Inside the Minds of Lemurs
Using GPS & GIS to Get There
Elena P. Cunningham
Wild monkeys know a lot about their environment. Like clever consumers who consider cost and rewards when deciding what store to visit, monkeys consider distance and the amount of fruit on a tree when deciding what tree to visit. Having studied the spatial memory of saki monkeys in Venezuela, I was intrigued by lemurs, monkeys’ primitive relatives. Do they rely on memory and learning?
Considered living fossils, lemurs have evolved in isolation in Madagascar. They are thought to be among the least intelligent of primates, and little is known about how they think. A better understanding of lemur spatial learning and memory might eventually help to unlock some of the unknowns in the evolution of intelligence in primates.
In order to find out what lemurs know about their environment, I realized I’d have to observe them in their natural habitat. A Dean’s Faculty Research Award from NYU College of Dentistry made it possible for me to visit several potential research sites in Madagascar. I decided to conduct my study in the remote Sahafina trail system, in the southeastern section of Ranomafana National Park. At Ranomafana, I knew I would have logistical support from the International Center for the Conservation of Tropical Environments (ICTE) and the Centre ValBio, a permanent research institution located on the edge of Ranomafana National Park. This support was essential for an ambitious short-term project.
I selected Varecia variegata, the black and white ruffed lemur, whose diet is 74 to 90 percent fruit,1 as my study species. Spatial memory may be particularly useful for primates that live in large home ranges and feed on patchily distributed resources, such as fruit.2 I needed to map the locations of fruit trees and the daily travel paths of the study animals. In Venezuela, a well-marked, mapped trail system divided the study site into quadrants of 25 by 50 meters, and using a compass, I could mark the locations of trees and monkeys in relation to this trail system. In Madagascar, the trail system was sparse. Even if I’d had the time to create an extensive trail system, the terrain was too rugged and the home ranges of the Varecia too large to make that plan feasible. GPS was the only way to get the data I needed.
The Sahafina trail system is probably one of the most difficult sites for collecting GPS data on the planet. A primary rainforest, it has dense tree cover and cloud cover, both of which reduce the ability of a GPS unit to receive a signal from a satellite. In addition, its many gullies and gorges further block the much-needed satellite signals. The site has no electricity and is about a 30-kilometer walk from the nearest road, through streams and rice paddies, and along a narrow, muddy, often steep and sometimes nonexistent path. Energy for the GPS receivers was a concern.
Tooling Up
Since I had no experience with GPS, I knew I needed help. I visited the ITS Statistics and Mapping Lab, a predecessor of the current NYU Data Service Studio, to discuss projects involving GPS and Geographic Information Systems (GIS) with ITS Senior Faculty Technology Specialist Frank LoPresti. He became a partner in my research project, working with me for over a year as I applied for funding and prepared for the expedition. Frank set me up with GIS tutorials and lent me a GPS receiver. He suggested that I conduct a practice research project in a New York City park before leaving for Madagascar, to give me experience working with GPS and mapping programs.
To get me started, Jamie Martinez, a student mapping aide within the Data Service Studio, accompanied me to Tompkins Square Park to demonstrate the use of GPS. We took a Trimble receiver, which is capable of determining a location’s latitude and longitude within less than a meter of accuracy. The Trimble also runs ArcPad, a GIS program created by ESRI that not only collects latitude and longitude readings, but also is capable of spatial analysis. Unfortunately, the Trimble had trouble picking up signals, even in the most open areas of the park under blue skies. In addition, the Trimble uses a battery that needs to be recharged after six to eight hours of use, while I was planning to have two teams collect 24 hours of data every day. In our remote site, how would we recharge the batteries? I was very concerned about the viability of my project until Pat Wright, the founder of ICTE and the Centre ValBio, recommended Garmin, another company that designs and sells GPS receivers.
After some investigation of devices and antennae, we decided on the Garmin 60CSx. This Garmin comes with a “sensitivity chip” which allows it to receive signals in dense tree cover. Although the Garmin is not as accurate as the Trimble, it worked in all outdoor conditions in New York — even standing under a tree on a rainy day surrounded by tall buildings — so I was hopeful it would work in Madagascar. In addition, the Garmin worked for 12 hours on two AA batteries. We could easily carry a month’s supply of AA batteries to the bush camp. I mapped the locations of trees and the movements of squirrels in Prospect Park using the Garmin and was able to transfer the data from MapSource (software running on the Garmin) to Excel and to ArcView, another GIS software product from ESRI. ArcView not only allows you to create maps but to analyze spatial relationships and to overlay layers of data.
In January 2008, I received great news from the National Geographic Society: They would fund my expedition! I wanted to start collecting data before the austral winter set in and the Varecia reduced their ranging — so I had only two months to get the expedition together. I was grateful to receive the additional funding from the Dean’s Faculty Research Award from NYU College of Dentistry. Frank was able to obtain three Garmin 60CSx and a laptop for the project. Although I was not a GPS expert when I left for Madagascar, I had the resources and the knowledge to get the data I needed.
Data Collection in Madagascar
The Centre ValBio had a team of experienced Malagasy research technicians waiting for me when I arrived at Ranomafana. In two days, we set out for the bushcamp. Our first task was to map the existing trails. The Garmin 60CSx is so user-friendly that Jean Claude Rakotonirina, one of the research technicians on my team, quickly learned how to record locations with it, even though he speaks little English, and I speak only a few words of Malagasy.
In a week, Jean Claude and Aimé Victor Tombotiana, another expert team member, traversed the Sahafina Trail System, marking it with orange flagging tape and recording locations every 25 meters for a map. At the same time, other members of my team were marking the locations of trees that are known to play an important role in the Varecia's diet. Using the simple MapSource software, we were able to create basic maps of the trail system and of the trees whose locations we had marked.
Once we started to observe the Varecia, we usually set out from camp just before dawn, making our way through the forest by flashlight. After we located the “focal animal” (the Varecia we were observing that day), Jean Claude used a Garmin to record its location every five minutes and the location of all the trees the animal fed in.
The Garmin always picked up a signal. Rain and cloud cover did not seem to affect its accuracy, which was usually seven to nine meters, but when we were collecting waypoints in a gully, the accuracy could decrease to 15 meters. With every reading, the Garmin also automatically recorded the altitude of the location. Team member Donné Randrianantenaina gave each feeding tree an identifying number and flagged it with pink tape. At various intervals, he also recorded the height of the focal animal in the canopy, the occurrence of any Varecia loud calls, and the identity of any Varecia within 25 meters of the focal animal in field books. François Ratalata collected feeding data for the project.
After two months, I had to return to New York. I was grateful for the help of Frank Princée at ValBio, who managed the GPS data in my absence. Data collection ended in the middle of December. In February, as political unrest grew in Madagascar, Pat Wright brought the field books with my data to New York, just weeks before a coup d’etat on March 17.
More Sophisticated Mapping & Further Analysis
The next step will be to transfer the GPS data from MapSource — and from field books — to ArcView. While MapSource was a simple and useful field tool, with ArcView, we can create maps with layers for various categories of information.
We will create layers mapping the locations of feeding trees, the focal animals’ daily paths, and the locations of other Varecia. This spatial information will be linked to nonspatial data sets, such as those recording the length of time focal animals visited feeding trees. The tree database and sets of maps will be made available to the Centre ValBio and other researchers. The Varecias’ travel decisions will be analyzed with the help of logistic regressions and two computer models created by Charles Janson, a biologist who studies capuchin monkeys and who advised me on my study of saki monkeys. As we analyze the data, we will see what GPS and GIS technology can tell us about the minds of lemurs.
