Influence of taxonomic resolution on mutualistic network properties

1. Ecologists are increasingly interested in plant–pollinator networks that synthesize in a single object the species and the interactions linking them within their ecological context. Numerous indices have been developed to describe the structural properties and resilience of these networks, but currently, these indices are calculated for a network resolved to the species level, thus preventing the full exploitation of numerous datasets with a lower taxonomic resolution. Here, we used datasets from the literature to study whether taxonomic resolution has an impact on the properties of plant–pollinator networks.
2. For a set of 41 plant–pollinator networks from the literature, we calculated nine network index values at three different taxonomic resolutions: species, genus, and family. We used nine common indices assessing the structural properties or resilience of networks: nestedness (estimated using the nestedness index based on overlap and decreasing fill [NODF], weighted NODF, discrepancy [BR], and spectral radius [SR]), connectance, modularity, robustness to species loss, motifs frequencies, and normalized degree.
3. We observed that modifying the taxonomic resolution of these networks significantly changes the absolute values of the indices that describe their properties, except for the spectral radius and robustness. After the standardization of indices measuring nestedness with the Z‐score, three indices—NODF, BR, and SR for binary matrices—are not significantly different at different taxonomic resolutions. Finally, the relative values of all indices are strongly conserved at different taxonomic resolutions.
4. We conclude that it is possible to meaningfully estimate the properties of plant–pollinator interaction networks with a taxonomic resolution lower than the species level. We would advise using either the SR or robustness on untransformed data, or the NODF, discrepancy, or SR (for weighted networks only) on Z‐scores. Additionally, connectance and modularity can be compared between low taxonomic resolution networks using the rank instead of the absolute values.

     

A waterfowl seed-dispersal network from the Neotropical region is nested and modular

Seed dispersal by vertebrates is fundamental for the persistence of plant species, forming networks of interactions that are often nested and modular. Networks involving angiosperms and frugivorous birds are relatively well-studied in the Neotropical region, but there are no previous studies of networks involving waterbirds. Here, we describe the structure of a Neotropical waterfowl seed-dispersal network and identify the species that have an important role for the network structure. We used information on 40 plant taxa found in fecal samples of five common waterfowl species to calculate the nestedness (NODF), weighted nestedness (WNODF), modularity, and weighted modularity of the network. We found that the network was nested, with yellow-billed teal showing the highest contribution both to nestedness and weighted nestedness. Twenty-four plant species contributed positively to weighted nestedness, with Salzmann's mille graines presenting the highest influence both to nestedness and weighted nestedness. The network was modular, but the weighted modularity was not significant. These results need to be considered with caution due to incomplete interaction sampling for two species. Ringed teal, Brazilian teal, and yellow-billed teal were considered hub modular species. Among plants, beak sedges and water snowflake were considered modular hub species, while Salzmann's mille graines and spikerush were network connectors. The structure of this Neotropical waterbird seed-dispersal network differed from the only previous waterfowl network study, from Europe, which found similar level of nestedness but no significant modularity. We include several possible explanations for this discrepancy and identified priorities for future research into waterbird–plant interaction networks. Abstract in Portuguese is available with online material.     

Food web structure changes with elevation but not rainforest stratum

Changes in species richness along elevational gradients are well documented. However, little is known about how trophic interactions between species and, in particular, the food webs that these interactions comprise, change with elevation. Here we present results for the first comparison of quantitative food webs in forest understorey and canopy along an elevational gradient. Replicate quantitative food webs were constructed for assemblages involving 23 species of cavity‐nesting Hymenoptera and 12 species of their parasitoids and kleptoparasites in subtropical rainforest in Australia. A total of 1589 insects were collected using trap nests across 20 plots distributed at sites ranging from 300 to 1100 m a.s.l. Insect abundance, insect diversity and parasitism rate generally decreased with increasing elevation. Food web structure significantly changed with elevation. In particular, weighted quantitative measures of linkage density, interaction evenness, nestedness (weighted NODF) and potential for enemy mediated interactions (PAC) decreased with increasing elevation, and network specialisation (H₂′) increased with increasing elevation, even after controlling for matrix size; but there was no change in weighted connectance. Changes in forest type and temperature along the elevational gradient are likely to be, at least partly, responsible for the patterns observed. We found no significant differences in insect abundance, insect diversity or parasitism rate between canopy and understorey. Furthermore, there were no differences in food web structure between strata. These results contribute further evidence to studies revealing changes in food web structure along natural environmental gradients and provide information that can potentially be used for predicting how communities may respond to climate change.     

