We test the efficacy of automated recording units (ARUs) for monitoring American woodcock (Scolopax minor) against human observers based on peent calls and twitter displays, evaluate the use of automated detection for American woodcock, and evaluate whether abundance estimates can be derived from the acoustic data. Human observers detected more woodcock and counted more twitter displays than ARUs with manual human review but counted similar numbers of peent calls, while the automated detection program monitoR successfully classified peent calls but was unable to consistently classify twitter displays.

Using data from 31 professional trappers across 4 states in the southeastern U.S., we evaluated the performance of 3 common wild pig trap types (corral, drop, passive net), as well as the effect of forage season (barren, green-up, masting) on trapping success. Across >850 capture events by 31 trappers, all 3 trap types evaluated were effective at capturing entire social groups of wild pigs. Our findings demonstrate that when operated by wildlife professionals, multiple designs of common wild pig traps can be effective at removing targeted groups of wild pigs.