Introduction
The factors driving global scale patterns in ecological community
structure are becoming increasingly well-known, with elevation, latitude
and anthropogenic disturbances playing major roles (Nash et al In press;
Romero et al 2020). However, because all organisms within an ecosystem
are closely interconnected, variation in the distribution of a
particular species in relation to the environment can also affect the
species with which it interacts (Forister et al., 2012). In particular,
a mechanistic understanding of how human activities alter the structure
of ecological networks would be timely. This is because our world is
facing accelerated anthropogenic changes, such as global warming, which
causes species to move to higher latitudes and elevations (Franco et
al., 2006; Memmott et al., 2007), and habitat disturbance, resulting in
global diversity declines (Newbold et al., 2015). This variation in
community structure is reflected in the structure of interaction
networks, with consequences for multiple vital ecosystem services such
as pest control (Macfadyen et al., 2011), fish stock production (Moi et
al. 2022) and pollination (Burkle & Alarcón, 2011). Furthermore,
current network structure predicts ongoing robustness to future natural
and human-induced perturbations (Morton et al., 2022).
One of the most fundamental parameters used to quantify variation in
network structure is ecological network specialisation (Dormann et al.,
2008; Bascompte et al., 2003). The interaction between two groups can
range from specialized, where a species interacts with a small subset of
available partners and is more vulnerable to change and extinction, to
generalized, where a species is less discriminate and interacts with a
wide range of partners and is therefore predicted to be more resilient
to change (Futuyma & Moreno., 1988).Most studies of network
specialisation fall into one of two broad categories: (i) Those that
compare different network types, such as different guilds, taxa, or
trophic levels without accounting for environmental variation (Blüthgen
et al., 2007; Cagnolo & Tavella, 2015, Guimarães et al., 2007), and
(ii) Those that examine specialisation in a specific network type across
environmental gradients, for example in relation to anthropogenic
habitat disturbances or latitude (Schleuning et al., 2012; Gorostiague
et al., 2023; Olesen & Jordano 2003; Luna et al., 2022). Studies from
the former category generally reach consistent conclusions, for example,
that pollinator networks are more specialized than seed dispersal
networks (Blüthgen et al., 2007). However, in the latter category
results are often inconsistent between studies, sometimes depending on
network size, taxonomic scope and/or geographical range of networks
employed. For example, some plant-pollinator systems are more
specialized in the tropics (Gorostiague et al., 2023), while others have
been found to be more specialized in temperate regions (Schleuning
2012). The specialisation of plant pollinators on plant species has been
reported to increase with elevation on islands (Olesen & Jordano,
2003), while a recent global analysis concluded that latitude and
elevation did not play a role in explaining the degree of pollinator
specialisation (Luna et al., 2022). As different network types can
interact with environmental gradients in a complex way, the simultaneous
evaluation of by drivers of specialisation is currently needed.
The application of different methods across different studies for
measuring network specialisation, some of which may be confounded by
other aspects of network structure (e.g. network size, network
connectance), means that global-scale patterns in specialisation remain
unclear (Pellissier et al., 2018). The classical method for measuring
specialisation at the network level, the H2’ index, is
based on the deviation from the expected probability distribution of
interaction frequencies between species (Blüthgen et al., 2006).
However, networks of different sizes, involving different numbers of
species and links, can vary in the observed value of H2’
regardless of specialisation (Blüthgen et al., 2008). One way to
overcome this shortcoming is to compare observed values of
H2’ to the distribution resulting from repeated
randomisation of the original network (Dormann at al., 2009). This
approach can generate a standardised effect size that is less affected
by other aspects of network structure (H2’ z-score;
Ulrich et al., 2009). Specialisation can also be affected by
availability of partner species, in particular those that are closely
phylogenetically related (Segar et al., 2020). The distance
specialisation index (dsi*) allows incorporation of phylogenetic
relationships and species abundances when quantifying specialisation
(Jorge et al., 2014; 2017). However, the degree to which phylogenetic
relatedness of resources determines consumer specialisation in networks
at large spatial scales is currently unknown. Such phylogenetic signals
in the interactions between species within the network are likely the
result of reciprocal coevolution or long-term adaptation of consumer
species to traits of resource species (Guimaraes et al, 2007). For
example, common milkweed (Asclepias syriaca ) produces chemical
defensive compounds that only a small number of closely related
herbivorous beetle can tolerate (Rasmann & Agrawal, 2011). A specialist
may interact with a suite of closely related resource species because
these are more likely to have the traits to which the consumer has
adapted (Rasmann & Agrawal, 2011). Hence there is a need to explore how
specialisation changed over the gradient of latitude and elevation, and
the presence of disturbance, as well as how phylogenetic relatedness of
the consumer or host influences these patterns.
