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Oikos 123: 257–266, 2014
doi: 10.1111/j.1600-0706.2013.01093.x
© 2013 The Author. Oikos © 2013 Nordic Society Oikos
Subject Editor: Dries Bonte. Accepted 8 September 2013
oice
Ecological and evolutionary responses in complex communities:
implications for invasions and eco-evolutionary feedbacks
Sharon Y. Strauss
S. Y. Strauss ([email protected]), Dept of Evolution and Ecology, University of California at Davis, Davis, CA 95616, USA.
Synthesis
It is easier to predict the ecological and evolutionary outcomes of interactions in less diverse communities. As species are
added to communities, their direct and indirect interactions multiply, their niches may shift, and there may be increased
ecological redundancy. Accompanying this complexity in ecological interactions, is also complexity in selection and
subsequent evolution, which may feed back to affect the ecology of the system, as species with different traits may
play different ecological roles. Drawing from my own work and that of many others, I first discuss what we currently
understand about ecology and evolution in light of simple and diverse communities, and suggest the importance of
escape from community complexity per se in the success of invaders. Then, I examine how community complexity
may influence the nature and magnitude of eco-evolutionary feedbacks, classifying eco-evolutionary dynamics into
three general types: those generating alternative stable states, cyclic dynamics, and those maintaining ecological stasis
and stability. The latter may be important and yet very hard to detect. I suggest future directions, as well as discuss
methodological approaches and their potential pitfalls, in assessing the importance and longevity of eco-evolutionary
feedbacks in complex communities.
The ecology, evolution and eco-evolutionary dynamics of simple and diverse communities are reviewed. In
more diverse communities, direct and indirect interactions multiply, species’ niches often shift, ecological redundancy can increase, and selection may be less directional. Community complexity may influence the magnitude and nature of eco-evolutionary dynamics, which are classified into three types: those generating alternative
stable states, cyclic dynamics, and those maintaining ecological stasis and stability. Strengths and pitfalls of
approaches to investigating eco-evolutionary feedbacks in complex field communities are discussed.
As species are added to communities, their direct and indirect
interactions multiply, their niches may shift, and there may be
increased ecological redundancy (Polis and Strong 1996, Finke
and Denno 2004, Edwards et al. 2010, Estes et al. 2013).
Accompanying this complexity in ecological interactions, is also
complexity in selection and subsequent evolution (Antonovics
1992, Miller and Travis 1996, Iwao and Rausher 1997, Inouye
and Stinchcombe 2001, Walsh 2013), which may feed back to
affect the ecology of the system, as species with different traits
may play different ecological roles. My work has focused on
the importance of community complexity in influencing ecological interactions, ensuing natural selection, evolution, and
eco-evolutionary feedbacks. Here, I review what we have learned
about the role of community complexity in natural communities and apply these findings to current challenges in invasion
biology and to the study of eco-evolutionary dynamics.
Simple systems are easier to predict ecologically
We are generally pretty good at predicting ecological outcomes
in simple communities, such as microcosms. Predator–prey
cyclic dynamics in microcosms often precisely match the
length of time lags, duration of cycles and amplitudes predicted by theory (Gause 1935, Hiltunen et al. 2013). We can
also generate trophic cascades in microcosms (Coll and Hargadon 2012). Though deterministic processes are at the heart
of ecological interactions, increasing community complexity
can lead to non-additive, complex interactions among species that make outcomes harder to predict (Strauss 1991,
Miller and Travis 1996, Estes et al. 2013). Some of the best
examples of this phenomenon are found in the alreadysimplified communities of agroecosystems and pest biocontrol efforts. Adding multiple enemy species to control
pests frequently does not result in additive effects on pest
control (Snyder and Ives 2003, Finke and Denno 2004).
Interactive effects of multiple enemies species through
altered behavior, such as the ecology of fear (Ripple and
Beschta 2004), or omnivory (Polis and Strong 1996) can
cause multiple predators or parasites to facilitate or impede
one another (Ferguson and Stiling 1996, Snyder and Ives
2003, Schneider and Brose 2013). Multiple predator effects
can have similar, non-additive impacts in natural trophic
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cascades. The relationship between strength of the ecological cascade and community complexity/trophic reticulation
has long been suggested (Polis and Strong 1996, Edwards
et al. 2010), though not always supported (Borer et al.
2005, Kurle and Cardinale 2011). In general, the outcomes
of interactions of many species are much harder to predict
than those involving a few.
