Camtrap update - March 2013
|Figure 1 - Camtrap grid design|
The truth is, it's as tough as any project. Usually I position 2 or 3 cameras at a time until all six the station possesses are out. The maximum distance between each consecutive camera is 1.4 km (if measuring the distance between two cameras placed diagonally in relation to one another on the grid) or 1 km if in the same row or column (figure 1). This does not sound like much – so why position so few cameras at a time?
Walking 1 km on a path does not take much time at all; walking 1 km down a forest trail (especially if you're used to the relief of the jungle floor and don't get stuck in mud) shouldn't take much longer. But walking 1 km through uncut, wild rainforest is a hassle and a half, only made possibly with a machete. At first I was concerned with the irony of coming to the jungle to carry out research in aid of conserving it, and then hacking through it with a blade. However, on the grand scale of things, cutting a few vines and nasty plants here and there doesn't affect the forest grievously and by the time I return to pick up the cameras, the vegetation has restored itself completely.
|Figure 2 - Gabriel Svobodny crossing the Payamino.|
However, I am enjoying my work, I'm hardly going to complain that I have to hike through rainforest! It is also very satisfying to see the raw products of camera trapping: whereas with most other scientific research your observations are names and numbers awaiting statistical analysis or interpretation, my project does have photos of tropical mammals and birds – awaiting identification. Although it is rather frustrating collecting a camera only to discover – for whatever reason, be it termites, batteries, or faulty equipment – there are no photos on the SD card.
Until now I haven't identified everything the traps have photographed. Some animals, such as tayras and ocelots (figure 3), are relatively easy to identify regardless of the quality of the photo. Things like armadillos, deer, and most of the birds (figure 4) are a little harder to determine down to the species level, especially if the photos don't show characteristic features, aren't clear enough, are in black and white (as the nocturnal ones are), or if the animal is too far away. This is because there are potentially different species of the same genus in the area. Other things like opossums and rodents (figure 5) are just a nuisance; I think I will be doing well if I can identify half of them down to the right genus. Agoutis and pacas (figure 6) are common types of rodent in Central and South America, and the species here are easily distinguishable. Unfortunately I can't say the same for the mouse, rate, and squirrel species.
Given I am nearly halfway through the data collection part of my project, I'm taking identifying the unidentifiable more seriously and starting to look for trends in occurrences (e.g. often there are particular animals which are photographed at the same time in the same place every few days). In May I'm planning to attend the II Latinamerican Mammal Conference in Puyo, Ecuador; hopefully I'll learn a thing or two to help me with the identification process!
|Figure 3 - a) Tayra, Eira barbara; b) ocelot, Leopardus pardalis|
|Figure 4 - a) Nine-banded armadillo (Dasypus novemcinctus); b) red brocket deer (Mazama americana); c) nocturnal curassow (Nothocrax urutum); grey-winged trumpeter, Psophia crepitans|
|Figure 5 - Yet to be identified a) mouse and b), c) opossum species.|
|Figure 6 - a) Agouti, Dasyprocta punctata; b) lowland paca, Cuniculus paca; c) green agouchi, Myoprocta pratti.|
|Figure 7 - Coati (Nasua nasua) feeding frenzy under a papaya tree.|
|Figure 8.1 - Can you spot the vertebrate in this picture?|
|Figure 8.2 - There it is!|