Sampling method influences the structure of plant-pollinator networks

Bumble bee diet breadth increases with local abundance and phenophase duration, not intraspecific variation in body size

Patterns of abundance across space and time, and intraspecific variation in body size, are two species attributes known to influence diet breadth and the structure of interaction networks. Yet, the relative influence of these attributes on diet breadth is often assumed to be equal among taxonomic groups, and the relationship between intraspecific variation in body size on interaction patterns is frequently neglected. We observed bee-flower interactions in multiple locations across Montana, USA, for two growing seasons and measured spatial and temporal patterns of abundance, along with interspecific and intraspecific variation in body size for prevalent species. We predicted that the association between spatial and temporal patterns of abundance and intraspecific variation in body size, and diet breadth, would be stronger for bumble bee compared to non-bumble bee species, because species with flexible diets and long activity periods can interact with more food items. Bumble bees had higher local abundance, occurred in many local communities, more intraspecific variation in body size, and longer phenophases compared to non-bumble bee species, but only local abundance and phenophase duration had a stronger positive association with the diet breadth of bumble bee compared to non-bumble bee species. Communities with a higher proportion of bumble bees also had higher intraspecific variation in body size at the network-level, and network-level intraspecific variation in body size was positively correlated with diet generalization. Our findings highlight that the association between species attributes and diet breadth changes depending on the taxonomic group, with implications for the structure of interaction networks.

Shortcomings of reusing species interaction networks created by different sets of researchers

Given the requisite cost associated with observing species interactions, ecologists often reuse species interaction networks created by different sets of researchers to test their hypotheses regarding how ecological processes drive network topology. Yet, topological properties identified across these networks may not be sufficiently attributable to ecological processes alone as often assumed. Instead, much of the totality of topological differences between networks-topological heterogeneity-could be due to variations in research designs and approaches that different researchers use to create each species interaction network. To evaluate the degree to which this topological heterogeneity is present in available ecological networks, we first compared the amount of topological heterogeneity across 723 species interaction networks created by different sets of researchers with the amount quantified from non-ecological networks known to be constructed following more consistent approaches. Then, to further test whether the topological heterogeneity was due to differences in study designs, and not only to inherent variation within ecological networks, we compared the amount of topological heterogeneity between species interaction networks created by the same sets of researchers (i.e., networks from the same publication) with the amount quantified between networks that were each from a unique publication source. We found that species interaction networks are highly topologically heterogeneous: while species interaction networks from the same publication are much more topologically similar to each other than interaction networks that are from a unique publication, they still show at least twice as much heterogeneity as any category of non-ecological networks that we tested. Altogether, our findings suggest that extra care is necessary to effectively analyze species interaction networks created by different researchers, perhaps by controlling for the publication source of each network.

Diversity of bees in two crops in an agroforestry ecosystem in Kangsabati South Forest Division, Purulia, West Bengal, India

The investigation study assesses the diversity of bees in Brinjal Solanum melongena L. and Ridge Gourd Luffa acutangula L. crop field from agroforestry ecosystem in South Kangsabati Forest Division, India. The study was carried out in  May 2021 to May 2022 that based on transect, focal observation and pan trap samplings. A total of 1,085 individuals were identified during the field work, belonging to three family seven genera (Apis, Tetragonula, Xylocopa, Ceratina, Amegelia, Nomia, and Megachile) and seventeen species, the non Apis bees (63.78%) were most abundant than Apis bees (36.22%). In brinjal, Shannon diversity index of bees is 2.12 and Shannon evenness index is 0.35, whereas, Shannon diversity index in ridge gourd was 1.94 and Shannon evenness index is 0.3. The observations signify greater diversity and population of wild bees. The natural habitat close to agricultural land helps to sustain the diversity and population of wild bees, which enhance the crop quality and yield.

The Early Season Community of Flower-Visiting Arthropods in a High-Altitude Alpine Environment

In mountain ecosystems, climate change can cause spatiotemporal shifts, impacting the composition of communities and altering fundamental biotic interactions, such as those involving flower-visiting arthropods. On of the main problems in assessing the effects of climate change on arthropods in these environments is the lack of baseline data. In particular, the arthropod communities on early flowering high-altitude plants are poorly investigated, although the early season is a critical moment for possible mismatches. In this study, we characterised the flower-visiting arthropod community on the early flowering high-altitude Alpine plant, Androsace brevis (Primulaceae). In addition, we tested the effect of abiotic factors (temperature and wind speed) and other variables (time, i.e., hour of the day, and number of flowers per plant) on the occurrence, abundance, and diversity of this community. A. brevis is a vulnerable endemic species growing in the Central Alps above 2000 m asl and flowering for a very short period immediately after snowmelt, thus representing a possible focal plant for arthropods in this particular moment of the season. Diptera and Hymenoptera were the main flower visitors, and three major features of the community emerged: an evident predominance of anthomyiid flies among Diptera, a rare presence of bees, and a relevant share of parasitoid wasps. Temperature and time (hour of the day), but not wind speed and number of flowers per plant, affected the flower visitors' activity. Our study contributes to (1) defining the composition of high-altitude Alpine flower-visiting arthropod communities in the early season, (2) establishing how these communities are affected by environmental variables, and (3) setting the stage for future evaluation of climate change effects on flower-visiting arthropods in high-altitude environments in the early season.

