Integrating wetland bird point count data from humans and acoustic recorders

Wetland loss is cause for concern for populations of many wetland bird species throughout North America. The North American Breeding Bird Survey, the primary resource for broad-scale avian population data, does not provide sufficient data for many marsh bird species. Targeted marsh bird monitoring programs have been implemented across the continent in an attempt to fill this gap. Despite these efforts, a number of wetland species are so elusive that they remain an analytical challenge because of small sample sizes and low detectability. Thus, there is need for tools and approaches that will increase sampling efficiency and boost geographic representation. Autonomous recording units (ARUs) have the potential to address some of these challenges, but require the ability to combine in-person survey data with ARU data for collective analysis. Our primary objective was to estimate statistical offsets, or correction factors, to account for systematic differences between in-person and ARU counts of wetland-associated bird species. We found that ARU recordings were generally equivalent to in-person point counts, with bias in a small number of species (2 of 19 for Song MeterTM SM2 and 1 of 16 for Song MeterTM SM4 Acoustic Recorders; Wildlife Acoustics Inc. ©, Maynard, MA). However, bias was removed in all of the species through use of our correction factors. Therefore, our correction factors were effective for integrating in-person and ARU point count data even for species where differences exist. We also found that commercially available SM4 recorders have larger effective detection radii than SM2 recorders. Researchers should consider the microphone sensitivity and signal-to-noise ratios of any recording unit before purchasing, and more sensitive models with lower noise should be used where possible. Our results, and particularly our correction factors, are useful for biologists combining in-person and ARU point count data to achieve larger sample sizes, higher statistical power, and ultimately better information for more effective wetland conservation

Atmospheric pressure predicts probability of departure for migratory songbirds

Abstract Background Weather can have both delayed and immediate impacts on animal populations, and species have evolved behavioral adaptions to respond to weather conditions. Weather has long been hypothesized to affect the timing and intensity of avian migration, and radar studies have demonstrated strong correlations between weather and broad-scale migration patterns. How weather affects individual decisions about the initiation of migratory flights, particularly at the beginning of migration, remains uncertain. Methods Here, we combine automated radio telemetry data from four species of songbirds collected at five breeding and wintering sites in North America with hourly weather data from a global weather model. We use these data to determine how wind profit, atmospheric pressure, precipitation, and cloud cover affect probability of departure from breeding and wintering sites. Results We found that the probability of departure was related to changes in atmospheric pressure, almost completely regardless of species, season, or location. Individuals were more likely to depart on nights when atmospheric pressure had been rising over the past 24 h, which is predictive of fair weather over the next several days. By contrast, wind profit, precipitation, and cloud cover were each only informative predictors of departure probability in a single species. Conclusions Our results suggest that individual birds actively use weather information to inform decision-making regarding the initiation of departure from the breeding and wintering grounds. We propose that birds likely choose which date to depart on migration in a hierarchical fashion with weather not influencing decision-making until after the departure window has already been narrowed down by other ultimate and proximate factors

Songbirds initiate migratory flights synchronously relative to civil dusk

Abstract Background Each spring and fall billions of songbirds depart on nocturnal migrations across the globe. Theory suggests that songbirds should depart on migration shortly after sunset to maximize their potential for nightly flight duration or to time departure with the emergence of celestial cues needed for orientation and navigation. Although captive studies have found that songbirds depart during a narrow window of time after sunset, observational studies have found that wild birds depart later and more asynchronously relative to sunset than predicted. Methods We used coded radio tags and automated radio-telemetry to estimate the time that nearly 400 individuals from nine songbird species departed their breeding or wintering grounds across North America. We also assessed whether each species was most likely beginning long-distance migratory flights at departure or instead first making non-migratory regional flights. We then explored variation in nocturnal departure time by post-departure movement type, species, age, sex, and season. Results We found that 90% of individuals from species that were likely initiating long-distance migratory flights departed within 69 min of civil dusk, regardless of species, season, age, or sex. By contrast, species that likely first made non-migratory regional movements away from the migratory destination departed later and more asynchronously throughout the night. Regardless of post-departure movement type, 98% of individuals departed after civil dusk but otherwise showed no preference in relation to twilight phase. Conclusions Although the presence of celestial orientation cues at civil dusk may set a starting point for departure each night, the fact that species likely beginning long-distance migration departed earlier and more synchronously relative to civil dusk than those first making non-migratory regional movements is consistent with the hypothesis that departing promptly after civil dusk functions to maximize the potential for nightly flight duration and distance. By studying the onset of migration, our study provides baseline information about departure decisions that may enhance our understanding of departure timing throughout migration