Dataset Information

Pollinator specialization increases with a decrease in a mass-flowering plant in networks inferred from DNA metabarcoding.

ABSTRACT: How native mass-flowering plants affect the specialization of insects at individual and species levels and the consequences for pollination networks have received much less attention than for mass-flowering crops or alien species and basically remain unexplored.Using existing DNA metabarcoding data on the pollen loads of 402 flower-visiting insects, we assessed the effects of a native mass-flowering plant of high reward quality, the shrub Rhododendron ferrugineum, on pollination networks by investigating: (a) the food niches of individual pollinators and pollinator species and (b) the structure of individual and species networks in subalpine heathland patches with extremely contrasted densities of R. ferrugineum.Relative to its high abundance in high-density patches, the shrub was greatly underrepresented and did not dominate individual's or species' generalized networks, rather individual and species specialization increased with a decrease in R. ferrugineum density. Furthermore, individuals of the more generalist dipteran Empididae species tended to extend exclusive interactions with rare plant species in low-density networks. The same trend was observed in the more specialist Apidea but toward rare species in high-density networks. Our results reveal a quite paradoxical view of pollination and a functional complementarity within networks. Niche and network indices mostly based on the occurrence of links showed that individual pollinators and pollinator species and networks were highly generalized, whereas indices of link strength revealed that species and above all individuals behave as quite strict specialists. Synthesis. Our study provides insights into the status of a native mass-flowering plant in individual's and insect species' food niches and pollination networks. It revealed that a generalist pollinator species can be highly specialized at the individual level and how rare plant species coexisting with mass-flowering plants may nevertheless be visited.

SUBMITTER: Pornon A

PROVIDER: S-EPMC6953672 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Pollinator specialization increases with a decrease in a mass-flowering plant in networks inferred from DNA metabarcoding.

Pornon André A Baksay Sandra S Escaravage Nathalie N Burrus Monique M Andalo Christophe C

Ecology and evolution 20190930 24

How native mass-flowering plants affect the specialization of insects at individual and species levels and the consequences for pollination networks have received much less attention than for mass-flowering crops or alien species and basically remain unexplored.Using existing DNA metabarcoding data on the pollen loads of 402 flower-visiting insects, we assessed the effects of a native mass-flowering plant of high reward quality, the shrub <i>Rhododendron ferrugineum</i>, on pollination networks ...[more]

PMID: 31938472

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Project description:AimSpecies differ in their degree of specialization when interacting with other species, with significant consequences for the function and robustness of ecosystems. In order to better estimate such consequences, we need to improve our understanding of the spatial patterns and drivers of specialization in interaction networks.MethodsHere, we used the extensive environmental gradient of Mt. Kilimanjaro (Tanzania, East Africa) to study patterns and drivers of specialization, and robustness of plant-pollinator interactions against simulated species extinction with standardized sampling methods. We studied specialization, network robustness and other network indices of 67 quantitative plant-pollinator networks consisting of 268 observational hours and 4,380 plant-pollinator interactions along a 3.4 km elevational gradient. Using path analysis, we tested whether resource availability, pollinator richness, visitation rates, temperature, and/or area explain average specialization in pollinator communities. We further linked pollinator specialization to different pollinator taxa, and species traits, that is, proboscis length, body size, and species elevational ranges.ResultsWe found that specialization decreased with increasing elevation at different levels of biological organization. Among all variables, mean annual temperature was the best predictor of average specialization in pollinator communities. Specialization differed between pollinator taxa, but was not related to pollinator traits. Network robustness against simulated species extinctions of both plants and pollinators was lowest in the most specialized interaction networks, that is, in the lowlands.ConclusionsOur study uncovers patterns in plant-pollinator specialization along elevational gradients. Mean annual temperature was closely linked to pollinator specialization. Energetic constraints, caused by short activity timeframes in cold highlands, may force ectothermic species to broaden their dietary spectrum. Alternatively or in addition, accelerated evolutionary rates might facilitate the establishment of specialization under warm climates. Despite the mechanisms behind the patterns have yet to be fully resolved, our data suggest that temperature shifts in the course of climate change may destabilize pollination networks by affecting network architecture.

