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Population Cycles in Forest
Lepidoptera Revisited
Judith H. Myers1 and Jenny S. Cory2
1
Department of Zoology, and Biodiversity Research Center, University of British Columbia,
Vancouver, BC, Canada V6T 1Z4; email: [email protected]
2
Department of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada V5A 1S6;
email: [email protected]
Annu. Rev. Ecol. Evol. Syst. 2013. 44:565–92
Keywords
First published online as a Review in Advance on
October 18, 2013
cyclic dynamics, synchrony, traveling waves, climate change, parasitism,
pathogens, immunity
The Annual Review of Ecology, Evolution, and
Systematics is online at ecolsys.annualreviews.org
This article’s doi:
10.1146/annurev-ecolsys-110512-135858
c 2013 by Annual Reviews.
Copyright All rights reserved
Abstract
A quarter century ago, the question was posed of whether a general hypothesis could explain population cycles of forest Lepidoptera. Since then, considerable progress has been made in elucidating mechanisms associated with
cyclic dynamics of forest Lepidoptera. Delayed density-related parasitism
and reduced fecundity during population peaks are common influences on
population dynamics, although why fecundity declines is not understood.
The hypothesis that sunspots explain cycles is rejected. The influences of
delayed-induced plant defenses on populations are inconsistent, but interactions between plant chemistry, pathogens, and immunity remain rich areas
for future study. Population dynamics of forest Lepidoptera can be synchronous over large geographic scales, and repeatable waves of spread of
outbreaks occur for some species. Climate warming could modify species distributions and population cycles, but mechanisms have not been elucidated
and changes in cyclic dynamics are not generally apparent. Integration of
top-down and bottom-up influences on cyclic dynamics and quantification
of dispersal are necessary for progress in understanding patterns of insect
outbreaks.
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INTRODUCTION
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All animal populations fluctuate over time and space. For a subset of species, populations oscillate
on a regular basis. In the relatively early days of the science of ecology, the oscillations of populations challenged the broadly held “equilibrium view” of population regulation. The question of
whether population cycles are determined by biotic or abiotic or by intrinsic or extrinsic factors
has been hotly debated ever since Elton (1927). Initially, most research on insect cycles was carried
out by field ecologists, who monitored populations over many generations. Their focus was primarily on the population trends and the causes of mortality. Myers (1988) reviewed the hypotheses
that were proposed to explain cyclic population dynamics, including climatic release, bottom-up
influences of food limitation, induced plant defenses or changes in food quality, top-down influences of pathogens, parasitoids or predators, and intrinsic changes in quality that are passed
on to offspring by their mothers. She posed the question of whether a general hypothesis could
explain population cycles of forest Lepidoptera and concluded that measuring mortality alone is
not sufficient for understanding cyclic dynamics. Information on reproduction and dispersal is
also needed. She also suggested that the importance of pathogens might have been generally overlooked. Twenty-five years later, we revisit the question of generality by reviewing recent work and
ask, “What are the common characteristics of forest Lepidoptera populations that might explain
their cyclic dynamics?”
Population ecologists have a tendency to emphasize the mystery of population cycles perhaps
to rationalize what they do. Without a doubt, the boom and bust dynamics of some species are
fascinating not only to ecologists but also nonecologists who see widespread defoliation and are
faced with periodic rains of frass or writhing masses of caterpillars. But the cyclic dynamics of
these populations are captivating in many regards. For example, given the long-term data sets that
are available, the influences of changing environmental conditions on population cycles can now
be identified. Currently for all ecological systems, climate change has the potential to dramatically
modify the patterns of population dynamics and the associations among species (Parmesan 2006).
The elegant symmetry in temporal population data of cyclic species is also of interest to theoretical
ecologists. Can models be developed that create cyclic dynamics? Can they mimic the observed
patterns of synchrony and spread?
Much has happened since the last review by Myers (1988); data sets have become longer, techniques for remote sensing have become more sophisticated, new and accessible statistical techniques have been developed, and more experimental results to investigate potential mechanisms
have accumulated. In order to assess whether we are approaching a better general understanding
of the underlying processes regulating population dynamics in forest Lepidoptera, we
1. review classic examples of population cycles to describe differences and similarities in patterns
of density change, parasitism, and fecundity;
2. evaluate some of the hypotheses proposed to explain the dynamics of cyclic populations in
the light of recent data;
3. consider the advances in elucidating patterns of synchrony among populations and waves of
outbreak spread and how they might be influenced by climate change and phenology;
4. suggest new directions for future studies to expand our understanding of potential mechanisms underpinning cyclic population dynamics at different scales.
CONDITIONS FOR CYCLIC DYNAMICS
Three factors are required for cyclic population dynamics: (a) sufficiently high fecundity and/or
survival to allow the population to increase by three to six orders of magnitude during the four
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a
1,000
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20
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1986
1990
1994
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2006
2010
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b
Population trend
(number of tents)
Population trend
Percent infected
Percent parasitized
Mean eggs
0
2014
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1
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0.1
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1990
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Mean eggs per mass (N+1)
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Percent parasitized
or families infected
Population trend
(number of tents)
10,000
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2014
Year
Figure 1
(a) Population trend (shaded area), percent parasitized (red dashed line), and percent families of western tent
caterpillars infected by nucleopolyhedrovirus (blue solid line) on Galiano Island in southwestern British
Columbia. (b) Mean eggs per egg mass for moths in the year indicated. These will give rise to the population
in the next generation. ( J. H. Myers and J. S. Cory, unpublished).
or five generations of the increase phase, (b) density-related, increased mortality factor(s) that
initiate the decline at peak density, and (c) a delayed density-related mechanism(s) that prolongs
the population decline. The factors that initiate the population decline need not be the same as
those that prolong the decline.
Examples of Population Cycles and Population Trends
To illustrate the cyclic dynamics of forest Lepidoptera, we have chosen three species that have
been studied for a sufficiently long period of time for patterns to be clear, and for which data
on population density and parasitism or disease have been collected (Figures 1–3). These are
the western tent caterpillar (WTC), Malacosoma californicum pluviale (Lasiocampidae) (Wellington 1960, Myers 2000, Cory & Myers 2009); the autumnal moth (AM), Epirrita autumnata
(Geometridae) (Bylund 1995, Ruohomäki et al. 2000, Tanhuanpää et al. 2002, Tenow et al. 2007);
and the larch budmoth (LBM), Zeiraphera diniana (Tortricidae) (Baltensweiler & Fischlin 1988,
Dormont et al. 2006). Each of these studies has measured insect abundance directly, rather than
having merely monitored patterns of defoliation, and this allows better illustration and understanding of their dynamics. Although overwintering as eggs and laying eggs in masses are traits
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Percent parasitized
or leaf length (mm)
Population trend
(larch budmoth / kg foliage)
10,000
Population trend
Percent parasitized
Leaf quality
20
1945 1950 1955 1960 1965 1970 1975 1980 1985 1990
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Year
Figure 2
Population trend (shaded ) and percent parasitized (red dashed line) with change in leaf quality, indicated by
needle length of subalpine larch for larch budmoth in the Engadine Valley in the Swiss Alps. Data collected
by W. Baltensweiler and made available by P. Turchin (http://www.eeb.uconn.edu/people/turchin/
NLTSM.htm).
that occur more commonly among outbreak species of forest Macrolepidoptera (Hunter 1991), of
these three species, only tent caterpillars lay eggs in masses and have gregarious larvae. All three
of the species have a single generation per year, overwinter as eggs, and have peaks of population
density every 6 to 11 years, with most outbreaks occurring every 8 to 10 years. In addition, the
patterns of the population cycles are comparable in that the duration of the increase and peak
phases tends to be more variable than that of the decline phase, which usually occurs over two
generations. This pattern is common in other cyclic species of forest Lepidoptera (Myers 1988).
Patterns of Parasitism and Disease
The impact of larval parasitoids has been monitored for all three focal species. The general trend
is for parasitism to reach high levels at or just after the peak of population density (Figures 1a–3a)
and remain high for one to two generations. According to models, parasitism explains a significant
portion of the density variation in the LBM (Turchin et al. 2003) and in the AM (Tanhuanpää
et al. 2002). Parasitism acts in a delayed density-dependent manner.
