Recent and ongoing research projects
Uncovering the mechanisms that structure mutualistic networks (partly funded by the British Ecological Society)
To properly appreciate how environmental change influences pollination services, we need to gain
a better understanding of the flower-visitor networks that provide these services, and especially the behaviour of individual pollinators (Ings et al 2009). This will enable us to make predictions about the impacts of the loss of species, or traits, from a network.
To begin to address this I have been constructing novel individual trait-based flower-bee networks. This allows me to compare key features of the individual-based networks with the standard species-averaged networks, and generate new individual-based behavioural parameters. I am currently expanding this to cover a greater range of flower-visitor taxa in order to develop general predictive models that will allow us to make comparisons across geographic boundaries and system types.
Pollinator behavioural plasticity: a new winter generation of bumblebees (initially funded by the Leverhulme Trust and QMUL)
Climate change is predicted to have a large impact on invertebrate communities, including pollinators that are essential for pollination of wild flowers and commercial crops. However, some organisms which possess behavioural and physiological plasticity may be able to adapt. One pollinator that appears to have demonstrated a high degree of plasticity is the common British bumblebee Bombus terrestris which has recently (since the 1990’s) undergone a dramatic shift in its behaviour. It has switched from having a single generation each year, with newly mated queens passing the winter in hibernation, to having two generations per year (Stelzer et al 2010). Intriguingly, this change has coincided with three elements of global change: warmer winters, increased cultivation of winter flowering shrubs and the importation and escape of Mediterranean B. terrestris (Ings, Ward & Chittka, 2006), which naturally has two generations per year. Therefore, I am using B. terrestris as a model to gain a better understanding of the determinants and expression of behavioural/physiological plasticity in relation to environmental change. Currently, I am using molecular techniques to determine the genetic basis for the observed behavioural plasticity – is it an inherent property in our natural populations or is it a result of hybridisation with imported bumblebees?
Predator avoidance learning
I have a keen interest in how prey learn to avoid being consumed by their predators. My initial work, in collaboration with Prof Lars Chittka at QMUL, investigated how bumblebees learn to avoid predators (crab spiders) with a special focus on whether predator crypsis can disrupt avoidance learning. This work involved the development of a complex avoidance learning paradigm which integrates artificial flowers, “robotic” predators and an automatic feeding system, with sophisticated 3D video tracking technology. We have demonstrated that bumblebees are able to develop colour-independent ‘search images’ of cryptic spiders (Ings, Wang & Chittka 2012). More importantly, we showed that a speed-accuracy trade-off occurs when bees are presented with cryptic predators, i.e. they actively slow down their inspection flights when they learn that cryptic spiders are present (Ings & Chittka 2008). Further studies have shown that the risk of predation by cryptic spiders can lead to bees avoiding a particular flower type (Ings and Chittka 2009). Our most recent work has shown that bees are able to simultaneously attend to two complex visual search tasks, i.e. choosing the most rewarding flower type when different species have a very similar appearance (colour) whilst simultaneously trying to avoid cryptic crab spiders (Wang et al 2013).