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Reliable automation of bat call identification for eastern New South Wales, Australia, using classification trees and AnaScheme software

100%

Adams M. D., Law B. S., Gibson M. S.

Acta Chiropterologica

2010

tom 12

nr 1

Accurate and efficient identification of bat (Microchiroptera) echolocation calls has been hampered by poor knowledge of the intraspecific variability in calls (including regional variation), a lack of call parameters for use in separating species and the amount of time required to manually identify individual calls or call sequences. We constructed and tested automated bat call identification keys for three regions in New South Wales, Australia, using over 4,000 reference calls in ≈300 call sequences per region. We used the program AnaScheme to extract time, frequency and shape parameters from calls recorded with the Anabat system. Classification trees were built to separate species using these parameters and provided the decision rules for construction of the keys. An ‘Unknown’ category was included in the keys for sequences that could not be confidently identified to species. The reliability of the keys was tested automatically with AnaScheme, using independent sets of reference call sequences, and keys were refined before further testing on additional test sequences. Regional keys contained 18–19 species or included species groups. We report rates of sequence misidentification (accuracy) and correct identification (detection) relative to all sequences (including ‘unknowns’) used to test each version of a key. Refined versions of the keys were accurate, with total misidentification rates of 0.5–5.3% for the three regions. Additionally, total correct identifications for regions were 56–75% (> 50% for most species), an overall high rate of detection. When ‘unknowns’ were ignored, as is common in many published studies, correct identification for regions increased to 91–99%, rates which compare favourably to the most successful classifiers tested to date. The future use of AnaScheme for automated bat call identification is promising, especially for the large-scale temporal and spatial acoustic sampling to which Anabat is particularly suited.

Designing effective habitat studies: quantifying multiple sources of variability in bat activity

88%

Fischer J., Stott J., Law B. S., Adams M. D., Forrester R. I.

Acta Chiropterologica

2009

tom 11

nr 1

Common aims of habitat studies are to differentiate between (i) suitable and unsuitable sites for a given species, and (ii) sites used by different communities of species. To quantify differences between sites, field data of site use must be precise enough that true underlying between-site variability is not masked by within-site measurement error. We designed a pilot study to guide the development of a survey protocol for a habitat study on bats in an agricultural landscape in southeastern Australia. Three woodland sites and two scattered tree sites of 2 ha each were surveyed for nine consecutive nights. At three locations within each site (spaced > 50 m apart) one or two Anabat detectors were mounted 1 m above ground or in a tree (2 m above ground). We used mixed regression models to quantify multiple sources of variability in bat calling activity, and graphical data analysis to visualise how increases in survey effort were likely to affect inference. For the five most active species, we found that typically over 40% of variability in nightly detections occurred at the between-site level; approximately 10% occurred between locations within sites; approximately 20% was explained by night-to-night differences; and approximately 30% of variability was not attributable to systematic variation within experimental units. Differences in community composition between sites were clearly evident when two or more detectors per site were used for four or more nights. We conclude with six general considerations for the design of effective habitat studies. These are to (i) consider key contrasts of interest; (ii) use data from mild, calm, dry nights only; (iii) calibrate detectors; (iv) use multiple detectors where possible, or move a single detector within a site; (v) survey for multiple nights; and (vi) where vertical differentiation in habitat use is likely, mount detectors at different heights. These considerations need to be balanced within the context of financial and logistical constraints.

Ograniczanie wyników

2 Acta Chiropterologica

2 Adams M. D.

2 Law B. S.

1 Fischer J.

1 Forrester R. I.

1 Gibson M. S.

1 Stott J.

1 2010

1 2009

Wyniki wyszukiwania

Reliable automation of bat call identification for eastern New South Wales, Australia, using classification trees and AnaScheme software

Designing effective habitat studies: quantifying multiple sources of variability in bat activity