Density-related infection by a baculovirus (nucleopolyhedrovirus, NPV) initiates the population declines of the WTC (Figure 1a). Baculovirus epizootics in forest Lepidoptera occur most
commonly in species in the families Lymantriidae [gypsy moth (GM), Lymantria dispar, and tussock moths, Orygia spp.] and Lasiocampidae (tent caterpillars) (Cory & Myers 2003). The role
of pathogens is less clear for the Geometridae and Tortricidae. Granulovirus infection (another
type of baculovirus) did occur in the LBM in the peak years of 1955 and 1964 (Baltensweiler &
Fischlin 1988). Tenow (1972) found high numbers of AM larvae killed by a cypovirus (CPV) in
the 1955 and 1965–1966 outbreaks, and NPV infection was observed in AM larvae in 2003–2004
and again in 2012 by Helena Bylund (personal communication). The occurrence of disease has
not been monitored in a consistent manner in LBM or AM.
Patterns of Fecundity and Surrogates of Fecundity
In addition to the changes in mortality of cyclic forest Lepidoptera, fecundity, moth size, and
fitness also vary with population density for these three species. Changes in fecundity are best
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Population trend,
autumnal moth
Population trend,
winter moth
Percent parasitized
Moth size
0
1959
1964
1984
1989
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Year
b
Moth size
2.5
Population trend
(larval density index)
1,000
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100
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Moth size (femur length, mm)
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Parasitized
1,000
Percent parasitized
Population trend
(mean number of larvae per branch)
a
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2.0
Year
Figure 3
(a) Population trend (shaded ) and percent parasitized (red dashed line) for autumnal moth based on two sites in
the Abisko Valley, Sweden. Data provided by O. Tenow and H. Bylund. (b) Population trend for autumnal
moth (shaded ) and that pooled with four generations of winter moth (thick line) in Hana, northern Norway.
Moth size is reflected by the femur length ( green dashed line). Note the continued high density of winter
moth after the autumnal moth declined. Data provided by T. Klemola (Klemola et al. 2008).
described for the WTC. Each female moth lays all of her eggs in a single egg mass that remains on
the branch and can be collected and counted after the eggs hatch. For the WTC, fecundity peaks
just before or at peak density and then declines for several consecutive generations (Figure 1b)
(Myers 2000). Three hypotheses that have been proposed to explain the decline in fecundity of
the WTC are (a) food limitation, (b) sublethal infection of late instar larvae or the costs of fighting
infection (Rothman & Myers 1996a), or (c) a cost of selection for resistance to viral infection. Direct
evidence from field experiments relates both larval density and viral exposure to the reduced egg
mass sizes of surviving moths and the pupal weights (a surrogate for fecundity) of their female
offspring (Rothman 1997). Evidence does not support the third hypothesis because larvae from
smaller egg masses are not more resistant to viral infection (Rothman & Myers 1996b, Cory &
Myers 2009). For field populations of WTCs, moth fecundity explains approximately 30% of the
variation in the rate of population increase between generations ( J. H. Myers and J. S. Cory,
unpublished data).
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Indicators of fecundity change for the LBM are indirect. Defoliation by high densities of
larvae reduces the length of larch needles in subsequent generations (Figure 2), and related to
this are increased fiber content and reduced nutritional quality. Based on laboratory studies by
Benz, who fed larvae needles of different lengths, Turchin (2003) calculated that needle length
explained 86% of the variation in LBM fitness measured as survival and fecundity. Baltensweiler
et al. (1977) reported that fecundity declines by 75% to 85% in the year following defoliation.
Thus, like the WTC, fecundity of the LBM is reduced during the population decline.
The sizes of moths and pupae are well correlated to fecundity (Kaitaniemi et al. 1999). Considerable experimental work has been carried out in this system to relate moth fecundity and fitness
to larval feeding damage to host trees. Pupae resulting from larvae reared in bags on trees over a
period of outbreak density were larger in the peak than in two subsequent years (T. Klemola et al.
2004). Pupal mass and moth size of the AM were weakly related to defoliation in the previous
generation (Kaitaniemi et al. 1999). T. Klemola et al. (2008) showed that adult moths were smaller
late in the peak but increased to moderate size again as the decline progressed (Figure 3b). An
interesting twist is that, in addition to outbreaks of the AM, the winter moth (WM), Operophtera
brumata, also feeds on the same trees in this area and typically reaches peak density two years after
the AM (Tenow et al. 2007). The decline in AM size and fecundity at peak densities is unlikely to
be explained by reduced host-tree quality as the host quality was still sufficient to support outbreak
densities of the WM. Kaitaniemi et al. (1999) concluded that the reduction of fecundity at peak
density of the AM is insufficient to explain the population decline without other factors.
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Summary
The similarities in population trends shown in Figures 1–3, and the characteristics associated
with the dynamics of these three well-studied species summarized in Figure 4, occur even though
the species are in different families, live in different habitats, and have different host trees and
parasitoid complexes. In all of these examples, crowding at peak density reduces moth size and
thus fecundity, and this can persist over several generations of population decline. It is unlikely
Feeding damage
Increased infection (WTC)
Reduced fecundity
Reduced larval survival
Negative R
Increased parasitism
Increased dispersal?
High density
Positive R
Low density
Increased fecundity
Improved survival
Low infection (WTC)
Reduced parasitism
Figure 4
Factors related to the rate of population increase R (density at Nt +1 /density at Nt ) of cyclic populations of
forest Lepidoptera. Abbreviation: WTC, western tent caterpillar.
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that the levels of reduced fecundity are sufficient to create cyclic dynamics without the influence of
increased mortality from parasitism that also occurs for several generations during the population
declines (Figures 1–3). This is an area that deserves more exploration with models such as those of
Turchin et al. (2003) and Kendall et al. (2005) that incorporate both parasitism and moth quality
and conclude that both are important. In addition, although the population cycles of eastern spruce
budworm, Choristoneura fumiferana, differ from the three species described above in that outbreaks
are more prolonged with defoliation lasting for 10 years or more, Régnière & Nealis (2008) propose
that the impact of larval defoliation on tree condition reduces the survival of dispersing early-instar
larvae. They attribute the cyclic population dynamics to reduced early larval survival exacerbated
by other factors, including maternal fecundity, infection by the microsporidian Nosema fumiferanae,
and weather influences, as well as density-related mortality from natural enemies. It is likely that
both top-down and bottom-up processes are involved in cyclic population dynamics of forest
Lepidoptera.
TESTING HYPOTHESES
Since 1988 considerable information has accumulated that allows a more critical look at some of the
hypotheses that have been formulated to explain cyclic population dynamics of forest Lepidoptera
and to suggest those that look most promising for future research. The complexity of these cyclic
populations and the variation of the habitats and communities in which they exist make it difficult
to reject any hypothesis definitively; however, it is becoming clear that no one hypothesis will
explain all population cycles in forest Lepidoptera, and combinations of several factors will form
the most likely explanation.
The Role of Parasitoids in Cyclic Dynamics
Alan Berryman (1996, 2002) has been the strongest proponent of the importance of parasitoids as
the driving force in population cycles. Certainly parasitism is a universal mortality factor for forest
Lepidoptera and, as shown in Figures 1–3, it can reach very high levels following peak population
densities of the hosts. Not only that, but parasitism generally remains high for several generations
following host decline and thus fulfills the delayed density-dependent criteria for cyclic dynamics.
Carrying out field experiments on the role of parasitoids is difficult, but this has been accomplished
recently for the AM (Klemola et al. 2010). Over four years of high and declining AM populations in
northern Finland, the exclusion of parasitoids allowed continued high host densities as compared
to natural populations or those in exclosures permeable to parasitoids.
In contrast, parasitism of larvae was found to be weakly correlated to population growth of
the AM and WM over an elevational gradient on a Norwegian coastal island (Schott et al. 2010).
Although some of the geographical variation in population growth rate was related to parasitism,
temporal variation in the rate of population growth was not. Larval densities at these sites were
lower than the outbreak densities of continental populations, and defoliation did not occur. Cyclic
dynamics were most apparent at high elevation sites only. It is possible that these populations are
influenced by immigration of moths or ballooning larvae from the traveling wave of outbreaks
that occur in continental populations (see below). In comparison, an analysis of Bylund’s (1995)
and subsequent data on a continental population of the AM (illustrated in Figure 3a) shows a
significant negative relationship between R = log (n + 1/n) and parasitism (r2 = 0.23, p < 0.02).
With a very simple model based on these data, Tanhuanpää et al. (2002) concluded that parasitism could explain the cycles of the AM. Klemola et al. (2009) compared parasitism and predation
of the AM and the WM over a population outbreak and found that increased parasitism occurred
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late in the peak of the AM but not of the WM. For the latter, predation of pupae was higher. In
addition, the models of the LBM (Turchin et al. 2003) and of the pine looper, Bupalus piniarus
(Kendall et al. 2005), provide strong support for the parasitoid hypothesis, although both of these
analyses also found that factors associated with food quality and fecundity strongly contributed to
the population dynamics.
