To some, the continuous green canopy of BCI’s rainforests looks the same across the island,

Rainforest Canopy

Rainforest Canopy

even though the forest is made up of 100’s of different tree species.  To an animal trying to make a living off seeds dropped out of these trees, however, there are the good and the bad areas.  The good neighborhoods have lots of food and the bad neighborhoods have little food.  From an agouti’s perspective, this comes down to how many palm trees are around, since palm nuts are their favorite food.

Our tree mapping already showed that there is huge variation in the number of palms in different agouti ‘neighborhoods’ across the island. In this new paper just published in the journal Biotropica, we added radio-tracking data collected both by following animals around in the forest, and by using our Automated Radio Tracking System.  We show that “rich” agoutis living in areas with palm (Astrocaryum) density had much smaller home ranges than their poorer island-mates. The reason behind this pattern is straightforward: if you have a high-quality all-you-can-eat restaurant just around the corner, why would you bother to waste your time and energy and face the risk of getting run over by a truck while going to the exact same restaurant eight blocks farther away? Although there are not too many trucks driving around on the BCI-trails, there are ocelots hunting agoutis, and the more an agouti has to run around looking for food the higher risk it has of running into an ocelot-truck.

But, agoutis live in holes in the ground or in hollow logs, not expensive houses.  These do provide refuge from ocelots, as dramatically shown in the below video.  So, if you are an agouti stuck in a bad neighborhood, why not just dig a few extra holes around your territory to give yourself more places to hide from the ocelot-trucks?  This seems like such a good idea the theory even has an official name ‘multiple-central place foraging’.  Do agoutis ‘multiple-central place forage’ to reduce ocelot predation risk in crappy neighborhoods?

Surprisingly, no, agoutis do not increase their ‘multiple-central place foraging’ in bad neighborhoods.  We tracked them down at night to see where they were sleeping, using our radio-tracking antenna to push through the thick vegetation and find their hide-outs.  Although most animals had more than one hidey-hole, there was no relationship with range size – big territories did not have more refuges.

And so we end with the classic scientific conundrum, answer one question, get a bunch of new ones.  WHY don’t agoutis make more holes in large territories?  Are refuges a limiting resource?  Do they need to import more armadillo construction workers to dig more holes?  Or maybe running away from ocelots isn’t that big of a concern for agoutis? We just don’t know, yet….

by Willem-Jan Emsens and Roland Kays

Agouti RefugeTypes

Agouti RefugeTypes


Agoutis have a reputation for being notoriously difficult to trap. In past years, the project has used the methods of Smythe from the 70’s. This year we changed several variables such as the type of bait (coconut instead of corn), the time of day we check the traps, and the distribution of food in and outside of the traps. During October 2008, we started a major trapping effort using a total of 50 traps. We ultimately caught a total of 57 agoutis, and placed radio collars on 31 of them. Of the radio-collared agoutis, 9 died in the past six months, thus we have a total of 22 agoutis alive and on the ARTS system. We are now working with 20 of these agoutis for the seed removal experiments.

Torrey is using our high tech within-trap animal restraint device to hold down the agouti, while Ben injects it with a sedative.



Corin with her brand new radio collar. The latest in agouti fashion accessories.



We are staring the project with two preliminary studies designed to improve our final product.  Jorien van Koten will be doing her thesis on the behavior of agoutis around traps, to help us improve our ability to trap agoutis.  Bart Kranstauber will be evaulating the potential for randomly placed camera traps in estimating animal density.