Simpler systems are also easier to predict evolutionarily
Through artificial selection and in laboratory studies, we can
often cause large evolutionary changes in response to a single
strong selective force. As examples, we can increase resistance to parasitoids in fruit flies (Fellowes et al. 1998), we
can decrease Drosophila lifespan (Stearns et al. 2000); we can
select for salt and other stress tolerance in plants (Stanton
et al. 2000), and for plasticity in different escape behaviors
and morphologies in tadpoles (Van Buskirk and Relyea
1998). For many ecologically important traits, there appears
to be ample existing genetic variation that allows organisms
to respond to selection (Carroll et al. 1998). Moving outside
the lab, in simplified agroecosystems, we have predictably
caused the evolution of pesticide resistance in more than
7700 species of pests to a diversity of pesticides (Whalon
et al. 2008). We have also caused the evolution of mimicry
of crop seeds and leaves by weed pests (Barrett 1983).
Less diverse natural systems also are somewhat more predictable evolutionarily.
Islands and island-like habitats often exhibit predictable
ecological and evolutionary responses
Habitats naturally low in species diversity, like islands, offer
us insights into selection, evolution and eco-evolutionary
dynamics. In Sweden, young, recently uplifted islands are
initially colonized by meadowsweet plants; meadowsweet on
young islands consistently has low resistance to herbivorous
galerucine leaf beetles (Stenberg et al. 2006). As islands
become older, leaf beetles colonize and select for increased
resistance in meadowsweet. Resistant meadowsweet then
slows growth rates and reproduction in beetles. These patterns are consistently found, as indicated by an age gradient
in resistance traits, and performance of beetles on meadowsweet hostplants of islands of different ages (Stenberg et al.
2006). Increased resistance in meadowsweet also causes an
eco-evolutionary feedback when beetles shift to using an
alternative host plant, Rubus, on older islands where
meadowsweet is more resistant and a less suitable host
(Stenberg et al. 2008). In other island examples, when deer
are introduced to previously herbivore-free islands, we find
an ecological impact in which more palatable species or
genotypes are the first to suffer great declines, and an evolutionary response favoring more resistant genotypes of
surviving vegetation (Vourc’h et al. 2001). When the
Galapagos finch Geospiza magnirostris colonized Daphne
island, resident finch Geospiza fortis exhibited a large
evolutionary response in beak size as a result of resource
competition (Grant and Grant 2006, but see Grant and
Grant 2002).
Similarly, in island-like mountain tops, traits of conifer
cones reflect the identity of the major seed predator(s) in
these small communities. Cone shape and crossbill beak
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shape coevolve in response to crossbill predation on cones,
when crossbills are the sole predators (Benkman et al. 2010,
2013). In areas where squirrels are present, cone morphology
is under strong divergent selection with respect to traits
favored by selection from birds. In general, cone shape is
more variable where interactors exerting conflicting selection
are present (Siepielski and Benkman 2010), a result that
supports the idea that that community complexity results
in more conflicting and variable selection, and no single
‘solution’. The evolution of cone shape is repeatable across
mountain ranges with differing communities of seed predators, as well as across different conifer/crossbill/squirrel systems comprising different species (Leslie 2011, Benkman
et al. 2013). While not completely straightforward, evolution in simpler island or island-like communities is often
predictable.
Evolution in complex communities is hard to predict
Community complexity may impose greater conflicting
selection on traits, maintaining variability in traits and
reducing coevolution between any pair of species (Thompson
1986, 1999). Diffuse coevolution in diverse communities
occurs when selection on traits in one species owing to
interactions with a second species also depends on the presence or absence of other community members; in addition
diffuse selection can occur when trait correlations change in
the presence of a third species (Miller and Travis 1996, Iwao
and Rausher 1997, Inouye and Stinchcombe 2001, Strauss
and Irwin 2004, Strauss et al. 2005, Haloin and Strauss
2008). A related concept is that of indirect selection, in
which trait values favored in one interaction are correlated
with changes in traits affecting other interactions. Community complexity can thus affect evolutionary responses of
component species and make them hard to predict (Inouye
and Stinchcombe 2001, Haloin and Strauss 2008, Siepielski
et al. 2009, Estes et al. 2013, Walsh 2013).
Studies of selection in natural field communities typically find conflicting selection on traits (Siepielski et al.
