How life-history traits affect ecosystem properties: Effects of dispersal in meta-ecosystems

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DOI: 10.1111/oik.03893
The concept of life-history traits and the study of these traits are the hallmark of population biology. Acknowledging their variability and evolution has allowed us to understand how species adapt in response to their environment. The same traits are also involved in how species alter ecosystems and shape their dynamics and functioning. Some theories, such as the metabolic theory of ecology, ecological stoichiometry or pace-of-life theory, already recognize this junction, but only do so in an implicitly non-spatial context. Meanwhile, for a decade now, it has been argued that ecosystem properties have to be understood at a larger scale using meta-ecosystem theory because source-sink dynamics, community assembly and ecosystem stability are all modified by spatial structure. Here, we argue that some ecosystem properties can be linked to a single life-history trait, dispersal, i.e. the tendency of organisms to live, compete and reproduce away from their birth place. By articulating recent theoretical and empirical studies linking ecosystem functioning and dynamics to species dispersal, we aim to highlight both the known connections between life-history traits and ecosystem properties and the unknown areas, which deserve further empirical and theoretical developments. This article is protected by copyright. All rights reserved.
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How life-history traits affect ecosystem properties: effects of
dispersal in meta-ecosystems
Fran ç ois Massol , Florian Altermatt , Isabelle Gounand , Dominique Gravel , Mathew A. Leibold
and Nicolas Mouquet
F. Massol (, CNRS, Univ. de Lille, UMR 8198 Evo-Eco-Paleo, SPICI
group, FR-59000 Lille, France. F. Altermatt and I. Gounand, Dept of Aquatic Ecology, Eawag, Swiss Federal Institute of Aquatic Science and
Technolog y, D ü bendorf, Switzerland, and: Dept of Evolutionary Biology and Environmental Studies, Univ. of Z ü rich, Z ü rich, Switzerland.
D. Gravel, D é pt de biologie, Univ. de Sherbrooke, Sherbrooke, Canada, and: Qu é bec Center for Biodiversity Science, Quebec, Canada. M. A.
Leibold, Dept of Integrative Biology, Univ. of Texas at Austin, Austin, TX, USA. N. Mouquet, 7 UMR MARBEC (MARine Biodiversity,
Exploitation and Conservation), Univ. de Montpellier, Montpellier, France.
e concept of life-history traits and the study of these traits are the hallmark of population biology. Acknowledging their
variability and evolution has allowed us to understand how species adapt in response to their environment.  e same traits
are also involved in how species alter ecosystems and shape their dynamics and functioning. Some theories, such as the
metabolic theory of ecology, ecological stoichiometry or pace-of-life theory, already recognize this junction, but only do
so in an implicitly non-spatial context. Meanwhile, for a decade now, it has been argued that ecosystem properties have
to be understood at a larger scale using meta-ecosystem theory because source sink dynamics, community assembly and
ecosystem stability are all modifi ed by spatial structure. Here, we argue that some ecosystem properties can be linked to a
single life-history trait, dispersal, i.e. the tendency of organisms to live, compete and reproduce away from their birth place.
By articulating recent theoretical and empirical studies linking ecosystem functioning and dynamics to species dispersal, we
aim to highlight both the known connections between life-history traits and ecosystem properties and the unknown areas,
which deserve further empirical and theoretical developments.
e study of life-history traits has primarily focused on
understanding how organism traits are aff ected by the
environment and has thus used principles of evolutionary
ecology and population dynamics.  is has involved basic
primary objectives such as: 1) understanding species adapta-
tions to their environment through the evolution of their life
cycle (initially dubbed as the study of life-history strategies,
Dingle 1974, Law 1979, Strathmann 1985); 2) making sense
of systematic, apparently non-adaptive phenomena such as
senescence in long-lived vertebrates or plants (Hamilton
1966, Reznick et al. 2006, Baudisch et al. 2013, Lema î tre
et al. 2015); and 3) connecting changes in organism life cycle
with their population dynamics through models of age- and
stage-structured population demographics (Charlesworth
1994, Caswell 2001).  e ip side of the issue is that life-
history traits can also be related to the eff ect of organisms on
their environment.
anks in part to the development of ecological theories
linking organism physiology to biogeochemical cycles, most
notably ecological stoichiometry (Sterner and Elser 2002)
and the metabolic theory of ecology (Brown et al. 2004), this
initial perspective has recently shifted to incorporate com-
plex ecological feedbacks such as ecosystem functioning and
ecological network complexity (Daufresne and Loreau 2001,
Berlow et al. 2009; Box 1 provides a glossary of concepts and
technical terms used in this paper). For example, Enquist
et al. (1999) proposed linking plant age at reproductive
maturity with biomass productivity through allometric rela-
tionships between biomass growth, standing biomass and
tissue/wood density. According to this theory, wood mass
at plant maturity should vary as the fourth power of plant
lifespan, thus allowing a rule-of-thumb to calculate the eff ect
of additional extrinsic plant mortality on biomass produc-
tion. Although empirical evidence behind theories based on
allometric relationships is hard to obtain (Nee et al. 2005),
it nonetheless relates life-history traits (here, age at maturity)
with ecosystem functioning (here, plant productivity and
carbon sequestration).
While ecological stoichiometry and the metabolic theory
of ecology have revealed a number of ways that life-history
can shape ecosystems (Elser et al. 2000, Berlow et al. 2009,
Hall et al. 2011, Ott et al. 2014), these hypotheses lack a
proper incorporation of ecological interactions (predation,
competition, pollination, parasitism, etc.) and do not take
the spatial structure of ecosystems into account. Other
work, most notably on host parasite interactions and the
© 2016  e Authors. Oikos © 2016 Nordic Society Oikos
Subject Editor: Dries Bonte. Editor-in-Chief: Dustin Marshall. Accepted 5 December 2016
Oikos 000: 001–015, 2017
doi: 10.1111/oik.03893
link between life-history strategies and organism immunity,
have succeeded in linking life-history traits to parasitic inter-
actions and ecosystem functioning through pace-of-life
syndromes (Barrett et al. 2008, R é ale et al. 2010, Wolf and
Weissing 2012, Flick et al. 2016). While pace-of-life theory-
based studies do take ecological interactions into account
to explain links between life-history traits and ecosystem
functioning, they still overlook the spatial structure of
More recently, metacommunity and meta-ecosystem
theories have improved the general understanding of the
links between the spatial structure of ecosystems and some
of their properties (Loreau et al. 2003b, Leibold et al. 2004,
Massol et al. 2011).  ese include species diversity (Mouquet
and Loreau 2003, Gravel et al. 2010b), productivity
(Mouquet et al. 2002, Loreau et al. 2003a), food web inter-
actions (Amarasekare 2008), interaction network complex-
ity (Calcagno et al. 2011, Pillai et al. 2011) and stability
(Gounand et al. 2014, Gravel et al. 2016). Nevertheless,
though such theories are based on the eff ects of traits on
the dynamics of communities, an explicit link between the
metacommunity literature sensu lato and life-history theories
is still lacking.
Combining metacommunity ecology with life-history
trait ecology has an obvious trait of choice : dispersal i.e.
the tendency of organisms to live, compete and reproduce
away from their birth place.  e aim of this article is to make
explicit the links that connect dispersal, as a life-history trait
in the population biology meaning of the word (Bonte and
Dahirel 2017), to meta-ecosystem properties using results
obtained in the fi eld of metacommunity/meta-ecosystem
research. By doing so, we hope to fulfi l two objectives.
First we show how meta-ecosystem theory together with
other theories presented above can bridge the gap between
life-history trait studies and ecosystem properties. We then
identify remaining questions that still need to be tackled
in meta-ecosystem ecology to answer life-history driven
questions. We specify theoretical predictions that need exper-
imental testing, as well as needed theoretical developments,
to achieve an overall and coherent understanding of natural
ecosystems. Below, we fi rst go through eff ects of dispersal
on the functioning of meta-ecosystems. We then describe
the eff ects of dispersal on the dynamics of ecosystems and
provide an empirical overview on the life-history traits driv-
ing spatial fl ows between ecosystems and meta-ecosystem
properties. Finally, we conclude by discussing interactions
between dispersal and other life-history traits in the context
of meta-ecosystem ecology, and provide perspectives for
future work, both theoretical and empirical.
Dispersal and the functioning of meta-ecosystems
Ecosystem functioning is a broad class of properties that
involve fl uxes and stocks of elements, energy, nutrients or
biomass among ecosystem compartments. While tradi-
tional, non-spatial ecosystem ecology considers fl uxes as
the result of primary production (from abiotic compart-
ments to a biotic one), biotic interactions between species
(from a biotic compartment to another one), or death and
recycling of organic material (from a biotic compartment to
an abiotic one), meta-ecosystem ecology acknowledges the
existence of a fourth kind of fl ux, i.e. fl uxes due to the physi-
cal movement of biotic or abiotic material from one place to
another (Massol and Petit 2013). Because dispersal links the
Box 1
Ecological stoichiometry .  e study of element (e.g. carbon, nitrogen, phosphorus...) content within organisms and its
stocks and fl uxes involved in ecological processes at larger scales.
Keystone and burden ecosystems . An ecosystem is said to be keystone if its removal from the meta-ecosystem leads to
disproportionately deleterious consequences for a given (or several) ecosystem property (e.g. productivity) at the meta-
ecosystem scale. Conversely, a burden ecosystem s removal leads to disproportionately benefi cial consequences at the
meta-ecosystem scale.  e defi nition of disproportionately in this context is based on what the removal of a typical
ecosystem of the same size would entail at the meta-ecosystem scale (Mouquet et al. 2013).
