We have a new paper out in the journal Methods in Ecology and Evolution:
One of the biggest problems studying seed dispersal is that seeds are hard to follow! With traditional seed tagging methods, many seeds simply cannot be found, especially when they travel long distances. One method researchers have used is to limit their search to a reasonable distance and track all the seeds within that radius. The problem with this method is that it tells one little/nothing about long distance dispersal. Given that long distance dispersal is believed to be particularly important, this lack of information is problematic. Patrick Jansen and colleagues developed a statistical method to reconstruct the shape of the tail of the seed dispersal distribution using the shape of the distribution inside the search radius. We thought this was a cool method and had the potential to be used more widely. Unfortunately, this method had never been tested with empirical data. Fortunately, we had a perfect dataset to test the method because we used radio-transmitters to track seeds in our project. We also decided to give it a name: the Censored Tail Reconstruction method (CTR). In general, we found that the CTR method worked exceptionally well at recreating the long-tail of the seed dispersal distribution. On the other hand, this method was highly sensitive to which mathematical function was used in the method, and what percentage of seeds were ‘overlooked’ by researchers searching for seeds. The upshot of our paper is that it is possible to calculate fairly accurate dispersal kernels using censored data collected with traditional low priced tagging methods. The caveat to this is that researchers need to be certain that they are able to find the vast majority of seeds within their search radius, and they must choose the most appropriate mathematical function for use in the CTR method (using AIC selection). We think this method should be widely adopted, especially by researchers who cannot afford tons of radio-transmitters.