2009). Focusing on plant examples, herbivores and pollinators exert opposing selective effects on plant flowering
displays (Ehrlén et al. 2002, Adler and Bronstein 2004,
Cariveau et al. 2004, Gomez 2008) or secondary chemistry (Irwin et al. 2003, Kessler et al. 2010), specialist and generalist herbivores exert opposing selection on plant
secondary chemistry and, competitors and herbivores exert
opposing selection on plant resistance/competition traits
(Agrawal et al. 2013a, Bossdorf 2013, Uesugi and Kessler
2013, Oduor et al. 2013). There is also evidence for indirect selection. A recent field study measuring natural selection for resistance to a diverse community of herbivores of
Solanum carolinense found significant genetic variation for
14 resistance traits and significant genetic covariances in
one-third of the pairwise combinations of these traits.
Genetic covariance constrained the evolution of plant
resistance to any one interactor (Wise and Rausher 2013).
Thus, conflicting selection owing to community complexity and/or trait covariances may constrain evolutionary
responses of component species and adaptation to any
single interactor (see also Thompson 1994, Siepielski and
Benkman 2010).
Introduced species: successful through escape from
complexity?
The success of many introduced species has been attributed
to escape from enemies (Enemy release hypothesis – Keane
and Crawley 2002) as well as to escape from the costs of
defense (Evolution of increased competitive ability EICA –
Blossey and Notzold 1995). The Shifting defense hypothesis
suggests that a crucial part of enemy escape is from specialist
enemies (Muller-Scharer et al. 2004). Here, I suggest that an
element of release in the novel range may specifically hinge
on introduced species’ escape from community complexity
and the ability to adapt to directional selection from fewer
fitness-impacting species. The exotic Lepidium draba is
attacked by over 164 insect herbivores in its native range – in
its introduced range in North America, it has only eight
recorded herbivores – and proportionally fewer seed-feeding
herbivores (Cripps et al. 2006). Native species are typically
caught between the rock and hard place of multiple enemy
species and mutualists, and constraints that prevent an overall ‘solution’ to interactions with fitness-affecting species.
For example, silencing the MPK4 gene in wild tobacco,
Nicotiana attenuata increases resistance to specialist
tobacco hornworm Manduca sexta but not to generalist
Spodoptera littoralis (Hettenhausen et al. 2013). Many studies show tradeoffs between resistance to, or selection from,
specialists and generalist herbivores (Mithen et al. 1995,
Lankau and Strauss 2008, Alba et al. 2012). If different compounds and mechanisms of resistance are required for different enemy species (Mithen et al. 1995, Alba et al. 2012,
Hettenhausen et al. 2013), escape from complexity and concomitant release from the costs of defense against multiple
species, may be a critical, evolutionary aspect of enemy
release.
There is some evidence that the simpler communities
experienced by exotic species may allow them to adapt to a
small number of antagonists (Berenbaum and Zangerl 2006),
potentially allowing an increase in overall fitness that may
aid their invasion (Schutzenhofer et al. 2009). In the parsnip/parsnip webworm model system of coevolution, the
detoxification abilities of webworms of different furanocoumarin compounds closely matched the relative abundance
profiles of four different furanocoumarins in 8/11 parsnip
populations in the exotic range. In contrast, in the Old
World where these species are native, only 3/20 populations
exhibited such matching, and lack of matching was attributed to the selection from of other species in the communities in both ranges (Zangerl and Berenbaum 2003,
Berenbaum and Zangerl 2006). Similarly, in experimental
microcosms, pairwise coevolution between Pseudomonas
fluorescens bacteria and a bacteriavirus is disrupted by the
introduction of a protist bacterial predator. When both
predator and bacterovirus are present, P. fluorescens diversifies into defense specialists, reflecting tradeoffs between
defenses against the two enemies (Friman and Buckling
2013; see also Thompson 1994). Thus, multiple enemies
may constrain the evolution of resistance to any one enemy,
and may come at substantive cost.
It may, therefore, be more important that exotic species
escape complexity, rather than specific types of enemies,
in novel habitats. Counter to expectation of release from
enemies and EICA, many introduced species increase
their investment in secondary compounds post-invasion
(Zangerl and Berenbaum 2005, Oduor et al. 2011). Such
increased investment in defense could be predicted to come
at a cost to growth rate (Lind et al. 2013), and in principle,
should reduce, rather than enhance, competitive ability.
However, increased investment in compounds might be less
costly than maintaining multiple different adaptations to
numerous enemies that require different defenses. While
many studies find that costs of defenses against multiple
enemies are not additive, the growth rate/fitness of multiply
resistant genotypes is typically lower than that of genotypes
resistant to only one enemy (Bohannan et al. 1999, Koskella
et al. 2012). Thus, escape from complexity, and the ability to
respond to directional selection from a few interactors, may
be the key to success of exotic species.
Community complexity and eco-evolutionary
feedbacks
Eco-evolutionary feedbacks occur when ecological factors
exert selection on organisms, cause trait changes in one or
more species, and these changes, in turn, alter ecological
properties of the system (Kinnison and Hairston 2007).
