Impact of climate warming on phenological asynchrony of plankton dynamics across Europe.

Climate warming alters the seasonal timing of biological events. This raises concerns that species-specific responses to warming may de-synchronize co-evolved consumer-resource phenologies, resulting in trophic mismatch and altered ecosystem dynamics. We explored the effects of warming on the synchrony of two events: the onset of the phytoplankton spring bloom and the spring/summer maximum of the grazer Daphnia. Simulation of 16 lake types over 31 years at 1907 North African and European locations under 5 climate scenarios revealed that the current median phenological delay between the two events varies greatly (20-190 days) across lake types and geographic locations. Warming moves both events forward in time and can lengthen or shorten the delay between them by up to ±60 days. Our simulations suggest large geographic and lake-specific variations in phenological synchrony, provide quantitative predictions of its dependence on physical lake properties and geographic location and highlight research needs concerning its ecological consequences.

Local and continental-scale controls of the onset of spring phytoplankton blooms: Conclusions from a proxy-based model.

A key phenological event in the annual cycle of many pelagic ecosystems is the onset of the spring algal bloom (OAB). Descriptions of the factors controlling the OAB in temperate to polar lakes have been limited to isolated studies of single systems and conceptual models. Here we present a validated modelling approach that, for the first time, enables a quantitative prediction of the OAB and a systematic assessment of the processes controlling its timing on a continental scale. We used a weather-driven, one-dimensional lake model to simulate the seasonal dynamics of the underwater light climate in 16 lake types characterized by the factorial combination of four lake depths with four levels of water transparency. We did so at 1962 locations across Western Europe and over 31 years (1979-2009). Assuming that phytoplankton production is light-limited in winter, we identified four patterns of OAB control across lake types and climate zones. OAB timing is controlled by (i) the timing of ice-off in ice-covered clear or shallow lakes, (ii) the onset of thermal stratification in sufficiently deep and turbid lakes and (iii) the seasonal increase in incident radiation in all other lakes, except for (iv) ice-free, shallow and clear lakes in the south, where phytoplankton is not light-limited. The model predicts that OAB timing should respond to two pervasive environmental changes, global warming and browning, in opposite ways. OAB timing should be highly sensitive to warming in lakes where it is controlled by either ice-off or the onset of stratification, but resilient to warming in lakes where it is controlled by incident radiation. Conversely, OAB timing should be most sensitive to browning where it is controlled by incident radiation, but resilient to browning where it is controlled by ice-off or the onset of stratification. Available lake data are consistent with our findings.

Boom-bust dynamics in biological invasions: towards an improved application of the concept.

Boom-bust dynamics - the rise of a population to outbreak levels, followed by a dramatic decline - have been associated with biological invasions and offered as a reason not to manage troublesome invaders. However, boom-bust dynamics rarely have been critically defined, analyzed, or interpreted. Here, we define boom-bust dynamics and provide specific suggestions for improving the application of the boom-bust concept. Boom-bust dynamics can arise from many causes, some closely associated with invasions, but others occurring across a wide range of ecological settings, especially when environmental conditions are changing rapidly. As a result, it is difficult to infer cause or predict future trajectories merely by observing the dynamic. We use tests with simulated data to show that a common metric for detecting and describing boom-bust dynamics, decline from an observed peak to a subsequent trough, tends to severely overestimate the frequency and severity of busts, and should be used cautiously if at all. We review and test other metrics that are better suited to describe boom-bust dynamics. Understanding the frequency and importance of boom-bust dynamics requires empirical studies of large, representative, long-term data sets that use clear definitions of boom-bust, appropriate analytical methods, and careful interpretations.

Chaos in a long-term experiment with a plankton community.

Mathematical models predict that species interactions such as competition and predation can generate chaos. However, experimental demonstrations of chaos in ecology are scarce, and have been limited to simple laboratory systems with a short duration and artificial species combinations. Here, we present the first experimental demonstration of chaos in a long-term experiment with a complex food web. Our food web was isolated from the Baltic Sea, and consisted of bacteria, several phytoplankton species, herbivorous and predatory zooplankton species, and detritivores. The food web was cultured in a laboratory mesocosm, and sampled twice a week for more than 2,300 days. Despite constant external conditions, the species abundances showed striking fluctuations over several orders of magnitude. These fluctuations displayed a variety of different periodicities, which could be attributed to different species interactions in the food web. The population dynamics were characterized by positive Lyapunov exponents of similar magnitude for each species. Predictability was limited to a time horizon of 15-30 days, only slightly longer than the local weather forecast. Hence, our results demonstrate that species interactions in food webs can generate chaos. This implies that stability is not required for the persistence of complex food webs, and that the long-term prediction of species abundances can be fundamentally impossible.

Coupled predator-prey oscillations in a chaotic food web.

Coupling of several predator-prey oscillations can generate intriguing patterns of synchronization and chaos. Theory predicts that prey species will fluctuate in phase if predator-prey cycles are coupled through generalist predators, whereas they will fluctuate in anti-phase if predator-prey cycles are coupled through competition between prey species. Here, we investigate predator-prey oscillations in a long-term experiment with a marine plankton community. Wavelet analysis of the species fluctuations reveals two predator-prey cycles that fluctuate largely in anti-phase. The phase angles point at strong competition between the phytoplankton species, but relatively little prey overlap among the zooplankton species. This food web architecture is consistent with the size structure of the plankton community, and generates highly dynamic food webs. Continued alternations in species dominance enable coexistence of the prey species through a non-equilibrium 'killing-the-winner' mechanism, as the system shifts back and forth between the two predator-prey cycles in a chaotic fashion.

Water management strategies against toxic Microcystis blooms in the Dutch delta.

To prevent flooding of the Dutch delta, former estuaries have been impounded by the building of dams and sluices. Some of these water bodies, however, experience major ecological problems. One of the problem areas is the former Volkerak estuary that was turned into a freshwater lake in 1987. From the early 1990s onward, toxic Microcystis blooms dominate the phytoplankton of the lake every summer. Two management strategies have been suggested to suppress these harmful algal blooms: flushing the lake with fresh water or reintroducing saline water into the lake. This study aims at an advance assessment of these strategies through the development of a mechanistic model of the population dynamics of Microcystis. To calibrate the model, we monitored the benthic and pelagic Microcystis populations in the lake during two years. Field samples of Microcystis were incubated in the laboratory to estimate growth and mortality rates as functions of light, temperature, and salinity. Recruitment and sedimentation rates were measured in the lake, using traps, to quantify benthic-pelagic coupling of the Microcystis populations. The model predicts that flushing with fresh water will suppress Microcystis blooms when the current flushing rate is sufficiently increased. Furthermore, the inlet of saline water will suppress Microcystis blooms for salinities exceeding 14 g/L. Both management options are technically feasible. Our study illustrates that quantitative ecological knowledge can be a helpful tool guiding large-scale water management.