Monitoring migration timing in remote habitats: assessing the value of extended duration audio recording

Because birds are frequently detected by sound, autonomous audio recorders (called automated recording units or ARUs) are now an established tool in addition to in-person observations for monitoring the status and trends of bird populations. ARUs have been evaluated and applied during breeding seasons, and to monitor the nocturnal flight calls of migrating birds. However, birds behave differently during migration than during the breeding season. Here we present a method for using ARUs to monitor land birds during the migration period in remote habitats. We conducted in-person point counts next to continuously recording ARUs, and compared estimates of the number of species detected and focal species relative abundance from point counts and ARUs. We used a desk-based audio bird survey method for processing audio recordings, which does not require automated species identification algorithms. We tested two methods of using extended duration ARU recording: surveying consecutive minutes and surveying randomly selected minutes. Desk-based surveys using randomly selected minutes from extended duration ARU recordings performed similarly to point counts, and better than desk-based surveys using consecutive minutes from ARU recordings. Surveying randomly selected minutes from ARUs provided estimates of relative abundance that were strongly correlated with estimates from point counts and successfully showed the increase in abundance associated with migration timing. Randomly selected minutes also provided estimates of the number of species present that were comparable to estimates from point counts. Our results suggest that ARUs are an effective way to track migration timing and intensity in remote or seasonally inaccessible habitat during spring migration. Additional testing is needed to determine the efficacy of our methods during fall migration, and at more southerly latitudes. We recommend that desk-based surveys use randomly sampled minutes from extended duration ARU recordings, rather than using consecutive minutes from recordings. Our methods can be immediately applied by researchers with the skills to conduct point counts, with no additional expertise necessary in automated species identification algorithms

What have biological records ever done for us? A systematic scoping review

Biological records provide biodiversity information over large spatial and temporal scales.  Our systematic scoping review of biological records from the well-recorded region of the United Kingdom (UK) and Ireland revealed that over half of all studies using biological records were studying species distributions (134 of 253 studies) and/or temporal trends (139 of 253 studies).  A minority of studies (61 of 253) focused on methodological questions, while most studies used biological records with existing methods as tools for answering biological and ecological questions.  However, only 31 of 253 studies tested models using independent data.  Most studies (154 of 253) integrated multiple biological records datasets, showing that biological records hold a largely untapped potential for independently testing conclusions by withholding some of those datasets for use as independent test data.  Our results provide guidance for data providers and researchers interested in more effectively collecting and using biological records

What have biological records ever done for us? A systematic scoping review

Biological records provide biodiversity information over large spatial and temporal scales.  Our systematic scoping review of biological records from the well-recorded region of the United Kingdom (UK) and Ireland revealed that over half of all studies using biological records were studying species distributions (134 of 253 studies) and/or temporal trends (139 of 253 studies).  A minority of studies (61 of 253) focused on methodological questions, while most studies used biological records with existing methods as tools for answering biological and ecological questions.  However, only 31 of 253 studies tested models using independent data.  Most studies (154 of 253) integrated multiple biological records datasets, showing that biological records hold a largely untapped potential for independently testing conclusions by withholding some of those datasets for use as independent test data.  Our results provide guidance for data providers and researchers interested in more effectively collecting and using biological records