Repeat cycle. Eco-evolutionary feedbacks may heuristically
be categorized as fitting into three general categories.
First, shifts in phenotypes of ecologically important species,
often as a result of novel selection, may result in alternative
stable states of ecological communities (Bassar et al. 2010,
Walsh et al. 2012). Second, cyclic ecological and evolutionary
dynamics may occur, if evolution is a result of density- or
frequency-dependent selection, and if different phenotypes
within species have different ecological and evolutionary
impacts (Chitty 1960, Pimentel 1961, Lankau and Strauss
2007, Yoshida et al. 2007, Turcotte et al. 2011). Third, an
underappreciated and cryptic role of eco-evolutionary feedbacks may be their contribution to the stability of ecosystems.
This stability could arise from stable cyclic dynamics (Yoshida
et al. 2007), or through interactions between different
genotypes of interacting species (G ⫻ G heterospecific
interactions; Vellend 2005) that buffer the system from
change, and contribute to ecosystem function. Our biggest
challenge remains to understand how often and when ecoevolutionary dynamics could be expected to have large,
long-lasting impacts in complex field ecosystems (Fussmann
et al. 2007, Schoener 2011).
1) Eco-evolutionary feedbacks and alternative stable states
Alternative stable states can arise from eco-evolutionary
dynamics in field communities, and are often in response to
a strongly altered selective regime. Alewives are fish that
migrate from the sea to freshwater lakes. When lakes are
dammed, and are stocked or naturally contain alewives, the
largest classes of zooplankton are rapidly driven extinct
(Brooks and Dodson 1965) and alewife populations diverge
from their usual anadromous, migratory form in response to
prey depletion (Post et al. 2008). Landlocked alewives exhibit
slower growth, earlier age and smaller size at maturity compared to migratory fish. Lakes with landlocked alewives, in
turn, have small-bodied zooplankton and zooplankton
Daphnia ambigua adapts to differences in predation pressure
259
in landlocked versus open lakes. Daphnia from lakes
with migratory alewife grow faster, mature earlier and produce larger clutches than Daphnia from either no alewife or
landlocked lakes (Walsh and Post 2011). Evolutionary
changes in zooplankton ramify to phytoplankton communities; thus, evolutionary shifts in alewives and zooplankton,
along with ecological changes, contribute to lakes with
different ecological stable states (Walsh and Post 2011).
Similar kinds of stable state differences may be found in
predator-rich and predator-free Trinidadian stream reaches
through the evolution of prey guppy populations, as documented using mesocosms stocked with different guppy genotypes (Palkovacs et al. 2009, Bassar et al. 2010). Differences
in the ecology of these communities are likely to cause further evolutionary change in component species, contributing to a system of eco-evolutionary feedbacks generating
alternative stable states.
2) Eco-evolutionary feedbacks and cyclic genetic and
ecological properties
Ecosystem consequences may arise from adaptation to density- and frequency-dependent selection in key species.
Chitty (1960) and Pimentel (1961) both proposed that
adaptive phenotypes within species are likely to vary under
high and low conspecific densities (reviewed by Lankau
and Strauss 2011; see also Abrams and Matsuda 1997,
Becks et al. 2012, Travis et al. 2013). Traits of species
favored at different densities may, in turn, alter ecosystem
properties. Lankau and Strauss (2007) examined evolution
of exotic Brassica nigra populations and the trait sinigrin, a
secondary compound that has allelopathic properties and
impacts on herbivores. In experimental field plots planted
with B. nigra genotypes that varied in sinigrin content,
high singirin genotypes excelled in heterospecific competition by inhibiting soil fungal mutualists of heterospecific
competitors (Lankau et al. 2011). In plots with only conspecific competition, however, low sinigrin B. nigra genotypes were favored over high sinigrin genotypes, presumably
because they did not incur the costs of sinigrin production.
In plots with heterospecifics, heterospecifics outcompeted
low, but not high sinigrin, B. nigra genotypes, completing
a cycle of intransitive competitive dynamics between genotypes of B. nigra and species composition (con- or heterospecifics). Community-driven frequency/density-dependent selection
on sinigrin maintained genetic variation in this trait, and trait
variation maintained species diversity in the community
(Lankau and Strauss 2007). When selection on singirin was
measured across non-experimental plant communities in the
field that varied in conspecific densities, the direction of selection on sinigrin supported experimental field plot results
(Lankau and Strauss 2007). Similar cyclic dynamics between
genotypes and heterospecific interactions have been shown in
microcosms, where algal genotypes resistant to rotifer predators
survive predation, but lose in competition with undefended
genotypes, which then increase when predators are rare(Yoshida
et al. 2007, Becks et al. 2012). Predators may also evolve
during these cycles. Tradeoffs between heterospecific and conspecific competitive abilities are being more frequently documented (B. Schmid pers. comm.) and may contribute to
ongoing eco-evolutionary dynamics that maintain long-term
stability in communities.