Using DNA Metabarcoding to Identify Floral Visitation by Pollinators

The identification of floral visitation by pollinators provides an opportunity to improve our understanding of the fine-scale ecological interactions between plants and pollinators, contributing to biodiversity conservation and promoting ecosystem health. In this review, we outline the various methods which can be used to identify floral visitation, including plant-focused and insect-focused methods. We reviewed the literature covering the ways in which DNA metabarcoding has been used to answer ecological questions relating to plant use by pollinators and discuss the findings of this research. We present detailed methodological considerations for each step of the metabarcoding workflow, from sampling through to amplification, and finally bioinformatic analysis. Detailed guidance is provided to researchers for utilisation of these techniques, emphasising the importance of standardisation of methods and improving the reliability of results. Future opportunities and directions of using molecular methods to analyse plant–pollinator interactions are then discussed.

Brief Pollination Assessment of a Critically Endangered Food-Deceptive Orchid (Cypripedium guttatum) Using a Network Approach

The translocation of orchids (Orchidaceae) cannot be successful if one is unaware of their effective pollinators and plant–pollinator interactions. Cypripedium guttatum is a generalized food-deceptive orchid, which is highly threatened in the Republic of Korea, thus, requiring immediate translocation actions. Although effective pollinators of the orchid are well known in China, little is known about the pollinators in the Republic of Korea and the ecological context in which the orchid can be successfully pollinated. To briefly assess the pollination of C. guttatum prior to translocation, we conducted a one-month survey of general pollination and the community-wide plant–pollinator network properties. Over 21 h of observation, we found that an effective pollinator of the orchid was the sweat bee Lasioglossum virideglaucum. The network was significantly specialized and modular, but not significantly nested. L. virideglaucum (pollinator) and Arabis gemmifera (plant) were determined to be keystone species, based on network metrics. A total of six network modules were identified and the flower colors of the plant species belonging to the C. guttatum module were purple, white, and yellow. After comparing the daily network patterns, we found that pollination of the orchid was accomplished when various flowering plant species bloom, and the nestedness value was high. This study revealed that high plant and pollinator richness could increase the chance that the deceptive orchid would be pollinated. Our study suggests that the network properties of this food-deceptive orchid community could provide useful insight into understanding the ecologically suitable habitat for the translocation of the highly threatened orchid species C. guttatum.

Network robustness and structure depend on the phenological characteristics of plants and pollinators

Many structural patterns have been found to be important for the stability and robustness of mutualistic plant-pollinator networks. These structural patterns are impacted by a suite of variables, including species traits, species abundances, their spatial configuration, and their phylogenetic history. Here, we consider a specific trait: phenology, or the timing of life history events. We expect that timing and duration of activity of pollinators, or of flowering in plants, could greatly affect the species' roles within networks in which they are embedded. Using plant-pollinator networks from 33 sites in southern British Columbia, Canada, we asked (a) how phenological species traits, specifically timing of first appearance in the network and duration of activity in a network, were related to species' roles within a network, and (b) how those traits affected network robustness to phenologically biased species loss. We found that long duration of activity increased connection within modules for both pollinators and plants and among modules for plants. We also found that date of first appearance was positively related to interaction strength asymmetry in plants but negatively related to pollinators. Networks were generally more robust to the loss of pollinators than plants, and robustness increased if the models allow new interactions to form when old ones are lost, constrained by overlapping phenology of plants and pollinators. Robustness declined with the loss of late-flowering plants, which tended to have higher interaction strength asymmetry. In addition, robustness declined with loss of early-flying or long-duration pollinators. These pollinators tended to be among-module connectors. Our results point to networks being limited by early-flying pollinators. If plants flower earlier due to climate change, plant fitness may decline as they will depend on early emerging pollinators, unless pollinators also emerge earlier.

Reconstruction of plant-pollinator networks from observational data

Empirical measurements of ecological networks such as food webs and mutualistic networks are often rich in structure but also noisy and error-prone, particularly for rare species for which observations are sparse. Focusing on the case of plant-pollinator networks, we here describe a Bayesian statistical technique that allows us to make accurate estimates of network structure and ecological metrics from such noisy observational data. Our method yields not only estimates of these quantities, but also estimates of their statistical errors, paving the way for principled statistical analyses of ecological variables and outcomes. We demonstrate the use of the method with an application to previously published data on plant-pollinator networks in the Seychelles archipelago and Kosciusko National Park, calculating estimates of network structure, network nestedness, and other characteristics.

