Many pollinators live in complex and changeable environments. The location of of their food sources changes with time of year (as plants flower), time of day (as flowers open and close or nectar flows) and physical location (for although plants may not move very much during a flowering season, the places that flowers may be found may differ dramatically with time). Natural selection has shaped the behaviours of pollinators so that they have a suite of behaviours that allow them to exploit their environment: although it is unlikely that they know exactly when and where food will be available, they are able to couple clues from the environment with a repertoire of behaviours that will allow them to find food.
Agriculture and other human-generated change is altering the enviroment that pollinators live within, and it is very likely that the rules they are following are not ideal for the changed landscape. Because pollinators are essential for crop production, agricultural policies often dictate that there is some concession to the pollinators. This could be through leaving set-aside ‘wild’ land for nests and wild flowers, or by adding corridors of uncropped land or hedgerows where beneficial species can travel between environments. However, the pollinators will still be following their evolved rule sets, which means that we need to consider whether our concessions to them are of any use. This is something that is difficult to measure, and we need to use a wide range of techniques to ask whether particular manipulations are of benefit to some or many helpful species.
As a behavioural ecologist, I’m interested in how the behavioural decisions made by individual animals allow them to interact with the environment. For most animals, the environment that they live in is highly complex and frequently unpredictable, and it is often a challenge for us to understand how a particular decision gives the animal an advantage over an alternative behaviour. As well as conducting experiments and making observations of behaviour, we can also use theoretical techniques for exploring how simple behaviours could be the best solutions for dealing with complex environments. Simulation techniques are particularly useful for understanding how particular sets of decision allow an animal to cope with changes at the landscape level (bringing together two very different disciplines: landscape ecology and behavioural ecology).
In a paper that has just been published in PeerJ (Rands 2014), I describe a series of models describe a framework for considering how landscape alterations affect the foraging success of a pollinator nesting within the environment. These models build on earlier ideas presented by Rands and Whitney (2010, 2012, discussed in an earlier blog entry), where we simulated landscapes with simple geometries and allowed pollinators to forage within them. In the new PeerJ paper, I describe how hedgerow removal and set-aside field creation may affect the movement of pollinators. The models demonstrate that decreasing either landscape connectivity (be removing hedges) or wild land availability (through having lots of fields of unusable crops) affect how often pollinators have to switch between different environmental types. This may be important for how they find and collect food: for example, swapping between habitats may lead to a temporary reduction in nectar uptake if the pollinator has to work out how to collect it from a newly-encountered shape of flower.
The models are a first step, and are presented as a means of discussing how we can manipulate the environment in a reproducible way within a model. What needs to be done now is to identify a suitable set of behavioural rules to follow (for those presented in the models are basic, and are very likely to be improved upon!). Ongoing work should be able to demonstrate whether particular environmental manipulations are of value to some of our threatened pollinator species.
Rands SA & Whitney HM (2010). Effects of pollinator density-dependent preferences on field margin pollination in the midst of agricultural monocultures: a modelling approach. Ecological Modelling 221: 1310-1316 | abstract | pdf (postprint version)