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The structure of mutualistic networks is likely to result from the simultaneous influence of neutrality and the constraints imposed by complementarity in species phenotypes, phenologies, spatial distributions, phylogenetic relationships, and sampling artifacts. We develop a conceptual and methodological framework to evaluate the relative contributions of these potential determinants. Applying this approach to the analysis of a plant-pollinator network, we show that information on relative abundance and phenology suffices to predict several aggregate network properties (connectance, nestedness, interaction evenness, and interaction asymmetry). However, such information falls short of predicting the detailed network structure (the frequency of pairwise interactions), leaving a large amount of variation unexplained. Taken together, our results suggest that both relative species abundance and complementarity in spatiotemporal distribution contribute substantially to generate observed network patters, but that this information is by no means sufficient to predict the occurrence and frequency of pairwise interactions. Future studies could use our methodological framework to evaluate the generality of our findings in a representative sample of study systems with contrasting ecological conditions.

1. Virtually all empirical ecological interaction networks to some extent suffer from undersampling. However, how limitations imposed by sampling incompleteness affect our understanding of ecological networks is still poorly explored, which may hinder further advances in the field. 2. Here, we use a plant–hummingbird network with unprecedented sampling effort (2716 h of focal observations) from the Atlantic Rainforest in Brazil, to investigate how sampling effort affects the description of network structure (i.e. widely used network metrics) and the relative importance of distinct processes (i.e. species abundances vs. traits) in determining the frequency of pairwise interactions. 3. By dividing the network into time slices representing a gradient of sampling effort, we show that quantitative metrics, such as interaction evenness, specialization (H2'), weighted nestedness (wNODF) and modularity (Q; QuanBiMo algorithm) were less biased by sampling incompleteness than binary metrics. Furthermore, the significance of some network metrics changed along the sampling effort gradient. Nevertheless, the higher importance of traits in structuring the network was apparent even with small sampling effort. 4. Our results (i) warn against using very poorly sampled networks as this may bias our understanding of networks, both their patterns and structuring processes, (ii) encourage the use of quantitative metrics little influenced by sampling when performing spatio-temporal comparisons and (iii) indicate that in networks strongly constrained by species traits, such as plant–hummingbird networks, even small sampling is sufficient to detect their relative importance for the frequencies of interactions. Finally, we argue that similar effects of sampling are expected for other highly specialized subnetworks.

Understanding the relative importance of multiple processes on structuring species interactions within communities is one of the major challenges in ecology. Here, we evaluated the relative importance of species abundance and forbidden links in structuring a hummingbird–plant interaction network from the Atlantic rainforest in Brazil. Our results show that models incorporating phenological overlapping and morphological matches were more accurate in predicting the observed interactions than models considering species abundance. This means that forbidden links, by imposing constraints on species interactions, play a greater role than species abundance in structuring the ecological network. We also show that using the frequency of interaction as a proxy for species abundance and network metrics to describe the detailed network structure might lead to biased conclusions regarding mechanisms generating network structure. Together, our findings suggest that species abundance can be a less important driver of species interactions in communities than previously thought.

Plant-animal interaction networks provide important information on community organization. One of the most critical assumptions of network analysis is that the observed interaction patterns constitute an adequate sample of the set of interactions present in plant-animal communities. In spite of its importance, few studies have evaluated this assumption, and in consequence, there is no consensus on the sensitivity of network metrics to sampling methodological shortcomings. In this study we examined how variation in sampling completeness influences the estimation of six network metrics frequently used in the literature (connectance, nestedness, modularity, robustness to species loss, path length, and centralization). We analyzed data of 186 flowering plants and 336 pollinator species in 10 networks from a forest-fragmented system in central Chile. Using species-based accumulation curves, we estimated the deviation of network metrics in undersampled communities with respect to exhaustively sampled communities and the effect of network size and sampling evenness on network metrics. Our results indicate that: (1) most metrics were affected by sampling completeness but differed in their sensitivity to sampling effort; (2) nestedness, modularity, and robustness to species loss were less influenced by insufficient sampling than connectance, path length, and centralization; (3) robustness was mildly influenced by sampling evenness. These results caution studies that summarize information from databases with high, or unknown, heterogeneity in sampling effort per species and should stimulate researchers to report sampling intensity to standardize its effects in the search for broad patterns in plant-pollinator networks.