Metabolic theory of ecolog y . A theory which links the diff erent rates involved in organism life history (growth, consumption,
death, etc.) with body size and temperature through chemical and physical processes and laws (Brown et al. 2004).
Neutral theory of community ecology . A theory which explains the diversity of species observed in ecological communities
solely through the interplay of stochastic processes (dispersal, ecological drift, speciation, remote colonization) and not
through species niche (Hubbell 2001).
‘ Pace-of-life theory of animal personality syndromes . A theory which posits that natural selection generally leads to the
existence of general personality syndromes linking physiological, immunological, foraging and life-history traits (R é ale
et al. 2010).
Resource ratio theory . A theory which explains the coexistence of species based on the complementarity of their resource
needs and their impacts on resource stocks (Le ó n and Tumpson 1975, Tilman 1980, 1982).  is theory has been
expanded since then to include other limiting factors, such as predator pressure (Leibold 1995).
functioning of diff erent localities, diff erences in dispersal can
also change the functioning of the entire meta-ecosystem by
increasing or decreasing total primary productivity, changing
source sink dynamics among biotic compartments or shift
the distribution of biomass across food webs (Loreau and
Holt 2004).
Initially studied as a natural extension of the insurance/
complementarity hypothesis behind the diversity-productivity
relationship (Yachi and Loreau 1999, Norberg et al. 2001),
the link between species dispersal and ecosystem productiv-
ity was fi rst made explicit for a single trophic level commu-
nity in the model by Loreau et al. (2003a).  e principle
behind this model is quite simple: when local environments
within patches fl uctuate in time (but out-of-phase), disper-
sal allows species to average their growth rate over several
patches and, hence, to perform better than if they had not
dispersed. As explained in models of the evolution of dis-
persal in variable environments, dispersal allows fi tness to
depend on its arithmetic spatial average rather than geomet-
ric temporal average (Metz et al. 1983, Massol and D é barre
2015).  is better performance is immediately translated
as higher productivity when the species considered are only
primary producers (positive green arrow linking insurance
to primary productivity ’ through ‘ temporal variability ’ on
the right-hand side of Fig. 1).
By contrast, when the environment is spatially heteroge-
neous, but temporally constant, productivity decreases with
dispersal (Mouquet and Loreau 2003), as dispersal maintains
maladapted species through source sink dynamics (Leibold
et al. 2004; negative green arrow linking local adaptation
to ‘ primary productivity ’ through ‘ quantitative spatial het-
erogeneity on the right-hand side of Fig. 1).  ese results
are linked to the eff ects of dispersal on species coexistence:
in the absence of dispersal, local diversity is limited. At very
high dispersal, only the best species at the regional level pre-
vails. As a consequence, local diversity peaks at intermediate
dispersal, while regional diversity decreases with dispersal
(Mouquet and Loreau 2003). Both in the absence or pres-
ence of temporal fl uctuations of the environment, models
based on the insurance hypothesis found positive diversity
productivity relationships in metacommunities (Loreau et al.
2003a, Mouquet and Loreau 2003, Cloern 2007).
Primary producer coexistence, and hence productivity
following the insurance/complementarity hypothesis, might
be improved through spatial structure, i.e. the fact that
ecosystems are distinct but connected by dispersal, when
producers are constrained by more than one limiting resource
(ecological stoichiometry models; Box 2, Fig. 2). In the
models of Mouquet et al. (2006) and Marleau et al. (2015),
nutrient co-limitation, i.e. the perfect case for coexistence
in the resource-ratio theory (Tilman 1982, 1988), can be
obtained through spatial structure and dispersal only. In
such a case, resource co-limitation does not exist locally, but
emerges at a larger scale due to diff erences in dispersal rates
among functional compartments (Fig. 2B).  is emergent
eff ect provides at the same time an explanation for increasing
primary producer growth with increasing nutrient concen-
trations in spite of potential top down control.
It is important to consider dispersal as a life-history
trait that can diff er among species within the ecosystem.
is can aff ect ecosystem functioning in the same way that
heterogeneity in dispersal rates has been acknowledged,
namely as a force shaping species coexistence and diversity
distribution within ecological communities (Amarasekare
2003, Calcagno et al. 2006, Laroche et al. 2016). For
instance, Gravel et al. (2010a), found that detritus/detriti-
vore or herbivore dispersal, but not that of the basal resource,
can enhance primary productivity. Gravel et al. (2010a) also
demonstrate that the expected source sink dynamics of
one compartment (e.g. plants) can be reversed when other
compartments (e.g. detritus or nutrients) disperse between
patches. In particular, the source sink dynamics of primary
producers are sensitive to the balance of nutrient versus
detritus diff usion; patches that would normally be unsuit-
able for them can become suitable when detritus diff usion
rate is high enough (Gravel et al. 2010a; positive green arrow
linking detritus to productivity on the left-hand side of
Fig. 1).
A positive or hump-shaped relationship between dispersal
and productivity can emerge due to the dual nature of disper-
sal (i.e. as a fl ux of material and energy and as a demographic
rate, Massol et al. 2011, Fig. 1). Because dispersal allows
the mixing of species across space, it tends to homogenize
composition among patches, and thus can have either a
positive or a negative eff ect on productivity depending on
whether environmental variability is spatial and/or temporal
(Loreau et al. 2003a, Mouquet and Loreau 2003, see the
link between ‘ local adaptation ’ / ’ insurance ’ and ‘ characteris-
tics of limiting factors in Fig. 1). By contrast, any dispersal
ux of living organism eventually fuels the detritus pool in
the recipient patch and, hence, fertilizes it (left-hand side
arrows linking all compartments, except basal resource, to
spatial heterogeneity of limiting factors on Fig. 1). Such an
enrichment will increase regional productivity because 1) the
recipient patch becomes suitable for primary producer if it
was not in the fi rst place, and 2) these fl uxes make resource
use more effi cient overall by preventing nutrient diff usion
out of the meta-ecosystem (Gravel et al. 2010a, Fig. 1).
Other forms of interspecifi c diff erences may be important
in mediating spatial eff ects on ecosystem functioning. For
instance, Mouquet et al. (2013) proposed the concept of
“ keystone ” and “ burden ecosystems, i.e. local ecosystems
that have disproportionately strong positive (for keystone)
or negative (for burden) impact on regional productivity.
Such eff ects arise with spatial heterogeneity of the envi-
ronment and of nutrient inputs. Keystone ecosystems
are characterized by relatively high nutrient inputs and
dominant primary producers that have the lowest limiting
resource requirements. Because ecological stoichiometry is
likely linked to demographic parameters (Klausmeier et al.
2004), which in turn have been empirically proved to be
connected to life-history traits (Munoz et al. 2016), the
road is not long to link interspecifi c variation in life-history
traits to the keystoneness of ecosystems in the framework
of Mouquet et al. (2013).
Dispersal and the dynamics of meta-ecosystems
Ecosystem dynamics refers to the temporal changes of
ecosystem variables (e.g. biomass of the diff erent compart-
ments) and associated ecosystem properties (e.g. primary
productivity). At least three diff erent temporal scales can
Box 2
Dispersal and stoichiometry in meta-ecosystems
e resource-ratio theory of plant coexistence (Tilman 1982, 1988), based on the seminal model of Le ó n and Tump-
son (1975), has been instrumental in our understanding of the intimate linkage between stoichiometry, community
assembly and ecosystem functioning.  e theory applies to two resources the R
* principle of competition theory. Its
main prediction is that stable coexistence between two species requires a particular ratio of the two limiting nutri-
ents. Owing to its accessible graphical representation, the theory has a central position in most ecological textbooks
(Begon et al. 2006).  e theory has also been further developed to derive a vast array of secondary predictions, such
as the impact of resource heterogeneity and fertilization on species richness and successional dynamics (Tilman 1982,
1985).  e resource-ratio theory builds on the idea that spatial heterogeneity in the ratio of limiting resources pro-
motes the maintenance of highly diverse communities (Tilman 1982).  is prediction does apply to various spatial
scales, from the individual-to-individual variation in soil properties, to landscape variations.  e theory does not,
however, consider the impact of spatial exchanges of plants, nutrients and other materials between localities. Both
metacommunity (Mouquet and Loreau 2002, Abrams and Wilson 2004) and meta-ecosystem (Gravel et al. 2010a)
theories in source sinks settings have shown that the outcome of competitive interactions could be signifi cantly
altered by these fl ows. While it is quite challenging to elaborate a full and comprehensive theory for stoichiometry
of nutrient fl ows in source sink meta-ecosystems, it is nonetheless possible to get some intuition from a graphical
representation of two patches and two nutrients.