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3) Cryptic eco-evolutionary feedbacks contribute to
ecosystem stability, not change
Community diversity may constrain or promote the evolution of component species (Vellend and Geber 2005,
de Mazancourt 2008, Urban et al. 2008), and both processes
can result in more globally stable ecosystems, stability
that obscures the underlying important eco-evolutionary
dynamics that contribute to it.
Resident community diversity can constrain the evolution of component species. Using phylogenetic reconstruction, (Rabosky and Glor 2010) reconstructed the effects of
lizard community diversity on diversification rates of species co-occupying islands. Diverse communities reduced
diversification rates of resident species, suggesting that
community complexity reduces the opportunities for evolutionary diversification within species. de Mazancourt
(2008) found a similar result using a modeling approach:
when a new niche/resource becomes available in a community, species in the community with the existing niche
closest to taking advantage of the new resource may exhibit
a small shift to occupy that niche space, and thus prevent
other species from using it. In contrast, when the community comprises just a single species with genetic variation,
that species may ‘radiate’ to occupy the new niche. This
phenomenon has also been found in lab microcosm model
systems. Experimental evolution of P. fluorescens bacteria
showed that the presence of a natural diverse soil community prevented diversification of the focal species from
occupying different niches, a diversification that occurred
when P. fluorescens was grown alone (Gomez and Buckling
2013). Grown alone, P. fluorescens differentiates into two
distinct types (wrinkly spreader and smooth), each with
different competitive abilities. Similarly, Fukami et al.
(2007) showed that a bacterium radiated to use alternative
resources in a microcosm when alone, but had its niche
contracted with the introduction of niche specialists that
use resources better. Such effects of community complexity may underlie why more species-rich communities are
more resilient to change and to perturbation, and may also
buffer component species from large evolutionary changes;
in this case, eco-evolutionary feedbacks occur, but result
in relative stasis of traits, rather than change, and may be
very important in ecosystem function.
An alternative mechanism with a similar ecological outcome of stasis may occur if species diversity within communities increases, rather than constrains, the genetic diversity
within component species (Vellend and Geber 2005, Vellend
2008, Bailey et al. 2013). If genotypes within species
play different ecological roles, then genotype ⫻ genotype
interactions across species, or genotype ⫻ species interactions
can maintain both genetic diversity and species diversity
(Vellend 2006, Fridley et al. 2007, Lankau and Strauss 2007,
Becks et al. 2012). These micro-scale eco-evolutionary
dynamics may combine to create ecosystems that are resilient
to change by virtue of a plethora of G ⫻ G ⫻ E interactions.
Recent experiments suggest that there are many genotypespecific ecological outcomes of interacting species that may
influence ecosystem properties and eco-evolutionary feedbacks. Palkovacs et al. (2009) showed that depletion of
aquatic invertebrate densities in mesocosm ecosystems was
more complete when sympatric, potentially coevolved, pop-
ulations of guppies Poecilia reticulata and killifish Rivulus
hartii were placed together than when populations of the
same species, but with no history of sympatry, were grown
together. Similarly, in experimentally assembled communities
of microbes, species differed in their resource use when they
evolved with others than when they were grown in monoculture; moreover, communities re-assembled from isolates that
had evolved within communities were more productive than
communities reassembled from isolates that had evolved
alone (Lawrence et al. 2012). When genetic change was
observed within these microbial populations, populations
grown in communities evolved many-fold more quickly than
populations grown alone, and adapted to fill different niches
(Lawrence et al. 2012). These results suggest that coevolution
of populations within communities may contribute to overall
ecosystem function. In a different kind of genotype ⫻ genotype interaction, in field experiments where mixtures of genotypes of grasses and sedges were grown together, genotypes of
the dominant grass varied in their growth based on the genotype of their sedge neighbor, with different genotypes of
grasses thriving with different genotypes of sedges, and vice
versa (Fridley et al. 2007). The identity of the genotype pairings with best performance also varied with soil environment,
a G ⫻ G ⫻ E interaction (Fridley and Grime 2010; see also
Aarssen and Turkington 1985a, Lau and Lennon 2012).
