Characterising animal foraging behaviour and implications for resource management

Menuka Udugama
The spatial-dynamics of animal movement behaviour are still under-studied and remain less understood than desired. Exploration of this phenomenon leads to important economic, ecological and natural-resource management implications. Yet despite the recent advances in technology and scientific methods, questions remain in terms of understating the complexities of movement patterns and robust quantification. Key factors impeding the investigation have been the lack of accurate data and incisive
more » ... hematical and quantification models. Animal movement in general, and foraging in particular, are vital characteristics of species which constantly adapt to changes in physical, biological, and social dynamics. Measuring animal movement patterns poses critical questions surrounding specification of appropriate representations of data generation. Accurate methods that identify underlying patterns from incomplete or imprecise raw data are therefore much desired in movement analysis. A better and deeper understanding of the actual heterogeneous patterns of movement can enable more effective management, conservation and development activities. Since the initial identification of a specific pattern termed Lévy flights in foraging animals by Viswanathan et al. (1996, 1999), many later studies have explored this phenomenon. Lévy flight is a special type of random walk derived from the so-called power-law distribution. A vast and diverse variety of foraging animals have been found to exhibit this movement pattern. However, Edwards (2011) overturned previous conclusions surrounding the existence of Lévy flights within a diverse sample of ecological settings, including five species: reindeer in Sweden (Mårell et al. 2002); side-striped jackals in Zimbabwe (Atkinson et al. 2002); microzooplankton (Bartumeus et al. 2003); grey seals (Austin et al. 2004); and humans in the form of fishers (Bertrand et al. 2007; Marchal et al. 2007) and hunter gatherers (Brown et al. 2007). Re-analysing the above data sets using a modern likelihood appro [...]
doi:10.48683/1926.00085383 fatcat:2tiwl4hcerg35fowv27mgk3qji