e graphical interpretation of the resource-ratio theory builds on a few important concepts. First, the zero
net growth isocline (ZNGI) represents the combination of the two nutrient concentrations resulting in a null
intrinsic growth rate for a given species (Fig. 2). In other words, it is the two-dimensional representation of the
* principle of competition theory. Nutrients are supplied at a given ratio in any locality, owing to processes such
as atmospheric depositions on land and river and stream infl ows in lakes. In absence of consumption by primary
producers, the nutrients do equilibrate to a given concentration and ratio, represented visually as the supply point S
(Fig. 2). A key concept is that a species is able to persist provided that the supply point is located somewhere above
its ZNGI. Once a species establishes, it consumes nutrients in a given ratio, which is represented by the consump-
tion vector (the slope of the vector corresponds to the ratio of nutrient consumption).  e system will converge at
equilibrium to the point corresponding to the intersection between the ZNGI and the consumption vector aligned
on the supply point. Coexistence of two species occurs provided that their ZNGIs do cross each other, and that
the supply point is located in the triangle defi ned by the projection of their respective consumption vectors (Fig. 2;
Tilman 1982, 1988). When limiting factors are not resources, but natural enemies (i.e. the case in models of appar-
ent competition), the same approach can also be used (Leibold 1995, Grover and Holt 1998), although ZNGIs and
the conclusions associated with the diff erent angles of intersections are not defi ned in exactly the same way, and
nonlinearities in predator functional responses can lead to departures from resource-ratio theory (Grover and Holt
Nutrient cycling and any spatial exchange of nutrients between localities, whether inorganic or sequestered in bio-
mass, signifi cantly complicate the situation and often make the underlying mathematics intractable. But fortunately, the
concept is pretty straightforward to illustrate graphically. In both cases, they represent an additional source of nutrient
inputs and therefore move the supply point in the two-nutrient space. In the simple case of decomposition of detritus,
where both nutrients are mineralized at the same rate, we do fi nd the net supply point (S ) moving away from its original
location. It increases the fertility of the system, but does not change the equilibrium situation because it keeps the same
ratio.  e net supply point will, however, move in one direction or another if the mineralization or the dispersal between
localities does not respect the ratio at which it is consumed. For mineralization to alter the conditions for coexistence,
it requires that the net supply point S is located within the projection of the two consumption vectors (Daufresne and
Hedin 2005).
e situation is slightly more complicated for nutrient diff usion, in particular when the two localities do have dif-
ferent nutrient supplies, or alternatively if they are occupied by diff erent species with distinct ZNGIs and consumption
vectors. If the movement of nutrients is passive, it will move by diff usion from the locality that has the highest nutrient
concentration (the source) to the locality with the lowest nutrient concentration (the sink).  e location of the net sup-
ply point will therefore move in both localities. If the two localities are occupied by the same species, it will inevitably
move the supply point toward the centre of the nutrient space, as it will homogenize the meta-ecosystem. It could, how-
ever, go in the other direction depending on the characteristics of each species inhabiting localities. As a consequence,
each nutrient in a patch could thus either increase or decrease in availability, thus eventually aff ecting the conditions for
an evolutionary perspective, an increase of prey extinction
rate due to predator occurrence increases the evolution-
arily stable dispersal rate in the predator, but is unimodally
linked to the evolutionarily stable dispersal rate in the prey
(Pillai et al. 2012). Overall, these results suggest that food
web assembly and more generally ecosystem assembly
depends on species dispersal rates in a complex fash-
ion, as predator-induced prey extinction tends to select for
more mobility in predator than in prey. When predator
presence increases prey extinction rate, foraging by the
predator can have the surprising eff ect of both increasing
maximal food chain length while decreasing the average
food chain length at the metacommunity scale (Calcagno
et al. 2011).
One key fi nding is that dispersal can substantially
modify theoretical predictions of ecosystem stability. May
(1972) showed with a simple model of random commu-
nity matrices that complex and diverse local ecosystems
are bound to be unstable. In contrast to May s conclusion,
dispersal can substantially increase the stability of diverse
and complex ecosystems (Gravel et al. 2016).  e general
principle is that dispersal tends to stabilize meta-ecosystem
dynamics because it averages responses to perturbations. As
a result, it buff ers extremely strong interaction strengths,
which are the most destabilizing.  e more ecosystems are
spatially averaged through dispersal (i.e. the more patches
are connected), the more stable the meta-ecosystem can be.
Numerical integration of Lotka Volterra systems (Mougi
and Kondoh 2016) and individual-based simulations (Coyte
et al. 2015) lead to the same result, with the additional
eff ect that very high dispersal tends to synchronize patch
dynamics and thus to homogenize ecosystem responses to
perturbations, which in turn cancels the stabilizing eff ect
of dispersal (Gravel et al. 2016). Hence, intermediate
dispersal rates provide the best conditions for species-rich
meta-ecosystem stability.
e eff ect of dispersal on the dynamics of simple food
web modules in two-patch systems is, however, contrasted.
be distinguished. First, on long time scales, a dynamical
aspect of ecosystems is their assembly, i.e. the building-up
of ecosystems by immigration, extinction and evolution of
its component species (Morton and Law 1997). Second,
on relatively shorter time scales, the synchrony of diff erent
ecosystems connected by dispersal qualifi es the coherence
of diff erent ecosystem dynamics (Koelle and Vandermeer
2005). Finally, on even shorter time scales, ecosystem stabil-
ity, in the sense employed by May (1972), is the tendency
of systems to return to their initial state after a small per-
turbation.  ese three aspects of ecosystem dynamics are
linked in complex ways (Briggs and Hoopes 2004), and, as
we develop below, are sensitive to the amount of dispersal
among ecosystems.
Colonisation and extinction processes are at the heart
of the simplest models of ecosystem assembly.  e theory
of island biogeography (MacArthur and Wilson 1963) has
been extended to food webs (Arii and Parrott 2004, Gravel
et al. 2011, Cazelles et al. 2015, Massol et al. 2017) and has
revealed rich and testable predictions (i.e. how many species,
trophic levels, etc. can be found on islands relatively to the
mainland).  ese predictions arise from the interplay of two
simple rules: predators colonize islands that contain at least
one of their prey; and the extinction of a predator s last prey
species entails its own extinction on an island.  ese rules
result in island community assembly resembling a sampling
of the mainland food web which depends on its topology
(Arii and Parrott 2004). In the same way, the strength of
extinction cascades triggered by a single random extinction
also depends on mainland food web topology (Massol et al.
In food chains, a patch-based metacommunity model
predicts that transient food chain assembly within patches
submitted to random perturbations depends on top down
eff ects of predators on prey colonisation and extinction
rates (Calcagno et al. 2011). Longer food chains are more
likely when predator presence decreases extinction rate and
increases colonisation rate (Calcagno et al. 2011). From
Finally, organisms themselves can move across the patches.  e impact of their dispersal has been extensively studied
in a wide range of conditions (Amarasekare and Nisbet 2001, Mouquet and Loreau 2002, Abrams and Wilson 2004).
Again, often the mathematics is hard to track in all of these models, but the graphical representation provides a use-
ful and general understanding of the consequences of source sink dynamics on species coexistence. Basically, dispersal
infl icts an increased loss of individuals in the location with highest density (emigration from the source), and an enrich-
ment in the location with lowest density (immigration to the sink). It provokes a translation of ZNGIs for both nutrients
(Fig. 2), moving them to higher values in the source location and to lower values in the sink. As a consequence, dispersal
might sustain a population in a location that would be otherwise inhospitable, as in traditional source sink systems
(Pulliam 1988) or in competitive systems (Mouquet and Loreau 2002).  e projection of the consumption vectors will
not be altered by dispersal of the organisms, even if there is nutrient cycling of their detritus, except in the case in which
the two nutrients are not recycled at the same rate.
In conclusion, spatial exchanges of nutrients, organisms and their detritus might alter the conditions for coexistence.
ey tend to promote regional coexistence in presence of spatial heterogeneity of supply points because 1) the supply
point moves toward the centre of the nutrient space, thereby making the conditions for coexistence more likely, and 2)
the ZNGIs move in a way that increases the tolerance of species to harsh conditions and decreases their performance in
good locations. More extensive analyses also show that it can lead to alternative stable states, and potentially dynamic
instabilities (Daufresne and Hedin 2005, Gravel et al. unpubl.). Another consequence is that dispersal, of all kinds, tends
to homogenize the meta-ecosystem in most situations.
Box 2 (Continued)
Empirical feedback to theory
Empirical work in ecology has been spurred by the theoreti-
cal development of the metapopulation and metacommu-
nity concepts, which eventually led to a better understanding
of natural ecosystems (Logue et al. 2011, Grainger and
Gilbert 2016). We are now at the point where theoretical
developments of the meta-ecosystem concept are also feed-
ing into experimental and comparative studies (Staddon
et al. 2010, Harvey et al. 2016, Gounand et al. 2017).
However, theory on meta-ecosystems is substantially more
advanced than its empirical counterpart, possibly because
of some inconsistencies between the general models and the
specifi cities of natural systems (Logue et al. 2011). One such
Predator dispersal tends to synchronize and destabilize
dynamics in both predator prey (Jansen 2001) and tri-
trophic food chains (Jansen 1995). By contrast, in nutrient
detritus – primary producer – consumer systems, nutrient and
detritus diff usion rates are destabilizing while producer and
consumer dispersal tends to be stabilizing (Gounand et al.
2014). In the latter study, intermediate consumer dispersal
rate can lead to alternative stable states of the meta-ecosystem,
with the meta-ecosystem being either in a symmetrically
oscillating state (same dynamics in the two patches) or in
an asymmetrically stable state (one patch becomes a source
of producers, consumers and detritus while the other stores
nutrients) without any underlying heterogeneity of the
environment (Gounand et al. 2014).
Local adaption
Basal resource
Effect of dispersal as
flux of material/energy
Effect of dispersal as
demographic rate
trophic level
Enrichment of scarcely
populated patches
Impoverishment of scarcely
populated patches
Disparate effects on limiting
factors among patches +/-
+ -
Qual. Quant.