We conclude that though it is difficult, time consuming, and expensive, more work should
focus on parasitism, including investigations of the host ranges and the geographical distributions
of parasitoids. Questions such as whether parasitoids are maintained by alternate hosts, whether
they move readily among populations and can synchronize host populations, and how egg and
pupal parasitoids contribute to host dynamics deserve further study.
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The Role of Predation at Low Prey Densities
As mentioned above, Klemola et al. (2009) found that predation on WM pupae was greater than
that on AM pupae, although in other field experiments differential predation was not statistically
significant (Heisswolf et al. 2010). Klemola et al. (2009) suggested that pupal predation could
prolong the lag phase for the WM as compared with the AM and cause the cycles of the two species
to be out of phase by one to two generations. Previously, Roland (1994) showed that the initial
decline of the WM introduced to Canada was associated with high parasitism by the biological
control agent, Cyzenis albicans, but that generalist ground predators, primarily polyphagous beetles,
regulated populations at lower densities. In a similar situation, deer mice, Peromyscus maniculatus,
feed on pupae and larvae of GMs, and Elkinton et al. (1996) suggested that deer mice could play a
role in maintaining low GM density. This situation is particularly interesting because it involves
three trophic levels: the GM prey, the predacious deer mice, and oak trees that provide leaves for
GM larvae and acorns for the mice. Although years of high acorn production were correlated to
increased mouse abundance, and thus predation on GM, further study showed that GM pupae
and larvae were not as attractive to deer mice as were alternative prey items and that predation
was closer to a type 2 functional response than to a type 3 functional response that could prolong
the low density of GMs. Elkinton et al. (2004) concluded that predation by small mammals was
unlikely to stabilize low-density populations of GMs. Models of GM populations that included
mortality from a generalist predator or parasitoid following a type 3 rather than a type 2 functional
response and a specialist virus resulted in more irregular lengths of cycles but not long periods
of low density (Dwyer et al. 2004). Further analysis of the total 86 years of GM defoliation in the
northeastern US by Allstadt et al. (2013) shows periods of noncyclical and cyclical dynamics with
harmonic oscillations of 4–5 and 8–10 years during the latter. They suggest that predators create
extended periods of noncyclical dynamics of GMs. Unfortunately there are no actual long-term
population data on GMs, small mammals, and viral infection to test the various models, and
thus conclusions remain speculative. The contradictory results of these studies make conclusions
impossible.
Bird predation is common for low-density populations of the forest tent caterpillar (FTC),
Malacosoma disstria, in aspen and mixed boreal forests in Alberta, Canada (Parry et al. 2003).
Generalist predation on FTC was higher in aspen than in mixed-wood stands, and Nixon &
Roland (2012) suggest that this may cause FTC populations to be slower to reach outbreak levels
in aspen stands. This relationship has not yet been tested.
To conclude, predators have not received as much empirical study as parasitoids in relation
to cyclic population dynamics, partially because they are difficult to study and require elaborate
designs to manipulate. Also they are generalists and not dependent on the moths. Predation from
spiders, beetles, small mammals, and birds remains a black box in most population studies. Support
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for the hypothesis that generalist predators maintain a low-density lag phase in the cyclic dynamics
of forest Lepidoptera is weak.
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Future direction: empirical studies of predation. Further experimental work to elucidate
the impact of generalist predators in low-density populations of forest Lepidoptera is required
to determine predators’ roles in the cyclic population dynamics of forest Lepidoptera. This
is of particular interest to the interactions between sympatric populations of the AM and the
WM.
Future direction: testing the predictions of models. Predictions arising from the numerous
models of the interactions among GM populations, predators and viral disease should be tested
with field data and reasons for contradictory conclusions among studies should be recognized
and discussed. It should be imperative for future modeling studies to explicitly state testable
predictions.
Pathogen Impact in Cyclic Populations
The main group of pathogens associated with forest Lepidoptera is baculoviruses. The symptoms
of infected larvae are very distinctive and can result in spectacular epizootics in high-density
populations and are often associated with population declines. The population dynamics of the
WTC and the GM are strongly influenced by NPV infection (Myers 2000, Cory & Myers 2009,
Dwyer & Elkinton 1993). In the buildup to an epizootic, NPV is spread horizontally following
the death of an infected larva. NPV infection clearly responds to rising host density and is strongly
implicated in the population crash in the WTC, with peak mortality and peak density coinciding
(Figure 1). In addition, baculoviruses can produce delayed influences through sublethal effects
(Rothman & Myers 1996a) or potentially, although less likely, through costs of resistance
(discussed above). Dwyer and colleagues have produced a detailed series of mathematical models
supported by manipulative lab and field experiments to describe the interaction between the GM
and NPV (Dwyer et al. 1997, 2000; Elderd et al. 2008). These models focus in particular on
heterogeneity in infection risk associated with resistance. The model outputs have been compared
to patterns of defoliation rather than to actual data on GM populations and infection and thus
are difficult to interpret particularly as dynamics change over time (Allstadt et al. 2013).
One of the key issues with the NPVs of the WTC and the GM is that they are both host-specific
and the host is univoltine. Thus the virus has to persist from one year to the next and across several
years when host populations are low, at least in the WTC (Figure 1). In the absence of alternative
hosts, the only way for the pathogen to persist is via either environmental persistence or vertical
transmission from parents to offspring.
Fuller et al. (2012) believe that environmental persistence is sufficient to maintain the pathogen
in GM populations. However, with the use of polymerase chain reaction (PCR) to amplify small
quantities of virus DNA or RNA from adult moths, it is clear that baculovirus infections can
persist in adult Lepidoptera. For example, 70% of adult eastern spruce budworm, Choristoneura
fumiferana, individuals sampled were positive for NPV DNA (Kemp et al. 2011). Presence of this
DNA is not usually expressed as overt disease in the offspring generation and is regarded as a
covert infection. Investigation of the WTC has also demonstrated the presence of covert NPV
infection, the level of which appears to fluctuate with host population density; i.e., it cycles ( J. S.
Cory and J. H. Myers, unpublished data).
To have a significant impact on population dynamics, covert virus would need to convert at
some rate to an overt infection that could be horizontally transmitted through the host population
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(Bonsall et al. 2005). Although a variety of mechanisms have been suggested as triggers, none
have been consistently found. Cross infection of FTCs from high-density populations with
WTC virus resulted in the apparent expression of a covert FTC NPV (Cooper et al. 2003). This
suggests that such conversions can occur when stimulated by a nonhost virus. Also, spontaneous
overt infection does occur at a low level (0.5% to 10% of egg masses or larvae) in larvae
hatching from surface-sterilized eggs transferred to trees not previously attacked by WTCs or in
laboratory-reared larvae ( J. S. Cory and J. H. Myers, unpublished data).
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Future direction: virus persistence through covert infection. Although it seems quite feasible
that different mechanisms play roles in host species with differing ecologies, a clear understanding
of the relative importance of environmental versus vertical routes of virus persistence at differing
host densities is needed to explain insect-pathogen dynamics fully. The transition from vertically
transmitted covert infection to lethal, horizontally transmitted, overt infection is of particular
relevance to field populations and of interest to theoretical and evolutionary ecologists.
Future direction: probing pathogen communities. The current lack of evidence for
widespread pathogen infection in other cyclic species might indicate that this is not a general
mechanism driving population dynamics of forest Lepidoptera. However, only the more obvious
pathogen infections (like NPVs) tend to be identified, and insects are likely to be carrying a range
of pathogens that may have chronic effects and be less readily identified visually. For example,
as mentioned above, viral infections, particularly cypovirus infections, have been observed in the
LBM, the AM, and the WM, and microsporidian infection is common in eastern spruce budworm.
With PCR and second-generation sequencing, it is now possible to identify the pathogen community present in host populations. This could be an important new way to describe the quality
of insects in different populations or at different stages of the cycle.
The Sunspot Hypothesis
Ecologists have long been interested in patterns of biological cycles among species (Huntington
1931). In a summary of population outbreaks of forest Lepidoptera, Myers (1998) observed an
apparent clustering of peak populations in some years. This caused her to look for a global cuing mechanism for population outbreaks. Sunspots seemed a possible explanation as troughs of
sunspots are associated with cooler temperatures. Ruohomäki et al. (2000) also noted the correspondence between sunspot cycles and AM population cycles. Selås et al. (2004) reported a
negative relationship between sunspot activity and populations of AM and WM in central and
southern Norway. They proposed a rather complex mechanism based on the ozone layer, and
the trade-off between the production of UV-B protective pigments and insect defenses. Haukioja
(2005) expanded on this idea, suggesting that high UV-B could trigger the octadecanoid pathway,
which could increase the immunocompetence of larvae and thus protect them against disease and
parasitism and allow the population outbreaks.
