The architecture of weighted mutualistic networks

Biological Microbial Interactions from Cooccurrence Networks in a High Mountain Lacustrine District

A fundamental question in biology is why some species tend to occur together in the same locations, while others are never observed coexisting. This question becomes particularly relevant for microorganisms thriving in the highly diluted waters of high mountain lakes, where biotic interactions might be required to make the most of an extreme environment. We studied a high-throughput gene data set of alpine lakes (>220 Pyrenean lakes) with cooccurrence network analysis to infer potential biotic interactions, using the combination of a probabilistic method for determining significant cooccurrences and coexclusions between pairs of species and a conceptual framework for classifying the nature of the observed cooccurrences and coexclusions. This computational approach (i) determined and quantified the importance of environmental variables and spatial distribution and (ii) defined potential interacting microbial assemblages. We determined the properties and relationships between these assemblages by examining node properties at the taxonomic level, indicating associations with their potential habitat sources (i.e., aquatic versus terrestrial) and their functional strategies (i.e., parasitic versus mixotrophic). Environmental variables explained fewer pairs in bacteria than in microbial eukaryotes for the alpine data set, with pH alone explaining the highest proportion of bacterial pairs. Nutrient composition was also relevant for explaining association pairs, particularly in microeukaryotes. We identified a reduced subset of pairs with the highest probability of species interactions (“interacting guilds”) that significantly reached higher occupancies and lower mean relative abundances in agreement with the carrying capacity hypothesis. The interacting bacterial guilds could be more related to habitat and microdispersal processes (i.e., aquatic versus soil microbes), whereas for microeukaryotes trophic roles (osmotrophs, mixotrophs, and parasitics) could potentially play a major role. Overall, our approach may add helpful information to guide further efforts for a mechanistic understanding of microbial interactions in situ.

IMPORTANCE A fundamental question in biology is why some species tend to occur together in the same locations, while others are never observed to coexist. This question becomes particularly relevant for microorganisms thriving in the highly diluted waters of high mountain lakes, in which biotic interactions might be required to make the most of an extreme environment. Microbial metacommunities are too often only studied in terms of their environmental niches and geographic barriers since they show inherent difficulties to quantify biological interactions and their role as drivers of ecosystem functioning. Our study highlights that telling apart potential interactions from both environmental and geographic niches may help for the initial characterization of organisms with similar ecologies in a large scope of ecosystems, even when information about actual interactions is partial and limited. The multilayered statistical approach carried out here offers the possibility of going beyond taxonomy to understand microbiological behavior in situ.

Geographical variation of multiplex ecological networks in marine intertidal communities

Understanding the drivers of geographical variation in species distributions, and the resulting community structure, constitutes one of the grandest challenges in ecology. Geographical patterns of species richness and composition have been relatively well studied. Less is known about how the entire set of trophic and non-trophic ecological interactions, and the complex networks that they create by gluing species together in complex communities, change across geographical extents. Here, we compiled data of species composition and three types of ecological interactions occurring between species in rocky intertidal communities across a large spatial extent (~970 km of shoreline) of central Chile, and analyzed the geographical variability in these multiplex networks (i.e., comprising several interaction types) of ecological interactions. We calculated nine network summary statistics common across interaction types, and additional network attributes specific to each of the different types of interactions. We then investigated potential environmental drivers of this multivariate network organization. These included variation in sea surface temperature and coastal upwelling, the main drivers of productivity in nearshore waters. Our results suggest that structural properties of multiplex ecological networks are affected by local species richness and modulated by factors influencing productivity and environmental predictability. Our results show that non-trophic negative interactions are more sensitive to spatially structured temporal environmental variation than feeding relationships, with non-trophic positive interactions being the least labile to it. We also show that environmental effects are partly mediated through changes in species richness and partly through direct influences on species interactions, probably associated to changes in environmental predictability and to bottom-up nutrient availability. Our findings highlight the need for a comprehensive picture of ecological interactions and their geographical variability if we are to predict potential effects of environmental changes on ecological communities.

