Data collection
We followed PRISMA protocol in defining our research questions,
conducting data collection, and also in reporting our results using a
standardised approach (O’Dea et al., 2021). This was done to minimise
potential biased associated with meta-analyses. We include a check list
in which our studies followed the PRISMA protocol in our supplementary
data (appendix 1) Our meta-analytical approach involved quantification
of network patterns through collation of original data, and calculation
of network metric using those data, rather than through collation of
effect sizes from previous studies (Xing & Fayle, 2021). This
manuscript is part of the LifeWebs project, a collaborative effort that
aims to use a meta-analytic approach to investigate how interaction
networks respond to global-scale environmental gradients
(www.lifewebs.net). We collated
existing ant-plant interaction networks by searching for publications on
the Web of Science (WoS) online database. These published datasets were
supplemented by direct requests to authors of papers in which the data
had not been published, and furthermore through requests to data authors
identified through snowballing (see below). We excluded datasets in
which the links between ant and plant species were not available (i.e.
where we were unable to build a bipartite network). The use of a single
search engine may have led to some studies being missed but allowed us
to focus on high quality network in a systematic manner. Data collection
activities were carried out throughout 2021, with no date limits
imposed. We searched the Web of Science database using the keywords
”ant-plant interaction” and then refine this search using the additional
keywords, ”extrafloral nectaries” (EFN) OR ”food bodies” (FB), OR
”myrmecophily”, OR “Co-occurrence”, OR ”ant-plant foraging,” OR
”myrmecochory”. We only selected networks that consisted of at least
three plant species and at least three ant species. We excluded networks
that consisted of only presence/absence data, as analyses on binary data
are more sensitive to sampling effort (Miranda et al., 2019), which
varied between studies in our collated data. We also excluded networks
collated from museum collections because these were not quantitative and
often lacked geographical data. Lastly, we excluded studies that pooled
ant-plant data across a whole region or country, for example,Macaranga spp. and Crematogaster spp. in Southeast Asia
(Fiala et al., 1999). Where necessary, we contacted authors to provide
metadata. In some cases, additional more recent data (post-2021) were
contributed to the network as a result. In addition, we conducted a
snowball search by identifying relevant references in all collated data
papers. Our decision tree for including/excluding network is presented
in Figure 1. It has to be noted that our studies has some geographical
limitation as there are not many studies in Africa fulfil our criteria.
Our protocol resulted in a total of 74 ant-plant interaction networks.
These included 18 myrmecophytic, 17 myrmecophilic, 14 myrmecochorous,
and 25 foraging networks. The networks spanned an absolute latitudinal
range of 1.8° to 49° and an elevational range from 4 m to 2800 m above
sea level (asl) with 41 networks in undisturbed areas, and 33 networks
in disturbed areas (Figure 2 & 3). In some cases, the network data were
not published with the corresponding paper and the author did not
respond to our request. Hence these networks were excluded. However,
since these occurrences were a minority (10 / 74) we believe our
collated networks represent a substantial proportion of those available.
We classified the networks into four types: (i) myrmecophytic :
networks where plants provide nesting space (domatia) for ants; (ii)myrmecophilic : networks where plants offer food to ants
(extrafloral nectaries (EFN) and food bodies (FB) but without domatia);
(iii) myrmecochorous : networks involving ant dispersal of plant
seeds, or ant consumption of fruits; (iv) foraging : networks in
which interactions between ants and plants were recorded, with ants
being found foraging on plants, but without utilising any plant-provided
resources. Latitude, elevation, and presence/absence of anthropogenic
disturbance were recorded as metadata for each network. If elevation was
not included in the article or provided by the author, we determined
this from the geographic coordinates in the study site description using
google earth (elevation determined in this way for 9 of 74 networks). If
the elevational range across multiple sites within a study was less than
300 meters, we combined these sites into a single network and used the
mean elevation value (14 of 74 networks resulted from such merging).
Where sites within a study were > 300 m apart in terms of
elevation we retained the data as multiple separate networks (10 of 74
networks). In these cases, study identity was retained as a random
factor in all models, to account for greater similarity in sampling
effort and methodology within studies than between studies. Each network
was classified as being in either anthropogenically disturbed (gardens,
recently cut secondary forests or production forests) or undisturbed
(primary forests or nature reserves), based on the original study
description. We combined different kinds of disturbed habitats into one
category because sample sizes for finer grained categories were not
large enough for statistical analyses. Finally, we updated the species
names of plants using taxize in R with the gbif database
(https://www.gbif.org/), accessed
January 2022. We manually fixed typos when names were classified as
“fuzzy” according to taxsize and rechecked the updated
plant names on the WFO database
(http://www.worldfloraonline.org/)
when names were classified as “doubtful “ Meanwhile, ant
taxonomic names were checked manually using the AntWeb
(https://www.antweb.org/) and
AntWiki databases
(https://www.antwiki.org/),
accessed July 2022. We mapped the network sampling locations using QGIS
3.16.15 to visualize the distribution of our sites. We also chose the
network with the median species richness from each interaction type to
visualize the differences in structure across each network type. These
networks were plotted using the plotweb function in thebipartite package.