Figure 1. Links between dispersal and primary productivity according to meta-ecosystem theory (Loreau et al. 2003a, Mouquet and Loreau
2003, Gravel et al. 2010a). On the left-hand side of the diagram, dispersal of consumers, detritus and producers, seen as fl uxes of material
and energy, tends to increase the amount of biomass in scarcely populated patches (i.e. those in which basal resource levels are too low for
the establishment of producers and/or consumers) and thus, through nutrient recycling, to decrease the spatial heterogeneity in nutrient
stocks among patches (blue arrow with a minus sign). Diff usion of the basal resource, nutrients (Gounand et al. 2014), or producers seen
as basal resource (Pedersen et al. 2016), on the other hand, will create a source sink movement from low-productivity patches to already
highly productive patches, thus aggravating the spatial heterogeneity of resource stocks among patches (blue arrow with a plus sign). Spa-
tially heterogeneous distribution of a single resource results in a negative eff ect on primary productivity (quantitative heterogeneity). How-
ever, in case of several resources, heterogeneity in local nutrient balances (qualitative heterogeneity) may lead to positive e ects on
productivity (Marleau et al. 2015). On the right-hand side of the diagram, dispersal of primary producers seen as a demographic rate (i.e.
the I and E of the BIDE framework proposed by Pulliam 1988) generally decreases local adaptation of primary producers (they end up in
patches in which they are less well adapted, but see Edelaar and Bolnick 2012 for possible counter-examples), but primary productivity
provided by the community of primary producers gains insurance against temporal variability of the environment. Dispersal thus increases
productivity at the regional scale when the environment is temporally variable, but decreases it when it is spatially heterogeneous (green
arrows going through spatial heterogeneity and spatial variability of limiting factors); the combination of the two results in a hump-shaped
link between dispersal and productivity.  e blue arrows on the right-hand side of the diagram represent the potential demographic eff ects
of consumer dispersal on limiting factor variability in time and space; as this eff ect is quite variable across scenarios, its eff ect on productiv-
ity is far from being predictable (Jansen 1995, 2001, Koelle and Vandermeer 2005, Gounand et al. 2014).
Nutrient 1
Nutrient 2
Eiii Eii
0 1020304050
Nutrient 1
0 1020304050
Nutrient 1
Figure 2. Graphical interpretation of the resource-ratio theory in a competitive meta-ecosystem. (A) Representation of a single ecosystem made of two resources and two competitors. Stable coexistence
will depend on where the supply point S
i is located relative to the projection of the consumption vectors C
A and C B . Equilibrium nutrient availability is indicated by the E
i and the location depends
on the fi nal species composition. (B) Conceptual representation of source sink dynamics of inorganic nutrients in a two-patch meta-ecosystem.  e location of the two supply points is moved toward
the centre of the nutrient space, to locations S
, resulting in the homogenization of the metacommunity. Regional coexistence is possible in absence of nutrient movement, but not local coexistence.
e movement of net supply points toward the centre, however, allows local coexistence of the two species. (C) Representation of the eff ect of dispersal of a single species on the location of the ZNGIs
in presence of source sink dynamics.  e ZNGI moves to the bottom left in the patch ii (a sink), because of immigration, allowing its stable persistence there. Similarly, the ZNGI moves to the top
right in patch i (a source), consequent to emigration.
foraging fi shes (Bray et al. 1981, Schindler and Scheuerell
2002, Vanni 2002) or feces of larges herbivores or migra-
tory birds (Bazely and Jeff eries 1985, Seagle 2003, Jeff eries
et al. 2004), or cadavers that serve as resources in the recipi-
ent ecosystem without having a population dynamics (e.g.
migrating aquatic species in streams, Helfi eld and Naiman
2002, Naiman et al. 2002, Muehlbauer et al. 2014). Disper-
sal in the strict sense (Massol et al. 2011) may actually be
not feasible between diff erent habitat types for most organ-
isms, as they can only live in one of these habitats and die
in the other one. In such a situation, material fl ows would
be the predominant exchange.  us, in many empirical sys-
tems, these material fl ows are causally linked to the death
of organisms (Nakano and Murakami 2001, Sitters et al.
2015), and thus directly depend on life span as one of the
most important life-history aspects.
Most of the empirical examples of strong meta-ecosystem
dynamics involve aquatic-terrestrial linkages, in which
spatial fl ows relax each other ecosystem s limitations, e.g.
terrestrial carbon input into carbon-limited aquatic systems
and converse subsidy of the terrestrial system with aquatic
nitrogen (Sitters et al. 2015). A textbook example thereof
would be emerging aquatic insects, which can be accidentally
diverted into terrestrial systems during their metamorphosis
to adulthood and reproductive fl ights, and subsequently die.
Importantly, these organisms, even if moving and mating
in the recipient ecosystem, oviposit in the donor ecosystem
(aquatic habitat) and do not always actively participate in
consumer-resource dynamics in the recipient ecosystem (ter-
restrial habitat) contrary to what meta-ecosystem models
assume regarding organism fl ows. Flows of aquatic organ-
isms serving as resources in terrestrial systems have been
extensively described for aquatic insects but also fi sh dying
after spawning (Naiman et al. 2002, Muehlbauer et al. 2014,
Sitters et al. 2015). However, these studies on strong spatial
couplings between ecosystems are mostly found in the eco-
system ecology fi eld literature, with observational data either
predating or only marginally linked to the theoretical con-
cept of meta-ecosystems, which historically emerged from
the fi eld of population and community ecology (Loreau
et al. 2003b).
In contrast, experimental work on meta-ecosystems has
been developed from classic experimental approaches used
for metacommunities (Logue et al. 2011, Grainger and
Gilbert 2016, Smeti et al. 2016). Such meta-ecosystem
experiments have been done almost exclusively using patches
of the same type of ecosystem (but see Venail et al. 2008 for
an example of microbial communities replicated on diff erent
carbon sources), including both dispersal and mass-fl ows of
resources (Howeth and Leibold 2010, Staddon et al. 2010,
Legrand et al. 2012, Livingston et al. 2012).  ese experi-
ments confi rm theoretical predictions that meta-ecosystem
dynamics can emerge from feedbacks between organism
dispersal and resource dynamics in same habitat-type cou-
pled systems, analogous to meta-ecosystem models (fi rst
scenario in Fig. 3), such as lake or island networks, or forest
patches in an agricultural matrix. However, the important
eff ects that may arise in the emblematic case studies of cou-
plings between ecosystems of diff erent habitat types (second
scenario in Fig. 3) have yet to be adequately modelled or
experimentally tested.
inconsistency is the functional nature of the element mov-
ing between patches, i.e. organisms dispersing versus mate-
rial fl ows. Another potential inconsistency comes from the
type of systems that are connected, because theory focuses
on fl uxes among habitats of the same type, while empiri-
cists have addressed fl uxes among diff erent habitat types
(habitat is used in this section synonymously to the term
biotope). We here exemplify how the meta-ecosystem con-
cept is applied to empirical studies, and discuss this in the
context of life-history traits. Based on a text-book example
of meta-ecosystem dynamics, we identify possible disparities
between the theoretical work and its empirical counterparts,
and give an outlook on how to resolve the disparities and
move forward.
e main focus of the metacommunity framework is
the eff ect of dispersal on species coexistence, and the most
important life-history context is with respect to decisions
to disperse or not. A few dispersing individuals can often
have major consequences on the connected communities.
Implicitly, even in presence of intense habitat selection, it is
assumed that habitats are of similar kind, e.g. diff erent ponds
connected by dispersal (Altermatt and Ebert 2010, Declerck
et al. 2011).  is has been paralleled by extensive experimen-
tal work on metacommunities, in which same-type habitats
were connected by dispersal (Cadotte et al. 2006, Cadotte
2007, Altermatt et al. 2011, Logue et al. 2011, Grainger and
Gilbert 2016). A key fi nding has been that the species traits
related to life history, such as dispersal mode or dispersal stage
induction, and life-history tradeoff s can strongly aff ect meta-
community dynamics and species distribution (Altermatt
and Ebert 2010, De Bie et al. 2012, Seymour et al. 2015).
ese studies, for example, found that induction of disper-
sal stages is linked to environmental deterioration inducing
specifi c life-history stages (dispersal stages), and eventually
aff ecting species spatial distribution (Altermatt and Ebert
2010, De Bie et al. 2012). Tradeoff s between competitive
ability and dispersal ability result in distributions of species
diff ering from neutral models assuming otherwise identical
life-history traits (Seymour et al. 2015).
e meta-ecosystem framework explicitly considers local
nutrient dynamics and material fl ows such that dispersing
organisms can also be seen as vectors of resources fl owing
across units of spatial organisation.  e theoretical work on
meta-ecosystems is indiff erent with respect to the identity
of these habitat types. Empirically, however, there are two
major and distinct scenarios: First, the patches may be of
the same habitat type, which would then be an extension
of the metacommunity in which resource fl ows would also
be added, e.g. exchange of dispersers and resources among
diff erent ponds in a wetland (Howeth and Leibold 2010),
intertidal communities (Menge et al. 2015), or litter wind-
blown across diff erent agroecosystems (Shen et al. 2011).
e second scenario, and possibly the most common one,
however, is that the fl ows are between diff erent habitat
types, such as resource fl
ows between pelagic and benthic
habitats, and more strikingly between terrestrial and
aquatic ecosystems. Massive spatial fl ows can occur between
contrasting ecosystems (Polis et al. 1997) and they are often
linked to species life-history, whereby species either trans-
port resources during foraging (e.g. seabirds on islands,
Polis and Hurd 1995) or migration, such as excretion of
traits, while in the second it arises from phenology and life
span history-traits.
