Introduction
Some of the earliest and most consistent observations of ecological responses to climate warming come from shifts in the timing of seasonal events (Parmesan & Yohe 2003; Thackeray et al. 2010). This has raised concerns that asynchronous responses to a changing climate could disrupt co-evolved consumer-resource phenologies, resulting in phenological mismatch (Stenseth & Mysterud 2002). Phenological mismatch occurs when the seasonal peak in consumer demand for a resource does not coincide with the seasonal peak in the availability of that resource (Visser & Gienapp 2019; Samplonius et al. 2021). While several studies have identified cases where climate change has led to phenological asynchrony with negative consequences for consumers, recent literature surveys concluded that the available evidence is weak and insufficient to draw general conclusions about the future prevalence of climate-mediated phenological asynchrony (Thackeray 2012; Kharouba & Wolkovich 2020; Samplonius et al. 2021).
A major reason for this lack of robust evidence is that most studies to date cannot answer one or more of the following questions (Kharouba & Wolkovich 2020). 1 - What is the reference state of phenological synchrony prior to climate change, and how variable is the degree of phenological synchrony in time and space under reference conditions? 2 - What are the climatic drivers of the phenology of different species, and do interacting species respond to the same drivers? 3 - How does climate change affect these drivers, and do interacting species respond equally strongly to these changes? Here, we address these questions in a study of phenological synchrony of an aquatic producer-grazer interaction that is central to pelagic ecosystem dynamics in most temperate to arctic freshwater lakes.
A conspicuous seasonal event in many lakes is the spring phytoplankton bloom. Its onset is usually triggered by the alleviation of light limitation, while its termination is often caused by grazing by zooplankton of the genus Daphnia (Sommer et al. 2012). The end of the spring bloom, the so-called clear water phase, therefore often closely coincides with the spring/summer maximum in Daphniaabundance (Straile & Adrian 2000; Berger et al. 2007). The onset of the spring phytoplankton bloom and the timing of the Daphnia maximum are not phenological life history events (such as the timing of flowering or breeding in longer-lived organisms) but numerical responses to changes in temperature, resource availability, and predation pressure (Thackeray 2012). The period between the two events thus correlates with both the overall duration of the spring bloom (an ecosystem characteristic) and the spring growth period of Daphnia (a characteristic of predator-prey dynamics). Warming-induced advances in the timing of the phytoplankton bloom have been suggested to result in phenological asynchrony and thus in a reduction of Daphniapopulation size (Winder & Schindler 2004; George 2012). Yet, other studies did not find a general relationship between warming and phenological asynchrony (Berger et al. 2014; Straile et al. 2015), and more research is needed to reconcile these contrasting findings.
Both the onset of the algal bloom and the timing of the Daphniamaximum correlate closely with physical events. The onset of the algal bloom (OAB) depends primarily on light and typically takes place once underwater light availability exceeds a specific threshold (Siegel et al. 2002; Diehl et al. 2015). In contrast, spring population growth ofDaphnia is most strongly influenced by temperature, and the timing of the Daphnia maximum (TDM) coincides closely with the seasonal exceedance of thresholds in near-surface water temperature that are similar across entire hemispheres (Gillooly & Dodson 2000; Straile et al. 2012). The tightness of these empirical relationships makes it possible to infer the phenology of OAB and TDM from physical conditions which, in turn, are amenable to process-based hydrodynamic modelling (Straile et al. 2015; Gronchi et al. 2021). We exploited this opportunity and used a numerical modelling to explore the phenologies of phytoplankton and Daphnia , as well as their synchrony, over a vast range of climatic conditions and physical lake properties.
Specifically, we simulated the physical drivers of OAB and TDM in 16 model lake types at the spatial scale of Western Europe and North Africa over three decades of the driving meteorology and two climatic conditions: the ambient climate and a constant warming scenario of + 4°C. We used the resulting 1,891,744 lake year simulations to address the three questions raised in (Kharouba & Wolkovich 2020) in the following specific ways. 1 - What are the phenological patterns of OAB and TDM across Europe under current climatic conditions? 2 - Which climatic and lake-specific factors determine the delay in the timings between the two events and, thus, their phenological asynchrony? 3 - How is warming expected to alter the magnitude of this phenological asynchrony in different lake types and at different geographic locations? To identify general, continental-scale and lake type-specific patterns of phenologies and their responses to warming, we focus, throughout the manuscript, on the median values of the predicted time series of OAB, TDM, and of the delay between these two phenological events. We compare these medians between lake types, locations and climate scenarios.