Together, these results suggest that species diversity and
genotypic diversity interact, and that individual fitness, as well
as community function, may be determined by local multispecies, multi-genotype interactions (Vellend 2006, Lau and
Lennon 2012). Hypotheses on the evolution of group functionality have been proposed in the past, and deserve more
attention. D. S. Wilson wrote “When many local communities
exist that vary in their species and genetic composition, those
that function well contribute differentially to the next generation of local communities.” (Wilson 1997, see also Wilson
1976). Evaluation of the importance of group or multi-level
selection requires experimental work in the field, and may be a
cryptic aspect of eco-evolutionary feedbacks contributing to
overall ecosystem function (see also Travis et al. 2013).
Future directions in community complexity and
eco-evolutionary feedbacks: when are they
important and long-lasting?
Most studies showing eco-evolutionary dynamics have, in
fact, been from systems simplified at some level – micro- or
mesocosms (Bassar et al. 2010, Becks et al. 2012, Gomez
and Buckling 2013), communities considering just a few
native species (Reznick and Ghalambor 2001, Agrawal et al.
2013a, b), or introduced species with simplified associations
(Lankau and Strauss 2007, Turcotte et al. 2011). Our challenge is to understand the extent to which eco-evolutionary
dynamics are important in complex systems with lots
of interactions (Fussmann et al. 2007, Schoener 2011).
Novel strong selection can cut the Gordian knot of
community complexity, and expose/cause eco-evolutionary
change
When novel selective pressures arise in complex field
communities, almost always as a result of human actions
(either direct ones like harvesting, or indirect ones caused
by introduced species, habitat loss or climate change
(Palumbi 2001), this directional selection often overrides
current selection on traits from complex communities and
environments, and can be expected to have strong ecoevolutionary feedbacks. For example, eco-evolutionary
feedbacks in a complex field community have been documented in lakes when they are dammed and when dams
prevent migration of a high impact alewife predator (Walsh
et al. 2012). In a meta-analysis, phenotypic change owing
to anthropogenic sources of selection was 1.7 times greater
than change measured in natural contexts (measured in
Haldanes and standardized by generation time; Darimont
et al. 2009). These shifts include plastic changes in
phenotypes, but as plasticity is often also under selection
(Franssen 2011) and both plastic and nonplastic responses
may be responding evolutionarily to strong novel selection.
Human-caused selection has yielded thousands of cases
of pesticide (Whalon et al. 2008) and antibiotic resistance,
big-horn sheep with small horns (Coltman et al. 2003),
and smaller fish in fisheries (Johnson et al. 2011); its impact
lies in its unwavering directionality, as well as its magnitude. Generally, we have not separated the ecological
impacts of adaptation to such novel and strong selection
from the ecological impact of the selective force (methods
in Ellner et al. 2011). For example, overharvesting large
fish has an ecological impact of reducing the density of
large fish. It also has an evolutionary impact on fish populations by selecting for earlier maturation at smaller size.
Thus, adaptation to selective harvest of large fish may have
the same ecological impact as removing large fish, and
could be indistinguishable from ecological effects of harvesting. The evolutionary impact would only be visible
when harvesting of large fish stops, but small fish, and the
ecological effects of small fish, persist for multiple generations (Johnson et al. 2011).
Adaptation may not always result in phenotypes that
work in concert with ecological impact of the selective
force, as in the previous example. In Australia, adaptation to toxic prey allows population rebound from the
ecological effects of ‘consumption’ (poisoning) by toads
(Shine 2010). Predators have adapted to introduced toxic
cane toad prey through prey aversion and evolution of
smaller mouths (Phillips and Shine 2006, Llewelyn et al.
2012); these evolutionary changes have allowed recovery
of predator populations that declined numerically (ecologically) with initial cane toad invasion (Shine 2010).
How these trait changes in survivors affect the ecological
properties of Australian communities, relative to uninvaded areas with similar densities of predators, has not
yet been addressed. In North America, native nettle
plants have adapted to invasion by garlic mustard via
reduced dependence on mycorrhizal fungi (Lankau
2012), but these adaptations make them poorer competitors with natives (Lankau 2012). While adaptation may
reduce the ecological impact of the agent imposing novel
strong selective pressure, ‘adapted’ organisms with different qualities may have other, unmeasured ecological
impacts, through altered traits and trait correlations. These
examples suggest that when humans, either directly or
indirectly, impose strong directional selection on complex
ecosystems, we can expect eco-evolutionary dynamics that
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manifest in alternative stable states (see also Estes et al.
2011).
