The project is aiming to affirm a model generated by citizen science data through Cornell Lab's eBird. More specifically, we are ground truthing the model on timber harvest lands through using Autonomous Recording Units (ARUs) and mist-netting. Along with bird banding, we are also collecting weather, vegetative, insect, and aquatic data to gain a better understanding of songbird concentrations across migratory pathways.
Timeline: August 15 - October 15 and/or April 27 - June 1 (tentatively)
Opportunity Type: Unpaid
Desired Skills: Bird ID, ability to walk in very rough terrain while also carrying gear, curiosity about insects/macroinvertebrates, positive attitude