The flaw in the original suggestion of a pattern between insect outbreaks, with normally an
8- to 10-year periodicity, and sunspots with an 11-year periodicity is that these two sequences
will run in and out of phase over time. This is exactly what was revealed by sufficiently long sets of
data. Nilssen et al. (2007) compared a 114-year data set showing the periodicity of AM outbreaks
and the sunspot record and found that the two sequences do run in and out of phase. Thus, even
though sunspot numbers might influence temperature and plant exposure to UV-B, they cannot
be considered to be a long-term driver of population cycles. The sunspot hypothesis should be
rejected.
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Induced Plant Defenses
The discovery that plant secondary compounds change following herbivore damage brought the
idea that this could drive the population cycles of forest Lepidoptera (Rhoades 1985, Haukioja
& Neuvonen 1987). Effects of the induced secondary compounds of trees can act rapidly in the
current generation of larvae as population density rises and defoliation increases, and they can also
be passed on through changes in foliage quality in the years following an outbreak. This creates
delayed effects that can extend into the population decline, thereby providing a mechanism to
promote cycles. The amount of work done on this hypothesis is extensive, and the results are contradictory (reviewed by Nykänen & Koricheva 2004, Kessler et al. 2012). Although there is clear
evidence that changes in plant quality as a result of damage can alter growth rate, survival, and
fecundity of moths, links to changing population density in the field have not been found. Much of
the work in this area has been done with the AM system. Haukioja (2005), who was one of the initial
proponents of the potentially important role of induced plant defenses in insect population dynamics, has concluded that “delayed inducible production of secondary compounds does not seem
to explain cyclic fluctuations in population density” for the AM (p. 313). Although induced effects
alone may not appear to have an impact, they could combine with other factors, such as through
their effect on immunity and interactions with natural enemies (see below). Induced plant defenses
are likely to vary among host tree species and conditions and thus are unlikely to be a general mechanism causing cyclic population dynamics. We conclude that by itself, the induced plant defense
hypothesis is not supported even though changes in plant chemistry following insect attack might
interact with insect diseases, parasitoids, or larval growth in complex ways (Sarfraz et al. 2013).
Future direction: host-quality influences on insect phenotypes in the field. Given the variation in response to different chemistries, further research in this area should focus on the overall
impacts on insect phenotype in field populations, including the impacts on life-history traits,
behavior, and selection at different phases of the population cycle.
Future direction: projections from individual phenotypes to population dynamics. Projections of the influences of induced plant changes on individual insects to population dynamics
should be done with caution. The variable conditions in the field such as different host plants and
levels of attack influence how individual impacts scale up to population dynamics.
Insect Quality and Immunocompetence
One area that has attracted increasing attention in recent years is the role of insect quality or
condition and, in particular, changes in insect immunocompetence. This returns us to the ideas of
Wellington (1960) and Chitty (1971) and moves the focus back to the impact of broader changes
in insect quality rather than identifying the individual factors that might modify it. The basic idea
is that changes in food quality or quantity could modify both insect condition and susceptibility
to disease or parasitism through influences on immunocompetence at different points of the
population cycle (Haukioja 2005, Shlichta & Smilanich 2012).
Immune response and natural enemy protection. A particular focus has been on population
increase and whether an enhanced immune response could allow individuals to escape their natural
enemies (Haukioja 2005). Considerable experimental work has been done on the pupal parasitoids
of the AM to test this relationship. Variation in tree quality (assessed by insect growth rate) and
plant chemistry can alter pupal immunocompetence. For example, changes in foliage quality the
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year following defoliation resulted in an increased ability of pupae to encapsulate a foreign object
used as a surrogate for parasitoid eggs (Kapari et al. 2006). However, observed encapsulation in the
laboratory was low, and no link could be found between changes in immunity and pupal parasitism
in the field. The idea that changes in immunocompetence either drive or modulate population
cycles in this system is not supported (N. Klemola et al. 2007, 2008).
Similarly the impact of induced plant chemicals on insect pathogens is variable. Many entomopathogens are affected by the insect host plant (Cory & Hoover 2006). However, whether
these changes are brought about through a direct effect of host-plant secondary chemicals on
the pathogen itself or altered immunity is less clear. As an example, in the GM the hydrolyzable
tannins induced by feeding on oak reduced NPV mortality in laboratory studies and led to the suggestion that induction actually protects the insects (Hunter & Schultz 1993). This was predicted
to destabilize GM populations at intermediate tannin levels (Foster et al. 1992). Transmission of
virus in the field is more complex and is related to insect behavior, variation in the dose ingested,
changes in insect susceptibility related to larval stage, and the breakdown in virus activity. A recent
study revisited the induction hypothesis and focused on the effect of induction on the variability in
the GM’s risk of infection (rather than the average risk). Variability in risk of infection declined in
insects exposed to leaves with increased hydrolyzable tannin levels, and incorporating this information destabilized models of population dynamics and resulted in cyclic behavior (Elderd et al.
2013).
An alternative route to enhanced immunity with increasing insect population density is through
density-dependent prophylaxis (DPP); that is, animals invest more in parasite resistance when
population density is high and the risk of infection is greater (Wilson & Reeson 1998). This
would be a response to the cost of immunity preventing the insect from upregulating the immune
system on a continual basis. A theoretical analysis of the impacts of DPP on population dynamics
(Reynolds et al. 2011) shows that the potential consequences on host population dynamics critically
depend on the time delay between the change in density and the increased resistance. As often
is the case with theoretical analyses, an array of host dynamics are possible from cyclic to stable
depending on conditions. One study on GMs failed to find evidence of DPP (Reilly & Hajek 2008),
and Klemola et al. (2007) found no evidence for increased immunity at higher insect densities.
The high levels of parasitism at peak host density (Figure 3a) indicate that the immune system is
not effectively defending against parasitoids. As WTCs are gregarious from birth until the fifth
instar and are thus always exposed locally to high larval densities, it also seems unlikely that this
species will demonstrate DPP. This conjecture is supported by an interspecific comparison of
solitary and gregarious Lepidoptera that indicated that gregarious species had lower, rather than
higher, values for several immune measures (Wilson et al. 2003). Therefore, this hypothesis seems
unlikely to be relevant in cyclic population dynamics.
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Changing immunity and conditions that lead to collapse. Changing levels of immunity and
a decrease in condition could also trigger the decline at outbreak densities by allowing pathogen
prevalence, in particular, to increase, thus leading to further mortality [this is the vicious circles
hypothesis by Beldomenico & Begon (2010)]. One trend seen in the dynamics of several forest
insects is that fecundity and survival can start to decline before the population peaks (Figure 1b). A
possible explanation is that increasingly high population densities result in some level of starvation
or detrimental changes in foliage quality, causing reduced immunity and increased susceptibility
to pathogens and parasitoids. Experimental data with the AM showed that starvation can alter
immunity, but different immune measures changed in opposite directions, making the impact
impossible to predict (Yang et al. 2007). The general message is that secondary chemicals have
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variable effects on different aspects of immunity, which may or may not influence the susceptibility
of the insects to parasites.
An indication of what might be happening in the field comes from studies on WTCs collected
from several sites before, during, and after a population peak, which clearly demonstrated that
the condition of the insects declined as density rose (Cory & Myers 2009). Larvae reared from
egg masses collected prepeak had very high levels of survival and were disease free, whereas larvae
reared in exactly the same manner in the following two years at peak and postpeak densities died
from a range of pathogens. Where these pathogens came from is unclear, but given that the
rearing conditions were the same each year and the eggs masses were surface-sterilized to remove
any contaminating pathogens, as were the leaves used to feed the larvae, it seems most likely
that infection resulted from pathogens being carried in a sublethal or latent form by the insects
themselves. It is not clear what triggers the expression of these pathogens or how they might be
retained within the insects; however, changes in immunity through nutritional stress resulting
from high-density insect populations or other as yet unidentified causes are likely mechanisms.
Future direction: the role of insect quality in population dynamics. Identifying and explaining changes in insect quality with changes in population density could be an important area
for understanding population fluctuations. The interplay between nutrition and susceptibility to
disease is part of this.
Future direction: plant quality and general disease resistance. Studies should investigate
the impact of a broader range of disease-causing microorganisms and use realistic measures of
the resistance to disease of field populations in relation to the overall plant quality rather than
responses to specific chemicals.