We propose that this distinction allows a better identi-
cation of the empirical and theoretical work needed: for
same-habitat-type meta-ecosystems, we lack observational
data to adequately quantify resource fl ows and we therefore
do not yet understand their signifi cance for local dynamics.
For diff erent-habitat type meta-ecosystems, fl ows are well
documented, but theoretical models that address the role
of organisms which are not dispersing between patches but
are instead crossing the barriers to fuel recipient resource
pools are currently lacking. In pioneering modelling work,
Leroux and Loreau (2012) opened the fi eld by investigat-
ing the eff ects of cross-ecosystem pulsed-fl ows of herbivores
as prey, but further developments in this direction are still
needed. On the experimental side, technical challenges have
to be addressed to causally separate spatial fl ows of materi-
als (resources) from spatial fl ows of organisms (dispersers)
(Harvey et al. 2016) in order to test precise meta-ecosystem
mechanisms. Empirical questions emerging from this sce-
nario are to test how species life-history traits in one habitat
type may cascade to other habitat types through mate-
rial fl ows. Furthermore, experimental tests disentangling
interactions between perturbation regimes and spatial
ows of resources may be highly relevant from an applied
empirical perspective, and can be addressed in an explicit
meta-ecosystem perspective. Ultimately, we expect the
dynamic interplay of theory (Loreau et al. 2003b, Massol
et al. 2011, Gounand et al. 2014) and empirical work to lead
to a more mechanistic understanding of spatial community
and ecosystems dynamics.
Dispersal: a life-history trait with many effects on
Previous sections have emphasized some ecosystem properties
that are aff ected by dispersal within meta-ecosystems. First,
depending on species coexistence mechanisms, dispersal
tends to increase local diversity and meta-ecosystem pro-
ductivity, at least until intermediate levels of dispersal (Levin
1974, Mouquet and Loreau 2002, Loreau et al. 2003a,
Economo and Keitt 2008). Second, provided that patches are
suffi ciently heterogeneous in their response to perturbations,
dispersal stabilizes meta-ecosystem dynamics (Gravel et al.
2016, Mougi and Kondoh 2016), although the dispersal of
some trophic levels is more stabilizing than others (Gounand
et al. 2014).  ird, in simple interaction networks, dispersal
tends to synchronize and destabilize local dynamics (Jansen
1995, 2001) while limited dispersal increases persistence of
otherwise ephemeral species assemblages (Briggs and Hoopes
2004). Fourth, in spatially structured heterogeneous ecosys-
tems, dispersal paves the way for nutrient co-limitation and
hence for species coexistence on a few limiting resources
(Mouquet et al. 2006, Marleau et al. 2015). On top of these
eff ects of dispersal on ecosystem functioning and dynam-
ics, species dispersal/colonization abilities shape food web
complexity (Calcagno et al. 2011, Pillai et al. 2011), which
Overall, feedback of empirical observations to meta-
ecosystem theory leads to the conclusion that the drivers
of meta-ecosystem dynamics may diff er depending on the
scenario of habitat types involved (Fig. 3). In same-habitat-
type meta-ecosystems, the spatial structure could be seen as
metacommunity-like, with organism dispersal as the domi-
nant spatial fl ow type, and meta-ecosystem eff ects would
mainly emerge from interactions between dispersal and
local resource dynamics (including local recycling). In dif-
ferent-habitat-type meta-ecosystems (e.g. aquatic-terrestrial
coupling), the spatial structure mostly consists of material
ows (dead organisms with negligible true dispersal), and
meta-ecosystem eff ects would emerge from interactions
between material fl ows and local community dynamics. In
the fi rst case, spatial couplings arise from species dispersal
Islands Rivers
Lakes / ponds Lakes / ponds
(scenario 1)
(scenario 2)
zoom on flowszoom on flows
Same species
LHT: dispersal
Different species
LHT: phenology, life span (death)
(A) (B)
(C) (D)
Figure 3. Two contrasting meta-ecosystem types based on empirical
observations and illustrated by aquatic terrestrial landscapes.
Panels (A) and (B) give examples of spatially structured landscapes
in which habitat patches are connected by spatial fl ows (arrows).
Blue and green colours refer to aquatic and terrestrial respectively.
Left column shows meta-ecosystems in which patches are of same
habitat type, while right column shows meta-ecosystems in which
patches are of diff erent habitat types. If we zoom on documented
ows between two patches (bottom panels), same-habitat-type
meta-ecosystems (C) are mostly linked by organism dispersal and
potential fl ows of resource (R), but these are poorly documented
(dotted arrows). Diff erent-habitat-type meta-ecosystems (D) are
linked by exchanges of dead organisms fuelling the resource pool.
Aq , and B
T refer to biomass of aquatic and terrestrial organisms
tradeoff preventing an organism from both moving and
eating at the same time). A second possibility is that dis-
persal correlates with the other trait because both traits are
structurally linked, e.g. they both scale with organism size
(allometric link) or they both respond similarly to biological
stoichiometric changes (stoichiometric link). Finally, both
dispersal and the other trait can be shaped by joint selective
pressures, with either the same pressures acting on both traits
at once (e.g. dormancy and dispersal, Vitalis et al. 2013) or
one or both trait(s) having a selective feedback on the other
(e.g. selfi ng and dispersal, Cheptou and Massol 2009, or local
adaptation and dispersal, Berdahl et al. 2015). In practice,
correlations between dispersal and other life-history traits
can only be uncovered when there is suffi cient variation in
the traits under study, which means that the wider the phy-
logenetic net , the easier it is to capture such correlations.
However, interpreting these correlations as resulting from
tradeoff s, structural constraints or joint evolution is often
diffi cult and experimentally challenging, especially when the
problem is framed as the inference of life-history invariants
(Nee et al. 2005).
It would be diffi cult to enumerate here all the possibilities
of dispersal-trait correlations that would likely have impacts
on meta-ecosystem functioning and dynamics. Some of
these have already been considered separately. For example,
Otto et al. (2007) s study on the eff ect of predator prey body
mass ratios on food web stability could be easily coupled
with Gravel et al. s (2016) study on the eff ect of dispersal on
ecosystem stability to gain insight into the combined eff ects
of dispersal and body size when both traits are structurally
linked. Others readily lend themselves to speculation. For
example, with higher passive dispersal in smaller organisms
and the relationship between initial growth, asymptotic size
and temperature in ectotherms (Atkinson et al. 2006), one
is tempted to think that warming oceans might become
less connected by dispersal, as some data on larval dispersal
already suggest (O’Connor et al. 2007), which in turn would
aff ect their functioning and dynamics as predicted by the
models described in previous sections.
An especially challenging issue regarding life-history trait
evolution and meta-ecosystem properties is to link ecologi-
cal stoichiometry with ecosystem properties through cell and
organism physiology (Jeyasingh and Weider 2007), e.g. as
proteins and rRNA have diff erent stoichiometry (Loladze
and Elser 2011). For instance, the proportion of phosphorus
content due to RNA (versus due to skeleton) is expected to
decrease with body mass in vertebrates (Gillooly et al. 2005).
In some insects, high-dispersal genotypes are associated
with particular alleles at genes coding for phosphoglucose
isomerase (PGI), e.g. in the Glanville fritillary butterfl y
(Haag et al. 2005, Hanski and Saccheri 2006). Effi cient PGI
genotypes have a higher peak metabolic rate and fl y longer
than less effi cient types (Niitep õ ld et al. 2009, Niitep õ ld and
Hanski 2013). As the PGI enzyme is involved in glycoly-
sis and gluconeogenesis, a link between PGI and ecological
stoichiometry might be expected (as suggested by experimen-
tal evidence on Daphnia pulex , Jeyasingh and Weider 2005,
Weider et al. 2005) which, in turn, would link ecological
stoichiometry with dispersal ability.  is eld of inquiry is
just beginning, but might reveal exceptional fi ndings linking
traits and ecosystem functioning, such as an increased spatial
can potentially feedback on ecosystem stability (Allesina and
Tang 2012, Neutel and  orne 2014, Grilli et al. 2016).
Meta-ecosystem theory is not solely geared towards
understanding the functioning of ecosystems, but also
grounded in the foundations laid out by metapopulation
and metacommunity theories.  erefore, the movements
of species within a meta-ecosystem are bound to be gov-
erned by how organisms perceive their environment and
where they thrive i.e. non-random dispersal, habitat selec-
tion, foraging and dispersal evolution (Amarasekare 2008).
e feedback of meta-ecosystem state on dispersal evolu-
tion has just begun to be studied, and has focused so far
on simple predator prey confi gurations (Chaianunporn and
Hovestadt 2012, Pillai et al. 2012, Drown et al. 2013, Travis
et al. 2013, Amarasekare 2015). On top of all the mecha-
nisms of dispersal evolution that are already known (Bowler
and Benton 2005, Ronce 2007, Duputi é and Massol 2013),
meta-ecosystem context is likely to provide new selection
mechanisms through the discrepancy in generation time
and spatial scale of motility of diff erent trophic levels. For
instance, dispersal is selected against when environmen-
tal quality of habitat patches is positively autocorrelated in
time, but selected for when it is positively autocorrelated in
space (Travis 2001, Massol and D é barre 2015). In the case
of a prey species for which predator presence is an environ-
mental characteristic , as predators live longer, have slower
population dynamics and can cover and forage over sev-
eral prey patches at once, the eff ective ’ autocorrelation of
the environment for the prey will likely be positive in both
time and space, thus aff ecting the evolution of prey dispersal.
