Ned and I have been monitoring a second vernal pool this year. The new pool is in Bridport on the southern extension of Snake Mountain. It is right in the middle of the Champlain Valley, but up on a rocky ridge. The pool is almost twice a big as our other one and a foot deeper. It is lower in elevation at 570 feet above sea level (the other one is in the foothills of the Green Mountains at 1260 feet a.s.l.).
The most important difference between the two pools might be chemical. The new pool sits between two ledges of Middle Cambrian dolostone, a limey rock which enriches the soil with calcium and magnesium. The old pool is surrounded by Cheshire quartzite and the vegetation there (red oak, beech, birch) suggests that the soils are not rich in calcium.
This summer there was a bat or two flying over the yard every evening, so I started lying in wait for them with a camera. For about 15 minutes at dusk there was enough light to capture a bat silhouette if I used a good DSLR at the highest ISO. The photos were fun, but you can’t tell what kind of bats they are from the photos. Someone suggested using a bat detector — an ultrasonic microphone that listens to the otherwise silent calls of bats and even suggests which species are calling.
A month ago, on May 10, I noticed a wad of dry grass in the birch tree outside my home office window. It was obvious what it was, and a noisy pair of Baltimore orioles soon confirmed that a nest was being constructed. Four days later the nest building seemed to be mostly completed, and I stopped taking photos (click them to enlarge).
May 11, 2012. Female Baltimore oriole weaving a nest in a paper birch tree
After it warmed up a bit yesterday, I tried out my new digital field protocol on a wildlife tracking transect behind my house. My goal was to record the identity, quantity, and location of large animal tracks in the snow which crossed the path I was walking (my “transect”). I am trying to develop a protocol for purely digital collection of these data.
Three types of data must be collected: date, location, and observation. The date (and time) is easy because most digital data has a time stamp. Collecting location data requires a GPS enabled device. To collect the wildlife observation information in digital form requires manual data entry (keypad or touchscreen) or audio or video collection. I have seen some smart phone apps which could be bent to this purpose, but I don’t have such a phone, so the easiest route for me is audio, although this will require later translation to textual data.
[Update: I abandoned this three-device protocol after a few trials and now use only the GPS to make waypoints for each observation. The new method is described here.]
Linking the GPS data with the audio observations is the hard part. There are mature protocols for attaching GPS coordinates to image files, but not to audio files, although it should be easy to implement this on a smart phone. I used a digital photo as a link between the GPS data and the audio file. A key component of my protocol is a program which attaches GPS coordinates to photo files and can also associate an audio file with each photo. The program can also create a KMZ file or GIS shapefile which includes the georeferenced audio files. The program is RoboGeo which costs $80. This is the program that I use to georeference photos that I have taken while the GPS is recording a tracklog.