Complex systems, like the internet, the brain, or social systems, can be represented as networks of websites, neurons, or people. As networks grow and change, special properties often emerge that can tell us about system stability and function. Similarly, ecological networks describe patterns of interactions between species, which can reveal how communities are assembled, what allows species to coexist, and how resilient communities are to disturbance. I study networks of mutualistic interactions between plants and their pollinators.
Habitat loss can reduce the number of species in a community. But habitat loss can also indirectly change the way the remaining species interact in a network, which may exacerbate the negative effects of habitat loss (Spiesman & Inouye 2013).
I am currently studying adaptive networks, where species shuffle their interaction partners to increase net resource gain. Field observations suggest that pollinator species adaptively partition resources among themselves in order to reduce competition for floral resources. This results in highly modular networks (Spiesman & Gratton 2016). In addition to allowing more species to coexist, modularity may also benefit communities by limiting cascading disturbances through the network, e.g., contagious disease.
A network approach is also useful for understanding how interactions between two species can have indirect consequences for others. For example, being eaten by a predator can ruin your day. But if that same predator also eats your competitor, suddenly having the predator around is not so bad. Indirect effects can range from positive to negative and can have important effects on biodiversity. I’m using models to examine how a range of interaction types (mutualism, competition, predation) can influence coexistence, community dynamics, and network structure (e.g., Spiesman & Inouye 2015).