Abstract The projected alterations to climate in the High Arctic are likely to result in changes to the short growing season, particularly with varying predicted effects on winter snowfall, the timing of summer snowmelt and air temperatures. These changes are likely to affect the phenology of interacting species in a variety of ways, but few studies have investigated the effects of combined climate drivers on plant–pollinator interactions in the High Arctic. In this study, we alter the timing of flowering phenology using a field manipulation experiment in which snow depth is increased using snow fences and temperatures are enhanced by open-top chambers (OTCs). We used this experiment to quantify the combined effects of treatments on the flowering phenology of six dominant plant species (Dryas octopetala, Cassiope tetragona, Bistorta vivipara, Saxifraga oppositifolia, Stellaria crassipes and Pedicularis hirsuita), and to simulate differing responses to climate between plants and pollinators in a subset of plots. Flowers were counted regularly throughout the growing season of 2015, and insect visitors were caught on flowers during standardised observation sessions. As expected, deep snow plots had delayed snow melt timing and this in turn delayed the first and peak flowering dates of the plants and shortened the prefloration period overall. The OTCs counteracted the delay in first and peak flowering to some extent. There was no effect of treatment on length of flowering season, although for all variables there were species-specific responses. The insect flower–visitor community was species poor, and although evidence of disruption to phenological overlaps was not found, the results do highlight the vulnerability of the plant–pollinator network in this system with differing phenological shifts between insects and plants and reduced visitation rates to flowers in plots with deep snow.

PREMISE OF THE STUDY: Geographic patterns of biodiversity have long inspired interest in processes that shape the assembly, diversity, and dynamics of communities at different spatial scales. To study mechanisms of community assembly, ecologists often compare spatial variation in community composition (beta-diversity) across environmental and spatial gradients. These same patterns inspired evolutionary biologists to investigate how micro-and macro-evolutionary processes create gradients in biodiversity. Central to these perspectives are species interactions, which contribute to community assembly and geographic variation in evolutionary processes. However, studies of beta-diversity have predominantly focused on single trophic levels, resulting in gaps in our understanding of variation in species-interaction networks (interaction beta-diversity), especially at scales most relevant to evolutionary studies of geographic variation. METHODS: We outline two challenges and their consequences in scaling-up studies of interaction beta-diversity from local to biogeographic scales using plant-pollinator interactions as a model system in ecology, evolution, and conservation. KEY RESULTS: First, we highlight how variation in regional species pools may contribute to variation in interaction beta-diversity among biogeographic regions with dissimilar evolutionary history. Second, we highlight how pollinator behavior (host-switching) links ecological networks to geographic patterns of plant-pollinator interactions and evolutionary processes. Third, we outline key unanswered questions regarding the role of geographic variation in plant-pollinator interactions for conservation and ecosystem services (pollination) in changing environments. CONCLUSIONS: We conclude that the largest advances in the burgeoning field of interaction beta-diversity will come from studies that integrate frameworks in ecology, evolution, and conservation to understand the causes and consequences of interaction beta-diversity across scales.

Most rare species appear to be specialists in plant-–pollinator networks. This observation could result either from real ecological processes or from sampling artifacts. Several methods have been proposed to overcome these artifacts, but they have the limitation of being based on visitation data, causing interactions involving rare visitor species to remain undersampled. We propose the analysis of food composition in bee trap nests to assess the reliability of network specialization estimates. We compared data from a plant-–pollinator network in the Monte Desert of Villavicencio Nature Reserve, Argentina, sampled by visit observation, and data from trap nests sampled at the same time and location. Our study shows that trap nest sampling was good for estimating rare species degree. The rare species in the networks appear to be more specialized than they really are, and the bias in the estimation of the species degree increases with the rareness. The low species degree of these rare species in the visitation networks results from insufficient sampling of the rare interactions, which could have important consequences for network structure.