Reconstruction of plant–pollinator networks from observational data

Empirical measurements of ecological networks such as food webs and mutualistic networks are often rich in structure but also noisy and error-prone, particularly for rare species for which observations are sparse. Focusing on the case of plant–pollinator networks, we here describe a Bayesian statistical technique that allows us to make accurate estimates of network structure and ecological metrics from such noisy observational data. Our method yields not only estimates of these quantities, but also estimates of their statistical errors, paving the way for principled statistical analyses of ecological variables and outcomes. We demonstrate the use of the method with an application to previously published data on plant–pollinator networks in the Seychelles archipelago and Kosciusko National Park, calculating estimates of network structure, network nestedness, and other characteristics.

Restoration of Degraded Alpine Meadows Improves Pollination Network Robustness and Function in the Tibetan Plateau

Ecological restoration is widely used to mitigate the negative impacts of anthropogenic activities. There is an increasing demand to identify suitable restoration management strategies for specific habitat and disturbance types to restore interactions between organisms of degraded habitats, such as pollination. In the Tibetan Plateau, alpine meadows have suffered severe degradation due to overgrazing and climate change. Protecting vegetation by fencing during the growing season is a widely applied management regime for restoration of degraded grasslands in this region. Here, we investigated the effect of this restoration strategy on plant–pollinator communities and plant reproduction in the eastern Tibetan Plateau. We collected interaction and seed set data monthly across three grazed (grazed all year) and three ungrazed (fenced during growing season) alpine meadows in growing seasons of two consecutive years. We found ungrazed meadows produced more flowers and attracted more pollinator visits. Many common network metrics, such as nestedness, connectance, network specialization, and modularity, did not differ between grazing treatments. However, plants in ungrazed meadows were more robust to secondary species extinction than those in grazed meadows. The observed changes in the networks corresponded with higher seed set of plants that rely on pollinators for reproduction. Our results indicate that protection from grazing in growing seasons improves pollination network stability and function and thus is a viable restoration approach for degraded meadows.

Seasonality of floral resources in relation to bee activity in agroecosystems

The contribution of wild insects to crop pollination is becoming increasingly important as global demand for crops dependent on animal pollination increases. If wild insect populations are to persist in agricultural landscapes, there must be sufficient resources over time and space. The temporal, within-season component of floral resource availability has rarely been investigated, despite growing recognition of its likely importance for pollinator populations. Here, we examined the visitation rates of common bee genera and the spatiotemporal availability of floral resources in agroecosystems over one season to determine whether local wild bee activity was limited by landscape floral resource abundance, and if so, whether it was limited by the present or past abundance of landscape floral resources. Visitation rates and landscape floral resources were measured in 27 agricultural sites in Ontario and Québec, Canada, across four time periods and three spatial scales. Floral resources were determined based on species-specific floral volume measurements, which we found to be highly correlated with published measurements of nectar sugar mass and pollen volume. Total floral volume at varying spatial scales predicted visits for commonly observed bee genera. We found Lasioglossum and Halictus visits were highest in landscapes that provided either a stable or increasing amount of floral resources over the season. Andrena visits were highest in landscapes with high floral resources at the start of the season, and Bombus visits appeared to be positively related to greater cumulative seasonal abundance of floral resources. These findings together suggest the importance of early-season floral resources to bees. Megachile visits were negatively associated with the present abundance of floral resources, perhaps reflecting pollinator movement or dilution. Our research provides insight into how seasonal fluctuations in floral resources affect bee activity and how life history traits of bee genera influence their responses to food availability within agroecosystems.

Impact of artificial light at night on diurnal plant-pollinator interactions

Artificial light at night has rapidly spread around the globe over the last decades. Evidence is increasing that it has adverse effects on the behavior, physiology, and survival of animals and plants with consequences for species interactions and ecosystem functioning. For example, artificial light at night disrupts plant-pollinator interactions at night and this can have consequences for the plant reproductive output. By experimentally illuminating natural plant-pollinator communities during the night using commercial street-lamps we tested whether light at night can also change interactions of a plant-pollinator community during daytime. Here we show that artificial light at night can alter diurnal plant-pollinator interactions, but the direction of the change depends on the plant species. We conclude that the effect of artificial light at night on plant-pollinator interactions is not limited to the night, but can also propagate to the daytime with so far unknown consequences for the pollinator community and the diurnal pollination function and services they provide.