Experimental approaches to studying eco-evolutionary
dynamics in field communities
To better understand when and whether eco-evolutionary
dynamics are important in complex natural communities,
we need to conduct experiments in more realistic field
settings.
Approach 1. Manipulating community members and
measuring ecological and evolutionary effects
While manipulation of the densities or presence/absence of
community members may provide us with an understanding
of the agents of selection and potential eco-evolutionary
feedbacks within communities, the approach is fraught with
challenges in complex communities. Manipulation of one
member can create ramifying effects that may make interpretation of evolutionary responses difficult, owing to community complexity. Indirect effects may be one reason why
long-term release of Rumex acetosa from grazing rabbit
herbivores did not result in the evolution of reduced resistance or tolerance to herbivory, as predicted, but instead
caused an evolutionary shift in plant growth rate (Turley
et al. 2013). This result may reflect indirect ecological effects
of grazing such as changes in community composition in
plots, nutrient availability, or selection arising from other
indirect effects of grazing release.
In addition, when our experimental manipulations are
unnatural, they may not accurately reflect the magnitude of
eco-evolutionary responses typical for natural communities,
though they may still provide valuable insights into agents
involved in eco-evolutionary dynamics. Frequently, manipulations represent a novel selective environment for at least
some genotypes. A four-year experiment removing all herbivores from a plant community – a very dramatic alteration of
community – likely represents a novel selective force (Agrawal
et al. 2013a, b). Four-year herbivore removal greatly increased
the percent cover of dandelions at the expense of Oenothera
biennis in experimental plots, presumably because herbivores
suppress dandelions more than Oenothera. The removal of
herbivores then favored Oenothera genotypes that were better dandelion competitors, and caused divergent evolution
in herbivore-protected Oenothera populations from populations experiencing ambient herbivory (Agrawal et al. 2013a).
These treatments revealed the importance of adaptation to
the combination of direct and indirect ecological effects of
herbivores. While these experiments may not accurately
reflect the magnitudes of eco-evolutionary responses to herbivory in natural communities, because the manipulation is
likely stronger and more consistently directional than selection in nature, these experiments do contribute by revealing
conflicting selection with multiple interactors, which interactions contribute most to fitness, and potentially by revealing the degree to which communities are coevolved.
If selection imposed by our treatments is strong or
unnatural, we may see rapid adaptation that alters the effect
sizes of our treatments (Strauss et al. 2008). Agrawal et al’s
(2013b) experiment above dramatically illustrates that
populations within multi-generational field experiments
may adapt to experimental manipulations within the time
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course of the experiment – one year after treatments, there
was large evolutionary change between plots in plant populations that ramified to attack rates by moths herbivores.
Such adaptation could reduce or potentially increase the
effect size of manipulations (Strauss et al. 2008, terHorst
et al. 2010, data in Agrawal et al. 2013a, b, though these
data were not discussed with this point in mind). However,
adaptation to treatments may reflect true eco-evolutionary
dynamics in the field, if treatments are biologically representative. terHorst et al. (2010) showed that predator introductions to pitcher plant communities initially decreased
protozoan densities, but protozoan densities subsequently
increased, after adaptation to predation. Protozoa had different cell sizes that possibly played different ecological roles as
a result of adaptation to predation. When treatments are
realistic in nature and magnitude, community manipulations, with subsequent tracking of evolutionary change, provide a powerful way to explore eco-evolutionary feedbacks
owing to direct and indirect effects of community complexity. Methods are available to quantify and parse out the relative importance of genotypic variation within species and
ecological impacts of species in explaining variance in ecological outcome (Ellner et al. 2011).
Approach 2. Experimentally mismatching genotypes with
communities
Another experimental approach is to examine ecological
effects of genotypes sampled from different communities
and reciprocally inserted back into these same communities. This approach can be very informative in identifying
how adaptation affects ecological properties of communities, (Lankau and Strauss 2007, Palkovacs et al. 2009,
Agrawal et al. 2013a, b) and is also the basis of resurrection
biology, in which ancestral lineages from past environments
are resuscitated and challenged with alternative conditions
(Lenski 1988, Kerfoot et al. 1999). It is important to consider, however, the selection of genotypes included in such
experiments (Tack et al. 2012). For example, if fish prey
genotypes are sampled from predator-rich, and predatorfree environments, and tested together in a predator-rich
environment, then the impact of genetic variation on ecology, and vice versa, may be much greater than in an experiment in which genotypes are sampled only from
predator-rich environments. In the first case, the genotype
treatment may reveal ecological impacts of adaptation to
predation, but these impacts are measured in greatly mismatched environments (predator-rich) for some genotypes.