Maternal Effects
Density-related, delayed intrinsic effects have been suggested as a mechanism for the generation
of population cycles in forest Lepidoptera (Rossiter 1994, Inchausti & Ginzburg 2009). Under
this scenario, population density in the maternal generation will have an impact on the quality of
resulting offspring, mainly through the direct effect of per capita investment or the consequences of
altered competition in the offspring environment. This impact will then feed back to population
density and result in an interplay between the two. The underlying drivers for these delayed
changes in life history characteristics tend to be divided into those related to nutritional factors
(primarily leaf quality) and nonnutritional aspects (for example, the impacts of crowding directly),
which alter the quality or quantity of egg provisioning (Rossiter 1991). Support for the maternal
(or more broadly parental) effects hypothesis for forest insects has been limited (Beckerman et al.
2002). In the analysis of pine looper moth population dynamics by Kendall et al. (2005), densityrelated effects on moth size that in turn influenced offspring performance and density-related
parasitism were important in driving the cycles. In general, defoliation resulting from high-density
populations clearly influences female pupal weight, and thus fecundity. This is particularly true
for capital breeders for which all the resources for reproduction are obtained through feeding as
larvae. A majority of outbreak species are capital breeders. Impacts of density and food limitation
on offspring quality and vital rates have received little attention.
Impact of food quality on survival and offspring quality. Some evidence exists for maternal effects in forest Lepidoptera, but in general, this area has not received much attention. In
C. fumiferana, lab studies showed that variation in food quality altered offspring fitness, resulting
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in poorer offspring survival, but this also resulted in selection for later instars with a greater resistance to starvation and a greater likelihood of surviving diapause (Carisey & Bauce 2002). In GMs
collected from field sites with low (<20%) and high (>90%) levels of defoliation, larvae from
nutritionally stressed sites had a lower tendency to disperse by ballooning than mothers from less
defoliated sites, and they weighed less (Diss et al. 1996). However, no differences were discernible
for the longevity of offspring, and impacts on yolk protein were variable. Maternal effects such
as development rate and final size of offspring are related to egg size and the order of laying
(Wellington 1965, Rossiter 1991), such that larvae from eggs with more yolk do better. In another
study on GMs, the number of eggs per mass was related to the density of the field populations and
varied from means of 600 to 800 eggs per mass in three low-density populations to means of 200
to 350 eggs per mass for three high-density populations. When reared in the laboratory, the only
factor that varied among larvae from eggs from high- and low-density populations was sex ratio;
more males developed from high-density populations (Myers et al. 1998). Thus when larvae were
reared on artificial media and without the influence of variation in the history of host-plant attack,
maternal effects on growth and fecundity were no longer expressed. As with other areas, studies
need to focus more on changes in field populations and manipulative experiments that mimic field
conditions more closely.
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Delayed immune effects and recovery from declines. Insects that have been exposed to but
have survived a pathogen challenge can express various conditions, such as a sublethal effect (cost)
from fighting off the pathogen, a persisting covert pathogen infection, or some type of maternal
effect (including epigenetic effects) that is passed onto the offspring. In the latter category is transgenerational immune priming, where immunity is up-regulated in the offspring generation (Little
et al. 2003). In terms of population dynamics, this is relevant as it could result in delayed protection
against pathogens (and other parasites) in one or more generations after population collapse.
Immune priming has been demonstrated in several insect species, mainly in response to a variety
of bacteria that range in pathogenicity and have been introduced artificially via injection (e.g., Roth
et al. 2009, Zanchi et al. 2011). Lepidoptera have been shown to demonstrate immune priming
to nonpathogenic bacteria (Freitak et al. 2009). There is also evidence of immune priming to a
baculovirus, which reduced susceptibility to the same virus in the offspring generation (Tidbury
et al. 2011). An alternative explanation for this result is that the virus persisted as a covert infection.
Variation in food quality can also cause immune priming. Larvae reared on poor-quality food
showed reduced immunity in the next generation compared with larvae reared on good food
(Triggs & Knell 2012). Interestingly this effect was seen through both maternal and paternal routes.
The authors suggest two explanations for this: maternal effects or imprinting, such as through some
epigenetic mechanism. They suggest that the evidence provides stronger support for the latter.
Experiments with the WTC to study the effect of food limitation and virus exposure showed no
evidence for changes in resistance to NPV in the offspring with either treatment, despite reductions
in moth fecundity and an increase in some measures of immunity in the parental generation (Myers
et al. 2011). This result may indicate that some of the measures now routinely used by ecologists to
estimate immunity in invertebrates need to be more closely linked to specific pathogen infections
for meaningful interpretation (e.g., Saejeng et al. 2010). What is clear from these studies is that
many factors can alter immune quality in a transgenerational manner, but the response in terms of
the direction of change and the possible interaction among different stressors are harder to predict.
Future direction: delayed immune effects. Improved understanding of immunocompetence
provides a mechanism that might be relevant to the recovery phase in population cycles if populations become more resistant to virus infection and parasitoids then. Further studies are clearly
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needed on what alters resistance to pathogens and parasitoids across generations, whether there
are costs to this resistance, and how this resistance affects insect populations in the field.
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Conclusions: Specific Hypotheses Versus General Syndromes
Although many fascinating hypotheses have been proposed to explain the population dynamics
of forest Lepidoptera, a more synthetic approach is necessary. Parasitism and quality change are
consistent characteristics that have been shown to be relevant in the model of the LBM (Turchin
et al. 2003) and that of the pine looper moth (Kendall et al. 2005). Models of the GM including
viral infection and generalist predators produce cyclic dynamics (Dwyer et al. 2004), although
defoliation data show periods of cyclic and noncyclic dynamics (Allstadt et al. 2013). Theoretical
models create cyclic dynamics in many ways. The impact of factors that change with population
density must be evaluated by a combination of manipulative experiments, quantitative analysis,
and mathematical modeling.
SYNCHRONY AMONG POPULATIONS AND SPECIES
AND WAVES OF SPREAD
Another characteristic of forest lepidopteran outbreaks is that they occur over vast distances, and
this is most readily apparent from the spatial extent of defoliation that occurs at outbreak densities
(Peltonen et al. 2002, Lynch 2012). The widespread patterns of defoliation that sometimes occur
give the impression that some cue initiates population increases over large areas simultaneously.
Three hypotheses have been proposed for how this synchronicity develops and is maintained.
Population fluctuations are synchronized by (a) exogenous weather signals, (b) dispersal among
populations, or (c) mobile natural enemies that move among populations. It is very difficult to tease
apart the impacts of these three factors, but if weather signals are involved, predictions of how
cycles will change with warming environments might be feasible. This would require identifying
which of a myriad of weather conditions can strongly influence insect populations. For northern
systems this might be severe winter cold killing eggs or conditions that promote the synchrony in
bud burst and egg hatch.
Spatial Synchrony
Synchrony of cyclic dynamics among species and populations has been of interest since the
Matamek Conference in 1931 in which the cyclic dynamics of many species and the possible
synchronizing factors were discussed (Huntington 1931). An early theoretical consideration of
how weather anomalies might synchronize cyclic populations was carried out by Moran (1953),
who was working with Dennis Chitty on small mammal cycles (Chitty’s idea and Moran’s model;
D. Chitty, personal communication). Moran proposed that two populations with similar dynamics
exposed to the same exogenous signal should be synchronized (Bjørnstad et al. 1999). One way
to investigate the influence of weather on populations is to examine the spatial relationships between patterns of weather and those of population dynamics (reviewed by Liebhold et al. 2012).
The spatial scale of synchrony of populations can be estimated by analyzing correlations among
populations at different distances (Bjørnstad et al. 1999). Density changes of populations that are
synchronized should be highly correlated.
In one example, Peltonen et al. (2002) analyzed landscape-scale, historical outbreak data based
on aerial surveys of forest damage for five cyclic forest lepidopteran species: eastern spruce budworms, western spruce budworms (Choristoneura occidentalis), LBMs, FTCs, and introduced GMs.
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10,000
Population trend
(number of tents)
1,000
Source
100
10
1
0.1
1985
Sink
1990
1995
2000
2005
2010
2015
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Year
Figure 5
Trends for two populations of western tent caterpillars on Galiano Island, British Columbia, Canada, one of
which is a sink population and the other a source population ( J. H. Myers and J. S. Cory, unpublished data).
Although the moth species varied in their dispersal ability from the flightless GM to the more
dispersive spruce budworm, the extent and level of synchrony of outbreaks were similar for each
species, with population dynamics correlated over a distance of 100–200 km. The decline in the spatial correlation among populations occurred over shorter distances than did those of temperature
and precipitation, which were still highly correlated at distances of 700 km. Peltonen and colleagues hypothesized that spatially dependent variation in density-dependent dynamics explained
the more rapid decay in population synchrony with distance and this could be associated with
variation in factors, such as host-plant quality, that influence populations over shorter distances.