Interaction network of vascular epiphytes and trees in a subtropical forest

The commensalistic interaction between vascular epiphytes and host trees is a type of biotic interaction that has been recently analysed with a network approach. This approach is useful to describe the network structure with metrics such as nestedness, specialization and interaction evenness, which can be compared with other vascular epiphyte-host tree networks from different forests of the world. However, in several cases these comparisons showed different and inconsistent patterns between these networks, and their possible ecological and evolutionary determinants have been scarcely studied. In this study, the interactions between vascular epiphytes and host trees of a subtropical forest of sierra de San Javier (Tucuman, Argentina) were analysed with a network approach. We calculated metrics to characterize the network and we analysed factors such as the abundance of species, tree size, tree bark texture, and tree wood density in order to predict interaction frequencies and network structure. The interaction network analysed exhibited a nested structure, an even distribution of interactions, and low specialization, properties shared with other obligated vascular epiphyte-host tree networks with a different assemblage structure. Interaction frequencies were predicted by the abundance of species, tree size and tree bark texture. Species abundance and tree size also predicted nestedness. Abundance indicated that abundant species interact more frequently; and tree size was an important predictor, since larger-diameter trees hosted more vascular epiphyte species than small-diameter trees. This is one of the first studies analyzing interactions between vascular epiphytes and host trees using a network approach in a subtropical forest, and taking the whole vascular epiphyte assemblage of the sampled community into account.     

The relative contribution of abundance and phylogeny to the structure of plant facilitation networks

The structure of the real ecological networks is determined by multiple factors including neutral processes, the relative abundances of species, and the phylogenetic relationships of the interacting species. Previous efforts directed to analyze the relative contribution of these factors to network structure have not been able to fully incorporate the phylogenetic relationships between the interacting species. This limitation stems from the difficulty of predicting interaction probabilities based on the independent phylogenies of interacting species (e.g. plants and animals). This is not the case for plant facilitation networks, where nurse and facilitated species evolve in a common phylogeny (e.g. spermatophyte phylogeny). Facilitation networks are characterized by both high nestedness and interactions tending to occur between distantly related nurse and facilitated species. We evaluate the relative contribution of phylogeny and species abundance to explain both the frequency of observed interactions as well as the network structure in a real plant facilitation network at Tehuacán Valley (central Mexico). Our results show that the combined effects of phylogeny and species abundance were, by far, the best predictors of both the frequency of the interactions observed in this community and the parameters (nestedness and connectance) defining the network structure. This finding indicates that species interact proportionally to both their phylogenetic distances and abundances simultaneously. In short, the phylogenetic history of species, acting together with other ecological factors, has a pervasive influence in the structure of ecological networks.     

尖峰岭热带山地雨林根部真菌-植物互作网络结构特征

不同功能群的根部真菌可能会与植物差异性地互作, 并进一步影响地下真菌与植物群落构建。本研究采用Illumina Miseq测序方法检测了海南尖峰岭热带山地雨林中常见植物的根部真菌; 采用网络分析法比较了丛枝菌根(AM)真菌、外生菌根(ECM)真菌, 以及所有根部真菌与植物互作的二分网络(bipartite networks)结构特性。从槭树科、番荔枝科、夹竹桃科、冬青科、棕榈科、壳斗科、樟科和木犀科等8科植物的根系中, 检测到297,831条真菌ITS1序列, 这些序列被划为1,279个真菌分类单元(OTUs), 其中子囊菌门748个、担子菌门354个、球囊菌亚门80个, 以及未知真菌97个。核心根部真菌群落(420个OTUs)中, 至少有三类不同生态功能的真菌常见, 即丛枝菌根真菌(40个OTUs, 占总序列数23.4%)、外生菌根真菌(48个OTUs, 13.9%)和腐生型真菌(83个OTUs, 19.8%)。尖峰岭山地雨林根部真菌-植物互作网络结构特性的指标普遍显著高于/低于假定物种随机互作的零模型期待值。在群落水平, 不同功能型的根部真菌-植物互作网络表现出不同或相反的结构特性, 如丛枝菌根互作网络表现为比零模型预测值高的嵌套性和连接性, 以及比零模型低的专一性, 而外生菌根互作网络呈现出比零模型预测值低的嵌套性和连接性, 以及比零模型高的专一性。在功能群水平, 植物的生态位重叠度在AM互作网络高, 而ECM互作网络低; 真菌的生态位宽度在ECM互作网络窄, 而在AM互作网络较宽。共现(co-occurrence)网络分析进一步揭示, ECM群落的物种对资源的高度种间竞争(植物、真菌高C-score), 以及AM群落的物种无明显种间竞争(低C-score), 可能分别是形成反嵌套ECM互作网络及高嵌套AM互作网络结构的原因。上述结果说明, 尖峰岭山地雨林中至少有两种及以上的种间互作机制调节群落构建: 驱动AM互作网络冗余(nestedness)及ECM互作网络的高生态位分化(专一性)。本研究在同一个森林内探讨了不同功能型的真菌-植物互作特性, 对深入理解热带森林的物种共存机制和生态恢复具有重要意义。     