Relative effects of anthropogenic pressures, climate, and sampling design on the structure of pollination networks at the global scale

Pollinators provide crucial ecosystem services that underpin to wild plant reproduction and yields of insect-pollinated crops. Understanding the relative impacts of anthropogenic pressures and climate on the structure of plant-pollinator interaction networks is vital considering ongoing global change and pollinator decline. Our ability to predict the consequences of global change for pollinator assemblages worldwide requires global syntheses, but these analytical approaches may be hindered by variable methods among studies that either invalidate comparisons or mask biological phenomena. Here we conducted a synthetic analysis that assesses the relative impact of anthropogenic pressures and climatic variability, and accounts for heterogeneity in sampling methodology to reveal network responses at the global scale. We analyzed an extensive dataset, comprising 295 networks over 123 locations all over the world, and reporting over 50,000 interactions between flowering plant species and their insect visitors. Our study revealed that anthropogenic pressures correlate with an increase in generalism in pollination networks while pollinator richness and taxonomic composition are more related to climatic variables with an increase in dipteran pollinator richness associated with cooler temperatures. The contrasting response of species richness and generalism of the plant-pollinator networks stresses the importance of considering interaction network structure alongside diversity in ecological monitoring. In addition, differences in sampling design explained more variation than anthropogenic pressures or climate on both pollination networks richness and generalism, highlighting the crucial need to report and incorporate sampling design in macroecological comparative studies of pollination networks. As a whole, our study reveals a potential human impact on pollination networks at a global scale. However, further research is needed to evaluate potential consequences of loss of specialist species and their unique ecological interactions and evolutionary pathways on the ecosystem pollination function at a global scale.

Flower visitors of Streptocarpus teitensis: implications for conservation of a critically endangered African violet species in Kenya

Background

The African violets are endangered plant species restricted mainly to the Eastern Arc Mountains biodiversity hotspots in Kenya and Tanzania. These plants grow well in shaded environments with high humidity. Given their restricted geographical range and published evidence of dependance on insect vectors to facilitate sexual reproduction, understanding their pollination biology is vital for their survival.

Methods

We conducted an empirical study using flower visitor observations, pan trapping and bagging experiments to establish the role of flower visitors in the fruit set of a locally endemic and critically endangered species of African violet in Taita Hills, Kenya, Streptocarpus teitensis.

Results

The study found that fruit set is increased by 47.8% in S. teitensis when flowers are visited by insects. However, it is important to note the presence of putative autogamy suggesting S. teitensis could have a mixed breeding system involving self-pollination and cross-pollination since bagged flowers produced 26.9% fruit set.

Conclusions

Insects appear to be essential flower visitors necessary for increased fruit set in S. teitensis. However, there is evidence of a mixed breeding system involving putative self-pollination and cross-pollination suggesting that S. teitensis is somewhat shielded from the negative effects of pollinator losses. Consequently, S. teitensis appears to be protected to a degree from the risks such as reproduction failure associated with pollinator losses by the presence of a safety net in putative self-pollination.

Manual Sampling and Video Observations: An Integrated Approach to Studying Flower-Visiting Arthropods in High-Mountain Environments

Despite the rising interest in biotic interactions in mountain ecosystems, little is known about high-altitude flower-visiting arthropods. In particular, since the research in these environment can be limited or undermined by harsh conditions and logistical difficulties, it is mandatory to develop effective approaches that maximize possibilities to gather high-quality data. Here we compared two different methods, manual sampling and video observations, to investigate the interactions between the high-mountain arthropod community and flowers of Androsace brevis (Primulaceae), a vulnerable endemic alpine species with a short flowering period occurring in early season. We manually sampled flower-visiting arthropods according to the timed-observations method and recorded their activity on video. We assessed differences and effectiveness of the two approaches to estimate flower-visiting arthropod diversity and to identify potential taxa involved in A. brevis pollination. Both methods proved to be effective and comparable in describing the diversity of flower visitors at a high taxonomic level. However, with manual sampling we were able to obtain a fine taxonomic resolution for sampled arthropods and to evaluate which taxa actually carry A. brevis pollen, while video observations were less invasive and allowed us to assess arthropod behavior and to spot rare taxa. By combining the data obtained with these two approaches we could accurately identify flower-visiting arthropods, characterize their behavior, and hypothesize a role of Hymenoptera Apoidea and Diptera Brachycera in A. brevis pollination. Therefore, we propose integrating the two approaches as a powerful instrument to unravel interactions between flowering plants and associated fauna that can provide crucial information for the conservation of vulnerable environments such as high-mountain ecosystems.

Loss of pollinator specialization revealed by historical opportunistic data: Insights from network-based analysis

We are currently facing a large decline in bee populations worldwide. Who are the winners and losers? Generalist bee species, notably those able to shift their diet to new or alternative floral resources, are expected to be among the least vulnerable to environmental change. However, studies of interactions between bees and plants over large temporal and geographical scales are limited by a lack of historical records. Here, we used a unique opportunistic century-old countrywide database of bee specimens collected on plants to track changes in the plant-bee interaction network over time. In each historical period considered, and using a network-based modularity analysis, we identified some major groups of species interacting more with each other than with other species (i.e. modules). These modules were related to coherent functional groups thanks to an a posteriory trait-based analysis. We then compared over time the ecological specialization of bees in the network by computing their degree of interaction within and between modules. “True” specialist species (or peripheral species) are involved in few interactions both inside and between modules. We found a global loss of specialist species and specialist strategies. This means that bee species observed in each period tended to use more diverse floral resources from different ecological groups over time, highly specialist species tending to enter/leave the network. Considering the role and functional traits of species in the network, combined with a long-term time series, provides a new perspective for the study of species specialization.