Dispersal is probably the least well measured and understood characteristic of cyclic populations
of forest caterpillars. Dispersal among populations at the local scale, however, is likely to be
common. For example, in the WTC, “sink” populations become extinct locally between outbreaks
and thus depend on dispersal from persistent source populations (Figure 5; J. H. Myers and J. S.
Cory, unpublished data). This situation can arise if heterogeneity in host-plant species or climatic
factors results in some locations being better for positive population growth rates than others
(Wellington 1964). In this situation, the increase phases are delayed in the sink population, but
the decline phases are synchronous. Even dispersal at relatively short distances, e.g., kilometers,
can suffice to synchronize outbreaks.
Another example in which spatial synchrony of populations has been evaluated is based on defoliation by GMs in New England (United States), Europe, and Japan ( Johnson et al. 2005).
Dominant periodicities of defoliation peaks were significant for only two of the five North
American states, whereas four of five European populations had significant dominant periodicities. The patterns of defoliation in New Hampshire and Massachusetts are shown in
Figure 6b, and it can be seen that some outbreaks are synchronized between these states, whereas
others are not. Particularly early on, populations did not have cyclic dynamics. It is possible that
cyclic dynamics started after the establishment of introduced parasitoids (Elkinton & Liebhold
1990), and this might illustrate the influence of parasitoids on the establishment of cyclic population dynamics. These data are further analyzed by Allstadt et al. (2013).
Host plants undoubtedly influence the population dynamics of forest Lepidoptera. In a recent
analysis of defoliation data for GMs in the northeastern United States from 1975 to 2005, Bjørnstad
et al. (2010) found that the periodicity of outbreaks differed between forest types; in dry, oak-pine
forests the periodicity of outbreaks was four to five years, whereas in drier, maple-beech-birch
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15,000
Ha defoliated × 1,000
a
10,000
5,000
1934
1944
1954
1964
1974
1984
1994
2004
2014
Year
1,000
Ha defoliated × 1,000
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0
1924
b
New Hampshire
Massachusetts
10
0.1
0.001
1924
1934
1944
1954
1964
1974
1984
1994
2004
2014
Year
Figure 6
(a) Trends in area defoliated by the gypsy moth in the northeastern United States. Data are plotted on a
linear scale to show the decline in the amplitude of the outbreaks in the past ten years. (b) Defoliation data
for New Hampshire (red solid circles and line) and Massachusetts (open blue circles and line). These two states are
geographically adjacent. Data from the US Forest Service (http://www.na.fs.fed.us/fhp/g/cfm_files/dsp/
dsp_defchart.cfm).
forests and intermediate oak-hickory forests the periodicity of outbreaks was nine to ten years
with a weak correlation also at four years in the latter (see Figure 6a). This demonstrates the
complexity that can occur in cycles of GM defoliation in different forest conditions. Some of the
variation in cycles is attributed by Bjørnstad et al. (2010) to small mammal predation on GMs,
and Elderd et al. (2013) relate the difference to varying levels of induced defenses between tree
species influencing the risk of virus infection of the GM. These hypotheses require experimental
testing and comparison to the recent patterns of declining defoliation (Figure 6a).
Widespread populations of FTCs in Ontario and Quebec in eastern Canada also vary in their
dynamics (Cooke et al. 2011), as indicated by patterns of defoliation. Seven out of nine populations
and the region as a whole fluctuated with a periodicity of approximately ten years. One population
had infrequent outbreaks. A major outbreak lasting from 1951 to 1954 affected all populations.
The densities of populations less than 100 km apart were highly correlated. These populations
illustrate how regional dynamics can be quite variable, but also synchronized at some times such
as was observed in 1951–1954.
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In Fennoscandia, Klemola et al. (2006) identified clusters of populations with synchronous
dynamics and positive cross correlations in population growth rates. The strongest synchrony
was within regional clusters, where moths shared similar environments. Synchrony was observed
over distances of 700 km, which is further than that for other species mentioned above. Southern
populations still cycled but with less amplitude.
Synchrony between species or genetically distinct biotypes more likely reflects exogenous inputs
such as weather anomalies or the impacts of common parasitoids. One such situation involves LBM
populations in France and Switzerland (Dormont et al. 2006). Two genetically distinct biotypes of
LBM exist, one that feeds on subalpine larch and the other on Cembran pine. In both areas where
populations have been monitored, peak densities have been within a year of each other. Little is
known about whether these two biotypes share parasitoids but it is likely that they do. As discussed
above, another European example of population synchrony between genetically distinct species
involves AMs and WMs that attack the same birch trees in Fennoscandia (Tenow et al. 2007).
These reach peak densities one or two years out of phase. Therefore, although they experience the
same climate and have the same food plants, some factor is influencing their dynamics in slightly
different ways. Mutual parasitoids could again be a factor, and different levels of predation could
influence the two species differentially. After the population decline, parasitism of experimentally
released AM larvae was high, which indicates that parasitoids remained common after the decline
of the AM and with continued high density of the WM (N. Klemola et al. 2008).
In conclusion, in most cases synchrony of insect population dynamics drops off at shorter scales
than does the spatial similarity in temperature and precipitation. A difficulty with these studies is
identifying what type of weather anomaly might be relevant to insect populations (see below).
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Waves of Outbreak Spread
In contrast to the widespread synchrony of population outbreaks is the occurrence of spatial waves
of outbreaking populations over geographical space. Based on 40 years of monitoring of defoliation
caused by the LBM, directional waves of spread were identified that travel from the western edge
of the larch forest distribution across the European Alps at a rate of 220 km/year. Models based
on host-parasitoid interactions support this observation as long as dispersal is directionally biased
or habitat quality varies across the landscape (Bjørnstad et al. 2002).
In Fennoscandia, waves of AM and WM outbreaks were observed to spread over an approximately 10-year period beginning in the northeast in eastern Finland and the border with Russia
in 1991, and moving westward and southward to reach the islands off the coast of Norway in
2000 (Tenow et al. 2007). The most recent analysis of the geographical structure of outbreaks of
WMs and other geometrids is based on six decades of data (Tenow et al. 2012; Figure 7). In each
decade a wave of outbreaks moved across Europe from ESE-WNW toward the Scandes and the
Atlantic Ocean, approximately a 3,000-km distance, at an average speed of 330 km/year. Tenow
et al. (2012) propose that stand isolation beyond the forest steppe zone to the east creates a hostile
zone for WMs, whereas in suitable habitats to the west, within-patch outbreaks are synchronized
by short-distance dispersal and perhaps more mobile and density-delayed parasitoids.
The geographical dynamics of the spread of moths in the family Geometridae, including AMs
and WMs, was further elucidated using satellite data in the next period of outbreaks from 2000
to 2008 ( Jepsen et al. 2009). This new technology allowed monitoring of both defoliation and
temperature patterns that relate to leaf phenology. The patterns of moth spread varied across the
cycle. In the incipient phase, defoliation started at many locations and was highly synchronous.
This resulted in long spread distances of 20–80 km being common. In the epidemic and crash
phases, spread distances were much shorter (0–15 km). The satellite data also indicated large-scale
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2010
2005
2000
1995
Year of outbreak
1990
1985
1980
1975
1970
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1965
1960
1955
1950
1945
–1,000 –500
0
500
1,000 1,500 2,000 2,500 3,000
Distance from western baseline (km)
Figure 7
Regressions of the relationships of outbreak occurrences to year for the decadal spread of winter moth and
associated geometrids in northern Europe. Each colored line indicates the geographic spread of population
outbreaks across Finland, Sweden, and Norway from approximately the border with Russia and going west
to the Atlantic Ocean. Regression lines are based on data from Tenow et al. (2012). The x-axis is the distance
from the western baseline that is parallel to the Norwegian coast and the y-axis is the year of outbreak. Each
wave lasts approximately 10 years and covers a distance of approximately 3,000 km. Slopes of the lines vary
slightly, indicating differences in the speeds of the waves, and line lengths are influenced by the available data
on outbreaks.
synchronization of spring phenology of plant growth during the incipient phase of the cycle. Jepsen
et al. (2009) conclude that these patterns support a synchronizing Moran effect acting through
phenological synchronization of egg hatch and bud development at the early stages of outbreak,
followed by dispersal (diffusion) as the outbreak progresses.
A problem with satellite data is that defoliation caused by AMs is indistinguishable from that
caused by WMs, and the occurrence of waves was not recognized in this study (O. Tenow, personal
communication). Therefore, although satellite data can be useful for looking at broad patterns of
insect outbreaks, it is important to also include the details of the system.
Future direction: use of satellite data to study spatial synchrony in outbreaks. Tenow et al.
