
It’s long been recognised that the scale at which we study the natural world – over long or short time periods, or across small areas or whole regions – affects the conclusions that we draw about ecological patterns and processes. This is certainly true of plant-pollinator interactions. For example, a widely distributed plant can have very different pollinators at the extremes of its range, and pollinators like bees may vary their focus on nectar and pollen sources from year to year.
The analysis of these interactions as networks of actors has become increasingly popular in the last couple of decades. However there is no consensus about how frequent sampling should be, or the geographical scale over which networks should be studied. In fact all scales (from regional “meta-networks” down to single-season, single-site, single taxon observations) are relevant, depending on the questions being asked or the hypotheses posed.
But it’s important that we acknowledge that conclusions drawn at one scale may not apply at other scales.
That’s the take home message from a paper published this week which is the latest output from the PhD work of Australian bee expert Kit Prendergast. We have collaborated on several papers based on her data and this is actually my 100th peer-reviewed publication: a proud milestone for me and one which I’m glad to share with a wonderful early career researcher like Kit!
Here’s the reference with a link to a read-only version of the paper:
And here’s the abstract:
Bipartite networks of flowering plants and their visitors (potential pollinators) are increasingly being used in studies of the structure and function of these ecological interactions. Whilst they hold much promise in understanding the ecology of plant– pollinator networks and how this may be altered by environmental perturbations, like land-use change and invasive species, there is no consensus about the scale at which such networks should be constructed and analysed. Ecologists, however, have emphasised that many processes are scale dependent. Here, we compare network- and species-level properties of ecological networks analysed at the level of a site, pooling across sites within a given habitat for each month of surveys, and pooling across all sites and months to create a single network per habitat type. We additionally considered how these three scales of resolution influenced conclusions regarding differences between networks according to two contrasting habitat types (urban bushland remnants and residential gardens) and the influence of honey bee abundance on network properties. We found that most network properties varied markedly depending on the scale of analysis, as did the significance, or lack thereof, of habitat type and honey bee abundance on network properties. We caution against pooling across sites and months as this can create unrealistic links, invalidating conclusions on network structure. In conclusion, consideration of scale of analysis is also important when conducting and interpreting plant–pollinator networks.

















The importance of urban environments for supporting pollinator populations is a topic that I’ve covered several times on the blog, for example: “