Effects of community composition on plant-pollinator interaction networks across a spatial gradient of oak-savanna habitats

Distance between habitats may impact the composition and corresponding interactions between trophic levels. Mutualistic networks, such as those of plants and pollinators tend to have a core set of properties that often relate to the resilience of the community, or the ability of the community to retain function and structure after a disturbance. Furthermore, network structure is highly dependent on the number of specialists and generalists; however, it is unclear how different groups of species with various life-history strategies influence network structure. In this study, we evaluated how the composition of plants and pollinators within 16 oak-savanna sites changed across a latitudinal gradient. In addition, we evaluated how the abundance of different groups of plants and pollinators affected network metrics related to resilience. We found that the composition of plants and pollinators varied between ecoregions, while pollinator composition further varied with habitat characteristics. Network metrics displayed no spatial pattern but were related to the abundance of several pollinator groups. Above-ground nesting insects had a positive relationship with nestedness and a negative relationship with modularity, while predatory larvae had a negative relationship with modularity. Thus, above-ground nesting insects and predatory larvae could be expected to increase network resilience. This study emphasizes how spatial scales can influence species compositions, which in turn affects the structure of interactions in the community with implications for resilience.

Molecular ecology as a tool for understanding pollination and other plant-insect interactions

Advances in molecular ecology offer unprecedented opportunities to understand the ecology and evolution of insects, the complex ways in which they interact and their role in ecosystem functioning. Rapidly developing DNA sequencing technologies are resolving previously intractable questions in taxonomic and functional biodiversity and provide significant potential to determine formerly difficult to observe plant-insect interactions. We provide an overview of the state-of-the-art and critically appraise the range of molecular approaches currently available for the study of insect pollination, host-parasitoid interactions and/or wider food-web studies. Species-interaction data are increasingly being incorporated into ecological network analyses. DNA metabarcoding offers opportunities to scale-up efforts to create large, highly resolved, phylogenetically structured networks within an exciting framework to study pressing questions in ecology and evolution.

Finding missing links in interaction networks

Documenting which species interact within ecological communities is challenging and labor intensive. As a result, many interactions remain unrecorded, potentially distorting our understanding of network structure and dynamics. We test the utility of four structural models and a new coverage-deficit model for predicting missing links in both simulated and empirical bipartite networks. We find they can perform well, although the predictive power of structural models varies with the underlying network structure. The accuracy of predictions can be improved by ensembling multiple models. Augmenting observed networks with most-likely missing links improves estimates of qualitative network metrics. Tools to identify likely missing links can be simple to implement, allowing the prioritization of research effort and more robust assessment of network properties.

Non-native honey bees disproportionately dominate the most abundant floral resources in a biodiversity hotspot

Most plant-pollinator mutualisms are generalized. As such, they are susceptible to perturbation by abundant, generalist, non-native pollinators such as the western honey bee ( Apis mellifera), which can reach high abundances and visit flowers of many plant species in their expansive introduced range. Despite the prevalence of non-native honey bees, their effects on pollination mutualisms in natural ecosystems remain incompletely understood. Here, we contrast community-level patterns of floral visitation by honey bees with that of the diverse native pollinator fauna of southern California, USA. We show that the number of honey bees visiting plant species increases much more rapidly with flower abundance than does that of non-honey bee insects, such that the percentage of all visitors represented by honey bees increases with flower abundance. Thus, honey bees could disproportionately impact the most abundantly blooming plant species and the large numbers of both specialized and generalized pollinator species that they sustain. Honey bees may preferentially exploit high-abundance floral resources because of their ability to recruit nest-mates; these foraging patterns may cause native insect species to forage on lower-abundance resources to avoid competition. Our results illustrate the importance of understanding foraging patterns of introduced pollinators in order to reveal their ecological impacts.

Revealing biases in the sampling of ecological interaction networks

The structure of ecological interactions is commonly understood through analyses of interaction networks. However, these analyses may be sensitive to sampling biases with respect to both the interactors (the nodes of the network) and interactions (the links between nodes), because the detectability of species and their interactions is highly heterogeneous. These ecological and statistical issues directly affect ecologists’ abilities to accurately construct ecological networks. However, statistical biases introduced by sampling are difficult to quantify in the absence of full knowledge of the underlying ecological network’s structure. To explore properties of large-scale ecological networks, we developed the software EcoNetGen, which constructs and samples networks with predetermined topologies. These networks may represent a wide variety of communities that vary in size and types of ecological interactions. We sampled these networks with different mathematical sampling designs that correspond to methods used in field observations. The observed networks generated by each sampling process were then analyzed with respect to the number of components, size of components and other network metrics. We show that the sampling effort needed to estimate underlying network properties depends strongly both on the sampling design and on the underlying network topology. In particular, networks with random or scale-free modules require more complete sampling to reveal their structure, compared to networks whose modules are nested or bipartite. Overall, modules with nested structure were the easiest to detect, regardless of the sampling design used. Sampling a network starting with any species that had a high degree (e.g., abundant generalist species) was consistently found to be the most accurate strategy to estimate network structure. Because high-degree species tend to be generalists, abundant in natural communities relative to specialists, and connected to each other, sampling by degree may therefore be common but unintentional in empirical sampling of networks. Conversely, sampling according to module (representing different interaction types or taxa) results in a rather complete view of certain modules, but fails to provide a complete picture of the underlying network. To reduce biases introduced by sampling methods, we recommend that these findings be incorporated into field design considerations for projects aiming to characterize large species interaction networks.