BACKGROUND: Some of the most exciting advances in pollination biology have resulted from interdisciplinary research combining ecological and evolutionary perspectives. For example, these two approaches have been essential for understanding the functional ecology of floral traits, the dynamics of pollen transport, competition for pollinator services, and patterns of specialization and generalization in plant-pollinator interactions. However, as research in these and other areas has progressed, many pollination biologists have become more specialized in their research interests, focusing their attention on either evolutionary or ecological questions. We believe that the continuing vigour of a synthetic and interdisciplinary field like pollination biology depends on renewed connections between ecological and evolutionary approaches. SCOPE: In this Viewpoint paper we highlight the application of ecological and evolutionary approaches to two themes in pollination biology: (1) links between pollinator behaviour and plant mating systems, and (2) generalization and specialization in pollination systems. We also describe how mathematical models and synthetic analyses have broadened our understanding of pollination biology, especially in human-modified landscapes. We conclude with several suggestions that we hope will stimulate future research. This Viewpoint also serves as the introduction to this Special Issue on the Ecology and Evolution of Plant-Pollinator Interactions. These papers provide inspiring examples of the synergy between evolutionary and ecological approaches, and offer glimpses of great accomplishments yet to come.

Species introductions have the potential to affect the functionality and stability of ecological communities, but because little is known about how introduced species form novel interactions, these impacts are difficult to predict. We quantified the impacts of species introductions on species interaction networks using five different model scenarios of how a novel species might form plant-pollinator interactions. The network structure was based on experimental manipulations on a community of plants and pollinators and shows that the community was more diverse, ordered, and compartmentalized, but less complex when an invasive plant generalist was present. Our models of species introductions reliably predicted several aspects of novel network structure in the field study. We found that introduced species that become incorporated into the community as generalists (both in the number and frequency of their interactions) have a much larger impact on the structure of plant-pollinator communities than introduced species that integrate into the community with few interactions. Average degree is strongly affected by the number of interactions the novel species forms and whether it competes for interactions, whereas connectance is affected by whether the novel species competes for interactions or adds new interaction partners. The number and size of compartments in the network change only when the novel species adds new interaction partners, while modularity and nestedness respond most to the number of interactions formed by the novel species. We provide a new approach for understanding the impacts of introduced and invasive species on plant-pollinator communities and demonstrate that it is critical to evaluate multiple structural characters simultaneously, as large changes in the fundamental structure of the community may be disguised.

Urban systems, particularly botanical gardens, often comprise a lot of exotic plant species that can integrate into local plant‐pollinator networks, influencing their temporal structural dynamics. However, revealing how plant‐pollinator interactions are continuously reshaped and how the roles of native plant and exotic plant species within networks alter over time remains a significant challenge. Here, we reconstructed monthly plant‐pollinator interaction networks for 12 months within an urban botanical garden. We focused on the monthly variations in the structure of pollination networks and the roles of native and exotic plant species. The results showed that the dynamics of plant‐pollinator interactions are characterized by significant changes in network structure and species alternations, which have substantial impacts on community processes. Each month, the plant‐pollinator network can be divided into several modules of closely interacting plants and pollinators, and these modules form complex fission‐fusion dynamics across the year. Monthly dynamic changes in plant‐pollinator network structure led to alternations of plant species occupying core positions within the networks. The core plant species in the pollination networks alternated between native and exotic species across the 12 months, suggesting that plant species can be core species independently of their origin in urban plant‐pollinator networks. Therefore, the roles of native and exotic plant species in plant‐pollinator networks can only be fully detected and understood from the perspective of time‐scale dynamics. These results suggest that information on the dynamic changes in plant‐pollinator network structure is critical for understanding the temporally varying role of core species in urban ecosystems. The structure of the plant‐pollinator network in the urban botanical garden is dynamic. The network can be divided into some modules of closely interacting species each month. Dynamic changes in network structure led to alterations of core plant species. The core plant species in networks alternated between native and exotic species. Plant species can be core species independently of their origin in urban networks.