Project description:Background and aimsModularity is a ubiquitous and important structural property of ecological networks which describes the relative strengths of sets of interacting species and gives insights into the dynamics of ecological communities. However, this has rarely been studied in species-rich, tropical plant-pollinator networks. Working in a biodiversity hotspot in the Peruvian Andes we assessed the structure of quantitative plant-pollinator networks in nine valleys, quantifying modularity among networks, defining the topological roles of species and the influence of floral traits on specialization.MethodsA total of 90 transects were surveyed for plants and pollinators at different altitudes and across different life zones. Quantitative modularity (QuanBiMo) was used to detect modularity and six indices were used to quantify specialization.Key resultsAll networks were highly structured, moderately specialized and significantly modular regardless of size. The strongest hubs were Baccharis plants, Apis mellifera, Bombus funebris and Diptera spp., which were the most ubiquitous and abundant species with the longest phenologies. Species strength showed a strong association with the modular structure of plant-pollinator networks. Hubs and connectors were the most centralized participants in the networks and were ranked highest (high generalization) when quantifying specialization with most indices. However, complementary specialization d' quantified hubs and connectors as moderately specialized. Specialization and topological roles of species were remarkably constant across some sites, but highly variable in others. Networks were dominated by ecologically and functionally generalist plant species with open access flowers which are closely related taxonomically with similar morphology and rewards. Plants associated with hummingbirds had the highest level of complementary specialization and exclusivity in modules (functional specialists) and the longest corollas.ConclusionsWe have demonstrated that the topology of networks in this tropical montane environment was non-random and highly organized. Our findings underline that specialization indices convey different concepts of specialization and hence quantify different aspects, and that measuring specialization requires careful consideration of what defines a specialist.

Project description:Pollination is a key component in agricultural food production and ecosystem maintenance, with plant-pollinator interactions an important research theme in ecological and evolutionary studies. Natural history collections provide unique access to samples collected at different spatial and temporal scales. Identification of the plant origins of pollen trapped on the bodies of pollinators in these collections provides insight into historic plant communities and pollinators' preferred floral taxa. In this study, pollen was sampled from Megachile venusta Smith bees from the National Collection of Insects, South Africa, spanning 93 years. Three barcode regions, the internal transcribed spacer 1 and 2 (ITS1 and ITS2) and ribulose-1,5-biphosphate carboxylase (rbcL), were sequenced from mixed pollen samples using a next-generation sequencing approach (MiSeq, Illumina). Sequenced reads were compared to sequence reference databases that were generated by extracting sequence and taxonomic data from GenBank. ITS1 and ITS2 were amplified successfully across all (or most) samples, while rbcL performed inconsistently. Age of sample had no impact on sequencing success. Plant classification was more informative using ITS2 than ITS1 barcode data. This study also highlights the need for comprehensive reference databases as limited local plant sequence representation in reference databases resulted in higher-level taxon classifications being more confidently interpreted. The results showed that small, insect-carried pollen samples from historic bee specimens collected from as early as 1914 can be used to obtain pollen metabarcodes. DNA metabarcoding of mixed origin pollen samples provided a faster, more accurate method of determining pollen provenance, without the need for expert palynologists. The use of historic collections to sample pollen directly from pollinators provided additional value to these collections. Sampling pollen from historic collections can potentially provide the spatial and temporal scales for investigations into changes in plant community structure or pollinator floral choice in the face of global climate change.

Dataset Information

Pollinator specialization increases with a decrease in a mass-flowering plant in networks inferred from DNA metabarcoding.

Publications

Pollinator specialization increases with a decrease in a mass-flowering plant in networks inferred from DNA metabarcoding.

Similar Datasets

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