Interactions between ants and plants provide a suitable system for
exploring changes in network specialisation along environmental
gradients. Ant-plant interactions are widespread and involve discrete
interaction types with varying degrees of specialisation (Ness & Lach,
2010) that are easily categorised. Furthermore, ant-plant systems are
well-studied, making a data collation and meta-analytical approach
tenable. Finally, there are well-resolved phylogenies for both groups,
allowing exploration of degree of phylogenetic specialisation in
networks. Ant-plant interactions range from obligate symbiotic
mutualisms such as those between myrmecophytic plants and their
long-term ant partners, to non-symbiotic facultative interactions such
as myrmecophily and myrmecochory (Heil & McKey, 2003), to less specific
interactions in which ants opportunistically forage on plants (Rico-Gray
& Oliveira, 2007). We define the myrmecophytic interactions as those in
which domatia are formed on plants to provide shelter for ants.
Myrmecophilic interactions, are those in which extrafloral nectaries and
fruiting bodies are produced by plants as a food source for ants, but
plants do not provide domatia as nest sites. Note that some domatia
bearing plants also provide extrafloral nectar and food bodies, but we
nonetheless classify these as myrmecophytes. Myrmecochorous interactions
are those in which ants help plants disperse seeds in exchange for food
(Heil & McKey, 2003). Finally, plants can provide a space for foraging
and patrolling without any apparent evolved mutualism, which we define
here as “foraging” interactions (Rico-Gray & Oliveira, 2007).
Although the specialisation drivers in local ant-plant networks have
been studied extensively (Juárez-Juárez et al., 2023) commonality of
patterns at global scales remains unclear. Myrmecophytic interactions
tend to be more specialized than other kinds of ant-plant interactions,
such as myrmecophily, seed dispersal (Blüthgen et al., 2007), and
frugivory (Guimaraes et al., 2007), presumably driven by tighter
co-evolution due to the greater intimacy of the interaction (Pires &
Guimaraes, 2013). These myrmecophytic networks become less specialised
with increasing elevation (Plowman et al., 2017) and anthropogenic
disturbance (Emer et al., 2013), probably due to loss of partner
species. However, they appear to be robust to forest fragmentation
(Passmore, 2012). Yet, it is currently unknown how specialisation of
myrmecophytic networks varies with latitude. Interestingly,
myrmecophilic networks show levels of specialisation similar to
ant-lepidopteran networks (Cagnolo & Tavella, 2015), perhaps because
ants are provided with carbohydrate-rich liquid food by plants and
lepidopteran larvae respectively in these cases. Interactions in which
ant workers forage on plants, but are not involved in mutualisms, are
expected to show lower specialisation than other interaction types,
although this has not been directly studied. The specialisation of such
foraging networks does not change along a 20° range in latitude (Dáttilo
& Vasconcelos 2019), although specialisation is reduced following
anthropogenic forest disturbance (Corro et al., 2019). Hence, whether
different types of interaction between these two ecologically important
groups show common responses to latitude, elevation and anthropogenic
disturbance remains unclear.
We collated globally distributed network data and used a meta-analytical
approach to determine how the specialisation of ant-plant networks
varies with interaction type (myrmecophytic, myrmecophilic,
myrmecochorous, and foraging), anthropogenic disturbance, latitude, and
elevation at global scales, including interactive effects between these
predictors. We predicted that myrmecophytic interactions would be the
most specialised as these involve tight co-evolutionary adaptations
between partners, followed by myrmecophilic, myrmecochorous, and
foraging. We also predicted that ant-plant specialisation will decrease
with increasing latitude, elevation, and anthropogenic disturbance due
to the scarcity of resources in these areas (Brown, 2014).