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.