Are Nested Networks More Robust to Disturbance? A Test Using Epiphyte-Tree,Comensalistic Networks

Recent research on ecological networks suggests that mutualistic networks are more nested than antagonistic ones and, as a result, they are more robust against chains of extinctions caused by disturbances. We evaluate whether mutualistic networks are more nested than comensalistic and antagonistic networks, and whether highly nested, host-epiphyte comensalistic networks fit the prediction of high robustness against disturbance. A review of 59 networks including mutualistic, antagonistic and comensalistic relationships showed that comensalistic networks are significantly more nested than antagonistic and mutualistic networks, which did not differ between themselves. Epiphyte-host networks from old-growth forests differed from those from disturbed forest in several topological parameters based on both qualitative and quantitative matrices. Network robustness increased with network size, but the slope of this relationship varied with nestedness and connectance. Our results indicate that interaction networks show complex responses to disturbances, which influence their topology and indirectly affect their robustness against species extinctions.     

Ant-Plant Interaction in a Tropical Savanna: May the Network Structure Vary over Time and Influence on the Outcomes of Associations?

Plant-animal interactions occur in a community context of dynamic and complex ecological interactive networks. The understanding of who interacts with whom is a basic information, but the outcomes of interactions among associates are fundamental to draw valid conclusions about the functional structure of the network. Ecological networks studies in general gave little importance to know the true outcomes of interactions and how they may change over time. We evaluate the dynamic of an interaction network between ants and plants with extrafloral nectaries, by verifying the temporal variation in structure and outcomes of mutualism for the plant community (leaf herbivory). To reach this goal, we used two tools: bipartite network analysis and experimental manipulation. The networks exhibited the same general pattern as other mutualistic networks: nestedness, asymmetry and low specialization and this pattern was maintained over time, but with internal changes (species degree, connectance and ant abundance). These changes influenced the protection effectiveness of plants by ants, which varied over time. Our study shows that interaction networks between ants and plants are dynamic over time, and that these alterations affect the outcomes of mutualisms. In addition, our study proposes that the set of single systems that shape ecological networks can be manipulated for a greater understanding of the entire system.     

Effect of temporal data aggregation on the perceived structure of a quantitative plant–floral visitor network

Seasonal turnover in plant and floral visitor communities changes the structure of the network of interactions they are involved in. Despite the dynamic nature of plant–visitor networks, a usual procedure is to pool year‐round interaction data into a single network which may result in a biased depiction of the real structure of the interaction network. The annual temporal dynamics and the effect of merging monthly data have previously been described for qualitative data (i.e. describing the occurrence of interactions) alone, while its quantitative aspect (i.e. the actual frequency with which interactions occur) remain little explored. For this, we built a set of 12 monthly networks describing year‐round plant–floral visitor interactions in a 30‐hectare planted forest and its adjacent agricultural landscape at Bahauddin Zakariya University Multan, Pakistan. A total of 80 plant and 162 insect species, which engaged in 1573 unique interactions, were recorded. Most network properties (particularly the number of plants, visitors and unique interactions) varied markedly during the year. Data aggregation showed that while animal species, plant species, unique interaction, weighted nestedness, interaction diversity and robustness increased, connectance and specialization decreased. The only metric which seemed relatively unaffected by data pooling was interaction evenness. In general, quantitative metrics were relatively less affected by temporal data aggregation than qualitative ones. Avoiding data aggregation not only gives a more realistic depiction of the dynamic nature of plant–visitor community networks, but also avoids biasing network metrics and, consequently, their expected response to disturbances such as the loss of species.     

