Internally driven alternation of functional traits in a multispecies predator-prey system.

The individual functional traits of different species play a key role for ecosystem function in aquatic and terrestrial systems. We modeled a multispecies predator-prey system with functionally different predator and prey species based on observations of the community dynamics of ciliates and their algal prey in Lake Constance. The model accounted for differences in predator feeding preferences and prey susceptibility to predation, and for the respective trade-offs. A low food demand of the predator was connected to a high food selectivity, and a high growth rate of the prey was connected to a high vulnerability to grazing. The data and the model did not show standard uniform predator-prey cycles, but revealed both complex dynamics and a coexistence of predator and prey at high biomass levels. These dynamics resulted from internally driven alternations in species densities and involved compensatory dynamics between functionally different species. Functional diversity allowed for ongoing adaptation of the predator and prey communities to changing environmental conditions such as food composition and grazing pressure. The trade-offs determined whether compensatory or synchronous dynamics occurred which influence the variability at the community level. Compensatory dynamics were promoted by a joint carrying capacity linking the different prey species which is particularly relevant at high prey biomasses, i.e., when grazers are less efficient. In contrast, synchronization was enhanced by the coupling of the different predator and prey species via common feeding links, e.g., by a high grazing pressure of a nonselective predator. The communities had to be functionally diverse in terms of their trade-offs and their traits to yield compensatory dynamics. Rather similar predator species tended to cycle synchronously, whereas profoundly different species did not coexist. Compensatory dynamics at the community level thus required intermediately strong tradeoffs for functional traits in both predators and their prey.

Predator-prey dynamics driven by feedback between functionally diverse trophic levels.

Neglecting the naturally existing functional diversity of communities and the resulting potential to respond to altered conditions may strongly reduce the realism and predictive power of ecological models. We therefore propose and study a predator-prey model that describes mutual feedback via species shifts in both predator and prey, using a dynamic trait approach. Species compositions of the two trophic levels were described by mean functional traits--prey edibility and predator food-selectivity--and functional diversities by the variances. Altered edibility triggered shifts in food-selectivity so that consumers continuously respond to the present prey composition, and vice versa. This trait-mediated feedback mechanism resulted in a complex dynamic behavior with ongoing oscillations in the mean trait values, reflecting continuous reorganization of the trophic levels. The feedback was only possible if sufficient functional diversity was present in both trophic levels. Functional diversity was internally maintained on the prey level as no niche existed in our system, which was ideal under any composition of the predator level due to the trade-offs between edibility, growth and carrying capacity. The predators were only subject to one trade-off between food-selectivity and grazing ability and in the absence of immigration, one predator type became abundant, i.e., functional diversity declined to zero. In the lack of functional diversity the system showed the same dynamics as conventional models of predator-prey interactions ignoring the potential for shifts in species composition. This way, our study identified the crucial role of trade-offs and their shape in physiological and ecological traits for preserving diversity.

A minimal mathematical model of nonphotochemical quenching of chlorophyll fluorescence.

Under natural conditions, plants are exposed to rapidly changing light intensities. To acclimate to such fluctuations, plants have evolved adaptive mechanisms that optimally exploit available light energy and simultaneously minimise damage of the photosynthetic apparatus through excess light. An important mechanism is the dissipation of excess excitation energy as heat which can be measured as nonphotochemical quenching of chlorophyll fluorescence (NPQ). In this paper, we present a highly simplified mathematical model that captures essential experimentally observed features of the short term adaptive quenching dynamics. We investigate the stationary and dynamic behaviour of the model and systematically analyse the dependence of characteristic system properties on key parameters such as rate constants and pool sizes. Comparing simulations with experimental data allows to derive conclusions about the validity of the simplifying assumptions and we further propose hypotheses regarding the role of the xanthophyll cycle in NPQ. We envisage that the presented theoretical description of the light reactions in conjunction with short term adaptive processes serves as a basis for the development of more detailed mechanistic models by which the molecular mechanisms of NPQ can be theoretically studied.

The effect of irradiance, vertical mixing and temperature on spring phytoplankton dynamics under climate change: long-term observations and model analysis.

Spring algal development in deep temperate lakes is thought to be strongly influenced by surface irradiance, vertical mixing and temperature, all of which are expected to be altered by climate change. Based on long-term data from Lake Constance, we investigated the individual and combined effects of these variables on algal dynamics using descriptive statistics, multiple regression models and a process-oriented dynamic simulation model. The latter considered edible and less-edible algae and was forced by observed or anticipated irradiance, temperature and vertical mixing intensity. Unexpectedly, irradiance often dominated algal net growth rather than vertical mixing for the following reason: algal dynamics depended on algal net losses from the euphotic layer to larger depth due to vertical mixing. These losses strongly depended on the vertical algal gradient which, in turn, was determined by the mixing intensity during the previous days, thereby introducing a memory effect. This observation implied that during intense mixing that had already reduced the vertical algal gradient, net losses due to mixing were small. Consequently, even in deep Lake Constance, the reduction in primary production due to low light was often more influential than the net losses due to mixing. In the regression model, the dynamics of small, fast-growing algae was best explained by vertical mixing intensity and global irradiance, whereas those of larger algae were best explained by their biomass 1 week earlier. The simulation model additionally revealed that even in late winter grazing may represent an important loss factor during calm periods when losses due to mixing are small. The importance of losses by mixing and grazing changed rapidly as it depended on the variable mixing intensity. Higher temperature, lower global irradiance and enhanced mixing generated lower algal biomass and primary production in the dynamic simulation model. This suggests that potential consequences of climate change may partly counteract each other.