The amazing scenery of Cat Tien national parc requires protection from the locals as otherwise it’s beautiful animals will be shot and the trees cut. Therefore, all the tribal people that once lived spread throughout the park are now moved together into a new tribal village. In return, they received a free stone house and support for starting up farming. I could witness myself that several tribal people refused to live in the stone houses (apperently to warm) and had rebuild their traditional bamboo huts next to the new ones and used the new ones as sheds. The discussion centered on balancing the rights of the tribal people and the park (which contains nearly extinct animals). Where does the freedom of the tribal people start and the ideals of the park end? Can they walk freely through the park (yes)? Can they shoot an animal when they are hungry (no)? The rules seemed fairly arbitrary to me.
Without noticing it at the moment, I had a very similar discussion the following day on a nearby island at the endangered primate species centre. How much is a monkey worth? Is it worth a very small chance of finding a cure for a human disease? And if that monkey specie is almost extinct? How can you explain the cost of 1 GPS tracker to visiting local schoolchildren if its 5 times the average annual salary in Vietnam? How much suffering for a monkey is justifiable? Anyway, it wasn’t all doom and gloom at the primate centre as the very friendly and knowledgeable manager and I talked about one of my favorite subjects: data.
The question at hand was: how can we optimize survival rates of monkeys that are released back into the wild? The answer is unknown and hidden in the data somewhere. However, the available data isn’t statistically significant, getting new data in is both time consuming and expensive. While we were looking at a monkey couple that were recently promoted from a cage to the ‘free range’ we thought of 10s of variables that could have an impact on the survival rates (even though the animals are solitary would it make sense to release a group at the same moment at the same location? etc.). What should be the testing sequence given resources, time an budget constraints?
Fortunately, there weren’t just questions, but also a path to an answer. And that was the data. Currently, the stored data is only what is tested (for example: does the survival rate depend on the time of the year where the animals are released?). That test is very important, but forgets to take into account other potentially explaining variables (age, time in captivity before the centre, performance of the monkey during the various stages in the center etc.). By storing all the data centrally a big jump forward could be made in the research.
However, the biggest idea was not storing the centre in a better way, it was opening the data up for everybody to see. Putting it on the Internet, inviting other centers around the world to store their data in a similar fashion and analyze the combined data together.
It was a fun (and heated) conversation, because our backgrounds were so different (evil businessman vs monkey saver). In the end we both thoroughly enjoyed finding ways to get more monkeys to survive in the forest.