Fine‐tuning the nested structure of pollination networks by adaptive interaction switching,biogeography and sampling effect in the Galápagos Islands

The structure of pollination networks, particularly its nestedness, contain important information on network assemblages. However, there is still limited understanding of the mechanisms underlying nested pollination network structures. Here, we investigate the role of adaptive interaction switching (AIS), island area, isolation, age and sampling effort in explaining the nestedness of pollination networks across ten Galápagos Islands. The AIS algorithm is inspired by Wallace's elimination of the unfit, where a species constantly replaces its least profitable mutualistic partner with a new partner selected at random. To explain network structures, we first use a dynamic model that includes functional response of pollination and AIS, with only species richness and binary connectance as input (hereafter the AIS model). Thereafter, other explanatory variables (isolation, area, age and sampling effort) were added to the model. In four out of ten islands, the pollination network was significantly nested, and predictions from the AIS model correlated with observed structures, explaining 69% variation in nestedness. Overall, in terms of independent contribution from hierarchical partitioning of variation in observed nestedness, the AIS model predictions contributed the most (37%), followed by sampling effort (28%) and island area (22%), with only trivial contributions from island isolation and age. Therefore, adaptive switching of biotic interactions seems to be key to ensure network function, with island biogeographic factors being only secondary. Although large islands could harbour more diverse assemblages and thus foster more nested structures, sufficient sampling proves to be essential for detecting non‐random network structures.     

Flower‐visitor networks only partially predict the function of pollen transport by bees

Mutualistic networks display distinct structural and organizational features such as nestedness, power‐law degree distribution and asymmetric dependencies. Attention is now focused on how these structural properties influence network function. Most plant‐pollinator networks are constructed using records of animals contacting flowers, which is based on the assumption that all visitors to flowers are pollinators; however, animals may visit flowers as nectar robbers, florivores, or to prey upon other visitors. To differentiate potential pollinator interactions from other interaction types, we examined individual bees that had visited flowers to detect if they carried pollen. Using these data, we constructed visitation and pollen‐transport networks for a spinifex‐dominated arid zone grassland. To determine how the structure of the visitation network reflects pollen transport, we compared the two networks using a null model approach to account for differences in network size. Differences in number of species, nestedness and connectance observed between the visitation and pollen‐transport networks were within expected ranges generated under the null model. The pollen‐transport network was more specialized, had lower interaction evenness, and fewer links compared to the visitation network. Almost half the number of species of the visitation network participated in the pollen‐transport network, and one‐third of unique visitation interactions resulted in pollen transport, highlighting that visitation does not always result in pollination. Floral visitor data indicate potential pollen transporters, but inferring pollination function from visitation networks needs to be performed cautiously as pollen transport resulted from both common and rare interactions, and depended on visitor identity. Although visitation and pollen‐transport networks are structurally similar, the function of all species cannot be predicted from the visitation network alone. Considering pollen transport in visitation networks is a simple first step towards determining pollinators from non‐pollinators. This is fundamental for understanding how network structure relates to network function.     

Trait-mediated interaction leads to structural emergence in mutualistic networks

As asymmetric structures of mutualistic networks can potentially contribute to system resilience, elucidating drivers behind the emergence of particular network architectures remains a major endeavour in ecology. Here, using an eco-evolutionary model for bipartite mutualistic networks with trait-mediated interactions, we explore how particular levels of connectance, nestedness and modularity are affected by three network assembly forces: resource accessibility, tolerance to trait difference between mutualistic pairs and competition intensity. We found that a moderate accessibility to intra-trophic resources and cross-trophic mutualistic support can result in a highly nested web, while low tolerance to trait difference between interacting pairs leads to a high level of modularity. Network-level trait complementarity leads to low connectance and high modularity, while network-level specialization can result in nested structures. Consequently, we argue that the interplay of ecological and evolutionary processes through trait-mediated interactions can explain these widely observed architectures in mutualistic networks.     

The nested structure of marine cleaning symbiosis: is it like flowers and bees?

In a given area, plant-animal mutualistic interactions form complex networks that often display nestedness, a particular type of asymmetry in interactions. Simple ecological and evolutionary factors have been hypothesized to lead to nested networks. Therefore, nestedness is expected to occur in other types of mutualisms as well. We tested the above prediction with the network structure of interactions in cleaning symbiosis at three reef assemblages. In this type of interaction, shrimps and fishes forage on ectoparasites and injured tissues from the body surface of fish species. Cleaning networks show strong patterns of nestedness. In fact, after controlling for species richness, cleaning networks are even more nested than plant-animal mutualisms. Our results support the notion that mutualisms evolve to a predictable community-level structure, be it in terrestrial or marine communities.     

Sampling method influences the structure of plant–pollinator networks

The search for general properties in the structure of ecological networks is currently a very active area of research. Meta‐analyses of published networks are a widely used technique. To have the best chance of discovering common properties though, networks should be constructed using a standardized approach. However, this is rarely the case, and pollination networks are constructed using two main methods: transects and timed observations. To investigate the potential for variation in network structure arising from different construction techniques we constructed plant–pollinator networks using two different methods at a single site, repeating our protocol over three field seasons. Transects and timed observation methods differ in the evenness of observation effort allocated among plant species in the observed community. We show that the uneven allocation of observation effort significantly affects the number of unique interactions in the network, and we reveal a strong trend in effects on web asymmetry and evenness of marginal abundance distributions. However, these effects do not appear to extend to the higher‐order properties of connectance and nestedness.     

