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Contents:
1 - Introduction; 2 - Spatial analysis of population data; 3 - Spatial analysis of sample data; 4- Spatial partitioning of regions: patch and boundary; 5 - Dealing with spatial autocorrelation; 6 - Spatio-temporal analysis; 7 - Closing comments and further directions.
Review:
Although the spatial dimension of ecology is recognised it is often not given equal billing with other, more biological, forces. This text aims to redress the balance by making spatial matters the central focus. As with all such texts there's also the opportunity of seeing a familiar topic from another angle to see what insights can be learnt.
Ecology, like geography, is essentially about two inter-related elements: pattern (what's where?) and process (why's it there?). Often the process is given priority in ecology but, as chapter one highlights, we can gain much insight by investigating the spatial side. It's not just a question of the location but the relationship between location and species i.e. is the location related to the species directly or indirectly? Chapter two examines the analysis of 'complete' populations i.e. rather than a sample. Techniques such as nearest-neighbour and network analysis are used here. A very useful summary diagram is presented to distinguish between the various methods noted. Chapter three moves on to examine the analysis of samples again using such techniques as network analysis and study of lattices/matrices. Not all measurements focus on the individual. As chapter four shows there's much work to be done on patches and boundaries. Previous work suggested that mean and variance were the same but this only worked in local areas. In chapter four we move both scale (to regional and above) as well as deal with differences in mean and variance. This means we need to delineate clusters and also the location of boundaries. Chapter five takes on a key problem in this kind of work: that data might be directly related to other features such as location. This idea of spatial dependence (or autocorrelation) is important if we need to separate out the effects of space from other factors. Having assessed that likely dependence of information, chapter six adds yet another level of complexity - time. This is a key component of animal studies but can also have application elsewhere. Here we have to cope not only with interdependence of response and location but also to the idea that responses may be non-linear i.e. chaotic. A final chapter summarises the main points in the text and calls for more work in this area.
Such work as this presented here is vital if ecology is to keep developing as a discipline. It asks more searching questions both of the data and ourselves as collectors of such data. There are some fascinating insights that can be of use but the text is one of the more advanced and technical books and does require a good understanding of ecology and statistics thus suiting it more to the undergraduate with some study in these areas.