02826nas a2200265 4500008004100000022001300041245010000054210006900154260001600223520198800239653002502227653002502252653002502277653000802302653002102310653003002331653002102361653001702382653001702399653003402416110003002450700001802480700001802498856004402516 2018 eng d a0110646500aUsing paired acoustic sampling to enhance population monitoring of New Zealand’s forest birds0 aUsing paired acoustic sampling to enhance population monitoring cNov-11-20193 a
Large-scale bird monitoring can provide valuable insights about drivers of population change across different spatial and temporal scales. Yet, challenging terrain and survey costs hinder the collection of data needed to estimate absolute abundance or population densities for New Zealand’s forest birds. Acoustic sampling is being used more frequently to increase efficiency in avian monitoring and paired sampling facilitates robust density estimation from acoustic data. In paired sampling, point counts are conducted simultaneously by human observers and autonomous recording units (ARUs) to allow estimation of statistical offsets that correct biases in ARU data relative to human observers. These offsets can then be used to calibrate count data collected only by ARUs in a larger sampling scheme. However, the effectiveness of paired sampling has not yet been evaluated in New Zealand. We assessed bias in bird counts from ARUs relative to traditional point counts and evaluated whether paired sampling reduced ARU bias, when present, at 280 count stations in six indigenous forest patches on the North Island from January to April 2017. For 13 forest bird species, we estimated δ, a statistical offset that represents the ratio of the effective detection radius (EDR) of the ARU data to human count data and compared bias in density estimates from ARUs relative to human observers between models with and without δ offsets. We found that δ estimates of EDR ratios were near 1.0 and 95% confidence intervals around δ overlapped 1.0 for nine of 13 species. Furthermore, densities produced by ARU counts were unbiased relative to human point counts for nine of 13 species. When models included δ offsets, ARU density estimate bias was removed for all species. Thus, paired acoustic sampling offers a promising strategy for increasing the efficiency, and spatial and temporal coverage of bird population monitoring across New Zealand.
10a5-minute bird counts10aabundance estimation10aacoustic survey bias10aARU10aaudio monitoring10aautonomous recording unit10aavian monitoring10abioacoustics10apoint counts10apopulation density estimation1 aColorado State University1 aBombaci, Sara1 aPejchar, Liba uhttps://newzealandecology.org/nzje/335602310nas a2200217 4500008004100000022001400041245009700055210006900152260001600221490000700237520161500244653002101859653002801880653002501908653003201933653001701965653002401982100002102006700002002027856004502047 2017 eng d a1712-656800aAutonomous recording units in avian ecological research: current use and future applications0 aAutonomous recording units in avian ecological research current cJan-01-20170 v123 aAcoustic surveys are a widely used sampling tool in ecological research and monitoring. They are used to monitor populations and ecosystems and to study various aspects of animal behavior. Autonomous recording units (ARUs) can record sound in most environments and are increasingly used by researchers to conduct acoustic surveys for birds. In this review, we summarize the use of ARUs in avian ecological research and synthesize current knowledge of the benefits and drawbacks of this technology. ARUs enable researchers to do more repeat visits with less time spent in the field, with the added benefits of a permanent record of the data collected and reduced observer bias. They are useful in remote locations and for targeting rare species. ARUs are mostly comparable to human observers in terms of species richness, but in some cases, they detect fewer species and at shorter distances. Drawbacks of ARUs include the cost of equipment, storage of recordings, loss of data if units fail, and potential sampling trade-offs in spatial vs. temporal coverage. ARUs generate large data sets of audio recordings, but advances in automated species recognition and acoustic processing techniques are contributing to make the processing time manageable. Future applications of ARUs include biodiversity monitoring and studying habitat use, animal movement, and various behavioral ecology questions based on vocalization activity. ARUs have the potential to make significant advances in avian ecological research and to be used in more innovative ways than simply as a substitute for a human observer in the field. 10aacoustic surveys10aBiodiversity monitoring10anoninvasive sampling10apassive acoustic monitoring10apoint counts10avocal communication1 aShonfield, Julia1 aBayne, Erin, M. uhttp://www.ace-eco.org/vol12/iss1/art14/