Evolution of dispersal in food webs also imposes a feedback
between the cost of dispersal and dispersal itself, as sparse
prey populations can diminish predation pressure and,
hence, decrease the cost of dispersal borne out of predation
between habitat patches. Finally, it is also noteworthy that,
even though dispersal evolution has begun being considered
in a food web context, the consequences of this evolution on
ecosystem functioning have yet to be studied.
Other life-history traits and their impact on
e central tenet of meta-ecosystem studies is that species
dispersal may be responsible for many observations that
would otherwise require more complicated theories to
explain, such as the maintenance of maladapted species (the
“ mass eff ect paradigm of metacommunity theory, Shmida
and Wilson 1985, Leibold et al. 2004) or the distribution
of species abundance in ecological samples, as predicted
by the neutral theory of ecology (Hubbell 2001, Volkov
et al. 2003). From this central tenet, it is no wonder that
the main connection made by these studies between life-
history traits and ecosystem properties considers dispersal as
the life-history trait of interest. However, dispersal generally
correlates with a wide palette of other traits (e.g. fecundity,
body size, etc., Bonte and Dahirel 2017), known collectively
as dispersal syndromes (Clobert et al. 2009, Ronce and
Clobert 2012, Duputi é and Massol 2013). Such correla-
tions can be explained in three ways: fi rst, the other trait
can correlate with dispersal ability because there is a tradeoff
constraining the values of both traits (e.g. time allocation
Experimental studies are required to explore whether 2)
diff erent ecosystem functions are aff ected diff erently by
the movements of nutrients, detritus, primary produc-
ers, consumers, etc. Existing models suggest that disper-
sal asymmetries can do more than just alter source-sink
dynamics (Gounand et al. 2014) and existing experiments
point out possible eff ects of basal species dispersal on spe-
cies regulation processes (Howeth and Leibold 2008).
e general prediction that intermediate dispersal rates 3)
should stabilize meta-ecosystems has to be tested prop-
erly, both experimentally (but see Howeth and Leibold
2010, 2013), and based on large-scale observational data-
sets of abundance time series (following the approach of
Jacquet et al. 2016).
e idea of spatial complementarity between habitats 4)
within a meta-ecosystem needs to be assessed and experi-
mentally challenged. For instance, when ecosystems are
intrinsically limited by diff erent nutrients in diff erent
habitats (e.g. C in aquatic habitats versus N in terrestrial
ones), experiments are needed to assess whether interme-
diate (or high) spatial fl ows of biotic compartments lead
to higher productivity.
Experiments should test whether spatial structure and 5)
heterogeneity of supply points can lead to the stable
coexistence of species with diff erent resource ratios
(Mouquet et al. 2006, Marleau et al. 2015), possibly
exploring situations more complicated than two-patch,
two-species, two-resource systems.
eoretical studies are needed to explore how perturba-6)
tions propagate within a meta-ecosystem, depending on
which compartments are dispersing more, on connectiv-
ity patterns, on fi rst-disturbed compartments and on the
nature of the perturbation (invasion, extinction, habitat
destruction, etc.), following new perspectives on the
notion of stability in ecology (Arnoldi et al. 2016).
One promising theoretical endeavour would be to pre-7)
dict the impact of ecosystem removals on diversity and
functioning in a spatially explicit fashion, thus merging
models of Economo and Keitt (2008, 2010) on diversity
in metacommunity networks and Mouquet et al. (2013)
on keystone ecosystems.
Species coevolution models are highly needed to assess 8)
whether evolution leads to increases or decreases in
productivity, fl uxes, synchronicity, stability, etc. at the
meta-ecosystem scale, e.g. focusing on the evolution of
dispersal at diff erent trophic levels within food webs.
Models of ecosystem assembly and disassembly should 9)
be developed to assess the conditions of existence of
“ forks (i.e. alternative trajectories), “ dead-ends or
loops in the topology of ecosystem successions (Law and
Morton 1993).
Acknowledgements We thank D. Bonte for organizing this special
issue and allowing FM to present the idea of the paper at the Nordic
Oikos Society meeting in Turku, February 2016. We thank Dries
Bonte for insightful comments on an earlier version of the
Funding FM was supported by the CNRS and through the
ANR-funded project ARSENIC (ANR-14-CE02-0012). DG was
supported by the NSERC and the Canada Research Chair Program.
diff usion of one type of nutrient over another one due to a
systematic association of body stoichiometry with dispersal
Challenges ahead for meta-ecosystem ecology
e study both theoretical and empirical of mecha-
nisms linking organism dispersal and ecosystem properties
is a recent endeavour in ecology. To date, meta-ecosystem
ecology has focused on linking community ecology (spe-
cies coexistence, distribution of diversity), with ecological
dynamics and demographics (ecosystem stability, synchrony,
assembly), ecological interaction networks (network com-
plexity, material/energy fl uxes) and functional ecology
(stocks, fl uxes and productivity). However, two interfaces
have yet to be strengthened with respect to life-history traits
and meta-ecosystem properties.
First, the integration of biogeography and functional
ecology through meta-ecosystems has only begun to be
addressed (Wieters et al. 2008, Meynard et al. 2011, Kissling
et al. 2012, Nogales et al. 2016).  is interface between
meta-ecosystem ecology and biogeography is a necessary
step if we are to extend species distribution models and other
map-based representations of biodiversity to map-based rep-
resentations of ecosystem functioning and link these with
the underlying mechanisms involved. As life-history traits
play key roles in determining species response to anthropi-
cally driven changes of the environment (Lindborg 2007,
Colautti et al. 2010, Ojanen et al. 2013), life-history traits,
and dispersal in particular, will probably play a key role in
explaining spatial distribution of ecosystem functioning.
Second, we can ask whether variability in life-history
traits such as dispersal may entail direct consequences for
ecosystem properties. For instance, Laroche et al. (2016)
recently studied the evolution of dispersal in a model based
on Hubbell s (2001) neutral model of biodiversity to assess
whether species would converge or diverge in dispersal rate.
As it turned out, diversity patterns are strongly altered by
disruptive selection on dispersal (Laroche et al. 2016). Spec-
ulation linking these results with others from meta-ecosystem
models (Gounand et al. 2014) may lead us to think heteroge-
neous selection on dispersal rates among trophic levels could
drive eco-evolutionary feedbacks linking dispersal evolution
and ecosystem functioning.
Closing words: empirical and theoretical directions
We list here several important directions that deserve further
enquiry, both on the empirical and theoretical fronts. Meta-
ecosystem ecology and its interface with life-history studies
in particular need to be strengthened by making experi-
ments to test important meta-ecosystem predictions and by
developing meta-ecosystem models in directions that will
more strongly link them to life-history traits:
e maximization of ecosystem productivity at inter-1)
mediate dispersal has to be tested with respect to the
mechanisms maintaining coexistence of primary produc-
ers (Mouquet et al. 2002, but see Howeth and Leibold
2008), and the eff ect of dispersal asymmetries between
trophic levels on productivity (Gravel et al. 2010a) needs
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MAL was supported by NSF-DEB 1353919. NM was supported
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at the National Institute for Mathematical and Biological Synthesis,
sponsored by the National Science Foundation, the US Dept of
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  • ... Dispersal: 'the tendency of organisms to live, compete and reproduce away from their birth place' [41]. Habitat: in this paper used as synonymous of biotope, that is, a set of uniform environmental conditions. ...
    ... When focusing on how the spatial flows resulting from organismal movements affect recipient ecosystem dynamics, we distinguish two contrasting types of effects: consumer and resource effects (Table I). Dispersal, which implies settlement away from the place of birth of an organism [41], essentially conveys consumer effects by adding individuals to the recipient ecosystem ( Figure IA,E). The immigrants and their subsequent offspring, for instance Milu deer individuals recolonising Chinese forests [72], primarily exert a top-down pressure on local resources, even if their production of detritus might ultimately enrich recipient ecosystems. ...
    ... -ecosystem theory has extended the metacommunity framework with general models that include both dispersal and resource flows to connect ecosystems [13]. However, true dis- persal, defined as the settlement and successful reproduction of individuals away from their place of birth [1,40,41], can only occur between ecosystems offering similar enough physical habitats for the dispersing organism to survive in both. Clearly, many organisms have some adaptations to deal with variations in habitat conditions, and often can cope with what is considered -and built into models -as environmental heterogeneity. ...
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    The meta-ecosystem framework demonstrates the significance of among-ecosystem spatial flows for ecosystem dynamics and has fostered a rich body of theory. The high level of abstraction of the models, however, impedes applications to empirical systems. We argue that further understanding of spatial dynamics in natural systems strongly depends on dense exchanges between field and theory. From empiricists, more and specific quantifications of spatial flows are needed, defined by the major categories of organismal movement (dispersal, foraging, life-cycle, and migration). In parallel, the theoretical framework must account for the distinct spatial scales at which these naturally common spatial flows occur. Integrating all levels of spatial connections among landscape elements will upgrade and unify landscape and meta-ecosystem ecology into a single framework for spatial ecology.
  • ... The combined effects of HMD on the individual species in spatial networks will drive local community and ecosystem properties and, ultimately, those of metacommunities and meta- ecosystems [63]. First, in contrast to typical views that human impacts cause foodwebs to become more connected and less modular [64], we anticipate complex changes in local communities because both mutualisms and antagonisms are shaped by both lower and higher-order interactions. ...
