Introduction
As a first approximation, ecologists often relate performance of plants
or animals to environmental conditions in that time and place.
Nonetheless, many ecological studies have highlighted the importance of
past environmental conditions for current performance of individuals and
populations. Such carry-over effects, which range from inter-life stage
to inter-generational impacts, are well documented in life history
literature (Pechenik 2006; Harrison et al. 2011; O’Connoret al. 2014; Liz & Ruiz-Herrera 2016). For example, the
nutritional environment experienced in juvenile stages of development in
animals can influence development times (Pechenik 2006) and aspects of
adult fitness including body size (e.g. Pereboom et al. 2003) and
fecundity (e.g. Lindström 1999). In such cases, changes in individual
quality (vital rates) can have lasting demographic consequences.
Carry-over effects can be an important component of long-term population
cycles (Beckerman et al. 2002), as well as responses to
environmental stochasticity (Sabo & Post 2008) and recovery from
extreme resource pulses or dearth (Gratton & Denno 2003; Yang et
al. 2008).
Effects of past conditions on future population dynamics have been
particularly well studied in stage-structured populations (Ezardet al. 2010; Stott et al. 2011). In many populations,
vital rates (such as individual growth, survival, and reproduction)
depend on the size of individual plants or animals. If these rates are
constant through time, the population reaches a stable size
distribution, and grows (or declines) at a constant rate associated with
that size distribution. In fluctuating environments, the population
growth rate in a particular year depends approximately equally on the
vital rates individuals experience in that year, and the size
distribution of individuals at the beginning of that year (Ellis &
Crone 2013; McDonald et al. 2016). In response to extreme changes
in the environment, changes in size distribution can create persistent
differences in abundance and transient multi-year changes in population
growth rates, even after vital rates have returned to average levels
(Gamelon et al. 2014). For example, a resource pulse might enable
many individuals to grow faster during that pulse, leading to more large
individuals and higher population growth rates for many years after the
pulse is over. The increase in growth rate occurs simply because the
population (after the pulse) started with more large individuals.
Similarly, a resource dearth might reduce individual size, leading to a
lack of large individuals and slower population growth rates after
resources return. In structured population projection models,
“transient dynamics” refer to the period between when a population’s
size distribution is perturbed, and when it returns to the size
distribution determined by the current environmental conditions. During
the past two decades, a large body of literature has focused on how to
quantify transient dynamics using simulation models (starting with
Neubert & Caswell 1997; see reviews by (Ezard et al. 2010; Stottet al. 2011). However, few studies have tested these predictions
with experiments (see Tenhumberg et al. 2009 for a notable
exception).
We use bumble bees (Bombus vosnesnesnkii ) as a model system for
understanding how current and historical environmental conditions affect
population dynamics. Within-colony dynamics of bumble bees are useful
for exploring population dynamics for several reasons. Bumble bees are
annual eusocial insects with colonies that grow via the production of
successive overlapping cohorts (generations) of worker bees. Colonies
typically grow exponentially, often producing ~ 5-10 (or
more) worker cohorts during its development. After this growth phase,
the colony stops making new workers and switches to reproduction (i.e.
production of males and new queens, (Duchateau & Velthuis 1988; Müller
& Schmid‐Hempel 1992; Goulson 2010; Crone & Williams 2016). Colonies
persist for several months; however, individual foragers live 1-4 weeks
(Rodd et al. 1980; Goldblatt & Fell 2011; Malfi et al.2019) during which time they provide the resources to rear subsequent
cohorts of workers (Alford 1975; Goulson 2010). Therefore, a single
bumble bee colony can be considered as an exponentially growing
population of workers, with the advantage that multi-cohort dynamics can
be studied in nature in a single growing season.
Bumble bee colonies are also a tractable system for studying
environmental drivers of population dynamics because it is
straightforward to manipulate a known environmental driver of colony and
population size: forage. Growth of bumble bee colonies is at least
partly food-limited (Pelletier & McNeil 2003). Larvae require pollen
and nectar to develop into adults, and adult size is affected by the
amount of food they receive as larvae (Couvillon & Dornhaus 2009; Malfiet al. 2019). Adults require nectar to fuel various colony
functions, including foraging itself. Colonies have a limited capacity
to store food resources (Goulson 2010); as a result, the spatiotemporal
availability of flowering plants strongly regulates colony growth and
the size of the intra-season worker population (Westphal et al.2009; Rundlöf et al. 2014; Crone & Williams 2016; Kämperet al. 2016; Spiesman et al. 2017; Rundlöf & Lundin
2019). Therefore, it seems likely that short-term changes in forage
resources would affect worker size distribution, leading to transient
effects on population growth rate. Other carry-over effects (e.g.,
persistent effects on size-based survival or foraging ability of
workers) are also possible (Malfi et al. 2019). In addition its
feasibility as a model system, understanding the effects of forage
resources on bumble bee colony growth and long-term population dynamics
is of immediate practical importance. Bumble bees are important
pollinators in natural and crop systems (Corbet et al. 1991;
Thomson & Goodell 2001; Kremen et al. 2002; Kleijn et al.2015), multiple bumble bee species are in decline (Bommarco et
al. 2012; Colla et al. 2012; Kerr et al. 2015; Woodet al. 2019), and millions of dollars are invested annually in
planting forage resources to support bumble bees and other bee
populations (USDA Farm Services Agency 2019). Revealing the mechanistic
connections between bumble bee colony and population dynamics and their
resource environment is important for conservation efforts (Roulston &
Goodell 2011).
In this study, we experimentally varied the amount and timing of food
available to free-foraging colonies of B. vosnesenskii and
measured the effects on within-colony population dynamics. We
supplemented colonies with abundant pollen and nectar resources for a
limited duration (20 days), either earlier or later in the growth phase
of colony development, simulating two resource environments that
differed in their seasonal patterns of food availability. These
supplementation treatments reflect the type of variation reported in
real-world landscapes, with a resource “pulse” (e.g., natural
resources or a mass-flowering crop) occurring either early or late in
the season (Westphal et al. 2009; Williams et al. 2012;
Rundlöf et al. 2014). Thus, we refer to our supplementation and
non-supplementation periods as “pulse” and “off-pulse” periods,
respectively. Using this experimental design, we evaluated the impacts
of varying resources levels and their timing on colony growth and
reproduction, specifically: (1) whether colony growth rates during the
pulse differed depending on pulse timing relative to colony development
(early vs. late); (2) whether the growth rate during the off-pulse
period (i.e. ambient resources only) depended on whether this period
came before or after the pulse; (3) whether early-pulse and late-pulse
colonies achieved similar peak sizes by the end of the colony growth
phase; (4) whether the timing of the pulse affected the switch point
from growth to decline and reproduction; and (5) whether early-pulse and
late-pulse colonies differed in reproductive success.