A risky business: predicting invasive species

Calculating risk….

In which we talk about identifying risk of pest species in light of climate change.

Consider these events: a violent home invasion, a major earthquake, and being hit by a ball on a cricket boundary. Which of these are you most at risk from? Obviously this may depend a little on who you are and where you are reading this. Currently, I am sitting at the Ashburton Oval watching my middle son trial for the Under 17 Canterbury cricket team. I am sitting on the boundary at backward of square or cover ( depending on the end being bowled from). I feel like I could be hit by a ball. I have been through a major quake (well several I guess) so that seems like a reasonable level of risk too. I haven’t had a home invasion myself but my auntie in a very quiet village in the Catlins was attacked and beaten last week. So that seems like something that could happen too. How to calculate the relative risks? In all of my years of cricket and cricket coaching, I have never been hit by the ball unless I was trying to stop it (although my car window was smashed on the boundary last year). Although I have been through the Canterbury quakes there is no real predicting if there will be another large one in this area anytime soon. Until last week I had never personally known anyone to be attacked in their home. Having a close family member attacked shouldn’t change my odds in any way. In order to sort this out I would need to collect data on rates of criminal activity in an area, plate boundary structure and how attentive people are to watching the bowling at cricket. In short, this is a difficult activity for our brains to work through and humans are notoriously bad at assessing risk. This is why we need models and computers to help us out.
One area of economic importance where risk needs to be clearly identified is with invasive species. Invasive species are a side effect of economic globalization. As products and people move around the globe there is always an opportunity for unwanted species to go with them. The wrong species establishing in the wrong place can create huge problems, from causing problems for domestic agricultural industries and lowering production to triggering quarantine restrictions for other countries. At Lincoln University we have the Bio-Protection Research Centre that focuses entirely on issues with invasive species. One of the areas of growth is in predicting areas that might be at a higher risk from invasion. (Woah! Almost hit by a ball! Must remember to look up from my iPad more often) Complicating  things are issues of climate change. If areas closer to the poles are getting warmer then they are at greater risk from species currently living closer to the equator.

Sue Worner from Lincoln, is part of the International Pest Risk Mapping Workgroup, a bunch of like-minded individuals who meet regularly to improve methods of estimating risks posed by invasive species. They have recently put together a special issue in the journal NeoBiota to showcase their findings. Sue is one of the authors of the summary paper that looks at progress in this area. In their introduction article they summaries major findings in pest risk science and: policy (understanding what information is critical in the time available for decisions), climate change (building better scenarios for local change), economics (better estimating the rate of spread of pest species through time), surveillance (developing pest risk maps) and uncertainty ( which arises from a fundamental lack of knowledge about sources of risk). The paper by Sue and her colleagues summarizes these issues and the papers in this issue attempt to develop solutions to these issues and get better at analyzing risk.

So are we better at assessing risk because of these models? It seems so. Models are getting more sophisticated and information is more detailed. There is definitely a sense of progress. It probably doesn’t help with my original problem so I might just finish up and keep a better eye on the batsman!

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