Plant-pollinator interaction webs: structure, sampling, scaling and dynamics

In a world facing rapid climate and land-use changes, it is increasingly vital to understand the dynamics of natural communities and the webs of species interactions that govern ecosystem functioning.  The interactions among plants and their pollinators are a particularly important focal system; they are complex not only because of the multitude of species involved, but also because their abundances vary markedly over space and time. Accurately measuring these plant-pollinator networks is vital not only because of the direct conservation value of the species involved, but also their contribution to the provisioning of pollination services (Ratto et al., 2022). Plant-pollinator networks are also as a well-studied example of ecological interaction networks more generally. Despite the importance of such networks, there are potentially serious methodological issues in quantifying them, some of which will be addressed in this studentship.

This project will examine natural and experimentally manipulated plant-pollinator interaction networks, allowing us to explore some key methodological and ecological issues about pollination function – and about interaction networks more generally.

The studentship could include several of the following topics (depending on the student’s skills and interests):

(a) Observed interaction webs are always incomplete, and the measured properties of the network may change with shifting sampling intensity (e.g. Henriksen et al., 2018) and survey methods (e.g. O’Conner et al., 2019).  This raises methodological challenges as to how best to survey such networks and their properties.  Rare species and rare interactions are often under-represented and distorted in typical network surveys. Are proposed Bayesian statistical approaches more suited to dealing with these rare events in data (Young et al., 2021)? Can we devise better survey structures (e.g. equal-effort monitoring) or methods (e.g. eDNA techniques) to provide more robust and accurate portrayals of species and network properties?

(b) How do the properties of interaction webs change as we move from fine to coarse spatial and temporal scales? Both floral and pollinator communities vary markedly across time and space (Zografou et al., 2020), and consequentially the set of species and interactions tends to grow with increasing spatial (and temporal) scales.  Spatially structured methods have been explored for assessing interactions (e.g. Pasquaretta et al., 2017), but they have been poorly explored to date. As we extend surveys spatially and temporally, how do the properties of the observed network change? Does the functional importance of rare species or interactions systematically increase (or decrease) at coarser spatio-temporal scales?

(c) Plants typically respond to environmental manipulations at far finer spatial scales than those affecting pollinators (e.g. Gabriel et al. 2010).  These differences in response scales could allow us to experimentally manipulate network architecture by examining impacts of landscape scale experiments.  The University’s new ‘Gair Wood’ project, which involves s an experimental planting of woodlands, shrublands and grassland regeneration, provides a rare opportunity to answer such questions. We can take advantage of small experimental plots nested within the 36 hectares of Gair Wood to examine the implications for plant-pollinator interaction network properties, and the potential implications for pollination function.

(d) Does altering pollination networks affect the dynamics of plant communities? Experimentally assembled pollinator communities have been shown to alter plant community level reproduction patterns and dynamics in artificially assembled communities (e.g. Fontaine et al., 2005, Albrecht et al., 2012), but little is known about impact in more natural settings.  We can alter the properties of fine-scale pollination networks by using screened cages to experimentally exclude whole functional groups of pollinators based on their body size. Using such exclosures placed over replicated communities of annual plants could allow us to examine not only the impacts on pollinator visitation rates and behaviour (e.g. floral constancy), but also the consequences for plant seed set and community dynamics between years.

(e) Can we effectively model the dynamics of a set of plant-pollinator interactions in space, capturing the very different scales at which plants and their pollinators respond to environmental drivers? Modelling frameworks for plant-pollinator interaction webs exist (e.g. Campbell et al., 2011), but to date these have been spatially implicit, ignoring the spatial scaling issues.  Ideally, these models should be parameterized using field data to make testable predictions about community dynamics in space and time. These models could also be used to assess the importance of rare species and links in the resilience of communities and function in the face of (correlated and uncorrelated) variability.

The project would adhere to principles of open science including the preregistering of experiments, to ensure the quality of the research while upholding transparency (O’Dea et al., 2021). Taken as a whole, the project would familiarize the doctoral student with a range of field and analytical skills, preparing them for research work in a range of disciplines and applications.

References 

Albrecht M, B Schmid, Y Hautier & C Muller (2012). Diverse pollinator communities enhance plant reproductive success. Proc. R. Soc. B 279: 4845-52. https://royalsocietypublishing.org/doi/epdf/10.1098/rspb.2012.1621

Campbell C, S Yang, R Albert & K Shea (2011). A network model for plant-pollinator community assembly.  PNAS 108: 197-202. https://www.pnas.org/doi/pdf/10.1073/pnas.1008204108

Fontaine C, I Dajoz, J Meriguet & M Loreau (2005). Functional diversity of plant-pollinator interaction webs enhances the persistence of plant communities. PLoS Biology 4: e1  https://doi.org/10.1371/journal.pbio.0040001

Gabriel D, SM Sait, JA Hodgson, U Schmutz, WE Kunin & TG Benton (2010). Scale matters: the impact of organic farming on biodiversity at different spatial scales. Ecology Letters 13: 858-869. https://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2010.01481.x

Henriksen, MV, DG Chapple, SL Chown & MA McGeoch (2018). The effect of network size and sampling completeness in depauperate networks.  Journal of Animal Ecology 88: 211-222. https://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2656.12912

O’Connor, RS, Kunin, WE, Garratt, MP, et al. (2019). Monitoring insect pollinators and flower visitation: The effectiveness and feasibility of different survey methods. Methods in Ecology and Evolution, 10: 2129-2140. https://doi.org/10.1098/rstb.2021.0172

O’Dea RE, TH Parker, YE Chee, et al. (2021). Towards open, reliable, and transparent ecology and evolutionary biology. BMC Biol 19: 68. https://doi.org/10.1186/s12915-021-01006-3

Pasquaretta C, R Jeanson, C Andalo, L Chittka & M Lihoreau (2017). Analysing plant-pollinator interactions with spatial movement networks. Ecological Entomology, Entomological Networks: Ecology, Behaviour and Evolution, 29th Symposium of the Royal Entomological Society, 42 (S1): 4-17. https://hal.archives-ouvertes.fr/hal-02105102

Ratto F, TD Breeze, LJ Cole, MP Garratt, D Kleijn, WE Kunin, et al. (2022). Rapid assessment of insect pollination services to inform decision‐making. Conservation Biology, 36: e13886. https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/cobi.13886

Young JG, FS Valdovinos, & MEJ Newman, (2021). Reconstruction of plant–pollinator networks from observational data. Nat. Commun. 12, 3911. https://doi.org/10.1038/s41467-021-24149-x

Zografou K, MT Swartz, VP Tilden, EN McKinney, JA Eckenrode, & BJ Sewall, (2020). Stable generalist species anchor a dynamic pollination network. Ecosphere, 11(8), p.e03225. https://doi.org/10.1002/ecs2.3225