Trait matching and sampling effort shape the structure of the frugivory network in Afrotropical forests

Abstract

Summary Frugivory in tropical forests is a major ecological process as most tree species rely on frugivores to disperse their seeds. However, the underlying mechanisms driving frugivore–plant networks remain understudied. Here, we evaluate the data available on the Afrotropical frugivory network to identify structural properties, as well as assess knowledge gaps. We assembled a database of frugivory interactions from the literature with > 10 000 links, between 807 tree and 285 frugivore species. We analysed the network structure using a block model that groups species with similar interaction patterns and estimates interaction probabilities among them. We investigated the species traits related to this grouping structure. This frugivory network was simplified into 14 tree and 14 frugivore blocks. The block structure depended on the sampling effort among species: Large mammals were better‐studied, while smaller frugivores were the least studied. Species traits related to frugivory were strong predictors of the species composition of blocks and interactions among them. Fruits from larger trees were consumed by most frugivores, and large frugivores had higher probabilities to consume larger fruits. To conclude, this large‐scale frugivory network was mainly structured by species traits involved in frugivory, and as expected by the distribution areas of species, while still being limited by sampling incompleteness.

Linking network ecology and ecosystem services to benefit people

“…Local and indigenous knowledge has also been channelled into network studies, for example, seed networks (Labeyrie et al., 2023) or plant ecosystem service knowledge networks (Cámara‐Leret et al., 2019; Tengö et al., 2014). However, only a small number of studies have used local and indigenous ecological knowledge to construct species interactions networks (Durand‐Bessart et al., 2023; Hawes & Peres, 2014; Ong et al., 2021; Pereyra et al., 2023), with none directly relating these ecological networks to the benefits they provide to the local or indigenous community.…”

“…For example, in a recent study by Durand‐Bessart et al. (2023) investigating frugivory networks in Gabon, 2382 interactions were identified by local communities over 41 days of interviews. This was comparable to a dataset founded on 41,234 days of fieldwork which contained 2666 interactions, requiring over 1000 times as many research hours for only 0.12% greater number of interactions (Durand‐Bessart et al., 2023).…”

“…(2023) investigating frugivory networks in Gabon, 2382 interactions were identified by local communities over 41 days of interviews. This was comparable to a dataset founded on 41,234 days of fieldwork which contained 2666 interactions, requiring over 1000 times as many research hours for only 0.12% greater number of interactions (Durand‐Bessart et al., 2023). The information provided by local and indigenous ecological knowledge can then identify critical components of networks that represent the flow of ecosystem services in a local context.…”

“…Species interactions reported through local and indigenous ecological knowledge have been carefully observed, and those observations passed on through cultural practice, enhancing our knowledge of ecosystem functions (Durand‐Bessart et al., 2023; Hawes & Peres, 2014; Ong et al., 2021; Pereyra et al., 2023). Nevertheless, it is important to consider that there may still be reporting bias toward cooccurrences and the most abundant or culturally valued species and the most pronounced interactions being observed most frequently (Ong et al., 2021), thus missing important information associated with rare interactions (Lyons et al., 2005; Pocock et al., 2012).…”

“…Furthermore, by focusing on the behaviour of species interacting, the relevance of ecological interactions reported and subsequent output for management decision making can be maximised, for example, referencing specific behaviours that infer successful seed dispersal when engaging with interview or workshop participants (see Ong et al., 2021). Local and indigenous ecological knowledge can also be combined with other data, such as observations of subsets of interactions (Song et al., 2023) or existing datasets and literature, to co‐produce information to identify interaction network components and structure, potentially increasing the resolution of network output informing ecosystem service management (Copete et al., 2023; Durand‐Bessart et al., 2023; Ong et al., 2021; Pereyra et al., 2023; Quintero et al., 2022; Tengö et al., 2014). Combining sampling techniques is known to affect network topology and structure, which may limit the effective incorporation of multiple types of data in interaction networks (Brimacombe et al., 2023; Durand‐Bessart et al., 2023).…”