Structure in plant–animal interaction assemblages

We present a comprehensive approach to detect pattern in assemblages of plant and animal species linked by interactions such as pollination, frugivory or herbivory. Simple structural models produce gradient, compartmented or nested patterns of interaction; intermediate patterns between a gradient and compartments are possible, and nesting within compartments produces a combined model. Interaction patterns can be visualized and analyzed either as matrices, as bipartite networks or as multivariate sets through correspondence analysis. We argue that differences among patterns represent outcomes of distinct evolutionary and ecological processes in these highly diversified assemblages. Instead of choosing one model a priori, assemblages should be probed for a suite of patterns. A plant–pollinator assemblage exemplifies a simple nested pattern, whereas a plant–herbivore assemblage illustrates a compound pattern with nested structures within compartments. Compartmentation should reflect coevolutionary histories and constraints, whereas differences in species abundance or dispersal may generate nestedness.     

Agricultural intensification drives changes in hybrid network robustness by modifying network structure

Within ecological communities, species engage in myriad interaction types, yet empirical examples of hybrid species interaction networks composed of multiple types of interactions are still scarce. A key knowledge gap is understanding how the structure and stability of such hybrid networks are affected by anthropogenic disturbance. Using 15,169 interaction observations, we constructed 16 hybrid herbivore‐plant‐pollinator networks along an agricultural intensification gradient to explore changes in network structure and robustness to local extinctions. We found that agricultural intensification led to declines in modularity but increases in nestedness and connectance. Notably, network connectance, a structural feature typically thought to increase robustness, caused declines in hybrid network robustness, but the directionality of changes in robustness along the gradient depended on the order of local species extinctions. Our results not only demonstrate the impacts of anthropogenic disturbance on hybrid network structure, but they also provide unexpected insights into the structure‐stability relationship of hybrid networks.     

Native and Non-Native Supergeneralist Bee Species Have Different Effects on Plant-Bee Networks

Supergeneralists, defined as species that interact with multiple groups of species in ecological networks, can act as important connectors of otherwise disconnected species subsets. In Brazil, there are two supergeneralist bees: the honeybee Apis mellifera, a non-native species, and Trigona spinipes, a native stingless bee. We compared the role of both species and the effect of geographic and local factors on networks by addressing three questions: 1) Do both species have similar abundance and interaction patterns (degree and strength) in plant-bee networks? 2) Are both species equally influential to the network structure (nestedness, connectance, and plant and bee niche overlap)? 3) How are these species affected by geographic (altitude, temperature, precipitation) and local (natural vs. disturbed habitat) factors? We analyzed 21 plant-bee weighted interaction networks, encompassing most of the main biomes in Brazil. We found no significant difference between both species in abundance, in the number of plant species with which each bee species interacts (degree), and in the sum of their dependencies (strength). Structural equation models revealed the effect of A. mellifera and T. spinipes, respectively, on the interaction network pattern (nestedness) and in the similarity in bee’s interactive partners (bee niche overlap). It is most likely that the recent invasion of A. mellifera resulted in its rapid settlement inside the core of species that retain the largest number of interactions, resulting in a strong influence on nestedness. However, the long-term interaction between native T. spinipes and other bees most likely has a more direct effect on their interactive behavior. Moreover, temperature negatively affected A. mellifera bees, whereas disturbed habitats positively affected T. spinipes. Conversely, precipitation showed no effect. Being positively (T. spinipes) or indifferently (A. mellifera) affected by disturbed habitats makes these species prone to pollinate plant species in these areas, which are potentially poor in pollinators.     

Analysis and assembling of network structure in mutualistic systems

It has been observed that mutualistic bipartite networks have a nested structure of interactions. In addition, the degree distributions associated with the two guilds involved in such networks (e.g., plants and pollinators or plants and seed dispersers) approximately follow a truncated power law (TPL). We show that nestedness and TPL distributions are intimately linked, and that any biological reasons for such truncation are superimposed to finite size effects. We further explore the internal organization of bipartite networks by developing a self-organizing network model (SNM) that reproduces empirical observations of pollination systems of widely different sizes. Since the only inputs to the SNM are numbers of plant and animal species, and their interactions (i.e., no data on local abundance of the interacting species are needed), we suggest that the well-known association between species frequency of interaction and species degree is a consequence rather than a cause, of the observed network structure.