Background: Movement behaviour is fundamental to the ecology of animals and their interactions with other organisms, and as such contributes to ecosystem dynamics. Waterfowl are key players in ecological processes in wetlands and surrounding habitats through predator-prey interactions and their transportation of nutrients and other organisms. Understanding the drivers of their movement behaviour is crucial to predict how environmental changes affect their role in ecosystem functioning. Mallards (Anas platyrhynchos) are the most abundant duck species worldwide and important dispersers of aquatic invertebrates, plants and pathogens like avian influenza viruses. By GPS tracking of 97 mallards in four landscape types along a gradient of wetland availability, we identified patterns in their daily movement behaviour and quantified potential effects of weather conditions and water availability on the spatial scale of their movements. Results: We demonstrate that mallard movement patterns were highly predictable, with regular commuting flights at dusk and dawn between a fixed day roost and one or several fixed nocturnal foraging sites, linked strongly to surface water. Wind and precipitation hardly affected movement, but flight distances and home range sizes increased when temperatures dropped towards zero. Flight distances and home range sizes increased exponentially with decreasing availability of freshwater habitat. Total shoreline length and the number of water bodies in the landscape surrounding the roost were the best predictors of the spatial scale of daily mallard movements. Conclusions: Our results show how mallards may flexibly adjust the spatial scale of their movements to wetland availability in the landscape. This implies that mallards moving between discrete habitat patches continue to preserve biotic connectivity in increasingly fragmented landscapes. The high predictability of mallard movement behaviour in relation to landscape features makes them reliable dispersal vectors for organisms to adapt to, and allows prediction of their ecological role in other landscapes.
|Date made available||2017|