Refuges from fire maintain pollinator-plant interaction networks

Fire is a major disturbance factor in many terrestrial ecosystems, leading to landscape transformation in fire-prone areas. Species in mutualistic interactions are often highly sensitive to disturbances like fire events, but the degree and complexity of their responses are unclear. We use bipartite insect-flower interaction networks across a recently burned landscape to explore how plant-pollinator interaction networks respond to a recent major fire event at the landscape level, and where fire refuges were present. We also investigate the effectiveness of these refuges at different elevations (valley to hilltop) for the conservation of displaced flower-visiting insects during fire events. Then, we explore how the degree of specialization of flower-visiting insects changes across habitats with different levels of fire impact. We did this in natural areas in the Greater Cape Floristic Region (GCFR) biodiversity hotspot, which is species rich in plants and pollinators. Bees and beetles were the most frequent pollinators in interactions, followed by wasps and flies. Highest interaction activity was in the fire refuges and least in burned areas. Interactions also tracked flower abundance, which was highest in fire refuges in the valley and lowest in burned areas. Interactions consisted mostly of specialized flower visitors, especially in refuge areas. The interaction network and species specialization were lowest in burned areas. However, species common to at least two fire classes showed no significant difference in species specialization. We conclude that flower-rich fire refuges sustain plant-pollinator interactions, especially those involving specialized species, in fire-disturbed landscape. This may be an important shelter for specialized pollinator species at the time that the burned landscape goes through regrowth and succession as part of ecosystem recovery process after a major fire event.

The influence of spatial sampling scales on ant-plant interaction network architecture

Despite great interest in metrics to quantify the structure of ecological networks, the effects of sampling and scale remain poorly understood. In fact, one of the most challenging issues in ecology is how to define suitable scales (i.e., temporal or spatial) to accurately describe and understand ecological systems. Here, we sampled a series of ant-plant interaction networks in the southern Brazilian Amazon rainforest in order to determine whether the spatial sampling scale, from local to regional, affects our understanding of the structure of these networks. To this end, we recorded ant-plant interactions in adjacent 25 × 30 m subplots (local sampling scale) nested within twelve 250 × 30 m plots (regional sampling scale). Moreover, we combined adjacent or random subplots and plots in order to increase the spatial sampling scales at the local and regional levels. We then calculated commonly used binary and quantitative network-level metrics for both sampling scales (i.e., number of species and interactions, nestedness, specialization and modularity), all of which encompass a wide array of structural patterns in interaction networks. We observed increasing species and interactions across sampling scales, and while most network descriptors remained relatively constant at the local level, there was more variation at the regional scale. Among all metrics, specialization was most constant across different spatial sampling scales. Furthermore, we observed that adjacent assembly did not generate more variation in network descriptor values compared to random assembly. This finding indicates that the spatially aggregated distribution of species/individuals and abiotic conditions does not affect the organization of these interacting assemblages. Our results have a direct impact on our empirical and theoretical understanding of the ecological dynamics of species interactions by demonstrating that small spatial sampling scales should suffice to record some patterns commonly found in ant-plant interaction networks in a highly diverse tropical rainforest.

Plant–frugivore interactions in an urban nature reserve and its nearby gardens

In the current global context of growing urbanization, urban nature reserves play a crucial role as habitats that serve educational, recreational and conservation purposes. Biodiversity conservation within urban reserves is a challenging task, particularly since connectivity between a reserve and its surrounding artificial green spaces (e.g. gardens and parks) may affect the ecological processes within the reserve in complex ways. In this context, we studied the feeding interactions between plants and birds to provide evidence that an urban nature reserve is connected to its surrounding artificial habitats by mobile organisms. We focused on fleshy-fruited plants and frugivorous birds, and we used a network approach to describe the feeding interactions between these two guilds. The most important connecting bird was Turdus rufiventris, an abundant and obligate frugivore, whose abundance was positively linked to fruit availability in most of the study sites. The apparent increase in the abundance of T. rufiventris in one habitat when it decreases in the other suggests that the two habitats may be complementary for this species. The nature reserve, with many native plants, however, seems to be the preferred site when both habitats offer an abundant fruit supply. Our results suggest changes in either habitat can have consequences in the other one, which has broad implications for the design of management plans of urban nature reserves.

