And, as long as there are good data available, the approach is "readily applicable to other organisms, invasion pathways, and ecosystems," adds invasion biologist Marjorie Wonham of the University of Edmonton in Alberta, Canada.
With increasing amounts of data available, machine learning approaches have been used to train models of the fragmentation process.
If experimental data are not available, approaches such as log-linear kinetics and "convenience" kinetics require mining the literature for parameter values, which (aside from the skepticism about the validity of combining parameter values from different conditions to simulate a specific experiment) could be impractical for large-scale models.
Yet, there are no clinical and only sparse pre-clinical in vivo data available for this approach.
The quality of the data available for such an approach is an issue for many countries in which the surveillance system has not been designed for this purpose.
31 However, due to the limited data available we feel the approach taken is the most appropriate, and further it allows a more nuanced investigation of order effects considering non-linear functions.
Given the air quality monitoring, meteorological, geographic, and other data available from 1988 2007, our modeling approach provides a reasonable balance of computational feasibility (using standard software) and complexity while representing the small- and large-scale spatial, temporal, and spatio-temporal features of the data.
One reason is the use of derived as well as published estimates, which adds considerably to the data available for analysis, an approach which might be improved still further by obtaining results for those studies which merely reported their findings non-quantitatively, e.g. as "no significant association".
With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format.
Geographic areas of interest were identified in a two-stage approach using data available in ArcView GIS 9.2 (Redlands, CA).
