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Despite the recognition of the importance of seasonal forcing in nature, remarkably few studies have theoretically explored periodically forced community dynamics. Here we employ a novel approach called 'successional state dynamics' (SSD) to model a seasonally forced predator--prey system. We first generated analytical predictions of the effects of altered seasonality on species persistence and the timing of community state transitions. We then parameterized the model using a zooplankton-phytoplankton system and tested quantitative predictions using controlled experiments. In the majority of cases, timing of zooplankton and algal population peaks matched model predictions. Decreases in growing-period length delayed algal blooms, consequently delaying peaks in zooplankton abundance. Predictions of increased probability of predator extinction at low growing-period lengths were also upheld experimentally. Our results highlight the utility of the SSD modeling approach as a framework for predicting the effects of altered seasonality on the structure and dynamics of multitrophic communities. Key words: Brachionus calyciflorus; Chlamydomonas reinhardtii; environmental forcing; periodic mortality; phytoplankton; predator-prey dynamics; seasonal succession; seasonality, transient dynamics; zooplank ton.

Phytoplankton growth and stoichiometry depend on the availability of multiple nutrients. We use a mathematical model of phytoplankton with flexible stoichiometry to explain patterns of phytoplankton composition in chemostat experiments and nutrient drawdown dynamics that are found in the field. Exponential growth and equilibrium represent two distinct phases, each amenable to mathematical analysis. In a chemostat at a fixed dilution (growth) rate, phytoplankton stoichiometry matches the nutrient supply stoichiometry over a wide range at low growth rates and over a narrow range at high growth rates. In a chemostat with a fixed nutrient supply stoichiometry, phytoplankton stoichiometry varies with dilution rate nonlinearly, between the supply stoichiometry at low dilution rates and a species-specific optimal ratio at high dilution rates. The flexible-stoichiometry model we study predicts low equilibrium concentrations of two nutrients over a wide range of supply ratios, contrary to the predictions of a traditional fixed-stoichiometry model. The model is in quantitative agreement with experimental data, except at extreme nutrient supply ratios, which require a negative feedback from quota to uptake to fit the data. Our analysis points to the importance of better understanding the regulation of uptake rates in determining phytoplankton stoichiometry and incorporating this knowledge into phytoplankton models.

Many physiological processes in phytoplankton, including nutrient uptake, vary on a number of temporal scales. Experiments show that the daily cycle in irradiance affects nutrient uptake rates. We used a Droop-based model of resource competition to investigate how diel variability in nutrient uptake influences phytoplankton competition and community structure. The analytical approximation we derive shows that if nutrient uptake is light dependent, the minimum nutrient requirements and, hence, nutrient competitive abilities depend on light regime in a species-specific way. Consequently, daily variations in irradiance may slow rates of competitive exclusion or reverse the identity of the superior competitor but not allow stable coexistence. Irradiance-induced fluctuations in the maximum nutrient uptake rate of the superior competitor can lead to fluctuations in ambient nutrient concentration and an increase in the average nutrient concentration compared to constant light conditions. This can enhance nutrient use by inferior competitors. These results may be applicable to bacteria-phytoplankton nutrient competition as well. Depending on the costs and benefits of maintaining nutrient uptake in the dark, different strategies of nutrient use are optimal under different light regimes. Our results suggest that by mediating limiting nutrient use, fluctuations in irradiance may alter the structure of phytoplankton communities.

Author(s): Christopher A. Klausmeier (corresponding author) [1, 2]; Elena Litchman [2, 3]; Tanguy Daufresne [1]; Simon A. Levin [1] Redfield noted the similarity between the average nitrogen-to-phosphorus ratio in plankton [...]

Phytoplankton often face the dilemma of living in contrasting gradients of two essential resources: light that is supplied from above and nutrients that are often supplied from below. In poorly mixed water columns, algae can be heterogeneously distributed, with thin layers of biomass found on the surface, at depth, or on the sediment surface. Here, we show that these patterns can result from intraspecific competition for light and nutrients. First, we present numerical solutions of a reaction-diffusion-taxis model of phytoplankton, nutrients, and light. We argue that motile phytoplankton can form a thin layer under poorly mixed conditions. We then analyze a related game theoretical model that treats the depth of a thin layer of phytoplankton as the strategy. The evolutionarily stable strategy is the depth at which the phytoplankton are equally limited by both resources, as long as the layer is restricted to the water column. The layer becomes shallower with an increase in the nutrient supply and deeper with an increase in the light supply. For low nutrient levels, low background attenuation, and shallow water columns, a benthic layer occurs; for intermediate nutrient levels in deep water columns, a deep chlorophyll maximum occurs; and for high nutrient levels, a surface scum occurs. These general patterns are in agreement with field observations. Thus, this model can explain many patterns of algal distribution found in poorly mixed aquatic ecosystems.

A model of competition among sessile organisms was modified to account for spatial distribution of sites on the landscape. By re-evaluating the assumption on colonization rates of succeeding species in the hierarchy of competition, the best competitors were found to be the first ones to become extinct because of habitat destruction. During habitat destruction, certain species become extinct and settle in the community after severe habitat destruction that causes extinction among competitive species.

The development of ecological stoichiometry has centered on organisms and their interactions, with less emphasis on the meaning or value of a comprehensive ecosystem stoichiometry at larger scales. A conceptual framework that relates internal processes and exogenous factors in spatially and temporally linked ecosystems is developed.

Pattern formation has long interested both theoretical biologists (1, 2) and plant ecologists (3, 4). Theoretical studies have shown that local interactions coupled by dispersal can cause nonuniform distributions of [...], Vegetation in many semiarid regions is strikingly patterned, forming regular stripes on hillsides and irregular mosaics on flat ground. A simple model of plant and water dynamics based on ecologically realistic assumptions and with reasonable parameter values captures both of these types of patterns. The regular patterns result from a Turing-like instability; the irregular patterns arise when the ecological dynamics amplify slight small-scale topographic variability. Because of the close agreement between observations and these theoretical results, this system provides a clear example of how nonlinear mechanisms can be important in determining the spatial structure of plant communities.