus (D). The flows or intercompartmental exchanges are modeled as a nonlinear system of four first‐order differential equations. The types of noise of interest are both independent and correlated. Because the noise is an integral part of the system's dynamics, a nonlinear time series approach is used to quantify the dynamics and predictability of the system. This involves fitting neural network models and estimating dynamical system quantities of interest such as global and local Lyapunov exponents, along with measures of uncertainty for these estimates. Copyright © 2004 John Wiley & Sons, Ltd.

Propagation of climatic events on ocean stratification, marine biology, and CO2: Case studies over the 1979–1999 period

We investigate the propagation of climatic events on ocean stratification, marine biology, and CO2 using a large‐scale ocean general circulation model coupled to a simple biogeochemical model of plankton dynamics and the carbon cycle. The model was forced with satellite and reanalysis fields during 1979–1999. We focus on three climatic events: (1) the North Atlantic Oscillation, (2) El Niño events, and (3) the Antarctic Circumpolar Wave. Such climatic events caused variability in ocean stratification, approximated by the mixing depth (MD), from ±20 m in the subtropics to ±100 s of meters at high latitudes. In the subtropics, deepening of the MD resupplied nutrient‐impoverished surface waters and increased marine biomass by 20–100%. In contrast, at high latitudes, shoaling of the MD lengthened the growing season (i.e., the length of time that light is available for plankton growth) and increased marine biomass by 10–20%. Variability in marine biology reached global peak‐to‐peak values of ±0.01 mg m−3 for surface chl a, ±3.4 Pg C yr−1 for primary production, and ±0.3 Pg C yr−1 for export production and its contribution to CO2 fluxes. Our model results suggest that changes in ocean stratification driven by short‐term climatic events could be used to understand and quantify the feedbacks from marine biology to CO2 and climate.

NPZ Models of Plankton Dynamics: Their Construction, Coupling to Physics, and Application

Nutrient-phytoplankton-zooplankton (NPZ) models have been in use in oceanography for at least three decades, and are still a common research tool. Given the discoveries of the last two decades, particularly concerning the role of bacteria in the plankton, there are questions as to whether NPZ models can still be supported as a useful tool in planktonic research. Here I review the construction of NPZ models, and some of the physical platforms they have been coupled to. I then discuss the applications of NPZ-physical models, and conclude that they still constitute an important and viable research tool, provided that the questions being explored are clearly stated.

Chaotic advection of reacting substances: Plankton dynamics on a meandering jet

We study the spatial patterns formed by interacting populations or reacting chemicals under the influence of chaotic flows. In particular, we have considered a three-component model of plankton dynamics advected by a meandering jet. We report general results, stressing the existence of a smooth-filamental transition in the concentration patterns depending on the relative strength of the stirring by the chaotic flow and the relaxation properties of planktonic dynamical system. Patterns obtained in open and closed flows are compared.

Spatio-temporal pattern formation in coupled models of plankton dynamics and fish school motion

Spatio-temporal pattern formation in coupled models of plankton dynamics and fish school motion

A model of plankton dynamics for the coastal upwelling system of Monterey Bay, California

A seven-box plankton model for the mixed layer of the open ocean (Fasham et al., 1990, Journal of Marine Research 48, 591–639) was modified and applied to the coastal upwelling ecosystem of Monterey Bay, California. Upwelling velocities, photosynthetically active radiation and changes in mixed-layer depth drove the model. The observed long-term mean (1989–1995) seasonal cycles of nitrate concentration, primary production and phytoplankton concentration within the mixed layer were reproduced. Bacteria and zooplankton biomass, and ammonium concentration were within the same order of magnitude as observations. Modeled dissolved organic nitrogen (labile) values were an order of magnitude lower than observations (total). New production estimates were high, leading to an annual f-ratio of 0.84, typical of productive coastal upwelling systems. Export production was much lower, and horizontal export by upwelling-induced advection was the dominant loss term for phytoplankton primary production. It exceeded sinking and grazing and the flux of zooplankton-derived detritus throughout most of the year. The model suggests that a large proportion of the daily phytoplankton growth is ungrazed in the mixed layer, and is advected downstream and offshore of the production site.

