In today's wildlife studies large investments are made in data collection. They require a lot of human and/or technical resources over long observation periods. Large volumes of data are gathered which are expressions of complex behaviors and environments. These datasets require powerful and fast mechanisms to be analyzed accurately in respect of their temporal components. Today's standard methods to analyze such data are static with very few exceptions. There is an enormous pressure in these studies to produce results in a very short time. This means that the data analysis is restricted by the available analytical methods, which can be easily applied to the data. Researchers apply these methods intended for use with static data, neglecting most temporal aspects inherent to the data. I would like to hypothesize that aside from an often incorrect application of such methods (e.g., Seaman and Jaeger, 1990; James and McCulloch, 1990) the neglect of time and its various aspects in such studies is a major source of error and hides much of the information and insights that could be available from the data.
A second reason why data is analyzed by static methods is that often the focus is set towards the complex habitat requirements of an animal. Even though a certain habitat or more precisely its definition may look very static and is thus considered to be constant, the environment an animal is living in is always changing. Analyzing dynamic animals with respect to a dynamic environment is still a very complex matter, normally too complex for ordinary studies. As I have shown above there is a lack of accurate methods for such data with distinct temporal properties.
In table 4.1 a classification of study types with respect to the perception of animals and habitat as either static or dynamic components in the analysis is shown. Most studies use animal observations as static, locationally fixed point objects. Habitat is seen as the static type of vegetation composition at a certain location. With these two views a study can be classified as type A study in table 4.1. It is clear that none of the two assumptions is correct. Animals are moving, and the habitat changes over time. Hence further research will be needed to achieve studies of class D, where animals are considered as moving and habitat is taken as a changing component. This will need substantial effort and will probably result in intermediate methods of type B and/or C, where one of either animal or habitat remains as a static component in the analysis.
Such methods for adequately analyzing temporal data in animal movements still need to be developed, defined and standardized. Standards are needed for acceptance and wider application of the methods.