(2012) conclude that knowledge of wave patterns is necessary for understanding local outbreaks
and that isolated local or even regional studies alone cannot explain the large-scale, spatio-temporal
dynamics of outbreaks of WMs. Satellite data are now available for looking at widespread patterns
relevant to the phenological synchrony of insects and their food plants, and these should be applied
to other systems. But they also require careful ground-truthing.
Future direction: roles of dispersal of moths and parasitoids in synchronizing populations.
More information on the movement of parasitoids, the dispersal of moths, and the identification of
unique weather conditions that could periodically synchronize populations is required. Looking at
the similarity of correlations between defoliation and weather is not sufficient to identify causation.
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Climate Change and Outbreaks of Forest Lepidoptera
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Population cycles of forest Lepidoptera tend to be more apparent in northern areas and at higher
elevations. Thus it might be predicted that warming climates will disrupt population dynamics
to a greater extent in these areas. Already, tree ring data from forests inhabited by the LBM
show that warming climates could influence the distribution of insects and their host trees and
thus change the location of the epicenters of population outbreaks ( Johnson et al. 2010). Based
on tree ring data, Büntgen et al. (2009) demonstrate consistent cycles of the LBM between
1700 and 2000. They report that though the periodicity of local outbreaks continues, alpinewide defoliation no longer occurs in Switzerland. Further analysis using isotopic signatures of
tree rings showed that below average July to August temperatures were coupled with defoliation events over more than three centuries (Kress et al. 2009). Although the amplitude of LBM
population cycles in the French Alps has declined two-and-a-half to six times since 1985, population peaks have continued to occur with the typical 8–9 year periodicity (A. Roques, personal
communication).
Although not likely to be the only factor related to population outbreaks, climate, including
both temperature and rain, has the potential to influence population growth rates, food availability, disease susceptibility, and the phenological relationships between insects, their food plants,
and their natural enemies (Both et al. 2009; reviewed by Lynch 2012). Patterns are unlikely to
be simple, and the literature on the relationship of temperature to cycles of forest Lepidoptera
is contradictory. Cool temperatures and precipitation are positively associated with population
outbreaks in several studies. For example, tree ring analysis shows that outbreaks of C. occidentalis
do not occur in years of drought, whereas C. fumiferana tends to outbreak in dry springs (Lynch
2012). A breakdown in cycles of the LBM was attributed to warm springs followed by cool summers
(Baltensweiler 1993), whereas Kress et al. (2009) found that defoliation by the LBM was associated
with cool summers. This is impossible to interpret.
Myers (1998) suggested that the high number of population outbreaks that occurred over the
mid-1950s (40% of 26 species had outbreaks in 1956 and 25% in 1954) might have been associated
with cool temperatures. If this were true, warmer climates could reduce the frequency of outbreaks.
For WTC populations, temperature and rate of population growth have been negatively related
over the time period of 2000 to 2012 (r2 = 0.52; J. H. Myers and J. S. Cory, unpublished data)
though the amplitudes of outbreaks have not changed over the past four cycles.
Future direction: the role of cool summers. Cool temperatures have been associated with
population outbreaks in several studies. Mechanisms that might lead to this association should be
identified and more detailed relationships between population growth and temperature should be
measured.
Future direction: continued cycles at lower population density. A most intriguing characteristic that needs to be explained is the continued periodicity of cycles in species such as the
LBM and the AM for which amplitudes of outbreaks have declined (Figure 3a for the AM). How
density-related factors thought to drive population cycles function when populations do not reach
outbreak densities but continue to cycle is a fascinating mystery.
Climate Warming and Phenological Mismatch
One of the key impacts of climate warming on populations could be phenological mismatch
(Miller-Rushing et al. 2010). The hypothesis that changing climate could influence insect
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populations through modification of the timing of egg hatch to bud burst is most apparent in
studies of WMs (van Asch & Visser 2007). As mentioned above, widespread synchronization of
the onset of the growing season and leafing of birch was apparently related to outbreaks of AMs
and WMs ( Jepsen et al. 2009). This could have acted through synchronization of egg hatch and
budburst.
In several cases the impact of mismatch between egg hatch and bud burst has been tested experimentally. Baltensweiler (1993) modified the hatch of LBM eggs through shading. Delayed hatch
in a warm spring synchronized the larvae beneficially with bud burst, whereas early hatch was detrimental. For GMs, delayed egg hatch was advantageous overall because even though food quality
was poor for late-hatching larvae, this reduced their density and they experienced lower attack
from a parasitoid that responded to host density (Hunter & Elkinton 2000). Delayed egg hatch had
no apparent influence on larval development of the WTC (Myers 1992). In a unique branch-level
warming experiment with the WTC (H. Kharouba, M. Vellend, R. M. Sarfraz, and J. H. Myers,
submitted), larvae that hatched two to three weeks before bud burst did not have reduced larval
growth, development, or survival. This agrees with Singer & Parmesan (2010), who point out that
species might not have evolved close phenological synchrony with bud burst but rather maintain
flexibility to respond to temporal variability in weather conditions. Thus, they maintain the potential to adapt to changing environments. The level of adaptation is likely to vary among species and
environments.
Future direction: temperature influences on plant and insect phenology. Determining
how temperature influences the relationships between bud burst and egg hatch and how this
affects the survival rates of life-history stages will be critical to the prediction of responses of
populations to climate change. Some species may be much more resilient to mismatch than
others and this could relate to whether they develop to larvae in the eggs before or after
diapause.
Future direction: heterogeneity in phenological relationships across species ranges. Variability in weather patterns across a species’ range might influence selection on budburst and egg
hatch phenology. Further experimental work should be done to determine whether generalizations
can be made about the importance of phenological mismatch to cyclic dynamics among sites and
species.
CONCLUSIONS
In Table 1 we summarize information on seven species of cyclic forest Lepidoptera and list some
questions that arise for future work. Even with all of the work that has gone on in the past 25 years
on cycling forest Lepidoptera, it is still a mystery as to how such a regular pattern of population
dynamics can be maintained for so long, how consistent waves of spread can persist for some species
but not others, and how populations can continue to cycle at low densities in phase with outbreak
populations. The biggest black box that remains is the extent of dispersal among populations, and
the relation of this to traveling waves should be a major focus in the future. Just how warming
climates will change population dynamics and distributions is still uncertain, and it is important
to differentiate between projections and observations in this regard. Some clear generalities exist
as cyclic species are similar in their population trends, relationships with parasitoids, and changes
in fecundity over the cycle.
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586
Northern Europe:
Fennoscandia.
Outbreaks do not
occur in southern
Finland
Europe:
Fennoscandia and
Holarctic
European Alps
Autumnal
moth (AM)
Winter moth
Larch
budmoth
Range
Myers
·
Cycle
Cory
9–10 years
9–10 years
9–10 years
length
Declining
amplitude of
peaks
Continuing
traveling waves
of outbreaks
Decreasing peak
densities with
poor recovery of
mountain birch
after defoliation
Current status
Traveling
waves
Traveling
waves
Traveling
waves
trends
Population
Relevant factors
Changes in food
quality and
parasitism
associated with
declines
Often lag behind
outbreaks in AM
Outbreaks less
high at coast
High pupal
predation
High parasitism
and decreasing
size at peak
Defoliation in
some areas at
higher elevations
and lower
densities at
coastal sites
Unanswered questions
(Continued )
What is the influence of warm
summers on population
success as current suggestions
are conflicting?
Are population epicenters
changing with warming
climates?
How does dispersal relate to
traveling waves?
What allows continued high
density following AM
outbreaks?
Does infection by CPV or
NPV play a role at peak
density?
What factors cause continued
cycles in areas without
defoliation?
How much and what is the
form of dispersal required to
synchronize populations and
cause traveling waves?
Does infection by a cypovirus
(CPV) or
nucleopolyhedrovirus (NPV)
play a role at peak density?
What factors cause continued
cycles in areas without
defoliation?
