Home ITCFULLY DIGITAL (UNTIL FURTHER NOTICE) : PhD Defence Sam Khosravifard | Perspective matters: Individual and species movement in spatial context

FULLY DIGITAL (UNTIL FURTHER NOTICE) : PhD Defence Sam Khosravifard | Perspective matters: Individual and species movement in spatial context

Perspective matters: Individual and species movement in spatial context

Due to the COVID-19 crisis the PhD defence of Sam Khosravifard will take place online (until further notice).

The PhD defence can be followed by a live stream.

Sam Khosravifard is a PhD student in the department of Natural Resources (NRS). His supervisor is prof.dr. A.K. Skidmore from the Faculty of Geo-Information Science and Earth Observation (ITC).

Movement is a fundamental characteristic of life that has been defined as a change across many spatial and temporal scales. It is also a ubiquitous ecological process which influences the structure and dynamics of populations, communities, and ecosystems. Movement has always been at the center of many observations, investigations and studies since the very first attempt to understand where a species may go. Naturalists have investigated the mysteries of movement since the writings of Aristotle (4th century B.C.) searched for common features unifying animal movements. He tried to explain movement such as flight through air and motion of animals in water in general terms on the basis of casual observations. Since then, researchers have traditionally used direct observation as a method to monitor wildlife, as well as to elucidate and to describe movement phenomena. Not losing sight of an animal is the most challenging part of this traditional type of research, but this has now been solved by deploying telemetry techniques radar, radio, satellite and Global Positioning System (GPS) tracking. Recent advances in telemetry techniques, such as extensive use of bio-loggers with GPS, have enabled spatiotemporal data to be collected on animals with ever-increasing accuracy. Also, recent advances in movement research have inspired a shift in the study at species-level or population-level patterns to individual-level patterns. 

This dissertation aims to contribute to the understanding of the movement phenomenon at individual-level pattern. The availability of movement data and recent advances in movement research are key factors to improve our understanding of animals' movement at individual levels. 

Although the techniques for studying animal movement have been advanced and flourished since earliest attempts, the incorporation of movement studies in other methodological advancements, particularly in species distribution modelling (SDM) has lagged behind. In the context of SDMs, the accessibility of habitats by species or populations has been considered rather than underlying the process of individuals' movement. 

Part of my dissertation is dedicated to providing evidence that including the individuals' movement of a species and accounting for their potential dispersal, along with environmental dynamics improves the accuracy and credibility of models to predict the potential distribution of species over time under climate change. Also, I illustrate the capacity of individuals’ movement data which can be considered as a reliable source for species distribution modelling. 

A common hypothesis is that when including the vertical movement of individuals improves the accuracy and credibility of the individual’s range maps. Another part of this dissertation provides evidence for this hypothesis and puts it to use in the utilization distribution model. I incorporated the vertical movement data to the 2D space use analysis and proved that the 3D volumetric analysis is a realistic depiction of species occurrence. To develop efficient nature conservation practices, it is necessary to know where and when wildlife may occur. This approach would give a better information to conservationists and wildlife managers while developing or practising conservation plans.

A complex phenomenon like movement involving uncertainties may create confusion for managers. In this dissertation, I also presented the use of movement data to classify different types of movement (i.e. flight). I am confident that application of movement data in wildlife management and conservation practices will continue to expand and improve.