Flying cheap: modelling the passive movement of plants and animals

Movement of organisms is a key process in ecology, as it enables colonization and gene flow. The ongoing worldwide decline of biodiversity and the increasing pressures of climate change and habitat fragmentation, stress the importance of movement ecology research. There is rapid progress in technology for monitoring movements and the environment in which organisms move. However, it remains a challenge to understand how interacting processes at the organism level shape population and species dynamics, due to the wide range of spatiotemporal scales involved. The aim of this thesis is to connect movement theory, movement data and environmental data to help improve our understanding of movement patterns of birds and plants. This thesis demonstrates how models, in combination with a general movement ecology framework, can be used to link movement patterns to internal and external drivers of movement at various spatiotemporal scales. In this way it shows: 1) which evolutionary pressures are relevant for shaping seed dispersal patterns, 2) how species traits and dispersal mechanisms translate to movement and dispersal patterns, and 3) how data of movement patterns can be used to obtain information about the environment.
In this thesis, model simulations are used to identify evolutionary drivers of seed dispersal in plants. These simulations demonstrate that seed dispersal can be viewed as a search process, where the shape of the entire seed distribution (dispersal kernel) is evolved to optimize trade-offs between finding habitat, avoiding kin competition and colonizing new patches. The trade-offs strongly depend on the spatiotemporal distribution of habitat, resulting in a tight connection between dispersal strategy and habitat distribution.
Mechanisms and traits responsible for shaping dispersal kernels are studied in wind-dispersed and waterbird-dispersed plant species. Costs and benefits of non-random timing of seed release in wind-dispersed plant species strongly influence dispersal distances. A combination of observational data and model simulations demonstrates that seed dispersal distances significantly increase when seeds are released above a wind speed threshold. However, risks of pre-dispersal seed loss greatly limit this threshold and, consequently, dispersal distances. Dispersal kernels of seeds that are dispersed by waterbirds are mainly determined by the movement patterns of the birds.Using a model of seed digestion by mallards and GPS data of mallard movement, it is shown that daily foraging flights of mallards result in frequent transport of seeds between distant waterbodies, thereby maintaining habitat connectivity for plants in fragmented wetlands. Seed size-related gut retention times and gut passage survival determine the proportion of seeds dispersed away from the ingestion area.
The relation between movement and environment can also be used to obtain information about the medium in which an organism is moving. This thesis develops a new method to estimate wind speed, wind direction and thermal updrafts from high-resolution GPS data of Griffon vultures. The strong correlation of these estimates with observations, demonstrates that bio-logging offers a novel alternative approach for estimating atmospheric conditions on a spatial and temporal scale that complements existing meteorological measurement systems.