A Meta-analysis of Plant Interaction Networks Reveals Competitive Hierarchies as well as Facilitation and Intransitivity

The extent to which competitive interactions and niche differentiation structure communities has been highly controversial. To quantify evidence for key features of plant community structure, I recharacterized published data from interaction experiments as networks of competitive and facilitative interactions. I measured the network structure of 31 woody and herbaceous communities, including the intensity, distribution, and diversity of interactions at the species-pair and community levels to determine the generality of competition, winner-loser relationships, and unequal interaction allocation. I developed novel methodology using meta-analysis to incorporate interaction uncertainty into estimates of structural metrics among independent networks. Plant communities were competitive, but intraspecific interactions were sometimes more intense than interspecific interactions. On the whole, interactions were imbalanced and communities were transitive. However, facilitation, balanced interactions, and intransitivity were common in individual communities. Synthesizing network metrics using meta-analysis is an original approach with which to generalize community structure in a systematic way.

The architecture of mutualistic networks as an evolutionary spandrel

Mutualistic networks have been shown to involve complex patterns of interactions among animal and plant species, including a widespread presence of nestedness. The nested structure of these webs seems to be positively correlated with higher diversity and resilience. Moreover, these webs exhibit marked measurable structural patterns, including broad distributions of connectivity, strongly asymmetrical interactions and hierarchical organization. Hierarchical organization is an especially interesting property, since it is positively correlated with biodiversity and network resilience, thus suggesting potential selection processes favouring the observed web organization. However, here we show that all these structural quantitative patterns-and nestedness in particular-can be properly explained by means of a very simple dynamical model of speciation and divergence with no selection-driven coevolution of traits. The agreement between observed and modelled networks suggests that the patterns displayed by real mutualistic webs might actually represent evolutionary spandrels.

Total Bee Dependence on One Flower Species Despite Available Congeners of Similar Floral Shape

Extreme specialization is a common phenomenon in antagonistic biotic interactions but it is quite rare in mutualistic ones. Indeed, bee specialization on a single flower species (monolecty) is a questioned fact. Here, we provide multiple lines of evidence on true monolecty in a solitary bee (Flavipanurgus venustus, Andrenidae), which is consistent across space (18 sites in SW Iberian Peninsula) and time (three years) despite the presence of closely related congeneric plant species whose flowers are morphologically similar. The host flower (Cistus crispus, Cistaceae) is in turn a supergeneralist, visited by at least 85 insect species. We uncover ultraviolet light reflectance as a distinctive visual cue of the host flower, which can be a key mechanism because bee specialization has an innate basis to recognize specific signals. Moreover, we hypothesized that a total dependence on an ephemeral resource (i.e. one flower species) must lead to spatiotemporal matching with it. Accordingly, we prove that the bee’s flight phenology is synchronized with the blooming period of the host flower, and that the densities of bee populations mirror the local densities of the host flower. This case supports the ‘predictable plethora’ hypothesis, that is, that host-specialization in bees is fostered by plant species providing predictably abundant floral resources. Our findings, along with available phylogenetic information on the genus Cistus, suggest the importance of historical processes and cognitive constraints as drivers of specialization in bee-plant interactions.

Modularity in ecological networks between frugivorous birds and congeneric plant species

Ecological and evolutionary factors influence the presence of modules in species interaction networks, and these modules usually cluster functional similar species. But whether closely related species form modules is still unknown. We tested whether the interaction networks formed by frugivorous birds and Miconia plants are modular and evaluated how modules were divided. To do so, we gathered from the literature data concerning four networks of Miconia and their frugivorous birds (three from Brazilian savanna and one from a rain forest in Panama). We quantified modularity using binary and weighted algorithms and also tested the relationship between bird traits (body mass, dietary specialization, migratory behaviour and phylogeny) in relation to within- and among-module connectivity indices (c and z values). If considering only binary information, networks did not present distinct modular structure. Nevertheless, by including interaction strength, modules can be detected in all four Miconia-bird networks. None of the bird traits, however, was related with the connectivity indices. The possible fluctuation of frugivorous bird abundance coupled with the asynchronic fruiting period of Miconia might favour the formation of temporal modules comprising birds and plant species with phenological overlap, ensuring seed dispersal and facilitating the coexistence in sympatry. Bird traits had little effect on the role that each species plays within the modular network, probably because the frugivorous assemblages were dominated by small-bodied and opportunistic species.