Incorporating the microbial loop in a simple plankton model

Restricted accessMoreSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InRedditEmail Cite this article Steele John H. 1998Incorporating the microbial loop in a simple plankton modelProc. R. Soc. Lond. B.2651771–1777http://doi.org/10.1098/rspb.1998.0501SectionRestricted accessIncorporating the microbial loop in a simple plankton model John H. Steele John H. Steele Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA Google Scholar Find this author on PubMed Search for more papers by this author John H. Steele John H. Steele Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA Google Scholar Find this author on PubMed Search for more papers by this author Published:22 September 1998https://doi.org/10.1098/rspb.1998.0501AbstractThe microbial loop, which recycles nutrients in the upper layers of the ocean, is an integral part of plankton dynamics. The usual method for modelling the complex patterns involved has been to consider the ‘Z’ in N/P/Z (nutrient/phytoplankton/zooplankton) models as containing all possible grazers on P and, implicitly, relegate the carnivorous metazoans to the loss term on Z. I propose the opposite approach—to define Z explicitly as the metazoans responsible for export fluxes—and to simulate the effects of the microbial loop implicitly in terms of grazing and excretion rates. The reasons for taking this alternative route are (i) the importance of copepods in the carbon/nitrogen flux from the euphotic zone to deeper water compared with (ii) the predominantly internal role of the microzooplankton in recycling nutrients; and (iii) the problems of sampling the microbial component, compared with sampling larger metazoans. Finally, there is the need to keep plankton models as simple as possible for later use in coupled physical—biological systems. Previous ArticleNext Article VIEW FULL TEXT DOWNLOAD PDF FiguresRelatedReferencesDetailsCited by Müller-Karulis B and Aigars J (2011) Modeling the long-term dynamics of nutrients and phytoplankton in the Gulf of Riga, Journal of Marine Systems, 10.1016/j.jmarsys.2011.03.006, 87:3-4, (161-176), Online publication date: 1-Sep-2011. Banas N, Lessard E, Kudela R, MacCready P, Peterson T, Hickey B and Frame E (2009) Planktonic growth and grazing in the Columbia River plume region: A biophysical model study, Journal of Geophysical Research, 10.1029/2008JC004993, 114 Wallhead P, Martin A, Srokosz M and Franks P (2009) Skill assessment via cross-validation and Monte Carlo simulation: An application to Georges Bank plankton models, Journal of Marine Systems, 10.1016/j.jmarsys.2008.03.010, 76:1-2, (134-150), Online publication date: 1-Feb-2009. Hood R and Christian J (2008) Ocean Nitrogen Cycle Modeling Nitrogen in the Marine Environment, 10.1016/B978-0-12-372522-6.00033-5, (1445-1495), . Miller C (2008) Copepod growth in detail: pattern similarity to decapod larvae, ICES Journal of Marine Science, 10.1093/icesjms/fsm180, 65:3, (332-338), Online publication date: 1-Apr-2008. Pahlow M, Vézina A, Casault B, Maass H, Malloch L, Wright D and Lu Y (2008) Adaptive model of plankton dynamics for the North Atlantic, Progress in Oceanography, 10.1016/j.pocean.2007.11.001, 76:2, (151-191), Online publication date: 1-Feb-2008. Hood R, Laws E, Armstrong R, Bates N, Brown C, Carlson C, Chai F, Doney S, Falkowski P, Feely R, Friedrichs M, Landry M, Keith Moore J, Nelson D, Richardson T, Salihoglu B, Schartau M, Toole D and Wiggert J (2006) Pelagic functional group modeling: Progress, challenges and prospects, Deep Sea Research Part II: Topical Studies in Oceanography, 10.1016/j.dsr2.2006.01.025, 53:5-7, (459-512), Online publication date: 1-Mar-2006. Barber R and Hiscock M (2006) A rising tide lifts all phytoplankton: Growth response of other phytoplankton taxa in diatom-dominated blooms, Global Biogeochemical Cycles, 10.1029/2006GB002726, 20:4, (n/a-n/a), Online publication date: 1-Dec-2006. Denman K (2003) Modelling planktonic ecosystems: parameterizing complexity, Progress in Oceanography, 10.1016/S0079-6611(03)00109-5, 57:3-4, (429-452), Online publication date: 1-Jun-2003. Crispi G, Crise A and Solidoro C (2002) Coupled Mediterranean ecomodel of the phosphorus and nitrogen cycles, Journal of Marine Systems, 10.1016/S0924-7963(02)00073-8, 33-34, (497-521), Online publication date: 1-Jun-2002. Lampe V, Nöthig E and Schartau M (2021) Spatio-Temporal Variations in Community Size Structure of Arctic Protist Plankton in the Fram Strait, Frontiers in Marine Science, 10.3389/fmars.2020.579880, 7 This Issue22 September 1998Volume 265Issue 1407 Article InformationDOI:https://doi.org/10.1098/rspb.1998.0501Published by:Royal SocietyPrint ISSN:0962-8452Online ISSN:1471-2954History: Published online22/09/1998Published in print22/09/1998 License: Citations and impact Keywordsmodelplanktonmicrobial loop Large datasets are available through Proceedings B's partnership with Dryad

