Project Details
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Daily and seasonal dynamics of ecological interaction networks: temporal structure and its functional consequences

Subject Area Ecology and Biodiversity of Animals and Ecosystems, Organismic Interactions
Ecology and Biodiversity of Plants and Ecosystems
Term from 2016 to 2021
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 322833943
 
Final Report Year 2021

Final Report Abstract

This project has focused on how interactions between plants and pollinators change over time, within a single day as well as over longer time spans. We used a multitude of approaches to address this topic. We found that the most pronounced changes happen over the regular progress of seasons within a year, but that changes are also important on smaller (different times of a day) and larger (variation among years) timescales. When studying networks of interactions among multiple species of plants and animals, the timescale is important to consider: networks exhibit different structures, depending on whether they are based on a single day of observations, a month, or even multiple years. For example, species in long-time networks appear more generalized. There are, at least, three reasons: more observation time means more of the existing interactions are detected, longer time means species encounter different partners at different times, and over time, species tend to interact with different species out of those available. An important part of this project was to develop and evaluate new (open source) software tools to analyze ecological network datasets in order to better understand how they change with time. These tools include a method to predict new interactions based on species traits and abundances, as well as a method to understand how much of the difference between two networks is due to species behaving differently in different situations. Surprisingly, despite good performance with simulated data, adding traits and phylogenetics provided little additional information over just using abundance for the test dataset of plant-hummingbird interactions. As for the other tool, we were surprised to find how strongly a published method for quantifying the similarity between networks underestimated the influence of differences in species composition. Across all studies of this project, we repeatedly found that a key determinant of how the networks change over time is the availability of interaction partners in time. Species are not always present, but only have restricted flowering or flight periods. Also, sometimes a species is abundant and at other times it is scarcely available. These changes in availability are often the most important driver of temporal network dynamics. For example, we performed a field experiment in which we made flowers of a certain group (Cichorieae), which normally closes its flowers around noon, available in the afternoon, to find that if these flowers are available at unusual times they are nevertheless visited at normal rates by both specialist and generalist pollinators. Although this plant group is very common in Central Europe and can cause very strong changes of plant-pollinator networks within a day, we found it to be largely irrelevant for a meadow dataset that we collected in this study. When comparing the importance of changes within a day to changes within year, we surprisingly found that although species differed in timing on both timescales, only seasonal timing appeared to be important for the structure of plant-pollinator networks as measured by typical statistical indicators. Despite a superficial description of the plant group Cichorieae as having flowers open in the morning, we found large variation in opening and closing times among species in this group. Accordingly, wild bees switched from visiting one species of the group in one hour to another species the next hour. As Cichorieae flowers are important for many wild bees, having multiple species of this group flower together may be beneficial for both bees and plants. This project was basic science and an important aim was to improve the study of species interaction networks by including a temporal perspective. As such, immediate applications outside the realm of science are not expected. That being said, given the enormous attention that pollinators currently receive, the research of this project could certainly be used to improve concepts for sustainable agriculture and insect conservation. The continuity of floral resources through time, both within the day and within the year, could be considered when trying to support pollinators by land management, e.g. when designing seed mixtures for wild flower strips. Likewise, for reliable crop pollination a high diversity of wild pollinators that occur at different times would be best.

Publications

  • (2020). Temporal scale-dependence of plant–pollinator networks. Oikos, 129: 1289-1302
    Schwarz B, Vázquez DP, CaraDonna PJ, Knight, TM, Benadi G, Dormann CF, Gauzens B, Motivans E, Resasco J, Blüthgen N, Burkle LA, Fang Q, Kaiser‐Bunbury CN, Alarcón R, Bain JA, Chacoff NP, Huang S-Q, LeBuhn G., MacLeod M, Petanidou T, Rasmussen C, Simanonok MP, Thompson AH, Fründ J
    (See online at https://doi.org/10.1111/oik.07303)
  • (2021) Dissimilarity of species interaction networks: how to partition rewiring and species turnover components. Ecosphere, 12: e03653
    Fründ J
    (See online at https://doi.org/10.1002/ecs2.3653)
  • (2021) Quantitative prediction of interactions in bipartite networks based on traits, abundances, and phylogeny. The American Naturalist
    Benadi G, Dormann C, Fründ J, Stephan R, Vázquez DP
    (See online at https://doi.org/10.1086/714420)
  • (2021) Within-day dynamics of plant–pollinator networks are dominated by early flower closure: an experimental test of network plasticity. Oecologia 196: 781–794
    Schwarz B, Dormann CF, Vázquez DP, Fründ J
    (See online at https://doi.org/10.1007/s00442-021-04952-5)
  • (2021). Wild insect diversity increases inter-annual stability in global crop pollinator communities. Proceedings of the Royal Society B: Biological Sciences, 288: 20210212
    Senapathi D, Fründ J, Albrecht M, Garratt MPD, Kleijn D, Pickles BJ, Potts SG, An J, Andersson GKS, Bänsch S, Basu P, Benjamin F, Bezerra ADM, Bhattacharya R, Biesmeijer JC, Blaauw B, Blitzer AJ, Brittain CA, Carvalheiro LG, Cariveau DP, Chakraborty P, Chatterjee A, Chatterjee S, Cusser S, Danforth BN, Degani E, Freitas BM, Garibaldi LA, Geslin B, de Groot GA, Harrison T, Howlett B, Isaacs R, Jha S, Klatt BK, Krewenka K, Leigh S, Lindström SAM, Mandelik Y, McKerchar M, Park M, Pisanty G, Rader R, Reemer M, Rundlöf M, Smith B, Smith HG, Silva PN, Steffan-Dewenter I, Tscharntke T, Webber S, Westbury DB, Westphal C, Wickens JB, Wickens VJ, Winfree R, Zhang H, Klein AM
    (See online at https://doi.org/10.1098/rspb.2021.0212)
  • (2021): Seeing through the static: The temporal dimension of plant–animal mutualistic interactions. Ecology Letters, 24: 149-161
    CaraDonna P, Burkle L, Schwarz B, Resasco, J, Knight T, Benadi G, Blüthgen N, Dormann CF, Fang Q, Fründ J, Gauzens B, Kaiser-Bunbury C, Winfree R, Vazquéz DP
    (See online at https://doi.org/10.1111/ele.13623)
 
 

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