28 October 2013
Subalpine
larch and
Cembran
pine
Birch and
oak
Primarily
mountain
birch
Host plants
ARI
Species
Table 1 Summary of characteristics of seven cyclic species of forest Lepidoptera, factors thought to be relevant to their cyclic dynamics, and unanswered
questions for future research
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Northeastern North
America
Eastern
spruce
budworm
Spruce-fir
forests
Primarily
trembling
aspen trees,
pure and
mixed
stands
Red alder,
apple,
cherry,
rose,
currant
30–40 years
∼10 years,
varies
6–11 years
Harmonic
oscillations
of 4–5 and
8–10 years
with
periods of
noncyclic
dynamics
No apparent
change
Cyclic dynamics
unchanged
Cyclic dynamics
unchanged
Decreasing peak
amplitudes with
subharmonics in
defoliation data
Greater
defoliation in
eastern areas
with decline
to west (New
Brunswick to
western
Ontario)
Geographical
variation in
synchrony in
Ontario and
Quebec;
duration of
peak related
to fragmentation
Island
populations
remain
synchronous
Spreading
distribution
Deteriorating
forest condition,
reduced survival
of early instar
larvae, and
delayed impact of
natural enemies
cause decline and
slow recovery
Parasitism and
viral infection
cause decline and
generalist
predators have a
role at low
densities
Reduced
fecundity, viral
infection, and
parasitism change
with density
Parasitoids,
fungus, and
control
procedures
reduce
population levels
Density-related
infection causes
declines
Will warming climates
influence areas of defoliation?
Does variation in predation
influence the rate of increase
of FTC between mixed and
pure forest stands of aspen?
What is the role of dispersal in
maintaining synchrony?
What reduces fecundity over
late increase and into
population decline?
How is virus maintained at low
host density?
What is the role of viral
infection in populations with
low amplitude peaks and at
the front of the spread in
distribution?
What is the relation of
defoliation to moth
population dynamics?
Why is the amplitude of peaks
of defoliation and duration of
outbreak declining?
28 October 2013
Primarily across
northern North
America
Primarily coastal
North America
Western tent
caterpillar
Primarily
oaks but
highly
polyphagous
ARI
Forest tent
caterpillar
(FTC)
Introduced to North
America
Gypsy moth
Table 1 (Continued )
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DISCLOSURE STATEMENT
The authors are not aware of any affiliations, memberships, funding, or financial holdings that
might be perceived as affecting the objectivity of this review.
ACKNOWLEDGMENTS
Annu. Rev. Ecol. Evol. Syst. 2013.44:565-592. Downloaded from www.annualreviews.org
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We dedicate this review to the memory of Werner Baltensweiler. We acknowledge the incredible
work that has been done over the years by Olle Tenow, Erkki Haukioja, and Tero Klemola and
colleagues that has contributed so much to our understanding of population cycles. We thank
Tero Klemola, Charles Krebs, Olle Tenow, Greg Dwyer, Bruce Kendall, Laurent Dormont, Alain
Roques, Jens Roland, and Helena Bylund for providing data, helpful comments on the manuscript,
and/or answering our questions. Isla Myers-Smith has taken after her father in her ability to wield
the red pen and helped greatly. Charles Krebs and Dennis Chitty were mentors to J.H.M. and
have provided many useful discussions over the years. Finally we greatly appreciate the students
who have contributed to our work on tent caterpillars. Together we have reared more caterpillars
than we like to remember. NSERC Canada provided funding for our own work that is presented
here.
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Contents
Annual Review of
Ecology, Evolution,
and Systematics
Volume 44, 2013
Annu. Rev. Ecol. Evol. Syst. 2013.44:565-592. Downloaded from www.annualreviews.org
by Lomonosov Moscow State University on 11/28/13. For personal use only.
Genomics in Ecology, Evolution, and Systematics Theme
Introduction to Theme “Genomics in Ecology, Evolution, and Systematics”
H. Bradley Shaffer and Michael D. Purugganan p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 1
Genotype-by-Environment Interaction and Plasticity: Exploring Genomic
Responses of Plants to the Abiotic Environment
David L. Des Marais, Kyle M. Hernandez, and Thomas E. Juenger p p p p p p p p p p p p p p p p p p p p p p 5
Patterns of Selection in Plant Genomes
Josh Hough, Robert J. Williamson, and Stephen I. Wright p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p31
Genomics and the Evolution of Phenotypic Traits
Gregory A. Wray p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p51
Geographic Mode of Speciation and Genomic Divergence
Jeffrey L. Feder, Samuel M. Flaxman, Scott P. Egan, Aaron A. Comeault,
and Patrik Nosil p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p73
High-Throughput Genomic Data in Systematics and Phylogenetics
Emily Moriarty Lemmon and Alan R. Lemmon p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p99
Population Genomics of Human Adaptation
Joseph Lachance and Sarah A. Tishkoff p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 123
Topical Reviews
Symbiogenesis: Mechanisms, Evolutionary Consequences,
and Systematic Implications
Thomas Cavalier-Smith p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 145
Cognitive Ecology of Food Hoarding: The Evolution of Spatial Memory
and the Hippocampus
Vladimir V. Pravosudov and Timothy C. Roth II p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 173
Genetic Draft, Selective Interference, and Population Genetics
of Rapid Adaptation
Richard A. Neher p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 195
Nothing in Genetics Makes Sense Except in Light of Genomic Conflict
William R. Rice p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 217
v
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The Evolutionary Genomics of Birds
Hans Ellegren p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 239
Community and Ecosystem Responses to Elevational Gradients:
Processes, Mechanisms, and Insights for Global Change
Maja K. Sundqvist, Nathan J. Sanders, and David A. Wardle p p p p p p p p p p p p p p p p p p p p p p p p p 261
Cytonuclear Genomic Interactions and Hybrid Breakdown
Ronald S. Burton, Ricardo J. Pereira, and Felipe S. Barreto p p p p p p p p p p p p p p p p p p p p p p p p p p p p 281
Annu. Rev. Ecol. Evol. Syst. 2013.44:565-592. Downloaded from www.annualreviews.org
by Lomonosov Moscow State University on 11/28/13. For personal use only.
How Was the Australian Flora Assembled Over the Last 65 Million Years?
A Molecular Phylogenetic Perspective
Michael D. Crisp and Lyn G. Cook p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 303
Introgression of Crop Alleles into Wild or Weedy Populations
Norman C. Ellstrand, Patrick Meirmans, Jun Rong, Detlef Bartsch, Atiyo Ghosh,
Tom J. de Jong, Patsy Haccou, Bao-Rong Lu, Allison A. Snow, C. Neal Stewart Jr.,
Jared L. Strasburg, Peter H. van Tienderen, Klaas Vrieling,
and Danny Hooftman p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 325
Plant Facilitation and Phylogenetics
Alfonso Valiente-Banuet and Miguel Verdú p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 347
Assisted Gene Flow to Facilitate Local Adaptation to Climate Change
Sally N. Aitken and Michael C. Whitlock p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 367
Ecological and Evolutionary Misadventures of Spartina
Donald R. Strong and Debra R. Ayres p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 389
Evolutionary Processes of Diversification in a Model Island Archipelago
Rafe M. Brown, Cameron D. Siler, Carl H. Oliveros, Jacob A. Esselstyn, Arvin C. Diesmos,
Peter A. Hosner, Charles W. Linkem, Anthony J. Barley, Jamie R. Oaks,
Marites B. Sanguila, Luke J. Welton, David C. Blackburn, Robert G. Moyle,
A. Townsend Peterson, and Angel C. Alcala p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 411
Perceptual Biases and Mate Choice
Michael J. Ryan and Molly E. Cummings p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 437
Thermal Ecology, Environments, Communities, and Global Change:
Energy Intake and Expenditure in Endotherms
Noga Kronfeld-Schor and Tamar Dayan p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 461
Diversity-Dependence, Ecological Speciation, and the Role of Competition
in Macroevolution
Daniel L. Rabosky p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 481
Consumer Fronts, Global Change, and Runaway Collapse in Ecosystems
Brian R. Silliman, Michael W. McCoy, Christine Angelini, Robert D. Holt,
John N. Griffin, and Johan van de Koppel p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 503
vi
Contents
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12:6
Implications of Time-Averaged Death Assemblages for Ecology
and Conservation Biology
Susan M. Kidwell and Adam Tomasovych p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 539
Population Cycles in Forest Lepidoptera Revisited
Judith H. Myers and Jenny S. Cory p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 565
Annu. Rev. Ecol. Evol. Syst. 2013.44:565-592. Downloaded from www.annualreviews.org
by Lomonosov Moscow State University on 11/28/13. For personal use only.
The Structure, Distribution, and Biomass of the World’s Forests
Yude Pan, Richard A. Birdsey, Oliver L. Phillips, and Robert B. Jackson p p p p p p p p p p p p p p p 593
The Epidemiology and Evolution of Symbionts
with Mixed-Mode Transmission
Dieter Ebert p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 623
Indexes
Cumulative Index of Contributing Authors, Volumes 40–44 p p p p p p p p p p p p p p p p p p p p p p p p p p p 645
Cumulative Index of Article Titles, Volumes 40–44 p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 649
Errata
An online log of corrections to Annual Review of Ecology, Evolution, and Systematics
articles may be found at http://ecolsys.annualreviews.org/errata.shtml
Contents
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