A model of the yearly cycle of nutrients and plankton in the Baltic Sea

Abstract A model of plankton dynamics in parts of the Baltic Sea is constructed which is as simple as possible but able to simulate the yearly cycle of nutrients and plankton in a horizontally averaged two layer system. State variables are limiting nutrients, phytoplankton, Zooplankton and detritus expressed by concentrations relative to a certain density of limiting nutrients. The physical control is reduced to the formation and destruction of a thermocline in spring and fall. The dynamical ingredients are nutrient limited growth, grazing, loss and recycling. Owing to problems of observational undersampling of marine ecosystems and to the integrated nature of the presented model, no attempt has been made to calibrate the model against data of a single field campaign. The model parameters are adjusted in such a manner that timing of the spring bloom and of the Zooplankton response as well as the relative magnitude of the peak values and the summer concentrations are consistent with the accumulated knowledge from many observations in the Arkona and the Bornholm basin of the Baltic Sea. Nutrient limited growth and food limited grazing are accounted for by quadratic modified versions of the Michaelis-Menten and the Ivlev approach. These expressions reduce consumption for low concentrations and do not require threshold assumptions. The presented model is stable and robust for a relatively wide range of parameter values. The effects of eutrophication can be described in a reasonable manner. The model is developed as a first step towards a coupled model of circulation and plankton dynamics in the Baltic Sea.

Effects of interaction between two warm-core rings on phytoplankton distribution

A modeling study was conducted to investigate the effects of interaction between two warm-core rings on the phytoplankton distribution. Using a quasi-geostrophic reduced-gravity model, the interaction between two vortices was calculated to reproduce the partial vortex merger between two warm-core rings, 86B and OR. On the calculated flow field, the three-dimensional model of plankton dynamics generated high phytoplankton biomass at the edge of the merged vortex. In the model, phytoplankton grew due to nutrient transport into the euphotic zone by upward motion of water caused by meanders of the current followed by the partial vortex merger. Further, the model reproduced the horizontal distribution of phytoplankton observed in 86B.

Nonequilibrium plankton community structures in an ecohydrodynamic model system

Abstract. Due to the local and global impacts of algae blooms and patchiness on water quality, carbon cycling and climate, models of plankton dynamics are of current interest. In this paper, the temporal and spatial patterns in natural plankton communities are interpreted as transient and stationary nonequilibrium solutions of dynamical nonlinear interaction-diffusion-advection systems. A simple model of phytoplankton-zooplankton dynamics (Scheffer, 1991) is presented in space and time. After summarizing the local properties as multiple stability and oscillations, the emergence of spatial and spatio- temporal patterns is considered, accounting also for diffusion and weak advection. In order to study the emergence and stability of these structures under hydrodynamic forcing, the interaction- diffusion-advection model is coupled to the hydrodynamic equations. It is shown, that the formation of nonequilibrium spatio-temporal density patterns due to the interplay of the deterministic nonlinear biological interactions and physical processes is a rare occurrence in rapidly flowing waters. The two-timing perturbation technique is applied to problems with very rapid single-directed steady flows. A channel under tidal forcing serves as and example for a system with a relatively high detention time of matter. Generally, due to the different time and length scales of planktic interactions, diffusion and transport, initial nonequilibrium plankton patches are simply moved through the system unless the strong hydrodynamic forces do not destroy them before.

Annual cycles of phytoplankton chlorophyll concentrations in the global ocean: A satellite view

Conceptual and mathematical models show that annual cycles of phytoplankton biomass are different within different regions of the ocean. The purpose of this manuscript is to use coastal zone color scanner chlorophyll imagery (CZCS‐Ch1) to determine annual cycles in phytoplankton chlorophyll (biomass) averaged over very large areas of the global ocean. A possible result is that large‐scale averaging of CZCS‐Ch1 will yield no interpretable signals because of spatial variability in annual cycles at scales much smaller than our averaging scale. Alternatively, if our analyses show regular and persistent global patterns, then our results will jprovide a basin‐scale overview of phytoplankton biomass seasonally for comparison with model results or with other large‐scale oceanographic measurements. Our results show that monthly mean CZCS‐Ch1 imagery (and using in situ concentrations for winter at latitudes poleward of 40 deg) resolves important differences in annual phytoplankton chlorophyll cycles for different ocean basins and latitude belts. As predicted by simple models of plankton dynamics, our results show: (1) global subtropical waters have circa 2X higher CZCS‐Ch1 concentrations in winter than in summer and (2) subpolar waters in the northern hemisphere (NH) have mean monthly CZCS‐Ch1 concentrations during May and June that are manyfold higher than in winter, particularly in the North Atlantic. Our results also show: (1) Northern Indian Ocean is the major subtropical anomaly, (2) subpolar waters in the SH do not show differences between spring maxima and winter minima as large as those in the subpolar NH and (3) larger ocean area in the SH is compensated by higher mean annual CZCS‐Ch1 concentrations in the NH, so that annual hemispherical integrals (mean annual concentrations multiplied by ocean areas) are very similar. The simple patterns we report imply that mean annual cycles in phytoplankton biomass averaged over very large areas of the global ocean are largely explainable by very simple mathematical models such as those presented several decades ago by Cushing, Riley, Steele, and others.