Insect-flower interaction networks vary among endemic pollinator taxa over an elevation gradient

Interaction networks are sensitive to elevation gradients through changes in local distribution of interacting partners. Here, we use plant-pollinator interaction network metrics to assess the effect of elevation on flowers and flower-visiting insect assemblages on a sentinel mountain used for monitoring climate change in the flower- and insect-rich Cape Floristic Region. We also use these interaction metrics to explain the effect of environmental factors on the interaction networks. We did this over four vegetation zones <1640m asl, as determined by former botanical studies. Overall, bees were the dominant flower visitors, followed by monkey beetles, and far behind were wasps and flies. The middle elevation zone (650-744 m a.s.l), which is also an ecotone between two distinct botanical zones, had the highest species richness and abundance of interacting plants and insects. Interaction frequency and size of network were also greatest in the middle zone, as were network diversity, generality, and linkage density, while lowest in the peak zone. In sum, there was distinct elevation zoning of flower-visiting insects. The greatest zonal change was between species at the middle compared with peak zone. Large-sized monkey beetles, bees and flies characterized the unique assemblage in the peak zone (1576-1640 m a.s.l.). The insect zonation tracked that of plant assemblages, with air temperature (lapse rate) being the primary driver of bee distribution, with lowest levels in the peak zone. In contrast, beetle distribution was driven mostly by flower assemblages as well as air temperature. In turn, wasp and fly interaction networks were not affected by any of the measured environmental variables. We conclude that increased elevation stress from reduced temperatures, changing abiotic weather conditions (e.g. strong winds at high elevations),and decline in flowering plant composition causes breakdown of interaction networks involving bees and beetles but not that of flies and wasps.

Drought and increased CO2 alter floral visual and olfactory traits with context-dependent effects on pollinator visitation

Climate change can alter species interactions essential for maintaining biodiversity and ecosystem function, such as pollination. Understanding the interactive effects of multiple abiotic conditions on floral traits and pollinator visitation are important to anticipate the implications of climate change on pollinator services. Floral visual and olfactory traits were measured from individuals of four forb species subjected to drought or normal water availability, and elevated or ambient concentrations of CO₂ in a factorial design. Pollinator visitation rates and community composition were observed in single-species and multi-species forb assemblages. Drought decreased floral visual traits and pollinator visitation rates but increased volatile organic compound (VOC) emissions, whereas elevated CO₂ positively affected floral visual traits, VOC emissions and pollinator visitation rates. There was little evidence of interactive effects of drought and CO₂ on floral traits and pollinator visitation. Interestingly, the effects of climate treatments on pollinator visitation depended on whether plants were in single- or multi-species assemblages. Components of climate change altered floral traits and pollinator visitation, but effects were modulated by plant community context. Investigating the response of floral traits, including VOCs, and context-dependency of pollinator attraction provides additional insights and may aid in understanding the overall effects of climate change on plant-pollinator interactions.

Phenology drives species interactions and modularity in a plant - flower visitor network

Phenology is often identified as one of the main structural driving forces of plant – flower visitor networks. Nevertheless, we do not yet have a full understanding of the effects of phenology in basic network build up mechanisms such as ecological modularity. In this study, we aimed to identify the effect of within-season temporal variation of plant and flower visitor activity on the network structural conformation. Thus, we analysed the temporal dynamics of a plant – flower visitor network in two Mediterranean alpine communities during one complete flowering season. In our approach, we built quantitative interaction networks and studied the dynamics through temporal beta diversity of species, interaction changes and modularity analysis. Within-season dissimilarity in the identity of interactions was mainly caused by species replacement through time (species turnover). Temporal replacement of species and interactions clearly impacted modularity, to the extent that species phenology emerged as a strong determinant of modularity in our networks. From an applied perspective, our results highlight the importance of considering the temporal variation of species interactions throughout the flowering season and the requirement of making comprehensive temporal sampling when aiming to build functionally consistent interaction networks.

Simulated tri-trophic networks reveal complex relationships between species diversity and interaction diversity

Most of earth’s biodiversity is comprised of interactions among species, yet it is unclear what causes variation in interaction diversity across space and time. We define interaction diversity as the richness and relative abundance of interactions linking species together at scales from localized, measurable webs to entire ecosystems. Large-scale patterns suggest that two basic components of interaction diversity differ substantially and predictably between different ecosystems: overall taxonomic diversity and host specificity of consumers. Understanding how these factors influence interaction diversity, and quantifying the causes and effects of variation in interaction diversity are important goals for community ecology. While previous studies have examined the effects of sampling bias and consumer specialization on determining patterns of ecological networks, these studies were restricted to two trophic levels and did not incorporate realistic variation in species diversity and consumer diet breadth. Here, we developed a food web model to generate tri-trophic ecological networks, and evaluated specific hypotheses about how the diversity of trophic interactions and species diversity are related under different scenarios of species richness, taxonomic abundance, and consumer diet breadth. We investigated the accumulation of species and interactions and found that interactions accumulate more quickly; thus, the accumulation of novel interactions may require less sampling effort than sampling species in order to get reliable estimates of either type of diversity. Mean consumer diet breadth influenced the correlation between species and interaction diversity significantly more than variation in both species richness and taxonomic abundance. However, this effect of diet breadth on interaction diversity is conditional on the number of observed interactions included in the models. The results presented here will help develop realistic predictions of the relationships between consumer diet breadth, interaction diversity, and species diversity within multi-trophic communities, which is critical for the conservation of biodiversity in this period of accelerated global change.