In contrast, the second experiment indicates the ecological
importance of local adaptation in predator/prey communities and the impact of that local adaptation on ecosystem
function (as in Palkovacs et al. 2009, Fridley and Grime
2010). In the latter case, we expect genetic variation to
have subtler effects, as all genotypes are coming from some
evolutionary history with a predator. Both experiments
tell us something about eco-evolutionary feedbacks, but
differ in the nature, and degree of these feedbacks.
Genotype-environment mismatch can also be effectively
exploited to understand cyclic eco-evolutionary feedbacks,
if genotypes adapted to different conspecific densities
are placed into communities in the field that vary in conspecific density (Lankau and Strauss 2007).
Approach 3. Field experiments in which community
diversity and genotypic diversity are manipulated
independently
May serve as a means to understand stabilizing ecoevolutionary processes. Several studies have manipulated
species diversity and genotypic diversity independently
(Vellend 2005, Fridley et al. 2007, Crawford and
Rudgers 2012, Lawrence et al. 2012), and all find important
interactions between these two levels of diversity in outcomes
and ecosystem properties. Few of them are run on a longterm basis, tracking both evolution within communities and
ecosystem function. Lawrence et al. (2012) found greater
rates of evolution and niche divergence in microbial populations grown for many generations in diverse communities
versus monocultures. Field experiments that manipulate
genetic and species diversity at realistic scales in natural settings, and that then correlate changes in ecological function
with evolution in resident populations, would be able address
the effects of, and interactions between, these two levels of
diversity. Genomic tools may make such approaches more
feasible.
Approach 4. Observational data complementing
experimental approaches
Observational data collections coupled with experimental
approaches can provide complementary insights (Lankau
and Strauss 2007, Walsh et al. 2012, Semchenko et al.
2013). Semchenko et al (2013) quantified the natural frequency of association of species (heterospecifics) and with
conspecifics in field communities and then experimentally
showed greater abilities of plants to compete with their
most frequent neighbor (see also Aarssen and Turkington
1985b). Descriptive data can strengthen conclusions of
ongoing experiments. Observations of communities and
genotypes of zooplankton in lakes supported predictions
based on alewife evolution in response to lake dams (Walsh
et al. 2012). In Lankau and Strauss (2007) the direction of
selection on sinigrin measured in experimentally assembled communities of con- and heterospecifics was the same
as in naturally occurring patches of plants that varied in
con- and heterospecific density. Observations can reinforce
the importance and longevity of eco-evolutionary feedbacks found in experimental systems. With regard to the
Oenothera experiments of Agrawl et al. (2013a, b), do naturally low herbivore density years favor the same genotypes
of Oenothera as in experimental herbivore removal manipulations? Similarly, measures of the productivity and functioning of genotype-genotype combinations across species
in the field could provide the basis for experiments on
G ⫻ G ⫻ E interactions and for investigations into multilevel selection and its impact on ecosystem function.
Conclusions
Community diversity has tremendous impacts on ecological interactions, ramifying through direct and indirect
effects. This interaction web generates complex selective
forces from direct and indirect interactions, as well as from
trait correlations, costs of traits and the interactions of all
of these with abiotic factors; evolutionary changes in
response to selection can feed back to affect the ecological
functioning of the system, as well as the nature of interactions. Results to date suggest that many eco-evolutionary
feedbacks occur, and that these feedbacks can cause altered
stable states in communities, cyclic density-dependent
dynamics, or communities whose properties may be buffered by G ⫻ G ⫻ E interactions. When communities are
artificially simplified, typically through human-generated
selection, we may find lasting evolutionary and ecological
shifts owing to stronger directional selection and ecoevolutionary feedbacks, often in the form of alternative
stable states. In natural, complex communities, ecoevolutionary feedbacks may play their most important role
at micro-spatial and evolutionary scales by buffering communities from change. Such effects may only be revealed by
experimentation, as they may be largely invisible without
documentation of evolutionary change. Experimental
approaches, mindful of the nature of selection they impose,
and of the genotypes used, complemented by observation,
can continue to shed light on how eco-evolutionary feedbacks contribute to system-wide biodiversity and function
in complex natural communities. Eco-evolutionary feedbacks re-emphasize the contributions of genetic diversity
within species as a means through which ecosystems cope
with and respond to environmental change.
Acknowledgements – I thank Oikos Society and the Per Brinck
Award Committee for the opportunity to think about these questions. The paper was enhanced by comments and conversation with
A. Agrawal, M. Johnson, M. Semchenko, C. terHorst, N. Turley
and K. Zobel.
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