    ... Here, the correlation between those traits of species promoting the likelihood of HVD, or the filtering effect of HAD, and those shaping interspecific interactions and ecological functions (e.g., body size) will condition the structural and functional consequences of HMD. Finally, we predict that HMD will change metaecosys- tem processes [63]. Again, depending on the human activities, we can predict different consequences. ...
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    Humans fundamentally affect dispersal, directly by transporting individuals and indirectly by altering landscapes and natural vectors. This human-mediated dispersal (HMD) modifies long-distance dispersal, changes dispersal paths, and overall benefits certain species or genotypes while disadvantaging others. HMD is leading to radical changes in the structure and functioning of spatial networks, which are likely to intensify as human activities increase in scope and extent. Here, we provide an overview to guide research into HMD and the resulting rewiring of spatial networks, making predictions about the ecological and evolutionary consequences and how these vary according to spatial scale and the traits of species. Future research should consider HMD holistically, assessing the range of direct and indirect processes to understand the complex impacts on eco-evolutionary dynamics.
  • ... As body size is central to both movement and resource consump- tion, its distribution in space and time is expected to have a strong impact on ecosystem stability, primary productivity, and biodiversity (Massol et al., 2017). Individuals in metapopulations or metacommu- nities function as mobile linkers that organize themselves in space to maximize their fitness according to their size ( Jeltsch et al., 2013). ...
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    Body size is a fundamental trait known to allometrically scale with metabolic rate and therefore a key determinant of individual development, life history, and consequently fitness. In spatially structured environments, movement is an equally important driver of fitness. Because movement is tightly coupled with body size, we expect habitat fragmentation to induce a strong selection pressure on size variation across and within species. Changes in body size distributions are then, in turn, expected to alter food web dynamics. However, no consensus has been reached on how spatial isolation and resource growth affect consumer body size distributions. Our aim was to investigate how these two factors shape the body size distribution of consumers under scenarios of size‐dependent and size‐independent consumer movement by applying a mechanistic, individual‐based resource–consumer model. We also assessed the consequences of altered body size distributions for important ecosystem traits such as resource abundance and consumer stability. Finally, we determined those factors that explain most variation in size distributions. We demonstrate that decreasing connectivity and resource growth select for communities (or populations) consisting of larger species (or individuals) due to strong selection for the ability to move over longer distances if the movement is size‐dependent. When including size‐dependent movement, intermediate levels of connectivity result in increases in local size diversity. Due to this elevated functional diversity, resource uptake is maximized at the metapopulation or metacommunity level. At these intermediate levels of connectivity, size‐dependent movement explains most of the observed variation in size distributions. Interestingly, local and spatial stability of consumer biomass is lowest when isolation and resource growth are high. Finally, we highlight that size‐dependent movement is of vital importance for the survival of populations or communities within highly fragmented landscapes. Our results demonstrate that considering size‐dependent movement is essential to understand how habitat fragmentation and resource growth shape body size distributions—and the resulting metapopulation or metacommunity dynamics—of consumers.
  • ... Finally, while current literature is often predicated on the assumption that dispersal is a fixed trait, convincing evidence shows that dispersal is a highly plastic trait that responds to numerous environmental and demographic cues (Clobert et al. 2009, Ronce and Clobert 2012, Bonte and Dahirel 2017, Massol et al. 2017). Termites, for instance, use an elaborated mechanism for detecting the frequency of vibro-acoustic signals to estimate the amount of food still available in their colonies (Evans et al. 2005), and as the amount of locally available resources becomes depleted, the number of alate primary reproductives increases ( Korb and Katrantzis 2004). ...
    Recent years have witnessed a growing interest in understanding the evolution of social behaviour in heterogeneous spatially structured populations. These studies, however, have neglected the impact of extinction–colonisation dynamics and ecological succession on the dynamical expression of social behaviour over time. Here, we present a kin‐selection model in which patches are structured into age‐classes. We show that ecological succession and patch age lead to highly plastic social phenotypes that vary dramatically as societies age since their initial establishment until their ultimate collapse. We find that the mode of colonisation following dispersal strongly influences the patch age‐dependent trajectories of social phenotypes. When patches are colonised by a random collection of immigrants, aggression is favoured during the build‐up of a society, but it slowly subsides until it eventually gives place to cooperation throughout the later stages of a society's lifespan. When newly established societies are formed by collectives of close relatives, cooperation is favoured during the build‐up of the society as well as when the society nears its eventual collapse. At intermediate societal ages, the genetic structure of the society is sufficiently resilient to the influx of immigrants such that cooperation remains relatively high. Moreover, we report a novel form of social terminal investment, whereby cooperative effort rises when patches approach their collapse. When dispersal is allowed to co‐evolve with cooperation, we observe a sudden rise in dispersal phenotypes before a patch's collapse, and the surprising result that clonal colonisation does not yield significantly higher levels of cooperation than the individual mode of colonisation. More generally, our results show that ecological succession strongly determines the dynamics of kin selection after colonisation, and therefore we expect that these findings will be valuable for understanding behavioural syndromes during range expansion or biological invasions. This article is protected by copyright. All rights reserved.
  • ... ve studies to test hypotheses on life history and eco-evolutionary dynamics in light of the gut microbiota are provided. Finally, from a spatial perspective, dispersal will as a central trait in life history, affect properties of meta-ecosystems. Source–sink dynamics, community assembly and ecosystem stability are all modified by spatial structure.Massol et al. (2017)provide an overview of recent theoretical and empirical studies that link ecosystem functioning and dynamics to species dispersal. They highlight that many relevant ecosystem properties can be linked to a single life history trait, dispersal. Areas that deserve further empirical and theoretical advances are put forward. The importance of ...
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    • From a metacommunity perspective, patterns of β‐diversity emerge from the interplay between spatial and environmental processes. For obligate aquatic dispersers, river network constraints can be reflected in diversity patterns. • Here, we aimed to determine the effects of environmental heterogeneity and spatial connectivity on β‐diversity components. We sampled fish assemblages in 21 sites across a longitudinal gradient. Beta‐diversity for taxonomic and functional composition among sites was decomposed into its turnover and nestedness components. We investigated whether environment was more important to functional β‐diversity and spatial factors had a higher contribution to dissimilarity in species composition. Further, we tested whether environmentally homogeneous sites with higher spatial connectivity showed lower compositional changes. • We found that spatial factors were more important for taxonomic β‐diversity, whereas environment explained functional dissimilarity among habitats. Although environment and spatial factors contribute to total β‐diversity, they explained different components: while environment explained a higher portion of turnover, spatial factors were related to nestedness. The effects of mere spatial isolation and directional connectivity differed for species and functional β‐diversity and for the components of β‐diversity. Including directionality in spatial connectivity enabled the explanation of a higher proportion of variation of total species β‐diversity and its turnover. • Our results suggest that niche and spatial processes may influence differently taxonomic and functional β‐diversity components. Thus, habitat filtering was the primary mechanism affecting functional diversity and species turnover, whereas spatial connectivity drove species nestedness.
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    Large terrestrial consumers have direct and indirect effects on forest ecosystem function, but few studies have investigated the impacts of terrestrial consumers on freshwater ecosystems. In the Cape Breton Highlands of Nova Scotia, browsing by hyper‐abundant moose following a spruce budworm outbreak has transformed boreal forest into grasslands. We conducted a field study to investigate the potential for cross‐ecosystem effects of hyper‐abundant moose following budworm outbreak on small boreal stream ecosystem structure and function. With our field study, we tested the prediction that watersheds with higher levels of moose‐mediated grasslands in their sub‐basin would have higher stream temperatures, total nitrogen, electrical conductivity, periphyton biomass and macroinvertebrate abundances. While our data supported several of our predictions pertaining to moose impacts on the abiotic variables (i.e. temperature range, total nitrogen, electrical conductivity) we found evidence of variable moose impacts on the benthic community. Specifically, we observed lower relative abundance of predatory invertebrates in streams with high moose impacts compared to streams with low moose impacts in their watersheds but no evidence of moose impacts on the relative abundance of shredders, filterers, gatherers, and grazers. This empirical study fills a key gap in our understanding of spatial ecosystem ecology by providing insight into the effects of large terrestrial consumers across ecosystem boundaries with potential implications for landscape‐scale management of hyper‐abundant ungulates. Given the broad availability and improvement in remote sensing technology, the novel integration of remote sensing and field studies employed here may provide a roadmap for future studies of meta‐ecosystem dynamics. This article is protected by copyright. All rights reserved.
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    An individual's body size is central to its behaviour and physiology, and tightly linked to its movement ability. The spatial arrangement of resources and a consumer's capacity to locate them are therefore expected to exert strong selection on consumer body size. We investigated the evolutionary impact of both the fragmentation and loss of habitat on consumer body size and its feedback effects on resource distribution, under varying levels of information used during habitat choice. We developed a mechanistic, individual-based, spatially explicit model, including several allometric rules for key consumer traits. Our model reveals that as resources become more fragmented and scarce, informed habitat choice selects for larger body sizes while random habitat choice promotes small sizes. Information use may thus be an overlooked explanation for the observed variation in body size responses to habitat fragmentation. Moreover, we find that resources can accumulate and aggregate if information about resource abundance is incomplete. Informed movement results in stable resource-consumer dynamics and controlled resources across space. However, habitat loss and fragmentation destabilize local dynamics and disturb resource suppression by the consumer. Considering information use during movement is thus critical to understand the eco-evolutionary dynamics underlying the functioning and structuring of consumer communities.
