Individual variation in the echolocation calls of big brown bats (Eptesicus fuscus) and their potential for acoustic identification and censusing

We compared the discriminability of the echolocation calls of big brown bats (Eptesicus fuscus) in three situations: (a) while held in the hand, (b) while perched on a platform, and (c) while flying in an anechoic chamber. Using variables describing each sonar call, we employed discriminant function analysis (DFA) to assign calls to bat across recording situations (which yielded 72% success), and, within a given recording situation (87% success).; Advances in computer equipment made it possible to replace our laboratory recording equipment with a laptop-based system. Using widely available software tools, it is also possible to take recordings analyze them automatically on a computer. This allows a researcher to record and analyze large numbers of calls without investing unreasonable amounts of time.; We recorded sonar calls of bats under laboratory and field conditions and tested the ability of neural networks to estimate the number of bats that produced a given set of recordings. Laboratory tests used calls from both big brown bats (E. fuscus) and little brown bats ( Myotis lucifugus) while field tests used calls from E. fuscus only. The number of animals tested in the lab ranged from three to 24 and in all cases the estimate was within 11 of the correct number. For field recordings, we tested between three and 26 animals and all estimates were within four of the correct number of bats. These results suggest that neural networks might be useful for acoustic censusing of bats in the field.; We tested a series of laboratory recordings of the sonar calls of E. fuscus with DFA and backpropagation neural networks to discriminate sonar calls using recordings made after various intervals. DFA could distinguish animals from recordings made up to five years apart; however, the network was unable to discriminate animals over time spans as short as five months. Using a distance measurement calculated during DFA, we found that bats recorded within five months could be discriminated reliably from novel animals.