Long-legged bees make adaptive leaps: linking adaptation to coevolution in a plant-pollinator network

Adaptation is evolution in response to natural selection. Hence, an adaptation is expected to originate simultaneously with the acquisition of a particular selective environment. Here we test whether long legs evolve in oil-collecting Rediviva bees when they come under selection by long-spurred, oil-secreting flowers. To quantify the selective environment, we drew a large network of the interactions between Rediviva species and oil-secreting plant species. The selective environment of each bee species was summarized as the average spur length of the interacting plant species weighted by interaction frequency. Using phylogenetically independent contrasts, we calculated divergence in selective environment and evolutionary divergence in leg length between sister species (and sister clades) of Rediviva We found that change in the selective environment explained 80% of evolutionary change in leg length, with change in body size contributing an additional 6% of uniquely explained variance. The result is one of four proposed steps in testing for plant-pollinator coevolution.

Identifying Causes of Patterns in Ecological Networks: Opportunities and Limitations

Ecological networks depict the interactions between species, mainly based on observations in the field. The information contained in such interaction matrices depends on the sampling design, and typically, compounds preferences (specialization) and abundances (activity). Null models are the primary vehicles to disentangle the effects of specialization from those of sampling and abundance, but they ignore the feedback of network structure on abundances. Hence, network structure, as exemplified here by modularity, is difficult to link to specific causes. Indeed, various processes lead to modularity and to specific interaction patterns more generally. Inferring (co)evolutionary dynamics is even more challenging, as competition and trait matching yield identical patterns of interactions. A satisfactory resolution of the underlying factors determining network structure will require substantial additional information, not only on independently assessed abundances, but also on traits, and ideally on fitness consequences as measured in experimental setups.

Pollinator importance networks illustrate the crucial value of bees in a highly speciose plant community

Accurate predictions of pollination service delivery require a comprehensive understanding of the interactions between plants and flower visitors. To improve measurements of pollinator performance underlying such predictions, we surveyed visitation frequency, pollinator effectiveness (pollen deposition ability) and pollinator importance (the product of visitation frequency and effectiveness) of flower visitors in a diverse Mediterranean flower meadow. With these data we constructed the largest pollinator importance network to date and compared it with the corresponding visitation network to estimate the specialisation of the community with greater precision. Visitation frequencies at the community level were positively correlated with the amount of pollen deposited during individual visits, though rarely correlated at lower taxonomic resolution. Bees had the highest levels of pollinator effectiveness, with Apis, Andrena, Lasioglossum and Osmiini bees being the most effective visitors to a number of plant species. Bomblyiid flies were the most effective non-bee flower visitors. Predictions of community specialisation (H₂′) were higher in the pollinator importance network than the visitation network, mirroring previous studies. Our results increase confidence in existing measures of pollinator redundancy at the community level using visitation data, while also providing detailed information on interaction quality at the plant species level.

Ecosystem restoration strengthens pollination network resilience and function

Land degradation results in declining biodiversity and the disruption of ecosystem functioning worldwide, particularly in the tropics. Vegetation restoration is a common tool used to mitigate these impacts and increasingly aims to restore ecosystem functions rather than species diversity. However, evidence from community experiments on the effect of restoration practices on ecosystem functions is scarce. Pollination is an important ecosystem function and the global decline in pollinators attenuates the resistance of natural areas and agro-environments to disturbances. Thus, the ability of pollination functions to resist or recover from disturbance (that is, the functional resilience) may be critical for ensuring a successful restoration process. Here we report the use of a community field experiment to investigate the effects of vegetation restoration, specifically the removal of exotic shrubs, on pollination. We analyse 64 plant-pollinator networks and the reproductive performance of the ten most abundant plant species across four restored and four unrestored, disturbed mountaintop communities. Ecosystem restoration resulted in a marked increase in pollinator species, visits to flowers and interaction diversity. Interactions in restored networks were more generalized than in unrestored networks, indicating a higher functional redundancy in restored communities. Shifts in interaction patterns had direct and positive effects on pollination, especially on the relative and total fruit production of native plants. Pollinator limitation was prevalent at unrestored sites only, where the proportion of flowers producing fruit increased with pollinator visitation, approaching the higher levels seen in restored plant communities. Our results show that vegetation restoration can improve pollination, suggesting that the degradation of ecosystem functions is at least partially reversible. The degree of recovery may depend on the state of degradation before restoration intervention and the proximity to pollinator source populations in the surrounding landscape. We demonstrate that network structure is a suitable indicator for pollination quality, highlighting the usefulness of interaction networks in environmental management.