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    Most spatial ecology focuses on how species dispersal affects community dynamics and coexistence. Ecosystems, however, are also commonly connected by flows of resources. We experimentally tested how neighbouring communities indirectly influence each other in absence of dispersal, via resource exchanges. Using two-patch microcosm meta-ecosystems, we manipulated community composition and dynamics, by varying separately species key functional traits (autotroph versus heterotroph species and size of consumer species) and trophic structure of aquatic communities (species growing alone or in presence of competitors or predators). We then analysed the effects of species functional traits and trophic structure on communities connected through spatial subsidies in the absence of actual dispersal. Both functional traits and trophic structure strongly affected dynamics across neighbouring communities. Heterotroph communities connected to autotroph neighbours developed better than with heterotroph neighbours, such that coexistence of competitors was determined by the functional traits of the neighbouring community. Densities in autotroph communities were also strikingly higher when receiving subsidies from heterotroph communities compared to their own subsidies when grown in isolated ecosystems. In contrast, communities connected to predator-dominated ecosystems collapsed, without any direct contact with the predators. Our results demonstrate that because community composition and structure modify the distribution of biomass within a community, they may also affect communities connected through subsidies through quantitative and qualitative changes of detritus flows. This stresses that ecosystem management should account for such interdependencies mediated by spatial subsidies, given that local community alterations cascade across space onto other ecosystems even if species dispersal is completely absent. This article is protected by copyright. All rights reserved.
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    To understand why and how species invade ecosystems, ecologists have made heavy use of observations of species colonization on islands. The theory of island biogeography, developed in the 1960s by R.H. MacArthur and E.O. Wilson, has had a tremendous impact on how ecologists understand the link between species diversity and characteristics of the habitat such as isolation and size. Recent developments have described how the inclusion of information on trophic interactions can further inform our understanding of island biogeography dynamics. Here, we extend the trophic theory of island biogeography to assess whether certain food web properties on the mainland affect colonization/extinction dynamics of species on islands. Our results highlight that both food web connectance and size on the mainland increase species diversity on islands. We also highlight that more heavily tailed degree distributions in the mainland food web correlate with less frequent but potentially more important extinction cascades on islands. The average shortest path to a basal species on islands follows a hump-shaped curve as a function of realized species richness, with food chains slightly longer than on the mainland at intermediate species richness. More modular mainland webs are also less persistent on islands. We discuss our results in the context of global changes and from the viewpoint of community assembly rules, aiming at pinpointing further theoretical developments needed to make the trophic theory of island biogeography even more useful for fundamental and applied ecology.
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    Most spatial ecology focuses on how species dispersal affects community dynamics and coexistence. Ecosystems, however, are also commonly connected by flows of resources. We experimentally tested how neighbouring communities indirectly influence each other in absence of dispersal, via resource exchanges. Using two-patch microcosm meta-ecosystems, we manipulated community composition and dynamics, by varying separately species key functional traits (autotroph versus heterotroph species and size of consumer species) and trophic structure of aquatic communities (species growing alone or in presence of competitors or predators). We then analysed the effects of species functional traits and trophic structure on communities connected through spatial subsidies in the absence of actual dispersal. Both functional traits and trophic structure strongly affected dynamics across neighbouring communities. Heterotroph communities connected to autotroph neighbours developed better than with heterotroph neighbours, such that coexistence of competitors was determined by the functional traits of the neighbouring community. Densities in autotroph communities were also strikingly higher when receiving subsidies from heterotroph communities compared to their own subsidies when grown in isolated ecosystems. In contrast, communities connected to predator-dominated ecosystems collapsed, without any direct contact with the predators. Our results demonstrate that because community composition and structure modify the distribution of biomass within a community, they may also affect communities connected through subsidies through quantitative and qualitative changes of detritus flows. This stresses that ecosystem management should account for such interdependencies mediated by spatial subsidies, given that local community alterations cascade across space onto other ecosystems even if species dispersal is completely absent. This article is protected by copyright. All rights reserved.
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    The study of tradeoffs among major life history components (age at maturity, lifespan and reproduction) allowed the development of a quantitative framework to understand how environmental variation shapes patterns of biodiversity among and within species. Because every environment is inherently spatially structured, and in most cases temporally variable, individuals need to move within and among habitats to maximize fitness. Dispersal is often assumed to be tightly integrated into life histories through genetic correlations with other vital traits. This assumption is particularly strong within the context of a fast-slow continuum of life-history variation. Such a framework is to date used to explain many aspects of population and community dynamics. Evidence for a consistent and context-independent integration of dispersal in life histories is, however, weak. We therefore advocate the explicit integration of dispersal into life history theory as a principal axis of variation influencing fitness, that is free to evolve, independently of other life history traits. We synthesize theoretical and empirical evidence on the central role of dispersal and its evolutionary dynamics on the spatial distribution of ecological strategies and its impact on population spread, invasions and coexistence. By applying an optimality framework we show that the inclusion of dispersal as an independent dimension of life histories might substantially change our view on evolutionary trajectories in spatially structured environments. Because changes in the spatial configuration of habitats affect the costs of movement and dispersal, adaptations to reduce these costs will increase phenotypic divergence among and within populations. We outline how this phenotypic heterogeneity is anticipated to further impact population and community dynamics. This article is protected by copyright. All rights reserved.
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    Ecosystems are linked to neighbouring ecosystems not only by dispersal, but also by the movement of subsidy. Such subsidy couplings between ecosystems have important landscape-scale implications because perturbations in one ecosystem may affect community structure and functioning in neighbouring ecosystems via increased/decreased subsidies. Here, we combine a general theoretical approach based on harvesting theory and a two-patch protist meta-ecosystem experiment to test the effect of regional perturbations on local community dynamics. We first characterized the relationship between the perturbation regime and local population demography on detritus production using a mathematical model. We then experimentally simulated a perturbation gradient affecting connected ecosystems simultaneously, thus altering cross- ecosystem subsidy exchanges. We demonstrate that the perturbation regime can interact with local population dynamicsto trigger unexpected temporal variations in subsidy pulses from one ecosystem to another. High perturbation intensity initially led to the highest level of subsidy flows; however, the level of perturbation interacted with population dynamics to generate a crash in sub- sidy exchange over time. Both theoretical and experimental results show that a perturbation regime interacting with local community dynamics can induce a collapse in population levels for recipient ecosystems. These results call for inte- grative management of human-altered landscapes that takes into account regional dynamics of both species and resource flows.
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    The diversity of life and its organization in networks of interacting species has been a long-standing theoretical puzzle for ecologists. Ever since May’s provocative paper challenging whether ‘large complex systems [are] stable’ various hypotheses have been proposed to explain when stability should be the rule, not the exception. Spatial dynamics may be stabilizing and thus explain high community diversity, yet existing theory on spatial stabilization is limited, preventing comparisons of the role of dispersal relative to species interactions. Here we incorporate dispersal of organisms and material into stability–complexity theory. We find that stability criteria from classic theory are relaxed in direct proportion to the number of ecologically distinct patches in the meta-ecosystem. Further, we find the stabilizing effect of dispersal is maximal at intermediate intensity. Our results highlight how biodiversity can be vulnerable to factors, such as landscape fragmentation and habitat loss, that isolate local communities.
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    Understanding the mechanisms responsible for stability and persistence of ecosystems is one of the greatest challenges in ecology. Robert May showed that, contrary to intuition, complex randomly built ecosystems are less likely to be stable than simpler ones. Few attempts have been tried to test May's prediction empirically, and we still ignore what is the actual complexity–stability relationship in natural ecosystems. Here we perform a stability analysis of 116 quantitative food webs sampled worldwide. We find that classic descriptors of complexity (species richness, connectance and interaction strength) are not associated with stability in empirical food webs. Further analysis reveals that a correlation between the effects of predators on prey and those of prey on predators, combined with a high frequency of weak interactions, stabilize food web dynamics relative to the random expectation. We conclude that empirical food webs have several non-random properties contributing to the absence of a complexity–stability relationship.
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    There has been a recent rise in the number of experiments investigating the effect of dispersal on diversity, with many of the predictions for these tests derived from metacommunity theory. Despite the promise of linking observed relationships between dispersal and diversity to underlying metacommunity processes, empirical studies have faced challenges in providing robust tests of theory. We review experimental studies that have tested how dispersal affects metacommunity diversity to determine why shortcomings emerge, and to provide a framework for empirical tests of theory that capture the processes structuring diversity in natural metacommunities. We first summarize recent experimental work to outline trends in results and to highlight common methods that cause a misalignment between empirical studies and the processes described by theory. We then identify the undesired implications of three widely used experimental methods that homogenize metacommunity structure or species traits, and present alternative methods that have been used to successfully integrate experiments and theory in a biologically relevant way. Finally, we present methodological and theoretical insights from three related ecological fields (coexistence, food web and priority effects theory) that, if integrated into metacommunity experiments, could help isolate the independent and joint effects of local interactions and dispersal on diversity, and reveal the mechanisms underlying observed dispersal–diversity patterns. Together, these methods can provide stronger tests of existing theory and stimulate new theoretical explorations.
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    Networks composed of distinct, densely connected subsystems are called modular. In ecology, it has been posited that a modular organization of species interactions would benefit the dynamical stability of communities, even though evidence supporting this hypothesis is mixed. Here we study the effect of modularity on the local stability of ecological dynamical systems, by presenting new results in random matrix theory, which are obtained using a quaternionic parameterization of the cavity method. Results show that modularity can have moderate stabilizing effects for particular parameter choices, while anti-modularity can greatly destabilize ecological networks.