Sapsucker Woods Acoustic Monitoring Project (SWAMP) is a collaboration between the Bioacoustics Research Program (BRP) and Information Science (IS) to help understand the complementary roles of acoustic monitoring and eBirding to develop better ways of understanding bird distribution and abundance.
We need your help. All you have to do is visit the SWAMP Avicaching locations shown in the map below, submit at least one short stationary checklist, and join in the fun. Each checklist you submit, earns you one more chance to win prizes, fame, and glory. We’ll be collecting this information until at least Aug 31 2018.
Where do I go?
Check out the locations here. If you want to load a map on your phone for easier navigation, here’s the Google Map link. And, of course, these locations are also visible in eBird mobile on iOS and Android when you submit checklists.
You will earn one point each time you visit an SWAMP avicache and submit a complete, stationary checklist of 5-60 minutes duration.
Prizes and Rankings
Each point enters your name once into a random drawing for a prize. For example, if you submit 10 qualifying checklists, you have 10 points, and ten chances to win. If you have 100 checklists, that’s 100 points = 100 times. There will be two winners drawn from participants; each of the prize winners will have the choice of a free eBird t-shirt or ballcap and there will be a special surprise thrown in as well.
There is also a ranking for the most species seen in Avicache locations: a Top 100 for the cumulative Avicache list. The eBirder who reports the highest species list from all Avicaches cumulatively through the end the Avicaching period will win in the species category. As of right now there is no prize for this category aside from the glory of seeing the most species. Of course, the real prize is bragging rights.
Both the total species tallies and Avicache scores will be displayed on the Avicaching Leaderboard. The leaderboard is updated in real-time as you submit sightings.
About the Science
The Cornell Lab deployed 30 in-house developed acoustic recorders (called SWIFT) which are configured to continuously monitor the soundscape in the Sapsucker Woods Sanctuary. Each of the units records acoustic data at 48 kHz sampling rate covering the frequency of all bird calls occurring in Sapsucker Woods. Scientific objectives we hope to address through this study are briefly outlined below:
- Ecology of vocalizations. The sensor array at Sapsucker Woods will allow us to get a better handle on variation in behavior/activity/song rates as a function of a variety of factors such as the time of day, Julian Date, and weather. Comparing these with eBird submissions will also allow us to understand how these influence detection rates using two types of methods (acoustic, and eBird).
- Bird Habitat usage. The collected acoustic data will be used to model heterogeneity in detectability of different bird species in SWS with high temporal and spatial resolution.
- Noise impact assessment. The collected data will allow us to assess how noise originating from Highway 13 traffic and the airport (aircraft operations including engine ignition, takeoff and landing) propagates throughout the sanctuary. We furthermore want to study how the propagation of sound varies with environmental conditions (weather, vegetation etc.), and if the anthropogenic noise impacts the vocal behavior of birds in the SWS.
- Acoustic biodiversity study. The Cornell Lab is currently working with several national and international partners on the development of new acoustic analysis techniques to extract biodiversity and ecosystem health information from acoustic data. Visual bird surveys with avicaching and general eBird submissions for the SWS will be crucial to groundtruth our results. The dense array of recorders, the extended recording period, and many checklist submissions from eBird will provide us with the best possible data set to tackle this research project!
- Automated Sound ID. The data will also be used within the scope of a new Cornell Lab project, BirdVox, which aims to develop advanced methods for the detection and classification of bird vocalizations.