It has been a while since I last put pen (so to speak) to paper and produced a blog post. I got caught up in writing up my MSc by research thesis and then took some time away from university to gather my thoughts and prepare myself for the forthcoming PhD (now started in earnest). While I’ve been away I have kept myself busy (either earning money or overland travelling with my family in our classic Land Rover) but it is amazing how quickly one gets out of practice when it comes to studying, and how tiring it is when you return to reading!
My current project is largely computational and I have had to re acquaint myself with R, it is shocking just how much gets pushed to the back of the mind over the course of a year and it was an eye opening experience to sit in front of a PC and think “I am sure that I know how to do multiple regression in R, if only I could remember where to start!” I am pleased to say that a few hours with a trusted text has brought all of this back to me and I am now pushing ahead and learning new techniques.
The text that I have found most helpful in getting back to using R has been Mark Gardeners “Statistics for Ecologists Using R and Excel” . This excellent little book leads the reader nicely through the basics. Starting with how to down load R and getting data into the programme through exploratory statistics and into basic analysis with a section on reporting results which includes visualising data. It also makes it easy for the reader to synthesise R and Excel and there is extra help and sample data available on the free companion webpage if needed. I recommended this text to the university library as well as to colleagues at my student workshops on R. Although I initially bought this book when I wanted to discover R I actually also learned new techniques for data manipulation and management in Excel. I am given to understand that this book is being revised by Gardener and look forward to seeing the new version.
My new project will include some community ecology and a good deal of spatial analysis. I was looking around for a decent GIS text when a colleague pointed me in the direction of Brunsdon and Comber’s “An introduction to R for spatial analysis and mapping” . As a GIS novice I have found this book really useful although the data in the examples may be less overtly biological. I really like the way that the authors do not assume that the re reader is an expert in R but show where basic tuition is freely available rather than filling the book with very basic techniques. The book tells the GIS student at which level in R they need to be to start and this allows it to lead more or less straight into the spatial content, it then combines this with more advanced R use such as writing functions and programming. Again data is provided via the companion website and the book is packed full of illustrations and code snippets, many of which have been added to my personal library for future use!
The final text that I have been using recently is another offering from Mark Gardener in the form of “Community Ecology, analytical methods using R and Excel”. In the interest of openness I should tell you that the publisher sent me a copy of this book and asked me to review it. This is a fairly substantial work from Gardener at well over 500 pages and the publishers say that it is aimed at advanced undergrads and post grads/ researchers beginning in community ecology. Without a doubt there is a challenge here since Gardener seeks to enlighten the reader about both community ecology as a topic (although he admits in the foreword that this is not exhaustive) and the analytical techniques needed to successfully study it. This is a feat which I felt that he managed reasonably well. I find his style easy going and he does well at not assuming the reader has expert knowledge. The book follows a logical path and is packed with reassuring screen shots and coding advice. The fact that it is written by an ecologist makes the data relevant to biologists and it all seems easy to follow, specimen data are again provided on the website. Gardener offers alternative analyses for each type of data, explains clearly when he thinks a particular analysis is most useful and then encourages the reader to ‘have a go’. I do have a couple of small criticisms though, firstly the book starts with a very basic introduction and I felt that it would better to point the reader to another source for this and secondly I have personally found that since using R for analysis my use of Excel has been limited to storing, manipulating and basic visualisation of data. With this in mind I found that the explanations of how to use Excel and then R, for the same analysis, were superfluous and that I skipped past the Excel parts to find how to do it with R. That being said, I guess that it is better to have too much information than not enough! Overall I found Community Ecology to be well written, useful and informative, and, as with the other volumes here I would recommend seeking it out.